WorldWideScience

Sample records for based motion-sensorless vector

  1. Active-flux based motion sensorless vector control of biaxial excitation generator/motor for automobiles (BEGA)

    DEFF Research Database (Denmark)

    Coroban-Schramel, Vasile; Boldea, Ion; Andreescu, Gheorghe-Daniel;

    2009-01-01

    the active-flux concept the estimated rotor position is given by the sum of the active flux angle and torque angle. The active flux is calculated by subtracting the term Lq i s from the estimated stator flux vector. The experimental results validate the active flux-principle and show good performance......This paper proposes a novel, active-flux based, motion-sensorless vector control structure for biaxial excitation generator for automobiles (BEGA) for wide speed range operation. BEGA is a hybrid excited synchronous machine having permanent magnets on q-axis and a dc excitation on daxis. Using...

  2. 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

    -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......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...... reference currents id* = 0 and iq* constant, and the reference frequency having ramp variation. This solution allows ultra low- speed sensorless control without initial rotor-position estimation, and without machine parameters identification. A first-order lag compensator is employed to ensure a smooth...

  3. IPMSM Motion-Sensorless Direct Torque and Flux Control

    DEFF Research Database (Denmark)

    Pitict, Christian Ilie; Andreescu, Gheorghe-Daniel; Blaabjerg, Frede;

    2005-01-01

    The paper presents a rather comprehensive implementation of a wide speed motion-sensorless control of IPMSM drives via direct torque and flux control (DTFC) with space vector modulation (SVM). Signal injection with only one D-module vector filter and phase-locked loop (PLL) observer is used at low...... provides for a smooth current waveform even at 1 rpm. The paper demonstrates through ample experiments a 1750 rpm 1 1 rpm speed range full-loaded with sensorless DTFC-SVM....

  4. Novel Motion Sensorless Control of Single Phase Brushless D.C. PM Motor Drive, with experiments

    DEFF Research Database (Denmark)

    Lepure, Liviu Ioan; Boldea, Ion; Andreescu, Gheorghe Daniel;

    2010-01-01

    A motion sensorless control for single phase permanent magnet brushless d.c. (PM-BLDC) motor drives, based on flux integration and prior knowledge of the PM flux/position characteristic is proposed here and an adequate correction algorithm is adopted, in order to increase the robustness to noise...

  5. Voltage Sags Ride-Through of Motion Sensorless Controlled PMSG for Wind Turbines

    DEFF Research Database (Denmark)

    Fatu, Marius; Lascu, Cristian; Andreescu, Gheorghe-Daniel;

    2007-01-01

    This paper describes a variable-speed motion-sensorless permanent magnet synchronous generator (PMSG) control system for wind energy generation. The proposed system contains a PMSG connected to the grid by a back-to-back PWM inverter with bidirectional power flow, a line filter, and a transformer....... The control system employs PI current controllers with crosscoupling decoupling for both inverters, an active power controller, and a DC link voltage controller. The PMSG rotor speed without using emf integration, and the line voltage frequency are estimated by two PLL based observers. A Dmodule...... filter is used to robustly estimate the grid voltage positivesequence for control in the case of asymmetric voltages. The paper investigates the ride-through performance of this system during asymmetric power grid voltage sags. Design details for various parts of the control system are presented...

  6. Grid to Standalone Transition Motion-Sensorless Dual-Inverter Control of PMSG With Asymmetrical Grid Voltage Sags and Harmonics Filtering

    DEFF Research Database (Denmark)

    Fatu, M.; Blaabjerg, Frede; Boldea, I.

    2014-01-01

    -coupling decoupling and line-voltage feedforward disturbance compensation. Also, a D-module filter is used to robustly extract the line voltage positive sequence followed by a phase-locked-loop (PLL) based observer to estimate the positive-sequence angle for control, including the case of asymmetric voltages and...... automatic seamless transfer method from grid connected to stand alone and vice versa. In stand-alone mode, a voltage control scheme with selective harmonic compensation is employed. The PMSG motion-sensorless control system uses an active power controller and a PLL-based observer to estimate the rotor...... position and speed without using the electromotive force (EMF) integration and initial rotor position. The paper investigates and validates the ride-through performance of this proposed system during asymmetric power grid-voltage sags, transition from grid connected to stand alone and vice versa and...

  7. I-f Starting and Active Flux Based Sensorless Vector Control of Reluctance Synchronous Motors, with Experiments

    DEFF Research Database (Denmark)

    Agarlita, Sorin-Christian; Fatu, M.; Tutelea, L. N.;

    2010-01-01

    This paper presents a novel, hybrid, motion sensorless control of an axially laminated anisotropic (ALA) reluctance synchronous machine (RSM). By separately controlling Id and Iq currents with the reference currents Id*, Iq* being held constant, and ramping the reference frequency, the motor starts...... flux based sensorless vector control and vice versa when the frequency reaches a certain level. The control also integrates a state observer based on the active “flux concept” used to deliver RSM rotor position and speed information. Experimental results validate the proposed control strategies....... with a robust start-up method called I-f control. This kind of control strategy also allows the motor to experience low speeds without initial position estimation or machine parameters identification. The control uses first order lag compensators to ensure smooth transitions from I-f control to active...

  8. "Active flux" orientation vector sensorless control of IPMSM

    DEFF Research Database (Denmark)

    Blaabjerg, Frede; Boldea, I.; Paicu, M.C.;

    2008-01-01

    This paper presents a novel strategy for the vector control of IPMSM, without signal injection. The overall performance of the motion-sensorless control depends strongly on the accuracy of the rotor position and speed estimation. The proposed state observer is based on the concept of the...... ldquoactive fluxrdquo (or ldquotorque producing fluxrdquo), which ldquoturns all the salient-pole rotor ac machines into nonsalient-pole onesrdquo. As well as giving a detailed explanation of the concept, the paper demonstrates, through a wide range of experimental results, the effectiveness of the active...

  9. 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...

  10. Motion Sensorless Control of BLDC PM Motor with Offline FEM Info Assisted State Observer

    DEFF Research Database (Denmark)

    Stirban, Alin; Boldea, Ion; Andreescu, Gheorghe-Daniel;

    2010-01-01

    This paper describes a new offline FEM assisted position and speed observer, for brushless dc (BLDC) PM motor drive sensorless control, based on the line-to-line PM flux linkage estimation. The zero-crossing of the line-to-line PM flux linkage occurs right in the middle of two commutation points...... identification. Digital simulations and experimental results are shown, demonstrating the reliability of the FEM assisted position and speed observer for BLDC PM motor sensorless control operation....

  11. High frequency injection assisted “active flux” based sensorless vector control of reluctance synchronous motors, with experiments from zero speed

    DEFF Research Database (Denmark)

    Agarlita, Sorin-Cristian; Boldea, Ion; Blaabjerg, Frede

    2012-01-01

    This paper presents a hybrid, motion sensorless control of an Axially Laminated Anisotropic (ALA) Reluctance Synchronous Machine (RSM). The zero and low speed sensorless method is a saliency based High Frequency Signal Injection technique (HFSI) that uses the motor itself as a resolver. The second...... method is based on a state observer incorporating the “active flux” concept used to deliver RSM rotor position and speed information for medium and high speed range. Even if both methods perform successfully in separate speed regions, estimation of the two algorithms is combined as a sensor fusion to...... improve performance at zero and very low speeds. Experimental results validate the proposed control strategies....

  12. High frequency injection assisted “active flux” based sensorless vector control of reluctance synchronous motors, with experiments from zero speed

    DEFF Research Database (Denmark)

    Agarliţă, Sorin-Cristian; Boldea, I.; Blaabjerg, Frede

    2011-01-01

    This paper presents a hybrid, motion sensorless control of an Axially Laminated Anisotropic (ALA) Reluctance Synchronous Machine (RSM). The zero and low speed sensorless method is a saliency based High Frequency Signal Injection technique (HFSI) that uses the motor itself as a resolver. The second...... method is based on a state observer incorporating the “active flux” concept used to deliver RSM rotor position and speed information for medium and high speed range. Even if both methods perform successfully in separate speed regions, estimation of the two algorithms is combined as a sensor fusion to...... improve performance at zero and very low speeds. Experimental results validate the proposed control strategies....

  13. Hybrid I-f starting and observer-based Ssnsorless control of single-phase BLDC-PM motor drives

    DEFF Research Database (Denmark)

    Iepure, Liviu Ioan; Boldea, Ion; Blaabjerg, Frede

    2012-01-01

    A motion sensorless control for single-phase permanent magnet brushless dc motor based on an I-f starting sequence and a real-time permanent magnet flux estimation is proposed here. The special calculation for extracting the position and speed used here implies the generating of an orthogonal flux......-speed blower-motor (40 W, 10 krpm, 12 Vdc)....

  14. Equiangular Vectors Approach to Mutually Unbiased Bases

    Directory of Open Access Journals (Sweden)

    Maurice R. Kibler

    2013-05-01

    Full Text Available Two orthonormal bases in the d-dimensional Hilbert space are said to be unbiased if the square modulus of the inner product of any vector of one basis with any vector of the other equals 1 d. The presence of a modulus in the problem of finding a set of mutually unbiased bases constitutes a source of complications from the numerical point of view. Therefore, we may ask the question: Is it possible to get rid of the modulus? After a short review of various constructions of mutually unbiased bases in Cd, we show how to transform the problem of finding d + 1 mutually unbiased bases in the d-dimensional space Cd (with a modulus for the inner product into the one of finding d(d+1 vectors in the d2-dimensional space Cd2 (without a modulus for the inner product. The transformation from Cd to Cd2 corresponds to the passage from equiangular lines to equiangular vectors. The transformation formulas are discussed in the case where d is a prime number.

  15. Nonlinear Growth of Singular Vector Based Perturbations

    Science.gov (United States)

    Reynolds, C. A.

    2002-12-01

    The nonlinearity of singular vector-based perturbation growth is examined within the context of a global atmospheric forecast model. The characteristics of these nonlinearities and their impact on the utility of SV-based diagnostics are assessed both qualitatively and quantitatively. Nonlinearities are quantified by examining the symmetry of evolving positive and negative "twin" perturbations. Perturbations initially scaled to be consistent with estimates of analysis uncertainty become significantly nonlinear by 12 hours. However, the relative magnitude of the nonlinearities is a strong function of scale and metric. Small scales become nonlinear very quickly while synoptic scales can remain significantly linear out to three day. Small shifts between positive and negative perturbations can result in significant nonlinearities even when the basic anomaly patterns are quite similar. Thus, singular vectors may be qualitatively useful even when nonlinearities are large. Post-time pseudo-inverse experiments show that despite significant nonlinear perturbation growth, the nonlinear forecast corrections are similar to the expected linear corrections, even at 72 hours. When the nonlinear correction does differ significantly from the expected linear correction, the nonlinear correction is usually better, indicating that in some cases the pseudo-inverse correction effectively suppresses error growth outside the subspace defined by the leading (dry) singular vectors. Because a significant portion of the nonlinear growth occurs outside of the dry singular vector subspace, an a priori nonlinearity index based on the full perturbations is not a good predictor of when pseudo-inverse based corrections will be ineffective. However, one can construct a reasonable predictor of pseudo-inverse ineffectiveness by focusing on nonlinearities in the synoptic scales or in the singular vector subspace only.

  16. Cost-Based Vectorization of Instance-Based Integration Processes

    Science.gov (United States)

    Boehm, Matthias; Habich, Dirk; Preissler, Steffen; Lehner, Wolfgang; Wloka, Uwe

    The inefficiency of integration processes—as an abstraction of workflow-based integration tasks—is often reasoned by low resource utilization and significant waiting times for external systems. With the aim to overcome these problems, we proposed the concept of process vectorization. There, instance-based integration processes are transparently executed with the pipes-and-filters execution model. Here, the term vectorization is used in the sense of processing a sequence (vector) of messages by one standing process. Although it has been shown that process vectorization achieves a significant throughput improvement, this concept has two major drawbacks. First, the theoretical performance of a vectorized integration process mainly depends on the performance of the most cost-intensive operator. Second, the practical performance strongly depends on the number of available threads. In this paper, we present an advanced optimization approach that addresses the mentioned problems. Therefore, we generalize the vectorization problem and explain how to vectorize process plans in a cost-based manner. Due to the exponential complexity, we provide a heuristic computation approach and formally analyze its optimality. In conclusion of our evaluation, the message throughput can be significantly increased compared to both the instance-based execution as well as the rule-based process vectorization.

  17. Vector Control Based on SVPWM for ACIM

    Directory of Open Access Journals (Sweden)

    Zhu Jun

    2013-05-01

    Full Text Available To solve the large torque ripple and current harmonics, low DC bus voltage problems, a new control strategy is proposed for AC induction motor by using space vector pulse width modulation, so that the static and dynamic performance are improved. The system simulation experiment mode was established based on SVPWM to verify the effectiveness of the system control mode. It is showed that it can reduce the current ripple and torque ripple, improve the utilization of DC bus voltage. It means that the control strategy based SVPWM can improve dynamic and static performance effectively for the ACIM servo system.

  18. Robust Video Stabilization Based on Motion Vectors

    Institute of Scientific and Technical Information of China (English)

    宋利; 周源华; 周军

    2005-01-01

    This paper proposes a new robust video stabilization algorithm to remove unwanted vibrations in video sequences. A complete theoretical analysis is first established for video stabilization, providing a basis for new stabilization algorithm. Secondly, a new robust global motion estimation (GME) algorithm is proposed. Different from classic methods, the GME algorithm is based on spatlal-temporal filtered motion vectors computed by block-matching methods. In addition, effective schemes are employed in correction phase to prevent boundary artifacts and error accumulation. Experiments show that the proposed algorithm has satisfactory stabilization effects while maintaining good tradeoff between speed and precision.

  19. DBSC-Based Grayscale Line Image Vectorization

    Institute of Scientific and Technical Information of China (English)

    Konstantin Melikhov; Feng Tian; Jie Qiu; Quan Chen; Hock Soon Seah

    2006-01-01

    Vector graphics plays an important role in computer animation and imaging technologies. However present techniques and tools cannot fully replace traditional pencil and paper. Additionally, vector representation of an image is not always available. There is not yet a good solution for vectorizing a picture drawn on a paper. This work attempts to solve the problem of vectorizing grayscale line drawings. The solution proposed uses Disk B-Spline curves to represent strokes of an image in vector form. The algorithm builds a vector representation from a grayscale raster image, which can be a scanned picture for instance. The proposed method uses a Gaussian sliding window to calculate skeleton and perceptive width of a stroke. As a result of vectorization, the given image is represented by a set of Disk B-Spline curves.

  20. 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

  1. Bethe vectors in GL(3)-based quantum integrable models

    CERN Document Server

    Pakuliak, S; Slavnov, N A

    2015-01-01

    We consider a composite generalized quantum integrable model solvable by the nested algebraic Bethe ansatz. Using explicit formulas of the action of the monodromy matrix elements onto Bethe vectors in the GL(3)-based quantum integrable models we prove a formula for the Bethe vectors of composite model. We show that this representation is a particular case of general coproduct property of the weight functions (Bethe vectors) found in the theory of the deformed Knizhnik--Zamolodchokov equation.

  2. Recent progress in polymer-based gene delivery vectors

    Institute of Scientific and Technical Information of China (English)

    HUANG Shiwen; ZHUO Renxi

    2003-01-01

    The gene delivery system is one of the three components of a gene medicine, which is the bottle neck of current gene therapy. Nonviral vectors offer advantages over the viral system of safety, ease of manufacturing, etc. As important nonviral vectors, polymer gene delivery systems have gained increasing attention and have begun to show increasing promising. In this review, the fundamental and recent progress of polymer-based gene delivery vectors is reviewed.

  3. One-Dimensional Vector Based Pattern Matching

    Directory of Open Access Journals (Sweden)

    Y.M.Fouda

    2014-08-01

    Full Text Available Template matching is a basic method in image analysis to extract useful information from images. In this paper, we suggest a new method for pattern matching. Our method transform the template image from two dimensional image into one dimensional vector. Also all sub - windows (same size of template in the reference image will transform into one dimensional vectors. The three similarity measures SAD, SSD, and Euclidean are used to c ompute the likeness between template and all sub - windows in the reference image to find the best match. The experimental results show the superior performance of the proposed metho d over the conventional methods on various template of different sizes

  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. A Fingerprint Minutiae Matching Method Based on Line Segment Vector

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    Minutiae-based fingerprint matching is the most commonly used in an automatic fingerprint identification system. In this paper, we propose a minutia matching method based on line segment vector. This method uses all the detected minutiae (the ridge ending and the ridge bifurcation) in a fingerprint image to create a set of new vectors (line segment vector). Using these vectors, we can determine a truer reference point more efficiently. In addition, this new minutiae vector can also increase the accuracy of the minutiae matching. By experiment on the public domain collections of fingerprint images fvc2004 DB3 set A and DB4 set A, the result shows that our algorithm can obtain an improved verification performance.

  6. Image Segmentation Based on Support Vector Machine

    Institute of Scientific and Technical Information of China (English)

    XU Hai-xiang; ZHU Guang-xi; TIAN Jin-wen; ZHANG Xiang; PENG Fu-yuan

    2005-01-01

    Image segmentation is a necessary step in image analysis. Support vector machine (SVM) approach is proposed to segment images and its segmentation performance is evaluated.Experimental results show that: the effects of kernel function and model parameters on the segmentation performance are significant; SVM approach is less sensitive to noise in image segmentation; The segmentation performance of SVM approach is better than that of back-propagation multi-layer perceptron (BP-MLP) approach and fuzzy c-means (FCM) approach.

  7. Image indexing based on vector quantization

    Science.gov (United States)

    Grana Romay, Manuel; Rebollo, Israel

    2000-10-01

    We propose the computation of the color palette of each image in isolation, using Vector Quantization methods. The image features are, then, the color palette and the histogram of the color quantization of the image with this color palette. We propose as a measure of similitude the weighted sum of the differences between the color palettes and the corresponding histograms. This approach allows the increase of the database without the recomputation of the image features and without substantial loss of discriminative power.

  8. 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...

  9. Improved NYVAC-based vaccine vectors.

    Directory of Open Access Journals (Sweden)

    Karen V Kibler

    Full Text Available While as yet there is no vaccine against HIV/AIDS, the results of the phase III Thai trial (RV144 have been encouraging and suggest that further improvements of the prime/boost vaccine combination of a poxvirus and protein are needed. With this aim, in this investigation we have generated derivatives of the candidate vaccinia virus vaccine vector NYVAC with potentially improved functions. This has been achieved by the re-incorporation into the virus genome of two host range genes, K1L and C7L, in conjunction with the removal of the immunomodulatory viral molecule B19, an antagonist of type I interferon action. These novel virus vectors, referred to as NYVAC-C-KC and NYVAC-C-KC-ΔB19R, have acquired relevant biological characteristics, giving higher levels of antigen expression in infected cells, replication-competency in human keratinocytes and dermal fibroblasts, activation of selective host cell signal transduction pathways, and limited virus spread in tissues. Importantly, these replication-competent viruses have been demonstrated to maintain a highly attenuated phenotype.

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

    International Nuclear Information System (INIS)

    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

  11. Risk based surveillance for vector borne diseases

    DEFF Research Database (Denmark)

    Bødker, Rene

    and new exotic diseases like Usutu and West Nile Virus may lead to outbreaks in the region. In the worst case the combined effect of climate change and globalization may potentially lead to European outbreaks of important zoonotic mosquito borne infections like Rift Valley Fever in cattle and Japanese...... Encephalitis in swine. Being able to model the impact of climate and environmental change on the transmission intensity of vector borne diseases is potentially a powerful tool to both monitor and prevent outbreaks in a cost effective way. The recent unexpected outbreaks of bluetongue and Schmallenberg virus...... is the direct result of climate change. The potential for virus transmission by biting midges was here modeled monthly for the Baltic See Region and the rest of Europe. The results showed that Baltic See Region has a lower transmission potential than most other areas in Europe. And the model identified...

  12. Fuzzy rule-based support vector regression system

    Institute of Scientific and Technical Information of China (English)

    Ling WANG; Zhichun MU; Hui GUO

    2005-01-01

    In this paper,we design a fuzzy rule-based support vector regression system.The proposed system utilizes the advantages of fuzzy model and support vector regression to extract support vectors to generate fuzzy if-then rules from the training data set.Based on the first-order linear Tagaki-Sugeno (TS) model,the structure of rules is identified by the support vector regression and then the consequent parameters of rules are tuned by the global least squares method.Our model is applied to the real world regression task.The simulation results gives promising performances in terms of a set of fuzzy rules,which can be easily interpreted by humans.

  13. Implicit Boundary Control of Vector Field Based Shape Deformations

    OpenAIRE

    von Funck, Wolfram; Theisel, Holger; Seidel, Hans-Peter

    2007-01-01

    We present a shape deformation approach which preserves volume, prevents self-intersections and allows for exact control of the deformation impact. The volume preservation and prevention of selfintersections are achieved by utilizing the method of Vector Field Based Shape Deformations. This method produces physically plausible deformations efficiently by integrating formally constructed divergence-free vector fields, where the region of influence is described by implicitly ...

  14. Support Vector Machine-Based Nonlinear System Modeling and Control

    Institute of Scientific and Technical Information of China (English)

    张浩然; 韩正之; 冯瑞; 于志强

    2003-01-01

    This paper provides an introduction to a support vector machine, a new kernel-based technique introduced in statistical learning theory and structural risk minimization, then presents a modeling-control framework based on SVM.At last a numerical experiment is taken to demonstrate the proposed approach's correctness and effectiveness.

  15. The integration profile of EIAV-based vectors.

    Science.gov (United States)

    Hacker, Caroline V; Vink, Conrad A; Wardell, Theresa W; Lee, Sheena; Treasure, Peter; Kingsman, Susan M; Mitrophanous, Kyriacos A; Miskin, James E

    2006-10-01

    Lentiviral vectors based on equine infectious anemia virus (EIAV) stably integrate into dividing and nondividing cells such as neurons, conferring long-term expression of their transgene. The integration profile of an EIAV vector was analyzed in dividing HEK293T cells, alongside an HIV-1 vector as a control, and compared to a random dataset generated in silico. A multivariate regression model was generated and the influence of the following parameters on integration site selection determined: (a) within/not within a gene, (b) GC content within 20 kb, (c) within 10 kb of a CpG island, (d) gene density within a 2-Mb window, and (e) chromosome number. The majority of the EIAV integration sites (68%; n = 458) and HIV-1 integration sites (72%; n = 162) were within a gene, and both vectors favored AT-rich regions. Sites within genes were examined using a second model to determine the influence of the gene-specific parameters, gene region, and transcriptional activity. Both EIAV and HIV-1 vectors preferentially integrated within active genes. Unlike the gammaretrovirus MLV, EIAV and HIV-1 vectors do not integrate preferentially into the promoter region or the 5' end of the transcription unit. PMID:16950499

  16. Product Quality Modelling Based on Incremental Support Vector Machine

    International Nuclear Information System (INIS)

    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.

  17. Dynamic Vector Space Secret Sharing Based on Certificates

    Institute of Scientific and Technical Information of China (English)

    XU Chunxiang; LI Jiajia; LIU Dongsu

    2006-01-01

    A vector space secret sharing scheme based on certificates is proposed in this paper. The difficulties of solving discrete logarithm assure confidential information's security, and the use of each participant's certificate makes the dealer have no need to transfer secret information to the participants. The proposed scheme is dynamic. It can effectively check cheaters and does not have secure channel requirements.

  18. 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.

  19. Copula-based integration of vector-valued functions

    Czech Academy of Sciences Publication Activity Database

    Klement, E.; Mesiar, Radko

    Vol. Part 6. Heidelberg: Springer, 2012 - (Greco, S.; Bouchon-Meunier, B.), s. 559-564. (Communications in Computer and Information Science. 300). ISBN 978-3-642-31724-8. [IPMU 2012 /14./. Catania (IT), 09.07.2012-13.07.2012] R&D Projects: GA ČR GAP402/11/0378 Institutional support: RVO:67985556 Keywords : capacity * copula * universal integral * vector-valued function Subject RIV: BA - General Mathematics http://library.utia.cas.cz/separaty/2012/E/mesiar-copula-based integration of vector-valued functions.pdf

  20. Estimation of sand liquefaction based on support vector machines

    Institute of Scientific and Technical Information of China (English)

    苏永华; 马宁; 胡检; 杨小礼

    2008-01-01

    The origin and influence factors of sand liquefaction were analyzed, and the relation between liquefaction and its influence factors was founded. A model based on support vector machines (SVM) was established whose input parameters were selected as following influence factors of sand liquefaction: magnitude (M), the value of SPT, effective pressure of superstratum, the content of clay and the average of grain diameter. Sand was divided into two classes: liquefaction and non-liquefaction, and the class label was treated as output parameter of the model. Then the model was used to estimate sand samples, 20 support vectors and 17 borderline support vectors were gotten, then the parameters were optimized, 14 support vectors and 6 borderline support vectors were gotten, and the prediction precision reaches 100%. In order to verify the generalization of the SVM method, two other practical samples’ data from two cities, Tangshan of Hebei province and Sanshui of Guangdong province, were dealt with by another more intricate model for polytomies, which also considered some influence factors of sand liquefaction as the input parameters and divided sand into four liquefaction grades: serious liquefaction, medium liquefaction, slight liquefaction and non-liquefaction as the output parameters. The simulation results show that the latter model has a very high precision, and using SVM model to estimate sand liquefaction is completely feasible.

  1. Retrovirus-based vectors for transient and permanent cell modification.

    Science.gov (United States)

    Schott, Juliane W; Hoffmann, Dirk; Schambach, Axel

    2015-10-01

    Retroviral vectors are commonly employed for long-term transgene expression via integrating vector technology. However, three alternative retrovirus-based platforms are currently available that allow transient cell modification. Gene expression can be mediated from either episomal DNA or RNA templates, or selected proteins can be directly transferred through retroviral nanoparticles. The different technologies are functionally graded with respect to safety, expression magnitude and expression duration. Improvement of the initial technologies, including modification of vector designs, targeted increase in expression strength and duration as well as improved safety characteristics, has allowed maturation of retroviral systems into efficient and promising tools that meet the technological demands of a wide variety of potential application areas. PMID:26433198

  2. 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.

  3. 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. PMID:22781241

  4. SAMEX vector magnetograph: a design study for a space-based solar vector magnetograph

    International Nuclear Information System (INIS)

    This report presents the results of a pre-phase A study performed by the Marshall Space Flight Center (MSFC) for the Air Force Geophysics Laboratory (AFGL) to develop a design concept for a space-based solar vector magnetograph and hydrogen-alpha telescope. These are two of the core instruments for a proposed Air Force mission, the Solar Activities Measurement Experiments (SAMEX). This mission is designed to study the processes which give rise to activity in the solar atmosphere and to develop techniques for predicting solar activity and its effects on the terrestrial environment

  5. 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

    2015-11-27

    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

  6. Versatile Supramolecular Gene Vector Based on Host-Guest Interaction.

    Science.gov (United States)

    Liu, Jia; Hennink, Wim E; van Steenbergen, Mies J; Zhuo, Renxi; Jiang, Xulin

    2016-04-20

    It is a great challenge to arrange multiple functional components into one gene vector system to overcome the extra- and intracellular obstacles for gene therapy. In this study, we developed a supramolecular approach for constructing a versatile gene delivery system composed of adamantyl-terminated functional polymers and a β-cyclodextrin based polymer. Adamantyl-functionalized low molecular weight PEIs (PEI-Ad) and PEG (Ad-PEG) as well as poly(β-cyclodextrin) (PCD) were synthesized by one-step chemical reactions. The supramolecular inclusion complex formed from PCD to assemble LMW PEI-Ad4 via host-guest interactions can condense plasmid DNA to form nanopolyplexes by electrostatic interactions. The supramolecular polyplexes can be further PEGylated with Ad-PEG to form inclusion complexes, which showed increased salt and serum stability. In vitro experiments revealed that these supramolecular assembly polyplexes had good cytocompatibility and showed high transfection activity close to that of the commercial ExGen 500 at high dose of DNA. Also, the supramolecular vector system exhibited about 60% silencing efficiency as a siRNA vector. Thus, a versatile effective supramolecular gene vector based on host-guest complexes was fabricated with good cytocompatbility and transfection activity. PMID:27019340

  7. Support vector machine-based multi-model predictive control

    Institute of Scientific and Technical Information of China (English)

    Zhejing BA; Youxian SUN

    2008-01-01

    In this paper,a support vector machine-based multi-model predictive control is proposed,in which SVM classification combines well with SVM regression.At first,each working environment is modeled by SVM regression and the support vector machine network-based model predictive control(SVMN-MPC)algorithm corresponding to each environment is developed,and then a multi-class SVM model is established to recognize multiple operating conditions.As for control,the current environment is identified by the multi-class SVM model and then the corresponding SVMN.MPCcontroller is activated at each sampling instant.The proposed modeling,switching and controller design is demonstrated in simulation results.

  8. Biosensor method and system based on feature vector extraction

    Science.gov (United States)

    Greenbaum, Elias; Rodriguez, Jr., Miguel; Qi, Hairong; Wang, Xiaoling

    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.

  9. Endpoint Prediction of EAF Based on Multiple Support Vector Machines

    Institute of Scientific and Technical Information of China (English)

    YUAN Ping; MAO Zhi-zhong; WANG Fu-li

    2007-01-01

    The endpoint parameters are very important to the process of EAF steel-making, but their on-line measurement is difficult. The soft sensor technology is widely used for the prediction of endpoint parameters. Based on the analysis of the smelting process of EAF and the advantages of support vector machines, a soft sensor model for predicting the endpoint parameters was built using multiple support vector machines (MSVM). In this model, the input space was divided by subtractive clustering and a sub-model based on LS-SVM was built in each sub-space. To decrease the correlation among the sub-models and to improve the accuracy and robustness of the model, the sub-models were combined by Principal Components Regression. The accuracy of the soft sensor model is perfectly improved. The simulation result demonstrates the practicability and efficiency of the MSVM model for the endpoint prediction of EAF.

  10. IRIS RECOGNITION BASED ON KERNELS OF SUPPORT VECTOR MACHINE

    OpenAIRE

    K.Saminathan; T. Chakravarthy; M.Chithra Devi

    2015-01-01

    Ensuring security biometrically is essential in most of the authentication and identification scenario. Recognition based on iris patterns is a thrust area of research cause to provide reliable, simple and rapid identification system. Machine learning classification algorithm of support vector machine [SVM] is applied in this work for personal identification. The profuse as well as unique patterns of iris are acquired and stored in the form of matrix template which contains 4800 elements for ...

  11. Classifier based on support vector machine for JET plasma configurations

    International Nuclear Information System (INIS)

    The last flux surface can be used to identify the plasma configuration of discharges. For automated recognition of JET configurations, a learning system based on support vector machines has been developed. Each configuration is described by 12 geometrical parameters. A multiclass system has been developed by means of the one-versus-the-rest approach. Results with eight simultaneous classes (plasma configurations) show a success rate close to 100%.

  12. Classifier based on support vector machine for JET plasma configurationsa)

    Science.gov (United States)

    Dormido-Canto, S.; Farias, G.; Vega, J.; Dormido, R.; Sánchez, J.; Duro, N.; Vargas, H.; Murari, A.; Jet-Efda Contributors

    2008-10-01

    The last flux surface can be used to identify the plasma configuration of discharges. For automated recognition of JET configurations, a learning system based on support vector machines has been developed. Each configuration is described by 12 geometrical parameters. A multiclass system has been developed by means of the one-versus-the-rest approach. Results with eight simultaneous classes (plasma configurations) show a success rate close to 100%.

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

    OpenAIRE

    Hongtao Liu; Lianglun Cheng

    2012-01-01

    Available bandwidth is of great importance to network Quality of Service assurance, network load balancing, streaming media rate control, routing, and congestion control, etc.. In this paper, the available bandwidth estimation strategy based on the Network Allocation Vector for Wireless Sensor Networks is proposed. According to the size of the average contention window, network nodes predict the probability of collision in process of frame transmission, and then estimate the number of retrans...

  14. 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

  15. Efficient Satellite Scheduling Based on Improved Vector Evaluated Genetic Algorithm

    Directory of Open Access Journals (Sweden)

    Tengyue Mao

    2012-03-01

    Full Text Available Satellite scheduling is a typical multi-peak, many-valley, nonlinear multi-objective optimization problem. How to effectively implement the satellite scheduling is a crucial research in space areas.This paper mainly discusses the performance of VEGA (Vector Evaluated Genetic Algorithm based on the study of basic principles of VEGA algorithm, algorithm realization and test function, and then improves VEGA algorithm through introducing vector coding, new crossover and mutation operators, new methods to assign fitness and hold good individuals. As a result, the diversity and convergence of improved VEGA algorithm of improved VEGA algorithm have been significantly enhanced and will be applied to Earth-Mars orbit optimization. At the same time, this paper analyzes the results of the improved VEGA, whose results of performance analysis and evaluation show that although VEGA has a profound impact upon multi-objective evolutionary research,  multi-objective evolutionary algorithm on the basis of Pareto seems to be a more effective method to get the non-dominated solutions from the perspective of diversity and convergence of experimental result. Finally, based on Visual C + + integrated development environment, we have implemented improved vector evaluation algorithm in the satellite scheduling.

  16. SAM: Support Vector Machine Based Active Queue Management

    International Nuclear Information System (INIS)

    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)

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

    Directory of Open Access Journals (Sweden)

    Hongtao Liu

    2012-12-01

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

  18. Neural cell image segmentation method based on support vector machine

    Science.gov (United States)

    Niu, Shiwei; Ren, Kan

    2015-10-01

    In the analysis of neural cell images gained by optical microscope, accurate and rapid segmentation is the foundation of nerve cell detection system. In this paper, a modified image segmentation method based on Support Vector Machine (SVM) is proposed to reduce the adverse impact caused by low contrast ratio between objects and background, adherent and clustered cells' interference etc. Firstly, Morphological Filtering and OTSU Method are applied to preprocess images for extracting the neural cells roughly. Secondly, the Stellate Vector, Circularity and Histogram of Oriented Gradient (HOG) features are computed to train SVM model. Finally, the incremental learning SVM classifier is used to classify the preprocessed images, and the initial recognition areas identified by the SVM classifier are added to the library as the positive samples for training SVM model. Experiment results show that the proposed algorithm can achieve much better segmented results than the classic segmentation algorithms.

  19. Riesz multiwavelet bases generated by vector refinement equation

    Institute of Scientific and Technical Information of China (English)

    2009-01-01

    In this paper, we investigate compactly supported Riesz multiwavelet sequences and Riesz multiwavelet bases for L2(Rs). Suppose ψ = (ψ1, . . . , ψr)T and ψ = ( ψ1, . . . , ψr)T are two compactly supported vectors of functions in the Sobolev space (Hμ(Rs))r for some μ > 0. We provide a characterization for the sequences {ψjk : = 1, . . . , r, j ∈ Z, k ∈ Zs} and {ψ jk : = 1, . . . , r, j ∈ Z, k ∈ Zs} to form two Riesz sequences for L2(Rs), where ψjk = mj/2ψ (M j ·k) and ψjk = mj/2 ψ (M j ·k), M is an s × s integer matrix such that limn→∞ Mn = 0 and m = |detM|. Furthermore, let = (1, . . . , r)T and = ( 1, . . . , r)T be a pair of compactly supported biorthogonal refinable vectors of functions associated with the refinement masks a, a and M, where a and a are finitely supported sequences of r × r matrices. We obtain a general principle for characterizing vectors of functions ψν = (ψν1, . . . , ψνr)T and ψν = ( ψν1, . . . , ψ?νr)T , ν = 1, . . . , m 1 such that two sequences {ψjνk : ν = 1, . . . , m 1, = 1, . . . , r, j ∈ Z, k ∈ Zs} and {ψ jνk : ν = 1, . . . , m 1, = 1, . . . , r, j ∈ Z, k ∈ Zs} form two Riesz multiwavelet bases for L2(Rs). The bracket product [f, g] of two vectors of functions f, g in (L2(Rs))r is an indispensable tool for our characterization.

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

    OpenAIRE

    Jiusheng Chen; Xiaoyu Zhang; Kai Guo

    2016-01-01

    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 th...

  1. 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.

  2. 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.

  3. Debris Flow Hazard Assessment Based on Support Vector Machine

    Institute of Scientific and Technical Information of China (English)

    YUAN Lifeng; ZHANG Youshui

    2006-01-01

    Seven factors, including the maximum volume of once flow , occurrence frequency of debris flow , watershed area , main channel length , watershed relative height difference , valley incision density and the length ratio of sediment supplement are chosen as evaluation factors of debris flow hazard degree. Using support vector machine (SVM) theory, we selected 259 basic data of 37 debris flow channels in Yunnan Province as learning samples in this study. We create a debris flow hazard assessment model based on SVM. The model was validated though instance applications and showed encouraging results.

  4. Stokes vector formalism based second harmonic generation microscopy

    Science.gov (United States)

    Qiu, Jianjun; Mazumder, Nirmal; Tsai, Han-Ruei; Hu, Chih-Wei; Kao, Fu-Jen

    2012-02-01

    In this study, we have developed a four-channel Stokes vector formalism based second harmonic generation (SHG) microscopy to map and analyze SHG signal. A four-channel Stokesmeter setup is calibrated and integrated into a laser scanning microscope to measure and characterize the SH's corresponding Stokes parameters. We are demonstrating the use of SH and its Stokes parameters to visualize the birefringence and crystalline orientation of KDP and collagen. We believe the developed method can reveal unprecedented information for biomedical and biomaterial studies.

  5. Support vector classification algorithm based on variable parameter linear programming

    Institute of Scientific and Technical Information of China (English)

    Xiao Jianhua; Lin Jian

    2007-01-01

    To solve the problems of SVM in dealing with large sample size and asymmetric distributed samples, a support vector classification algorithm based on variable parameter linear programming is proposed.In the proposed algorithm, linear programming is employed to solve the optimization problem of classification to decrease the computation time and to reduce its complexity when compared with the original model.The adjusted punishment parameter greatly reduced the classification error resulting from asymmetric distributed samples and the detailed procedure of the proposed algorithm is given.An experiment is conducted to verify whether the proposed algorithm is suitable for asymmetric distributed samples.

  6. IRIS RECOGNITION BASED ON KERNELS OF SUPPORT VECTOR MACHINE

    Directory of Open Access Journals (Sweden)

    K. Saminathan

    2015-01-01

    Full Text Available Ensuring security biometrically is essential in most of the authentication and identification scenario. Recognition based on iris patterns is a thrust area of research cause to provide reliable, simple and rapid identification system. Machine learning classification algorithm of support vector machine [SVM] is applied in this work for personal identification. The profuse as well as unique patterns of iris are acquired and stored in the form of matrix template which contains 4800 elements for each iris. The row vectors of 2400 elements are passed as inputs to SVM classifier. The SVM generates separate classes for each user and performs matching based on the template’s unique spectral features of iris. The experimental results of this proposed work illustrate a better performance of 98.5% compared to the existing methods such as hamming distance, local binary pattern and various kernels of SVM. The popular CASIA (Chinese Academy of Sciences – Institute of Automation iris database with fifty users’ eye image samples are experimented to prove, that the least Square method of Quadratic kernel based SVM is comparatively better with minimal true rejection rate.

  7. Terminal Design in Vector Network based on Windows Platform

    Directory of Open Access Journals (Sweden)

    Aqun Zhao

    2013-03-01

    Full Text Available The research work of this study focuses on the design and implementation technology of terminal in Vector Network (VN based indows platform. The VN is a kind of new communication network with vector address as the switching adon Wdress. The premise of successful deployment of VN is its integration with the current IP networks, so it is necessary to study the implementation technology of VN terminal on the base of IP terminal. Firstly, a kind of software implementation method of VN terminal and a kind of integration method of VN and IP networks named “IP over VN” were proposed in this study. Secondly, the VN driver module was designed and implemented based on the NDIS driver interface and the key technique in the implementation was summarized. Finally, the experiment network was built to test the functions of VN terminal. The test results validated the rationality of the design and implementation scheme of VN terminal. The work of this study establishes the foundation for the deployment of VN and provides an example to the development of similar systems.

  8. 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; Munoz-Aguilar, Raul S.; Bellar, Maria D.

    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 shown....... Simulation results by using a space vector approach are presented. Special emphasis is given on the total harmonic distortion (THD) by making a comparison with those of the classical NPC topologies....

  9. Threat Assessment of Targets Based on Support Vector Machine

    Institute of Scientific and Technical Information of China (English)

    CAI Huai-ping; LIU Jing-xu; CHEN Ying-wu

    2006-01-01

    In the context of cooperative engagement of armored vehicles, the threat factors of offensive targets are analyzed, and a threat assessment (TA) model is built based on a support v.ector machine (SVM) method. The SVM-based model has some advantages over the traditional method-based models: the complex factors of threat are considered in the cooperative engagement; the shortcomings of neural networks, such as local minimum and "over fitting", are overcome to improve the generalization ability; its operation speed is high and meets the needs of real time C2 of cooperative engagement; the assessment results could be more reasonable because of its self-learning capability. The analysis and simulation indicate that the SVM method is an effective method to resolve the TA problems.

  10. Development and Applications of VSV Vectors Based on Cell Tropism

    OpenAIRE

    HidekiTani; YoshiharuMatsuura

    2012-01-01

    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 env...

  11. Disturbance observer based current controller for vector controlled IM drives

    DEFF Research Database (Denmark)

    Teodorescu, Remus; Dal, Mehmet

    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......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...... change in current control loop and, also to remove undesired cross coupling existing between components of the stator current. The observer uses the measured stator currents and estimated PWM voltages, and produces a disturbance signal with a low pass filter. The proposed control scheme reduces cross...

  12. 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.

  13. Parallel Kalman filter track fit based on vector classes

    International Nuclear Information System (INIS)

    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 μm and 44 μm for x and y track parameters and relative momentum resolution of 0.7%. The fitting time of 0.053 μs per track has been achieved on Intel Xeon X5550 with 8 cores at 2.6 GHz by using in addition Intel Threading Building Blocks.

  14. Facial biometrics based on 2D vector geometry

    Science.gov (United States)

    Malek, Obaidul; Venetsanopoulos, Anastasios; Androutsos, Dimitrios

    2014-05-01

    The main challenge of facial biometrics is its robustness and ability to adapt to changes in position orientation, facial expression, and illumination effects. This research addresses the predominant deficiencies in this regard and systematically investigates a facial authentication system in the Euclidean domain. In the proposed method, Euclidean geometry in 2D vector space is being constructed for features extraction and the authentication method. In particular, each assigned point of the candidates' biometric features is considered to be a 2D geometrical coordinate in the Euclidean vector space. Algebraic shapes of the extracted candidate features are also computed and compared. The proposed authentication method is being tested on images from the public "Put Face Database". The performance of the proposed method is evaluated based on Correct Recognition (CRR), False Acceptance (FAR), and False Rejection (FRR) rates. The theoretical foundation of the proposed method along with the experimental results are also presented in this paper. The experimental results demonstrate the effectiveness of the proposed method.

  15. Normal Vector Based Subdivision Scheme to Generate Fractal Curves

    Directory of Open Access Journals (Sweden)

    Yi Li

    2013-08-01

    Full Text Available In this paper, we firstly devise a new and general p-ary subdivision scheme based on normal vectors with multi-parameters to generate fractals. Rich and colorful fractals including some known fractals and a lot of unknown ones can be generated directly and conveniently by using it uniformly. The method is easy to use and effective in generating fractals since the values of the parameters and the directions of normal vectors can be designed freely to control the shape of generated fractals. Secondly, we illustrate the technique with some design results of fractal generation and the corresponding fractal examples from the point of view of visualization, including the classical Lévy curves, Dragon curves, Sierpiński gasket, Koch curve, Koch-type curves and other fractals. Finally, some fractal properties of the limit of the presented subdivision scheme, including existence, self-similarity, non-rectifiability, and continuity but nowhere differentiability are described from the point of view of theoretical analysis.

  16. 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.

  17. A three-axis SQUID-based absolute vector magnetometer

    Science.gov (United States)

    Schönau, T.; Zakosarenko, V.; Schmelz, M.; Stolz, R.; Anders, S.; Linzen, S.; Meyer, M.; Meyer, H.-G.

    2015-10-01

    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/Hz1/2. 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.

  18. Three—Dimensional Vector Field Visualization Based on Tensor Decomposition

    Institute of Scientific and Technical Information of China (English)

    梁训东; 李斌; 等

    1996-01-01

    This paper presents a visualization method called the deformed cube for visualizing 3D velocity vector field.Based on the decomposition of the tensor which describes the changes of the velocity,it provides a technique for visualizing local flow.A deformed cube,a cube transformed by a tensor in a local coordinate frame,shows the local stretch,shear and rigid body rotation of the local flow corresponding to the decomposed component of the tensor.Users can interactively view the local deformation or any component of the changes.The animation of the deformed cube moving along a streamline achieves a more global impression of the flow field.This method is intended as a complement to global visualization methods.

  19. Support vector machine based battery model for electric vehicles

    International Nuclear Information System (INIS)

    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%

  20. BEHAVIOR BASED CREDIT CARD FRAUD DETECTION USING SUPPORT VECTOR MACHINES

    Directory of Open Access Journals (Sweden)

    V. Dheepa

    2012-07-01

    Full Text Available Along with the great increase of internet and e-commerce, the use of credit card is an unavoidable one. Due to the increase of credit card usage, the frauds associated with this have also increased. There are a lot of approaches used to detect the frauds. In this paper, behavior based classification approach using Support Vector Machines are employed and efficient feature extraction method also adopted. If any discrepancies occur in the behaviors transaction pattern then it is predicted as suspicious and taken for further consideration to find the frauds. Generally credit card fraud detection problem suffers from a large amount of data, which is rectified by the proposed method. Achieving finest accuracy, high fraud catching rate and low false alarms are the main tasks of this approach.

  1. Image replica detection based on support vector classifier

    Science.gov (United States)

    Maret, Y.; Dufaux, F.; Ebrahimi, T.

    2005-08-01

    In this paper, we propose a technique for image replica detection. By replica, we mean equivalent versions of a given reference image, e.g. after it has undergone operations such as compression, filtering or resizing. Applications of this technique include discovery of copyright infringement or detection of illicit content. The technique is based on the extraction of multiple features from an image, namely texture, color, and spatial distribution of colors. Similar features are then grouped into groups and the similarity between two images is given by several partial distances. The decision function to decide whether a test image is a replica of a given reference image is finally derived using Support Vector Classifier (SVC). In this paper, we show that this technique achieves good results on a large database of images. For instance, for a false negative rate of 5 % the system yields a false positive rate of only 6 " 10-5.

  2. A three-axis SQUID-based absolute vector magnetometer

    International Nuclear Information System (INIS)

    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/Hz1/2. 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

  3. TYRE DYNAMICS MODELLING OF VEHICLE BASED ON SUPPORT VECTOR MACHINES

    Institute of Scientific and Technical Information of China (English)

    ZHENG Shuibo; TANG Houjun; HAN Zhengzhi; ZHANG Yong

    2006-01-01

    Various methods of tyre modelling are implemented from pure theoretical to empirical or semi-empirical models based on experimental results. A new way of representing tyre data obtained from measurements is presented via support vector machines (SVMs). The feasibility of applying SVMs to steady-state tyre modelling is investigated by comparison with three-layer backpropagation(BP) neural network at pure slip and combined slip. The results indicate SVMs outperform the BP neural network in modelling the tyre characteristics with better generalization performance. The SVMs-tyre is implemented in 8-DOF vehicle model for vehicle dynamics simulation by means of the PAC 2002 Magic Formula as reference. The SVMs-tyre can be a competitive and accurate method to model a tyre for vehicle dynamics simulation.

  4. SENSITIVITY ANALYSIS FOR ROLLING PROCESS BASED ON SUPPORT VECTOR MACHINE

    Institute of Scientific and Technical Information of China (English)

    Huang Yanwei; Wu Tihua; Zhao Jingyi; Wang Yiqun

    2005-01-01

    A method for the calculation of the sensitivity factors of the rolling process has been obtained by differentiating the roll force model based on support vector machine. It can eliminate the algebraic loop of the analytical model of the rolling process. The simulations in the first stand of five stand cold tandem rolling mill indicate that the calculation for sensitivities by this proposed method can obtain a good accuracy, and an appropriate adjustment on the control variables determined directly by the sensitivity has an excellent compensation accuracy. Moreover, the roll gap has larger effect on the exit thickness than both front tension and back tension, and it is more efficient to select the roll gap as the controlvariable of the thickness control system in the first stand.

  5. 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...

  6. Molecular bases of proliferation of Francisella tularensis in Arthropod vectors

    OpenAIRE

    Asare, Rexford; Akimana, Christine; Jones, Snake; Kwaik, Yousef Abu

    2010-01-01

    Arthropod vectors are important vehicles for transmission of Francisella tularensis between mammals, but very little is known about the F. tularensis-arthropod vector interaction. Drosophila melanogaster has been recently developed as an arthropod vector model for F. tularensis. We have shown that intracellular trafficking of F. tularensis within human monocytes-derived macrophages and D. melanogaster-derived S2 cells is very similar. Within both evolutionarily distant host cells, the Francis...

  7. Vector ordinal optimization based multi-objective transmission planning

    International Nuclear Information System (INIS)

    The deregulation of the power industry has resulted in a restructured industry. The integrated power industry has been separated into generation companies, transmission company and distribution companies. Each individual market participant has its own goal of maximizing its profit in power system planning and power system operation. In this paper, the vector ordinal optimization (VOO) theory was applied to solve the multi-objective transmission expansion planning (TEP) problems. The weight-summation of multiple objectives was considered as a single objective. In order to reflect the interests of different market participants and the social benefit, the authors used the Transmission Economic Assessment Methodology (TEAM) to formulate the multi-objective TEP. The VOO solution algorithm was presented and tested based on the TEAM model. Numerical examples were presented to test the proposed VOO based solution algorithm. The 4 indices of the transmission economic assessment methodology were used as the 4 objectives for transmission planning. VOO uses crude models to estimate the indices of the TEAM base multi-objective optimization problem to determine a select subset of schemes to simulate and find solutions which have been termed as good enough. The calculation burden was reduced significantly by using this method. Test results on the modified IEEE 14-bus system show that the VOO is efficient and practical for solving multi-objective TEP problems. The test results show that the proposed VOO approach can find good enough solutions in a short time with less computational burden. 11 refs., 5 tabs., 3 figs., 1 appendix.

