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...
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...
IPMSM Motion-Sensorless Direct Torque and Flux Control
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....
Novel Motion Sensorless Control of Single Phase Brushless D.C. PM Motor Drive, with experiments
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...
Voltage Sags Ride-Through of Motion Sensorless Controlled PMSG for Wind Turbines
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...
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...
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...
"Active flux" orientation vector sensorless control of IPMSM
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...
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...
Motion Sensorless Control of BLDC PM Motor with Offline FEM Info Assisted State Observer
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....
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....
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....
Hybrid I-f starting and observer-based Ssnsorless control of single-phase BLDC-PM motor drives
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)....
Equiangular Vectors Approach to Mutually Unbiased Bases
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.
Nonlinear Growth of Singular Vector Based Perturbations
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.
Cost-Based Vectorization of Instance-Based Integration Processes
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.
Vector Control Based on SVPWM for ACIM
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.
Robust Video Stabilization Based on Motion Vectors
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.
DBSC-Based Grayscale Line Image Vectorization
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.
Support vector machines optimization based theory, algorithms, and extensions
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
Bethe vectors in GL(3)-based quantum integrable models
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.
Recent progress in polymer-based gene delivery vectors
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.
One-Dimensional Vector Based Pattern Matching
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
Great Ellipse Route Planning Based on Space Vector
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.
A Fingerprint Minutiae Matching Method Based on Line Segment Vector
无
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.
Image Segmentation Based on Support Vector Machine
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.
Image indexing based on vector quantization
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.
LandSat-Based Land Use-Land Cover (Vector)
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...
Improved NYVAC-based vaccine vectors.
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.
A stable RNA virus-based vector for citrus trees
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
Risk based surveillance for vector borne diseases
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...
Fuzzy rule-based support vector regression system
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.
Implicit Boundary Control of Vector Field Based Shape Deformations
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 ...
Support Vector Machine-Based Nonlinear System Modeling and Control
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.
The integration profile of EIAV-based vectors.
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
Product Quality Modelling Based on Incremental Support Vector Machine
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.
Dynamic Vector Space Secret Sharing Based on Certificates
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.
Prediction of Banking Systemic Risk Based on Support Vector Machine
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.
Copula-based integration of vector-valued functions
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
Estimation of sand liquefaction based on support vector machines
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.
Retrovirus-based vectors for transient and permanent cell modification.
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
Efficient Vector-Based Forwarding for Underwater Sensor Networks
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.
Digital video steganalysis using motion vector recovery-based features.
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
SAMEX vector magnetograph: a design study for a space-based solar vector magnetograph
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
Vaxvec: The first web-based recombinant vaccine vector database and its data analysis.
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
Versatile Supramolecular Gene Vector Based on Host-Guest Interaction.
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
Support vector machine-based multi-model predictive control
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.
Biosensor method and system based on feature vector extraction
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.
Endpoint Prediction of EAF Based on Multiple Support Vector Machines
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.
IRIS RECOGNITION BASED ON KERNELS OF SUPPORT VECTOR MACHINE
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 ...
Classifier based on support vector machine for JET plasma configurations
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%.
Classifier based on support vector machine for JET plasma configurationsa)
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%.
Available Bandwidth Estimation Strategy Based on the Network Allocation Vector
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...
A new generation of pPRIG-based retroviral vectors
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
Efficient Satellite Scheduling Based on Improved Vector Evaluated Genetic Algorithm
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.
SAM: Support Vector Machine Based Active Queue Management
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)
Available Bandwidth Estimation Strategy Based on the Network Allocation Vector
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.
Neural cell image segmentation method based on support vector machine
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.
Riesz multiwavelet bases generated by vector refinement equation
无
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.
A Core Set Based Large Vector-Angular Region and Margin Approach for Novelty Detection
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...
2D Vector Field Simplification Based on Robustness
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.
Slope Deformation Prediction Based on Support Vector Machine
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.
Debris Flow Hazard Assessment Based on Support Vector Machine
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.
