New proxy replacement algorithm for multimedia streaming
Wong, Hau Ling; Lo, Kwok-Tung
2001-11-01
Proxy servers play an important role in between servers and clients in various multimedia systems on the Internet. Since proxy servers do not have an infinite-capacity cache for keeping all the continuous media data, the challenge for the replacement policy is to determine which streams should be cached or removed from the proxy server. In this paper, a new proxy replacement algorithm, named the Least Popular Used (LPU) caching algorithm, is proposed for layered encoded multimedia streams in the Internet. The LPU method takes both the short-term and long-term popularity of the video into account in determining the replacement policy. Simulation evaluation shows that our proposed scheme achieves better results than some existing methods in term of the cache efficiency and replacement frequency under both static and dynamic access environments.
Vectorized algorithms for spiking neural network simulation.
Brette, Romain; Goodman, Dan F M
2011-06-01
High-level languages (Matlab, Python) are popular in neuroscience because they are flexible and accelerate development. However, for simulating spiking neural networks, the cost of interpretation is a bottleneck. We describe a set of algorithms to simulate large spiking neural networks efficiently with high-level languages using vector-based operations. These algorithms constitute the core of Brian, a spiking neural network simulator written in the Python language. Vectorized simulation makes it possible to combine the flexibility of high-level languages with the computational efficiency usually associated with compiled languages.
Algorithms for quadratic matrix and vector equations
Poloni, Federico
2011-01-01
This book is devoted to studying algorithms for the solution of a class of quadratic matrix and vector equations. These equations appear, in different forms, in several practical applications, especially in applied probability and control theory. The equations are first presented using a novel unifying approach; then, specific numerical methods are presented for the cases most relevant for applications, and new algorithms and theoretical results developed by the author are presented. The book focuses on “matrix multiplication-rich” iterations such as cyclic reduction and the structured doubling algorithm (SDA) and contains a variety of new research results which, as of today, are only available in articles or preprints.
Flash-Aware Page Replacement Algorithm
Directory of Open Access Journals (Sweden)
Guangxia Xu
2014-01-01
Full Text Available Due to the limited main memory resource of consumer electronics equipped with NAND flash memory as storage device, an efficient page replacement algorithm called FAPRA is proposed for NAND flash memory in the light of its inherent characteristics. FAPRA introduces an efficient victim page selection scheme taking into account the benefit-to-cost ratio for evicting each victim page candidate and the combined recency and frequency value, as well as the erase count of the block to which each page belongs. Since the dirty victim page often contains clean data that exist in both the main memory and the NAND flash memory based storage device, FAPRA only writes the dirty data within the victim page back to the NAND flash memory based storage device in order to reduce the redundant write operations. We conduct a series of trace-driven simulations and experimental results show that our proposed FAPRA algorithm outperforms the state-of-the-art algorithms in terms of page hit ratio, the number of write operations, runtime, and the degree of wear leveling.
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
Digital practical tracking: Algorithms with vector settling time
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Stojčić Mihajlo J.
2005-01-01
Full Text Available In this paper nonlinear stationary digital system with separated control is treated. The new definitions of practical tracking with vector settling time are presented. Furthermore, new criteria and control algorithms which ensure digital practical tracking with vector settling time are given and proven. The results are simulated on an example.
Parallel-vector algorithms for analysis of large structures
Soegiarso, R.; Adeli, H.
1995-01-01
In analysis of large space structures, the major computational steps are evaluation and assembly of the structure stiffness matrix and solution of the resulting simultaneous linear equations. In this paper we present efficient parallel-vector algorithms for these steps of structural analysis. The goal is to optimize the performance of the algorithms through judicious combination of parallel processing and vectorization. Parallel-vector algorithms are presented for solution of linear simultaneous equations using Cholesky decomposition and preconditioned conjugate gradient approaches. The algorithms are applied to three large space structures modeling the exterior envelope of high-rise and super high-rise building structures in the range of 50-162 stories with up to 6,136 members. Performance results are presented in terms of central-processing-unit time on a Cray Y-MP8/864 supercomputer, MFLOPS (millions of floating point operations per second), and speedup.