  8. DBCSVM: Density Based Clustering Using Support VectorMachines

    Directory of Open Access Journals (Sweden)

    Santosh Kumar Rai

    2012-07-01

    Full Text Available Data categorization is challenging job in a current scenario. The growth rate of a multimedia data are increase day to day in an internet technology. For the better retrieval and efficient searching of a data, a process required for grouping the data. However, data mining can find out helpful implicit information in large databases. To detect the implicit useful information from large databases various data mining techniques are use. Data clustering is an important data mining technique for grouping data sets into different clusters and each cluster having same properties of data. In this paper we have taken image data sets and firstly applying the density based clustering to grouped the images, density based clustering grouped the images according to the nearest feature sets but not grouped outliers, then we used an important super hyperplane classifier support vector machine (SVM which classify the all outlier left from density based clustering. This method improves the efficiency of image grouping and gives better results.

  9. Hybrid Support Vector Machines-Based Multi-fault Classification

    Institute of Scientific and Technical Information of China (English)

    GAO Guo-hua; ZHANG Yong-zhong; ZHU Yu; DUAN Guang-huang

    2007-01-01

    Support Vector Machines (SVM) is a new general machine-learning tool based on structural risk minimization principle. This characteristic is very signific ant for the fault diagnostics when the number of fault samples is limited. Considering that SVM theory is originally designed for a two-class classification, a hybrid SVM scheme is proposed for multi-fault classification of rotating machinery in our paper. Two SVM strategies, 1-v-1 (one versus one) and 1-v-r (one versus rest), are respectively adopted at different classification levels. At the parallel classification level, using 1-v-1 strategy, the fault features extracted by various signal analysis methods are transferred into the multiple parallel SVM and the local classification results are obtained. At the serial classification level, these local results values are fused by one serial SVM based on 1-v-r strategy. The hybrid SVM scheme introduced in our paper not only generalizes the performance of signal binary SVMs but improves the precision and reliability of the fault classification results. The actually testing results show the availability suitability of this new method.

  10. Progress in Chimeric Vector and Chimeric Gene Based Cardiovascular Gene Therapy

    Institute of Scientific and Technical Information of China (English)

    HU Chun-Song; YOON Young-sup; ISNER Jeffrey M.; LOSORDO Douglas W.

    2003-01-01

    Gene therapy for cardiovascular diseases has developed from preliminary animal experiments to clinical trials. However, vectors and target genes used currently in gene therapy are mainly focused on viral, nonviral vector and single target gene or monogene. Each vector system has a series of advantages and limitations. Chimeric vectors which combine the advantages of viral and nonviral vector,chimeric target genes which combine two or more target genes and novel gene delivery modes are being developed. In this article, we summarized the progress in chimeric vectors and chimeric genes based cardiovascular gene therapy, which including proliferative or occlusive vascular diseases such as atheroslerosis and restenosis, hypertonic vascular disease such as hypertension and cardiac diseases such as myocardium ischemia, dilated cardiomyopathy and heart failure, even heart transplantation. The development of chimeric vector, chimeric gene and their cardiovascular gene therapy is promising.

  11. 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.

  12. Noninvasive extraction of fetal electrocardiogram based on Support Vector Machine

    Science.gov (United States)

    Fu, Yumei; Xiang, Shihan; Chen, Tianyi; Zhou, Ping; Huang, Weiyan

    2015-10-01

    The fetal electrocardiogram (FECG) signal has important clinical value for diagnosing the fetal heart diseases and choosing suitable therapeutics schemes to doctors. So, the noninvasive extraction of FECG from electrocardiogram (ECG) signals becomes a hot research point. A new method, the Support Vector Machine (SVM) is utilized for the extraction of FECG with limited size of data. Firstly, the theory of the SVM and the principle of the extraction based on the SVM are studied. Secondly, the transformation of maternal electrocardiogram (MECG) component in abdominal composite signal is verified to be nonlinear and fitted with the SVM. Then, the SVM is trained, and the training results are compared with the real data to ensure the effect of the training. Meanwhile, the parameters of the SVM are optimized to achieve the best performance so that the learning machine can be utilized to fit the unknown samples. Finally, the FECG is extracted by removing the optimal estimation of MECG component from the abdominal composite signal. In order to evaluate the performance of FECG extraction based on the SVM, the Signal-to-Noise Ratio (SNR) and the visual test are used. The experimental results show that the FECG with good quality can be extracted, its SNR ratio is significantly increased as high as 9.2349 dB and the time cost is significantly decreased as short as 0.802 seconds. Compared with the traditional method, the noninvasive extraction method based on the SVM has a simple realization, the shorter treatment time and the better extraction quality under the same conditions.

  13. Priori Information Based Support Vector Regression and Its Applications

    Directory of Open Access Journals (Sweden)

    Litao Ma

    2015-01-01

    Full Text Available In order to extract the priori information (PI provided by real monitored values of peak particle velocity (PPV and increase the prediction accuracy of PPV, PI based support vector regression (SVR is established. Firstly, to extract the PI provided by monitored data from the aspect of mathematics, the probability density of PPV is estimated with ε-SVR. Secondly, in order to make full use of the PI about fluctuation of PPV between the maximal value and the minimal value in a certain period of time, probability density estimated with ε-SVR is incorporated into training data, and then the dimensionality of training data is increased. Thirdly, using the training data with a higher dimension, a method of predicting PPV called PI-ε-SVR is proposed. Finally, with the collected values of PPV induced by underwater blasting at Dajin Island in Taishan nuclear power station in China, contrastive experiments are made to show the effectiveness of the proposed method.

  14. Space Vector Based Hybrid PWM Techniques for Reduced Current Ripple

    OpenAIRE

    Narayanan, G.; Zhao, Di; Krishnamurthy, Harish K; Ayyanar, Rajapandian; Ranganathan, VT

    2008-01-01

    This paper investigates certain novel switching sequences involving division of active vector time for space vectorbased pulsewidth modulation (PWM) generation for a voltage source inverter. This paper proposes two new sequences, and identifies all possible sequences, which result in the same average switching frequency as conventional space vector PWM (CSVPWM) at a given sampling frequency. This paper brings out amethod for designing hybrid PWMtechniques involving multiple sequences to reduc...

  15. Space vector-based analysis of overmodulation in triangle-comparison based PWM for voltage source inverter

    OpenAIRE

    Modi, Manoj Kumar; Venugopal, S.; Narayanan, G.

    2013-01-01

    The equivalence of triangle-comparison-based pulse width modulation (TCPWM) and space vector based PWM (SVPWM) during linear modulation is well-known. This paper analyses triangle-comparison based PWM techniques (TCPWM) such as sine-triangle PWM (SPWM) and common-mode voltage injection PWM during overmodulation from a space vector point of view. The average voltage vector produced by TCPWM during overmodulation is studied in the stationary (a-b) reference frame. This is compared and contraste...

  16. Permissive growth of human adenovirus type 4 vaccine strain-based vector in porcine cell lines.

    Science.gov (United States)

    Gao, Dong-Sheng; Li, Xiao-Jing; Wan, Wen-Yan; Li, Hong-Jie; Wang, Xiao-Xue; Yang, Xia; Li, Yong-Tao; Chang, Hong-Tao; Chen, Lu; Wang, Chuan-Qing; Zhao, Jun

    2016-02-01

    In recent years, there has been considerable interest in using adenoviruses as live vectors to develop recombinant vaccines. Previous studies have demonstrated the safety and effectiveness of HIV/SIV and influenza vaccine candidates based on human adenovirus type 4 (Ad4) replication-competent vectors in rhesus macaque and human model. To explore the possibility of human Ad4 vaccine strain used as a vector in developing porcine vaccines, the growth properties of replication-competent human Ad4 vaccine strain recombinant encoding EGFP in different porcine cell lines were investigated. All tested cell lines are permissive for Ad4 vaccine strain vector with varied replication efficiency. Thus, human Ad4 based vectors would be promising supplement to adenovirus vectors as a delivery vehicle for recombinant vaccines in swine industry. PMID:26850542

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

    DEFF Research Database (Denmark)

    Krenk, Steen; Nielsen, Martin Bjerre

    2014-01-01

    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......A conservative time integration formulation is developed for rigid bodies based on a convected set of orthonormal base vectors. The base vectors are represented in terms of their absolute coordinates, and thus the formulation makes use of three translation components, plus nine components......-strain conditions as well as external constraints via Lagrange multipliers. Subsequently, the Lagrange multipliers associated with the internal zero-strain constraints are eliminated by use of a set of orthogonality conditions between the generalized displacements and the momentum vector, leaving a set...

  18. Agent-based modeling of malaria vectors: the importance of spatial simulation

    OpenAIRE

    Bomblies, Arne

    2014-01-01

    Background The modeling of malaria vector mosquito populations yields great insight into drivers of malaria transmission at the village scale. Simulation of individual mosquitoes as “agents” in a distributed, dynamic model domain may be greatly beneficial for simulation of spatial relationships of vectors and hosts. Methods In this study, an agent-based model is used to simulate the life cycle and movement of individual malaria vector mosquitoes in a Niger Sahel village, with individual simul...

  19. A Vector-based Cellular Automata Model for Simulating Urban Land Use Change

    Institute of Scientific and Technical Information of China (English)

    LU Yi; CAO Min; ZHANG Lei

    2015-01-01

    Cellular Automata (CA) is widely used for the simulation of land use changes.This study applied a vector-based CA model to simulate land use change in order to minimize or eliminate the scale sensitivity in traditional raster-based CA model.The cells of vector-based CA model are presented according to the shapes and attributes of geographic entities,and the transition rules of vector-based CA model are improved by taking spatial variables of the study area into consideration.The vector-based CA model is applied to simulate land use changes in downtown of Qidong City,Jiangsu Province,China and its validation is confirmed by the methods of visual assessment and spatial accuracy.The simulation result of vector-based CA model reveals that nearly 75% of newly increased urban cells are located in the northwest and southwest parts of the study area from 2002 to 2007,which is in consistent with real land use map.In addition,the simulation results of the vector-based and raster-based CA models are compared to real land use data and their spatial accuracies are found to be 84.0% and 81.9%,respectively.In conclusion,results from this study indicate that the vector-based CA model is a practical and applicable method for the simulation of urbanization processes.

  20. 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.

  1. 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......A conservative time integration algorithm based on a convected set of orthonormal base vectors is presented. The equations of motion are derived from an extended Hamiltonian formulation, combining the components of the three base vectors with a set of orthonormality constraints. The particular form...

  2. A Novel Coding Method Based on Fuzzy Vector Quantization for Noised Image

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    In this paper a novel coding method based on fuzzy vector quantization for noised image with Gaussian white-noise pollution is presented. By restraining the high frequency subbands of wavelet image the noise is significantly removed and coded with fuzzy vector quantization. The experimental result shows that the method can not only achieve high compression ratio but also remove noise dramatically.

  3. ELABORATION OF A VECTOR BASED SEMANTIC CLASSIFICATION OVER THE WORDS AND NOTIONS OF THE NATURAL LANGUAGE

    OpenAIRE

    Safonov, K.; Lichargin, D.

    2009-01-01

    The problem of vector-based semantic classification over the words and notions of the natural language is discussed. A set of generative grammar rules is offered for generating the semantic classification vector. Examples of the classification application and a theorem of optional formal classification incompleteness are presented. The principles of assigning the meaningful phrases functions over the classification word groups are analyzed.

  4. New Iterative Learning Control Algorithms Based on Vector Plots Analysis1)

    Institute of Scientific and Technical Information of China (English)

    XIESheng-Li; TIANSen-Ping; XIEZhen-Dong

    2004-01-01

    Based on vector plots analysis, this paper researches the geometric frame of iterativelearning control method. New structure of iterative learning algorithms is obtained by analyzingthe vector plots of some general algorithms. The structure of the new algorithm is different fromthose of the present algorithms. It is of faster convergence speed and higher accuracy. Simulationspresented here illustrate the effectiveness and advantage of the new algorithm.

  5. Classification of Regional Ionospheric Disturbances Based on Support Vector Machines

    Science.gov (United States)

    Begüm Terzi, Merve; Arikan, Feza; Arikan, Orhan; Karatay, Secil

    2016-07-01

    Ionosphere is an anisotropic, inhomogeneous, time varying and spatio-temporally dispersive medium whose parameters can be estimated almost always by using indirect measurements. Geomagnetic, gravitational, solar or seismic activities cause variations of ionosphere at various spatial and temporal scales. This complex spatio-temporal variability is challenging to be identified due to extensive scales in period, duration, amplitude and frequency of disturbances. Since geomagnetic and solar indices such as Disturbance storm time (Dst), F10.7 solar flux, Sun Spot Number (SSN), Auroral Electrojet (AE), Kp and W-index provide information about variability on a global scale, identification and classification of regional disturbances poses a challenge. The main aim of this study is to classify the regional effects of global geomagnetic storms and classify them according to their risk levels. For this purpose, Total Electron Content (TEC) estimated from GPS receivers, which is one of the major parameters of ionosphere, will be used to model the regional and local variability that differs from global activity along with solar and geomagnetic indices. In this work, for the automated classification of the regional disturbances, a classification technique based on a robust machine learning technique that have found wide spread use, Support Vector Machine (SVM) is proposed. SVM is a supervised learning model used for classification with associated learning algorithm that analyze the data and recognize patterns. In addition to performing linear classification, SVM can efficiently perform nonlinear classification by embedding data into higher dimensional feature spaces. Performance of the developed classification technique is demonstrated for midlatitude ionosphere over Anatolia using TEC estimates generated from the GPS data provided by Turkish National Permanent GPS Network (TNPGN-Active) for solar maximum year of 2011. As a result of implementing the developed classification

  6. Research on Matrix Converter Based on Space Vector Modulation

    Directory of Open Access Journals (Sweden)

    Zhanjun Qiao

    2013-09-01

    Full Text Available In this study, we study the control strategy for matrix converter. Through absorbing ideas about virtual rectification put forward by P.D.Ziogas, the common control idea of AC-DC-AC convertor is introduced into control of matrix converter; SPWM modulation strategy and space vector modulation strategy for matrix converter are studied respectively. In terms of SPWM modulation strategy, it has some advantages: for example, main circuit structure is simple; control program is simple; control switch function does not need complex mathematical derivation and calculation. In terms of space vector modulation strategy, it has advantages as follows: the physical conception is clear; input power factor can be adjusted; output voltage and current sine degree are high. In this chapter, an in-depth analysis will be conducted for this control method

  7. 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)...

  8. Wireless Localization Based on RSSI Fingerprint Feature Vector

    OpenAIRE

    Aiguo Zhang; Ying Yuan; Qunyong Wu; Shunzhi Zhu; Jian Deng

    2015-01-01

    RSSI wireless signal is a reference information that is widely used in indoor positioning. However, due to the wireless multipath influence, the value of the received RSSI will have large fluctuations and cause large distance error when RSSI is fitted to distance. But experimental data showed that, being affected by the combined factors of the environment, the received RSSI feature vector which is formed by lots of RSSI values from different APs is a certain stability. Therefore, the paper pr...

  9. Window-Based Example Selection in Learning Vector Quantization

    OpenAIRE

    Witoelar, A. W.; Ghosh, Anarta; De Vries, J.J.G.; Hammer, B; Biehl, M.

    2010-01-01

    A variety of modifications have been employed to learning vector quantization (LVQ) algorithms using either crisp or soft windows for selection of data. Although these schemes have been shown in practice to improve performance, a theoretical study on the influence of windows has so far been limited. Here we rigorously analyze the influence of windows in a controlled environment of gaussian mixtures in high dimensions. Concepts from statistical physics and the theory of online learning allow a...

  10. Research on Matrix Converter Based on Space Vector Modulation

    OpenAIRE

    Zhanjun Qiao; Wei Xu

    2013-01-01

    In this study, we study the control strategy for matrix converter. Through absorbing ideas about virtual rectification put forward by P.D.Ziogas, the common control idea of AC-DC-AC convertor is introduced into control of matrix converter; SPWM modulation strategy and space vector modulation strategy for matrix converter are studied respectively. In terms of SPWM modulation strategy, it has some advantages: for example, main circuit structure is simple; control program is simple; control swit...

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

    OpenAIRE

    Krenk, Steen; Nielsen, Martin Bjerre

    2013-01-01

    A conservative time integration algorithm based on a convected set of orthonormal base vectors is presented. The equations of motion are derived from an extended Hamiltonian formulation, combining the components of the three base vectors with a set of orthonormality constraints. The particular form 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 strai...

  12. 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.

  13. A new method for comparing scanpaths based on vectors and dimensions

    OpenAIRE

    Dewhurst, Richard; Jarodzka, Halszka; Holmqvist, Kenneth; Foulsham, Tom; Nyström, Marcus

    2011-01-01

    Dewhurst, R., Jarodzka, H., Holmqvist, K., Foulsham, T., & Nyström, M. (2011, May). A new method for comparing scanpaths based on vectors and dimensions. Vision Sciences Society 2011, Naples, Florida.

  14. An evidence-based vector control strategy for military deployments: the British Army experience.

    Science.gov (United States)

    Croft, A M; Baker, D; von Bertele, M J

    2001-01-01

    We describe the British Army's current strategy for controlling arthropod vectors of disease during overseas deployments. Military commanders and medical officers have different, but complementary responsibilities in achieving vector control. In this paper we define a hierarchy of evidence-based vector control guidelines. Field guidelines must be based on the best available research evidence, preferably that derived from pragmatic randomised controlled trials (RCTs), and from systematic reviews of trials. Assessing the effectiveness of different vector control measures involves a trade-off between the relative benefits and harm of different technology options. There is compelling scientific evidence that bed nets and screens treated with a pyrethroid insecticide are highly effective in protecting against nocturnally active, anthropophilic arthropods (including ectoparasites), and will reduce the incidence of malaria, leishmaniasis, lymphatic filariasis and Chagas' disease. Etofenprox and deltamethrin are the safest pyrethroids, and permethrin the least safe. Vector control strategies of probable effectiveness are the use of insecticide-treated clothing, the wearing of protective clothing, and the correct use of DEET-based topical insect repellents. Aerosol insecticides are of debatable effectiveness. Other effective vector control measures, of limited usefulness during deployments, include electric fans, mosquito coils/vaporising mats, and smoke. "Biological" vector control measures, and insect buzzers/electrocuters are ineffective. Practical insect avoidance measures, based on an understanding of vector biology, complete the military vector-control arsenal. We conclude that practical insect avoidance measures, combined with pyrethroid-treated nets and clothing, and DEET-based topical repellents, can achieve almost 100% protection against biting arthropods. PMID:11584666

  15. Formulation of 2D Graphene Deformation Based on Chiral-Tube Base Vectors

    International Nuclear Information System (INIS)

    The intrinsic feature of graphene honeycomb lattice is defined by its chiral index (n,m), which can be taken into account when using molecular dynamics. However, how to introduce the index into the continuum model of graphene is still an open problem. The present manuscript adopts the continuum shell model with single director to describe the mechanical behaviors of graphene. In order to consider the intrinsic features of the graphene honeycomb lattice chira index (n,m), the chiral-tube vectors of graphene in real space have been used for construction of reference unit base vectors of the shell model; therefore, the formulations will contain the chiral index automatically, or in an explicit form in physical components. The results are quite useful for future studies of graphene mechanics

  16. Formulation of 2D Graphene Deformation Based on Chiral-Tube Base Vectors

    Directory of Open Access Journals (Sweden)

    Bohua Sun

    2010-01-01

    Full Text Available The intrinsic feature of graphene honeycomb lattice is defined by its chiral index (n,m, which can be taken into account when using molecular dynamics. However, how to introduce the index into the continuum model of graphene is still an open problem. The present manuscript adopts the continuum shell model with single director to describe the mechanical behaviors of graphene. In order to consider the intrinsic features of the graphene honeycomb lattice—chiral index (n,m, the chiral-tube vectors of graphene in real space have been used for construction of reference unit base vectors of the shell model; therefore, the formulations will contain the chiral index automatically, or in an explicit form in physical components. The results are quite useful for future studies of graphene mechanics.

  17. Soft Sensing Based on Hilbert-Huang Transform and Wavelet Support Vector Machine

    Directory of Open Access Journals (Sweden)

    Qiang Wang

    2013-07-01

    Full Text Available At present, much more soft sensing have been widely used in industrial process control to improve the quality of product and assure safety in production. A novel method using  Hilbert-Huang transform(HHT combined with wavelet support vector machine(WSVM is put forward.Firstly the method analyzes the intrinsic mode function (IMF obtained after the empirical mode decomposition (EMD, then extracts IMF energy feature as the input feature vectors of the wavelet support vector machine. Based on the wavelet analysis and conditions of the support vector kernel function, a novel multi-dimension admissible support vector wavelet kernel function is presented, which is a multidimensional wavelet kernel, thus enhancing the generalization ability of the SVM. The proposed method is used to build soft sensing of diesel oil solidifying point. Compared with other two models, the result shows that HHT-WSVM approach has a better prediction and generalization.

  18. Real-time traffic information extraction based on compressed video with interframe motion vector

    Institute of Scientific and Technical Information of China (English)

    黄庆明; 王聪

    2003-01-01

    Extraction of traffic information from image or video sequence is a hot research topic in intelligenttransportation system and computer vision. A real-time traffic information extraction method based on com-pressed video with interframe motion vectors for speed, density and flow detection, has been proposed for ex-traction of traffic information under fixed camera setting and well-defined environment. The motion vectors arefirst separated from the compressed video streams, and then filtered to eliminate incorrect and noisy vectors u-sing the well-defined environmental knowledge. By applying the projective transform and using the filtered mo-tion vectors, speed can be calculated from motion vector statistics, density can be estimated using the motionvector occupancy, and flow can be detected using the combination of speed and density. The embodiment of aprototype system for sky camera traffic monitoring using the MPEG video has been implemented, and experi-mental results proved the effectiveness of the method proposed.

  19. Bethe vectors for models based on the super-Yangian $Y(\\mathfrak{gl}(m|n))$

    CERN Document Server

    Pakuliak, S Z; Slavnov, N A

    2016-01-01

    We study Bethe vectors of integrable models based on the super-Yangian $Y(\\mathfrak{gl}(m|n))$. Starting from the super-trace formula, we exhibit recursion relations for these vectors in the case of $Y(\\mathfrak{gl}(2|1))$ and $Y(\\mathfrak{gl}(1|2))$. These recursion relations allow to get explicit expressions for the Bethe vectors. Using an antimorphism of the super-Yangian $Y(\\mathfrak{gl}(m|n))$, we also construct a super-trace formula for dual Bethe vectors, and, for $Y(\\mathfrak{gl}(2|1))$ and $Y(\\mathfrak{gl}(1|2))$ super-Yangians, show recursion relations for them. Again, the latter allow us to get explicit expressions for dual Bethe vectors.

  20. Video Surveillance Application Based on Application Specific Vector Processors

    Czech Academy of Sciences Publication Activity Database

    Bartosinski, Roman; Daněk, Martin; Sýkora, Jaroslav; Kohout, Lukáš; Honzík, P.

    Gières: Electronic Chips & Systems design Initiative, 2012 - (Morawiec, A.; Hinderscheit, J.), s. 248-255 ISBN 978-2-9539987-2-6. ISSN 1966-7116. [Conference on Design & Architectures for Signal & Image Processing . Karlsruhe (DE), 23.10.2012-25.10.2012] R&D Projects: GA MŠk(CZ) 7H10001 Institutional support: RVO:67985556 Keywords : video surveillance * smart camera * custom accelerators * vector processing * FPGA Subject RIV: JC - Computer Hardware ; Software http://library.utia.cas.cz/separaty/2012/ZS/bartosinski-0382184.pdf

  1. Emotional Vector Distance Based Sentiment Analysis of Wakamono Kotoba

    Institute of Scientific and Technical Information of China (English)

    2012-01-01

    In this paper, we propose a method for estimating emotion in Wakamono Kotoba that were not registered in the system, by using Wakamono Kotoba example sentences as features. The pro- posed method applies Earth Mover's Distance (EMD) to vector of words. As a result of the evaluation ex- periment using 14 440 sentences, higher estimation accuracy is obtained by considering emotional dis- tance between words - an approach that had not been used in the conventional research - than by using only word importance value.

  2. Digital Simulation of Space Vector Modulation Based Induction Motor Drive

    Directory of Open Access Journals (Sweden)

    G.V. Siva Krishna Rao and T.S. Surendra

    2011-04-01

    Full Text Available This study deals with simulation of Space vector modulated inverter fed induction motor drive. The drive system is modeled using matlab simulink and the results are presented. This drive has advantages like reduced harmonics and heating. Fixed AC is converted into DC and this DC is converted into variable voltage and variable frequency AC using SVM inverter. The output of SVM is applied to the stator of induction motor. The simulation results are compared with the analytical results. The FFT analysis shows that the current spectrum has reduced harmonics compared to the conventional system.

  3. Automatic SIMD vectorization of SSA-based control flow graphs

    CERN Document Server

    Karrenberg, Ralf

    2015-01-01

    Ralf Karrenberg presents Whole-Function Vectorization (WFV), an approach that allows a compiler to automatically create code that exploits data-parallelism using SIMD instructions. Data-parallel applications such as particle simulations, stock option price estimation or video decoding require the same computations to be performed on huge amounts of data. Without WFV, one processor core executes a single instance of a data-parallel function. WFV transforms the function to execute multiple instances at once using SIMD instructions. The author describes an advanced WFV algorithm that includes a v

  4. Sagnac Interferometer Based Generation of Controllable Cylindrical Vector Beams

    Directory of Open Access Journals (Sweden)

    Cristian Acevedo

    2016-01-01

    Full Text Available We report on a novel experimental geometry to generate cylindrical vector beams in a very robust manner. Continuous control of beams’ properties is obtained using an optically addressable spatial light modulator incorporated into a Sagnac interferometer. Forked computer-generated holograms allow introducing different topological charges while orthogonally polarized beams within the interferometer permit encoding the spatial distribution of polarization. We also demonstrate the generation of complex waveforms obtained by combining two orthogonal beams having both radial modulations and azimuthal dislocations.

  5. Inertial Vector Based Attitude Stabilization of Rigid Body Without Angular Velocity Measurements

    OpenAIRE

    Benziane, L.; Benallegue, A.; Chitour, Y.; Tayebi, A.

    2015-01-01

    We address the problem of attitude stabilization of a rigid body, in which neither the angular velocity nor the instantaneous measurements of the attitude are used in the feedback, only body vector measurements are needed. The design of the controller is based on an angular velocity observer-like system, where a first order linear auxiliary system based directly on vector measurements is introduced. The introduction of gain matrices provides more tuning flexibility and better results compared...

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

    Directory of Open Access Journals (Sweden)

    Huang Zhuojie

    2012-08-01

    Full Text Available Abstract Background 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. Methods 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. Results 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. Conclusions 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

  7. Mass detection algorithm based on support vector machine and relevance feedback

    Institute of Scientific and Technical Information of China (English)

    Ying WANG; Xinbo GAO

    2008-01-01

    To improve the detection of mass with appearance that borders on the similarity between mass and density tissues in the breast,an support vector machine classifier based on typical features iS designed to classify the region of interest(ROI).Furthermore,relevance feedback is introduced to improve the performance of support vector machines.A new mass detection scheme based on the support vector machine and the relevance feedback is proposed.Simulation experiments on mammograms illustrate that the novel support vector machine classifier based on typical features can improve the detection performance of the featureless classifier by 5%,while the introduction of relevance feedback can further improve the detection performance to about 90%.

  8. Aero-Engine Condition Monitoring Based on Support Vector Machine

    Science.gov (United States)

    Zhang, Chunxiao; Wang, Nan

    The maintenance and management of civil aero-engine require advanced monitor approaches to estimate aero-engine performance and health in order to increase life of aero-engine and reduce maintenance costs. In this paper, we adopted support vector machine (SVM) regression approach to monitor an aero-engine health and condition by building monitoring models of main aero-engine performance parameters(EGT, N1, N2 and FF). The accuracy of nonlinear baseline models of performance parameters is tested and the maximum relative error does not exceed ±0.3%, which meets the engineering requirements. The results show that SVM nonlinear regression is an effective method in aero-engine monitoring.

  9. An Even Grid Based Lattice Vector Quantization Algorithm for Mobile Audio Coding

    Directory of Open Access Journals (Sweden)

    Bo Hang

    2011-06-01

    Full Text Available This paper proposed an even grid based lattice vector quantization method for audio coding. The method uses energy priority, with basic code book and the ball-type expansion, which is applicable to the low rate of the variable-rate vector quantization coding. The method uses the lattice characteristics to resolve rapid index distribution problem, as well as the compression of the basic code book. The experiment results show that the proposed method is as good as vector quantization method in ITU-T standard G729.1 in quality, with lower storage cost and computational complexity.

  10. 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.

  11. The electronic image stabilization technology research based on improved optical-flow motion vector estimation

    Science.gov (United States)

    Wang, Chao; Ji, Ming; Zhang, Ying; Jiang, Wentao; Lu, Xiaoyan; Wang, Jiaoying; Yang, Heng

    2016-01-01

    The electronic image stabilization technology based on improved optical-flow motion vector estimation technique can effectively improve the non normal shift, such as jitter, rotation and so on. Firstly, the ORB features are extracted from the image, a set of regions are built on these features; Secondly, the optical-flow vector is computed in the feature regions, in order to reduce the computational complexity, the multi resolution strategy of Pyramid is used to calculate the motion vector of the frame; Finally, qualitative and quantitative analysis of the effect of the algorithm is carried out. The results show that the proposed algorithm has better stability compared with image stabilization based on the traditional optical-flow motion vector estimation method.

  12. Incremental learning algorithm based on support vector machine with Mahalanobis distance (ISVMM) for intrusion prevention

    OpenAIRE

    Myint, Hnin Ohnmar; Meesad, Phayung

    2009-01-01

    In this paper we propose a new classifier called an incremental learning algorithm based on support vector machine with Mahalanobis distance (ISVMM). Prediction of the incoming data type by supervised learning of support vector machine (SVM), reducing the step of calculation and complexity of the algorithm by finding a support set, error set and remaining set, providing of hard and soft decisions, saving the time for repeatedly training the datasets by applying the incremental learning, a new...

  13. BET-independent MLV-based Vectors Target Away From Promoters and Regulatory Elements

    Science.gov (United States)

    El Ashkar, Sara; De Rijck, Jan; Demeulemeester, Jonas; Vets, Sofie; Madlala, Paradise; Cermakova, Katerina; Debyser, Zeger; Gijsbers, Rik

    2014-01-01

    Stable integration in the host genome renders murine leukemia virus (MLV)-derived vectors attractive tools for gene therapy. Adverse events in otherwise successful clinical trials caused by proto-oncogene activation due to vector integration hamper their application. MLV and MLV-based vectors integrate near strong enhancers, active promoters, and transcription start sites (TSS) through specific interaction of MLV integrase (IN) with the bromodomain and extra-terminal (BET) family of proteins, accounting for insertional mutagenesis. We identified a BET-interaction motif in the C-terminal tail of MLV IN conserved among gammaretroviruses. By deletion of this motif or a single point mutation (INW390A), BET-independent MLV (BinMLV) were engineered. BinMLV vectors carrying INW390A integrate at wild-type efficiency, with an integration profile that no longer correlates with BET chromatin distribution nor with the traditional markers of MLV integration. In particular, BinMLV vector integration associated less with oncogene TSS compared to the MLV vectors currently used in clinical trials. Together, these findings open perspectives to increase the biosafety of gammaretroviral vectors for gene therapy. PMID:25072693

  14. Performance of matched subspace detectors and support vector machines for induction-based land mine detection

    Science.gov (United States)

    Torrione, Peter A.; Collins, Leslie M.

    2002-08-01

    Wideband electromagnetic induction (EMI) data provides an opportunity to apply statistical signal processing techniques to potentially mitigate false alarm rates in landmine detection. This paper explores the application of matched subspace detectors and support vector machines (SVMs) to this problem. A library of landmine responses is generated from background-corrected calibration data and a bank of matched subspace detectors, each tuned to a specific mine type, is generated. Support vector machines are implemented based on the full mine responses, decay rate estimates, and the outputs of the matched subspace filter banks. Different training approaches are considered for the support vector machines. Receiver operating characteristics (ROCs) for the matched subspace detectors and support vector machines operating in a blind field test are presented. The results indicate that substantial reductions in the false alarm rates can be achieved using these techniques.

  15. Direct power control of DFIG based on discrete space vector modulation

    Energy Technology Data Exchange (ETDEWEB)

    Verij Kazemi, Mohammad; Sadeghi Yazdankhah, Ahmad; Madadi Kojabadi, Hossein [Electrical Engineering Department, Sahand University of Technology, Tabriz (Iran)

    2010-05-15

    This paper presents a new direct power control (DPC) strategy for a double fed induction generator (DFIG) based wind energy generation system. Switching vectors for rotor side converter were selected from the optimal switching table using the estimated stator flux position and the errors of the active and reactive power. A few number of voltage vectors may cause undesired power and stator current ripple. In this paper the increased number of voltage vectors with application of the Discrete Space Vector Modulation (DSVM) will be presented. Then a new switching table in supersynchronous and subsynchronous frames will be proposed. Simulation results of a 2 MW DFIG system demonstrate the effectiveness and robustness of the proposed control strategy during variations of active and reactive power, machine parameters, and wind speed. (author)

  16. A versatile bacterial expression vector based on the synthetic biology plasmid pSB1.

    Science.gov (United States)

    Skrlj, Nives; Erculj, Nina; Dolinar, Marko

    2009-04-01

    We have developed an Escherichia coli expression vector that is particularly useful for construction and production of fusion proteins. Based on the synthetic biology pSB1C3 platform, the resulting vector offers a combination of useful features: the strong T7 promoter combined with lac operator, OmpA signal sequence, a selection of cloning sites located at convenient positions and a 3'-terminal His-10 tag. Each of these regions is flanked by a restriction site that allows for easy vector modification, including removal of the signal sequence without perturbation of the reading frame. All the elements were assembled by stepwise addition of three cassettes for which the design was made de novo. To prove the efficiency of the new vector, named pMD204, we successfully produced a cysteine proteinase inhibitor variant in the periplasm and in the cytoplasm of E. coli, in both cases as a soluble and active protein. PMID:19027858

  17. Space vector-based analysis of overmodulation in triangle-comparison based PWM for voltage source inverter

    Indian Academy of Sciences (India)

    Manoj Kumar Modi; S Venugopal; G Narayanan

    2013-06-01

    The equivalence of triangle-comparison-based pulse width modulation (TCPWM) and space vector based PWM (SVPWM) during linear modulation is well-known. This paper analyses triangle-comparison based PWM techniques (TCPWM) such as sine-triangle PWM (SPWM) and common-mode voltage injection PWM during overmodulation from a space vector point of view. The average voltage vector produced by TCPWM during overmodulation is studied in the stationary (a–b) reference frame. This is compared and contrasted with the average voltage vector corresponding to the well-known standard two-zone algorithm for space vector modulated inverters. It is shown that the two-zone overmodulation algorithm itself can be derived from the variation of average voltage vector with TCPWM. The average voltage vector is further studied in a synchronously revolving (d-q) reference frame. The RMS value of low-order voltage ripple can be estimated, and can be used to compare harmonic distortion due to different PWM methods during overmodulation. The measured values of the total harmonic distortion (THD) in the line currents are presented at various fundamental frequencies. The relative values of measured current THD pertaining to different PWM methods tally with those of analytically evaluated RMS voltage ripple.

  18. A replication competent lentivirus (RCL) assay for equine infectious anaemia virus (EIAV)-based lentiviral vectors.

    Science.gov (United States)

    Miskin, J; Chipchase, D; Rohll, J; Beard, G; Wardell, T; Angell, D; Roehl, H; Jolly, D; Kingsman, S; Mitrophanous, K

    2006-02-01

    Lentiviral vectors are being developed to satisfy a wide range of currently unmet medical needs. Vectors destined for clinical evaluation have been rendered multiply defective by deletion of all viral coding sequences and nonessential cis-acting sequences from the transfer genome. The viral envelope and accessory proteins are excluded from the production system. The vectors are produced from separate expression plasmids that are designed to minimize the potential for homologous recombination. These features ensure that the regeneration of the starting virus is impossible. It is a regulatory requirement to confirm the absence of any replication competent virus, so we describe here the development and validation of a replication competent lentivirus (RCL) assay for equine infectious anaemia virus (EIAV)-based vectors. The assay is based on the guidelines developed for testing retroviral vectors, and uses the F-PERT (fluorescent-product enhanced reverse transcriptase) assay to test for the presence of a transmissible reverse transcriptase. We have empirically modelled the replication kinetics of an EIAV-like entity in human cells and devised an amplification protocol by comparison with a replication competent MLV. The RCL assay has been validated at the 20 litre manufacturing scale, during which no RCL was detected. The assay is theoretically applicable to any lentiviral vector and pseudotype combination. PMID:16208418

  19. Vector perturbation based adaptive distributed precoding scheme with limited feedback for CoMP systems

    Directory of Open Access Journals (Sweden)

    Cuthbert Laurie

    2011-01-01

    Full Text Available Abstract A downlink adaptive distributed precoding scheme is proposed for coordinated multi-point (CoMP transmission systems. The serving base station (BS obtains the optimal precoding vector via user feedback. Meanwhile, the precoding vector of each coordinated BS is determined by adaptive gradient iteration according to the perturbation vector and the adjustment factor based on the vector perturbation method. In each transmission frame, the CoMP user feeds the precoding matrix index back to the serving BS, and feeds back the adjustment factor index to the coordinated BSs, which can reduce the uplink feedback overhead. The selected adjustment factor for each coordinated BS is obtained via the precoding vector of the coordinated BS used in the previous frame and the preferred precoding vector of the serving BS in this frame. The proposed scheme takes advantage of the spatial non-correlation and temporal correlation of the distributed MIMO channel. The design of the adjustment factor set is given and the channel feedback delay is considered. The system performance of the proposed scheme is verified with and without feedback delay respectively and the system feedback overhead is analyzed. Simulation results show that the proposed scheme has a good trade-off between system performance and the system control information overhead on feedback.

  20. Direct Time-Domain-Based Approach for Study of Space-Vector Pulsewidth Modulation

    DEFF Research Database (Denmark)

    Oleschuk, V.; Blaabjerg, Frede; Stankovic, A.M.

    Direct time-do main-based approach, which is characterized by the simplicity and clarity, is proposed for the study and design of space-vector based methods of pulsewidth modulation (PWM) for standard voltage source inverters for adjustable speed motor drives. This approach is based on the detailed...... consideration of switching state sequences of three-phase inverter (with the corresponding duty-cycles), which are integrated characteristics of space vector PWM schemes and versions. It also permits providing of synchronization of output voltage waveforms and improvement of computational effectiveness of...

  1. Cloning and stable maintenance of DNA fragments over 300 kb in Escherichia coli with conventional plasmid-based vectors.

    OpenAIRE

    Tao, Q.; Zhang, H. B.

    1998-01-01

    Bacterial artificial chromosome (BAC) and P1-derived artificial chromosome (PAC) systems were previously developed for cloning of very large eukaryotic DNA fragments in bacteria. We report the feasibility of cloning very large fragments of eukaryotic DNA in bacteria using conventional plasmid-based vectors. One conventional plasmid vector (pGEM11), one conventional binary plasmid vector (pSLJ1711) and one conventional binary cosmid vector (pCLD04541) were investigated using the widely used BA...

  2. Opportunities for Improved Chagas Disease Vector Control Based on Knowledge, Attitudes and Practices of Communities in the Yucatan Peninsula, Mexico

    OpenAIRE

    Kathryn Rosecrans; Gabriela Cruz-Martin; Ashley King; Eric Dumonteil

    2014-01-01

    BACKGROUND: Chagas disease is a vector-borne parasitic disease of major public health importance. Current prevention efforts are based on triatomine vector control to reduce transmission to humans. Success of vector control interventions depends on their acceptability and value to affected communities. We aimed to identify opportunities for and barriers to improved vector control strategies in the Yucatan peninsula, Mexico. METHODOLOGY/PRINCIPAL FINDINGS: We employed a sequence of qualitative...

  3. Small-time scale network traffic prediction based on a local support vector machine regression model

    Institute of Scientific and Technical Information of China (English)

    Meng Qing-Fang; Chen Yue-Hui; Peng Yu-Hua

    2009-01-01

    In this paper we apply the nonlinear time series analysis method to small-time scale traffic measurement data. The prediction-based method is used to determine the embedding dimension of the traffic data. Based on the reconstructed phase space, the local support vector machine prediction method is used to predict the traffic measurement data, and the BIC-based neighbouring point selection method is used to choose the number of the nearest neighbouring points for the local support vector machine regression model. The experimental results show that the local support vector machine prediction method whose neighbouring points are optimized can effectively predict the small-time scale traffic measurement data and can reproduce the statistical features of real traffic measurements.

  4. The generation of arbitrary vector beams using a division of a wavefront-based setup

    Science.gov (United States)

    Kalita, Ranjan; Gaffar, Md; Boruah, Bosanta R.

    2016-07-01

    In this paper, we introduce an arbitrary vector-beam-forming scheme using a simple arrangement involving only one liquid crystal spatial light modulator. An arbitrary vector beam can be obtained by overlapping two orthogonally polarized beams. In most of the existing vector-beam-forming schemes the two orthogonally polarized beams are essentially copies of a single incident wavefront. However, in the proposed scheme the two orthogonally polarized beams correspond to two separated parts of a single incident wavefront. Taking a cue from the two-beam interference phenomenon, the present scheme can be referred to as a division of a wavefront-based scheme. The proposed setup offers certain important advantages and is more suitable for the generation of higher average-power vector beams. We demonstrate the working of the vector-beam-forming scheme by generating various vector beams such as radially polarized, azimuthally polarized, and Bessel–Gauss beams and also a boat-shaped beam in the focal volume of a low-numerical-aperture focusing lens. The boat-shaped beam comprises a dark center surrounded by intense light from all but one direction. The beam is realized at the focus of an azimuthally polarized beam in the presence of a moderate amount of coma in the beam. The experimental results obtained using the proposed setup are verified by comparing them with the theoretical results.

  5. Development of avian sarcoma and leukosis virus-based vector-packaging cell lines

    Energy Technology Data Exchange (ETDEWEB)

    Stoker, A.W.; Bissell, M.J. (Univ. of California, Berkeley (USA))

    1988-03-01

    The authors have constructed an avian leukosis virus derivative with a 5{prime} deletion extending from within the tRNA primer binding site to a SacI site in the leader region. The aim was to remove cis-acting replicative and/or encapsidation sequences and to use this derivative, RAV-1{Psi}{sup {minus}}, to develop vector-packaging cell lines. They show that RAV-1{Psi}{sup {minus}} can be stably expressed in the quail cell line QT6 and chicken embryo fibroblasts and that it is completely replication deficient in both cell types. Moreover, they have demonstrated that QT6-derived lines expressing RAV-1{Psi}{sup {minus}} can efficiently package four structurally different replication-defective v-src expression vectors into infectious virus, with very low or undetectable helper virus release. These RAV-{Psi}{sup {minus}}-expressing cell lines comprise the first prototype avian sarcoma and leukosis virus-based vector-packaging system. The construction of our vectors has also shown us that a sequence present within gag, thought to facilitate virus packaging, is not necessary for efficient vector expression and high virus production. They show that quantitation and characterization of replication-defective viruses can be achieved with a sensitive immunocytochemical procedure, presenting an alternative to internal selectable vector markers.

  6. Optical mass-storage based on vector wave holography

    Science.gov (United States)

    Yatagai, Toyohiko; Barada, Daisuke

    2013-06-01

    Holographic data storage based on polarization techniques is proposed. Angular and shift multiplexing techniques, as well as polarization multiplexing, are developed to increase storage capacity. Some experimental results are presented.

  7. Model based wind vector field reconstruction from lidar data

    OpenAIRE

    Schlipf, David; Rettenmeier, Andreas; Haizmann, Florian; Hofsäß, Martin; Courtney, Mike; Cheng, Po Wen

    2012-01-01

    In recent years lidar technology found its way into wind energy for resource assessment and control. For both fields of application it is crucial to reconstruct the wind field from the limited information provided by a lidar system. For lidar assisted wind turbine control model based wind field reconstruction is used to obtain signals from wind characteristics such as wind speed, direction and shears in a high temporal resolution. This work shows how these methods can be used for lidar based ...

  8. Numerical Characterisation of Jet-Vane based Thrust Vector Control Systems

    Directory of Open Access Journals (Sweden)

    M.S.R. Chandra Murthy

    2015-07-01

    Full Text Available Computational fluid dynamics methodology was used in characterising jet vane based thrust vector control systems of tactical missiles. Three-dimensional Reynolds Averaged Navier-Stokes equations were solved along with two-equation turbulence model for different operating conditions. Nonlinear regression analysis was applied to the detailed CFD database to evolve a mathematical model for the thrust vector control system. The developed model was validated with series of ground based 6-Component static tests. The proven methodology is applied toa new configuration.Defence Science Journal, Vol. 65, No. 4, July 2015, pp. 261-264, DOI: http://dx.doi.org/10.14429/dsj.65.7960

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

    OpenAIRE

    Guixia He; Jiaquan Gao

    2016-01-01

    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 ...

  10. Hybrid Asymmetric Space Vector Modulation for inverter based direct torque control induction motor drive

    Directory of Open Access Journals (Sweden)

    Nandakumar Sundararaju

    2014-05-01

    Full Text Available This paper proposes novel hybrid asymmetric space vector modulation technique for inverter operated direct torque control induction motor drive. The hybridization process is performed by the combination of continuous asymmetric space vector modulation pulse width technique (ASVPWM and fuzzy operated discontinuous ASVPWM technique. Combination process is based on pulse mismatching technique. Pulse mismatching technique helps to reduce the active region of the switch. Finally, optimal pulses are applied to control the inverter. The optimal hybrid pulse condense switching losses of the inverter and also improves the operating performance of the direct torque control (DTC based drive system like smooth dynamic response in speed reversal, minimum torque error, settling time of speed. Simulation results of proposed hybrid asymmetric space vector pulse width modulation technique to direct torque control (HASVPWM-DTC approach has been carried out by using Matlab-Simulink environment.

  11. 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 vector and for assessing uncertainties, dense topographic constraints alone were not sufficient to significantly narrow the wide (vector orientations that resulted from accounting for epistemic uncertainties.

  12. Acoustic Event Detection Based on MRMR Selected Feature Vectors

    OpenAIRE

    VOZARIKOVA Eva; Juhar, Jozef; CIZMAR Anton

    2012-01-01

    This paper is focused on the detection of potentially dangerous acoustic events such as gun shots and breaking glass in the urban environment. Various feature extraction methods can be used forrepresenting the sound in the detection system based on Hidden Markov Models of acoustic events. Mel – frequency cepstral coefficients, low - level descriptors defined in MPEG-7 standard and another time andspectral features were considered in the system. For the selection of final subset of features Mi...

  13. Image Replica Detection based on Binary Support Vector Classifier

    OpenAIRE

    Maret, Y.; Dufaux, F.; Ebrahimi, T.

    2005-01-01

    In this paper, we present a system for image replica detection. More specifically, the technique is based on the extraction of 162 features corresponding to texture, color and gray-level characteristics. These features are then weighted and statistically normalized. To improve training and performances, the features space dimensionality is reduced. Lastly, a decision function is generated to classify the test image as replica or non-replica of a given reference image. Experimental results sho...

  14. Support Vector Machine Based on Adaptive Acceleration Particle Swarm Optimization

    OpenAIRE

    2014-01-01

    Existing face recognition methods utilize particle swarm optimizer (PSO) and opposition based particle swarm optimizer (OPSO) to optimize the parameters of SVM. However, the utilization of random values in the velocity calculation decreases the performance of these techniques; that is, during the velocity computation, we normally use random values for the acceleration coefficients and this creates randomness in the solution. To address this problem, an adaptive acceleration particle swarm opt...

  15. Support vector machine based on adaptive acceleration particle swarm optimization.

    Science.gov (United States)

    Abdulameer, Mohammed Hasan; Sheikh Abdullah, Siti Norul Huda; Othman, Zulaiha Ali

    2014-01-01

    Existing face recognition methods utilize particle swarm optimizer (PSO) and opposition based particle swarm optimizer (OPSO) to optimize the parameters of SVM. However, the utilization of random values in the velocity calculation decreases the performance of these techniques; that is, during the velocity computation, we normally use random values for the acceleration coefficients and this creates randomness in the solution. To address this problem, an adaptive acceleration particle swarm optimization (AAPSO) technique is proposed. To evaluate our proposed method, we employ both face and iris recognition based on AAPSO with SVM (AAPSO-SVM). In the face and iris recognition systems, performance is evaluated using two human face databases, YALE and CASIA, and the UBiris dataset. In this method, we initially perform feature extraction and then recognition on the extracted features. In the recognition process, the extracted features are used for SVM training and testing. During the training and testing, the SVM parameters are optimized with the AAPSO technique, and in AAPSO, the acceleration coefficients are computed using the particle fitness values. The parameters in SVM, which are optimized by AAPSO, perform efficiently for both face and iris recognition. A comparative analysis between our proposed AAPSO-SVM and the PSO-SVM technique is presented. PMID:24790584

  16. Support Vector Machine Based on Adaptive Acceleration Particle Swarm Optimization

    Directory of Open Access Journals (Sweden)

    Mohammed Hasan Abdulameer

    2014-01-01

    Full Text Available Existing face recognition methods utilize particle swarm optimizer (PSO and opposition based particle swarm optimizer (OPSO to optimize the parameters of SVM. However, the utilization of random values in the velocity calculation decreases the performance of these techniques; that is, during the velocity computation, we normally use random values for the acceleration coefficients and this creates randomness in the solution. To address this problem, an adaptive acceleration particle swarm optimization (AAPSO technique is proposed. To evaluate our proposed method, we employ both face and iris recognition based on AAPSO with SVM (AAPSO-SVM. In the face and iris recognition systems, performance is evaluated using two human face databases, YALE and CASIA, and the UBiris dataset. In this method, we initially perform feature extraction and then recognition on the extracted features. In the recognition process, the extracted features are used for SVM training and testing. During the training and testing, the SVM parameters are optimized with the AAPSO technique, and in AAPSO, the acceleration coefficients are computed using the particle fitness values. The parameters in SVM, which are optimized by AAPSO, perform efficiently for both face and iris recognition. A comparative analysis between our proposed AAPSO-SVM and the PSO-SVM technique is presented.

  17. Scale-Invariance of Support Vector Machines based on the Triangular Kernel

    OpenAIRE

    Sahbi, Hichem; Fleuret, François

    2002-01-01

    This report focuses on the scale-invariance and the good performances of Support Vector Machines based on the triangular kernel. After a mathematica- l analysis of the scale-invariance of learning with that kernel, we illustrate its behavior with a simple 2D classification problem and compare its performances to those of a Gaussian kernel on face detection and handwritten character recognition

  18. Yeast recombination-based cloning as an efficient way of constructing vectors for Zymoseptoria tritici

    OpenAIRE

    Kilaru, S.; Steinberg, G.