Stokes vector formalism based second harmonic generation microscopy
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.
Support vector classification algorithm based on variable parameter linear programming
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.
IRIS RECOGNITION BASED ON KERNELS OF SUPPORT VECTOR MACHINE
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.
Terminal Design in Vector Network based on Windows Platform
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.
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....
Threat Assessment of Targets Based on Support Vector Machine
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.
Development and Applications of VSV Vectors Based on Cell Tropism
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...
Disturbance observer based current controller for vector controlled IM drives
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...
Matrix-Vector Based Fast Fourier Transformations on SDR Architectures
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.
Parallel Kalman filter track fit based on vector classes
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.
Facial biometrics based on 2D vector geometry
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.
Normal Vector Based Subdivision Scheme to Generate Fractal Curves
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.
A three-axis SQUID-based absolute vector magnetometer
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.
A three-axis SQUID-based absolute vector magnetometer
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.
Three—Dimensional Vector Field Visualization Based on Tensor Decomposition
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.
Support vector machine based battery model for electric vehicles
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%
BEHAVIOR BASED CREDIT CARD FRAUD DETECTION USING SUPPORT VECTOR MACHINES
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.
Image replica detection based on support vector classifier
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.
A three-axis SQUID-based absolute vector magnetometer
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
TYRE DYNAMICS MODELLING OF VEHICLE BASED ON SUPPORT VECTOR MACHINES
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.
SENSITIVITY ANALYSIS FOR ROLLING PROCESS BASED ON SUPPORT VECTOR MACHINE
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.
High stability vector-based direct power control for DFIG-based wind turbine
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...
Molecular bases of proliferation of Francisella tularensis in Arthropod vectors
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...
Vector ordinal optimization based multi-objective transmission planning
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.
DBCSVM: Density Based Clustering Using Support VectorMachines
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.
Hybrid Support Vector Machines-Based Multi-fault Classification
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.
Progress in Chimeric Vector and Chimeric Gene Based Cardiovascular Gene Therapy
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.
A Wavelet Kernel-Based Primal Twin Support Vector Machine for Economic Development Prediction
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.
Noninvasive extraction of fetal electrocardiogram based on Support Vector Machine
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.
Priori Information Based Support Vector Regression and Its Applications
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.
Space Vector Based Hybrid PWM Techniques for Reduced Current Ripple
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...
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...
Permissive growth of human adenovirus type 4 vaccine strain-based vector in porcine cell lines.
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
Conservative rigid body dynamics by convected base vectors with implicit constraints
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...
Agent-based modeling of malaria vectors: the importance of spatial simulation
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...
A Vector-based Cellular Automata Model for Simulating Urban Land Use Change
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.
Development and applications of VSV vectors based on cell tropism
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.
Rigid Body Time Integration by Convected Base Vectors with Implicit Constraints
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...
A Novel Coding Method Based on Fuzzy Vector Quantization for Noised Image
无
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.
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.
New Iterative Learning Control Algorithms Based on Vector Plots Analysis1）
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.
Classification of Regional Ionospheric Disturbances Based on Support Vector Machines
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
Research on Matrix Converter Based on Space Vector Modulation
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
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)...
Wireless Localization Based on RSSI Fingerprint Feature Vector
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...
Window-Based Example Selection in Learning Vector Quantization
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...
Research on Matrix Converter Based on Space Vector Modulation
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...
Rigid Body Time Integration by Convected Base Vectors with Implicit Constraints
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...
Chord Recognition Based on Temporal Correlation Support Vector Machine
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.
A new method for comparing scanpaths based on vectors and dimensions
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.
An evidence-based vector control strategy for military deployments: the British Army experience.
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
Formulation of 2D Graphene Deformation Based on Chiral-Tube Base Vectors
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
Formulation of 2D Graphene Deformation Based on Chiral-Tube Base Vectors
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.
Soft Sensing Based on Hilbert-Huang Transform and Wavelet Support Vector Machine
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.
Real-time traffic information extraction based on compressed video with interframe motion vector
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.