An efficient parallel algorithm for matrix-vector multiplication
Energy Technology Data Exchange (ETDEWEB)
Hendrickson, B.; Leland, R.; Plimpton, S.
1993-03-01
The multiplication of a vector by a matrix is the kernel computation of many algorithms in scientific computation. A fast parallel algorithm for this calculation is therefore necessary if one is to make full use of the new generation of parallel supercomputers. This paper presents a high performance, parallel matrix-vector multiplication algorithm that is particularly well suited to hypercube multiprocessors. For an n x n matrix on p processors, the communication cost of this algorithm is O(n/[radical]p + log(p)), independent of the matrix sparsity pattern. The performance of the algorithm is demonstrated by employing it as the kernel in the well-known NAS conjugate gradient benchmark, where a run time of 6.09 seconds was observed. This is the best published performance on this benchmark achieved to date using a massively parallel supercomputer.
Fast vector quantization using a Bat algorithm for image compression
Karri, Chiranjeevi; Jena, Umaranjan
2017-01-01
Linde–Buzo–Gray (LBG), a traditional method of vector quantization (VQ) generates a local optimal codebook which results in lower PSNR value. The performance of vector quantization (VQ) depends on the appropriate codebook, so researchers proposed optimization techniques for global codebook generation. Particle swarm optimization (PSO) and Firefly algorithm (FA) generate an efficient codebook, but undergoes instability in convergence when particle velocity is high and non-availability of brigh...
DEFF Research Database (Denmark)
Frandsen, Rasmus John Normand; Andersson, Jens A.; Kristensen, Matilde Bylov
2008-01-01
Background: The rapid increase in whole genome fungal sequence information allows large scale functional analyses of target genes. Efficient transformation methods to obtain site-directed gene replacement, targeted over-expression by promoter replacement, in-frame epitope tagging or fusion of cod...... with an average efficiency of 84% for gene replacement and 80% for targeted overexpression. Conclusion: The new vectors designed for USER Friendly cloning provided a fast reliable method to construct vectors for targeted gene manipulations in fungi....
Electricity Load Forecasting Using Support Vector Regression with Memetic Algorithms
Hu, Zhongyi; Xiong, Tao
2013-01-01
Electricity load forecasting is an important issue that is widely explored and examined in power systems operation literature and commercial transactions in electricity markets literature as well. Among the existing forecasting models, support vector regression (SVR) has gained much attention. Considering the performance of SVR highly depends on its parameters; this study proposed a firefly algorithm (FA) based memetic algorithm (FA-MA) to appropriately determine the parameters of SVR forecasting model. In the proposed FA-MA algorithm, the FA algorithm is applied to explore the solution space, and the pattern search is used to conduct individual learning and thus enhance the exploitation of FA. Experimental results confirm that the proposed FA-MA based SVR model can not only yield more accurate forecasting results than the other four evolutionary algorithms based SVR models and three well-known forecasting models but also outperform the hybrid algorithms in the related existing literature. PMID:24459425
Electricity Load Forecasting Using Support Vector Regression with Memetic Algorithms
Directory of Open Access Journals (Sweden)
Zhongyi Hu
2013-01-01
Full Text Available Electricity load forecasting is an important issue that is widely explored and examined in power systems operation literature and commercial transactions in electricity markets literature as well. Among the existing forecasting models, support vector regression (SVR has gained much attention. Considering the performance of SVR highly depends on its parameters; this study proposed a firefly algorithm (FA based memetic algorithm (FA-MA to appropriately determine the parameters of SVR forecasting model. In the proposed FA-MA algorithm, the FA algorithm is applied to explore the solution space, and the pattern search is used to conduct individual learning and thus enhance the exploitation of FA. Experimental results confirm that the proposed FA-MA based SVR model can not only yield more accurate forecasting results than the other four evolutionary algorithms based SVR models and three well-known forecasting models but also outperform the hybrid algorithms in the related existing literature.