    2015-01-01

    Highlights • Yeast recombination-based cloning (YRBC) is a reliable and inexpensive way of generating plasmids. • We provide 4 vectors for YRBC that a cover different resistance genes. • Using this technique promises rapid generation of molecular tools to study Z. tritici.

  19. Factors Affecting Learning of Vector Math from Computer-Based Practice: Feedback Complexity and Prior Knowledge

    Science.gov (United States)

    Heckler, Andrew F.; Mikula, Brendon D.

    2016-01-01

    In experiments including over 450 university-level students, we studied the effectiveness and time efficiency of several levels of feedback complexity in simple, computer-based training utilizing static question sequences. The learning domain was simple vector math, an essential skill in introductory physics. In a unique full factorial design, we…

  20. Energy-saving technology of vector controlled induction motor based on the adaptive neuro-controller

    Science.gov (United States)

    Engel, E.; Kovalev, I. V.; Karandeev, D.

    2015-10-01

    The ongoing evolution of the power system towards a Smart Grid implies an important role of intelligent technologies, but poses strict requirements on their control schemes to preserve stability and controllability. This paper presents the adaptive neuro-controller for the vector control of induction motor within Smart Gird. The validity and effectiveness of the proposed energy-saving technology of vector controlled induction motor based on adaptive neuro-controller are verified by simulation results at different operating conditions over a wide speed range of induction motor.

  1. 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.

  2. Space Vector Based Generalized Dpwm Algorithms for Vsi Fed Induction Motor Drive

    Directory of Open Access Journals (Sweden)

    N. Praveena

    2013-09-01

    Full Text Available This paper presents Space Vector based Generalized DiscontinuousPulse width modulation (GDPWM algorithms for VSI fed Induction motor drive. To avoid the complexity due to angle calculation and sector identification involved in Conventional space vector pulse width modulation (CSVPWM. The Proposed algorithms use the concept of Imaginary Switching times and a constant variable µ and modulation phase angle δ are used to generate modulating waveforms.The proposed algorithms results in reduced current ripple over CSVPWM. To validate the proposed methods, simulation is carried on V/f controlled Induction Motor drive in MATLAB/SIMULINK environment and the results are discussed.

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

    Science.gov (United States)

    Kumar, Manoj; Dutta, S.; Pal, Ramjay; Jain, K. K.; Gupta, Sudha; Bhan, R. K.

    2016-04-01

    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.

  4. Production of Retrovirus-Based Vectors in Mildly Acidic pH Conditions.

    Science.gov (United States)

    Holic, Nathalie; Fenard, David

    2016-01-01

    Gene transfer vectors based on retroviridae are increasingly becoming a tool of choice for biomedical research and for the development of biotherapies in rare diseases or cancers. To meet the challenges of preclinical and clinical production, different steps of the production process of self-inactivating γ-retroviral (RVs) and lentiviral vectors (LVs) have been improved (e.g., transfection, media optimization, cell culture conditions). However, the increasing need for mass production of such vectors is still a challenge and could hamper their availability for therapeutic use. Recently, we observed that the use of a neutral pH during vector production is not optimal. The use of mildly acidic pH conditions (pH 6) can increase by two- to threefold the production of RVs and LVs pseudotyped with the vesicular stomatitis virus G (VSV-G) or gibbon ape leukemia virus (GALV) glycoproteins. Here, we describe the production protocol in mildly acidic pH conditions of GALVTR- and VSV-G-pseudotyped LVs using the transient transfection of HEK293T cells and the production protocol of GALV-pseudotyped RVs produced from a murine producer cell line. These protocols should help to achieve higher titers of vectors, thereby facilitating experimental research and therapeutic applications. PMID:27317171

  5. VGSC: A Web-Based Vector Graph Toolkit of Genome Synteny and Collinearity.

    Science.gov (United States)

    Xu, Yiqing; Bi, Changwei; Wu, Guoxin; Wei, Suyun; Dai, Xiaogang; Yin, Tongming; Ye, Ning

    2016-01-01

    Background. In order to understand the colocalization of genetic loci amongst species, synteny and collinearity analysis is a frequent task in comparative genomics research. However many analysis software packages are not effective in visualizing results. Problems include lack of graphic visualization, simple representation, or inextensible format of outputs. Moreover, higher throughput sequencing technology requires higher resolution image output. Implementation. To fill this gap, this paper publishes VGSC, the Vector Graph toolkit of genome Synteny and Collinearity, and its online service, to visualize the synteny and collinearity in the common graphical format, including both raster (JPEG, Bitmap, and PNG) and vector graphic (SVG, EPS, and PDF). Result. Users can upload sequence alignments from blast and collinearity relationship from the synteny analysis tools. The website can generate the vector or raster graphical results automatically. We also provide a java-based bytecode binary to enable the command-line execution. PMID:27006949

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

    International Nuclear Information System (INIS)

    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.

  7. Research on Amplifier Performance Evaluation Based on δ-Support Vector Regression

    Directory of Open Access Journals (Sweden)

    Xing Huo

    2014-01-01

    Full Text Available Focusing on the amplifier performance evaluation demand, a novel evaluation strategy based on δ-support vector regression (δ-SVR is proposed in this paper. Lower computer calculation demand is considered firstly. And this is dealt with by the superiority of δ-SVR which can be significantly improved on the number of support vectors. Moreover, the function of δ-SVR employs the modified RBF kernel function which is constructed from an original kernel by removing the last coordinate and adding the linear term with the last coordinate. Experiment adopted the typical circuit Sallen-Key low pass filter to prove the proposed evaluation strategy via the eight performance indexes. Simulation results reveal that the need of the number of δ-SVR support vectors is the lowest among the other two methods LSSVR and ε-SVR under obtaining nearly the same evaluation result. And this is also suitable for promotion computational speed.

  8. Alternative-splicing-based bicistronic vectors for ratio-controlled protein expression and application to recombinant antibody production.

    OpenAIRE

    Fallot, Stéphanie; Ben Naya, Raouia; Hieblot, Corinne; Mondon, Philippe; Lacazette, Eric; Bouayadi, Khalil; Kharrat, Abdelhakim; Touriol, Christian; Prats, Hervé

    2009-01-01

    In the last decade polycistronic vectors have become essential tools for both basic science and gene therapy applications. In order to co-express heterologous polypeptides, different systems have been developed from Internal Ribosome Entry Site (IRES) based vectors to the use of the 2A peptide. Unfortunately, these methods are not fully suitable for the efficient and reproducible modulation of the ratio between the proteins of interest. Here we describe a novel bicistronic vector type based o...

  9. HADOOP-BASED DISTRIBUTED SYSTEM FOR ONLINE PREDICTION OF AIR POLLUTION BASED ON SUPPORT VECTOR MACHINE

    Directory of Open Access Journals (Sweden)

    Z. Ghaemi

    2015-12-01

    Full Text Available The critical impact of air pollution on human health and environment in one hand and the complexity of pollutant concentration behavior in the other hand lead the scientists to look for advance techniques for monitoring and predicting the urban air quality. Additionally, recent developments in data measurement techniques have led to collection of various types of data about air quality. Such data is extremely voluminous and to be useful it must be processed at high velocity. Due to the complexity of big data analysis especially for dynamic applications, online forecasting of pollutant concentration trends within a reasonable processing time is still an open problem. The purpose of this paper is to present an online forecasting approach based on Support Vector Machine (SVM to predict the air quality one day in advance. In order to overcome the computational requirements for large-scale data analysis, distributed computing based on the Hadoop platform has been employed to leverage the processing power of multiple processing units. The MapReduce programming model is adopted for massive parallel processing in this study. Based on the online algorithm and Hadoop framework, an online forecasting system is designed to predict the air pollution of Tehran for the next 24 hours. The results have been assessed on the basis of Processing Time and Efficiency. Quite accurate predictions of air pollutant indicator levels within an acceptable processing time prove that the presented approach is very suitable to tackle large scale air pollution prediction problems.

  10. Hadoop-Based Distributed System for Online Prediction of Air Pollution Based on Support Vector Machine

    Science.gov (United States)

    Ghaemi, Z.; Farnaghi, M.; Alimohammadi, A.

    2015-12-01

    The critical impact of air pollution on human health and environment in one hand and the complexity of pollutant concentration behavior in the other hand lead the scientists to look for advance techniques for monitoring and predicting the urban air quality. Additionally, recent developments in data measurement techniques have led to collection of various types of data about air quality. Such data is extremely voluminous and to be useful it must be processed at high velocity. Due to the complexity of big data analysis especially for dynamic applications, online forecasting of pollutant concentration trends within a reasonable processing time is still an open problem. The purpose of this paper is to present an online forecasting approach based on Support Vector Machine (SVM) to predict the air quality one day in advance. In order to overcome the computational requirements for large-scale data analysis, distributed computing based on the Hadoop platform has been employed to leverage the processing power of multiple processing units. The MapReduce programming model is adopted for massive parallel processing in this study. Based on the online algorithm and Hadoop framework, an online forecasting system is designed to predict the air pollution of Tehran for the next 24 hours. The results have been assessed on the basis of Processing Time and Efficiency. Quite accurate predictions of air pollutant indicator levels within an acceptable processing time prove that the presented approach is very suitable to tackle large scale air pollution prediction problems.

  11. A comparative study on change vector analysis based change detection techniques

    Indian Academy of Sciences (India)

    Sartajvir Singh; Rajneesh Talwar

    2014-12-01

    Detection of Earth surface changes are essential to monitor regional climatic, snow avalanche hazard analysis and energy balance studies that occur due to air temperature irregularities. Geographic Information System (GIS) enables such research activities to be carried out through change detection analysis. From this viewpoint, different change detection algorithms have been developed for land-use land-cover (LULC) region. Among the different change detection algorithms, change vector analysis (CVA) has level headed capability of extracting maximuminformation in terms of overall magnitude of change and the direction of change between multispectral bands from multi-temporal satellite data sets. Since past two–three decades, many effective CVA based change detection techniques e.g., improved change vector analysis (ICVA), modified change vector analysis (MCVA) and change vector analysis posterior-probability space (CVAPS), have been developed to overcome the difficulty that exists in traditional change vector analysis (CVA). Moreover, many integrated techniques such as cross correlogram spectral matching (CCSM) based CVA. CVA uses enhanced principal component analysis (PCA) and inverse triangular (IT) function, hyper-spherical direction cosine (HSDC), and median CVA (m-CVA), as an effective LULC change detection tools. This paper comprises a comparative analysis on CVA based change detection techniques such as CVA, MCVA, ICVA and CVAPS. This paper also summarizes the necessary integrated CVA techniques along with their characteristics, features and shortcomings. Based on experiment outcomes, it has been evaluated that CVAPS technique has greater potential than other CVA techniques to evaluate the overall transformed information over three differentMODerate resolution Imaging Spectroradiometer (MODIS) satellite data sets of different regions. Results of this study are expected to be potentially useful for more accurate analysis of LULC changes which will, in turn

  12. 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.

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

    OpenAIRE

    Mushtaq, M. T.; Khan, I.; M. S. Khan; Koudelka, O.

    2015-01-01

    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 success...

  14. Bluetongue disease risk assessment based on observed and projected Culicoides obsoletus spp. vector densities.

    Directory of Open Access Journals (Sweden)

    Katharina Brugger

    Full Text Available Bluetongue is an arboviral disease of ruminants causing significant economic losses. Our risk assessment is based on the epidemiological key parameter, the basic reproduction number. It is defined as the number of secondary cases caused by one primary case in a fully susceptible host population, in which values greater than one indicate the possibility, i.e., the risk, for a major disease outbreak. In the course of the Bluetongue virus serotype 8 (BTV-8 outbreak in Europe in 2006 we developed such a risk assessment for the University of Veterinary Medicine Vienna, Austria. Basic reproduction numbers were calculated using a well-known formula for vector-borne diseases considering the population densities of hosts (cattle and small ruminants and vectors (biting midges of the Culicoides obsoletus spp. as well as temperature dependent rates. The latter comprise the biting and mortality rate of midges as well as the reciprocal of the extrinsic incubation period. Most important, but generally unknown, is the spatio-temporal distribution of the vector density. Therefore, we established a continuously operating daily monitoring to quantify the seasonal cycle of the vector population by a statistical model. We used cross-correlation maps and Poisson regression to describe vector densities by environmental temperature and precipitation. Our results comprise time series of observed and simulated Culicoides obsoletus spp. counts as well as basic reproduction numbers for the period 2009-2011. For a spatio-temporal risk assessment we projected our results from the location of Vienna to the entire region of Austria. We compiled both daily maps of vector densities and the basic reproduction numbers, respectively. Basic reproduction numbers above one were generally found between June and August except in the mountainous regions of the Alps. The highest values coincide with the locations of confirmed BTV cases.

  15. Can community-based integrated vector control hasten the process of LF elimination?

    Science.gov (United States)

    Sunish, I P; Kalimuthu, M; Kumar, V Ashok; Munirathinam, A; Nagaraj, J; Tyagi, B K; White, Graham B; Arunachalam, N

    2016-06-01

    Community-based integrated vector control (IVC) using polystyrene beads (EPS) and pyrethroid impregnated curtains (PIC) as an adjunct to mass drug administration (MDA) was implemented for lymphatic filariasis elimination, in the filaria endemic villages of Tirukoilur, south India. In all the villages, MDA was carried out by the state health machinery, as part of the national filariasis elimination programme. Thirty-six difficult-to-control villages were grouped as, viz, MDA alone, MDA + EPS and MDA + EPS + PIC arms. Implementation and monitoring of IVC was carried out by the community. After 3 years of IVC, higher reductions in filariometric indices were observed in both the community and vector population. Decline in antigenaemia prevalence was higher in MDA + IVC as compared to MDA alone arm. Vector density dropped significantly (P < 0.05) in both the IVC arms, and nil transmission was observed during post-IVC period. Almost 53.8 and 75.8 % of the cesspits in MDA + EPS and MDA + EPS + PIC arms were closed by the householders, due to the enhanced awareness on vector breeding. The paper presents the key elements of IVC implementation through social mobilization in a LF prevalent area. Thus, community-based IVC strategy can hasten LF elimination, as it reduced the transmission and filariometric indices significantly. Indices were maintained at low level with nil transmission, by the community through IVC tools. PMID:26969179

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

    International Nuclear Information System (INIS)

    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)

  17. Yeast recombination-based cloning as an efficient way of constructing vectors for Zymoseptoria tritici.

    Science.gov (United States)

    Kilaru, S; Steinberg, G

    2015-06-01

    Many pathogenic fungi are genetically tractable. Analysis of their cellular organization and invasion mechanisms underpinning virulence determinants profits from exploiting such molecular tools as fluorescent fusion proteins or conditional mutant protein alleles. Generation of these tools requires efficient cloning methods, as vector construction is often a rate-limiting step. Here, we introduce an efficient yeast recombination-based cloning (YRBC) method to construct vectors for the fungus Zymoseptoria tritici. This method is of low cost and avoids dependency on the availability of restriction enzyme sites in the DNA sequence, as needed in more conventional restriction/ligation-based cloning procedures. Furthermore, YRBC avoids modification of the DNA of interest, indeed this potential risk limits the use of site-specific recombination systems, such as Gateway cloning. Instead, in YRBC, multiple DNA fragments, with 30bp overlap sequences, are transformed into Saccharomyces cerevisiae, whereupon homologous recombination generates the vector in a single step. Here, we provide a detailed experimental protocol and four vectors, each encoding a different dominant selectable marker cassette, that enable YRBC of constructs to be used in the wheat pathogen Z. tritici. PMID:26092792

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

    International Nuclear Information System (INIS)

    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)

  19. Viral vector-based reversible neuronal inactivation and behavioral manipulation in the macaque monkey

    Directory of Open Access Journals (Sweden)

    Kristina Juliane Nielsen

    2012-06-01

    Full Text Available Viral vectors are promising tools for the dissection of neural circuits. In principle, they can manipulate neurons at a level of specificity not otherwise achievable. While many studies have used viral vector-based approaches in the rodent brain, only a few have employed this technique in the non-human primate, despite the importance of this animal model for neuroscience research. Here, we report for the first time that a viral vector-based approach can be used to manipulate a monkey’s behavior in a task. For this purpose, we used the allatostatin receptor/allatostatin (AlstR/AL system, which has previously been shown to allow inactivation of neurons in vivo. The AlstR was expressed in neurons in monkey V1 by injection of an AAV1 vector. Two monkeys were trained in a detection task, in which they had to make a saccade to a faint peripheral target. Injection of AL caused a retinotopic deficit in the detection task in one monkey. Specifically, the monkey showed marked impairment for detection targets placed at the visual field location represented at the virus injection site, but not for targets shown elsewhere. We confirmed that these deficits indeed were due to the interaction of AlstR and AL by injecting saline, or AL at a V1 location without AlstR expression. Post-mortem histology confirmed AlstR expression in this monkey. We failed to replicate the behavioral results in a second monkey, as AL injection did not impair the second monkey’s performance in the detection task. However, post-mortem histology revealed a very low level of AlstR expression in this monkey. Our results demonstrate that viral vector-based approaches can produce effects strong enough to influence a monkey’s performance in a behavioral task, supporting the further development of this approach for studying how neuronal circuits control complex behaviors in non-human primates.

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

    International Nuclear Information System (INIS)

    Based on the interdependent relationship between fission neutrons (252Cf) and fission chain (235U 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 252Cf 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)

  1. Vector quantization based on a psychovisual lattice for a visual subband coding scheme

    Science.gov (United States)

    Senane, Hakim; Saadane, Abdelhakim; Barba, Dominique

    1997-01-01

    A vector quantization based on a psychovisual lattice is used in a visual components image coding scheme to achieve a high compression ratio with an excellent visual quality. The vectors construction methodology preserves the main properties of the human visual system concerning the perception of quantization impairments and takes into account the masking effect due to interaction between subbands with the same radial frequency but with different orientations. The vectors components are the local band limited contrasts Cij defined as the ratio between the luminance Lij at point, which belongs to the radial subband i and angular sector j, and the average luminance at this location corresponding to the radial frequencies up to subband i-1. Hence the vectors dimension is depending on the orientation selectivity of the chosen decomposition. The low pass subband, which is nondirectional is scalar quantized. The performances of the coding scheme have been evaluated on a set of images in terms of peak SNR, true bit rates and visual quality. For this, no impairments are visible at a distance of 4 times the height of a high quality TV monitor. The SNR are about 6 to 8 dB under the ones of classical subband image coding schemes when producing the same visual quality. Due to the use of the local band limited contrast, the particularity of this approach relies in the structure of the reconstruction image error which is found to be highly correlated to the structure of the original image.

  2. A Parallel Decision Model Based on Support Vector Machines and Its Application to Fault Diagnosis

    Institute of Scientific and Technical Information of China (English)

    Yan Weiwu(阎威武); Shao Huihe

    2004-01-01

    Many industrial process systems are becoming more and more complex and are characterized by distributed features. To ensure such a system to operate under working order, distributed parameter values are often inspected from subsystems or different points in order to judge working conditions of the system and make global decisions. In this paper, a parallel decision model based on Support Vector Machine (PDMSVM) is introduced and applied to the distributed fault diagnosis in industrial process. PDMSVM is convenient for information fusion of distributed system and it performs well in fault diagnosis with distributed features. PDMSVM makes decision based on synthetic information of subsystems and takes the advantage of Support Vector Machine. Therefore decisions made by PDMSVM are highly reliable and accurate.

  3. Minimum Distortion Direction Prediction-based Fast Half-pixel Motion Vector Search Algorithm

    Institute of Scientific and Technical Information of China (English)

    DONG Hai-yan; ZHANG Qi-shan

    2005-01-01

    A minimum distortion direction prediction-based novel fast half-pixel motion vector search algorithm is proposed, which can reduce considerably the computation load of half-pixel search. Based on the single valley characteristic of half-pixel error matching function inside search grid, the minimum distortion direction is predicted with the help of comparative results of sum of absolute difference(SAD) values of four integer-pixel points around integer-pixel motion vector. The experimental results reveal that, to all kinds of video sequences, the proposed algorithm can obtain almost the same video quality as that of the half-pixel full search algorithm with a decrease of computation cost by more than 66%.

  4. Efficient production of transgenic chickens using self-inactive HIV-based lentiviral vectors

    Institute of Scientific and Technical Information of China (English)

    Shiyong XU; Yan SUN; Hongmei DING; Meng WANG; Yafei CAI; Jie CHEN; Honglin LIU

    2009-01-01

    We demonstrated the simple and effective production of transgenic chickens, in which the enhanced green fluorescence protein (EGFP) was expressed by using third-generation self-inactive HIV-based lentiviral vectors. In our experiments, lentiviruses were injected into 204 fertilized eggs, from which 30 ( 15% ) chickens were hatched. The exogenous gene was detected in the genomes of 16 out of 30 (53%) chickens. The green fluorescence signal was observed directly in various body parts, and was particularly significant in the testes. The transgenes were also found in the offspring of these chickens. The results indicate that HIV-based lentivirul vectors can be used to generate transgenic birds economically and effectively [Current Zoology 55 (5): 383 - 387,2009].

  5. Study on College Physical Education Management Information System Based on Support Vector Regression

    Directory of Open Access Journals (Sweden)

    Haibo Yan

    2013-12-01

    Full Text Available In order to effectively alleviate the great pressure of sports function development and social service needs, changing the structure of a single, working form the old educational pattern, this study is based on the current situation of college sports management, introduced the support vector construction of information of college sports management system, learning theory and the information model of college sports management value through the analysis of fuzzy evaluation method, satisfactory results have been obtained. College sports management model based on support vector regression conforms to the trend of information management, to promote the standardization of sports teaching management, to promote the college physical education teaching and research has practical significance.

  6. Support vector machine based nonlinear model multi-step-ahead optimizing predictive control

    Institute of Scientific and Technical Information of China (English)

    ZHONG Wei-min; PI Dao-ying; SUN You-xian

    2005-01-01

    A support vector machine with guadratic polynomial kernel function based nonlinear model multi-step-ahead optimizing predictive controller was presented. A support vector machine based predictive model was established by black-box identification. And a quadratic objective function with receding horizon was selected to obtain the controller output. By solving a nonlinear optimization problem with equality constraint of model output and boundary constraint of controller output using Nelder-Mead simplex direct search method, a sub-optimal control law was achieved in feature space. The effect of the controller was demonstrated on a recognized benchmark problem and a continuous-stirred tank reactor. The simulation results show that the multi-step-ahead predictive controller can be well applied to nonlinear system, with better performance in following reference trajectory and disturbance-rejection.

  7. 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. PMID:15005407

  8. Climate-based models for West Nile Culex mosquito vectors in the Northeastern US

    Science.gov (United States)

    Gong, Hongfei; Degaetano, Arthur T.; Harrington, Laura C.

    2011-05-01

    Climate-based models simulating Culex mosquito population abundance in the Northeastern US were developed. Two West Nile vector species, Culex pipiens and Culex restuans, were included in model simulations. The model was optimized by a parameter-space search within biological bounds. Mosquito population dynamics were driven by major environmental factors including temperature, rainfall, evaporation rate and photoperiod. The results show a strong correlation between the timing of early population increases (as early warning of West Nile virus risk) and decreases in late summer. Simulated abundance was highly correlated with actual mosquito capture in New Jersey light traps and validated with field data. This climate-based model simulates the population dynamics of both the adult and immature mosquito life stage of Culex arbovirus vectors in the Northeastern US. It is expected to have direct and practical application for mosquito control and West Nile prevention programs.

  9. Novel Sensorless Vector Control System of Induction Machine Based on Flux Observer in Field Weakening

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    A speed-sensorless vector control system for induction machines (IMs) is presented. According to the vector control theory of IMs, the rotor flux is estimated based on a flux observer,and the speed is estimated through the method of q-axis rotor flux converging on zero with proportional integral regulator. A 0.75 kW,50 Hz,two-pole induction machine was used in the simulation and experimental verification. The simulation model was constructed in Matlab. A series of tests were performed in the field weakening region, for both no-load and loaded operation. The estimated speed tracks the actual speed well in the based speed region and field weakening region (1 per unit value to 4 per unit value). The small estimation error of residual speed is due to the existence of slip.

  10. A DSP-based discrete space vector modulation direct torque control of sensorless induction machines

    Energy Technology Data Exchange (ETDEWEB)

    Khoucha, F.; Marouani, K.; Kheloui, A.; Aliouane, K.

    2004-07-01

    In this paper, we present a Direct Torque Control scheme of an induction motor operating without speed sensor. The estimation of the stator flux and the rotor speed is performed by an adaptive observer. In order to reduce the torque, flux, current and speed ripple a Discrete Space Vector Modulation (DSVM-DTC) strategy is implemented using a DSP-based hardware. To illustrate the performances of this control scheme, experimental results are presented. (author)

  11. Vector magnetic measurement based on directional scattering between polarized plasmon wave and arrayed nanoparticles

    Science.gov (United States)

    Zhang, Zhaochuan; Guo, Tuan; Liu, Fu; Wu, Qiang; Li, Jie; Cheng, Linghao; Guan, Bai-Ou

    2015-09-01

    A vector magnetic field sensor based on surface plasmon resonance (SPR) of a 15° tilted fiber Bragg grating (TFBG) and magnetic fluid is proposed and experimentally demonstrated. Both the orientation and the amplitude of the magnetic fields can be determined unambiguously via the wavelength and intensity monitoring of the SPR, which is essentially dominated by the arrayed Fe3O4 nanoparticles over the nanometric-film of fiber surface.

  12. Study on College Physical Education Management Information System Based on Support Vector Regression

    OpenAIRE

    Haibo Yan; Tingting Wang

    2013-01-01

    In order to effectively alleviate the great pressure of sports function development and social service needs, changing the structure of a single, working form the old educational pattern, this study is based on the current situation of college sports management, introduced the support vector construction of information of college sports management system, learning theory and the information model of college sports management value through the analysis of fuzzy evaluation method, satisfactory ...

  13. Switching Loss Characteristics of Sequences Involving Active State Division in Space Vector Based PWM

    OpenAIRE

    Zhao, Di; Narayanan, G.; Ayyanar, Raja

    2004-01-01

    This paper analyzes the switching loss characteristics of sequences involving division of active state duration in space vector based PWM. This analysis, together with the THD performance of the different sequences, reported recently, is used to design new hybrid PWM techniques for induction motor drives, which result in simultaneous reduction in both THD as well as inverter switching losses. Experimental results are presented to demonstrate the feasibility and advantages of the proposed PWM ...

  14. An adaptation of the vector-space model for ontology based information retrieval

    OpenAIRE

    Castells, Pablo; Fernández Sánchez, Miriam; Vallet Weadon, David Jordi

    2007-01-01

    Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. P. Castells, M. Fernández, D. Vallet. "An Adaptation of the Vector-Space Model for Ontology-Based Information Retrieval", IEEE...

  15. Fast Training of Support Vector Machines Using Error-Center-Based Optimization

    Institute of Scientific and Technical Information of China (English)

    L. Meng; Q. H. Wu

    2005-01-01

    This paper presents a new algorithm for Support Vector Machine (SVM) training, which trains a machine based on the cluster centers of errors caused by the current machine. Experiments withvarious training sets show that the computation time of this new algorithm scales almost linear with training set size and thus may be applied to much larger training sets, in comparison to standard quadratic programming (QP) techniques.

  16. Space vector-based modeling and control of a modular multilevel converter in HVDC applications

    DEFF Research Database (Denmark)

    Bonavoglia, M.; Casadei, G.; Zarri, L.; Mengoni, M.; Tani, A.; Serra, G.; Teodorescu, Remus

    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....

  17. A Support Vector Machine-based Evaluation Model of Customer Satisfaction Degree in Logistics

    Institute of Scientific and Technical Information of China (English)

    SUN Hua-li; XIE Jian-ying

    2007-01-01

    This paper pressnts a novel evaluation model of the customer satisfaction degree (CSD) in logistics based on support vector machine (SVM). Firstly, the relation between the suppliers and the customers is analyzed. Secondly, the evaluation index system and fuzzy quantitative methods are provided. Thirdly, the CSD evaluation system including eight indexes and three ranks rinsed on one-against-one mode of SVM is built. Last simulation experiment is presented to illustrate the theoretical results.

  18. Tracking and registration method based on vector operation for augmented reality system

    Science.gov (United States)

    Gao, Yanfei; Wang, Hengyou; Bian, Xiaoning

    2015-08-01

    Tracking and registration is one key issue for an augmented reality (AR) system. For the marker-based AR system, the research focuses on detecting the real-time position and orientation of camera. In this paper, we describe a method of tracking and registration using the vector operations. Our method is proved to be stable and accurate, and have a good real-time performance.

  19. Drifting model approach to modeling based on weighted support vector machines

    Institute of Scientific and Technical Information of China (English)

    冯瑞; 宋春林; 邵惠鹤

    2004-01-01

    This paper proposes a novel drifting modeling (DM) method. Briefly, we first employ an improved SVMs algorithm named weighted support vector machines (W_SVMs), which is suitable for locally learning, and then the DM method using the algorithm is proposed. By applying the proposed modeling method to Fluidized Catalytic Cracking Unit (FCCU), the simulation results show that the property of this proposed approach is superior to global modeling method based on standard SVMs.

  20. PSO-Based Support Vector Machine with Cuckoo Search Technique for Clinical Disease Diagnoses

    OpenAIRE

    Xiaoyong Liu; Hui Fu

    2014-01-01

    Disease diagnosis is conducted with a machine learning method. We have proposed a novel machine learning method that hybridizes support vector machine (SVM), particle swarm optimization (PSO), and cuckoo search (CS). The new method consists of two stages: firstly, a CS based approach for parameter optimization of SVM is developed to find the better initial parameters of kernel function, and then PSO is applied to continue SVM training and find the best parameters of SVM. Experimental results ...

  1. 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.

  2. 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. PMID:26357256

  3. Vector quantizer based on brightness maps for image compression with the polynomial transform

    Science.gov (United States)

    Escalante-Ramirez, Boris; Moreno-Gutierrez, Mauricio; Silvan-Cardenas, Jose L.

    2002-11-01

    We present a vector quantization scheme acting on brightness fields based on distance/distortion criteria correspondent with psycho-visual aspects. These criteria quantify sensorial distortion between vectors that represent either portions of a digital image or alternatively, coefficients of a transform-based coding system. In the latter case, we use an image representation model, namely the Hermite transform, that is based on some of the main perceptual characteristics of the human vision system (HVS) and in their response to light stimulus. Energy coding in the brightness domain, determination of local structure, code-book training and local orientation analysis are all obtained by means of the Hermite transform. This paper, for thematic reasons, is divided in four sections. The first one will shortly highlight the importance of having newer and better compression algorithms. This section will also serve to explain briefly the most relevant characteristics of the HVS, advantages and disadvantages related with the behavior of our vision in front of ocular stimulus. The second section shall go through a quick review of vector quantization techniques, focusing their performance on image treatment, as a preview for the image vector quantizer compressor actually constructed in section 5. Third chapter was chosen to concentrate the most important data gathered on brightness models. The building of this so-called brightness maps (quantification of the human perception on the visible objects reflectance), in a bi-dimensional model, will be addressed here. The Hermite transform, a special case of polynomial transforms, and its usefulness, will be treated, in an applicable discrete form, in the fourth chapter. As we have learned from previous works 1, Hermite transform has showed to be a useful and practical solution to efficiently code the energy within an image block, deciding which kind of quantization is to be used upon them (whether scalar or vector). It will also be

  4. Similarity measure of spectral vectors based on set theory and its application in hyperspectral RS image retrieval

    Institute of Scientific and Technical Information of China (English)

    Peijun Du (杜培军); Tao Fang (方涛); Hong Tang (唐宏); Pengfei Shi (施鹏飞)

    2003-01-01

    In this paper, two new similarity measure methods based on set theory were proposed. Firstly, similarity measure of two sets based on set theory and set operation was discussed. This principle was used to spectral vectors, and two approaches were proposed. The first method was to create a spectral polygon corresponding to spectral curve, and similarity of two spectral vectors can be replaced by that of two polygons. Area of spectral polygon was used as quantification function and some effective indexes for similarity and dissimilarity were computed. The second method was to transform the original spectral vector to encoding vector according to absorption or reflectance feature bands, and similarity measure was conducted to encoding vectors. It proved that the spectral polygon-based approach was effective and can be used to hyperspectral RS image retrieval.

  5. A Single Loop Vectorization Method Based on Assemble Code%一种基于汇编代码的单重循环向量化方法

    Institute of Scientific and Technical Information of China (English)

    陆洪毅; 戴葵; 王志英

    2003-01-01

    Through loops vectorization in instruction sequence, the vector power provided by hardware can be fully utilized. This paper analyzes the RISC instructton set, and presents a single loop vectorization method that is based on assemble code, it can efficiently detect single loops in instruct sequence and vectorize them.

  6. Recognition of low-contrast FLIR tank object based on multiscale fractal character vector

    Science.gov (United States)

    Xue, Donghui; Zhu, Yaoting; Zhu, Guang-Xi; Xiong, Yan

    1996-05-01

    Low-contrast FLIR tank object detection is a difficulty. This paper presents a new method based on fractal geometry and multiscale analysis for the target detection. A new metric called multiscale fractal character vector which can distinguish man-made objects and natural scenes is defined. And then a segmentation algorithm based on this new metric is given. Finally, experimental results have shown our method can give better segmentation results than the usual segmentation method which is based on H parameter of only one scale image.

  7. Generation of a helper cell line for packaging avian leukosis virus-based vectors.

    OpenAIRE

    Savatier, P; Bagnis, C.; Thoraval, P; Poncet, D; Belakebi, M; Mallet, F.; Legras, C.; Cosset, F L; Thomas, J.L.; Chebloune, Y

    1989-01-01

    We constructed an avian leukosis virus-based packaging cell line, pHF-g, containing Rous-associated virus DNA with several alterations to abolish RNA packaging. One of them is a 52-base-pair deletion encompassing the putative encapsidation signal in the leader region. The 3' long terminal repeat was also removed and replaced by the polyadenylation sequence from the herpes simplex virus thymidine kinase gene. When pHF-g cells were transfected by an avian leukosis virus-based vector, they produ...

  8. Evaluation of cache-based superscalar and cacheless vector architectures for scientific computations

    Energy Technology Data Exchange (ETDEWEB)

    Oliker, Leonid; Canning, Andrew; Carter, Jonathan; Shalf, John; Skinner, David; Ethier, Stephane; Biswas, Rupak; Djomehri, Jahed; Van der Wijngaart, Rob

    2003-05-01

    The growing gap between sustained and peak performance for scientific applications is a well-known problem in high end computing. The recent development of parallel vector systems offers the potential to bridge this gap for many computational science codes and deliver a substantial increase in computing capabilities. This paper examines the intranode performance of the NEC SX-6 vector processor and the cache-based IBM Power3/4 superscalar architectures across a number of scientific computing areas. First, we present the performance of a microbenchmark suite that examines low-level machine characteristics. Next, we study the behavior of the NAS Parallel Benchmarks. Finally, we evaluate the performance of several scientific computing codes. Results demonstrate that the SX-6 achieves high performance on a large fraction of our applications and often significantly out performs the cache-based architectures. However, certain applications are not easily amenable to vectorization and would re quire extensive algorithm and implementation reengineering to utilize the SX-6 effectively.

  9. Advances in SVM-Based System Using GMM Super Vectors for Text-Independent Speaker Verification

    Institute of Scientific and Technical Information of China (English)

    ZHAO Jian; DONG Yuan; ZHAO Xianyu; YANG Hao; LU Liang; WANG Haila

    2008-01-01

    For text-independent speaker verification,the Gaussian mixture model (GMM) using a universal background model strategy and the GMM using support vector machines are the two most commonly used methodologies.Recently,a new SVM-based speaker verification method using GMM super vectors has been proposed.This paper describes the construction of a new speaker verification system and investigates the use of nuisance attribute projection and test normalization to further enhance performance.Experiments were conducted on the core test of the 2006 NIST speaker recognition evaluation corpus.The experimental results indicate that an SVM-based speaker verification system using GMM super vectors can achieve ap-pealing performance.With the use of nuisance attribute projection and test normalization,the system per-formance can be significantly improved,with improvements in the equal error rate from 7.78% to 4.92% and detection cost function from 0.0376 to 0.0251.

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

    International Nuclear Information System (INIS)

    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

  11. An Improved Endmember Selection Method Based on Vector Length for MODIS Reflectance Channels

    Directory of Open Access Journals (Sweden)

    Yuanliu Xu

    2015-05-01

    Full Text Available Endmember selection is the basis for sub-pixel land cover classifications using multiple endmember spectral mixture analysis (MESMA that adopts variant endmember matrices for each pixel to mitigate errors caused by endmember variability in SMA. A spectral library covering a large number of endmembers can account for endmember variability, but it also lowers the computational efficiency. Therefore, an efficient endmember selection scheme to optimize the library is crucial to implement MESMA. In this study, we present an endmember selection method based on vector length. The spectra of a land cover class were divided into subsets using vector length intervals of the spectra, and the representative endmembers were derived from these subsets. Compared with the available endmember average RMSE (EAR method, our approach improved the computational efficiency in endmember selection. The method accuracy was further evaluated using spectral libraries derived from the ground reference polygon and Moderate Resolution Imaging Spectroradiometer (MODIS imagery respectively. Results using the different spectral libraries indicated that MESMA combined with the new approach performed slightly better than EAR method, with Kappa coefficient improved from 0.75 to 0.78. A MODIS image was used to test the mapping fraction, and the representative spectra based on vector length successfully modeled more than 90% spectra of the MODIS pixels by 2-endmember models.

  12. 2D Gaze Estimation Based on Pupil-Glint Vector Using an Artificial Neural Network

    Directory of Open Access Journals (Sweden)

    Jianzhong Wang

    2016-06-01

    Full Text Available Gaze estimation methods play an important role in a gaze tracking system. A novel 2D gaze estimation method based on the pupil-glint vector is proposed in this paper. First, the circular ring rays location (CRRL method and Gaussian fitting are utilized for pupil and glint detection, respectively. Then the pupil-glint vector is calculated through subtraction of pupil and glint center fitting. Second, a mapping function is established according to the corresponding relationship between pupil-glint vectors and actual gaze calibration points. In order to solve the mapping function, an improved artificial neural network (DLSR-ANN based on direct least squares regression is proposed. When the mapping function is determined, gaze estimation can be actualized through calculating gaze point coordinates. Finally, error compensation is implemented to further enhance accuracy of gaze estimation. The proposed method can achieve a corresponding accuracy of 1.29°, 0.89°, 0.52°, and 0.39° when a model with four, six, nine, or 16 calibration markers is utilized for calibration, respectively. Considering error compensation, gaze estimation accuracy can reach 0.36°. The experimental results show that gaze estimation accuracy of the proposed method in this paper is better than that of linear regression (direct least squares regression and nonlinear regression (generic artificial neural network. The proposed method contributes to enhancing the total accuracy of a gaze tracking system.

  13. A direct torque control scheme for permanent magnet synchronous motors based on space vector modulation

    Science.gov (United States)

    Su, Xiao-hui; Xu, Shu-Ping

    2013-03-01

    In order to solve the problem of direct torque control (DTC) for permanent magnet synchronous motor (PMSM) related to the flux and the torque ripple and the uncertainty of switching frequency, A novel direct torque control system based on space vector modulation(SVM-DTC) for permanent magnet synchronous motor was proposed. In this method flux and torque are controlled through stator voltage components in stator flux linkage coordinate axes and space vector modulation is used to control inverters. Therefore, the errors of torque and flux linkage could be compensated accurately. The whole system has only one easily adjustable PI adjuster and needs no high for hardware and easy for realize. The simulation results verify the feasibility of this method, reduction of the flux and the torque ripple, and the good performance of DTC.

  14. Principal Component based Auto-Associative Support Vector Regression for Signal Validation in Nuclear Power Plants

    International Nuclear Information System (INIS)

    For the past two decades, the nuclear industry has attempted to move towards condition-based maintenance philosophies using new technologies developed to ascertain the condition of plant equipment during operation. From the early 1980's the application of artificial intelligence techniques to nuclear power plants were investigated for instrument condition monitoring. The Multivariate State Estimation System (MSET) was developed in the late 1980s. And the Plant Evaluation and Analysis by Neural Operators (PEANO) was developed; it uses auto associative neural networks (AANN) and applies them to the monitoring of nuclear power plant sensors. In this paper, a method that utilizes the attractive merits of principal component analysis (PCA) for extracting predominant feature vectors and Auto- Associative support vector regression (AASVR) for databased statistical learning is proposed for the on-line monitoring and signal validation with the use of real plant data

  15. Compensation method for temperature error of fiber optical gyroscope based on relevance vector machine.

    Science.gov (United States)

    Wang, Guochen; Wang, Qiuying; Zhao, Bo; Wang, Zhenpeng

    2016-02-10

    Aiming to improve the bias stability of the fiber optical gyroscope (FOG) in an ambient temperature-change environment, a temperature-compensation method based on the relevance vector machine (RVM) under Bayesian framework is proposed and applied. Compared with other temperature models such as quadratic polynomial regression, neural network, and the support vector machine, the proposed RVM method possesses higher accuracy to explain the temperature dependence of the FOG gyro bias. Experimental results indicate that, with the proposed RVM method, the bias stability of an FOG can be apparently reduced in the whole temperature ranging from -40°C to 60°C. Therefore, the proposed method can effectively improve the adaptability of the FOG in a changing temperature environment. PMID:26906376

  16. Privacy Preserving Fall Detection Based on Simple Human Silhouette Extraction and a Linear Support Vector Machine

    Directory of Open Access Journals (Sweden)

    Velislava Spasova

    2016-06-01

    Full Text Available The paper presents a novel fast, real-time and privacy protecting algorithm for fall detection based on geometric properties of the human silhouette and a linear support vector machine. The algorithm uses infrared and visible light imagery in order to detect the human. A simple real-time human silhouette extraction algorithm has been developed and used to extract features for training of the support vector machine. The achieved sensitivity and specificity of the proposed approach are over 97% which match state of the art research in the area of fall detection. The developed solution uses low-cost hardware components and open source software library and is suitable for usage in assistive systems for the home or nursing homes.

  17. A NEW FUZZY LOGIC BASED SPACE VECTOR MODULATION APPROACH ON DIRECT TORQUE CONTROLLED INDUCTION MOTORS

    Directory of Open Access Journals (Sweden)

    Fatih Korkmaz

    2013-11-01

    Full Text Available The induction motors are indispensable motor types for industrial applications due to its wellknown advantages. Therefore, many kind of control scheme are proposed for induction motors over the past years and direct torque control has gained great importance inside of them due to fast dynamic torque response behavior and simple control structure. This paper suggests a new approach on the direct torque controlled induction motors, Fuzzy logic based space vector modulation, to overcome disadvantages of conventional direct torque control like high torque ripple. In the proposed approach, optimum switching states are calculated by fuzzy logic controller and applied by space vector pulse width modulator to voltage source inverter. In order to test and compare the proposed DTC scheme with conventional DTC scheme simulations, in Matlab/Simulink, have been carried out in different speed and load conditions. The simulation results showed that a significant improvement in the dynamic torque and speed responses when compared to the conventional DTC scheme.

  18. Vibration reliability analysis for aeroengine compressor blade based on support vector machine response surface method

    Institute of Scientific and Technical Information of China (English)

    GAO Hai-feng; BAI Guang-chen

    2015-01-01

    To ameliorate reliability analysis efficiency for aeroengine components, such as compressor blade, support vector machine response surface method (SRSM) is proposed. SRSM integrates the advantages of support vector machine (SVM) and traditional response surface method (RSM), and utilizes experimental samples to construct a suitable response surface function (RSF) to replace the complicated and abstract finite element model. Moreover, the randomness of material parameters, structural dimension and operating condition are considered during extracting data so that the response surface function is more agreeable to the practical model. The results indicate that based on the same experimental data, SRSM has come closer than RSM reliability to approximating Monte Carlo method (MCM); while SRSM (17.296 s) needs far less running time than MCM (10958 s) and RSM (9840 s). Therefore, under the same simulation conditions, SRSM has the largest analysis efficiency, and can be considered a feasible and valid method to analyze structural reliability.

  19. Modelling of chaotic systems based on modified weighted recurrent least squares support vector machines

    Institute of Scientific and Technical Information of China (English)

    Sun Jian-Cheng; Zhang Tai-Yi; Liu Feng

    2004-01-01

    Positive Lyapunov exponents cause the errors in modelling of the chaotic time series to grow exponentially. In this paper, we propose the modified version of the support vector machines (SVM) to deal with this problem. Based on recurrent least squares support vector machines (RLS-SVM), we introduce a weighted term to the cost function to compensate the prediction errors resulting from the positive global Lyapunov exponents. To demonstrate the effectiveness of our algorithm, we use the power spectrum and dynamic invariants involving the Lyapunov exponents and the correlation dimension as criterions, and then apply our method to the Santa Fe competition time series. The simulation results shows that the proposed method can capture the dynamics of the chaotic time series effectively.

  20. A Simplified Sensorless Vector Control Based on Average DC Bus Current for Fan Motor

    Science.gov (United States)

    Sumita, Satoshi; Tobari, Kazuaki; Aoyagi, Shigehisa; Maeda, Daisuke

    This paper describes a simplified sensorless vector control based on the average DC bus current for PMSM. This method can be used to design a drive control system at a relatively low cost because the microcontroller does not require a precise timer and the calculation load is slight. In the proposed method, one of the two possible current estimation processes is chosen according to the operation mode. First, the controller estimates d-axis current and identifies the back-EMF parameter in the synchronous operation mode at low speeds. The error in the back-EMF identification affects the efficiency of the proposed system, so it needs to be zero. Second, the controller estimates q-axis current in vector control mode. The identified parameter and q-axis current define voltage reference to realize high efficiency drive. The obtained experimental results confirm the effectiveness of the proposed method.

  1. Polarization imaging of multiply-scattered radiation based on integral-vector Monte Carlo method

    International Nuclear Information System (INIS)

    A new integral-vector Monte Carlo method (IVMCM) is developed to analyze the transfer of polarized radiation in 3D multiple scattering particle-laden media. The method is based on a 'successive order of scattering series' expression of the integral formulation of the vector radiative transfer equation (VRTE) for application of efficient statistical tools to improve convergence of Monte Carlo calculations of integrals. After validation against reference results in plane-parallel layer backscattering configurations, the model is applied to a cubic container filled with uniformly distributed monodispersed particles and irradiated by a monochromatic narrow collimated beam. 2D lateral images of effective Mueller matrix elements are calculated in the case of spherical and fractal aggregate particles. Detailed analysis of multiple scattering regimes, which are very similar for unpolarized radiation transfer, allows identifying the sensitivity of polarization imaging to size and morphology.

  2. Recursions in Calogero-Sutherland Model Based on Virasoro Singular Vectors

    International Nuclear Information System (INIS)

    The present work is much motivated by finding an explicit way in the construction of the Jack symmetric function, which is the spectrum generating function for the Calogero-Sutherland (CS) model. To accomplish this work, the hidden Virasoro structure in the CS model is much explored. In particular, we found that the Virasoro singular vectors form a skew hierarchy in the CS model. Literally, skew is analogous to coset, but here specifically refer to the operation on the Young tableaux. In fact, based on the construction of the Virasoro singular vectors, this hierarchical structure can be used to give a complete construction of the CS states, i.e. the Jack symmetric functions, recursively. The construction is given both in operator formalism as well as in integral representation. This new integral representation for the Jack symmetric functions may shed some insights on the spectrum constructions for the other integrable systems. (general)

  3. The study of underwater acoustic communication technology based-on the acoustic vector sensor

    Institute of Scientific and Technical Information of China (English)

    QIAO Gang; SANG Enfang

    2007-01-01

    Underwater acoustic (UWA) communication based on an acoustic vector sensor is studied. The method of joint weighted sound pressure and velocity processing is used in phase modulation high-speed UWA communication system combined with coherent demodulation and adaptive equalization algorithm to demodulate and decode. Whereas the sound intensity could be used instead of pressure for frequency decoding in frequency modulation UWA communication system. The results of theory analysis, simulation calculations and lake trials have shown that either in phase modulation or in frequency modulation UWA communication system, the processing gain can be evidently increased, so that the BER (bit error rate) can be effectively reduced and the telemetry distance can be enlarged by using the acoustic vector sensor.

  4. Boost OCR accuracy using iVector based system combination approach

    Science.gov (United States)

    Peng, Xujun; Cao, Huaigu; Natarajan, Prem

    2015-01-01

    Optical character recognition (OCR) is a challenging task because most existing preprocessing approaches are sensitive to writing style, writing material, noises and image resolution. Thus, a single recognition system cannot address all factors of real document images. In this paper, we describe an approach to combine diverse recognition systems by using iVector based features, which is a newly developed method in the field of speaker verification. Prior to system combination, document images are preprocessed and text line images are extracted with different approaches for each system, where iVector is transformed from a high-dimensional supervector of each text line and is used to predict the accuracy of OCR. We merge hypotheses from multiple recognition systems according to the overlap ratio and the predicted OCR score of text line images. We present evaluation results on an Arabic document database where the proposed method is compared against the single best OCR system using word error rate (WER) metric.

  5. Bidding Strategy with Forecast Technology Based on Support Vector Machine in Electrcity Market

    CERN Document Server

    Gao, C; Napoli, R; Wan, Q

    2007-01-01

    The participants of the electricity market concern very much the market price evolution. Various technologies have been developed for price forecast. SVM (Support Vector Machine) has shown its good performance in market price forecast. Two approaches for forming the market bidding strategies based on SVM are proposed. One is based on the price forecast accuracy, with which the being rejected risk is defined. The other takes into account the impact of the producer's own bid. The risks associated with the bidding are controlled by the parameters setting. The proposed approaches have been tested on a numerical example.

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

    OpenAIRE

    Xian-Xia Zhang; Ye Jiang; Shiwei Ma; Bing Wang

    2013-01-01

    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 ...

  7. Accurate performance estimators for information retrieval based on span bound of support vector machines

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    Support vector machines have met with significant success in the information retrieval field, especially in handling text classification tasks. Although various performance estimators for SVMs have been proposed,these only focus on accuracy which is based on the leave-one-out cross validation procedure. Information-retrieval-related performance measures are always neglected in a kernel learning methodology. In this paper, we have proposed a set of information-retrieval-oriented performance estimators for SVMs, which are based on the span bound of the leave-one-out procedure. Experiments have proven that our proposed estimators are both effective and stable.