Bethe vectors for models based on the super-Yangian $Y(\\mathfrak{gl}(m|n))$
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.
Video Surveillance Application Based on Application Specific Vector Processors
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
Emotional Vector Distance Based Sentiment Analysis of Wakamono Kotoba
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.
Digital Simulation of Space Vector Modulation Based Induction Motor Drive
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.
Automatic SIMD vectorization of SSA-based control flow graphs
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
Sagnac Interferometer Based Generation of Controllable Cylindrical Vector Beams
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.
Inertial Vector Based Attitude Stabilization of Rigid Body Without Angular Velocity Measurements
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...
Web-based GIS: the vector-borne disease airline importation risk (VBD-AIR tool
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
Mass detection algorithm based on support vector machine and relevance feedback
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%.
Aero-Engine Condition Monitoring Based on Support Vector Machine
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.
An Even Grid Based Lattice Vector Quantization Algorithm for Mobile Audio Coding
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.
A sight on the current nanoparticle-based gene delivery vectors
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.
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.
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...
BET-independent MLV-based Vectors Target Away From Promoters and Regulatory Elements
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
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.
Direct power control of DFIG based on discrete space vector modulation
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)
A versatile bacterial expression vector based on the synthetic biology plasmid pSB1.
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
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.
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
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.
Direct Time-Domain-Based Approach for Study of Space-Vector Pulsewidth Modulation
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...
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...
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...
Small-time scale network traffic prediction based on a local support vector machine regression model
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.
The generation of arbitrary vector beams using a division of a wavefront-based setup
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.
Development of avian sarcoma and leukosis virus-based vector-packaging cell lines
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.
Optical mass-storage based on vector wave holography
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.
Model based wind vector field reconstruction from lidar data
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 ...
Numerical Characterisation of Jet-Vane based Thrust Vector Control Systems
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
A Novel CSR-Based Sparse Matrix-Vector Multiplication on GPUs
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 ...
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.
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.
Acoustic Event Detection Based on MRMR Selected Feature Vectors
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...
Image Replica Detection based on Binary Support Vector Classifier
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...
Support Vector Machine Based on Adaptive Acceleration Particle Swarm Optimization
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...
Support vector machine based on adaptive acceleration particle swarm optimization.
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
Support Vector Machine Based on Adaptive Acceleration Particle Swarm Optimization
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.
Scale-Invariance of Support Vector Machines based on the Triangular Kernel
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
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.
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…
Energy-saving technology of vector controlled induction motor based on the adaptive neuro-controller
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.
A NEW METHOD OF CHANNEL FRICTION INVERSION BASED ON KALMAN FILTER WITH UNKNOWN PARAMETER VECTOR
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.
Space Vector Based Generalized Dpwm Algorithms for Vsi Fed Induction Motor Drive
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.
Design and simulation of MEMS vector hydrophone with reduced cross section based meander beams
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.
Production of Retrovirus-Based Vectors in Mildly Acidic pH Conditions.
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
VGSC: A Web-Based Vector Graph Toolkit of Genome Synteny and Collinearity.
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
A support vector density-based importance sampling for reliability assessment
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.
Research on Amplifier Performance Evaluation Based on δ-Support Vector Regression
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.
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...
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.
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.
A comparative study on change vector analysis based change detection techniques
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
A Novel CSR-Based Sparse Matrix-Vector Multiplication on GPUs
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.
Signal Detection for QPSK Based Cognitive Radio Systems using Support Vector Machines
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...
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.
Can community-based integrated vector control hasten the process of LF elimination?
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
A method for attitude measurement of a test vehicle based on the tracking of vectors
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)
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
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)
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.
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)
Vector quantization based on a psychovisual lattice for a visual subband coding scheme
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.
A Parallel Decision Model Based on Support Vector Machines and Its Application to Fault Diagnosis
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.
Minimum Distortion Direction Prediction-based Fast Half-pixel Motion Vector Search Algorithm
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%.
Efficient production of transgenic chickens using self-inactive HIV-based lentiviral vectors
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].