Matrix Multiplication Algorithm Selection with Support Vector Machines
2015-05-01
libraries that could intelligently choose the optimal algorithm for a particular set of inputs. Users would be oblivious to the underlying algorithmic...SAT.” J. Artif . Intell. Res.(JAIR), vol. 32, pp. 565–606, 2008. [9] M. G. Lagoudakis and M. L. Littman, “Algorithm selection using reinforcement...Artificial Intelligence , vol. 21, no. 05, pp. 961–976, 2007. [15] C.-C. Chang and C.-J. Lin, “LIBSVM: A library for support vector machines,” ACM
Cache Memory: An Analysis on Replacement Algorithms and Optimization Techniques
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QAISAR JAVAID
2017-10-01
Full Text Available Caching strategies can improve the overall performance of a system by allowing the fast processor and slow memory to at a same pace. One important factor in caching is the replacement policy. Advancement in technology results in evolution of a huge number of techniques and algorithms implemented to improve cache performance. In this paper, analysis is done on different cache optimization techniques as well as replacement algorithms. Furthermore this paper presents a comprehensive statistical comparison of cache optimization techniques.To the best of our knowledge there is no numerical measure which can tell us the rating of specific cache optimization technique. We tried to come up with such a numerical figure. By statistical comparison we find out which technique is more consistent among all others. For said purpose we calculated mean and CV (Coefficient of Variation. CV tells us about which technique is more consistent. Comparative analysis of different techniques shows that victim cache has more consistent technique among all.
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Kristensen Matilde B
2008-08-01
Full Text Available Abstract Background The rapid increase in whole genome fungal sequence information allows large scale functional analyses of target genes. Efficient transformation methods to obtain site-directed gene replacement, targeted over-expression by promoter replacement, in-frame epitope tagging or fusion of coding sequences with fluorescent markers such as GFP are essential for this process. Construction of vectors for these experiments depends on the directional cloning of two homologous recombination sequences on each side of a selection marker gene. Results Here, we present a USER Friendly cloning based technique that allows single step cloning of the two required homologous recombination sequences into different sites of a recipient vector. The advantages are: A simple experimental design, free choice of target sequence, few procedures and user convenience. The vectors are intented for Agrobacterium tumefaciens and protoplast based transformation technologies. The system has been tested by the construction of vectors for targeted replacement of 17 genes and overexpression of 12 genes in Fusarium graminearum. The results show that four fragment vectors can be constructed in a single cloning step with an average efficiency of 84% for gene replacement and 80% for targeted overexpression. Conclusion The new vectors designed for USER Friendly cloning provided a fast reliable method to construct vectors for targeted gene manipulations in fungi.
Fast vector quantization using a Bat algorithm for image compression
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Chiranjeevi Karri
2016-06-01
Full Text Available Linde–Buzo–Gray (LBG, a traditional method of vector quantization (VQ generates a local optimal codebook which results in lower PSNR value. The performance of vector quantization (VQ depends on the appropriate codebook, so researchers proposed optimization techniques for global codebook generation. Particle swarm optimization (PSO and Firefly algorithm (FA generate an efficient codebook, but undergoes instability in convergence when particle velocity is high and non-availability of brighter fireflies in the search space respectively. In this paper, we propose a new algorithm called BA-LBG which uses Bat Algorithm on initial solution of LBG. It produces an efficient codebook with less computational time and results very good PSNR due to its automatic zooming feature using adjustable pulse emission rate and loudness of bats. From the results, we observed that BA-LBG has high PSNR compared to LBG, PSO-LBG, Quantum PSO-LBG, HBMO-LBG and FA-LBG, and its average convergence speed is 1.841 times faster than HBMO-LBG and FA-LBG but no significance difference with PSO.