  8. Thrust estimator design based on least squares support vector regression machine

    Institute of Scientific and Technical Information of China (English)

    ZHAO Yong-ping; SUN Jian-guo

    2010-01-01

    In order to realize direct thrust control instead of traditional sensor-based control for nero-engines,it is indispensable to design a thrust estimator with high accuracy,so a scheme for thrust estimator design based on the least square support vector regression machine is proposed to solve this problem.Furthermore,numerical simulations confirm the effectiveness of our presented scheme.During the process of estimator design,a wrap per criterion that can not only reduce the computational complexity but also enhance the generalization performance is proposed to select variables as input variables for estimator.

  9. System identification modelling of ship manoeuvring motion based onε- support vector regression

    Institute of Scientific and Technical Information of China (English)

    王雪刚; 邹早建; 侯先瑞; 徐锋

    2015-01-01

    Based on theε-support vector regression, three modelling methods for the ship manoeuvring motion, i.e., the white-box modelling, the grey-box modelling and the black-box modelling, are investigated. Theoo10/10,oo20/20 zigzag tests and the o35 turning circle manoeuvre are simulated. Part of the simulation data for theoo20/20 zigzag test are used to train the support vectors, and the trained support vector machine is used to predict the wholeoo20/20 zigzag test. Comparison between the simula- ted and predictedoo20/20 zigzag test shows a good predictive ability of the three modelling methods. Then all mathematical models obtained by the modelling methods are used to predict theoo10/10 zigzag test ando35 turning circle manoeuvre, and the predicted results are compared with those of simulation tests to demonstrate the good generalization performance of the mathematical models. Finally, the modelling methods are analyzed and compared with each other in terms of the application conditions, the prediction accuracy and the computation speed. An appropriate modelling method can be chosen according to the intended use of the mathematical models and the available data for the system identification.

  10. Vegetation change detection for urban areas based on extended change vector analysis

    Science.gov (United States)

    Yu, Hui; Jia, Yonghong

    2006-10-01

    This study sought to develop a modified change vector analysis(CVA) using normalized multi-temporal data to detect urban vegetation change. Because of complex change in urban areas, modified CVA application based on NDVI and mask techniques can minify the effect of non-vegetation changes and improve upon efficiency to a great extent. Moreover, drawing from methods in Polar plots, the extended CVA technique measures absolute angular changes and total magnitude of perpendicular vegetation index (PVI) and two of Tasseled Cap indices (greenness and wetness). Polar plots summarized change vectors to quantify and visualize both magnitude and direction of change, and magnitude is applied to determine change pixels through threshold segmentation while direction is applied as pixel's feature to classifying change pixels through supervised classification. Then this application is performed with Landsat ETM+ imageries of Wuhan in 2002 and 2005, and assessed by error matrix, which finds that it could detect change pixels 95.10% correct, and could classify change pixels 91.96% correct in seven change classes through performing supervised classification with direction angles. The technique demonstrates the ability of change vectors in multiple biophysical dimensions to vegetation change detection, and the application can be trended as an efficient alternative to urban vegetation change detection and classification.

  11. A Parallel Genetic Algorithm Based Feature Selection and Parameter Optimization for Support Vector Machine

    Directory of Open Access Journals (Sweden)

    Zhi Chen

    2016-01-01

    Full Text Available The extensive applications of support vector machines (SVMs require efficient method of constructing a SVM classifier with high classification ability. The performance of SVM crucially depends on whether optimal feature subset and parameter of SVM can be efficiently obtained. In this paper, a coarse-grained parallel genetic algorithm (CGPGA is used to simultaneously optimize the feature subset and parameters for SVM. The distributed topology and migration policy of CGPGA can help find optimal feature subset and parameters for SVM in significantly shorter time, so as to increase the quality of solution found. In addition, a new fitness function, which combines the classification accuracy obtained from bootstrap method, the number of chosen features, and the number of support vectors, is proposed to lead the search of CGPGA to the direction of optimal generalization error. Experiment results on 12 benchmark datasets show that our proposed approach outperforms genetic algorithm (GA based method and grid search method in terms of classification accuracy, number of chosen features, number of support vectors, and running time.

  12. Triple-image encryption based on phase-truncated Fresnel transform and basic vector operation.

    Science.gov (United States)

    Pan, Xuemei; Meng, Xiangfeng; Yang, Xiulun; Wang, Yurong; Peng, Xiang; He, Wenqi; Dong, Guoyan; Chen, Hongyi

    2015-10-01

    A triple-image encryption method is proposed that is based on phase-truncated Fresnel transform (PTFT), basic vector composition, and XOR operation. In the encryption process, two random phase masks, with one each placed at the input plane and the transform plane, are generated by basic vector resolution operations over the first and the second plaintext images, and then a ciphered image in the input plane is fabricated by XOR encoding for the third plaintext image. When the cryptosystem is illuminated by an on-axis plane, assisted by PTFT, the ciphered image is finally encrypted into an amplitude-only noise-like image in the output plane. During decryption, possessing the correct private key, decryption keys, and the assistant geometrical parameter keys, and placing them at the corresponding correct positions, the original three plaintext images can be successfully decrypted by inverse PTFT, basic vector composition, and XOR decoding. Theoretical analysis and numerical simulations both verify the feasibility of the proposed method. PMID:26479627

  13. A series of TA-based and zero-background vectors for plant functional genomics.

    Directory of Open Access Journals (Sweden)

    Chuntao Wang

    Full Text Available With the sequencing of genomes from many organisms now complete and the development of high-throughput sequencing, life science research has entered the functional post-genome era. Therefore, deciphering the function of genes and how they interact is in greater demand. To study an unknown gene, the basic methods are either overexpression or gene knockout by creating transgenic plants, and gene construction is usually the first step. Although traditional cloning techniques using restriction enzymes or a site-specific recombination system (Gateway or Clontech cloning technology are highly useful for efficiently transferring DNA fragments into destination plasmids, the process is time consuming and expensive. To facilitate the procedure of gene construction, we designed a TA-based cloning system in which only one step was needed to subclone a DNA fragment into vectors. Such a cloning system was developed from the pGreen binary vector, which has a minimal size and facilitates construction manipulation, combined with the negative selection marker gene ccdB, which has the advantages of eliminating the self-ligation background and directly enabling high-efficiency TA cloning technology. We previously developed a set of transient and stable transformation vectors for constitutive gene expression, gene silencing, protein tagging, subcellular localization analysis and promoter activity detection. Our results show that such a system is highly efficient and serves as a high-throughput platform for transient or stable transformation in plants for functional genome research.

  14. DNA vector-based RNAi approach for stable depletion of poly(ADP-ribose) polymerase-1

    International Nuclear Information System (INIS)

    RNA-mediated interference (RNAi) is a powerful technique that is now being used in mammalian cells to specifically silence a gene. Some recent studies have used this technique to achieve variable extent of depletion of a nuclear enzyme poly(ADP-ribose) polymerase-1 (PARP-1). These studies reported either transient silencing of PARP-1 using double-stranded RNA or stable silencing of PARP-1 with a DNA vector which was introduced by a viral delivery system. In contrast, here we report that a simple RNAi approach which utilizes a pBS-U6-based DNA vector containing strategically selected PARP-1 targeting sequence, introduced in the cells by conventional CaPO4 protocol, can be used to achieve stable and specific silencing of PARP-1 in different types of cells. We also provide a detailed strategy for selection and cloning of PARP-1-targeting sequences for the DNA vector, and demonstrate that this technique does not affect expression of its closest functional homolog PARP-2

  15. Robust Vision-Based Pose Estimation Algorithm for AN Uav with Known Gravity Vector

    Science.gov (United States)

    Kniaz, V. V.

    2016-06-01

    Accurate estimation of camera external orientation with respect to a known object is one of the central problems in photogrammetry and computer vision. In recent years this problem is gaining an increasing attention in the field of UAV autonomous flight. Such application requires a real-time performance and robustness of the external orientation estimation algorithm. The accuracy of the solution is strongly dependent on the number of reference points visible on the given image. The problem only has an analytical solution if 3 or more reference points are visible. However, in limited visibility conditions it is often needed to perform external orientation with only 2 visible reference points. In such case the solution could be found if the gravity vector direction in the camera coordinate system is known. A number of algorithms for external orientation estimation for the case of 2 known reference points and a gravity vector were developed to date. Most of these algorithms provide analytical solution in the form of polynomial equation that is subject to large errors in the case of complex reference points configurations. This paper is focused on the development of a new computationally effective and robust algorithm for external orientation based on positions of 2 known reference points and a gravity vector. The algorithm implementation for guidance of a Parrot AR.Drone 2.0 micro-UAV is discussed. The experimental evaluation of the algorithm proved its computational efficiency and robustness against errors in reference points positions and complex configurations.

  16. 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.

  17. 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.

  18. PDM-16QAM vector signal generation and detection based on intensity modulation and direct detection

    Science.gov (United States)

    Chen, Long; Yu, Jianjun; Li, Xinying

    2016-07-01

    We experimentally demonstrate a novel and simple method to generate and detect high speed polarization-division-multiplexing 16-ary quadrature-amplitude-modulation (PDM-16QAM) vector signal enabled by Mach-Zehnder modulator-based (MZM-based) optical-carrier-suppression (OCS) intensity modulation and direct detection. Due to the adoption of OCS intensity modulation, carrier beating can be avoided at the receiver, and thus polarization de-multiplexing can be implemented by digital-signal-processing-based (DSP-based) cascaded multi-modulus algorithm (CMMA) equalization instead of a polarization tracking system. The change of both amplitude and phase information due to the adoption of OCS modulation can be equalized by DSP-based amplitude and phase precoding at the transmitter. Up to 64-Gb/s PDM-16QAM vector signal is generated and detected after 2-km single-mode fiber-28 (SMF-28) or 20-km large-effective-area fiber (LEAF) transmission with a bit-error-ratio (BER) less than the hard-decision forward-error-correction (HD-FEC) threshold of 3.8×10-3.

  19. A Quick-Simulation Tool for Induction Motor Drives Controlled Using Advanced Space-Vector-Based PWM Techniques

    OpenAIRE

    Hari, Pavan Kumar VSS; Narayanan, G.

    2013-01-01

    Space-vector-based pulse width modulation (PWM) for a voltage source inverter (VSI) offers flexibility in terms of different switching sequences. Numerical simulation is helpful to assess the performance of a PWM method before actual implementation. A quick-simulation tool to simulate a variety of space-vector-based PWM strategies for a two-level VSI-fed squirrel cage induction motor drive is presented. The simulator is developed using C and Python programming languages, and has a graphica...

  20. Comparison of strapdown inertial navigation algorithm based on rotation vector and dual quaternion

    Institute of Scientific and Technical Information of China (English)

    Wang Zhenhuan; Chen Xijun; Zeng Qingshuang

    2013-01-01

    For the navigation algorithm of the strapdown inertial navigation system,by comparing to the equations of the dual quaternion and quaternion,the superiority of the attitude algorithm based on dual quaternion over the ones based on rotation vector in accuracy is analyzed in the case of the rotation of navigation frame.By comparing the update algorithm of the gravitational velocity in dual quaternion solution with the compensation algorithm of the harmful acceleration in traditional velocity solution,the accuracy advantage of the gravitational velocity based on dual quaternion is addressed.In view of the idea of the attitude and velocity algorithm based on dual quaternion,an improved navigation algorithm is proposed,which is as much as the rotation vector algorithm in computational complexity.According to this method,the attitude quaternion does not require compensating as the navigation frame rotates.In order to verify the correctness of the theoretical analysis,simulations are carried out utilizing the software,and the simulation results show that the accuracy of the improved algorithm is approximately equal to the dual quaternion algorithm.

  1. Ecotope-Based Entomological Surveillance and Molecular Xenomonitoring of Multidrug Resistant Malaria Parasites in Anopheles Vectors

    Directory of Open Access Journals (Sweden)

    Prapa Sorosjinda-Nunthawarasilp

    2014-01-01

    Full Text Available The emergence and spread of multidrug resistant (MDR malaria caused by Plasmodium falciparum or Plasmodium vivax have become increasingly important in the Greater Mekong Subregion (GMS. MDR malaria is the heritable and hypermutable property of human malarial parasite populations that can decrease in vitro and in vivo susceptibility to proven antimalarial drugs as they exhibit dose-dependent drug resistance and delayed parasite clearance time in treated patients. MDR malaria risk situations reflect consequences of the national policy and strategy as this influences the ongoing national-level or subnational-level implementation of malaria control strategies in endemic GMS countries. Based on our experience along with current literature review, the design of ecotope-based entomological surveillance (EES and molecular xenomonitoring of MDR falciparum and vivax malaria parasites in Anopheles vectors is proposed to monitor infection pockets in transmission control areas of forest and forest fringe-related malaria, so as to bridge malaria landscape ecology (ecotope and ecotone and epidemiology. Malaria ecotope and ecotone are confined to a malaria transmission area geographically associated with the infestation of Anopheles vectors and particular environments to which human activities are related. This enables the EES to encompass mosquito collection and identification, salivary gland DNA extraction, Plasmodium- and species-specific identification, molecular marker-based PCR detection methods for putative drug resistance genes, and data management. The EES establishes strong evidence of Anopheles vectors carrying MDR P. vivax in infection pockets epidemiologically linked with other data obtained during which a course of follow-up treatment of the notified P. vivax patients receiving the first-line treatment was conducted. For regional and global perspectives, the EES would augment the epidemiological surveillance and monitoring of MDR falciparum and

  2. Flagellin Encoded in Gene-Based Vector Vaccines Is a Route-Dependent Immune Adjuvant.

    Science.gov (United States)

    Rady, Hamada F; Dai, Guixiang; Huang, Weitao; Shellito, Judd E; Ramsay, Alistair J

    2016-01-01

    Flagellin has been tested as a protein-based vaccine adjuvant, with the majority of studies focused on antibody responses. Here, we evaluated the adjuvant activity of flagellin for both cellular and humoral immune responses in BALB/c mice in the setting of gene-based immunization, and have made several novel observations. DNA vaccines and adenovirus (Ad) vectors were engineered to encode mycobacterial protein Ag85B, with or without flagellin of Salmonella typhimurium (FliC). DNA-encoded flagellin given IM enhanced splenic CD4+ and CD8+ T cell responses to co-expressed vaccine antigen, including memory responses. Boosting either IM or intranasally with Ad vectors expressing Ag85B without flagellin led to durable enhancement of Ag85B-specific antibody and CD4+ and CD8+ T cell responses in both spleen and pulmonary tissues, correlating with significantly improved protection against challenge with pathogenic aerosolized M. tuberculosis. However, inclusion of flagellin in both DNA prime and Ad booster vaccines induced localized pulmonary inflammation and transient weight loss, with route-dependent effects on vaccine-induced T cell immunity. The latter included marked reductions in levels of mucosal CD4+ and CD8+ T cell responses following IM DNA/IN Ad mucosal prime-boosting, although antibody responses were not diminished. These findings indicate that flagellin has differential and route-dependent adjuvant activity when included as a component of systemic or mucosally-delivered gene-based prime-boost immunization. Clear adjuvant activity for both T and B cell responses was observed when flagellin was included in the DNA priming vaccine, but side effects occurred when given in an Ad boosting vector, particularly via the pulmonary route. PMID:26844553

  3. Flagellin Encoded in Gene-Based Vector Vaccines Is a Route-Dependent Immune Adjuvant.

    Directory of Open Access Journals (Sweden)

    Hamada F Rady

    Full Text Available Flagellin has been tested as a protein-based vaccine adjuvant, with the majority of studies focused on antibody responses. Here, we evaluated the adjuvant activity of flagellin for both cellular and humoral immune responses in BALB/c mice in the setting of gene-based immunization, and have made several novel observations. DNA vaccines and adenovirus (Ad vectors were engineered to encode mycobacterial protein Ag85B, with or without flagellin of Salmonella typhimurium (FliC. DNA-encoded flagellin given IM enhanced splenic CD4+ and CD8+ T cell responses to co-expressed vaccine antigen, including memory responses. Boosting either IM or intranasally with Ad vectors expressing Ag85B without flagellin led to durable enhancement of Ag85B-specific antibody and CD4+ and CD8+ T cell responses in both spleen and pulmonary tissues, correlating with significantly improved protection against challenge with pathogenic aerosolized M. tuberculosis. However, inclusion of flagellin in both DNA prime and Ad booster vaccines induced localized pulmonary inflammation and transient weight loss, with route-dependent effects on vaccine-induced T cell immunity. The latter included marked reductions in levels of mucosal CD4+ and CD8+ T cell responses following IM DNA/IN Ad mucosal prime-boosting, although antibody responses were not diminished. These findings indicate that flagellin has differential and route-dependent adjuvant activity when included as a component of systemic or mucosally-delivered gene-based prime-boost immunization. Clear adjuvant activity for both T and B cell responses was observed when flagellin was included in the DNA priming vaccine, but side effects occurred when given in an Ad boosting vector, particularly via the pulmonary route.

  4. Face Recognition Based on Support Vector Machine and Nearest Neighbor Classifier

    Institute of Scientific and Technical Information of China (English)

    张燕昆; 刘重庆

    2003-01-01

    Support vector machine (SVM), as a novel approach in pattern recognition, has demonstrated a success in face detection and face recognition. In this paper, a face recognition approach based on the SVM classifier with the nearest neighbor classifier (NNC) is proposed. The principal component analysis (PCA) is used to reduce the dimension and extract features. Then one-against-all stratedy is used to train the SVM classifiers. At the testing stage, we propose an algorithm by combining SVM classifier with NNC to improve the correct recognition rate. We conduct the experiment on the Cambridge ORL face database. The result shows that our approach outperforms the standard eigenface approach and some other approaches.

  5. Hydroxyl PAMAM dendrimer-based gene vectors for transgene delivery to human retinal pigment epithelial cells

    Science.gov (United States)

    Mastorakos, Panagiotis; Kambhampati, Siva P.; Mishra, Manoj K.; Wu, Tony; Song, Eric; Hanes, Justin; Kannan, Rangaramanujam M.

    2015-02-01

    Ocular gene therapy holds promise for the treatment of numerous blinding disorders. Despite the significant progress in the field of viral and non-viral gene delivery to the eye, significant obstacles remain in the way of achieving high-level transgene expression without adverse effects. The retinal pigment epithelium (RPE) is involved in the pathogenesis of retinal diseases and is a key target for a number of gene-based therapeutics. In this study, we addressed the inherent drawbacks of non-viral gene vectors and combined different approaches to design an efficient and safe dendrimer-based gene-delivery platform for delivery to human RPE cells. We used hydroxyl-terminated polyamidoamine (PAMAM) dendrimers functionalized with various amounts of amine groups to achieve effective plasmid compaction. We further used triamcinolone acetonide (TA) as a nuclear localization enhancer for the dendrimer-gene complex and achieved significant improvement in cell uptake and transfection of hard-to-transfect human RPE cells. To improve colloidal stability, we further shielded the gene vector surface through incorporation of PEGylated dendrimer along with dendrimer-TA for DNA complexation. The resultant complexes showed improved stability while minimally affecting transgene delivery, thus improving the translational relevance of this platform.Ocular gene therapy holds promise for the treatment of numerous blinding disorders. Despite the significant progress in the field of viral and non-viral gene delivery to the eye, significant obstacles remain in the way of achieving high-level transgene expression without adverse effects. The retinal pigment epithelium (RPE) is involved in the pathogenesis of retinal diseases and is a key target for a number of gene-based therapeutics. In this study, we addressed the inherent drawbacks of non-viral gene vectors and combined different approaches to design an efficient and safe dendrimer-based gene-delivery platform for delivery to human RPE

  6. Fast Matrix Computation Algorithms Based on Rough Attribute Vector Tree Method in RDSS

    Institute of Scientific and Technical Information of China (English)

    2005-01-01

    The concepts of Rough Decision Support System (RDSS)and equivalence matrix are introduced in this paper. Based on a rough attribute vector tree (RAVT) method, two kinds of matrix computation algorithms - Recursive Matrix Computation (RMC) and Parallel Matrix Computation (PMC) are proposed for rules extraction, attributes reduction and data cleaning finished synchronously. The algorithms emphasize the practicability and efficiency of rules generation. A case study of PMC is analyzed, and a comparison experiment of RMC algorithm shows that it is feasible and efficient for data mining and knowledge-discovery in RDSS.

  7. Parallelization of automatic classification systems based on support vector machines: Comparison and application to JET database

    International Nuclear Information System (INIS)

    In learning machines, the larger the training dataset the better model can be obtained. Therefore, the training phase can be very demanding in terms of computational time in mono-processor computers. To overcome this difficulty, codes should be parallelized. This article describes two general purpose parallelization techniques of a classification system based on support vector machines (SVM). Both of them have been applied to the recognition of the L-H confinement regime in JET. This has allowed reducing the training computation time from 70 h to 3 min.

  8. Application of frequency estimation algorithm based on a single vector sensor in underwater acoustic communication

    Institute of Scientific and Technical Information of China (English)

    QIAO Gang; ZHANG Xiao-ping; ZHAO Xin

    2006-01-01

    A method of high resolution frequency estimation based on a single vector sensor using ESPRIT (Estimating Signal Parameters via Rotational Invariance Techniques) algorithm is proposed and applied to the underwater acoustic (UWA) communication system of frequency modulation. Higher resolution frequency estimation can be obtained by this algorithm using fewer snapshots comparing with the sound intensity frequency estimation. Results of simulation and lake experiment show that the proposed algorithm can improve the communication data rate and reduce the bandwidth of the system.Because higher signal-to-noise ratio (SNR) is demanded, this algorithm can be used in high speed short range UWA communication at present.

  9. STATE SPACE POINT DISTRIBUTION PARAMETER FOR SUPPORT VECTOR MACHINE BASED CV UNIT CLASSIFICATION

    Directory of Open Access Journals (Sweden)

    N K Narayanan

    2012-01-01

    Full Text Available In this paper we extend Support Vector Machines (SVM for speaker independent Consonant – Vowel (CV unit classification. Here we adopt the technique known as Decision Directed Acyclic Graph (DDAG , which is used to combine many two class classifiers into multiclass classifier. Using Reconstructed State Space (RSS based State Space Point Distribution (SSPD parameters, we obtain an average speaker independent phoneme recognition accuracy of 90% on the Malayalam V/CV speech unit database. The recognition results indicate that this method is efficient and can be adopted for developing a complete speech recognition system for Malayalam language.

  10. A response surface method based on support vector machines trained with an adaptive experimental design

    International Nuclear Information System (INIS)

    Structural reliability is nowadays largely used to take into account uncertainties related to the input data of a structural model. When the structural response becomes complex, the mechanical model is designed within the framework of the finite element method and therefore, the computational time required by a coupling reliability/finite element analysis is driven by the number of performance function calls. This paper aims at proposing an original approach to approximate implicit limit state functions. It is based on the support vector machine used in regression trained with an adaptive experimental design. Several numerical examples proposed in the published literature are considered to assess the efficiency of the proposed method. (authors)

  11. Design optical antenna and fiber coupling system based on the vector theory of reflection and refraction.

    Science.gov (United States)

    Jiang, Ping; Yang, Huajun; Mao, Shengqian

    2015-10-01

    A Cassegrain antenna system and an optical fiber coupling system which consists of a plano-concave lens and a plano-convex lens are designed based on the vector theory of reflection and refraction, so as to improve the transmission performance of the optical antenna and fiber coupling system. Three-dimensional ray tracing simulation are performed and results of the optical aberrations calculation and the experimental test show that the aberrations caused by on-axial defocusing, off-axial defocusing and deflection of receiving antenna can be well corrected by the optical fiber coupling system. PMID:26480125

  12. Local Sequence Information-based Support Vector Machine to Classify Voltage-gated Potassium Channels

    Institute of Scientific and Technical Information of China (English)

    Li-Xia LIU; Meng-Long LI; Fu-Yuan TAN; Min-Chun LU; Ke-Long WANG; Yan-Zhi GUO; Zhi-Ning WEN; Lin JIANG

    2006-01-01

    In our previous work, we developed a computational tool, PreK-ClassK-ClassKv, to predict and classify potassium (K+) channels. For K+ channel prediction (PreK) and classification at family level (ClassK), this method performs well. However, it does not perform so well in classifying voltage-gated potassium (Kv) channels (ClassKv). In this paper, a new method based on the local sequence information of Kv channels is introduced to classify Kv channels. Six transmembrane domains of a Kv channel protein are used to define a protein, and the dipeptide composition technique is used to transform an amino acid sequence to a numerical sequence. A Kv channel protein is represented by a vector with 2000 elements, and a support vector machine algorithm is applied to classify Kv channels. This method shows good performance with averages of total accuracy (Acc), sensitivity (SE), specificity (SP); reliability (R) and Matthews correlation coefficient (MCC) of 98.0%, 89.9%, 100%, 0.95 and 0.94 respectively. The results indicate that the local sequence information-based method is better than the global sequence information-based method to classify Kv channels.

  13. Cross-Layer Optimization of MIMO-Based Mesh Networks with Gaussian Vector Broadcast Channels

    CERN Document Server

    Liu, Jia

    2007-01-01

    MIMO technology is one of the most significant advances in the past decade to increase channel capacity and has a great potential to improve network capacity for mesh networks. In a MIMO-based mesh network, the links outgoing from each node sharing the common communication spectrum can be modeled as a Gaussian vector broadcast channel. Recently, researchers showed that ``dirty paper coding'' (DPC) is the optimal transmission strategy for Gaussian vector broadcast channels. So far, there has been little study on how this fundamental result will impact the cross-layer design for MIMO-based mesh networks. To fill this gap, we consider the problem of jointly optimizing DPC power allocation in the link layer at each node and multihop/multipath routing in a MIMO-based mesh networks. It turns out that this optimization problem is a very challenging non-convex problem. To address this difficulty, we transform the original problem to an equivalent problem by exploiting the channel duality. For the transformed problem,...

  14. 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.

  15. Factors affecting learning of vector math from computer-based practice: Feedback complexity and prior knowledge

    Science.gov (United States)

    Heckler, Andrew F.; Mikula, Brendon D.

    2016-06-01

    In experiments including over 450 university-level students, we studied the effectiveness and time efficiency of several levels of feedback complexity in simple, computer-based training utilizing static question sequences. The learning domain was simple vector math, an essential skill in introductory physics. In a unique full factorial design, we studied the relative effects of "knowledge of correct response" feedback and "elaborated feedback" (i.e., a general explanation) both separately and together. A number of other factors were analyzed, including training time, physics course grade, prior knowledge of vector math, and student beliefs about both their proficiency in and the importance of vector math. We hypothesize a simple model predicting how the effectiveness of feedback depends on prior knowledge, and the results confirm this knowledge-by-treatment interaction. Most notably, elaborated feedback is the most effective feedback, especially for students with low prior knowledge and low course grade. In contrast, knowledge of correct response feedback was less effective for low-performing students, and including both kinds of feedback did not significantly improve performance compared to elaborated feedback alone. Further, while elaborated feedback resulted in higher scores, the learning rate was at best only marginally higher because the training time was slightly longer. Training time data revealed that students spent significantly more time on the elaborated feedback after answering a training question incorrectly. Finally, we found that training improved student self-reported proficiency and that belief in the importance of the learned domain improved the effectiveness of training. Overall, we found that computer based training with static question sequences and immediate elaborated feedback in the form of simple and general explanations can be an effective way to improve student performance on a physics essential skill, especially for less prepared and low

  16. The behaviour of conjugate gradient based algorithms on a multi-vector processor with a memory hierarchy

    Energy Technology Data Exchange (ETDEWEB)

    Jalby, W.; Meier, U.; Sameh, A.

    1986-11-23

    The conjugate gradient algorithm is one of the most efficient solvers for elliptic partial differential equations and has been successfully implemented on various vector computers. In this paper, the behaviour of conjugate gradient based algorithms on a multi-vector processor with a two-level memory hierarchy is investigated. Several domain decomposition techniques are considered as well as preconditioners that are suitable to be parallelized such as polynomial preconditioners or a vectorized version of the ICCG. Experimental results for the Poisson equation performed on an Alliant FX/8 are presented. 16 refs., 17 figs., 13 tabs.

  17. 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.

  18. Research on bearing life prediction based on support vector machine and its application

    International Nuclear Information System (INIS)

    Life prediction of rolling element bearing is the urgent demand in engineering practice, and the effective life prediction technique is beneficial to predictive maintenance. Support vector machine (SVM) is a novel machine learning method based on statistical learning theory, and is of advantage in prediction. This paper develops SVM-based model for bearing life prediction. The inputs of the model are features of bearing vibration signal and the output is the bearing running time-bearing failure time ratio. The model is built base on a few failed bearing data, and it can fuse information of the predicted bearing. So it is of advantage to bearing life prediction in practice. The model is applied to life prediction of a bearing, and the result shows the proposed model is of high precision.

  19. Settlement Prediction of Road Soft Foundation Using a Support Vector Machine (SVM Based on Measured Data

    Directory of Open Access Journals (Sweden)

    Yu Huiling

    2016-01-01

    Full Text Available The suppor1t vector machine (SVM is a relatively new artificial intelligence technique which is increasingly being applied to geotechnical problems and is yielding encouraging results. SVM is a new machine learning method based on the statistical learning theory. A case study based on road foundation engineering project shows that the forecast results are in good agreement with the measured data. The SVM model is also compared with BP artificial neural network model and traditional hyperbola method. The prediction results indicate that the SVM model has a better prediction ability than BP neural network model and hyperbola method. Therefore, settlement prediction based on SVM model can reflect actual settlement process more correctly. The results indicate that it is effective and feasible to use this method and the nonlinear mapping relation between foundation settlement and its influence factor can be expressed well. It will provide a new method to predict foundation settlement.

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

    Directory of Open Access Journals (Sweden)

    Lara del Val

    2015-06-01

    Full Text Available 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.

  1. MULTI-VIEW FACE DETECTION BASED ON KERNEL PRINCIPAL COMPONENT ANALYSIS AND KERNEL SUPPORT VECTOR TECHNIQUES

    Directory of Open Access Journals (Sweden)

    Muzhir Shaban Al-Ani

    2011-05-01

    Full Text Available Detecting faces across multiple views is more challenging than in a frontal view. To address this problem,an efficient approach is presented in this paper using a kernel machine based approach for learning suchnonlinear mappings to provide effective view-based representation for multi-view face detection. In thispaper Kernel Principal Component Analysis (KPCA is used to project data into the view-subspaces thencomputed as view-based features. Multi-view face detection is performed by classifying each input imageinto face or non-face class, by using a two class Kernel Support Vector Classifier (KSVC. Experimentalresults demonstrate successful face detection over a wide range of facial variation in color, illuminationconditions, position, scale, orientation, 3D pose, and expression in images from several photo collections.

  2. Experimental Study on MUSIC-Based DOA Estimation by Using Universal Steering Vector

    Science.gov (United States)

    Yuan, Qiaowei; Chen, Qiang; Sawaya, Kunio

    MUSIC-based estimation of direction of arrival (DOA) using universal steering vector (USV) is experimentally studied. A four-element array antenna and a four-channel receiver are employed for the experiment. In order to improve the accuracy of DOA estimation, USV which has already included the effect of mutual coupling between array elements and effect of array elements themselves is compensated to further include the electric delay and loss of four channels in the receiver. The compensated USV (C-USV) approach proposed in this paper does not need the time-consuming measurement of array element pattern because the compensating matrix for USV is obtained by measuring the S parameters between RF input ports of the feeding cables and IF output ports of the receiver. The experimental results of MUSIC-based DOA estimation show that C-USV approach is an accurate, effective and practical method for the MUSIC-based DOA estimation.

  3. Double-stranded RNA transcribed from vector-based oligodeoxynucleotide acts as transcription factor decoy

    International Nuclear Information System (INIS)

    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

  4. 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.

  5. 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.

  6. Clifford algebra-based structure filtering analysis for geophysical vector fields

    Science.gov (United States)

    Yu, Z.; Luo, W.; Yi, L.; Hu, Y.; Yuan, L.

    2013-07-01

    A new Clifford algebra-based vector field filtering method, which combines amplitude similarity and direction difference synchronously, is proposed. Firstly, a modified correlation product is defined by combining the amplitude similarity and direction difference. Then, a structure filtering algorithm is constructed based on the modified correlation product. With custom template and thresholds applied to the modulus and directional fields independently, our approach can reveal not only the modulus similarities but also the classification of the angular distribution. Experiments on exploring the tempo-spatial evolution of the 2002-2003 El Niño from the global wind data field are used to test the algorithm. The results suggest that both the modulus similarity and directional information given by our approach can reveal the different stages and dominate factors of the process of the El Niño evolution. Additional information such as the directional stability of the El Niño can also be extracted. All the above suggest our method can provide a new powerful and applicable tool for geophysical vector field analysis.

  7. Clifford algebra-based structure filtering analysis for geophysical vector fields

    Directory of Open Access Journals (Sweden)

    Z. Yu

    2013-07-01

    Full Text Available A new Clifford algebra-based vector field filtering method, which combines amplitude similarity and direction difference synchronously, is proposed. Firstly, a modified correlation product is defined by combining the amplitude similarity and direction difference. Then, a structure filtering algorithm is constructed based on the modified correlation product. With custom template and thresholds applied to the modulus and directional fields independently, our approach can reveal not only the modulus similarities but also the classification of the angular distribution. Experiments on exploring the tempo-spatial evolution of the 2002–2003 El Niño from the global wind data field are used to test the algorithm. The results suggest that both the modulus similarity and directional information given by our approach can reveal the different stages and dominate factors of the process of the El Niño evolution. Additional information such as the directional stability of the El Niño can also be extracted. All the above suggest our method can provide a new powerful and applicable tool for geophysical vector field analysis.

  8. A Discriminant Distance Based Composite Vector Selection Method for Odor Classification

    OpenAIRE

    Sang-Il Choi; Gu-Min Jeong

    2014-01-01

    We present a composite vector selection method for an effective electronic nose system that performs well even in noisy environments. Each composite vector generated from a electronic nose data sample is evaluated by computing the discriminant distance. By quantitatively measuring the amount of discriminative information in each composite vector, composite vectors containing informative variables can be distinguished and the final composite features for odor classification are extracted using...

  9. 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

  10. In vivo image analysis of BoHV-4-based vector in mice.

    Directory of Open Access Journals (Sweden)

    Valentina Franceschi

    Full Text Available Due to its biological characteristics bovine herpesvirus 4 (BoHV-4 has been considered as an appropriate gene delivery vector. Its genomic clone, modified as a bacterial artificial chromosome (BAC, is better genetically manipulable and can be used as an efficient gene delivery and vaccine vector. Although a large amount of data have been accumulated in vitro on this specific aspect, the same cannot be asserted for the in vivo condition. Therefore, here we investigated the fate of a recombinant BoHV-4 strain expressing luciferase (BoHV-4-A-CMVlucΔTK after intraperitoneal or intravenous inoculation in mice, by generating a novel recombinant BoHV-4 expressing luciferase (BoHV-4-A-CMVlucΔTK and by following the virus replication through in vivo imaging analysis. BoHV-4-A-CMVlucΔTK was first characterized in vitro where it was shown, on one hand that its replication properties are identical to those of the parental virus, and on the other that the transduced/infected cells strongly express luciferase. When BoHV-4-A-CMVlucΔTK was inoculated in mice, either intraperitoneally or intravenously, BoHV-4-A-CMVlucΔTK infection/transduction was exclusively localized to the liver, as detected by in vivo image analysis, and in particular almost exclusively in the hepatocytes, as determined by immuno-histochemistry. These data, that add a new insight on the biology of BoHV-4 in vivo, provide the first indication for the potential use of a BoHV-4-based vector in gene-transfer in the liver.

  11. Improvement of avian leukosis virus (ALV)-based retrovirus vectors by using different cis-acting sequences from ALVs.

    OpenAIRE

    Cosset, F L; Legras, C.; Thomas, J.L.; Molina, R. M.; Chebloune, Y; Faure, C.; Nigon, V M; Verdier, G

    1991-01-01

    Production and expression of double-expression vectors which transduce both Neo(r) and lacZ genes and are based on the structure of avian leukosis virus were enhanced by using cis-acting sequences (long terminal repeats and noncoding sequences) from Rous-associated virus-1 and Rous-associated virus-2 rather than those of avian erythroblastosis virus previously used in our constructs. Polyclonal producer cells obtained after transfection of these vectors into the Isolde packaging cell line gav...

  12. Hybrid-parallel sparse matrix-vector multiplication with explicit communication overlap on current multicore-based systems

    OpenAIRE

    Schubert, Gerald; Fehske, Holger; Hager, Georg; Wellein, Gerhard

    2011-01-01

    We evaluate optimized parallel sparse matrix-vector operations for several representative application areas on widespread multicore-based cluster configurations. First the single-socket baseline performance is analyzed and modeled with respect to basic architectural properties of standard multicore chips. Beyond the single node, the performance of parallel sparse matrix-vector operations is often limited by communication overhead. Starting from the observation that nonblocking MPI is not able...

  13. Opportunities for improved chagas disease vector control based on knowledge, attitudes and practices of communities in the yucatan peninsula, Mexico.

    Directory of Open Access Journals (Sweden)

    Kathryn Rosecrans

    2014-03-01

    Full Text Available BACKGROUND: Chagas disease is a vector-borne parasitic disease of major public health importance. Current prevention efforts are based on triatomine vector control to reduce transmission to humans. Success of vector control interventions depends on their acceptability and value to affected communities. We aimed to identify opportunities for and barriers to improved vector control strategies in the Yucatan peninsula, Mexico. METHODOLOGY/PRINCIPAL FINDINGS: We employed a sequence of qualitative and quantitative research methods to investigate knowledge, attitudes and practices surrounding Chagas disease, triatomines and vector control in three rural communities. Our combined data show that community members are well aware of triatomines and are knowledgeable about their habits. However, most have a limited understanding of the transmission dynamics and clinical manifestations of Chagas disease. While triatomine control is not a priority for community members, they frequently use domestic insecticide products including insecticide spray, mosquito coils and plug-in repellents. Families spend about $32 US per year on these products. Alternative methods such as yard cleaning and window screens are perceived as desirable and potentially more effective. Screens are nonetheless described as unaffordable, in spite of a cost comparable to the average annual spending on insecticide products. CONCLUSION/SIGNIFICANCE: Further education campaigns and possibly financing schemes may lead families to redirect their current vector control spending from insecticide products to window screens. Also, synergism with mosquito control efforts should be further explored to motivate community involvement and ensure sustainability of Chagas disease vector control.

  14. High expression of hepatitis B virus based vector with reporter gene in hepatitis B virus infection system

    Institute of Scientific and Technical Information of China (English)

    Shi-Hong Li; Wen-Ge Huang; Bing Huang; Xi-Gu Chen

    2007-01-01

    AIM: To construct a hepatitis B virus (HBV)-based vector with a reporter gene and to establish an HBV infection system to evaluate the availability of the vector.METHODS: The HBV-based vectors with green fluorescence protein (GFP) were packaged into the liver of immunodeficient mice through transfer and helper plasmid using hydrodynamic technology. Wild type HBV (wt HBV) was provided by plasmid MC2009. Primary human hepatocytes (PHH) were isolated and infected with recombinant HBV (rHBV) or wt HBV. GFP expression was monitored by confocal and flow cytometry. HBV DNA and HBV surface antigen (HBSAg) were analyzed by PCR and ELISA.RESULTS: 3 × 107 wt HBV copies/mL and 5 × 106 rHBV copies/mL were collected from mice serum. In the wt HBV infected group, HBV progeny was 2 × 107 copies/mL and HBSAg was 770 ng/mL. In the rHBV infected group, GFP fluorescence was detected on d 3 post-infection and over 85% of the parenchymal cells expressed green fluorescence on d 12 post-infection. Compared with wt HBV in the PHH infection system, no rHBV DNA or HBSAg were detected in PHH culture media.CONCLUSION: An effective HBV based vector was developed, which proved to be a useful HBV infection system. This vector and infection system can be applied to develop a therapeutic vector and study the HBV life cycle and viral pathogenesis.

  15. Relevance Vector Machines for Enhanced BER Probability in DMT-Based Systems

    Directory of Open Access Journals (Sweden)

    Ashraf A. Tahat

    2010-01-01

    Full Text Available A new channel estimation method for discrete multitone (DMT communication system based on sparse Bayesian learning relevance vector machine (RVM method is presented. The Bayesian frame work is used to obtain sparse solutions for regression tasks with linear models. By exploiting a probabilistic Bayesian learning framework, sparse Bayesian learning provides accurate models for estimation and consequently equalization. We consider frequency domain equalization (FEQ using the proposed channel estimate at both the transmitter (preequalization and receiver (postequalization and compare the resulting bit error rate (BER performance curves for both approaches and various channel estimation techniques. Simulation results show that the proposed RVM-based method is superior to the traditional least squares technique.

  16. Bearing Degradation Process Prediction Based on the Support Vector Machine and Markov Model

    Directory of Open Access Journals (Sweden)

    Shaojiang Dong

    2014-01-01

    Full Text Available Predicting the degradation process of bearings before they reach the failure threshold is extremely important in industry. This paper proposed a novel method based on the support vector machine (SVM and the Markov model to achieve this goal. Firstly, the features are extracted by time and time-frequency domain methods. However, the extracted original features are still with high dimensional and include superfluous information, and the nonlinear multifeatures fusion technique LTSA is used to merge the features and reduces the dimension. Then, based on the extracted features, the SVM model is used to predict the bearings degradation process, and the CAO method is used to determine the embedding dimension of the SVM model. After the bearing degradation process is predicted by SVM model, the Markov model is used to improve the prediction accuracy. The proposed method was validated by two bearing run-to-failure experiments, and the results proved the effectiveness of the methodology.

  17. Vector rectangular-shape laser based on reduced graphene oxide interacting with long fiber taper

    CERN Document Server

    Gao, Lei; Zeng, Jing; Huang, Wei; Liu, Min

    2014-01-01

    A vector dual-wavelength rectangular-shape laser (RSL) based on a long fiber taper deposited with reduced graphene oxide is proposed, where the nonlinearity is enhanced due to large evanescent-field-interacting length and strong field confinement of a 8 mm fiber taper with a waist diameter of 4 micronmeters. Graphene flakes are deposited uniformly on the taper waist with light pressure effect, so this structure guarantees both excellent saturable absorption and high nonlinearity. The RSL with a repetition rate of 7.9 MHz exhibits fast polarization switching in two orthogonal polarization directions, and the temporal and spectral characteristics are investigated. The results suggest that the long taper-based graphene structure is an efficient choice for nonlinear devices.

  18. Combining Self-organizing Feature Map with Support Vector Regression Based on Expert System

    Institute of Scientific and Technical Information of China (English)

    WANGLing; MUZhi-Chun; GUOHui

    2005-01-01

    A new approach is proposed to model nonlinear dynamic systems by combining SOM(self-organizing feature map) with support vector regression (SVR) based on expert system. The whole system has a two-stage neural network architecture. In the first stage SOM is used as a clustering algorithm to partition the whole input space into several disjointed regions. A hierarchical architecture is adopted in the partition to avoid the problem of predetermining the number of partitioned regions. Then, in the second stage, multiple SVR, also called SVR experts, that best fit each partitioned region by the combination of different kernel function of SVR and promote the configuration and tuning of SVR. Finally, to apply this new approach to time-series prediction problems based on the Mackey-Glass differential equation and Santa Fe data, the results show that SVR experts has effective improvement in the generalization performance in comparison with the single SVR model.

  19. Anomaly Detection System Based on Principal Component Analysis and Support Vector Machine

    Institute of Scientific and Technical Information of China (English)

    LI Zhanchun; LI Zhitang; LIU Bin

    2006-01-01

    This article presents an anomaly detection system based on principal component analysis (PCA) and support vector machine (SVM). The system first creates a profile defining a normal behavior by frequency-based scheme, and then compares the similarity of a current behavior with the created profile to decide whether the input instance is normal or anomaly. In order to avoid overfitting and reduce the computational burden, normal behavior principal features are extracted by the PCA method. SVM is used to distinguish normal or anomaly for user behavior after training procedure has been completed by learning. In the experiments for performance evaluation the system achieved a correct detection rate equal to 92.2% and a false detection rate equal to 2.8%.

  20. A reliability assessment method based on support vector machines for CNC equipment

    Institute of Scientific and Technical Information of China (English)

    WU Jun; DENG Chao; SHAO XinYu; XIE S Q

    2009-01-01

    With the applications of high technology, a catastrophic failure of CNC equipment rarely occurs at normal operation conditions. So it is difficult for traditional reliability assessment methods based on time-to-failure distributions to deduce the reliability level. This paper presents a novel reliability assessment methodology to estimate the reliability level of equipment with machining performance degradation data when only a few samples are available. The least squares support vector machines(LS-SVM) are introduced to analyze the performance degradation process on the equipment. A two-stage parameter optimization and searching method is proposed to improve the LS-SVM regression performance and a reliability assessment model based on the LS-SVM is built. A machining performance degradation experiment has been carried out on an OTM650 machine tool to validate the effectiveness of the proposed reliability assessment methodology.

  1. Support-vector-based emergent self-organising approach for emotional understanding

    Science.gov (United States)

    Nguwi, Yok-Yen; Cho, Siu-Yeung

    2010-12-01

    This study discusses the computational analysis of general emotion understanding from questionnaires methodology. The questionnaires method approaches the subject by investigating the real experience that accompanied the emotions, whereas the other laboratory approaches are generally associated with exaggerated elements. We adopted a connectionist model called support-vector-based emergent self-organising map (SVESOM) to analyse the emotion profiling from the questionnaires method. The SVESOM first identifies the important variables by giving discriminative features with high ranking. The classifier then performs the classification based on the selected features. Experimental results show that the top rank features are in line with the work of Scherer and Wallbott [(1994), 'Evidence for Universality and Cultural Variation of Differential Emotion Response Patterning', Journal of Personality and Social Psychology, 66, 310-328], which approached the emotions physiologically. While the performance measures show that using the full features for classifications can degrade the performance, the selected features provide superior results in terms of accuracy and generalisation.

  2. Assessment Method of Harmonic Emission Level Based on the Improved Weighted Support Vector Machine Regression

    Science.gov (United States)

    Jiang, Wei-Zhong; Su, Ning; Ding, Li-Ping; Qiu, Si-Yu

    This paper presents a new method to estimate the system harmonic impedance and the harmonic emission level based on the improved weighted support vector machine (WSVM) regression. According to the differences of harmonic measurement data at the point of common coupling, the WSVM can be obtained by correcting the error requirement of SVM by Euclidean distance as a weighted index and determining the weighted coefficient of penalty parameter by linear interpolation, then the system harmonic impedance and the harmonic emission level can be calculated. Based on analyzing the simulation of the circuit and the practical application of field data, it proves that the proposed method can effectively restrain the influence caused by the fluctuation of background harmonic on estimation results. Compared with other methods, the estimate result of the proposed method is more reasonable.

  3. A reliability assessment method based on support vector machines for CNC equipment

    Institute of Scientific and Technical Information of China (English)

    2009-01-01

    With the applications of high technology,a catastrophic failure of CNC equipment rarely occurs at normal operation conditions.So it is difficult for traditional reliability assessment methods based on time-to-failure distributions to deduce the reliability level.This paper presents a novel reliability assessment methodology to estimate the reliability level of equipment with machining performance degradation data when only a few samples are available.The least squares support vector machines(LS-SVM) are introduced to analyze the performance degradation process on the equipment.A two-stage parameter optimization and searching method is proposed to improve the LS-SVM regression performance and a reliability assessment model based on the LS-SVM is built.A machining performance degradation experiment has been carried out on an OTM650 machine tool to validate the effectiveness of the proposed reliability assessment methodology.

  4. New Metric Based Algorithm for Test Vector Generation in VLSI Testing

    Directory of Open Access Journals (Sweden)

    M. V. Atre

    1995-07-01

    Full Text Available A new algorithm for test-vector-generation (TVG for combinational circuits has been presented for testing VLSI chips. This is done by defining a suitable metric or distance, in the space of all input vectors, between a vector and a set of vectors. The test vectors are generated by suitably maximising the above distance. Two different methods of maximising the distance are suggested. Performances of the two methods for different circuits are presented and compared with the random method of TVG. It was observed that method B is superior to the other two methods. Also, method A is slightly better than method R.

  5. The development of vector based 2.5D print methods for a painting machine

    Science.gov (United States)

    Parraman, Carinna

    2013-02-01

    Through recent trends in the application of digitally printed decorative finishes to products, CAD, 3D additive layer manufacturing and research in material perception, [1, 2] there is a growing interest in the accurate rendering of materials and tangible displays. Although current advances in colour management and inkjet printing has meant that users can take for granted high-quality colour and resolution in their printed images, digital methods for transferring a photographic coloured image from screen to paper is constrained by pixel count, file size, colorimetric conversion between colour spaces and the gamut limits of input and output devices. This paper considers new approaches to applying alternative colour palettes by using a vector-based approach through the application of paint mixtures, towards what could be described as a 2.5D printing method. The objective is to not apply an image to a textured surface, but where texture and colour are integral to the mark, that like a brush, delineates the contours in the image. The paper describes the difference between the way inks and paints are mixed and applied. When transcribing the fluid appearance of a brush stroke, there is a difference between a halftone printed mark and a painted mark. The issue of surface quality is significant to subjective qualities when studying the appearance of ink or paint on paper. The paper provides examples of a range of vector marks that are then transcribed into brush stokes by the painting machine.

  6. Support vector machine based classification of fast Fourier transform spectroscopy of proteins

    Science.gov (United States)

    Lazarevic, Aleksandar; Pokrajac, Dragoljub; Marcano, Aristides; Melikechi, Noureddine

    2009-02-01

    Fast Fourier transform spectroscopy has proved to be a powerful method for study of the secondary structure of proteins since peak positions and their relative amplitude are affected by the number of hydrogen bridges that sustain this secondary structure. However, to our best knowledge, the method has not been used yet for identification of proteins within a complex matrix like a blood sample. The principal reason is the apparent similarity of protein infrared spectra with actual differences usually masked by the solvent contribution and other interactions. In this paper, we propose a novel machine learning based method that uses protein spectra for classification and identification of such proteins within a given sample. The proposed method uses principal component analysis (PCA) to identify most important linear combinations of original spectral components and then employs support vector machine (SVM) classification model applied on such identified combinations to categorize proteins into one of given groups. Our experiments have been performed on the set of four different proteins, namely: Bovine Serum Albumin, Leptin, Insulin-like Growth Factor 2 and Osteopontin. Our proposed method of applying principal component analysis along with support vector machines exhibits excellent classification accuracy when identifying proteins using their infrared spectra.

  7. Carbohydrate-Based Ice Recrystallization Inhibitors Increase Infectivity and Thermostability of Viral Vectors

    Science.gov (United States)

    Ghobadloo, Shahrokh M.; Balcerzak, Anna K.; Gargaun, Ana; Muharemagic, Darija; Mironov, Gleb G.; Capicciotti, Chantelle J.; Briard, Jennie G.; Ben, Robert N.; Berezovski, Maxim V.