Study on College Physical Education Management Information System Based on Support Vector Regression
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.
Support vector machine based nonlinear model multi-step-ahead optimizing predictive control
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.
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
Climate-based models for West Nile Culex mosquito vectors in the Northeastern US
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.
无
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.
A DSP-based discrete space vector modulation direct torque control of sensorless induction machines
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)
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.
Study on College Physical Education Management Information System Based on Support Vector Regression
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 ...
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 ...
An adaptation of the vector-space model for ontology based information retrieval
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...
Fast Training of Support Vector Machines Using Error-Center-Based Optimization
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.
Space vector-based modeling and control of a modular multilevel converter in HVDC applications
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....
A Support Vector Machine-based Evaluation Model of Customer Satisfaction Degree in Logistics
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.
Tracking and registration method based on vector operation for augmented reality system
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.
Drifting model approach to modeling based on weighted support vector machines
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.
PSO-Based Support Vector Machine with Cuckoo Search Technique for Clinical Disease Diagnoses
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 ...
Robustness-Based Simplification of 2D Steady and Unsteady Vector Fields
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.
Robustness-Based Simplification of 2D Steady and Unsteady Vector Fields.
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
Vector quantizer based on brightness maps for image compression with the polynomial transform
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
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.
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
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.
Recognition of low-contrast FLIR tank object based on multiscale fractal character vector
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.
Generation of a helper cell line for packaging avian leukosis virus-based vectors.
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...
Evaluation of cache-based superscalar and cacheless vector architectures for scientific computations
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.
Advances in SVM-Based System Using GMM Super Vectors for Text-Independent Speaker Verification
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.
Support vector regression model based predictive control of water level of U-tube steam generators
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
An Improved Endmember Selection Method Based on Vector Length for MODIS Reflectance Channels
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.
2D Gaze Estimation Based on Pupil-Glint Vector Using an Artificial Neural Network
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.
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.
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
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
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.
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.
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.
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.
A Simplified Sensorless Vector Control Based on Average DC Bus Current for Fan Motor
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.
Polarization imaging of multiply-scattered radiation based on integral-vector Monte Carlo method
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.
Recursions in Calogero-Sutherland Model Based on Virasoro Singular Vectors
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)
The study of underwater acoustic communication technology based-on the acoustic vector sensor
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.
Boost OCR accuracy using iVector based system combination approach
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.
Bidding Strategy with Forecast Technology Based on Support Vector Machine in Electrcity Market
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.
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 ...
无
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.
Thrust estimator design based on least squares support vector regression machine
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.
System identification modelling of ship manoeuvring motion based onε- support vector regression
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.
Vegetation change detection for urban areas based on extended change vector analysis
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.
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.
Triple-image encryption based on phase-truncated Fresnel transform and basic vector operation.
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
A series of TA-based and zero-background vectors for plant functional genomics.
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.
DNA vector-based RNAi approach for stable depletion of poly(ADP-ribose) polymerase-1
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
Robust Vision-Based Pose Estimation Algorithm for AN Uav with Known Gravity Vector
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.
Development of expression vectors for Escherichia coli based on the pCR2 replicon
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.
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.
PDM-16QAM vector signal generation and detection based on intensity modulation and direct detection
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.
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...
Comparison of strapdown inertial navigation algorithm based on rotation vector and dual quaternion
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.
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
Flagellin Encoded in Gene-Based Vector Vaccines Is a Route-Dependent Immune Adjuvant.
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
Flagellin Encoded in Gene-Based Vector Vaccines Is a Route-Dependent Immune Adjuvant.
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.
Face Recognition Based on Support Vector Machine and Nearest Neighbor Classifier
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.
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
Fast Matrix Computation Algorithms Based on Rough Attribute Vector Tree Method in RDSS
无
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.
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.
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.
STATE SPACE POINT DISTRIBUTION PARAMETER FOR SUPPORT VECTOR MACHINE BASED CV UNIT CLASSIFICATION
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.
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)