A Semisupervised Support Vector Machines Algorithm for BCI Systems
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Jianzhao Qin
2007-07-01
Full Text Available As an emerging technology, brain-computer interfaces (BCIs bring us new communication interfaces which translate brain activities into control signals for devices like computers, robots, and so forth. In this study, we propose a semisupervised support vector machine (SVM algorithm for brain-computer interface (BCI systems, aiming at reducing the time-consuming training process. In this algorithm, we apply a semisupervised SVM for translating the features extracted from the electrical recordings of brain into control signals. This SVM classifier is built from a small labeled data set and a large unlabeled data set. Meanwhile, to reduce the time for training semisupervised SVM, we propose a batch-mode incremental learning method, which can also be easily applied to the online BCI systems. Additionally, it is suggested in many studies that common spatial pattern (CSP is very effective in discriminating two different brain states. However, CSP needs a sufficient labeled data set. In order to overcome the drawback of CSP, we suggest a two-stage feature extraction method for the semisupervised learning algorithm. We apply our algorithm to two BCI experimental data sets. The offline data analysis results demonstrate the effectiveness of our algorithm.
Single Directional SMO Algorithm for Least Squares Support Vector Machines
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Xigao Shao
2013-01-01
Full Text Available Working set selection is a major step in decomposition methods for training least squares support vector machines (LS-SVMs. In this paper, a new technique for the selection of working set in sequential minimal optimization- (SMO- type decomposition methods is proposed. By the new method, we can select a single direction to achieve the convergence of the optimality condition. A simple asymptotic convergence proof for the new algorithm is given. Experimental comparisons demonstrate that the classification accuracy of the new method is not largely different from the existing methods, but the training speed is faster than existing ones.
Thrust vector control algorithm design for the Cassini spacecraft
Enright, Paul J.
1993-01-01
This paper describes a preliminary design of the thrust vector control algorithm for the interplanetary spacecraft, Cassini. Topics of discussion include flight software architecture, modeling of sensors, actuators, and vehicle dynamics, and controller design and analysis via classical methods. Special attention is paid to potential interactions with structural flexibilities and propellant dynamics. Controller performance is evaluated in a simulation environment built around a multi-body dynamics model, which contains nonlinear models of the relevant hardware and preliminary versions of supporting attitude determination and control functions.
Robert, Michael A; Okamoto, Kenichi; Lloyd, Alun L; Gould, Fred
2013-01-01
Genetic approaches for controlling disease vectors have aimed either to reduce wild-type populations or to replace wild-type populations with insects that cannot transmit pathogens. Here, we propose a Reduce and Replace (R&R) strategy in which released insects have both female-killing and anti-pathogen genes. We develop a mathematical model to numerically explore release strategies involving an R&R strain of the dengue vector Aedes aegypti. We show that repeated R&R releases may lead to a temporary decrease in mosquito population density and, in the absence of fitness costs associated with the anti-pathogen gene, a long-term decrease in competent vector population density. We find that R&R releases more rapidly reduce the transient and long-term competent vector densities than female-killing releases alone. We show that releases including R&R females lead to greater reduction in competent vector density than male-only releases. The magnitude of reduction in total and competent vectors depends upon the release ratio, release duration, and whether females are included in releases. Even when the anti-pathogen allele has a fitness cost, R&R releases lead to greater reduction in competent vectors than female-killing releases during the release period; however, continued releases are needed to maintain low density of competent vectors long-term. We discuss the results of the model as motivation for more detailed studies of R&R strategies.
[Rule induction algorithm for brain glioma using support vector machine].
Li, Guozheng; Yang, Jie; Wang, Jiaju; Geng, Daoying
2006-04-01
A new proposed data mining technique, support vector machine (SVM), is used to predict the degree of malignancy in brain glioma. Based on statistical learning theory, SVM realizes the principle of data dependent structure risk minimization, so it can depress the overfitting with better generalization performance, since the prediction in medical diagnosis often deals with a small sample. SVM based rule induction algorithm is implemented in comparison with other data mining techniques such as artificial neural networks, rule induction algorithm and fuzzy rule extraction algorithm based on fuzzy max-min neural networks (FRE-FMMNN) proposed recently. Computation results by 10 fold cross validation method show that SVM can get higher prediction accuracy than artificial neural networks and FRE-FMMNN, which implies SVM can get higher accuracy and more reliability. On the whole data sets, SVM gets one rule with the classification accuracy of 89.29%, while FRE-FMMNN gets two rules of 84. 64%, in which the rule got by SVM is of quantity relation and contains more information than the two rules by FRE-FMMNN. All the above show SVM is a potential algorithm for the medical diagnosis such as the prediction of the degree of malignancy in brain glioma.