    2014-07-01

    The inability of vaccines to retain sufficient thermostability has been an obstacle to global vaccination programs. To address this major limitation, we utilized carbohydrate-based ice recrystallization inhibitors (IRIs) to eliminate the cold chain and stabilize the potency of Vaccinia virus (VV), Vesicular Stomatitis virus (VSV) and Herpes virus-1 (HSV-1). The impact of these IRIs was tested on the potency of the viral vectors using a plaque forming unit assay following room temperature storage, cryopreservation with successive freeze-thaw cycles and lyophilization. Viral potency after storage with all three conditions demonstrated that N-octyl-gluconamide (NOGlc) recovered the infectivity of shelf stored VV, 5.6 Log10 PFU mL-1 during 40 days, and HSV-1, 2.7 Log10 PFU mL-1 during 9 days. Carbon-linked antifreeze glycoprotein analogue ornithine-glycine-glycine-galactose (OGG-Gal) increases the recovery of VV and VSV more than 1 Log10 PFU mL-1 after 10 freeze-thaw cycles. In VSV, cryostorage with OGG-Gal maintains high infectivity and reduces temperature-induced aggregation of viral particles by 2 times that of the control. In total, OGG-Gal and NOGlc preserve virus potency during cryostorage. Remarkably, NOGlc has potential to eliminate the cold chain and permit room temperature storage of viral vectors.

  8. 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. PMID:23912835

  9. 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.

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

    International Nuclear Information System (INIS)

    Highlights: → The structure of the permanent magnet linear synchronous motor (SW-PMLSM) is new. → A new current control method CEVPC is employed in this motor. → The sectional power supply method is different to the others and effective. → 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.

  11. Normal mammogram detection based on local probability difference transforms and support vector machines

    International Nuclear Information System (INIS)

    Automatic detection of normal mammograms, as a ''first look'' for breast cancer, is a new approach to computer-aided diagnosis. This approach may be limited, however, by two main causes. The first problem is the presence of poorly separable ''crossed-distributions'' in which the correct classification depends upon the value of each feature. The second problem is overlap of the feature distributions that are extracted from digitized mammograms of normal and abnormal patients. Here we introduce a new Support Vector Machine (SVM) based method utilizing with the proposed uncrossing mapping and Local Probability Difference (LPD). Crossed-distribution feature pairs are identified and mapped into a new features that can be separated by a zero-hyperplane of the new axis. The probability density functions of the features of normal and abnormal mammograms are then sampled and the local probability difference functions are estimated to enhance the features. From 1,000 ground-truth-known mammograms, 250 normal and 250 abnormal cases, including spiculated lesions, circumscribed masses or microcalcifications, are used for training a support vector machine. The classification results tested with another 250 normal and 250 abnormal sets show improved testing performances with 90% sensitivity and 89% specificity. (author)

  12. A microwave polarimetric scattering model for forest canopies based on vector radiative transfer theory

    International Nuclear Information System (INIS)

    A microwave polarimetric scattering model for a forest canopy is developed based on the iterative solution of the vector radiative transfer equations up to the second order. The forest canopy constituents (branches, leaves, stems, and trunks) are embedded in a multi-layered medium over a rough interface. The branches, stems, and trunks are modeled as finite randomly oriented cylinders. Deciduous leaves are modeled as randomly oriented discs and coniferous leaves are modeled as randomly oriented needles. The vector radiative transfer equations contain non-diagonal extinction matrices that account for the difference in propagation constants and the attenuation rates between the vertical and horizontal polarizations. For a plane wave exciting the canopy, the average Mueller matrix is formulated, and then used to determine the linearly polarized backscattering coefficients including both the copolarized and cross-polarized power returns. Comparisons of the model with measurements from Les Landes Forest of France showed good agreements over a wide frequency band and gave a quantitative understanding of the relation between the backscattering coefficients and the age of the trees in the forest and forest biomass. (author)

  13. A Discriminant Distance Based Composite Vector Selection Method for Odor Classification

    Directory of Open Access Journals (Sweden)

    Sang-Il Choi

    2014-04-01

    Full Text Available We present a composite vector selection method for an effective electronic nose system that performs well even in noisy environments. Each composite vector generated from a electronic nose data sample is evaluated by computing the discriminant distance. By quantitatively measuring the amount of discriminative information in each composite vector, composite vectors containing informative variables can be distinguished and the final composite features for odor classification are extracted using the selected composite vectors. Using the only informative composite vectors can be also helpful to extract better composite features instead of using all the generated composite vectors. Experimental results with different volatile organic compound data show that the proposed system has good classification performance even in a noisy environment compared to other methods.

  14. Development and evaluation of a biomedical search engine using a predicate-based vector space model.

    Science.gov (United States)

    Kwak, Myungjae; Leroy, Gondy; Martinez, Jesse D; Harwell, Jeffrey

    2013-10-01

    Although biomedical information available in articles and patents is increasing exponentially, we continue to rely on the same information retrieval methods and use very few keywords to search millions of documents. We are developing a fundamentally different approach for finding much more precise and complete information with a single query using predicates instead of keywords for both query and document representation. Predicates are triples that are more complex datastructures than keywords and contain more structured information. To make optimal use of them, we developed a new predicate-based vector space model and query-document similarity function with adjusted tf-idf and boost function. Using a test bed of 107,367 PubMed abstracts, we evaluated the first essential function: retrieving information. Cancer researchers provided 20 realistic queries, for which the top 15 abstracts were retrieved using a predicate-based (new) and keyword-based (baseline) approach. Each abstract was evaluated, double-blind, by cancer researchers on a 0-5 point scale to calculate precision (0 versus higher) and relevance (0-5 score). Precision was significantly higher (ppredicate-based (80%) than for the keyword-based (71%) approach. Relevance was almost doubled with the predicate-based approach-2.1 versus 1.6 without rank order adjustment (ppredicate--versus keyword-based approach respectively. Predicates can support more precise searching than keywords, laying the foundation for rich and sophisticated information search. PMID:23892296

  15. Kochen-Specker vectors

    International Nuclear Information System (INIS)

    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, Hn, 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 Rn, 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

  16. Eco-bio-social research on community-based approaches for Chagas disease vector control in Latin America.

    Science.gov (United States)

    Gürtler, Ricardo E; Yadon, Zaida E

    2015-02-01

    This article provides an overview of three research projects which designed and implemented innovative interventions for Chagas disease vector control in Bolivia, Guatemala and Mexico. The research initiative was based on sound principles of community-based ecosystem management (ecohealth), integrated vector management, and interdisciplinary analysis. The initial situational analysis achieved a better understanding of ecological, biological and social determinants of domestic infestation. The key factors identified included: housing quality; type of peridomestic habitats; presence and abundance of domestic dogs, chickens and synanthropic rodents; proximity to public lights; location in the periphery of the village. In Bolivia, plastering of mud walls with appropriate local materials and regular cleaning of beds and of clothes next to the walls, substantially decreased domestic infestation and abundance of the insect vector Triatoma infestans. The Guatemalan project revealed close links between house infestation by rodents and Triatoma dimidiata, and vector infection with Trypanosoma cruzi. A novel community-operated rodent control program significantly reduced rodent infestation and bug infection. In Mexico, large-scale implementation of window screens translated into promising reductions in domestic infestation. A multi-pronged approach including community mobilisation and empowerment, intersectoral cooperation and adhesion to integrated vector management principles may be the key to sustainable vector and disease control in the affected regions. PMID:25604759

  17. Sensitivity Analysis of a Spatio-Temporal Avalanche Forecasting Model Based on Support Vector Machines

    Science.gov (United States)

    Matasci, G.; Pozdnoukhov, A.; Kanevski, M.

    2009-04-01

    The recent progress in environmental monitoring technologies allows capturing extensive amount of data that can be used to assist in avalanche forecasting. While it is not straightforward to directly obtain the stability factors with the available technologies, the snow-pack profiles and especially meteorological parameters are becoming more and more available at finer spatial and temporal scales. Being very useful for improving physical modelling, these data are also of particular interest regarding their use involving the contemporary data-driven techniques of machine learning. Such, the use of support vector machine classifier opens ways to discriminate the ``safe'' and ``dangerous'' conditions in the feature space of factors related to avalanche activity based on historical observations. The input space of factors is constructed from the number of direct and indirect snowpack and weather observations pre-processed with heuristic and physical models into a high-dimensional spatially varying vector of input parameters. The particular system presented in this work is implemented for the avalanche-prone site of Ben Nevis, Lochaber region in Scotland. A data-driven model for spatio-temporal avalanche danger forecasting provides an avalanche danger map for this local (5x5 km) region at the resolution of 10m based on weather and avalanche observations made by forecasters on a daily basis at the site. We present the further work aimed at overcoming the ``black-box'' type modelling, a disadvantage the machine learning methods are often criticized for. It explores what the data-driven method of support vector machine has to offer to improve the interpretability of the forecast, uncovers the properties of the developed system with respect to highlighting which are the important features that led to the particular prediction (both in time and space), and presents the analysis of sensitivity of the prediction with respect to the varying input parameters. The purpose of the

  18. Murine leukemia virus-based Tat-inducible long terminal repeat replacement vectors: a new system for anti-human immunodeficiency virus gene therapy.

    Science.gov (United States)

    Cannon, P M; Kim, N; Kingsman, S M; Kingsman, A J

    1996-11-01

    We have constructed new murine leukemia virus (MLV)-based vectors (TIN vectors) which, following integration, contain human immunodeficiency virus (HIV) type 1 U3 and R sequences in place of the MLV U3 and R regions. This provides, for the first time, single transcriptional unit retroviral vectors under the control of Tat. TIN vectors have several advantages for anti-HIV gene therapy applications. PMID:8892960

  19. Murine leukemia virus-based Tat-inducible long terminal repeat replacement vectors: a new system for anti-human immunodeficiency virus gene therapy.

    OpenAIRE

    Cannon, P M; Kim, N.; Kingsman, S M; Kingsman, A J

    1996-01-01

    We have constructed new murine leukemia virus (MLV)-based vectors (TIN vectors) which, following integration, contain human immunodeficiency virus (HIV) type 1 U3 and R sequences in place of the MLV U3 and R regions. This provides, for the first time, single transcriptional unit retroviral vectors under the control of Tat. TIN vectors have several advantages for anti-HIV gene therapy applications.

  20. A newborn screening system based on service-oriented architecture embedded support vector machine.

    Science.gov (United States)

    Hsu, Kai-Ping; Hsieh, Sung-Huai; Hsieh, Sheau-Ling; Cheng, Po-Hsun; Weng, Yung-Ching; Wu, Jang-Hung; Lai, Feipei

    2010-10-01

    The clinical symptoms of metabolic disorders are rarely apparent during the neonatal period, and if they are not treated earlier, irreversible damages, such as mental retardation or even death, may occur. Therefore, the practice of newborn screening is essential to prevent permanent disabilities in newborns. In the paper, we design, implement a newborn screening system using Support Vector Machine (SVM) classifications. By evaluating metabolic substances data collected from tandem mass spectrometry (MS/MS), we can interpret and determine whether a newborn has a metabolic disorder. In addition, National Taiwan University Hospital Information System (NTUHIS) has been developed and implemented to integrate heterogeneous platforms, protocols, databases as well as applications. To expedite adapting the diversities, we deploy Service-Oriented Architecture (SOA) concepts to the newborn screening system based on web services. The system can be embedded seamlessly into NTUHIS. PMID:20703618

  1. Optical image encryption based on multi-beam interference and common vector decomposition

    Science.gov (United States)

    Chen, Linfei; He, Bingyu; Chen, Xudong; Gao, Xiong; Liu, Jingyu

    2016-02-01

    Based on multi-beam interference and common vector decomposition, we propose a new method for optical image encryption. In encryption process, the information of an original image is encoded into n amplitude masks and n phase masks which are regarded as a ciphertext and many keys. In decryption process, parallel light irradiates the amplitude masks and phase masks, then passes through lens that takes place Fourier transform, and finally we obtain the original image at the output plane after interference. The security of the encryption system is also discussed in the paper, and we find that only when all the keys are correct, can the information of the original image be recovered. Computer simulation results are presented to verify the validity and the security of the proposed method.

  2. Risk assessment for bluetongue virus vectors occurrence based on geographical information systems and statistical modelling

    OpenAIRE

    Pacheco, Solange Almeida

    2009-01-01

    RESUMO - Análise do risco da ocorrência de vectores da Língua Azul com base em Sistemas de Informação Geográfica e modelos estatísticos. - A Língua Azul (LA) está entre as doenças da lista da Organização Mundial de Saúde Animal (OIE) devido ao seu potencial de rápida disseminação e do grave impacto económico na pecuária. No passado, devido à sua epidemiologia, apenas os países do sul da Europa eram afectados pela doença. No entanto, no segundo semestre de 2006, um surto sem ...

  3. Tungsten disulphide based all fiber Q-switching cylindrical-vector beam generation

    International Nuclear Information System (INIS)

    We proposed and demonstrated an all fiber passively Q-switching laser to generate cylindrical-vector beam, a two dimensional material, tungsten disulphide (WS2), was adopted as a saturable absorber inside the laser cavity, while a few-mode fiber Bragg grating was used as a transverse mode-selective output coupler. The repetition rate of the Q-switching output pulses can be varied from 80 kHz to 120 kHz with a shortest duration of 958 ns. Attributed to the high damage threshold and polarization insensitivity of the WS2 based saturable absorber, the radially polarized beam and azimuthally polarized beam can be easily generated in the Q-switching fiber laser

  4. A Stress Vector-Based Constitutive Model for Cohesionless Soil( Ⅱ )-Application

    Institute of Scientific and Technical Information of China (English)

    史宏彦; 谢定义; 白琳

    2002-01-01

    The stress vector-based constitutive model for cohesionless soil, proposed by SHI Hong-yan et al., was applied to analyze the deformation behaviors of materials subjected to various stress paths. The result of analysis shows that the constitutive model can capture well the main deformation behavior of cohesionless soil, such as stress-strain nonlinearity,hardening property, dilatancy , stress path dependency, non- coaxiality between the principal stress and the principal strain increment directions, and the coupling of mean effective and deviatoric stress with deformation. In addition, the model can also take into account the rotation of principal stress axes and the influence of intermediate principal stress on deformation and strength of soil simultaneously. The excellent agreement between the predicted and measured behavior indicates the comprehensive applicability of the model.

  5. Analysis of dengue infection based on Raman spectroscopy and support vector machine (SVM).

    Science.gov (United States)

    Khan, Saranjam; Ullah, Rahat; Khan, Asifullah; Wahab, Noorul; Bilal, Muhammad; Ahmed, Mushtaq

    2016-06-01

    The current study presents the use of Raman spectroscopy combined with support vector machine (SVM) for the classification of dengue suspected human blood sera. Raman spectra for 84 clinically dengue suspected patients acquired from Holy Family Hospital, Rawalpindi, Pakistan, have been used in this study.The spectral differences between dengue positive and normal sera have been exploited by using effective machine learning techniques. In this regard, SVM models built on the basis of three different kernel functions including Gaussian radial basis function (RBF), polynomial function and linear functionhave been employed to classify the human blood sera based on features obtained from Raman Spectra.The classification model have been evaluated with the 10-fold cross validation method. In the present study, the best performance has been achieved for the polynomial kernel of order 1. A diagnostic accuracy of about 85% with the precision of 90%, sensitivity of 73% and specificity of 93% has been achieved under these conditions. PMID:27375941

  6. Sensorless tension control of shuttleless loom system based on support vector regression

    Science.gov (United States)

    Han, Dong Chang; Back, Woon Jae; Lee, Yoon Chul; Lee, Sang Hwa; Lee, Hyuk Jin; Noh, Seok Hong; Kim, Han Kil; Park, Jae Yong; Lee, Suk Gyu; Chun, Du Hwan

    2005-12-01

    Tension control of loom system are usually achieved by using loadcell sensor and powder clutch, which require additional mounting space, reduce the reliability in harsh environments and increase the cost of a loom system. Moreover, the physical properties of textile fabrics are very sensitive to several factors(temperature, humidity, radius change of warp beam etc.) which result in tension change. In this paper, a novel sensorless tension control of a shuttleless loom system based on SVR(Support Vector Regression) is presented. The sensorless tension algorithm of shuttleless loom system driven by servo motor which is robust to disturbance and tension variation. First, the modeling and dynamic behaviors of a shuttleless loom system is described. Then, different tension control strategies are analyzed and discussed. And finally, the validity and the usefulness of proposed algorithm are thoroughly verified through numerical simulation.

  7. Blind multiuser detector for chaos-based CDMA using support vector machine.

    Science.gov (United States)

    Kao, Johnny Wei-Hsun; Berber, Stevan Mirko; Kecman, Vojislav

    2010-08-01

    The algorithm and the results of a blind multiuser detector using a machine learning technique called support vector machine (SVM) on a chaos-based code division multiple access system is presented in this paper. Simulation results showed that the performance achieved by using SVM is comparable to existing minimum mean square error (MMSE) detector under both additive white Gaussian noise (AWGN) and Rayleigh fading conditions. However, unlike the MMSE detector, the SVM detector does not require the knowledge of spreading codes of other users in the system or the estimate of the channel noise variance. The optimization of this algorithm is considered in this paper and its complexity is compared with the MMSE detector. This detector is much more suitable to work in the forward link than MMSE. In addition, original theoretical bit-error rate expressions for the SVM detector under both AWGN and Rayleigh fading are derived to verify the simulation results. PMID:20570769

  8. Compression of 3D meshes based on a decomposition into singular vectors

    Directory of Open Access Journals (Sweden)

    El Mostafa RAJAALLAH

    2016-06-01

    Full Text Available Compression of 3D meshes is an important operation for many applications involving transfer and storage of 3D objects data in their process, such as research by content and navigation in 3D objects databases. Compression is to reduce the space needed to store and/or display the 3D mesh. To do that, we usually try to project it in a frequency space where information is less correlated. The approach suggested in this work is based on a decomposition into singular vectors of the laplacian transform of the adjacency matrix of the vertices of the 3D mesh. The obtained results show the invariance of this approach to a normalization and very encouraging performance semantically.

  9. Tungsten disulphide based all fiber Q-switching cylindrical-vector beam generation

    Energy Technology Data Exchange (ETDEWEB)

    Lin, J.; Yan, K.; Zhou, Y. [Department of Optics and Optical Engineering, University of Science and Technology of China, Hefei 230026 (China); Xu, L. X., E-mail: xulixin@ustc.edu.cn; Gu, C. [Department of Optics and Optical Engineering, University of Science and Technology of China, Hefei 230026 (China); Haixi Collaborative Innovation Center for New Display Devices and Systems Integration, Fuzhou University, Fuzhou 350002 (China); Zhan, Q. W. [Electro-Optics Program, University of Dayton, Dayton, Ohio 45469 (United States)

    2015-11-09

    We proposed and demonstrated an all fiber passively Q-switching laser to generate cylindrical-vector beam, a two dimensional material, tungsten disulphide (WS{sub 2}), was adopted as a saturable absorber inside the laser cavity, while a few-mode fiber Bragg grating was used as a transverse mode-selective output coupler. The repetition rate of the Q-switching output pulses can be varied from 80 kHz to 120 kHz with a shortest duration of 958 ns. Attributed to the high damage threshold and polarization insensitivity of the WS{sub 2} based saturable absorber, the radially polarized beam and azimuthally polarized beam can be easily generated in the Q-switching fiber laser.

  10. PSO-based support vector machine with cuckoo search technique for clinical disease diagnoses.

    Science.gov (United States)

    Liu, Xiaoyong; Fu, Hui

    2014-01-01

    Disease diagnosis is conducted with a machine learning method. We have proposed a novel machine learning method that hybridizes support vector machine (SVM), particle swarm optimization (PSO), and cuckoo search (CS). The new method consists of two stages: firstly, a CS based approach for parameter optimization of SVM is developed to find the better initial parameters of kernel function, and then PSO is applied to continue SVM training and find the best parameters of SVM. Experimental results indicate that the proposed CS-PSO-SVM model achieves better classification accuracy and F-measure than PSO-SVM and GA-SVM. Therefore, we can conclude that our proposed method is very efficient compared to the previously reported algorithms. PMID:24971382

  11. PSO-Based Support Vector Machine with Cuckoo Search Technique for Clinical Disease Diagnoses

    Directory of Open Access Journals (Sweden)

    Xiaoyong Liu

    2014-01-01

    Full Text Available Disease diagnosis is conducted with a machine learning method. We have proposed a novel machine learning method that hybridizes support vector machine (SVM, particle swarm optimization (PSO, and cuckoo search (CS. The new method consists of two stages: firstly, a CS based approach for parameter optimization of SVM is developed to find the better initial parameters of kernel function, and then PSO is applied to continue SVM training and find the best parameters of SVM. Experimental results indicate that the proposed CS-PSO-SVM model achieves better classification accuracy and F-measure than PSO-SVM and GA-SVM. Therefore, we can conclude that our proposed method is very efficient compared to the previously reported algorithms.

  12. Concise vector analysis

    CERN Document Server

    Eliezer, C J; Maxwell, E A; Sneddon, I N

    1963-01-01

    Concise Vector Analysis is a five-chapter introductory account of the methods and techniques of vector analysis. These methods are indispensable tools in mathematics, physics, and engineering. The book is based on lectures given by the author in the University of Ceylon.The first two chapters deal with vector algebra. These chapters particularly present the addition, representation, and resolution of vectors. The next two chapters examine the various aspects and specificities of vector calculus. The last chapter looks into some standard applications of vector algebra and calculus.This book wil

  13. AN INTEGRATED FRAMEWORK BASED ON TEXTURE FEATURES, CUCKOO SEARCH AND RELEVANCE VECTOR MACHINE FOR MEDICAL IMAGE RETRIEVAL SYSTEM

    Directory of Open Access Journals (Sweden)

    Yogapriya Jaganathan

    2013-01-01

    Full Text Available As medical images are widely used in healthcare applications, Content Based Medical Image Retrieval (CBMIR system is needed for physicians to convey effective decisions to patients and for medical research students to learn imaging characteristics for their extensive research based on visual features. However the performance of the retrieval is restricted due to high feature dimensionality of visual features. To reduce the high feature dimension, an integrated approach is proposed such as Visual feature extraction, Feature selection, Feature Classification and Similarity measurements. The selected feature is texture features by using Local Binary Patterns (LBP in which extracted texture features are designed as feature vector database. Fuzzy based Cuckoo Search (FCKS techniques are applied for feature selection to reduce the high feature vector dimensionality and addresses the difficulty of feature vectors being surrounded in local feature optima also the global optimum feature position to be special for all feature cuckoo hosts. Fuzzy based Relevance Vector Machine (FRVM classification is an proficient method to customize the collections of relevant image features that would classify dimensionally determined optimized feature vectors of images. The Euclidean Distance (ED is a standard technique for similarity measurement between the query image and the image database. The proposed system is implemented on thousands of medical images and achieved a high retrieval precision and recall compared with other two methods as validated through experiments.

  14. Improved Reliability-Based Optimization with Support Vector Machines and Its Application in Aircraft Wing Design

    Directory of Open Access Journals (Sweden)

    Yu Wang

    2015-01-01

    Full Text Available A new reliability-based design optimization (RBDO method based on support vector machines (SVM and the Most Probable Point (MPP is proposed in this work. SVM is used to create a surrogate model of the limit-state function at the MPP with the gradient information in the reliability analysis. This guarantees that the surrogate model not only passes through the MPP but also is tangent to the limit-state function at the MPP. Then, importance sampling (IS is used to calculate the probability of failure based on the surrogate model. This treatment significantly improves the accuracy of reliability analysis. For RBDO, the Sequential Optimization and Reliability Assessment (SORA is employed as well, which decouples deterministic optimization from the reliability analysis. The improved SVM-based reliability analysis is used to amend the error from linear approximation for limit-state function in SORA. A mathematical example and a simplified aircraft wing design demonstrate that the improved SVM-based reliability analysis is more accurate than FORM and needs less training points than the Monte Carlo simulation and that the proposed optimization strategy is efficient.

  15. Efficient gray-level digital image watermarking based on vector quantization

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    Digital watermarking has been presented as a new method for copyright protection by embedding a se cret signal in a digital image or video sequence. Common digital image watermarking techniques are based on the concept of spread-spectrum communications, which can be classified in two catalogues: spatial-domain and transform-domain based. Most of transform-domain watermarking methods are based on discrete cosine trans forms (DCT) and robust to JPEG lossy compression. Recently, digital image watermarking based on another important lossy compression technique, vector quantization (VQ), has been presented, which carries water mark information by codeword indices. It is secret and efficient, and is robust to VQ compression with the same codebook. However, the embedded information is less and the extraction process requires the original image.This paper presents a more efficient VQ-based image watermarking method, which can embed a large gray-level watermark into the original image with less extra distortion and perform the watermark extraction without the original image. In addition, the proposed watermarking algorithm is very secret because two keys are required for watermark extraction. Experimental results demonstrate the effectiveness of the proposed technique.

  16. Texture discrimination of green tea categories based on least squares support vector machine (LSSVM) classifier

    Science.gov (United States)

    Li, Xiaoli; He, Yong; Qiu, Zhengjun; Wu, Di

    2008-03-01

    This research aimed for development multi-spectral imaging technique for green tea categories discrimination based on texture analysis. Three key wavelengths of 550, 650 and 800 nm were implemented in a common-aperture multi-spectral charged coupled device camera, and images were acquired for 190 unique images in a four different kinds of green tea data set. An image data set consisting of 15 texture features for each image was generated based on texture analysis techniques including grey level co-occurrence method (GLCM) and texture filtering. For optimization the texture features, 5 features that weren't correlated with the category of tea were eliminated. Unsupervised cluster analysis was conducted using the optimized texture features based on principal component analysis. The cluster analysis showed that the four kinds of green tea could be separated in the first two principal components space, however there was overlapping phenomenon among the different kinds of green tea. To enhance the performance of discrimination, least squares support vector machine (LSSVM) classifier was developed based on the optimized texture features. The excellent discrimination performance for sample in prediction set was obtained with 100%, 100%, 75% and 100% for four kinds of green tea respectively. It can be concluded that texture discrimination of green tea categories based on multi-spectral image technology is feasible.

  17. Design of Space Vector-Based Hybrid PWM Techniques for Reduced Current Ripple

    OpenAIRE

    Krishnamurthy, H.; Narayanan, G.; Ayyanar, R; Ranganathan, VT

    2003-01-01

    Switching sequence used by conventional space vector PWM (CSVPWM) involves equal division of zero vector time between the two zero states in every subcycle. The sequences employed by bus-clamping PWM involve use of only one zero state in a subcycle. This paper deals with two sequences, which use only one zero state and involve division of active vector time within a subcycle. A novel hybrid PWM technique, employing these two sequences in conjunction with the conventional sequence, is proposed...

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

    OpenAIRE

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

    2012-01-01

    Abstract Background 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 event...

  19. Improved antibiotic-free DNA vaccine vectors utilizing a novel RNA based plasmid selection system

    OpenAIRE

    Luke, Jeremy; Carnes, Aaron E; Hodgson, Clague P.; Williams, James A.

    2009-01-01

    To ensure safety, regulatory agencies recommend elimination of antibiotic resistance markers from therapeutic and vaccine plasmid DNA vectors. Here, we describe the development and application of a novel antibiotic-free selection system. Vectors incorporate and express a 150 bp RNA-OUT antisense RNA. RNA-OUT represses expression of a chromosomally integrated constitutively expressed counter-selectable marker (sacB), allowing plasmid selection on sucrose. Sucrose selectable DNA vaccine vectors...

  20. Minimal requirement for a lentivirus vector based on human immunodeficiency virus type 1.

    Science.gov (United States)

    Kim, V N; Mitrophanous, K; Kingsman, S M; Kingsman, A J

    1998-01-01

    The use of human immunodeficiency virus vectors for gene therapy is hampered by concern over their safety. This concern might be ameliorated, in part, if the viral accessory genes and proteins could be eliminated from the vector genomes and particles. Here we describe a minimal vector system that is capable of transducing nondividing cells and which does not contain tat, vif, vpr, vpu, and nef. PMID:9420292

  1. Minimal Requirement for a Lentivirus Vector Based on Human Immunodeficiency Virus Type 1

    OpenAIRE

    Kim, V. Narry; Mitrophanous, Kyriacos; Kingsman, Susan M.; Kingsman, Alan J.

    1998-01-01

    The use of human immunodeficiency virus vectors for gene therapy is hampered by concern over their safety. This concern might be ameliorated, in part, if the viral accessory genes and proteins could be eliminated from the vector genomes and particles. Here we describe a minimal vector system that is capable of transducing nondividing cells and which does not contain tat, vif, vpr, vpu, and nef.

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

    OpenAIRE

    Deb J K; Walia Rupali; Mukherjee K J

    2007-01-01

    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% st...

  3. A STRESS VECTOR-BASED CONSTITUTIVE MODEL FOR COHESIONLESS SOIL (Ⅰ)-THEORY

    Institute of Scientific and Technical Information of China (English)

    史宏彦; 谢定义

    2002-01-01

    On the basis of the sufficient consideration of vectorial characteristics of stress,a new nonlinear constitutive model for cohesionless soil under plane strain and 3-D conditions was presented in a way that the action effects of stress vector are decomposed into the action effect of mean effective stress and that of the stress ratio vector (ratio of deviatoric stress vector to mean effective stress ). The constitutive model can take account of the influence of both numerical and directional changes of stress vector on deformation of soil simultaneously, and is applicable of both static and dynamic loading.

  4. Bacillus subtilis genome vector-based complete manipulation and reconstruction of genomic DNA for mouse transgenesis

    OpenAIRE

    Iwata, Tetsuo; Kaneko, Shinya; Shiwa, Yuh; Enomoto, Takayuki; Yoshikawa, Hirofumi; Hirota, Junji

    2013-01-01

    Background The Bacillus subtilis genome (BGM) vector is a novel cloning system for large DNA fragments, in which the entire 4.2 Mb genome of B. subtilis functions as a vector. The BGM vector system has several attractive properties, such as a large cloning capacity of over 3 Mb, stable propagation of cloned DNA and various modification strategies using RecA-mediated homologous recombination. However, genetic modifications using the BGM vector system have not been fully established, and this s...

  5. Modal macro-strain vector based damage detection methodology with long-gauge FBG sensors

    Science.gov (United States)

    Xu, Bin; Liu, Chongwu W.; Masri, Sami F.

    2009-07-01

    Advances in optic fiber sensing technology provide easy and reliable way for the vibration-based strain measurement of engineering structures. As a typical optic fiber sensing techniques with high accuracy and resolution, long-gauge Fiber Bragg Grating (FBG) sensors have been widely employed in health monitoring of civil engineering structures. Therefore, the development of macro strain-based identification methods is crucial for damage detection and structural condition evaluation. In the previous study by the authors, a damage detection algorithm for a beam structure with the direct use of vibration-based macro-strain measurement time history with neural networks had been proposed and validated with experimental measurements. In this paper, a damage locating and quantifying method was proposed using modal macrostrain vectors (MMSVs) which can be extracted from vibration induced macro-strain response measurement time series from long-gage FBG sensors. The performance of the proposed methodology for damage detection of a beam with different damage scenario was studied with numerical simulation firstly. Then, dynamic tests on a simply-supported steel beam with different damage scenarios were carried out and macro-strain measurements were employed to detect the damage severity. Results show that the proposed MMSV based structural identification and damage detection methodology can locate and identify the structural damage severity with acceptable accuracy.

  6. Vector-based dynamic modeling and control of the quattro parallel robot by means of leg orientations.

    OpenAIRE

    Ozgür, Erol; Andreff, Nicolas; Martinet, Philippe

    2010-01-01

    One of the key steps in high-speed control of a parallel robot is to define an efficient dynamic model. It is usually not easy to have such a model for parallel robots, since many of them have complex structures. Here, we propose a vector-based approach, which employs the robot leg orientations, to obtain a simplified inverse dynamic model. At the least, this vector-based methodology is pioneering, when combined with the observation of orientations by a calibrated camera, in the sense of solv...

  7. Adenoviral vector expressing murine β-defensin 2 enhances immunogenicity of an adenoviral vector based H5N1 influenza vaccine in aged mice.

    Science.gov (United States)

    Vemula, Sai V; Pandey, Aseem; Singh, Neetu; Katz, Jacqueline M; Donis, Ruben; Sambhara, Suryaprakash; Mittal, Suresh K

    2013-10-01

    The ability to resist infections and respond to vaccinations is greatly reduced in the older adult population owing to a general decline in innate and adaptive immune functions with aging. Over the years several strategies such as increasing the vaccine dose, number of immunizations and using adjuvants have been evaluated to improve the immunogenicity and efficacy of vaccines in the older adult population. Murine β-defensin 2 (Mbd2) has been shown to function as a molecular adjuvant by recruiting and activating immature dendritic cells (DCs), professional antigen-presenting cells (APC), to the site of the immunization. In this study, we evaluated the potential utility of Mbd2 to enhance the efficacy of an adenoviral vector-based H5N1 influenza vaccine expressing hemagglutinin (HA) and nucleoprotein (NP) (HAd-HA-NP) in an aged mouse model. Our results indicated that immunostimulation with an adenoviral vector expressing Mbd2 (HAd-Mbd2) activated DCs and significantly enhanced the humoral and cellular immune responses induced by HAd-HA-NP. Furthermore, immunostimulation with HAd-Mbd2 followed by immunization with HAd-HA-NP resulted in significantly lower virus titers in the lungs following challenge with a H5N1 influenza virus compared to the group immunized with HAd-HA-NP without immunostimulation. Overall, our results highlight the potential utility of Mbd2 as a molecular adjuvant to enhance the immunogenicity and protective efficacy of vaccines for the elderly. PMID:23892144

  8. vSmartMOM: A vector matrix operator method-based radiative transfer model linearized with respect to aerosol properties

    Science.gov (United States)

    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

  9. MAPPING LOCAL CLIMATE ZONES WITH A VECTOR-BASED GIS METHOD

    Directory of Open Access Journals (Sweden)

    E. Lelovics

    2013-03-01

    Full Text Available In this study we determined Local Climate Zones in a South-Hungarian city, using vector-based and raster-based databases. We calculated seven of the originally proposed ten physical (geometric, surface cover and radiative properties for areas which are based on the mobile temperature measurement campaigns earlier carried out in this city.As input data we applied 3D building database (earlier created with photogrammetric methods, 2D road database, topographic map, aerial photographs, remotely sensed reflectance information from RapidEye satellite image and our local knowledge about the area. The values of the properties were calculated by GIS methods developed for this purpose.We derived for the examined areas and applied for classification sky view factor, mean building height, terrain roughness class, building surface fraction, pervious surface fraction, impervious surface fraction and albedo.Six built and one land cover LCZ classes could be detected with this method on our study area. From each class one circle area was selected, which is representative for that class. Their thermal reactions were examined with the application of mobile temperature measurement dataset. The comparison was made in cases, when the weather was clear and calm and the surface was dry. We found that compact built-in types have more temperature surplus than open ones, and midrise types also have more than lowrise ones. According to our primary results, these categories provide a useful opportunity for intra- and inter-urban comparisons.

  10. Nondestructive detection of pork comprehensive quality based on spectroscopy and support vector machine

    Science.gov (United States)

    Liu, Yuanyuan; Peng, Yankun; Zhang, Leilei; Dhakal, Sagar; Wang, Caiping

    2014-05-01

    Pork is one of the highly consumed meat item in the world. With growing improvement of living standard, concerned stakeholders including consumers and regulatory body pay more attention to comprehensive quality of fresh pork. Different analytical-laboratory based technologies exist to determine quality attributes of pork. However, none of the technologies are able to meet industrial desire of rapid and non-destructive technological development. Current study used optical instrument as a rapid and non-destructive tool to classify 24 h-aged pork longissimus dorsi samples into three kinds of meat (PSE, Normal and DFD), on the basis of color L* and pH24. Total of 66 samples were used in the experiment. Optical system based on Vis/NIR spectral acquisition system (300-1100 nm) was self- developed in laboratory to acquire spectral signal of pork samples. Median smoothing filter (M-filter) and multiplication scatter correction (MSC) was used to remove spectral noise and signal drift. Support vector machine (SVM) prediction model was developed to classify the samples based on their comprehensive qualities. The results showed that the classification model is highly correlated with the actual quality parameters with classification accuracy more than 85%. The system developed in this study being simple and easy to use, results being promising, the system can be used in meat processing industry for real time, non-destructive and rapid detection of pork qualities in future.

  11. Support vector machine-based classification of Alzheimer's disease from whole-brain anatomical MRI

    International Nuclear Information System (INIS)

    We present and evaluate a new automated method based on support vector machine (SVM) classification of whole-brain anatomical magnetic resonance imaging to discriminate between patients with Alzheimer's disease (AD) and elderly control subjects. We studied 16 patients with AD [mean age ± standard deviation (SD)=74.1 ±5.2 years, mini-mental score examination (MMSE) = 23.1 ± 2.9] and 22 elderly controls (72.3±5.0 years, MMSE=28.5± 1.3). Three-dimensional T1-weighted MR images of each subject were automatically parcellated into regions of interest (ROIs). Based upon the characteristics of gray matter extracted from each ROI, we used an SVM algorithm to classify the subjects and statistical procedures based on bootstrap resampling to ensure the robustness of the results. We obtained 94.5% mean correct classification for AD and control subjects (mean specificity, 96.6%; mean sensitivity, 91.5%). Our method has the potential in distinguishing patients with AD from elderly controls and therefore may help in the early diagnosis of AD. (orig.)

  12. MULTI-SOURCE REMOTE SENSING IMAGE FUSION BASED ON SUPPORT VECTOR MACHINE

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    Remote Sensing image fusion is an effective way to use the large volume of data from multi-source images.This paper introduces a new method of remote sensing image fusion based on support vector machine (SVM), using highspatial resolution data SPIN-2 and multi-spectral remote sensing data SPOT-4. Firstly, the new method is established bybuilding a model of remote sensing image fusion based on SVM. Then by using SPIN-2 data and SPOT-4 data, image classification fusion is tested. Finally, an evaluation of the fusion result is made in two ways. 1 ) From subjectivity assessment,the spatial resolution of the fused image is improved compared to the SPOT-4. And it is clearly that the texture of thefused image is distinctive. 2) From quantitative analysis, the effect of classification fusion is better. As a whole, the result shows that the accuracy of image fusion based on SVM is high and the SVM algorithm can be recommended for application in remote sensing image fusion processes.

  13. MULTI—SOURCE REMOTE SENSING IMAGE FUSION BASED ON SUPPORT VECTOR MACHINE

    Institute of Scientific and Technical Information of China (English)

    ZHAOShu-he; FENGXue-zhi; 等

    2002-01-01

    Remote Sensing image fusion is an effective way to use the large volume of data from multi-source images.This paper introduces a new method of remote sensing image fusion based on support vector machine(SVM),using high spatial resolution data SPIN-2 and multi-spectral remote sensing data SPOT-4.Firstly,the new method is established by building a model of remote sensing image fusion based on SVM.Then by using SPIN-2 data and SPOT-4 data ,image classify-cation fusion in tested.Finally,and evaluation of the fusion result is made in two ways.1)From subjectivity assessment,the spatial resolution of the fused image is improved compared to the SPOT-4.And it is clearly that the texture of the fused image is distinctive.2)From quantitative analysis,the effect of classification fusion is better.As a whole ,the re-sult shows that the accuracy of image fusion based on SVM is high and the SVM algorithm can be recommended for applica-tion in remote sensing image fusion processes.

  14. Characteristics of a class of vector-valued non-separable higher-dimensional wavelet packet bases

    International Nuclear Information System (INIS)

    In this paper, we introduce vector-valued non-separable higher-dimensional wavelet packets with an arbitrary integer dilation factor. An approach for constructing vector-valued higher-dimensional wavelet packet bases is proposed. Their characteristics are investigated by means of harmonic analysis method, matrix theory and operator theory, and three orthogonality formulas concerning the wavelet packets are presented. Orthogonal decomposition relation formulas of the space L2(Rn)p are derived by designing a series of subspaces of the vector-valued wavelet packets. Moreover, several orthonormal wavelet packet bases of L2(Rn)p are constructed from the wavelet packets. Relation to some physical theories such as E-infinity theory and multifractal theory is also discussed.

  15. Insulated Foamy Viral Vectors.

    Science.gov (United States)

    Browning, Diana L; Collins, Casey P; Hocum, Jonah D; Leap, David J; Rae, Dustin T; Trobridge, Grant D

    2016-03-01

    Retroviral vector-mediated gene therapy is promising, but genotoxicity has limited its use in the clinic. Genotoxicity is highly dependent on the retroviral vector used, and foamy viral (FV) vectors appear relatively safe. However, internal promoters may still potentially activate nearby genes. We developed insulated FV vectors, using four previously described insulators: a version of the well-studied chicken hypersensitivity site 4 insulator (650cHS4), two synthetic CCCTC-binding factor (CTCF)-based insulators, and an insulator based on the CCAAT box-binding transcription factor/nuclear factor I (7xCTF/NF1). We directly compared these insulators for enhancer-blocking activity, effect on FV vector titer, and fidelity of transfer to both proviral long terminal repeats. The synthetic CTCF-based insulators had the strongest insulating activity, but reduced titers significantly. The 7xCTF/NF1 insulator did not reduce titers but had weak insulating activity. The 650cHS4-insulated FV vector was identified as the overall most promising vector. Uninsulated and 650cHS4-insulated FV vectors were both significantly less genotoxic than gammaretroviral vectors. Integration sites were evaluated in cord blood CD34(+) cells and the 650cHS4-insulated FV vector had fewer hotspots compared with an uninsulated FV vector. These data suggest that insulated FV vectors are promising for hematopoietic stem cell gene therapy. PMID:26715244

  16. Geographic Distribution of Chagas Disease Vectors in Brazil Based on Ecological Niche Modeling

    Directory of Open Access Journals (Sweden)

    Rodrigo Gurgel-Gonçalves

    2012-01-01

    Full Text Available Although Brazil was declared free from Chagas disease transmission by the domestic vector Triatoma infestans, human acute cases are still being registered based on transmission by native triatomine species. For a better understanding of transmission risk, the geographic distribution of Brazilian triatomines was analyzed. Sixteen out of 62 Brazilian species that both occur in >20 municipalities and present synanthropic tendencies were modeled based on their ecological niches. Panstrongylus geniculatus and P. megistus showed broad ecological ranges, but most of the species sort out by the biome in which they are distributed: Rhodnius pictipes and R. robustus in the Amazon; R. neglectus, Triatoma sordida, and T. costalimai in the Cerrado; R. nasutus, P. lutzi, T. brasiliensis, T. pseudomaculata, T. melanocephala, and T. petrocchiae in the Caatinga; T. rubrovaria in the southern pampas; T. tibiamaculata and T. vitticeps in the Atlantic Forest. Although most occurrences were recorded in open areas (Cerrado and Caatinga, our results show that all environmental conditions in the country are favorable to one or more of the species analyzed, such that almost nowhere is Chagas transmission risk negligible.

  17. Pointing-Vector and Velocity Based Frequency Predicts for Deep-Space Uplink Array Applications

    Science.gov (United States)

    Tsao, P.; Vilnrotter, Victor A.; Jamnejad, V.

    2008-01-01

    Uplink array technology is currently being developed for NASA's Deep Space Network (DSN) to provide greater range and data throughput for future NASA missions, including manned missions to Mars and exploratory missions to the outer planets, the Kuiper belt, and beyond. Here we describe a novel technique for generating the frequency predicts that are used to compensate for relative Doppler, derived from interpolated earth position and spacecraft ephemerides. The method described here guarantees velocity and range estimates that are consistent with each other, hence one can always be recovered from the other. Experimental results have recently proven that these frequency predicts are accurate enough to maintain the phase of a three element array at the EPOXI spacecraft for three hours. Previous methods derive frequency predicts directly from interpolated relative velocities. However, these velocities were found to be inconsistent with the corresponding spacecraft range, meaning that range could not always be recovered accurately from the velocity predicts, and vice versa. Nevertheless, velocity-based predicts are also capable of maintaining uplink array phase calibration for extended periods, as demonstrated with the EPOXI spacecraft, however with these predicts important range and phase information may be lost. A comparison of the steering-vector method with velocity-based techniques for generating precise frequency predicts specifically for uplink array applications is provided in the following sections.

  18. 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.

  19. Short-Term Traffic Flow Local Prediction Based on Combined Kernel Function Relevance Vector Machine Model

    Directory of Open Access Journals (Sweden)

    Qichun Bing

    2015-01-01

    Full Text Available Short-term traffic flow prediction is one of the most important issues in the field of adaptive traffic control system and dynamic traffic guidance system. In order to improve the accuracy of short-term traffic flow prediction, a short-term traffic flow local prediction method based on combined kernel function relevance vector machine (CKF-RVM model is put forward. The C-C method is used to calculate delay time and embedding dimension. The number of neighboring points is determined by use of Hannan-Quinn criteria, and the CKF-RVM model is built based on genetic algorithm. Finally, case validation is carried out using inductive loop data measured from the north–south viaduct in Shanghai. The experimental results demonstrate that the CKF-RVM model is 31.1% and 52.7% higher than GKF-RVM model and GKF-SVM model in the aspect of MAPE. Moreover, it is also superior to the other two models in the aspect of EC.

  20. An Enhanced MEMS Error Modeling Approach Based on Nu-Support Vector Regression

    Directory of Open Access Journals (Sweden)

    Deepak Bhatt

    2012-07-01

    Full Text Available Micro Electro Mechanical System (MEMS-based inertial sensors have made possible the development of a civilian land vehicle navigation system by offering a low-cost solution. However, the accurate modeling of the MEMS sensor errors is one of the most challenging tasks in the design of low-cost navigation systems. These sensors exhibit significant errors like biases, drift, noises; which are negligible for higher grade units. Different conventional techniques utilizing the Gauss Markov model and neural network method have been previously utilized to model the errors. However, Gauss Markov model works unsatisfactorily in the case of MEMS units due to the presence of high inherent sensor errors. On the other hand, modeling the random drift utilizing Neural Network (NN is time consuming, thereby affecting its real-time implementation. We overcome these existing drawbacks by developing an enhanced Support Vector Machine (SVM based error model. Unlike NN, SVMs do not suffer from local minimisation or over-fitting problems and delivers a reliable global solution. Experimental results proved that the proposed SVM approach reduced the noise standard deviation by 10–35% for gyroscopes and 61–76% for accelerometers. Further, positional error drifts under static conditions improved by 41% and 80% in comparison to NN and GM approaches.

  1. Predictive based monitoring of nuclear plant component degradation using support vector regression

    Energy Technology Data Exchange (ETDEWEB)

    Agarwal, Vivek [Idaho National Lab. (INL), Idaho Falls, ID (United States). Dept. of Human Factors, Controls, Statistics; Alamaniotis, Miltiadis [Purdue Univ., West Lafayette, IN (United States). School of Nuclear Engineering; Tsoukalas, Lefteri H. [Purdue Univ., West Lafayette, IN (United States). School of Nuclear Engineering

    2015-02-01

    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.

  2. Point-based warping with optimized weighting factors of displacement vectors

    Science.gov (United States)

    Pielot, Ranier; Scholz, Michael; Obermayer, Klaus; Gundelfinger, Eckart D.; Hess, Andreas

    2000-06-01

    The accurate comparison of inter-individual 3D image brain datasets requires non-affine transformation techniques (warping) to reduce geometric variations. Constrained by the biological prerequisites we use in this study a landmark-based warping method with weighted sums of displacement vectors, which is enhanced by an optimization process. Furthermore, we investigate fast automatic procedures for determining landmarks to improve the practicability of 3D warping. This combined approach was tested on 3D autoradiographs of Gerbil brains. The autoradiographs were obtained after injecting a non-metabolized radioactive glucose derivative into the Gerbil thereby visualizing neuronal activity in the brain. Afterwards the brain was processed with standard autoradiographical methods. The landmark-generator computes corresponding reference points simultaneously within a given number of datasets by Monte-Carlo-techniques. The warping function is a distance weighted exponential function with a landmark- specific weighting factor. These weighting factors are optimized by a computational evolution strategy. The warping quality is quantified by several coefficients (correlation coefficient, overlap-index, and registration error). The described approach combines a highly suitable procedure to automatically detect landmarks in autoradiographical brain images and an enhanced point-based warping technique, optimizing the local weighting factors. This optimization process significantly improves the similarity between the warped and the target dataset.

  3. An Improved Approach for Topic Ontology Based Categorization of Blogs Using Support Vector Machine

    Directory of Open Access Journals (Sweden)

    V. Subramaniyaswamy

    2012-01-01

    Full Text Available Problem statement: Information search, collection and categorization from the blogosphere are still one of the important issues to be resolved. Mainly, the blogs assist the variety of interesting and useful information. Because of its increasing growth, blogs can not be categorized effectively. Therefore it is difficult to find relevant topics from the blogs. Hence blogs need to be categorized topically to make easy for readers. Approach: Blog contents are associated with a set of predefined topic ontology keywords. This study proposes categorization of blogs to facilitate easy identification of user expected topic from the massive collection of blogs. Tags, page contents were collected as inputs from the blogs and the blogs were categorized using Support Vector Machine (SVM algorithm. Most frequent occurrences of topic ontological keywords are used to train the classifier. This approach has effectively improved blog categorization process using SVM. Results: The performance was evaluated for precision and recall for blog categorization based on topic ontology using SVM with Naive Bayes algorithm. It was proved that topic ontology assisted SVM improves the classification accuracy than Naïve Bayes algorithm. Conclusion: This study has effectively improved the classification of blogs based on topic ontology assisted SVM. Experiments showed the effectiveness of the blog categorization.

  4. Land Cover Classification from Full-Waveform LIDAR Data Based on Support Vector Machines

    Science.gov (United States)

    Zhou, M.; Li, C. R.; Ma, L.; Guan, H. C.

    2016-06-01

    In this study, a land cover classification method based on multi-class Support Vector Machines (SVM) is presented to predict the types of land cover in Miyun area. The obtained backscattered full-waveforms were processed following a workflow of waveform pre-processing, waveform decomposition and feature extraction. The extracted features, which consist of distance, intensity, Full Width at Half Maximum (FWHM) and back scattering cross-section, were corrected and used as attributes for training data to generate the SVM prediction model. The SVM prediction model was applied to predict the types of land cover in Miyun area as ground, trees, buildings and farmland. The classification results of these four types of land covers were obtained based on the ground truth information according to the CCD image data of Miyun area. It showed that the proposed classification algorithm achieved an overall classification accuracy of 90.63%. In order to better explain the SVM classification results, the classification results of SVM method were compared with that of Artificial Neural Networks (ANNs) method and it showed that SVM method could achieve better classification results.