Improved algorithm for data conversion from raster to vector
Teng, Junhua; Wang, Fahui
2007-06-01
Transforming Remote Sensing (RS) classification result from the raster to vector format (R2V) is a common task in Geographic Information Systems (GIS) and RS image processing. R2V acts as a bridge connecting GIS and RS data integration, and is an important module in many commercial software packages such as ENVI and ArcGIS. While considering inconvenience and inefficiency existed in current R2V algorithm, it still has some room to improve. In this paper some technologies and skills are addressed to improve R2V, including sub-image dynamical separation, fast edge tracing, segment combination and partial topology construction. A new method of two-Arm chain edge tracing is introduced. The improved algorithm has so me advantages: It can transform all types of RS classification only once, and build complete topology relationship; The shared edge between two polygons is recorded only once, the diagonal pixels with same attribution are connected automatically; It is scalable while processing large dimension image,it runs fast and enjoys a significant advantage in processing large RS images; It is convenient to edit and modify the vectorised map because of its complete topology information. Based on case study, the preliminary results show its some advantages over Envi and ArcGIS.
Joint Smoothed l0-Norm DOA Estimation Algorithm for Multiple Measurement Vectors in MIMO Radar
National Research Council Canada - National Science Library
Jing Liu; Weidong Zhou; Filbert H Juwono
2017-01-01
.... In this paper, a novel fast sparse DOA estimation algorithm, named the joint smoothed l0 -norm algorithm, is proposed for multiple measurement vectors in multiple-input multiple-output (MIMO) radar...
An algorithm for the exact Fisher information matrix of vector ARMAX time series processes
Klein, A.; Melard, G.
2011-01-01
In this paper an algorithm is developed for the exact Fisher information matrix of a vector ARMAX Gaussian process, VARMAX. The algorithm developed in this paper is composed by recursion equations at a vector-matrix level and some of these recursions consist of derivatives. For that purpose
A selective-update affine projection algorithm with selective input vectors
Kong, NamWoong; Shin, JaeWook; Park, PooGyeon
2011-10-01
This paper proposes an affine projection algorithm (APA) with selective input vectors, which based on the concept of selective-update in order to reduce estimation errors and computations. The algorithm consists of two procedures: input- vector-selection and state-decision. The input-vector-selection procedure determines the number of input vectors by checking with mean square error (MSE) whether the input vectors have enough information for update. The state-decision procedure determines the current state of the adaptive filter by using the state-decision criterion. As the adaptive filter is in transient state, the algorithm updates the filter coefficients with the selected input vectors. On the other hand, as soon as the adaptive filter reaches the steady state, the update procedure is not performed. Through these two procedures, the proposed algorithm achieves small steady-state estimation errors, low computational complexity and low update complexity for colored input signals.
Luo, Liyan; Xu, Luping; Zhang, Hua
2015-07-07
In order to enhance the robustness and accelerate the recognition speed of star identification, an autonomous star identification algorithm for star sensors is proposed based on the one-dimensional vector pattern (one_DVP). In the proposed algorithm, the space geometry information of the observed stars is used to form the one-dimensional vector pattern of the observed star. The one-dimensional vector pattern of the same observed star remains unchanged when the stellar image rotates, so the problem of star identification is simplified as the comparison of the two feature vectors. The one-dimensional vector pattern is adopted to build the feature vector of the star pattern, which makes it possible to identify the observed stars robustly. The characteristics of the feature vector and the proposed search strategy for the matching pattern make it possible to achieve the recognition result as quickly as possible. The simulation results demonstrate that the proposed algorithm can effectively accelerate the star identification. Moreover, the recognition accuracy and robustness by the proposed algorithm are better than those by the pyramid algorithm, the modified grid algorithm, and the LPT algorithm. The theoretical analysis and experimental results show that the proposed algorithm outperforms the other three star identification algorithms.