  5. An Irregularity Measurement Based Cardiac Status Recognition Using Support Vector Machine

    Directory of Open Access Journals (Sweden)

    Poulami Banerjee

    2015-01-01

    Full Text Available An automated robust feature extraction technique is proposed in this paper based on inherent structural distribution of heart sound to analyze the phonocardiogram signal in presence of environmental noise and interference of lung sound signal. The structural complexity of the heart sound signal is estimated in terms of sample entropy using a nonlinear signal processing framework. The effectiveness of the feature is evaluated using a support vector machine under two different circumstances which include Gaussian noise and pulmonary perturbation. The analysis framework has been executed on a composite data set of 60 healthy and 60 pathological individuals for different SNR levels (−5 to 10 dB and the performance accuracy is close to that of the clean signal. In addition, a comparative study has been done with conventional approaches which includes waveform analysis, spectral domain inspection, and spectrogram evaluation. The experimental results show that sample entropy based classification method gives an accuracy of 96.67% for clean data and 91.66% for noisy data of SNR 10 dB. The result suggests that the proposed method performs significantly well over the visual and audio test.

  6. Time series online prediction algorithm based on least squares support vector machine

    Institute of Scientific and Technical Information of China (English)

    WU Qiong; LIU Wen-ying; YANG Yi-han

    2007-01-01

    Deficiencies of applying the traditional least squares support vector machine (LS-SVM) to time series online prediction were specified. According to the kernel function matrix's property and using the recursive calculation of block matrix, a new time series online prediction algorithm based on improved LS-SVM was proposed. The historical training results were fully utilized and the computing speed of LS-SVM was enhanced. Then, the improved algorithm was applied to time series online prediction. Based on the operational data provided by the Northwest Power Grid of China, the method was used in the transient stability prediction of electric power system. The results show that, compared with the calculation time of the traditional LS-SVM(75-1 600 ms), that of the proposed method in different time windows is 40-60 ms, and the prediction accuracy(normalized root mean squared error) of the proposed method is above 0.8. So the improved method is better than the traditional LS-SVM and more suitable for time series online prediction.

  7. A novel harmonic mitigator-based 12-pulse rectification for vector-controlled induction motor drives

    Energy Technology Data Exchange (ETDEWEB)

    Singh, Bim; Bhuvaneswari, G.; Garg, Vipin [Indian Inst. of Technology, Dept. of Electrical Engineering, New Delhi (India)

    2006-07-01

    This paper presents an optimised 12-pulse autotransformer-based AC-DC converter with reduced kVA magnetics for reducing the harmonic distortion in AC mains current in a vector-controlled induction motor drive (VCIMD). The proposed AC-DC converter results in elimination of fifth, seventh and 11th harmonics in the supply current. The proposed system consists of an autotransformer and a tuned passive filter. A small rating passive filter is tuned to 11th harmonic frequency and it reduces the harmonic currents generated by the AC-DC converter, thus reducing the total harmonic distortion of AC mains current. The filter is tuned such that the supply current is less than the converter input AC current. The detailed simulations of the drive system along with the 12-pulse AC-DC converter are carried out in MATLAB environment using SIMULINK and power system blockset toolboxes. Four different topologies of 12-pulse autotransformer connections have been considered to feed voltage source inverter-based VCIMD. A set of power quality parameters such as total harmonic distortion and crest factor of AC mains current, power factor, displacement factor and distortion factor at AC mains and DC bus ripple factor for a VCIMD fed from different 12-pulse converters are computed and tabulated. The effect of load on VCIMD is also studied to demonstrate the effectiveness of the proposed topology for power quality improvement of AC mains. (Author)

  8. Knowledge-based analysis of microarray gene expression data by using support vector machines

    Energy Technology Data Exchange (ETDEWEB)

    William Grundy; Manuel Ares, Jr.; David Haussler

    2001-06-18

    The authors introduce a method of functionally classifying genes by using gene expression data from DNA microarray hybridization experiments. The method is based on the theory of support vector machines (SVMs). SVMs are considered a supervised computer learning method because they exploit prior knowledge of gene function to identify unknown genes of similar function from expression data. SVMs avoid several problems associated with unsupervised clustering methods, such as hierarchical clustering and self-organizing maps. SVMs have many mathematical features that make them attractive for gene expression analysis, including their flexibility in choosing a similarity function, sparseness of solution when dealing with large data sets, the ability to handle large feature spaces, and the ability to identify outliers. They test several SVMs that use different similarity metrics, as well as some other supervised learning methods, and find that the SVMs best identify sets of genes with a common function using expression data. Finally, they use SVMs to predict functional roles for uncharacterized yeast ORFs based on their expression data.

  9. Multiplex CRISPR/Cas9-based genome engineering from a single lentiviral vector.

    Science.gov (United States)

    Kabadi, Ami M; Ousterout, David G; Hilton, Isaac B; Gersbach, Charles A

    2014-10-29

    Engineered DNA-binding proteins that manipulate the human genome and transcriptome have enabled rapid advances in biomedical research. In particular, the RNA-guided CRISPR/Cas9 system has recently been engineered to create site-specific double-strand breaks for genome editing or to direct targeted transcriptional regulation. A unique capability of the CRISPR/Cas9 system is multiplex genome engineering by delivering a single Cas9 enzyme and two or more single guide RNAs (sgRNAs) targeted to distinct genomic sites. This approach can be used to simultaneously create multiple DNA breaks or to target multiple transcriptional activators to a single promoter for synergistic enhancement of gene induction. To address the need for uniform and sustained delivery of multiplex CRISPR/Cas9-based genome engineering tools, we developed a single lentiviral system to express a Cas9 variant, a reporter gene and up to four sgRNAs from independent RNA polymerase III promoters that are incorporated into the vector by a convenient Golden Gate cloning method. Each sgRNA is efficiently expressed and can mediate multiplex gene editing and sustained transcriptional activation in immortalized and primary human cells. This delivery system will be significant to enabling the potential of CRISPR/Cas9-based multiplex genome engineering in diverse cell types. PMID:25122746

  10. 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. PMID:26888111

  11. The Determinants of U.S. Treasury Bill Rates: An Approach Based on A Vector Autoregressive Model (VAR)

    OpenAIRE

    Fadiga, Ismael Tanou

    2009-01-01

    This dissertation examines the determinants of U.S. Treasury bill rates based on vector autoregressions for the period 1959-2009. Our main conclusions are: (1) monetary base, inflation rate and output affect the dynamics of Treasury bill rates and those results are consistent with the theory in regards to the factors affecting yield curves. Accurately, we find that the growth rates of monetary base, inflation and output are all significant in explaining the growth of U.S. Treasury bill rates;...

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

    DEFF Research Database (Denmark)

    Askou, Anne Louise; Aagaard, Lars; Kostic, Corinne; Arsenijevic, Yvan; Hollensen, Anne Kruse; Bek, Toke; Jensen, Thomas G.; Mikkelsen, Jacob Giehm; Corydon, Thomas Juhl

    2015-01-01

    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) cluster...... combination therapies for amelioration of age-related macular degeneration....

  13. Open Source Scalable Vector Graphics Components for Enabling GIS in Web-based Public Health Surveillance Systems

    OpenAIRE

    Kamadjeu, Raoul; Tolentino, Herman

    2006-01-01

    Geographic Information Systems (GIS) are useful for visual analysis and sharing of spatial data. Open standards like Scalable Vector Graphics (SVG) provide viable alternatives to overcome traditional GIS limitations in resource-constrained settings (low-bandwidth, cost and manpower barriers). This project describes the design and implementation of reusable SVG components for managing geographic information for web-based public health surveillance systems.

  14. Influence of the velocity vector base relocation to the center of mass of the interrogation area on PIV accuracy

    Directory of Open Access Journals (Sweden)

    Kouba Jan

    2014-03-01

    Full Text Available This paper is aimed at modification of calculation algorithm used in data processing from PIV (Particle Image Velocimetry method. The modification of standard Multi-step correlation algorithm is based on imaging the centre of mass of the interrogation area to define the initial point of the respective vector, instead of the geometrical centre. This paper describes the principle of initial point-vector assignment, the corresponding data processing methodology including the test track analysis. Both approaches are compared within the framework of accuracy in the conclusion. The accuracy test is performed using synthetic and real data.

  15. Development of a novel Gateway-based vector system for efficient, multiparallel protein expression in Escherichia coli.

    Science.gov (United States)

    Freuler, Felix; Stettler, Thomas; Meyerhofer, Marco; Leder, Lukas; Mayr, Lorenz M

    2008-06-01

    We describe a cloning and expression system which is based on the Escherichia coli T7 expression system and Gateway recombination technology. We have produced numerous destination vectors with selected fusion tags and an additional set of entry vectors containing the gene of interest and optional labeling tags. This powerful system enables us to transfer a cDNA to several expression vectors in parallel and combine them with various labeling tags. To remove the attached amino terminal tags along with the unwanted attB1 site, we inserted PreScission protease cleavage sites. In contrast to the commercially available destination vectors, our plasmids provide kanamycin resistance, which can be an advantage when expressing toxic proteins in E. coli. Some small-scale protein expression experiments are shown to demonstrate the usefulness of these novel Gateway vectors. In summary, this system has some benefits over the widely used and commercially available Gateway standard system, and it enables many different combinations for expression constructs from a single gene of interest. PMID:18375142

  16. Flood damage assessment performed based on Support Vector Machines combined with Landsat TM imagery and GIS

    Science.gov (United States)

    Alouene, Y.; Petropoulos, G. P.; Kalogrias, A.; Papanikolaou, F.

    2012-04-01

    Floods are a water-related natural disaster affecting and often threatening different aspects of human life, such as property damage, economic degradation, and in some instances even loss of precious human lives. Being able to provide accurately and cost-effectively assessment of damage from floods is essential to both scientists and policy makers in many aspects ranging from mitigating to assessing damage extent as well as in rehabilitation of affected areas. Remote Sensing often combined with Geographical Information Systems (GIS) has generally shown a very promising potential in performing rapidly and cost-effectively flooding damage assessment, particularly so in remote, otherwise inaccessible locations. The progress in remote sensing during the last twenty years or so has resulted to the development of a large number of image processing techniques suitable for use with a range of remote sensing data in performing flooding damage assessment. Supervised image classification is regarded as one of the most widely used approaches employed for this purpose. Yet, the use of recently developed image classification algorithms such as of machine learning-based Support Vector Machines (SVMs) classifier has not been adequately investigated for this purpose. The objective of our work had been to quantitatively evaluate the ability of SVMs combined with Landsat TM multispectral imagery in performing a damage assessment of a flood occurred in a Mediterranean region. A further objective has been to examine if the inclusion of additional spectral information apart from the original TM bands in SVMs can improve flooded area extraction accuracy. As a case study is used the case of a river Evros flooding of 2010 located in the north of Greece, in which TM imagery before and shortly after the flooding was available. Assessment of the flooded area is performed in a GIS environment on the basis of classification accuracy assessment metrics as well as comparisons versus a vector

  17. Metrics for vector quantization-based parametric speech enhancement and separation

    DEFF Research Database (Denmark)

    Christensen, Mads Græsbøll

    2013-01-01

    Speech enhancement and separation algorithms sometimes employ a two-stage processing scheme, wherein the signal is first mapped to an intermediate low-dimensional parametric description after which the parameters are mapped to vectors in codebooks trained on, for exam- ple, individual noise......-free sources using a vector quantizer. To obtain accurate parameters, one must employ a good estimator in finding the parameters of the intermediate representation, like a maximum like- lihood estimator. This leaves some unanswered questions, however, like what metrics to use in the subsequent vector...

  18. RELIABILITY ASSESSMENT OF STRUCTURAL SYSTEMS BASED ON DIRECTIONAL VECTOR SIMULATION TECHNIQUE

    Institute of Scientific and Technical Information of China (English)

    Zhang Liangxin; Hu Yunchang

    2000-01-01

    The new improved directional vector simulation method for analyzing the reliability of struc tural systems failure probability is researched. This paper also points out the defects of general directional vector simulation, and gives rise to a new higher accuracy approximate integral formula of structural systems failure probability. A new geometric meaning of characteristic function is obtained. A new simple method of generating uniformly distributed random vector samples in n-dimensional unit hyper-spherical surface is put forward and strictly proved. This method is easy to put into practice. Numerical examples are given to show the applicability and effectiveness of the suggested approach to structural systems reliability problems.

  19. Hybrid-parallel sparse matrix-vector multiplication with explicit communication overlap on current multicore-based systems

    CERN Document Server

    Schubert, Gerald; Hager, Georg; Wellein, Gerhard

    2011-01-01

    We evaluate optimized parallel sparse matrix-vector operations for several representative application areas on widespread multicore-based cluster configurations. First the single-socket baseline performance is analyzed and modeled with respect to basic architectural properties of standard multicore chips. Beyond the single node, the performance of parallel sparse matrix-vector operations is often limited by communication overhead. Starting from the observation that nonblocking MPI is not able to hide communication cost using standard MPI implementations, we demonstrate that explicit overlap of communication and computation can be achieved by using a dedicated communication thread, which may run on a virtual core. Moreover we identify performance benefits of hybrid MPI/OpenMP programming due to improved load balancing even without explicit communication overlap. We compare performance results for pure MPI, the widely used "vector-like" hybrid programming strategies, and explicit overlap on a modern multicore-b...

  20. A NOVEL ARTIFICIAL HYDROCARBON NETWORKS BASED SPACE VECTOR PULSE WIDTH MODULATION CONTROLLER FOR INDUCTION MOTORS

    Directory of Open Access Journals (Sweden)

    Hiram Ponce

    2014-01-01

    Full Text Available Most of machine-operated industrial processes implement electric machinery as their work sources, implying the necessary improvement of control techniques and power electronics drivers. Many years have passed since the control conflicts related to induction motors have been overcome through torque-flux control techniques so their advantages over direct current motors have made them to be the most common electric actuator found behind industrial automation. In fact, induction motors can be easily operated using a Direct Torque Control (DTC. Since, it is based on a hysteresis control of the torque and flux errors, its performance is characterized by a quick reaching of the set point, but also a high ripple on both torque and flux. In order to enhance that technique, this study introduces a novel hybrid fuzzy controller with artificial hydrocarbon networks (FMC that is used in a Space Vector Pulse Width Modulation (SVPWM technique, so-called FMC-SVPWM-DTC. In fact, this study describes the proposal and its design method. Experimental results over a velocity-torque cascade topology proved that the proposed FMC-SVPWM-DTC responses highly effective almost suppressing rippling in torque and flux. It also performed a faster speed response than in a conventional DTC. In that sense, the proposed FMC-SVPWM-DTC can be used an alternative approach for controlling induction motors.

  1. On the Coloring of Grid Wireless Sensor Networks: the Vector-Based Coloring Method

    CERN Document Server

    Amdouni, Ichrak; Minet, Pascale

    2011-01-01

    Graph coloring is used in wireless networks to optimize network resources: bandwidth and energy. Nodes access the medium according to their color. It is the responsibility of the coloring algorithm to ensure that interfering nodes do not have the same color. In this research report, we focus on wireless sensor networks with grid topologies. How does a coloring algorithm take advantage of the regularity of grid topology to provide an optimal periodic coloring, that is a coloring with the minimum number of colors? We propose the Vector-Based Coloring Method, denoted VCM, a new method that is able to provide an optimal periodic coloring for any radio transmission range and for any h-hop coloring, h>=1. This method consists in determining at which grid nodes a color can be reproduced without creating interferences between these nodes while minimizing the number of colors used. We compare the number of colors provided by VCM with the number of colors obtained by a distributed coloring algorithm with line and colum...

  2. A Fault Alarm and Diagnosis Method Based on Sensitive Parameters and Support Vector Machine

    Science.gov (United States)

    Zhang, Jinjie; Yao, Ziyun; Lv, Zhiquan; Zhu, Qunxiong; Xu, Fengtian; Jiang, Zhinong

    2015-08-01

    Study on the extraction of fault feature and the diagnostic technique of reciprocating compressor is one of the hot research topics in the field of reciprocating machinery fault diagnosis at present. A large number of feature extraction and classification methods have been widely applied in the related research, but the practical fault alarm and the accuracy of diagnosis have not been effectively improved. Developing feature extraction and classification methods to meet the requirements of typical fault alarm and automatic diagnosis in practical engineering is urgent task. The typical mechanical faults of reciprocating compressor are presented in the paper, and the existing data of online monitoring system is used to extract fault feature parameters within 15 types in total; the inner sensitive connection between faults and the feature parameters has been made clear by using the distance evaluation technique, also sensitive characteristic parameters of different faults have been obtained. On this basis, a method based on fault feature parameters and support vector machine (SVM) is developed, which will be applied to practical fault diagnosis. A better ability of early fault warning has been proved by the experiment and the practical fault cases. Automatic classification by using the SVM to the data of fault alarm has obtained better diagnostic accuracy.

  3. 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.

  4. Classifying Data Sets Using Support Vector Machines Based on Geometric Distance

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    Support vector machines (SVMs) are not as favored for large-scale data mining as for pattern recognition and machine learning because the training complexity of SVMs is highly dependent on the size of data set. This paper presents a geometric distance-based SVM (GDB-SVM). It takes the distance between a point and classified hyperplane as classification rule,and is designed on the basis of theoretical analysis and geometric intuition. Experimental code is derived from LibSVM with Microsoft Visual C ++ 6.0 as system of translating and editing. Four predicted results of five of GDB-SVM are better than those of the method of one against all (OAA). Three predicted results of five of GDB-SVM are better than those of the method of one against one (OAO). Experiments on real data sets show that GDB-SVM is not only superior to the methods of OAA and OAO,but highly scalable for large data sets while generating high classification accuracy.

  5. Off-Line Signature Authentication Based on Moment Invariants Using Support Vector Machine

    Directory of Open Access Journals (Sweden)

    k. R. Radhika

    2010-01-01

    Full Text Available Problem statement: The research addressed the computational load reduction in off-line signature verification based on minimal features using bayes classifier, fast Fourier transform, linear discriminant analysis, principal component analysis and support vector machine approaches. Approach: The variation of signature in genuine cases is studied extensively, to predict the set of quad tree components in a genuine sample for one person with minimum variance criteria. Using training samples, with a high degree of certainty the Minimum Variance Quad tree Components (MVQC of a signature for a person are listed to apply on imposter sample. First, Hu moment is applied on the selected subsections. The summation values of the subsections are provided as feature to classifiers. Results: Results showed that the SVM classifier yielded the most promising 8% False Rejection Rate (FRR and 10% False Acceptance Rate (FAR. The signature is a biometric, where variations in a genuine case, is a natural expectation. In the genuine signature, certain parts of signature vary from one instance to another. Conclusion: The proposed system aimed to provide simple, faster robust system using less number of features when compared to state of art works.

  6. Large-scale ligand-based predictive modelling using support vector machines.

    Science.gov (United States)

    Alvarsson, Jonathan; Lampa, Samuel; Schaal, Wesley; Andersson, Claes; Wikberg, Jarl E S; Spjuth, Ola

    2016-01-01

    The increasing size of datasets in drug discovery makes it challenging to build robust and accurate predictive models within a reasonable amount of time. In order to investigate the effect of dataset sizes on predictive performance and modelling time, ligand-based regression models were trained on open datasets of varying sizes of up to 1.2 million chemical structures. For modelling, two implementations of support vector machines (SVM) were used. Chemical structures were described by the signatures molecular descriptor. Results showed that for the larger datasets, the LIBLINEAR SVM implementation performed on par with the well-established libsvm with a radial basis function kernel, but with dramatically less time for model building even on modest computer resources. Using a non-linear kernel proved to be infeasible for large data sizes, even with substantial computational resources on a computer cluster. To deploy the resulting models, we extended the Bioclipse decision support framework to support models from LIBLINEAR and made our models of logD and solubility available from within Bioclipse. PMID:27516811

  7. Power Load Event Detection and Classification Based on Edge Symbol Analysis and Support Vector Machine

    Directory of Open Access Journals (Sweden)

    Lei Jiang

    2012-01-01

    Full Text Available Energy signature analysis of power appliance is the core of nonintrusive load monitoring (NILM where the detailed data of the appliances used in houses are obtained by analyzing changes in the voltage and current. This paper focuses on developing an automatic power load event detection and appliance classification based on machine learning. In power load event detection, the paper presents a new transient detection algorithm. By turn-on and turn-off transient waveforms analysis, it can accurately detect the edge point when a device is switched on or switched off. The proposed load classification technique can identify different power appliances with improved recognition accuracy and computational speed. The load classification method is composed of two processes including frequency feature analysis and support vector machine. The experimental results indicated that the incorporation of the new edge detection and turn-on and turn-off transient signature analysis into NILM revealed more information than traditional NILM methods. The load classification method has achieved more than ninety percent recognition rate.

  8. Delineating Individual Trees from Lidar Data: A Comparison of Vector- and Raster-based Segmentation Approaches

    Directory of Open Access Journals (Sweden)

    Maggi Kelly

    2013-08-01

    Full Text Available Light detection and ranging (lidar data is increasingly being used for ecosystem monitoring across geographic scales. This work concentrates on delineating individual trees in topographically-complex, mixed conifer forest across the California’s Sierra Nevada. We delineated individual trees using vector data and a 3D lidar point cloud segmentation algorithm, and using raster data with an object-based image analysis (OBIA of a canopy height model (CHM. The two approaches are compared to each other and to ground reference data. We used high density (9 pulses/m2, discreet lidar data and WorldView-2 imagery to delineate individual trees, and to classify them by species or species types. We also identified a new method to correct artifacts in a high-resolution CHM. Our main focus was to determine the difference between the two types of approaches and to identify the one that produces more realistic results. We compared the delineations via tree detection, tree heights, and the shape of the generated polygons. The tree height agreement was high between the two approaches and the ground data (r2: 0.93–0.96. Tree detection rates increased for more dominant trees (8–100 percent. The two approaches delineated tree boundaries that differed in shape: the lidar-approach produced fewer, more complex, and larger polygons that more closely resembled real forest structure.

  9. Knodle: A Support Vector Machines-Based Automatic Perception of Organic Molecules from 3D Coordinates.

    Science.gov (United States)

    Kadukova, Maria; Grudinin, Sergei

    2016-08-22

    Here we address the problem of the assignment of atom types and bond orders in low molecular weight compounds. For this purpose, we have developed a prediction model based on nonlinear Support Vector Machines (SVM), implemented in a KNOwledge-Driven Ligand Extractor called Knodle, a software library for the recognition of atomic types, hybridization states, and bond orders in the structures of small molecules. We trained the model using an excessive amount of structural data collected from the PDBbindCN database. Accuracy of the results and the running time of our method is comparable with other popular methods, such as NAOMI, fconv, and I-interpret. On the popular Labute's benchmark set consisting of 179 protein-ligand complexes, Knodle makes five to six perception errors, NAOMI makes seven errors, I-interpret makes nine errors, and fconv makes 13 errors. On a larger set of 3,000 protein-ligand structures collected from the PDBBindCN general data set (v2014), Knodle and NAOMI have a comparable accuracy of approximately 3.9% and 4.7% of errors, I-interpret made 6.0% of errors, while fconv produced approximately 12.8% of errors. On a more general set of 332,974 entries collected from the Ligand Expo database, Knodle made 4.5% of errors. Overall, our study demonstrates the efficiency and robustness of nonlinear SVM in structure perception tasks. Knodle is available at https://team.inria.fr/nano-d/software/Knodle . PMID:27405533

  10. 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.

  11. A Novel Classification Algorithm Based on Incremental Semi-Supervised Support Vector Machine

    Science.gov (United States)

    Gao, Fei; Mei, Jingyuan; Sun, Jinping; Wang, Jun; Yang, Erfu; Hussain, Amir

    2015-01-01

    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. PMID:26275294

  12. Video Waterscrambling: Towards a Video Protection Scheme Based on the Disturbance of Motion Vectors

    Directory of Open Access Journals (Sweden)

    Yann Bodo

    2004-10-01

    Full Text Available With the popularity of high-bandwidth modems and peer-to-peer networks, the contents of videos must be highly protected from piracy. Traditionally, the models utilized to protect this kind of content are scrambling and watermarking. While the former protects the content against eavesdropping (a priori protection, the latter aims at providing a protection against illegal mass distribution (a posteriori protection. Today, researchers agree that both models must be used conjointly to reach a sufficient level of security. However, scrambling works generally by encryption resulting in an unintelligible content for the end-user. At the moment, some applications (such as e-commerce may require a slight degradation of content so that the user has an idea of the content before buying it. In this paper, we propose a new video protection model, called waterscrambling, whose aim is to give such a quality degradation-based security model. This model works in the compressed domain and disturbs the motion vectors, degrading the video quality. It also allows embedding of a classical invisible watermark enabling protection against mass distribution. In fact, our model can be seen as an intermediary solution to scrambling and watermarking.

  13. A replicating plasmid-based vector for GFP expression in Mycoplasma hyopneumoniae.

    Science.gov (United States)

    Ishag, H Z A; Liu, M J; Yang, R S; Xiong, Q Y; Feng, Z X; Shao, G Q

    2016-01-01

    Mycoplasma hyopneumoniae (M. hyopneumoniae) causes porcine enzootic pneumonia (PEP) that significantly affects the pig industry worldwide. Despite the availability of the whole genome sequence, studies on the pathogenesis of this organism have been limited due to the lack of a genetic manipulation system. Therefore, the aim of the current study was to generate a general GFP reporter vector based on a replicating plasmid. Here, we describe the feasibility of GFP reporter expression in M. hyopneumoniae (strain 168L) controlled by the p97 gene promoter of this mycoplasma. An expression plasmid (pMD18-TOgfp) containing the p97 gene promoter, and origin of replication (oriC) of M. hyopneumoniae, tetracycline resistant marker (tetM), and GFP was constructed and used to transform competent M. hyopneumoniae cells. We observed green fluorescence in M. hyopneumoniae transformants under fluorescence microscopy, which indicates that there was expression of the GFP reporter that was driven by the p97 gene promoter. Additionally, an electroporation method for M. hyopneumoniae with an efficiency of approximately 1 x 10(-6) transformants/μg plasmid DNA was optimized and is described herein. In conclusion, our data demonstrate the susceptibility of M. hyopneumoniae to genetic manipulation whereby foreign genes are expressed. This work may encourage the development of genetic tools to manipulate the genome of M. hyopneumoniae for functional genomic analyses. PMID:27173288

  14. An Artificial Immune System-Based Support Vector Machine Approach for Classifying Ultrasound Breast Tumor Images.

    Science.gov (United States)

    Wu, Wen-Jie; Lin, Shih-Wei; Moon, Woo Kyung

    2015-10-01

    A rapid and highly accurate diagnostic tool for distinguishing benign tumors from malignant ones is required owing to the high incidence of breast cancer. Although various computer-aided diagnosis (CAD) systems have been developed to interpret ultrasound images of breast tumors, feature selection and the setting of parameters are still essential to classification accuracy and the minimization of computational complexity. This work develops a highly accurate CAD system that is based on a support vector machine (SVM) and the artificial immune system (AIS) algorithm for evaluating breast tumors. Experiments demonstrate that the accuracy of the proposed CAD system for classifying breast tumors is 96.67%. The sensitivity, specificity, PPV, and NPV of the proposed CAD system are 96.67, 96.67, 95.60, and 97.48%, respectively. The receiver operator characteristic (ROC) area index A z is 0.9827. Hence, the proposed CAD system can reduce the number of biopsies and yield useful results that assist physicians in diagnosing breast tumors. PMID:25561066

  15. QoS Requirement Generation and Algorithm Selection for Composite Service Based on Reference Vector

    Institute of Scientific and Technical Information of China (English)

    Bang-Yu Wu; Chi-Hung Chi; Shi-Jie Xu; Ming Gu; Jia-Guang Sun

    2009-01-01

    Under SOA (Service-Oriented Architecture), composite service is formed by aggregating multiple component services together in a given workflow. One key criterion of this research topic is QoS composition. Most work on service composition mainly focuses on the algorithms about how to compose services according to assumed QoS, without considering where the required QoS comes from and the selection of user preferred composition algorithm among those with different computational cost and different selection results. In this paper, we propose to strengthen current service composition mechanism by generation of QoS requirement and its algorithm selection based on the QoS reference vectors which are calculated optimally from the existing individual services' QoS by registry to represent QoS overview about the best QoS,the worst (or most economical) QoS, or the average QoS of all composite services. To implement QoS requirement, which is determined according to QoS overview, this paper introduces two selection algorithms as two kinds of experiment examples,one aiming at the most accurate service selection and the other chasing for trade-off between selection cost and result.Experimental results show our mechanism can help the requester achieve his expected composite service with appropriate QoS requirement and customized selection algorithm.

  16. Online learning vector quantization: a harmonic competition approach based on conservation network.

    Science.gov (United States)

    Wang, J H; Sun, W D

    1999-01-01

    This paper presents a self-creating neural network in which a conservation principle is incorporated with the competitive learning algorithm to harmonize equi-probable and equi-distortion criteria. Each node is associated with a measure of vitality which is updated after each input presentation. The total amount of vitality in the network at any time is 1, hence the name conservation. Competitive learning based on a vitality conservation principle is near-optimum, in the sense that problem of trapping in a local minimum is alleviated by adding perturbations to the learning rate during node generation processes. Combined with a procedure that redistributes the learning rate variables after generation and removal of nodes, the competitive conservation strategy provides a novel approach to the problem of harmonizing equi-error and equi-probable criteria. The training process is smooth and incremental, it not only achieves the biologically plausible learning property, but also facilitates systematic derivations for training parameters. Comparison studies on learning vector quantization involving stationary and nonstationary, structured and nonstructured inputs demonstrate that the proposed network outperforms other competitive networks in terms of quantization error, learning speed, and codeword search efficiency. PMID:18252343

  17. Advances in Viral Vector-Based TRAIL Gene Therapy for Cancer

    International Nuclear Information System (INIS)

    Numerous biologic approaches are being investigated as anti-cancer therapies in an attempt to induce tumor regression while circumventing the toxic side effects associated with standard chemo- or radiotherapies. Among these, tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) has shown particular promise in pre-clinical and early clinical trials, due to its preferential ability to induce apoptotic cell death in cancer cells and its minimal toxicity. One limitation of TRAIL use is the fact that many tumor types display an inherent resistance to TRAIL-induced apoptosis. To circumvent this problem, researchers have explored a number of strategies to optimize TRAIL delivery and to improve its efficacy via co-administration with other anti-cancer agents. In this review, we will focus on TRAIL-based gene therapy approaches for the treatment of malignancies. We will discuss the main viral vectors that are being used for TRAIL gene therapy and the strategies that are currently being attempted to improve the efficacy of TRAIL as an anti-cancer therapeutic

  18. Bioreducible cross-linked polymers based on G1 peptide dendrimer as potential gene delivery vectors.

    Science.gov (United States)

    Li, Chun-Yan; Wang, Hai-Jiao; Cao, Jing-Ming; Zhang, Ji; Yu, Xiao-Qi

    2014-11-24

    A series of cationic polymers based on low generation (G1) peptide dendrimer were synthesized with disulfide-containing linkages. The DNA binding abilities of the target polymers were studied by gel electrophoresis and fluorescence quenching assay. The bioreducible property of the disulfide-containing polymers P2 and P3 was also investigated in the presence of dithiothreitol (DTT). Results from dynamic light scattering (DLS) and transmission electron microscopy (TEM) assays reveal that these materials may condense DNA into nanoparticles with proper sizes and zeta-potentials. In vitro cell experiments show that compared to branched 25 KDa PEI, P2 and P3 may exhibit much higher gene transfection efficiency and lower cytotoxicity in both HEK293 and U-2OS cells. Additionally, polymer prepared from Michael addition gives better gene transfection ability, while polymer prepared from ring-opening reaction has better serum tolerance. Results indicate that these polymers might be promising non-viral gene vectors for their easy preparation, very low cytotoxicity, and good transfection efficiency. PMID:25282264

  19. Fault diagnosis of direct-drive wind turbine based on support vector machine

    International Nuclear Information System (INIS)

    A fault diagnosis method of direct-drive wind turbine based on support vector machine (SVM) and feature selection is presented. The time-domain feature parameters of main shaft vibration signal in the horizontal and vertical directions are considered in the method. Firstly, in laboratory scale five experiments of direct-drive wind turbine with normal condition, wind wheel mass imbalance fault, wind wheel aerodynamic imbalance fault, yaw fault and blade airfoil change fault are carried out. The features of five experiments are analyzed. Secondly, the sensitive time-domain feature parameters in the horizontal and vertical directions of vibration signal in the five conditions are selected and used as feature samples. By training, the mapping relation between feature parameters and fault types are established in SVM model. Finally, the performance of the proposed method is verified through experimental data. The results show that the proposed method is effective in identifying the fault of wind turbine. It has good classification ability and robustness to diagnose the fault of direct-drive wind turbine.

  20. Considering polarization in MODIS-based cloud property retrievals by using a vector radiative transfer code

    International Nuclear Information System (INIS)

    In this study, a full-vector, adding–doubling radiative transfer model is used to investigate the influence of the polarization state on cloud property retrievals from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite observations. Two sets of lookup tables (LUTs) are developed for the retrieval purposes, both of which provide water cloud and ice cloud reflectivity functions at two wavelengths in various sun-satellite viewing geometries. However, only one of the LUTs considers polarization. The MODIS reflectivity observations at 0.65 μm (band 1) and 2.13 μm (band 7) are used to infer the cloud optical thickness and particle effective diameter, respectively. Results indicate that the retrievals for both water cloud and ice cloud show considerable sensitivity to polarization. The retrieved water and ice cloud effective diameter and optical thickness differences can vary by as much as ±15% due to polarization state considerations. In particular, the polarization state has more influence on completely smooth ice particles than on severely roughened ice particles. - Highlights: • Impact of polarization on satellite-based retrieval of water/ice cloud properties is studied. • Inclusion of polarization can change water/ice optical thickness and effective diameter values by up to ±15%. • Influence of polarization on cloud property retrievals depends on sun-satellite viewing geometries

  1. IntelliGO: a new vector-based semantic similarity measure including annotation origin

    Directory of Open Access Journals (Sweden)

    Devignes Marie-Dominique

    2010-12-01

    Full Text Available Abstract Background The Gene Ontology (GO is a well known controlled vocabulary describing the biological process, molecular function and cellular component aspects of gene annotation. It has become a widely used knowledge source in bioinformatics for annotating genes and measuring their semantic similarity. These measures generally involve the GO graph structure, the information content of GO aspects, or a combination of both. However, only a few of the semantic similarity measures described so far can handle GO annotations differently according to their origin (i.e. their evidence codes. Results We present here a new semantic similarity measure called IntelliGO which integrates several complementary properties in a novel vector space model. The coefficients associated with each GO term that annotates a given gene or protein include its information content as well as a customized value for each type of GO evidence code. The generalized cosine similarity measure, used for calculating the dot product between two vectors, has been rigorously adapted to the context of the GO graph. The IntelliGO similarity measure is tested on two benchmark datasets consisting of KEGG pathways and Pfam domains grouped as clans, considering the GO biological process and molecular function terms, respectively, for a total of 683 yeast and human genes and involving more than 67,900 pair-wise comparisons. The ability of the IntelliGO similarity measure to express the biological cohesion of sets of genes compares favourably to four existing similarity measures. For inter-set comparison, it consistently discriminates between distinct sets of genes. Furthermore, the IntelliGO similarity measure allows the influence of weights assigned to evidence codes to be checked. Finally, the results obtained with a complementary reference technique give intermediate but correct correlation values with the sequence similarity, Pfam, and Enzyme classifications when compared to

  2. Content-based retrieval based on binary vectors for 2-D medical images

    Institute of Scientific and Technical Information of China (English)

    龚鹏; 邹亚东; 洪海

    2003-01-01

    In medical research and clinical diagnosis, automated or computer-assisted classification and retrieval methods are highly desirable to offset the high cost of manual classification and manipulation by medical experts. To facilitate the decision-making in the health-care and the related areas, in this paper, a two-step content-based medical image retrieval algorithm is proposed. Firstly, in the preprocessing step, the image segmentation is performed to distinguish image objects, and on the basis of the ...

  3. Evaluation of Zika Vector Control Strategies Using Agent-Based Modeling

    OpenAIRE

    Gunaratne, Chathika; Akbas, Mustafa Ilhan; Garibay, Ivan; Ozmen, Ozlem

    2016-01-01

    Aedes Aegypti is the vector of several deadly diseases, including Zika. Effective and sustainable vector control measures must be deployed to keep A. aegypti numbers under control. The distribution of A. Aegypti is subject to spatial and climatic constraints. Using agentbased modeling, we model the population dynamics of A. aegypti subjected to the spatial and climatic constraints of a neighborhood in the Key West. Satellite imagery was used to identify vegetation, houses(CO2 zones) both crit...

  4. Towards a resource-based habitat approach for spatial modelling of vector-borne disease risks

    OpenAIRE

    Hartemink, Nienke; Vanwambeke, Sophie O; Purse, Bethan V.; Gilbert, Marius; Van Dyck, Hans

    2015-01-01

    Given the veterinary and public health impact of vector-borne diseases, there is a clear need to assess the suitability of landscapes for the emergence and spread of these diseases. Current approaches for predicting disease risks neglect key features of the landscape as components of the functional habitat of vectors or hosts, and hence of the pathogen. Empirical-statistical methods do not explicitly incorporate biological mechanisms, whereas current mechanistic models are rarely spatially ex...

  5. An Artificial Intelligence Approach for Groutability Estimation Based on Autotuning Support Vector Machine

    OpenAIRE

    Hong-Hai Tran; Nhat-Duc Hoang

    2014-01-01

    Permeation grouting is a commonly used approach for soil improvement in construction engineering. Thus, predicting the results of grouting activities is a crucial task that needs to be carried out in the planning phase of any grouting project. In this research, a novel artificial intelligence approach—autotuning support vector machine—is proposed to forecast the result of grouting activities that employ microfine cement grouts. In the new model, the support vector machine (SVM) algorithm is u...

  6. Bearing Fault Diagnosis Based on Multiscale Permutation Entropy and Support Vector Machine

    OpenAIRE

    Jian-Jiun Ding; Chun-Chieh Wang; Chiu-Wen Wu; Po-Hung Wu; Shuen-De Wu

    2012-01-01

    Bearing fault diagnosis has attracted significant attention over the past few decades. It consists of two major parts: vibration signal feature extraction and condition classification for the extracted features. In this paper, multiscale permutation entropy (MPE) was introduced for feature extraction from faulty bearing vibration signals. After extracting feature vectors by MPE, the support vector machine (SVM) was applied to automate the fault diagnosis procedure. Simulation results demonstr...

  7. A 'Drift' algorithm for integrating vector polyline and DEM based on the spherical DQG

    International Nuclear Information System (INIS)

    The efficient integration method of vector and DEM data on a global scale is one of the important issues in the community of Digital Earth. Among the existing methods, geometry-based approach maintains the characteristics of vector data necessary for inquiry and analysis. However, the complexity of geometry-based approach, which needs lots of interpolation calculation, limits its applications greatly in the multi-source spatial data integration on a global scale. To overcome this serious deficiency, a novel 'drift' algorithm is developed based on the spherical Degenerate Quadtree Grid (DQG) on which the global DEMs data is represented. The main principle of this algorithm is that the vector node in a DQG cell can be moved to the cell corner-point without changing the visualization effects if the cell is smaller or equal to a pixel of screen. A detailed algorithm and the multi-scale operation steps are also presented. By the 'drift' algorithm, the vector polylines and DEM grids are integrated seamlessly, avoiding lots of interpolation calculating. Based on the approach described above, we have developed a computer program in platform OpenGL 3D API with VC++ language. In this experiment, USGS GTOPO30 DEM data and 1:1,000,000 DCW roads data sets in China area are selected. Tests have shown that time consumption of the 'drift' algorithm is only about 25% of that of the traditional ones, moreover, the mean error of drift operation on vector nodes can be controlled within about half a DQG cell. In the end, the conclusions and future works are also given

  8. Application of Support Vector Machine-Based Semiactive Control for Seismic Protection of Structures with Magnetorheological Dampers

    OpenAIRE

    Shengning Lan; Qing Liu; Chunxiang Li

    2012-01-01

    Based on recent research by Li and Liu in 2011, this paper proposes the application of support vector machine- (SVM-) based semiactive control methodology for seismic protection of structures with magnetorheological (MR) dampers. An important and challenging task of designing the MR dampers is to develop an effective semiactive control strategy that can fully exploit the capabilities of MR dampers. However, amplification of the local acceleration response of structures exists in the widely us...

  9. Quantitative evaluation of first, second, and third generation hairpin systems reveals the limit of mammalian vector-based RNAi

    OpenAIRE

    Watanabe, Colin; Cuellar, Trinna L.; Haley, Benjamin

    2016-01-01

    ABSTRACT Incorporating miRNA-like features into vector-based hairpin scaffolds has been shown to augment small RNA processing and RNAi efficiency. Therefore, defining an optimal, native hairpin context may obviate a need for hairpin-specific targeting design schemes, which confound the movement of functional siRNAs into shRNA/artificial miRNA backbones, or large-scale screens to identify efficacious sequences. Thus, we used quantitative cell-based assays to compare separate third generation a...

  10. Support vector regression based prediction of global solar radiation on a horizontal surface

    International Nuclear Information System (INIS)

    Highlights: • We appraise precision of the SVR methodology to estimate global solar radiation. • Sunshine hours and maximum possible sunshine hours are used as only input elements. • The predictions of SVRs are compared with empirical models. • SVR models show high level of precision for global radiation prediction. • SVR-rbf outperforms the SVR-poly in terms of accuracy. - Abstract: In this paper, the support vector regression (SVR) methodology was adopted to estimate the horizontal global solar radiation (HGSR) based upon sunshine hours (n) and maximum possible sunshine hours (N) as input parameters. The capability of two SVRs of radial basis function (rbf) and polynomial basis function (poly) was investigated and compared with the conventional sunshine duration-based empirical models. For this purpose, long-term measured data for a city situated in sunny part of Iran was utilized. Exploration was performed on both daily and monthly mean scales to accomplish a more complete analysis. Through a statistical comparative study, using 6 well-known statistical parameters, the results proved the superiority of developed SVR models over the empirical models. Also, SVR-rbf outperformed the SVR-poly in terms of accuracy. For SVR-rbf model on daily estimation, the mean absolute percentage error, mean absolute bias error, root mean square error, relative root mean square error and coefficient of determination were 10.4466%, 1.2524 MJ/m2, 2.0046 MJ/m2, 9.0343% and 0.9133, respectively. Also, on monthly mean estimation the values were 1.4078%, 0.2845 MJ/m2, 0.45044 MJ/m2, 2.2576% and 0.9949, respectively. The achieved results conclusively demonstrated that the SVR-rbf is highly qualified for HGSR estimation using n and N

  11. 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.

  12. Prediction of CO concentrations based on a hybrid Partial Least Square and Support Vector Machine model

    Science.gov (United States)

    Yeganeh, B.; Motlagh, M. Shafie Pour; Rashidi, Y.; Kamalan, H.

    2012-08-01

    Due to the health impacts caused by exposures to air pollutants in urban areas, monitoring and forecasting of air quality parameters have become popular as an important topic in atmospheric and environmental research today. The knowledge on the dynamics and complexity of air pollutants behavior has made artificial intelligence models as a useful tool for a more accurate pollutant concentration prediction. This paper focuses on an innovative method of daily air pollution prediction using combination of Support Vector Machine (SVM) as predictor and Partial Least Square (PLS) as a data selection tool based on the measured values of CO concentrations. The CO concentrations of Rey monitoring station in the south of Tehran, from Jan. 2007 to Feb. 2011, have been used to test the effectiveness of this method. The hourly CO concentrations have been predicted using the SVM and the hybrid PLS-SVM models. Similarly, daily CO concentrations have been predicted based on the aforementioned four years measured data. Results demonstrated that both models have good prediction ability; however the hybrid PLS-SVM has better accuracy. In the analysis presented in this paper, statistic estimators including relative mean errors, root mean squared errors and the mean absolute relative error have been employed to compare performances of the models. It has been concluded that the errors decrease after size reduction and coefficients of determination increase from 56 to 81% for SVM model to 65-85% for hybrid PLS-SVM model respectively. Also it was found that the hybrid PLS-SVM model required lower computational time than SVM model as expected, hence supporting the more accurate and faster prediction ability of hybrid PLS-SVM model.

  13. Physical Characterization of Gemini Surfactant-Based Synthetic Vectors for the Delivery of Linear Covalently Closed (LCC DNA Ministrings.

    Directory of Open Access Journals (Sweden)

    Chi Hong Sum

    Full Text Available In combination with novel linear covalently closed (LCC DNA minivectors, referred to as DNA ministrings, a gemini surfactant-based synthetic vector for gene delivery has been shown to exhibit enhanced delivery and bioavailability while offering a heightened safety profile. Due to topological differences from conventional circular covalently closed (CCC plasmid DNA vectors, the linear topology of LCC DNA ministrings may present differences with regards to DNA interaction and the physicochemical properties influencing DNA-surfactant interactions in the formulation of lipoplexed particles. In this study, N,N-bis(dimethylhexadecyl-α,ω-propanediammonium(16-3-16gemini-based synthetic vectors, incorporating either CCC plasmid or LCC DNA ministrings, were characterized and compared with respect to particle size, zeta potential, DNA encapsulation, DNase sensitivity, and in vitro transgene delivery efficacy. Through comparative analysis, differences between CCC plasmid DNA and LCC DNA ministrings led to variations in the physical properties of the resulting lipoplexes after complexation with 16-3-16 gemini surfactants. Despite the size disparities between the plasmid DNA vectors (CCC and DNA ministrings (LCC, differences in DNA topology resulted in the generation of lipoplexes of comparable particle sizes. The capacity for ministring (LCC derived lipoplexes to undergo complete counterion release during lipoplex formation contributed to improved DNA encapsulation, protection from DNase degradation, and in vitro transgene delivery.

  14. Physical Characterization of Gemini Surfactant-Based Synthetic Vectors for the Delivery of Linear Covalently Closed (LCC) DNA Ministrings.

    Science.gov (United States)

    Sum, Chi Hong; Nafissi, Nafiseh; Slavcev, Roderick A; Wettig, Shawn

    2015-01-01

    In combination with novel linear covalently closed (LCC) DNA minivectors, referred to as DNA ministrings, a gemini surfactant-based synthetic vector for gene delivery has been shown to exhibit enhanced delivery and bioavailability while offering a heightened safety profile. Due to topological differences from conventional circular covalently closed (CCC) plasmid DNA vectors, the linear topology of LCC DNA ministrings may present differences with regards to DNA interaction and the physicochemical properties influencing DNA-surfactant interactions in the formulation of lipoplexed particles. In this study, N,N-bis(dimethylhexadecyl)-α,ω-propanediammonium(16-3-16)gemini-based synthetic vectors, incorporating either CCC plasmid or LCC DNA ministrings, were characterized and compared with respect to particle size, zeta potential, DNA encapsulation, DNase sensitivity, and in vitro transgene delivery efficacy. Through comparative analysis, differences between CCC plasmid DNA and LCC DNA ministrings led to variations in the physical properties of the resulting lipoplexes after complexation with 16-3-16 gemini surfactants. Despite the size disparities between the plasmid DNA vectors (CCC) and DNA ministrings (LCC), differences in DNA topology resulted in the generation of lipoplexes of comparable particle sizes. The capacity for ministring (LCC) derived lipoplexes to undergo complete counterion release during lipoplex formation contributed to improved DNA encapsulation, protection from DNase degradation, and in vitro transgene delivery. PMID:26561857

  15. Local effects of redundant terrestrial and GPS-based tie vectors in ITRF-like combinations

    Science.gov (United States)

    Abbondanza, Claudio; Altamimi, Zuheir; Sarti, Pierguido; Negusini, Monia; Vittuari, Luca

    2009-11-01

    Tie vectors (TVs) between co-located space geodetic instruments are essential for combining terrestrial reference frames (TRFs) realised using different techniques. They provide relative positioning between instrumental reference points (RPs) which are part of a global geodetic network such as the international terrestrial reference frame (ITRF). This paper gathers the set of very long baseline interferometry (VLBI)-global positioning system (GPS) local ties performed at the observatory of Medicina (Northern Italy) during the years 2001-2006 and discusses some important aspects related to the usage of co-location ties in the combinations of TRFs. Two measurement approaches of local survey are considered here: a GPS-based approach and a classical approach based on terrestrial observations (i.e. angles, distances and height differences). The behaviour of terrestrial local ties, which routinely join combinations of space geodetic solutions, is compared to that of GPS-based local ties. In particular, we have performed and analysed different combinations of satellite laser ranging (SLR), VLBI and GPS long term solutions in order to (i) evaluate the local effects of the insertion of the series of TVs computed at Medicina, (ii) investigate the consistency of GPS-based TVs with respect to space geodetic solutions, (iii) discuss the effects of an imprecise alignment of TVs from a local to a global reference frame. Results of ITRF-like combinations show that terrestrial TVs originate the smallest residuals in all the three components. In most cases, GPS-based TVs fit space geodetic solutions very well, especially in the horizontal components (N, E). On the contrary, the estimation of the VLBI RP Up component through GPS technique appears to be awkward, since the corresponding post fit residuals are considerably larger. Besides, combination tests including multi-temporal TVs display local effects of residual redistribution, when compared to those solutions where Medicina TVs

  16. A comprehensive comparison of random forests and support vector machines for microarray-based cancer classification

    Directory of Open Access Journals (Sweden)

    Wang Lily

    2008-07-01

    Full Text Available Abstract Background Cancer diagnosis and clinical outcome prediction are among the most important emerging applications of gene expression microarray technology with several molecular signatures on their way toward clinical deployment. Use of the most accurate classification algorithms available for microarray gene expression data is a critical ingredient in order to develop the best possible molecular signatures for patient care. As suggested by a large body of literature to date, support vector machines can be considered "best of class" algorithms for classification of such data. Recent work, however, suggests that random forest classifiers may outperform support vector machines in this domain. Results In the present paper we identify methodological biases of prior work comparing random forests and support vector machines and conduct a new rigorous evaluation of the two algorithms that corrects these limitations. Our experiments use 22 diagnostic and prognostic datasets and show that support vector machines outperform random forests, often by a large margin. Our data also underlines the importance of sound research design in benchmarking and comparison of bioinformatics algorithms. Conclusion We found that both on average and in the majority of microarray datasets, random forests are outperformed by support vector machines both in the settings when no gene selection is performed and when several popular gene selection methods are used.

  17. Estimating differential quantities from point cloud based on a linear fitting of normal vectors

    Institute of Scientific and Technical Information of China (English)

    CHENG ZhangLin; ZHANG XiaoPeng

    2009-01-01

    Estimation of differential geometric properties on a discrete surface Is a fundamental work in computer graphics and computer vision.In this paper,we present an accurate and robust method for estimating differential quantities from unorganized point cloud.The principal curvatures and principal directions at each point are computed with the help of partial derivatives of the unit normal vector at that point,where the normal derivatives are estimated by fitting a linear function to each component of the normal vectors in a neighborhood.This method takes into account the normal information of all neighboring points and computes curvatures directly from the varlation of unit normal vectors,which improves the accuracy and robustness of curvature estimation on irregular sampled noisy data.The main advantage of our approach is that the estimation of curvatures at a point does not rely on the accuracy of the normal vector at that point,and the normal vectors can he refined In the process of curvature estimation.Compared with the state of the art methods for estimating curvatures and Darboux frames on both synthetic and real point clouds,the approach is shown to be more accurate and robust for noisy and unorganized point cloud data.

  18. Quantitative evaluation of first, second, and third generation hairpin systems reveals the limit of mammalian vector-based RNAi.

    Science.gov (United States)

    Watanabe, Colin; Cuellar, Trinna L; Haley, Benjamin

    2016-01-01

    Incorporating miRNA-like features into vector-based hairpin scaffolds has been shown to augment small RNA processing and RNAi efficiency. Therefore, defining an optimal, native hairpin context may obviate a need for hairpin-specific targeting design schemes, which confound the movement of functional siRNAs into shRNA/artificial miRNA backbones, or large-scale screens to identify efficacious sequences. Thus, we used quantitative cell-based assays to compare separate third generation artificial miRNA systems, miR-E (based on miR-30a) and miR-3G (based on miR-16-2 and first described in this study) to widely-adopted, first and second generation formats in both Pol-II and Pol-III expression vector contexts. Despite their unique structures and strandedness, and in contrast to first and second-generation RNAi triggers, the third generation formats operated with remarkable similarity to one another, and strong silencing was observed with a significant fraction of the evaluated target sequences within either promoter context. By pairing an established siRNA design algorithm with the third generation vectors we could readily identify targeting sequences that matched or exceeded the potency of those discovered through large-scale sensor-based assays. We find that third generation hairpin systems enable the maximal level of siRNA function, likely through enhanced processing and accumulation of precisely-defined guide RNAs. Therefore, we predict future gains in RNAi potency will come from improved hairpin expression and identification of optimal siRNA-intrinsic silencing properties rather than further modification of these scaffolds. Consequently, third generation systems should be the primary format for vector-based RNAi studies; miR-3G is advantageous due to its small expression cassette and simplified, cost-efficient cloning scheme. PMID:26786363

  19. A novel balanced-lethal host-vector system based on glmS.

    Directory of Open Access Journals (Sweden)

    Kwangsoo Kim

    Full Text Available During the last decade, an increasing number of papers have described the use of various genera of bacteria, including E. coli and S. typhimurium, in the treatment of cancer. This is primarily due to the facts that not only are these bacteria capable of accumulating in the tumor mass, but they can also be engineered to deliver specific therapeutic proteins directly to the tumor site. However, a major obstacle exists in that bacteria because the plasmid carrying the therapeutic gene is not needed for bacterial survival, these plasmids are often lost from the bacteria. Here, we report the development of a balanced-lethal host-vector system based on deletion of the glmS gene in E. coli and S. typhimurium. This system takes advantage of the phenotype of the GlmS(- mutant, which undergoes lysis in animal systems that lack the nutrients required for proliferation of the mutant bacteria, D-glucosamine (GlcN or N-acetyl-D-glucosamine (GlcNAc, components necessary for peptidoglycan synthesis. We demonstrate that plasmids carrying a glmS gene (GlmS(+p complemented the phenotype of the GlmS(- mutant, and that GlmS(+ p was maintained faithfully both in vitro and in an animal system in the absence of selection pressure. This was further verified by bioluminescent signals from GlmS (+pLux carried in bacteria that accumulated in grafted tumor tissue in a mouse model. The signal was up to several hundred-fold stronger than that from the control plasmid, pLux, due to faithful maintenance of the plasmid. We believe this system will allow to package a therapeutic gene onto an expression plasmid for bacterial delivery to the tumor site without subsequent loss of plasmid expression as well as to quantify bioluminescent bacteria using in vivo imaging by providing a direct correlation between photon flux and bacterial number.

  20. Support vector machine based classification and mapping of atherosclerotic plaques using fluorescence lifetime imaging (Conference Presentation)

    Science.gov (United States)

    Fatakdawala, Hussain; Gorpas, Dimitris S.; Bec, Julien; Ma, Dinglong M.; Yankelevich, Diego R.; Bishop, John W.; Marcu, Laura

    2016-02-01

    The progression of atherosclerosis in coronary vessels involves distinct pathological changes in the vessel wall. These changes manifest in the formation of a variety of plaque sub-types. The ability to detect and distinguish these plaques, especially thin-cap fibroatheromas (TCFA) may be relevant for guiding percutaneous coronary intervention as well as investigating new therapeutics. In this work we demonstrate the ability of fluorescence lifetime imaging (FLIm) derived parameters (lifetime values from sub-bands 390/40 nm, 452/45 nm and 542/50 nm respectively) for generating classification maps for identifying eight different atherosclerotic plaque sub-types in ex vivo human coronary vessels. The classification was performed using a support vector machine based classifier that was built from data gathered from sixteen coronary vessels in a previous study. This classifier was validated in the current study using an independent set of FLIm data acquired from four additional coronary vessels with a new rotational FLIm system. Classification maps were compared to co-registered histological data. Results show that the classification maps allow identification of the eight different plaque sub-types despite the fact that new data was gathered with a different FLIm system. Regions with diffuse intimal thickening (n=10), fibrotic tissue (n=2) and thick-cap fibroatheroma (n=1) were correctly identified on the classification map. The ability to identify different plaque types using FLIm data alone may serve as a powerful clinical and research tool for studying atherosclerosis in animal models as well as in humans.

  1. DDoS detection based on wavelet kernel support vector machine

    Institute of Scientific and Technical Information of China (English)

    YANG Ming-hui; WANG Ru-chuan

    2008-01-01

    To enhance the detection accuracy and deduce false positive rate of distributed denial of service (DDoS) attack detection, a new machine learning method was proposed. With the analysis of support vector machine (SVM) and the wavelet kernel function theory, an admissive support vector kernel, which is a wavelet kernel constructed in this article, implements the combination of the wavelet technique with SVM. Then, wavelet support vector machine (WSVM) is applied to DDoS attack detections and as a classifying means to test the validity of the wavelet kernel function. Simulation experiments show that under the same conditions, the predictive ability of WSVM is improved and the computation burden is alleviated. The detection accuracy of WSVM is higher than the traditional SVM by about 4%, while its false positive is lower than the traditional SVM. Thus, for DDoS detections, WSVM shows better detection performance and is more adaptive to the changing network environment.

  2. A Support Vector Machine-Based Dynamic Network for Visual Speech Recognition Applications

    Directory of Open Access Journals (Sweden)

    Gordan Mihaela

    2002-01-01

    Full Text Available Visual speech recognition is an emerging research field. In this paper, we examine the suitability of support vector machines for visual speech recognition. Each word is modeled as a temporal sequence of visemes corresponding to the different phones realized. One support vector machine is trained to recognize each viseme and its output is converted to a posterior probability through a sigmoidal mapping. To model the temporal character of speech, the support vector machines are integrated as nodes into a Viterbi lattice. We test the performance of the proposed approach on a small visual speech recognition task, namely the recognition of the first four digits in English. The word recognition rate obtained is at the level of the previous best reported rates.

  3. 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

  4. 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

  5. Sampling strategies based on singular vectors for assimilated models in ocean forecasting systems

    Science.gov (United States)

    Fattorini, Maria; Brandini, Carlo; Ortolani, Alberto

    2016-04-01

    Meteorological and oceanographic models do need observations, not only as a ground truth element to verify the quality of the models, but also to keep model forecast error acceptable: through data assimilation techniques which merge measured and modelled data, natural divergence of numerical solutions from reality can be reduced / controlled and a more reliable solution - called analysis - is computed. Although this concept is valid in general, its application, especially in oceanography, raises many problems due to three main reasons: the difficulties that have ocean models in reaching an acceptable state of equilibrium, the high measurements cost and the difficulties in realizing them. The performances of the data assimilation procedures depend on the particular observation networks in use, well beyond the background quality and the used assimilation method. In this study we will present some results concerning the great impact of the dataset configuration, in particular measurements position, on the evaluation of the overall forecasting reliability of an ocean model. The aim consists in identifying operational criteria to support the design of marine observation networks at regional scale. In order to identify the observation network able to minimize the forecast error, a methodology based on Singular Vectors Decomposition of the tangent linear model is proposed. Such a method can give strong indications on the local error dynamics. In addition, for the purpose of avoiding redundancy of information contained in the data, a minimal distance among data positions has been chosen on the base of a spatial correlation analysis of the hydrodynamic fields under investigation. This methodology has been applied for the choice of data positions starting from simplified models, like an ideal double-gyre model and a quasi-geostrophic one. Model configurations and data assimilation are based on available ROMS routines, where a variational assimilation algorithm (4D-var) is

  6. An efficient nonviral gene-delivery vector based on hyperbranched cationic glycogen derivatives

    Directory of Open Access Journals (Sweden)

    Liang X

    2014-01-01

    Full Text Available Xuan Liang,1,* Xianyue Ren,2,* Zhenzhen Liu,1 Yingliang Liu,1 Jue Wang,2 Jingnan Wang,2 Li-Ming Zhang,1 David YB Deng,2 Daping Quan,1 Liqun Yang1 1Institute of Polymer Science, School of Chemistry and Chemical Engineering, Key Laboratory of Designed Synthesis and Application of Polymer Material, Key Laboratory for Polymeric Composite and Functional Materials of Ministry of Education, Sun Yat-Sen University, Guangzhou, People's Republic of China; 2Research Center of Translational Medicine, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, People's Republic of China *Both these authors contributed equally to this work Background: The purpose of this study was to synthesize and evaluate hyperbranched cationic glycogen derivatives as an efficient nonviral gene-delivery vector. Methods: A series of hyperbranched cationic glycogen derivatives conjugated with 3-(dimethylamino-1-propylamine (DMAPA-Glyp and 1-(2-aminoethyl piperazine (AEPZ-Glyp residues were synthesized and characterized by Fourier-transform infrared and hydrogen-1 nuclear magnetic resonance spectroscopy. Their buffer capacity was assessed by acid–base titration in aqueous NaCl solution. Plasmid deoxyribonucleic acid (pDNA condensation ability and protection against DNase I degradation of the glycogen derivatives were assessed using agarose gel electrophoresis. The zeta potentials and particle sizes of the glycogen derivative/pDNA complexes were measured, and the images of the complexes were observed using atomic force microscopy. Blood compatibility and cytotoxicity were evaluated by hemolysis assay and MTT (3-[4,5-dimethylthiazol-2-yl]-2,5-diphenyltetrazolium bromide assay, respectively. pDNA transfection efficiency mediated by the cationic glycogen derivatives was evaluated by flow cytometry and fluorescence microscopy in the 293T (human embryonic kidney and the CNE2 (human nasopharyngeal carcinoma cell lines. In vivo delivery of pDNA in model animals (Sprague Dawley

  7. Flight test results of a vector-based failure detection and isolation algorithm for a redundant strapdown inertial measurement unit

    Science.gov (United States)

    Morrell, F. R.; Bailey, M. L.; Motyka, P. R.

    1988-01-01

    Flight test results of a vector-based fault-tolerant algorithm for a redundant strapdown inertial measurement unit are presented. Because the inertial sensors provide flight-critical information for flight control and navigation, failure detection and isolation is developed in terms of a multi-level structure. Threshold compensation techniques for gyros and accelerometers, developed to enhance the sensitivity of the failure detection process to low-level failures, are presented. Four flight tests, conducted in a commercial transport type environment, were used to determine the ability of the failure detection and isolation algorithm to detect failure signals, such a hard-over, null, or bias shifts. The algorithm provided timely detection and correct isolation of flight control- and low-level failures. The flight tests of the vector-based algorithm demonstrated its capability to provide false alarm free dual fail-operational performance for the skewed array of inertial sensors.

  8. Structure-Activity Relationships of JMV4463, a Vectorized Cathepsin D Inhibitor with Antiproliferative Properties: The Unique Role of the AMPA-Based Vector.

    Science.gov (United States)

    Vezenkov, Lubomir L; Sanchez, Clément A; Bellet, Virginie; Martin, Vincent; Maynadier, Marie; Bettache, Nadir; Lisowski, Vincent; Martinez, Jean; Garcia, Marcel; Amblard, Muriel; Hernandez, Jean-François

    2016-02-01

    Cathepsin D (CathD) is overexpressed and secreted by several solid tumors and stimulates their growth, the mechanism of which is still not understood. In this context, the pepstatin bioconjugate JMV4463 [Ac-arg-O2 Oc-(Val)3-Sta-Ala-Sta-(AMPA)4-NH2; O2 Oc=8-amino-3,6-dioxaoctanoyl, Sta=statine, AMPA=ortho-aminomethylphenylacetyl], containing a new kind of cell-penetrating vector, was previously shown to exhibit potent antiproliferative effects in vitro and to delay the onset of tumors in vivo. In this study, we performed a structure-activity relationship analysis to evaluate the significance of the inhibitor and vector moieties of JMV4463. By modifying both statine residues of pepstatin we found that the antiproliferative activity is correlated with CathD inhibition, supporting a major role of the catalytic activity of intracellular CathD in cancer cell proliferation. Replacing the vector composed of four AMPA units with other vectors was found to abolish cytotoxicity, although all of the conjugates enabled pepstatin transport into cells. In addition, the AMPA4 vector must be localized at the C terminus of the bioconjugate. The unexpected importance of the vector structure and position for cytotoxic action suggests that AMPA4 enables pepstatin to inhibit the proteolysis of critical CathD substrates involved in cell proliferation via a unique mechanism of action. PMID:26639308

  9. Modification of a viral satellite DNA-based gene silencing vector and its application to leaf or flower color change in Petunia hybrida

    Institute of Scientific and Technical Information of China (English)

    TAO Xiaorong; QIAN Yajuan; ZHOU Xueping

    2006-01-01

    Virus-induced gene silencing offers a powerful reverse-genetic tool for the study of gene function in plants. We have previously reported effective gene silencing of plant genes using a viral satellite DNA associated with Tomato yellow leaf curl China virus (TYLCCNV). In this study, we further modified the viral satellite DNA-based vector. The modified vector can induce sulfu (Su) gene silencing as effective as the original vector in Nicotiana benthamiana plants, but the new system simplifies procedures for construction of vector derivative. Furthermore, a fragment of petunia Su or chalcone synthase (CHS) endogenous gene was inserted into the modified vector. When petunia plants were agro- inoculated with the modified vector carrying a Su or CHS gene, the Su silenced plants started to appear yellowing in veins of systemically infected upper leaves two weeks after agroinoculation, while the CHS silenced plants started to show flower color change one month after agroinoculation and later single-color flowers became mosaic.

  10. Support Vector Machine Based Red Palm Weevil (Rynchophorus Ferrugineous, Olivier Recognition System

    Directory of Open Access Journals (Sweden)

    Ghulam M. Hassan

    2012-01-01

    Full Text Available Problem statement: Red palm weevil (Rynchophorus Ferrugineous, Oliveir is an insect which threatens the existence of palm trees. The proposed research is to develop a RPW identification system using Support Vector Machine method. The problem is to extract image features from an image and using SVM to find out the existence of RPW in an image. Approach: Images are snapped and image processing techniques of Regional Properties and Zernike Moments are used to extract different features of an image. The obtained features are fed into the SVM based system individually as well as in combination. The database used to train and test the system includes 326 RPW and 93 other insect images. The input data from database is selected randomly and fed into the system in three steps i.e., 25, 50 and 75% while remaining database is used for testing purpose. In SVM, polynomial kernel function and Radial Basis Function are used for training. Each experiment is repeated 10 times and the average results are used for analysis. Results: The optimal results are obtained by using Radial Basis Function in SVM at lower values of sigma σ while Polynomial kernel function is not successful in returning adequate results. Further detailed analysis of results for σ value of 10 and 15 revealed that proposed system works well with large training data and with inputs obtained by Regional Properties. The optimal value of σ for proposed system is found to be 10 when training data ratio is 50%. The training time for proposed system depends on size of database and is found to be 0.025 sec per image while time consumed by proposed system for identification of RPW in an image is found to be 15 milli sec. The proposed systems success in identification of RPW and other insect is found to be 97 and 93% respectively. Conclusion: It is concluded that SVM based system using Radial Basis Function having σ value of 10 is optimal in identifying RPW from an image. The optimal input

  11. Automated beam placement for breast radiotherapy using a support vector machine based algorithm

    International Nuclear Information System (INIS)

    Purpose: To develop an automated beam placement technique for whole breast radiotherapy using tangential beams. We seek to find optimal parameters for tangential beams to cover the whole ipsilateral breast (WB) and minimize the dose to the organs at risk (OARs). Methods: A support vector machine (SVM) based method is proposed to determine the optimal posterior plane of the tangential beams. Relative significances of including/avoiding the volumes of interests are incorporated into the cost function of the SVM. After finding the optimal 3-D plane that separates the whole breast (WB) and the included clinical target volumes (CTVs) from the OARs, the gantry angle, collimator angle, and posterior jaw size of the tangential beams are derived from the separating plane equation. Dosimetric measures of the treatment plans determined by the automated method are compared with those obtained by applying manual beam placement by the physicians. The method can be further extended to use multileaf collimator (MLC) blocking by optimizing posterior MLC positions. Results: The plans for 36 patients (23 prone- and 13 supine-treated) with left breast cancer were analyzed. Our algorithm reduced the volume of the heart that receives >500 cGy dose (V5) from 2.7 to 1.7 cm3 (p = 0.058) on average and the volume of the ipsilateral lung that receives >1000 cGy dose (V10) from 55.2 to 40.7 cm3 (p = 0.0013). The dose coverage as measured by volume receiving >95% of the prescription dose (V95%) of the WB without a 5 mm superficial layer decreases by only 0.74% (p = 0.0002) and the V95% for the tumor bed with 1.5 cm margin remains unchanged. Conclusions: This study has demonstrated the feasibility of using a SVM-based algorithm to determine optimal beam placement without a physician's intervention. The proposed method reduced the dose to OARs, especially for supine treated patients, without any relevant degradation of dose homogeneity and coverage in general.

  12. Support Vector Machines Parameter Selection Based on Combined Taguchi Method and Staelin Method for E-mail Spam Filtering

    OpenAIRE

    Wei-Chih Hsu; Tsan-Ying Yu

    2012-01-01

    Support vector machines (SVM) are a powerful tool for building good spam filtering models. However, the performance of the model depends on parameter selection. Parameter selection of SVM will affect classification performance seriously during training process. In this study, we use combined Taguchi method and Staelin method to optimize the SVM-based E-mail Spam Filtering model and promote spam filtering accuracy. We compare it with other parameters optimization methods, such as g...

  13. Alcohols' Classification by Infrared Spectra Segment Based on Support Vector Machines

    Institute of Scientific and Technical Information of China (English)

    Wei XIE; Fu Sheng NIE; Meng Long LI; Guang Ming LI; Min Chun LU

    2006-01-01

    This paper studies various classifiers to identify primary, secondary or tertiary alcohols by using segmental spectra and their combinations to support vector machines (SVMs). The results showed that the O-H in-plane bending absorption contributed most to identification their substitute. This conclusion disagrees with related known research results.

  14. Permanent Magnet Flux Online Estimation Based on Zero-Voltage Vector Injection Method

    DEFF Research Database (Denmark)

    Xie, Ge; Lu, Kaiyuan; Kumar, Dwivedi Sanjeet;

    2015-01-01

    may also be further developed to inject two opposite voltage vectors to reduce the effects of inverter voltage error on the position estimation accuracy. The effectiveness of the proposed method is demonstrated by comparing with other sensorless control method. Theoretical analysis and experimental...

  15. Implementation of a Vector-based Tracking Loop Receiver in a Pseudolite Navigation System

    OpenAIRE

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

    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.

  16. Inhibition of Marek's disease virus replication by retroviral vector-based RNA interference

    Science.gov (United States)

    RNA interference (RNAi) is a promising antiviral methodology. We recently demonstrated that retroviral vectors expressing short hairpin RNAs (shRNA-mirs) in the context of a modified endogenous micro-RNA (miRNA) can be effective in reducing replication of other retroviruses in chicken cells. In thi...

  17. Neighboring block based disparity vector derivation for multiview compatible 3D-AVC

    Science.gov (United States)

    Kang, Jewon; Chen, Ying; Zhang, Li; Zhao, Xin; Karczewicz, Marta

    2013-09-01

    3D-AVC being developed under Joint Collaborative Team on 3D Video Coding (JCT-3V) significantly outperforms the Multiview Video Coding plus Depth (MVC+D) which simultaneously encodes texture views and depth views with the multiview extension of H.264/AVC (MVC). However, when the 3D-AVC is configured to support multiview compatibility in which texture views are decoded without depth information, the coding performance becomes significantly degraded. The reason is that advanced coding tools incorporated into the 3D-AVC do not perform well due to the lack of a disparity vector converted from the depth information. In this paper, we propose a disparity vector derivation method utilizing only the information of texture views. Motion information of neighboring blocks is used to determine a disparity vector for a macroblock, so that the derived disparity vector is efficiently used for the coding tools in 3D-AVC. The proposed method significantly improves a coding gain of the 3D-AVC in the multiview compatible mode about 20% BD-rate saving in the coded views and 26% BD-rate saving in the synthesized views on average.

  18. Gene vectors based on DOEPC/DOPE mixed cationic liposomes : a physicochemical study

    NARCIS (Netherlands)

    Munoz-Ubeda, Monica; Rodriguez-Pulido, Alberto; Nogales, Aurora; Llorca, Oscar; Quesada-Perez, Manuel; Martin-Molina, Alberto; Aicart, Emilio; Junquera, Elena

    2011-01-01

    A double approach, experimental and theoretical, has been followed to characterize from a physicochemical standpoint the compaction process of DNA by means of cationic colloidal aggregates. The colloidal vectors are cationic liposomes constituted by a mixture of a novel cationic lipid, 1,2-dioleoyl-

  19. Production of intense attosecond vector beam pulse trains based on harmonics

    Science.gov (United States)

    Han, Yu-Jing; Liao, Guo-Qian; Chen, Li-Ming; Li, Yu-Tong; Wang, Wei-Min; Zhang, Jie

    2015-11-01

    We provide the first report on the harmonics generated by an intense femtosecond vector beam that is normally incident on a solid target. By using 2D particle-in-cell (PIC) codes, we observe the third and the fifth harmonic signals with the same vector structure as the driving beam, and obtain an attosecond vector beam pulse train. We also show that the conversion efficiencies of the third and the fifth harmonics reach their maxima for a plasma density of four times the critical density due to the plasma resonating with the driving force. This method provides a new means of generating intense extreme ultraviolet (XUV) vector beams via ultra-intense laser-driven harmonics. Project supported by the National Basic Research Program of China (Grant Nos. 2013CBA01501 and 2013CBA01504), the National Key Scientific Instrument and Equipment Development Project of China (Grant No. 2012YQ120047), Chinese Academy of Science Key Program, the National Natural Science of China (Grant Nos. 11135012 and 11375262), and the Project of Shandong Province Higher Educational Science and Technology Program, China (Grant No. J11LA52).

  20. Inhibition of avian leukosis virus replication by vector-based RNA interference

    Science.gov (United States)

    RNAi has recently emerged as a promising antiviral technique in vertebrates. To date, most studies have used exogenous short interfering RNAs (siRNAs) to inhibit viral replication, though vectors expressing short hairpin RNAs (shRNA-mirs) in the context of a modified endogenous micro-RNA (miRNA) are...

  1. Simulation and Prediction of Alkalinity in Sintering Process Based on Grey Least Squares Support Vector Machine

    Institute of Scientific and Technical Information of China (English)

    SONG Qiang; WANG Ai-min

    2009-01-01

    The prediction of the alkalinity is difficult during the sintering process. Whether or not the level of the alkalinity of sintering process is successful is directly related to the quality of sinter. There is no very good method for predicting the alkalinity by now owing to the high complexity, high nonlinearity, strong coupling, high time delay, and etc. Therefore, a new technique, the grey squares support machine, was introduced. The grey support vector machine model of the alkalinity enabled the development of new equation and algorithm to predict the alkalinity. During modelling, the fluctuation of data sequence was weakened by the grey theory and the support vector machine was capable of processing nonlinear adaptable information, and the grey support vector machine has a combination of those advantages. The results revealed that the alkalinity of sinter could be accurately predicted using this model by reference to small sample and information. The experimental results showed that the grey support vector machine model was effective and practical owing to the advantages of high precision, less samples required, and simple calculation.

  2. Peptide-Mediated Tumor Targeting by a Degradable Nano Gene Delivery Vector Based on Pluronic-Modified Polyethylenimine

    Science.gov (United States)

    Wu, Zhaoyong; Zhan, Shuyu; Fan, Wei; Ding, Xueying; Wu, Xin; Zhang, Wei; Fu, Yinghua; Huang, Yueyan; Huang, Xuan; Chen, Rubing; Li, Mingjuan; Xu, Ningyin; Zheng, Yongxia; Ding, Baoyue

    2016-03-01

    Polyethylenimine (PEI) is considered to be a promising non-viral gene delivery vector. To solve the toxicity versus efficacy and tumor-targeting challenges of PEI used as gene delivery vector, we constructed a novel non-viral vector DR5-TAT-modified Pluronic-PEI (Pluronic-PEI-DR5-TAT), which was based on the attachment of low-molecular-weight polyethylenimine (LMW-PEI) to the amphiphilic polymer Pluronic to prepare Pluronic-modified LMW-PEI (Pluronic-PEI). This was then conjugated to a multifunctional peptide containing a cell-penetrating peptide (TAT) and a synthetic peptide that would bind to DR5—a receptor that is overexpressed in cancer cells. The vector showed controlled degradation, favorable DNA condensation and protection performance. The Pluronic-PEI-DR5-TAT/DNA complexes at an N/P ratio of 15:1 were spherical nanoparticles of 122 ± 11.6 nm and a zeta potential of about 22 ± 2.8 mV. In vitro biological characterization results indicated that Pluronic-PEI-DR5-TAT/DNA complexes had a higher specificity for the DR5 receptor and were taken up more efficiently by tumor cells than normal cells, compared to complexes formed with PEI 25 kDa or Pluronic-PEI. Thus, the novel complexes showed much lower cytotoxicity to normal cells and higher gene transfection efficiency in tumor cells than that exhibited by PEI 25 kDa and Pluronic-PEI. In summary, our novel, degradable non-viral tumor-targeting vector is a promising candidate for use in gene therapy.

  3. Peptide-Mediated Tumor Targeting by a Degradable Nano Gene Delivery Vector Based on Pluronic-Modified Polyethylenimine.

    Science.gov (United States)

    Wu, Zhaoyong; Zhan, Shuyu; Fan, Wei; Ding, Xueying; Wu, Xin; Zhang, Wei; Fu, Yinghua; Huang, Yueyan; Huang, Xuan; Chen, Rubing; Li, Mingjuan; Xu, Ningyin; Zheng, Yongxia; Ding, Baoyue

    2016-12-01

    Polyethylenimine (PEI) is considered to be a promising non-viral gene delivery vector. To solve the toxicity versus efficacy and tumor-targeting challenges of PEI used as gene delivery vector, we constructed a novel non-viral vector DR5-TAT-modified Pluronic-PEI (Pluronic-PEI-DR5-TAT), which was based on the attachment of low-molecular-weight polyethylenimine (LMW-PEI) to the amphiphilic polymer Pluronic to prepare Pluronic-modified LMW-PEI (Pluronic-PEI). This was then conjugated to a multifunctional peptide containing a cell-penetrating peptide (TAT) and a synthetic peptide that would bind to DR5-a receptor that is overexpressed in cancer cells. The vector showed controlled degradation, favorable DNA condensation and protection performance. The Pluronic-PEI-DR5-TAT/DNA complexes at an N/P ratio of 15:1 were spherical nanoparticles of 122 ± 11.6 nm and a zeta potential of about 22 ± 2.8 mV. In vitro biological characterization results indicated that Pluronic-PEI-DR5-TAT/DNA complexes had a higher specificity for the DR5 receptor and were taken up more efficiently by tumor cells than normal cells, compared to complexes formed with PEI 25 kDa or Pluronic-PEI. Thus, the novel complexes showed much lower cytotoxicity to normal cells and higher gene transfection efficiency in tumor cells than that exhibited by PEI 25 kDa and Pluronic-PEI. In summary, our novel, degradable non-viral tumor-targeting vector is a promising candidate for use in gene therapy. PMID:26932761

  4. 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.

  5. 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

  6. Characterization of the immune responses elicited by baculovirus-based vector vaccines against influenza virus hemagglutinin

    Institute of Scientific and Technical Information of China (English)

    Zhi-peng HU; Juan YIN; Yuan-yuan ZHANG; Shu-ya JIA; Zuo-jia CHEN; Jiang ZHONG

    2012-01-01

    Aim:To compare the specific immune responses elicited by different baculovirus vectors in immunized mice.Methods:We constructed and characterized two recombinant baculoviruses carrying the expression cassette for the H5N1 influenza virus hemagglutinin (HA) gene driven by either an insect cell promoter (vAc-HA) or a dual-promoter active both in insect and mammalian cells (vAc-HA-DUAL).Virus without the HA gene (vAc-EGFP) was used as a control.These viruses were used to immunize mice subcutaneously and intraperitoneally.The production of total and specific antibodies was determined by ELISA and competitive ELISA.Cytokine production by the spleen cells of immunized mice was studied using the ELISPOT assay.Results:Both the vAc-HA and vAc-HA-DUAL vectors expressed HA proteins in insect Sf9 cells,and HA antigen was present in progeny virions.The vAc-HA-DUAL vector also mediated HA expression in virus-transduced mammalian cell lines (BHK and A547).Both vAo-HA and vAc-HA-DUAL exhibited higher transduction efficiencies than vAc-EGFP in mammalian cells,as shown by the expression of the reporter gene egfp.Additionally,both vAc-HA and vAc-HA-DUAL induced high levels of HA-specific antibody production in immunized mice; vAc-HA-DUAL was more efficient in inducing IFN-Y and IL-2 upon stimulation with specific antigen,whereas vAc-HA was more efficient in inducing IL-4 and IL-6.Conclusion:Baculovirus vectors elicited efficient,specific immune responses in immunized mice.The vector displaying the HA antigen on the virion surface (vAc-HA) elicited a Th2-biased immune response,whereas the vector displaying HA and mediating HA expression in the cell (vAc-HA-DUAL) elicited a Th1-biased immune response.

  7. New Evaluation Vector through the Stanford Mobile Inquiry-Based Learning Environment (SMILE) for Participatory Action Research

    Science.gov (United States)

    An, Ji-Young

    2016-01-01

    Objectives This article reviews an evaluation vector model driven from a participatory action research leveraging a collective inquiry system named SMILE (Stanford Mobile Inquiry-based Learning Environment). Methods SMILE has been implemented in a diverse set of collective inquiry generation and analysis scenarios including community health care-specific professional development sessions and community-based participatory action research projects. In each scenario, participants are given opportunities to construct inquiries around physical and emotional health-related phenomena in their own community. Results Participants formulated inquiries as well as potential clinical treatments and hypothetical scenarios to address health concerns or clarify misunderstandings or misdiagnoses often found in their community practices. From medical universities to rural village health promotion organizations, all participatory inquiries and potential solutions can be collected and analyzed. The inquiry and solution sets represent an evaluation vector which helps educators better understand community health issues at a much deeper level. Conclusions SMILE helps collect problems that are most important and central to their community health concerns. The evaluation vector, consisting participatory and collective inquiries and potential solutions, helps the researchers assess the participants' level of understanding on issues around health concerns and practices while helping the community adequately formulate follow-up action plans. The method used in SMILE requires much further enhancement with machine learning and advanced data visualization. PMID:27525157

  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. Mechanical Fault Diagnosis for HV Circuit Breakers Based on Ensemble Empirical Mode Decomposition Energy Entropy and Support Vector Machine

    Directory of Open Access Journals (Sweden)

    Jianfeng Zhang

    2015-01-01

    Full Text Available During the operation process of the high voltage circuit breaker, the changes of vibration signals can reflect the machinery states of the circuit breaker. The extraction of the vibration signal feature will directly influence the accuracy and practicability of fault diagnosis. This paper presents an extraction method based on ensemble empirical mode decomposition (EEMD. Firstly, the original vibration signals are decomposed into a finite number of stationary intrinsic mode functions (IMFs. Secondly, calculating the envelope of each IMF and separating the envelope by equal-time segment and then forming equal-time segment energy entropy to reflect the change of vibration signal are performed. At last, the energy entropies could serve as input vectors of support vector machine (SVM to identify the working state and fault pattern of the circuit breaker. Practical examples show that this diagnosis approach can identify effectively fault patterns of HV circuit breaker.

  10. Neutron–gamma discrimination based on the support vector machine method

    Energy Technology Data Exchange (ETDEWEB)

    Yu, Xunzhen [School of Physical Science and Technology, Sichuan University, Chengdu 610041, Sichuan (China); Key Laboratory of High Energy Density Physics and Technology (Ministry of Education ), Sichuan University, Chengdu 610064 (China); Zhu, Jingjun [School of Physical Science and Technology, Sichuan University, Chengdu 610041, Sichuan (China); Lin, ShinTed [School of Physical Science and Technology, Sichuan University, Chengdu 610041, Sichuan (China); Key Laboratory of High Energy Density Physics and Technology (Ministry of Education ), Sichuan University, Chengdu 610064 (China); Wang, Li [School of Physical Science and Technology, Sichuan University, Chengdu 610041, Sichuan (China); Department of Engineering Physics, Tsinghua University, Beijing 100084 (China); Xing, Haoyang, E-mail: xhy@scu.edu.cn [School of Physical Science and Technology, Sichuan University, Chengdu 610041, Sichuan (China); Key Laboratory of High Energy Density Physics and Technology (Ministry of Education ), Sichuan University, Chengdu 610064 (China); Zhang, Caixun; Xia, Yuxi; Liu, Shukui [School of Physical Science and Technology, Sichuan University, Chengdu 610041, Sichuan (China); Yue, Qian [Department of Engineering Physics, Tsinghua University, Beijing 100084 (China); Wei, Weiwei; Du, Qiang [School of Physical Science and Technology, Sichuan University, Chengdu 610041, Sichuan (China); Tang, Changjian [School of Physical Science and Technology, Sichuan University, Chengdu 610041, Sichuan (China); Key Laboratory of High Energy Density Physics and Technology (Ministry of Education ), Sichuan University, Chengdu 610064 (China)

    2015-03-21

    In this study, the combination of the support vector machine (SVM) method with the moment analysis method (MAM) is proposed and utilized to perform neutron/gamma (n/γ) discrimination of the pulses from an organic liquid scintillator (OLS). Neutron and gamma events, which can be firmly separated on the scatter plot drawn by the charge comparison method (CCM), are detected to form the training data set and the test data set for the SVM, and the MAM is used to create the feature vectors for individual events in the data sets. Compared to the traditional methods, such as CCM, the proposed method can not only discriminate the neutron and gamma signals, even at lower energy levels, but also provide the corresponding classification accuracy for each event, which is useful in validating the discrimination. Meanwhile, the proposed method can also offer a predication of the classification for the under-energy-limit events.

  11. Direct Vector Control of Induction Motor Based on Sinusoidal PWM Inverter with Fuzzy Logic Controller

    Directory of Open Access Journals (Sweden)

    Nirban Chakraborty

    2014-04-01

    Full Text Available This paper presents the speed control scheme of direct vector control of Induction Motor drive (IM drive. The Fuzzy logic controller is (FLC used as the controller part here for the direct vector control of Induction Motor using Sinusoidal PWM Inverter (SPWM. Fuzzy logic controller has become a very popular controlling scheme in the field of Industrial application. The entire module of this IM is divided into several parts such as IM body module, Inverter module, coordinate transformation module and Sinusoidal pulse width modulation (SPWM production module and so on. With the help of this module we can analyze a variety of different simulation waveforms, which provide an effective means for the analysis and design of the IM control system using FLC technique.

  12. AAV Vectors for FRET-Based Analysis of Protein-Protein Interactions in Photoreceptor Outer Segments

    Science.gov (United States)

    Becirovic, Elvir; Böhm, Sybille; Nguyen, Ong N. P.; Riedmayr, Lisa M.; Hammelmann, Verena; Schön, Christian; Butz, Elisabeth S.; Wahl-Schott, Christian; Biel, Martin; Michalakis, Stylianos

    2016-01-01

    Fluorescence resonance energy transfer (FRET) is a powerful method for the detection and quantification of stationary and dynamic protein-protein interactions. Technical limitations have hampered systematic in vivo FRET experiments to study protein-protein interactions in their native environment. Here, we describe a rapid and robust protocol that combines adeno-associated virus (AAV) vector-mediated in vivo delivery of genetically encoded FRET partners with ex vivo FRET measurements. The method was established on acutely isolated outer segments of murine rod and cone photoreceptors and relies on the high co-transduction efficiency of retinal photoreceptors by co-delivered AAV vectors. The procedure can be used for the systematic analysis of protein-protein interactions of wild type or mutant outer segment proteins in their native environment. Conclusively, our protocol can help to characterize the physiological and pathophysiological relevance of photoreceptor specific proteins and, in principle, should also be transferable to other cell types. PMID:27516733

  13. Neutron–gamma discrimination based on the support vector machine method

    International Nuclear Information System (INIS)

    In this study, the combination of the support vector machine (SVM) method with the moment analysis method (MAM) is proposed and utilized to perform neutron/gamma (n/γ) discrimination of the pulses from an organic liquid scintillator (OLS). Neutron and gamma events, which can be firmly separated on the scatter plot drawn by the charge comparison method (CCM), are detected to form the training data set and the test data set for the SVM, and the MAM is used to create the feature vectors for individual events in the data sets. Compared to the traditional methods, such as CCM, the proposed method can not only discriminate the neutron and gamma signals, even at lower energy levels, but also provide the corresponding classification accuracy for each event, which is useful in validating the discrimination. Meanwhile, the proposed method can also offer a predication of the classification for the under-energy-limit events

  14. Mobile Tracking Based on Support Vector Regressors Ensemble and Game Theory

    OpenAIRE

    Fanzi Zeng; Shaoyuan Liu; Renfa Li; Qingguang Zeng

    2014-01-01

    A two-step tracking strategy is proposed to mitigate the adverse effect of non-line-of-sight (NLOS) propagation to the mobile node tracking. This strategy firstly uses support vector regressors ensemble (SVRM) to establish the mapping of node position to radio parameters by supervising learning. Then by modelling the noise as the adversary of position estimator, a game between position estimator and noise is constructed. After that the position estimation from SVRM is smoothed by game theory....

  15. An Improved MRAS Based Sensorless Vector Control Method for Wind Power Generator

    OpenAIRE

    M. Delimar; MILICEVIC, D.; VASIC, V.; KATIC, V.; DUMNIC, B.

    2012-01-01

    This paper describes an improved sensorless vector control strategy for a squirrel cage induction generator used invariable speed wind energy conversion systems (WECS). The main goal is to design a robust control algorithmimmune to generator parameter variations. In order to estimate the rotational speed of the induction generator, amodel reference adaptive system (MRAS observer) is used. It is shown that a generator parameter mismatch has agreat influence on the rotor speed estimation. In or...

  16. Multichannel audio signal source separation based on an Interchannel Loudness Vector Sum

    OpenAIRE

    Park, Taejin; Lee, Taejin

    2015-01-01

    In this paper, a Blind Source Separation (BSS) algorithm for multichannel audio contents is proposed. Unlike common BSS algorithms targeting stereo audio contents or microphone array signals, our technique is targeted at multichannel audio such as 5.1 and 7.1ch audio. Since most multichannel audio object sources are panned using the Inter-channel Loudness Difference (ILD), we employ the ILVS (Inter-channel Loudness Vector Sum) concept to cluster common signals (such as background music) from ...

  17. A Novel Local Network Intrusion Detection System Based on Support Vector Machine

    OpenAIRE

    Muamer N. Mohammad; Norrozila Sulaiman; Emad T Khalaf

    2011-01-01

    Problem statement: Past few years have witnessed a growing recognition of intelligent techniques for the construction of efficient and reliable Intrusion Detection Systems (IDS). Many methods and techniques were used for modeling the IDS, but some of them contribute little or not to resolve it. Approach: Intrusion detection system for local area network by using Support Vector Machines (SVM) was proposed. First, the intrusion ways and intrusion connecting of Local Area Network were defined fo...

  18. Facial expression recognition based on local region specific features and support vector machines

    OpenAIRE

    Ghimire, Deepak; Jeong, Sunghwan; Lee, Joonwhoan; Park, Sang Hyun

    2016-01-01

    Facial expressions are one of the most powerful, natural and immediate means for human being to communicate their emotions and intensions. Recognition of facial expression has many applications including human-computer interaction, cognitive science, human emotion analysis, personality development etc. In this paper, we propose a new method for the recognition of facial expressions from single image frame that uses combination of appearance and geometric features with support vector machines ...

  19. 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. PMID:22163552

  20. Implementation of a Vector-based Tracking Loop Receiver in a Pseudolite Navigation System

    Directory of Open Access Journals (Sweden)

    Hyoungmin So

    2010-06-01

    Full Text Available 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.

  1. MEL FREQUENCY CEPSTRAL COEFFICIENTS (MFCC) BASED SPEAKER IDENTIFICATION IN NOISY ENVIRONMENT USING LBG VECTOR QUANTIZATION

    OpenAIRE

    Arun Kumar Choudhary; Jitendra Kumar Mishra

    2016-01-01

    Recognizing A speaker can simplify task of translating speech in systems that have been trained on specific person's voices or it can be used to the authenticate or verify the identity of a speaker as part of a security process. This work discusses Implementation of an Enhanced Speaker Recognition system using MFCC and the LBG Algorithm. The MFCC has been used the extensively for purposes of Speaker Recognition. This work has augmented the existing work by using Vector Quantization and Cl...

  2. Implementing Cargo Movement into Climate Based Risk Assessment of Vector-Borne Diseases

    OpenAIRE

    Stephanie Margarete Thomas; Nils Benjamin Tjaden; Sanne van den Bos; Carl Beierkuhnlein

    2014-01-01

    During the last decades the disease vector Aedes albopictus (Asian tiger mosquito) has rapidly spread around the globe. Global shipment of goods contributes to its permanent introduction. Invaded regions are facing novel and serious public health concerns, especially regarding the transmission of formerly non-endemic arboviruses such as dengue and chikungunya. The further development and potential spread to other regions depends largely on their climatic suitability. Here, we have developed a...

  3. Multi-Scale Analysis Based Ball Bearing Defect Diagnostics Using Mahalanobis Distance and Support Vector Machine

    OpenAIRE

    Chun-Chieh Wang; Tian-Yau Wu; Chiu-Wen Wu; Shuen-De Wu

    2013-01-01

    The objective of this research is to investigate the feasibility of utilizing the multi-scale analysis and support vector machine (SVM) classification scheme to diagnose the bearing faults in rotating machinery. For complicated signals, the characteristics of dynamic systems may not be apparently observed in a scale, particularly for the fault-related features of rotating machinery. In this research, the multi-scale analysis is employed to extract the possible fault-related features in differ...

  4. Bethe vectors of quantum integrable models based on Uq( gl-hat N)

    International Nuclear Information System (INIS)

    We study quantum Uq( gl-hat N) integrable models solvable by the nested algebraic Bethe ansatz. Different formulas are given for the right and left universal off-shell nested Bethe vectors. It is shown that these formulas can be related by certain morphisms of the positive Borel subalgebra in Uq( gl-hat N) into analogous subalgebra in Uq−1( gl-hat N). (paper)

  5. Cometabolic oxidation of polychlorinated biphenyls in soil with a surfactant-based field application vector.

    OpenAIRE

    Lajoie, C. A.; Layton, A C; Sayler, G. S.

    1994-01-01

    Polychlorinated biphenyl (PCB)-degradative genes, under the control of a constitutive promoter, were cloned into a broad-host-range plasmid and a transposon. These constructs were inserted into a surfactant-utilizing strain, Pseudomonas putida IPL5, to create a field application vector (FAV) in which a surfactant-degrading organism cometabolizes PCB. By utilizing a surfactant not readily available to indigenous populations and a constitutive promoter, selective growth and PCB-degradative gene...

  6. 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. PMID:17079096

  7. Implementing Cargo Movement into Climate Based Risk Assessment of Vector-Borne Diseases

    Directory of Open Access Journals (Sweden)

    Stephanie Margarete Thomas

    2014-03-01

    Full Text Available During the last decades the disease vector Aedes albopictus (Asian tiger mosquito has rapidly spread around the globe. Global shipment of goods contributes to its permanent introduction. Invaded regions are facing novel and serious public health concerns, especially regarding the transmission of formerly non-endemic arboviruses such as dengue and chikungunya. The further development and potential spread to other regions depends largely on their climatic suitability. Here, we have developed a tool for identifying and prioritizing European areas at risk for the establishment of Aedes albopictus by taking into account, for the first time, the freight imports from this mosquito’s endemic countries and the climate suitability at harbors and their surrounding regions. In a second step we consider the further transport of containers by train and inland waterways because these types of transport can be well controlled. We identify European regions at risk, where a huge amount of transported goods meet climatically suitable conditions for the disease vector. The current and future suitability of the climate for Aedes albopictus was modeled by a correlative niche model approach and the Regional Climate Model COSMO-CLM. This risk assessment combines impacts of globalization and global warming to improve effective and proactive interventions in disease vector surveillance and control actions.

  8. Mass Spectrometry Based Proteomic Analysis of Salivary Glands of Urban Malaria Vector Anopheles stephensi

    Directory of Open Access Journals (Sweden)

    Sonam Vijay

    2014-01-01

    Full Text Available Salivary gland proteins of Anopheles mosquitoes offer attractive targets to understand interactions with sporozoites, blood feeding behavior, homeostasis, and immunological evaluation of malaria vectors and parasite interactions. To date limited studies have been carried out to elucidate salivary proteins of An. stephensi salivary glands. The aim of the present study was to provide detailed analytical attributives of functional salivary gland proteins of urban malaria vector An. stephensi. A proteomic approach combining one-dimensional electrophoresis (1DE, ion trap liquid chromatography mass spectrometry (LC/MS/MS, and computational bioinformatic analysis was adopted to provide the first direct insight into identification and functional characterization of known salivary proteins and novel salivary proteins of An. stephensi. Computational studies by online servers, namely, MASCOT and OMSSA algorithms, identified a total of 36 known salivary proteins and 123 novel proteins analysed by LC/MS/MS. This first report describes a baseline proteomic catalogue of 159 salivary proteins belonging to various categories of signal transduction, regulation of blood coagulation cascade, and various immune and energy pathways of An. stephensi sialotranscriptome by mass spectrometry. Our results may serve as basis to provide a putative functional role of proteins in concept of blood feeding, biting behavior, and other aspects of vector-parasite host interactions for parasite development in anopheline mosquitoes.

  9. Mos1 transposon-based transformation of fish cell lines using baculoviral vectors

    Energy Technology Data Exchange (ETDEWEB)

    Yokoo, Masako [Laboratory of Applied Molecular Entomology, Division of Applied Bioscience, Research Faculty of Agriculture, Hokkaido University, Sapporo 060-8589 (Japan); Fujita, Ryosuke [Laboratory of Applied Molecular Entomology, Division of Applied Bioscience, Research Faculty of Agriculture, Hokkaido University, Sapporo 060-8589 (Japan); Innate Immunity Laboratory, Graduate School of Life Science and Creative Research Institution, Hokkaido University, Sapporo 001-0021 (Japan); Nakajima, Yumiko [Functional Genomics Group, COMB, Tropical Biosphere Research Center, University of the Ryukyus, Okinawa 903-0213 (Japan); Yoshimizu, Mamoru; Kasai, Hisae [Faculty of Fisheries Sciences, Hokkaido University, Hakodate 041-8611 (Japan); Asano, Shin-ichiro [Laboratory of Applied Molecular Entomology, Division of Applied Bioscience, Research Faculty of Agriculture, Hokkaido University, Sapporo 060-8589 (Japan); Bando, Hisanori, E-mail: hban@abs.agr.hokudai.ac.jp [Laboratory of Applied Molecular Entomology, Division of Applied Bioscience, Research Faculty of Agriculture, Hokkaido University, Sapporo 060-8589 (Japan)

    2013-09-13

    Highlights: •The baculovirus vector infiltrates the cells of economic important fishes. •Drosophila Mos1 transposase expressed in fish cells maintains its ability to localize to the nucleus. •The baculoviral vector carrying Mos1 is a useful tool to stably transform fish cells. -- Abstract: Drosophila Mos1 belongs to the mariner family of transposons, which are one of the most ubiquitous transposons among eukaryotes. We first determined nuclear transportation of the Drosophila Mos1-EGFP fusion protein in fish cell lines because it is required for a function of transposons. We next constructed recombinant baculoviral vectors harboring the Drosophila Mos1 transposon or marker genes located between Mos1 inverted repeats. The infectivity of the recombinant virus to fish cells was assessed by monitoring the expression of a fluorescent protein encoded in the viral genome. We detected transgene expression in CHSE-214, HINAE, and EPC cells, but not in GF or RTG-2 cells. In the co-infection assay of the Mos1-expressing virus and reporter gene-expressing virus, we successfully transformed CHSE-214 and HINAE cells. These results suggest that the combination of a baculovirus and Mos1 transposable element may be a tool for transgenesis in fish cells.