An Autonomous Star Identification Algorithm Based on One-Dimensional Vector Pattern for Star Sensors
Luo, Liyan; Xu, Luping; Zhang, Hua
2015-01-01
In order to enhance the robustness and accelerate the recognition speed of star identification, an autonomous star identification algorithm for star sensors is proposed based on the one-dimensional vector pattern (one_DVP). In the proposed algorithm, the space geometry information of the observed stars is used to form the one-dimensional vector pattern of the observed star. The one-dimensional vector pattern of the same observed star remains unchanged when the stellar image rotates, so the problem of star identification is simplified as the comparison of the two feature vectors. The one-dimensional vector pattern is adopted to build the feature vector of the star pattern, which makes it possible to identify the observed stars robustly. The characteristics of the feature vector and the proposed search strategy for the matching pattern make it possible to achieve the recognition result as quickly as possible. The simulation results demonstrate that the proposed algorithm can effectively accelerate the star identification. Moreover, the recognition accuracy and robustness by the proposed algorithm are better than those by the pyramid algorithm, the modified grid algorithm, and the LPT algorithm. The theoretical analysis and experimental results show that the proposed algorithm outperforms the other three star identification algorithms. PMID:26198233
Support Vector Regression and Genetic Algorithm for HVAC Optimal Operation
Directory of Open Access Journals (Sweden)
Ching-Wei Chen
2016-01-01
Full Text Available This study covers records of various parameters affecting the power consumption of air-conditioning systems. Using the Support Vector Machine (SVM, the chiller power consumption model, secondary chilled water pump power consumption model, air handling unit fan power consumption model, and air handling unit load model were established. In addition, it was found that R2 of the models all reached 0.998, and the training time was far shorter than that of the neural network. Through genetic programming, a combination of operating parameters with the least power consumption of air conditioning operation was searched. Moreover, the air handling unit load in line with the air conditioning cooling load was predicted. The experimental results show that for the combination of operating parameters with the least power consumption in line with the cooling load obtained through genetic algorithm search, the power consumption of the air conditioning systems under said combination of operating parameters was reduced by 22% compared to the fixed operating parameters, thus indicating significant energy efficiency.
Analysis of human protein replacement stable cell lines established using snoMEN-PR vector.
Directory of Open Access Journals (Sweden)
Motoharu Ono
Full Text Available The study of the function of many human proteins is often hampered by technical limitations, such as cytotoxicity and phenotypes that result from overexpression of the protein of interest together with the endogenous version. Here we present the snoMEN (snoRNA Modulator of gene ExpressioN vector technology for generating stable cell lines where expression of the endogenous protein can be reduced and replaced by an exogenous protein, such as a fluorescent protein (FP-tagged version. SnoMEN are snoRNAs engineered to contain complementary sequences that can promote knock-down of targeted RNAs. We have established and characterised two such partial protein replacement human cell lines (snoMEN-PR. Quantitative mass spectrometry was used to analyse the specificity of knock-down and replacement at the protein level and also showed an increased pull-down efficiency of protein complexes containing exogenous, tagged proteins in the protein replacement cell lines, as compared with conventional co-expression strategies. The snoMEN approach facilitates the study of mammalian proteins, particularly those that have so far been difficult to investigate by exogenous expression and has wide applications in basic and applied gene-expression research.
Yuanyuan Zhao; Qian Chen
2014-01-01
To make production plan, online order priority evaluation is the current priority weakness of online order evaluation model. This thesis proposes an online order priority evaluation model based on hybrid harmony search algorithm of optimized support vector machine (HHS-SVM). Firstly, an online order priority evaluation index system is build, and then support vector machine is adopted to build an online order priority evaluation model; secondly, harmony search algorithm is used to optimize the...