  10. Promising plasmid DNA vector based on APTES-modified silica nanoparticles

    Directory of Open Access Journals (Sweden)

    Cheang TY

    2012-02-01

    Full Text Available Tuck-yun Cheang1,*, Bing Tang1,*, An-wu Xu2, Guang-qi Chang1, Zuo-jun Hu1, Wei-ling He1, Zhou-hao Xing2, Jian-bo Xu1, Mian Wang1, Shen-ming Wang11Department of Vascular Surgery, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China; 2Division of Nanomaterials and Chemistry, Hefei National Laboratory for Physical Sciences at Microscale, University of Science and Technology of China, Hefei, China  *Both authors contributed equally to this workAbstract: Nanoparticles have an enormous potential for development in biomedical applications, such as gene or drug delivery. We developed and characterized aminopropyltriethoxysilane-functionalized silicon dioxide nanoparticles (APTES-SiNPs for gene therapy. Lipofectamine® 2000, a commonly used agent, served as a contrast. We showed that APTES-SiNPs had a gene transfection efficiency almost equal to that of Lipofectamine 2000, but with lower cytotoxicity. Thus, these novel APTES-SiNPs can achieve highly efficient transfection of plasmid DNA, and to some extent reduce cytotoxicity, which might overcome the critical drawbacks in vivo of conventional carriers, such as viral vectors, organic polymers, and liposomes, and seem to be a promising nonviral gene therapy vector.Keywords: aminopropyltriethoxysilane, silicon dioxide nanoparticles, Lipofectamine® 2000, gene therapy vector, nanomedicine

  11. Protein trans-splicing based dual-vector delivery of the coagulation factor Ⅷ gene

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    A dual-vector system was explored for the delivery of the coagulation factor VIII gene,using intein-mediated protein trans-splicing as a means to produce intact functional factor VIII post-translationally.A pair of eukaryotic expression vectors,expressing Ssp DnaB intein-fused heavy and light chain genes of B-domain deleted factor VIII (BDD-FVIII),was constructed.With transient co-transfection of the two vectors into 293 and COS-7 cells,the culture supernatants contained (137±23) and (109±22) ng mL–1 spliced BDD-FVIII antigen with an activity of (1.05±0.16) and (0.79±0.23) IU mL–1 for 293 and COS-7 cells,respectively.The spliced BDD-FVIII was also detected in supernatants from a mixture of cells transfected with inteinfused heavy and light chain genes.The spliced BDD-FVIII protein bands from cell lysates were visualized by Western blotting.The data demonstrated that intein could be used to transfer the split factor VIII gene and provided valuable information on factor VIII gene delivery by dual-adeno-associated virus in hemophilia A gene therapy.

  12. Combined prediction model for supply risk in nuclear power equipment manufacturing industry based on support vector machine and decision tree

    International Nuclear Information System (INIS)

    The prediction index for supply risk is developed based on the factor identifying of nuclear equipment manufacturing industry. The supply risk prediction model is established with the method of support vector machine and decision tree, based on the investigation on 3 important nuclear power equipment manufacturing enterprises and 60 suppliers. Final case study demonstrates that the combination model is better than the single prediction model, and demonstrates the feasibility and reliability of this model, which provides a method to evaluate the suppliers and measure the supply risk. (authors)

  13. Optimized Method for Real-Time Face Recognition System Based on PCA and Multiclass Support Vector Machine

    Directory of Open Access Journals (Sweden)

    Reza Azad

    2013-11-01

    Full Text Available Automatic face recognition system is one of the core technologies in computer vision, machine learning, and biometrics. The present study presents a novel and improved way for face recognition. In the suggested approach, first, the place of face is extracted from the original image and then is sent to feature extraction stage, which is based on Principal Component Analysis (PCA technique. In the previous procedures which were established on PCA technique, the whole picture was taken as a vector feature, then among these features, key features were extracted with use of PCA algorithm, revealing finally some poor efficiency. Thus, in the recommended approach underlying the current investigation, first the areas of face features are extracted; then, the areas are combined and are regarded as vector features. Ultimately, its key features are extracted with use of PCA algorithm. Taken together, after extracting the features, for face recognition and classification, Multiclass Support Vector Machine (SVMs classifiers, which are typical of high efficiency, have been employed. In the result part, the proposed approach is applied on FEI database and the accuracy rate achieved 98.45%.

  14. Fault Diagnosis of Plunger Pump in Truck Crane Based on Relevance Vector Machine with Particle Swarm Optimization Algorithm

    Directory of Open Access Journals (Sweden)

    Wenliao Du

    2013-01-01

    Full Text Available Promptly and accurately dealing with the equipment breakdown is very important in terms of enhancing reliability and decreasing downtime. A novel fault diagnosis method PSO-RVM based on relevance vector machines (RVM with particle swarm optimization (PSO algorithm for plunger pump in truck crane is proposed. The particle swarm optimization algorithm is utilized to determine the kernel width parameter of the kernel function in RVM, and the five two-class RVMs with binary tree architecture are trained to recognize the condition of mechanism. The proposed method is employed in the diagnosis of plunger pump in truck crane. The six states, including normal state, bearing inner race fault, bearing roller fault, plunger wear fault, thrust plate wear fault, and swash plate wear fault, are used to test the classification performance of the proposed PSO-RVM model, which compared with the classical models, such as back-propagation artificial neural network (BP-ANN, ant colony optimization artificial neural network (ANT-ANN, RVM, and support vectors, machines with particle swarm optimization (PSO-SVM, respectively. The experimental results show that the PSO-RVM is superior to the first three classical models, and has a comparative performance to the PSO-SVM, the corresponding diagnostic accuracy achieving as high as 99.17% and 99.58%, respectively. But the number of relevance vectors is far fewer than that of support vector, and the former is about 1/12–1/3 of the latter, which indicates that the proposed PSO-RVM model is more suitable for applications that require low complexity and real-time monitoring.

  15. 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.

  16. A nonintegrative lentiviral vector-based vaccine provides long-term sterile protection against malaria.

    Directory of Open Access Journals (Sweden)

    Frédéric Coutant

    Full Text Available Trials testing the RTS,S candidate malaria vaccine and radiation-attenuated sporozoites (RAS have shown that protective immunity against malaria can be induced and that an effective vaccine is not out of reach. However, longer-term protection and higher protection rates are required to eradicate malaria from the endemic regions. It implies that there is still a need to explore new vaccine strategies. Lentiviral vectors are very potent at inducing strong immunological memory. However their integrative status challenges their safety profile. Eliminating the integration step obviates the risk of insertional oncogenesis. Providing they confer sterile immunity, nonintegrative lentiviral vectors (NILV hold promise as mass pediatric vaccine by meeting high safety standards. In this study, we have assessed the protective efficacy of NILV against malaria in a robust pre-clinical model. Mice were immunized with NILV encoding Plasmodium yoelii Circumsporozoite Protein (Py CSP and challenged with sporozoites one month later. In two independent protective efficacy studies, 50% (37.5-62.5 of the animals were fully protected (p = 0.0072 and p = 0.0008 respectively when compared to naive mice. The remaining mice with detectable parasitized red blood cells exhibited a prolonged patency and reduced parasitemia. Moreover, protection was long-lasting with 42.8% sterile protection six months after the last immunization (p = 0.0042. Post-challenge CD8+ T cells to CSP, in contrast to anti-CSP antibodies, were associated with protection (r = -0.6615 and p = 0.0004 between the frequency of IFN-g secreting specific T cells in spleen and parasitemia. However, while NILV and RAS immunizations elicited comparable immunity to CSP, only RAS conferred 100% of sterile protection. Given that a better protection can be anticipated from a multi-antigen vaccine and an optimized vector design, NILV appear as a promising malaria vaccine.

  17. PMSVM: An Optimized Support Vector Machine Classification Algorithm Based on PCA and Multilevel Grid Search Methods

    Directory of Open Access Journals (Sweden)

    Yukai Yao

    2015-01-01

    Full Text Available We propose an optimized Support Vector Machine classifier, named PMSVM, in which System Normalization, PCA, and Multilevel Grid Search methods are comprehensively considered for data preprocessing and parameters optimization, respectively. The main goals of this study are to improve the classification efficiency and accuracy of SVM. Sensitivity, Specificity, Precision, and ROC curve, and so forth, are adopted to appraise the performances of PMSVM. Experimental results show that PMSVM has relatively better accuracy and remarkable higher efficiency compared with traditional SVM algorithms.

  18. Online Least Squares One-Class Support Vector Machines-Based Abnormal Visual Event Detection

    OpenAIRE

    Tian Wang; Jie Chen; Yi Zhou; Hichem Snoussi

    2013-01-01

    The abnormal event detection problem is an important subject in real-time video surveillance. In this paper, we propose a novel online one-class classification algorithm, online least squares one-class support vector machine (online LS-OC-SVM), combined with its sparsified version (sparse online LS-OC-SVM). LS-OC-SVM extracts a hyperplane as an optimal description of training objects in a regularized least squares sense. The online LS-OC-SVM learns a training set with a limited number of samp...

  19. Support Vector Regression Model Based on Empirical Mode Decomposition and Auto Regression for Electric Load Forecasting

    Directory of Open Access Journals (Sweden)

    Hong-Juan Li

    2013-04-01

    Full Text Available Electric load forecasting is an important issue for a power utility, associated with the management of daily operations such as energy transfer scheduling, unit commitment, and load dispatch. Inspired by strong non-linear learning capability of support vector regression (SVR, this paper presents a SVR model hybridized with the empirical mode decomposition (EMD method and auto regression (AR for electric load forecasting. The electric load data of the New South Wales (Australia market are employed for comparing the forecasting performances of different forecasting models. The results confirm the validity of the idea that the proposed model can simultaneously provide forecasting with good accuracy and interpretability.

  20. Converter of laser beams with circular polarization to cylindrical vector beams based on anisotropic crystals

    Science.gov (United States)

    Paranin, Vyacheslav D.; Karpeev, Sergey V.; Kazanskiy, Nikolay L.; Krasnov, Andrey P.

    2016-03-01

    The optical system for converting laser beams with circular polarization to cylindrical vector beams on the basis of anisotropic crystals has been developed. The experimental research of beam formation quality has been carried out on the both polarization and structural characteristics. The research showed differences in the formation of the azimuthal and radial polarizations for Gaussian modes and Bessel beams. The boundaries of changes of the optical system parameters to form different types of polarizations with different amplitude and phase distributions have been identified.

  1. A new vector for recombination-based cloning of large DNA fragments from yeast artificial chromosomes.

    OpenAIRE

    Bradshaw, M S; Bollekens, J A; Ruddle, F H

    1995-01-01

    The functional analysis of genes frequently requires manipulation of large genomic regions embedded in yeast artificial chromosomes (YACs). We have designed a yeast-bacteria shuttle vector, pClasper, that can be used to clone specific regions of interest from YACs by homologous recombination. The important feature of pClasper is the presence of the mini-F factor replicon. This leads to a significant increase in the size of the plasmid inserts that can be maintained in bacteria after cloning b...

  2. Multiclass Support Vector Machine-Based Lesion Mapping Predicts Functional Outcome in Ischemic Stroke Patients

    OpenAIRE

    Forkert, Nils Daniel; Verleger, Tobias; Cheng, Bastian; Thomalla, Götz; Hilgetag, Claus C.; Fiehler, Jens

    2015-01-01

    Purpose The aim of this study was to investigate if ischemic stroke final infarction volume and location can be used to predict the associated functional outcome using a multi-class support vector machine (SVM). Material and Methods Sixty-eight follow-up MR FLAIR datasets of ischemic stroke patients with known modified Rankin Scale (mRS) functional outcome after 30 days were used. The infarct regions were segmented and used to calculate the percentage of lesioned voxels in the predefined MNI,...

  3. Direct detection prospects of dark vectors with xenon-based dark matter experiments

    CERN Document Server

    An, Haipeng; Pospelov, Maxim; Pradler, Josef; Ritz, Adam

    2015-01-01

    Dark matter experiments primarily search for the scattering of WIMPs on target nuclei of well shielded underground detectors. The results from liquid scintillator experiments furthermore provide precise probes of very light and very weakly coupled particles that may be absorbed by electrons. In these proceedings we summarize previously obtained constraints on long-lived dark matter vector particles $V$ (dark photons) in the $0.01-100$ keV mass range. In addition, we provide a first projected sensitivity reach for the upcoming XENON1T dark matter search to detect dark photons.

  4. Development of avian sarcoma and leukosis virus-based vector-packaging cell lines.

    OpenAIRE

    Stoker, A W; BISSELL, M. J.

    1988-01-01

    We have constructed an avian leukosis virus derivative with a 5' deletion extending from within the tRNA primer binding site to a SacI site in the leader region. Our aim was to remove cis-acting replicative and/or encapsidation sequences and to use this derivative, RAV-1 psi-, to develop vector-packaging cell lines. We show that RAV-1 psi- can be stably expressed in the quail cell line QT6 and chicken embryo fibroblasts and that it is completely replication deficient in both cell types. Moreo...

  5. Vector analysis

    CERN Document Server

    Brand, Louis

    2006-01-01

    The use of vectors not only simplifies treatments of differential geometry, mechanics, hydrodynamics, and electrodynamics, but also makes mathematical and physical concepts more tangible and easy to grasp. This text for undergraduates was designed as a short introductory course to give students the tools of vector algebra and calculus, as well as a brief glimpse into these subjects' manifold applications. The applications are developed to the extent that the uses of the potential function, both scalar and vector, are fully illustrated. Moreover, the basic postulates of vector analysis are brou

  6. Multi-Sensor Data Fusion Using a Relevance Vector Machine Based on an Ant Colony for Gearbox Fault Detection

    Directory of Open Access Journals (Sweden)

    Zhiwen Liu

    2015-08-01

    Full Text Available Sensors play an important role in the modern manufacturing and industrial processes. Their reliability is vital to ensure reliable and accurate information for condition based maintenance. For the gearbox, the critical machine component in the rotating machinery, the vibration signals collected by sensors are usually noisy. At the same time, the fault detection results based on the vibration signals from a single sensor may be unreliable and unstable. To solve this problem, this paper proposes an intelligent multi-sensor data fusion method using the relevance vector machine (RVM based on an ant colony optimization algorithm (ACO-RVM for gearboxes’ fault detection. RVM is a sparse probability model based on support vector machine (SVM. RVM not only has higher detection accuracy, but also better real-time accuracy compared with SVM. The ACO algorithm is used to determine kernel parameters of RVM. Moreover, the ensemble empirical mode decomposition (EEMD is applied to preprocess the raw vibration signals to eliminate the influence caused by noise and other unrelated signals. The distance evaluation technique (DET is employed to select dominant features as input of the ACO-RVM, so that the redundancy and inference in a large amount of features can be removed. Two gearboxes are used to demonstrate the performance of the proposed method. The experimental results show that the ACO-RVM has higher fault detection accuracy than the RVM with normal the cross-validation (CV.

  7. Multi-Sensor Data Fusion Using a Relevance Vector Machine Based on an Ant Colony for Gearbox Fault Detection.

    Science.gov (United States)

    Liu, Zhiwen; Guo, Wei; Tang, Zhangchun; Chen, Yongqiang

    2015-01-01

    Sensors play an important role in the modern manufacturing and industrial processes. Their reliability is vital to ensure reliable and accurate information for condition based maintenance. For the gearbox, the critical machine component in the rotating machinery, the vibration signals collected by sensors are usually noisy. At the same time, the fault detection results based on the vibration signals from a single sensor may be unreliable and unstable. To solve this problem, this paper proposes an intelligent multi-sensor data fusion method using the relevance vector machine (RVM) based on an ant colony optimization algorithm (ACO-RVM) for gearboxes' fault detection. RVM is a sparse probability model based on support vector machine (SVM). RVM not only has higher detection accuracy, but also better real-time accuracy compared with SVM. The ACO algorithm is used to determine kernel parameters of RVM. Moreover, the ensemble empirical mode decomposition (EEMD) is applied to preprocess the raw vibration signals to eliminate the influence caused by noise and other unrelated signals. The distance evaluation technique (DET) is employed to select dominant features as input of the ACO-RVM, so that the redundancy and inference in a large amount of features can be removed. Two gearboxes are used to demonstrate the performance of the proposed method. The experimental results show that the ACO-RVM has higher fault detection accuracy than the RVM with normal the cross-validation (CV). PMID:26334280

  8. Dorsolateral Striatal Lesions Impair Navigation Based on Landmark-Goal Vectors but Facilitate Spatial Learning Based on a "Cognitive Map"

    Science.gov (United States)

    Kosaki, Yutaka; Poulter, Steven L.; Austen, Joe M.; McGregor, Anthony

    2015-01-01

    In three experiments, the nature of the interaction between multiple memory systems in rats solving a variation of a spatial task in the water maze was investigated. Throughout training rats were able to find a submerged platform at a fixed distance and direction from an intramaze landmark by learning a landmark-goal vector. Extramaze cues were…

  9. Support-vector-machines-based multidimensional signal classification for fetal activity characterization

    Science.gov (United States)

    Ribes, S.; Voicu, I.; Girault, J. M.; Fournier, M.; Perrotin, F.; Tranquart, F.; Kouamé, D.

    2011-03-01

    Electronic fetal monitoring may be required during the whole pregnancy to closely monitor specific fetal and maternal disorders. Currently used methods suffer from many limitations and are not sufficient to evaluate fetal asphyxia. Fetal activity parameters such as movements, heart rate and associated parameters are essential indicators of the fetus well being, and no current device gives a simultaneous and sufficient estimation of all these parameters to evaluate the fetus well-being. We built for this purpose, a multi-transducer-multi-gate Doppler system and developed dedicated signal processing techniques for fetal activity parameter extraction in order to investigate fetus's asphyxia or well-being through fetal activity parameters. To reach this goal, this paper shows preliminary feasibility of separating normal and compromised fetuses using our system. To do so, data set consisting of two groups of fetal signals (normal and compromised) has been established and provided by physicians. From estimated parameters an instantaneous Manning-like score, referred to as ultrasonic score was introduced and was used together with movements, heart rate and associated parameters in a classification process using Support Vector Machines (SVM) method. The influence of the fetal activity parameters and the performance of the SVM were evaluated using the computation of sensibility, specificity, percentage of support vectors and total classification accuracy. We showed our ability to separate the data into two sets : normal fetuses and compromised fetuses and obtained an excellent matching with the clinical classification performed by physician.

  10. TALEN-based gene disruption in the dengue vector Aedes aegypti.

    Directory of Open Access Journals (Sweden)

    Azadeh Aryan

    Full Text Available In addition to its role as the primary vector for dengue viruses, Aedes aegypti has a long history as a genetic model organism for other bloodfeeding mosquitoes, due to its ease of colonization, maintenance and reproductive productivity. Though its genome has been sequenced, functional characterization of many Ae. aegypti genes, pathways and behaviors has been slow. TALE nucleases (TALENs have been used with great success in a number of organisms to generate site-specific DNA lesions. We evaluated the ability of a TALEN pair to target the Ae. aegypti kmo gene, whose protein product is essential in the production of eye pigmentation. Following injection into pre-blastoderm embryos, 20-40% of fertile survivors produced kmo alleles that failed to complement an existing kh(w mutation. Most of these individuals produced more than 20% white-eyed progeny, with some producing up to 75%. Mutant alleles were associated with lesions of 1-7 bp specifically at the selected target site. White-eyed individuals could also be recovered following a blind intercross of G1 progeny, yielding several new white-eyed strains in the genetic background of the sequenced Liverpool strain. We conclude that TALENs are highly active in the Ae. aegypti germline, and have the potential to transform how reverse genetic experiments are performed in this important disease vector.

  11. An Artificial Intelligence Approach for Groutability Estimation Based on Autotuning Support Vector Machine

    Directory of Open Access Journals (Sweden)

    Hong-Hai Tran

    2014-01-01

    Full Text Available Permeation grouting is a commonly used approach for soil improvement in construction engineering. Thus, predicting the results of grouting activities is a crucial task that needs to be carried out in the planning phase of any grouting project. In this research, a novel artificial intelligence approach—autotuning support vector machine—is proposed to forecast the result of grouting activities that employ microfine cement grouts. In the new model, the support vector machine (SVM algorithm is utilized to classify grouting activities into two classes: success and  failure. Meanwhile, the differential evolution (DE optimization algorithm is employed to identify the optimal tuning parameters of the SVM algorithm, namely, the penalty parameter and the kernel function parameter. The integration of the SVM and DE algorithms allows the newly established method to operate automatically without human prior knowledge or tedious processes for parameter setting. An experiment using a set of in situ data samples demonstrates that the newly established method can produce an outstanding prediction performance.

  12. Support Vector Machine-Based Human Behavior Classification in Crowd through Projection and Star Skeletonization

    Directory of Open Access Journals (Sweden)

    Yogameena, B.

    2010-01-01

    Full Text Available Problem statement: Detection of individual’s abnormal human behaviors in the crowd has become a critical problem because in the event of terror strikes. This study presented a real-time video surveillance system which classifies normal and abnormal behaviors in crowds. The aim of this research was to provide a system which can aid in monitoring crowded urban environments. Approach: The proposed behaviour classification was through projection which separated individuals and using star skeletonization the features like body posture and the cyclic motion cues were obtained. Using these cues the Support Vector Machine (SVM classified the normal and abnormal behaviors of human. Results: Experimental results demonstrated the method proposed was robust and efficient in the classification of normal and abnormal human behaviors. A comparative study of classification accuracy between principal component analysis and Support Vector Machine (SVM classification was also presented. Conclusion: The proposed method classified the behavior such as running people in a crowded environment, bending down movement while most are walking or standing, a person carrying a long bar and a person waving hand in the crowd is classified.

  13. Underwater hybrid near-field acoustical holography based on the measurement of vector hydrophone array

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    Hybrid near-field acoustical holography(NAH) is developed for reconstructing acoustic radiation from a cylindrical source in a complex underwater environment. In hybrid NAH,we combine statistically optimized near-field acoustical holography(SONAH) and broadband acoustical holography from intensity measurements(BAHIM) to reconstruct the underwater cylindrical source field. First,the BAHIM is utilized to regenerate as much acoustic pressures on the hologram surface as necessary,and then the acoustic pressures are taken as input to the formulation implemented numerically by SONAH. The main advantages of this technology are that the complex pressure on the hologram surface can be reconstructed without reference signal,and the measurement array can be smaller than the source,thus the practicability and efficiency of this technology are greatly enhanced. Numerical examples of a cylindrical source are demonstrated. Test results show that hybrid NAH can yield a more accurate reconstruction than conventional NAH. Then,an experiment has been carried out with a vector hydrophone array. The experimental results show the advantage of hybrid NAH in the reconstruction of an acoustic field and the feasibility of using a vector hydrophone array in an underwater NAH measurement,as well as the identification and localization of noise sources.

  14. TALEN-based gene disruption in the dengue vector Aedes aegypti.

    Science.gov (United States)

    Aryan, Azadeh; Anderson, Michelle A E; Myles, Kevin M; Adelman, Zach N

    2013-01-01

    In addition to its role as the primary vector for dengue viruses, Aedes aegypti has a long history as a genetic model organism for other bloodfeeding mosquitoes, due to its ease of colonization, maintenance and reproductive productivity. Though its genome has been sequenced, functional characterization of many Ae. aegypti genes, pathways and behaviors has been slow. TALE nucleases (TALENs) have been used with great success in a number of organisms to generate site-specific DNA lesions. We evaluated the ability of a TALEN pair to target the Ae. aegypti kmo gene, whose protein product is essential in the production of eye pigmentation. Following injection into pre-blastoderm embryos, 20-40% of fertile survivors produced kmo alleles that failed to complement an existing kh(w) mutation. Most of these individuals produced more than 20% white-eyed progeny, with some producing up to 75%. Mutant alleles were associated with lesions of 1-7 bp specifically at the selected target site. White-eyed individuals could also be recovered following a blind intercross of G1 progeny, yielding several new white-eyed strains in the genetic background of the sequenced Liverpool strain. We conclude that TALENs are highly active in the Ae. aegypti germline, and have the potential to transform how reverse genetic experiments are performed in this important disease vector. PMID:23555893

  15. A Cognitive Skill Classification Based On Multi Objective Optimization Using Learning Vector Quantization for Serious Games

    Directory of Open Access Journals (Sweden)

    Moh. Aries Syufagi

    2011-12-01

    Full Text Available Nowadays, serious games and game technology are poised to transform the way of educating and training students at all levels. However, pedagogical value in games do not help novice students learn, too many memorizing and reduce learning process due to no information of player’s ability. To asses the cognitive level of player ability, we propose a Cognitive Skill Game (CSG. CSG improves this cognitive concept to monitor how players interact with the game. This game employs Learning Vector Quantization (LVQ for optimizing the cognitive skill input classification of the player. CSG is using teacher’s data to obtain the neuron vector of cognitive skill pattern supervise. Three clusters multi objective target will be classified as; trial and error, carefully and, expert cognitive skill. In the game play experiments using 33 respondent players demonstrates that 61% of players have high trial and error cognitive skill, 21% have high carefully cognitive skill, and 18% have high expert cognitive skill. CSG may provide information to game engine when a player needs help or when wanting a formidable challenge. The game engine will provide the appropriate tasks according to players’ ability. CSG will help balance the emotions of players, so players do not get bored and frustrated. Players have a high interest to finish the game if the player is emotionally stable. Interests in the players strongly support the procedural learning in a serious game.

  16. A graph kernel based on context vectors for extracting drug-drug interactions.

    Science.gov (United States)

    Zheng, Wei; Lin, Hongfei; Zhao, Zhehuan; Xu, Bo; Zhang, Yijia; Yang, Zhihao; Wang, Jian

    2016-06-01

    The clinical recognition of drug-drug interactions (DDIs) is a crucial issue for both patient safety and health care cost control. Thus there is an urgent need that DDIs be extracted automatically from biomedical literature by text-mining techniques. Although the top-ranking DDIs systems explore various features of texts, these features can't yet adequately express long and complicated sentences. In this paper, we present an effective graph kernel which makes full use of different types of contexts to identify DDIs from biomedical literature. In our approach, the relations among long-range words, in addition to close-range words, are obtained by the graph representation of a parsed sentence. Context vectors of a vertex, an iterative vectorial representation of all labeled nodes adjacent and nonadjacent to it, adequately capture the direct and indirect substructures' information. Furthermore, the graph kernel considering the distance between context vectors is used to detect DDIs. Experimental results on the DDIExtraction 2013 corpus show that our system achieves the best detection and classification performance (F-score) of DDIs (81.8 and 68.4, respectively). Especially for the Medline-2013 dataset, our system outperforms the top-ranking DDIs systems by F-scores of 10.7 and 12.2 in detection and classification, respectively. PMID:27012903

  17. Cloud removal of remote sensing image based on multi-output suppor t vector regression

    Institute of Scientific and Technical Information of China (English)

    Gensheng Hu; Xiaoqi Sun; Dong Liang; Yingying Sun

    2014-01-01

    Removal of cloud cover on the satel ite remote sens-ing image can effectively improve the availability of remote sensing images. For thin cloud cover, support vector value contourlet trans-form is used to achieve multi-scale decomposition of the area of thin cloud cover on remote sensing images. Through enhancing coefficients of high frequency and suppressing coefficients of low frequency, the thin cloud is removed. For thick cloud cover, if the areas of thick cloud cover on multi-source or multi-temporal remote sensing images do not overlap, the multi-output support vector regression learning method is used to remove this kind of thick clouds. If the thick cloud cover areas overlap, by using the multi-output learning of the surrounding areas to predict the sur-face features of the overlapped thick cloud cover areas, this kind of thick cloud is removed. Experimental results show that the pro-posed cloud removal method can effectively solve the problems of the cloud overlapping and radiation difference among multi-source images. The cloud removal image is clear and smooth.

  18. Development and assessment of plant-based synthetic odor baits for surveillance and control of malaria vectors.

    Directory of Open Access Journals (Sweden)

    Vincent O Nyasembe

    Full Text Available BACKGROUND: Recent malaria vector control measures have considerably reduced indoor biting mosquito populations. However, reducing the outdoor biting populations remains a challenge because of the unavailability of appropriate lures to achieve this. This study sought to test the efficacy of plant-based synthetic odor baits in trapping outdoor populations of malaria vectors. METHODOLOGY AND PRINCIPAL FINDING: Three plant-based lures ((E-linalool oxide [LO], (E-linalool oxide and (E-β-ocimene [LO + OC], and a six-component blend comprising (E-linalool oxide, (E-β-ocimene, hexanal, β-pinene, limonene, and (E-β-farnesene [Blend C], were tested alongside an animal/human-based synthetic lure (comprising heptanal, octanal, nonanal, and decanal [Blend F] and worn socks in a malaria endemic zone in the western part of Kenya. Mosquito Magnet-X (MM-X and lightless Centre for Disease Control (CDC light traps were used. Odor-baited traps were compared with traps baited with either solvent alone or solvent + carbon dioxide (controls for 18 days in a series of randomized incomplete-block designs of days × sites × treatments. The interactive effect of plant and animal/human odor was also tested by combining LO with either Blend F or worn socks. Our results show that irrespective of trap type, traps baited with synthetic plant odors compared favorably to the same traps baited with synthetic animal odors and worn socks in trapping malaria vectors, relative to the controls. Combining LO and worn socks enhanced trap captures of Anopheles species while LO + Blend F recorded reduced trap capture. Carbon dioxide enhanced total trap capture of both plant- and animal/human-derived odors. However, significantly higher proportions of male and engorged female Anopheles gambiae s.l. were caught when the odor treatments did not include carbon dioxide. CONCLUSION AND SIGNIFICANCE: The results highlight the potential of plant-based odors and specifically linalool oxide

  19. Support Vector Machines Parameter Selection Based on Combined Taguchi Method and Staelin Method for E-mail Spam Filtering

    Directory of Open Access Journals (Sweden)

    Wei-Chih Hsu

    2012-04-01

    Full Text Available Support vector machines (SVM are a powerful tool for building good spam filtering models. However, the performance of the model depends on parameter selection. Parameter selection of SVM will affect classification performance seriously during training process. In this study, we use combined Taguchi method and Staelin method to optimize the SVM-based E-mail Spam Filtering model and promote spam filtering accuracy. We compare it with other parameters optimization methods, such as grid search. Six real-world mail data sets are selected to demonstrate the effectiveness and feasibility of the method. The results show that our proposed methods can find the effective model with high classification accuracy

  20. Reduction of Delay in Detecting Initial Dips from Functional Near-Infrared Spectroscopy Signals Using Vector-Based Phase Analysis.

    Science.gov (United States)

    Hong, Keum-Shik; Naseer, Noman

    2016-05-01

    In this paper, we present a systematic method to reduce the time lag in detecting initial dips using a vector-based phase diagram and an autoregressive moving average with exogenous signals (ARMAX) model-based [Formula: see text]-step-ahead prediction algorithm. With functional near-infrared spectroscopy (fNIRS), signals related to mental arithmetic and right-hand clenching are acquired from the prefrontal and left primary motor cortices, respectively. The interrelationship between oxygenated hemoglobin, deoxygenated hemoglobin, total hemoglobin and cerebral oxygen exchange are related to initial dips. Specifically, a threshold value from the resting state hemodynamics is incorporated, as a decision criterion, into the vector-based phase diagram to determine the occurrence of initial dips. To further reduce the time lag, a [Formula: see text]-step-ahead prediction method is applied to predict the occurrence of the dips. A combination of the threshold criterion and the prediction method resulted in the delay time of about 0.9[Formula: see text]s. The results demonstrate that rapid detection of initial dip is possible and therefore can be used for real-time brain-computer interfacing. PMID:26971785

  1. Structure-activity relationship study of oxindole-based inhibitors of cyclin-dependent kinases based on least-squares support vector machines

    Energy Technology Data Exchange (ETDEWEB)

    Li Jiazhong [Department of Chemistry, Lanzhou University, Lanzhou 730000 (China); Liu Huanxiang [Department of Chemistry, Lanzhou University, Lanzhou 730000 (China); Yao Xiaojun [Department of Chemistry, Lanzhou University, Lanzhou 730000 (China)]. E-mail: xjyao@lzu.edu.cn; Liu Mancang [Department of Chemistry, Lanzhou University, Lanzhou 730000 (China); Hu Zhide [Department of Chemistry, Lanzhou University, Lanzhou 730000 (China); Fan Botao [Universite Paris 7-Denis Diderot, ITODYS 1, rue Guy de la Brosse, 75005 Paris (France)

    2007-01-09

    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.

  2. An online estimator for rotor resistance in vector drives of induction machines based on Walsh functions

    Institute of Scientific and Technical Information of China (English)

    Hamidreza SHIRAZI; Jalal NAZARZADEH

    2014-01-01

    In a modern electrical driver, rotor field oriented control (RFOC) method has been used to achieve a good performance and an appropriate transient response. In this method, the space vector of the rotor flux comes handy by the rotor resistance value. The rotor resistance is one of the important parameters which varies according to motor speed and room temperature alteration. In this paper, a new on-line estimation method is utilized to obtain the rotor resistance by using Walsh functions domain. The Walsh functions are one of the most applicable functions in piecewise constant basis functions (PCBF) to solve dynamic equations. On the other hand, an integral operational matrix is used to simplify the process and speed of the computation algorithm. The simulations results show that the proposed method is capable of solving the dynamic equations in an electrical machine on a time interval which robustly estimates the rotor resistance in contrast with injection noises.

  3. Electrocardiogram Pattern Recognition and Analysis Based on Artificial Neural Networks and Support Vector Machines: A Review

    Directory of Open Access Journals (Sweden)

    Mario Sansone

    2013-01-01

    Full Text Available Computer systems for Electrocardiogram (ECG analysis support the clinician in tedious tasks (e.g., Holter ECG monitored in Intensive Care Units or in prompt detection of dangerous events (e.g., ventricular fibrillation. Together with clinical applications (arrhythmia detection and heart rate variability analysis, ECG is currently being investigated in biometrics (human identification, an emerging area receiving increasing attention. Methodologies for clinical applications can have both differences and similarities with respect to biometrics. This paper reviews methods of ECG processing from a pattern recognition perspective. In particular, we focus on features commonly used for heartbeat classification. Considering the vast literature in the field and the limited space of this review, we dedicated a detailed discussion only to a few classifiers (Artificial Neural Networks and Support Vector Machines because of their popularity; however, other techniques such as Hidden Markov Models and Kalman Filtering will be also mentioned.

  4. Predicting and Classifying User Identification Code System Based on Support Vector Machines

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    In digital fingerprinting, preventing piracy of images by colluders is an important and tedious issue. Each image will be embedded with a unique User IDentification (U ID) code that is the fingerprint for tracking the authorized user. The proposed hiding scheme makes use of a random number generator to scramble two copies of a UID,which will then be hidden in the randomly selected medium frequency coefficients of the host image. The linear support vector machine (SVM) will be used to train classifications by calculating the normalized correlation (NC) for the 2-class UID codes. The trained classifications will be the models used for identifying unreadable UID codes.Experimental results showed that the success of predicting the unreadable UID codes can be increased by applying SVM. The proposed scheme can be used to provide protections to intellectual property rights of digital images and to keep track of users to prevent collaborative piracies.

  5. An Improved MRAS Based Sensorless Vector Control Method for Wind Power Generator

    Directory of Open Access Journals (Sweden)

    M. Delimar

    2012-10-01

    Full Text Available This paper describes an improved sensorless vector control strategy for a squirrel cage induction generator used invariable speed wind energy conversion systems (WECS. The main goal is to design a robust control algorithmimmune to generator parameter variations. In order to estimate the rotational speed of the induction generator, amodel reference adaptive system (MRAS observer is used. It is shown that a generator parameter mismatch has agreat influence on the rotor speed estimation. In order to estimate the speed accurately, the generator statorresistance must be identified at the same time to correct the mismatched resistance value used in the observer. Theproposed rotor speed estimator with parallel stator resistance identification is first verified by computer simulation.Finally, the experiment is conducted in order to verify the obtained simulation results. It is proved that this controlscheme can enhance the efficiency of a variable speed WECS.

  6. Space Vector Modulation Based Direct Matrix Converter for Stand-Alone system

    Directory of Open Access Journals (Sweden)

    Chandra Sekhar Ajin Sekhar

    2014-02-01

    Full Text Available In this paper Permanent Magnet Synchronous Generator (PMSG is used for wind power generation in standalone system due to their feature of high efficiency and low maintenance cost, which was fed with smart direct matrix converter for direct AC-AC conversion, It provides sinusoidal output waveforms with minimal higher order harmonics and no sub harmonics and also it eliminate the usage of dc-link and other passive elements. Space vector modulation (SVM controlled technique is used for matrix converter switching which can eliminate the switching loses by selected switching states.Proposed work are often seen as a future concept for variable speed drives technology.The  proposed model for RL load was analysed and verified by varying the resistor and inductance value and analysed using MATLAB simulation.

  7. Process Optimization of Ultrasonic Extraction of Puerarin Based on Support Vector Machine

    Institute of Scientific and Technical Information of China (English)

    Juan Chen; Xiaoyi Huang; Yanlei Qi; Xin Qi; Qing Guo

    2014-01-01

    In ultrasonic extraction technology, optimization of technical parameters often considers extraction medium only, without including ultrasonic parameters. This paper focuses on controlling the ultrasonic extraction process of puerarin, investigating the influence of ultrasonic parameters on extraction rate, and empirical y analyzing the main components of Pueraria, i.e., isoflavone compounds. A method is presented combining orthogonal experi-mental design with a support vector machine and a predictive model is established for optimization of technical parameters. From the analysis with the predictive model, appropriate process parameters are achieved for higher extraction rate. With these parameters in the ultrasonic extraction of puerarin, the experimental result is satisfactory. This method is of significance to the study of extracting root-stock plant medicines.

  8. Support vector machine-based feature extractor for L/H transitions in JETa)

    Science.gov (United States)

    González, S.; Vega, J.; Murari, A.; Pereira, A.; Ramírez, J. M.; Dormido-Canto, S.; Jet-Efda Contributors

    2010-10-01

    Support vector machines (SVM) are machine learning tools originally developed in the field of artificial intelligence to perform both classification and regression. In this paper, we show how SVM can be used to determine the most relevant quantities to characterize the confinement transition from low to high confinement regimes in tokamak plasmas. A set of 27 signals is used as starting point. The signals are discarded one by one until an optimal number of relevant waveforms is reached, which is the best tradeoff between keeping a limited number of quantities and not loosing essential information. The method has been applied to a database of 749 JET discharges and an additional database of 150 JET discharges has been used to test the results obtained.

  9. Support vector machine-based feature extractor for L/H transitions in JET

    International Nuclear Information System (INIS)

    Support vector machines (SVM) are machine learning tools originally developed in the field of artificial intelligence to perform both classification and regression. In this paper, we show how SVM can be used to determine the most relevant quantities to characterize the confinement transition from low to high confinement regimes in tokamak plasmas. A set of 27 signals is used as starting point. The signals are discarded one by one until an optimal number of relevant waveforms is reached, which is the best tradeoff between keeping a limited number of quantities and not loosing essential information. The method has been applied to a database of 749 JET discharges and an additional database of 150 JET discharges has been used to test the results obtained.

  10. A Vector-based Method for the Extraction of Catchment from Grid DEMs

    Institute of Scientific and Technical Information of China (English)

    ZHU Qing; TIAN Yixiang

    2005-01-01

    The methodology of catchment extraction especially from regular grid digital elevation models (DEMs) is briefly reviewed.Then an efficient algorithm, which combines vector process and traditional neighbourhood raster process, is designed for extracting the catchments and subcatchments from depressionless DEMs.The catchment area of each river in the grid DEM data is identified and delineated, then is divided into subcatchments as required.Compared to traditional processes, this method for identifying catchments focuses on the boundaries instead of the area inside the catchments and avoids the boundary intersection phenomena.Last, the algorithm is tested with a set of DEMs of different sizes, and the result proves that the computation efficiency and accuracy are better than existent methods.

  11. Vector-based model of elastic bonds for DEM simulation of solids

    CERN Document Server

    Kuzkin, Vitaly A

    2012-01-01

    A new model for computer simulation of solids, composed of bonded particles, is proposed. Vectors rigidly connected with particles are used for description of deformation of a single bond. The expression for potential energy of the bond and corresponding expressions for forces and moments are proposed. Formulas, connecting parameters of the model with longitudinal, shear, bending and torsional stiffnesses of the bond, are derived. It is shown that the model allows to describe any values of the bond stiffnesses exactly. Two different calibration procedures depending on bond length/thickness ratio are proposed. It is shown that parameters of model can be chosen so that under small deformations the bond is equivalent to either Bernoulli-Euler or Timoshenko rod or short cylinder connecting particles. Simple expressions, connecting parameters of V-model with geometrical and mechanical characteristics of the bond, are derived. Computer simulation of dynamical buckling of the straight discrete rod and discrete half-...

  12. Support-vector-machine tree-based domain knowledge learning toward automated sports video classification

    Science.gov (United States)

    Xiao, Guoqiang; Jiang, Yang; Song, Gang; Jiang, Jianmin

    2010-12-01

    We propose a support-vector-machine (SVM) tree to hierarchically learn from domain knowledge represented by low-level features toward automatic classification of sports videos. The proposed SVM tree adopts a binary tree structure to exploit the nature of SVM's binary classification, where each internal node is a single SVM learning unit, and each external node represents the classified output type. Such a SVM tree presents a number of advantages, which include: 1. low computing cost; 2. integrated learning and classification while preserving individual SVM's learning strength; and 3. flexibility in both structure and learning modules, where different numbers of nodes and features can be added to address specific learning requirements, and various learning models can be added as individual nodes, such as neural networks, AdaBoost, hidden Markov models, dynamic Bayesian networks, etc. Experiments support that the proposed SVM tree achieves good performances in sports video classifications.

  13. Multiple mental tasks classification based on nonlinear parameter of mean period using support vector machines

    Institute of Scientific and Technical Information of China (English)

    Liu Hailong; Wang Jue; Zheng Chongxun

    2007-01-01

    Mental task classification is one of the most important problems in Brain-computer interface. This paper studies the classification of five-class mental tasks. The nonlinear parameter of mean period obtained from frequency domain information was used as features for classification implemented by using the method of SVM (support vector machines). The averaged classification accuracy of 85.6% over 7 subjects was achieved for 2-second EEG segments. And the results for EEG segments of 0.5s and 5.0s compared favorably to those of Garrett's. The results indicate that the parameter of mean period represents mental tasks well for classification. Furthermore, the method of mean period is less computationally demanding, which indicates its potential use for online BCI systems.

  14. Retrieval algorithm of sea surface wind vectors for WindSat based on a simple forward model

    Institute of Scientific and Technical Information of China (English)

    ZHAO Yili

    2013-01-01

    WindSat/Coriolis is the first satellite-borne polarimetric microwave radiometer,which aims to improve the potential of polarimetric microwave radiometry for measuring sea surface wind vectors from space.In this paper,a wind vector retrieval algorithm based on a novel and simple forward model was developed for WindSat.The retrieval algorithm of sea surface wind speed was developed using multiple linear regression based on the simulation dataset of the novel forward model.Sea surface wind directions that minimize the difference between simulated and measured values of the third and fourth Stokes parameters were found using maximum likelihood estimation,by which a group of ambiguous wind directions was obtained.A median filter was then used to remove ambiguity of wind direction.Evaluated with sea surface wind speed and direction data from the U.S.National Data Buoy Center (NDBC),root mean square errors are 1.2 m/s and 30° for retrieved wind speed and wind direction,respectively.The evaluation results suggest that the simple forward model and the retrieval algorithm are practicable for near-real time applications,without reducing accuracy.

  15. A role for the histone deacetylase HDAC4 in the life-cycle of HIV-1-based vectors

    Directory of Open Access Journals (Sweden)

    Kao Gary D

    2010-09-01

    Full Text Available Abstract HIV-1 integration is mediated by the HIV-1 integrase protein, which joins 3'-ends of viral DNA to host cell DNA. To complete the integration process, HIV-1 DNA has to be joined to host cell DNA also at the 5'-ends. This process is called post-integration repair (PIR. Integration and PIR involve a number of cellular co-factors. These proteins exhibit different degrees of involvement in integration and/or PIR. Some are required for efficient integration or PIR. On the other hand, some reduce the efficiency of integration. Finally, some are involved in integration site selection. We have studied the role of the histone deacetylase HDAC4 in these processes. HDAC4 was demonstrated to play a role in both cellular double-strand DNA break repair and transcriptional regulation. We observed that HDAC4 associates with viral DNA in an integrase-dependent manner. Moreover, infection with HIV-1-based vectors induces foci of the HDAC4 protein. The related histone deacetylases, HDAC2 and HDAC6, failed to associate with viral DNA after infection. These data suggest that HDAC4 accumulates at integration sites. Finally, overexpression studies with HDAC4 mutants suggest that HDAC4 may be required for efficient transduction by HIV-1-based vectors in cells that are deficient in other DNA repair proteins. We conclude that HDAC4 is likely involved in PIR.

  16. A support vector regression-firefly algorithm-based model for limiting velocity prediction in sewer pipes.

    Science.gov (United States)

    Ebtehaj, Isa; Bonakdari, Hossein

    2016-01-01

    Sediment transport without deposition is an essential consideration in the optimum design of sewer pipes. In this study, a novel method based on a combination of support vector regression (SVR) and the firefly algorithm (FFA) is proposed to predict the minimum velocity required to avoid sediment settling in pipe channels, which is expressed as the densimetric Froude number (Fr). The efficiency of support vector machine (SVM) models depends on the suitable selection of SVM parameters. In this particular study, FFA is used by determining these SVM parameters. The actual effective parameters on Fr calculation are generally identified by employing dimensional analysis. The different dimensionless variables along with the models are introduced. The best performance is attributed to the model that employs the sediment volumetric concentration (C(V)), ratio of relative median diameter of particles to hydraulic radius (d/R), dimensionless particle number (D(gr)) and overall sediment friction factor (λ(s)) parameters to estimate Fr. The performance of the SVR-FFA model is compared with genetic programming, artificial neural network and existing regression-based equations. The results indicate the superior performance of SVR-FFA (mean absolute percentage error = 2.123%; root mean square error =0.116) compared with other methods. PMID:27148727

  17. Application of vector projection method based on decision-tree-based support vector machines in fault diagnosis for transformer%DTBSVM的向量投影法在变压器故障诊断中的应用

    Institute of Scientific and Technical Information of China (English)

    张翠玲; 王大志; 江雪晨; 宁一

    2013-01-01

    By applying vector projection method in fault diagnosis for transformer ,the problem that how to structure effective SVM hierarchy based on decision-tree-based support vector machines (DTBSVM ) is solved . According to the cross situation between classification and classification sample sets ,Euclidean distance and radial basis function are utilized to calculate spatial distance and divisibility measure between different classifi-cations ,and the sequence on the basis of divisibility measure is made to design more reasonable hierarchy structure for classification .The fault diagnosis model combining one-to-rest with rest-to-rest classification is established by using the method of vector projection on decision-tree-based support vector machines ,and it can solve the multi-classification problem better .The method of vector projection aiming at N classification problem just constructs (N-1) SVM classifiers and has no unrecognized sector ,so the classification process is faster and the generalization ability is better .The test results show that correct-sentence rate increases compa-ring with traditional three-ratio method and neural network method in fault diagnosis ,so the method has bet-ter utility value .%文章将向量投影法应用在变压器故障诊断中,解决了如何构建有效SVM 层次的问题。按照类与类样本集之间的相交情况,利用欧氏距离和径向基函数计算类与类的空间距离和类间可分性测度,根据可分性测度进行排序,设计比较合理的层次结构进行分类。这种方法建立的故障诊断模型,是一种一对多、多对多分类相结合的故障诊断模型,用于解决多分类问题效果较好;这种方法对于 N类分类问题,只需构造(N-1)个SVM分类器,并且不存在不可识别的区域,分类过程比较快速,具有较好的泛化能力。实验证明与传统的三比值法和神经网络方法相比,所提出的方法在故障诊断的正判率

  18. Short-term wind speed prediction using an unscented Kalman filter based state-space support vector regression approach

    International Nuclear Information System (INIS)

    Highlights: • A novel hybrid modeling method is proposed for short-term wind speed forecasting. • Support vector regression model is constructed to formulate nonlinear state-space framework. • Unscented Kalman filter is adopted to recursively update states under random uncertainty. • The new SVR–UKF approach is compared to several conventional methods for short-term wind speed prediction. • The proposed method demonstrates higher prediction accuracy and reliability. - Abstract: Accurate wind speed forecasting is becoming increasingly important to improve and optimize renewable wind power generation. Particularly, reliable short-term wind speed prediction can enable model predictive control of wind turbines and real-time optimization of wind farm operation. However, this task remains challenging due to the strong stochastic nature and dynamic uncertainty of wind speed. In this study, unscented Kalman filter (UKF) is integrated with support vector regression (SVR) based state-space model in order to precisely update the short-term estimation of wind speed sequence. In the proposed SVR–UKF approach, support vector regression is first employed to formulate a nonlinear state-space model and then unscented Kalman filter is adopted to perform dynamic state estimation recursively on wind sequence with stochastic uncertainty. The novel SVR–UKF method is compared with artificial neural networks (ANNs), SVR, autoregressive (AR) and autoregressive integrated with Kalman filter (AR-Kalman) approaches for predicting short-term wind speed sequences collected from three sites in Massachusetts, USA. The forecasting results indicate that the proposed method has much better performance in both one-step-ahead and multi-step-ahead wind speed predictions than the other approaches across all the locations

  19. Identifying Multi-Dimensional Co-Clusters in Tensors Based on Hyperplane Detection in Singular Vector Spaces.

    Science.gov (United States)

    Zhao, Hongya; Wang, Debby D; Chen, Long; Liu, Xinyu; Yan, Hong

    2016-01-01

    Co-clustering, often called biclustering for two-dimensional data, has found many applications, such as gene expression data analysis and text mining. Nowadays, a variety of multi-dimensional arrays (tensors) frequently occur in data analysis tasks, and co-clustering techniques play a key role in dealing with such datasets. Co-clusters represent coherent patterns and exhibit important properties along all the modes. Development of robust co-clustering techniques is important for the detection and analysis of these patterns. In this paper, a co-clustering method based on hyperplane detection in singular vector spaces (HDSVS) is proposed. Specifically in this method, higher-order singular value decomposition (HOSVD) transforms a tensor into a core part and a singular vector matrix along each mode, whose row vectors can be clustered by a linear grouping algorithm (LGA). Meanwhile, hyperplanar patterns are extracted and successfully supported the identification of multi-dimensional co-clusters. To validate HDSVS, a number of synthetic and biological tensors were adopted. The synthetic tensors attested a favorable performance of this algorithm on noisy or overlapped data. Experiments with gene expression data and lineage data of embryonic cells further verified the reliability of HDSVS to practical problems. Moreover, the detected co-clusters are well consistent with important genetic pathways and gene ontology annotations. Finally, a series of comparisons between HDSVS and state-of-the-art methods on synthetic tensors and a yeast gene expression tensor were implemented, verifying the robust and stable performance of our method. PMID:27598575

  20. Cloning vector

    Science.gov (United States)

    Guilfoyle, Richard A.; Smith, Lloyd M.

    1994-01-01

    A vector comprising a filamentous phage sequence containing a first copy of filamentous phage gene X and other sequences necessary for the phage to propagate is disclosed. The vector also contains a second copy of filamentous phage gene X downstream from a promoter capable of promoting transcription in a bacterial host. In a preferred form of the present invention, the filamentous phage is M13 and the vector additionally includes a restriction endonuclease site located in such a manner as to substantially inactivate the second gene X when a DNA sequence is inserted into the restriction site.