Research on the improved vector coding algorithm for two dimensional Discrete Fourier Transform
Zhang, Hao; Chen, Zhaodou; Yang, Jin
2017-03-01
Discrete Fourier Transform (DFT) plays a crucial role in signal processing. In this paper, a new fast algorithm is presented for two dimensional DFT with different lengths. This algorithm is derived using a technique for multidimensional integral point called `vector coding'. The new algorithm significantly reduces the multiplications and recursive stages compared with row-column algorithm, and also skip the data transposing. The algorithm can spread to multidimensional DFT. For two dimensional, compared with row-column algorithm, the vector coding algorithm has the same addition, but about three-quarters of multiplication, and reduce the recursive stages a half. This original article was incorrectly published with pages 5 and 6 missing. At the request of the Proceedings Editor, a corrected version of this article was published online 24 March 2017. This article has also been corrected in the printed version of the volume.
Uni-Vector-Sensor Dimensionality Reduction MUSIC Algorithm for DOA and Polarization Estimation
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Lanmei Wang
2014-01-01
Full Text Available This paper addresses the problem of multiple signal classification- (MUSIC- based direction of arrival (DOA and polarization estimation and proposes a new dimensionality reduction MUSIC (DR-MUSIC algorithm. Uni-vector-sensor MUSIC algorithm provides estimation for DOA and polarization; accordingly, a four-dimensional peak search is required, which hence incurs vast amount of computation. In the proposed DR-MUSIC method, the signal steering vector is expressed in the product form of arrival angle function matrix and polarization function vector. The MUSIC joint spectrum is converted to the form of Rayleigh-Ritz ratio by using the feature where the 2-norm of polarization function vector is constant. A four-dimensional MUSIC search reduced the dimension to two two-dimensional searches and the amount of computation is greatly decreased. The theoretical analysis and simulation results have verified the effectiveness of the proposed algorithm.
Directory of Open Access Journals (Sweden)
Wen-Gang Zhou
2015-06-01
Full Text Available With the deep research of genomics and proteomics, the number of new protein sequences has expanded rapidly. With the obvious shortcomings of high cost and low efficiency of the traditional experimental method, the calculation method for protein localization prediction has attracted a lot of attention due to its convenience and low cost. In the machine learning techniques, neural network and support vector machine (SVM are often used as learning tools. Due to its complete theoretical framework, SVM has been widely applied. In this paper, we make an improvement on the existing machine learning algorithm of the support vector machine algorithm, and a new improved algorithm has been developed, combined with Bayesian algorithms. The proposed algorithm can improve calculation efficiency, and defects of the original algorithm are eliminated. According to the verification, the method has proved to be valid. At the same time, it can reduce calculation time and improve prediction efficiency.
Guiding vector field algorithm for a moving path following problem
Kapitanyuk, Yuri A.; Garcia de Marina, Hector; Proskurnikov, A.V.; Cao, Ming; Dochain, Denis; Henrion, Didier; Peaucelle, Dimitri
2017-01-01
This paper presents a guidance algorithm solving the problem of moving path following, that is, steering a mobile robot to a curvilinear path attached to a moving frame. The nonholonomic robot is described by the unicycle-type model under the influence of some constant exogenous disturbance. The
A Corporate Credit Rating Model Using Support Vector Domain Combined with Fuzzy Clustering Algorithm
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Xuesong Guo
2012-01-01
Full Text Available Corporate credit-rating prediction using statistical and artificial intelligence techniques has received considerable attentions in the literature. Different from the thoughts of various techniques for adopting support vector machines as binary classifiers originally, a new method, based on support vector domain combined with fuzzy clustering algorithm for multiclassification, is proposed in the paper to accomplish corporate credit rating. By data preprocessing using fuzzy clustering algorithm, only the boundary data points are selected as training samples to accomplish support vector domain specification to reduce computational cost and also achieve better performance. To validate the proposed methodology, real-world cases are used for experiments, with results compared with conventional multiclassification support vector machine approaches and other artificial intelligence techniques. The results show that the proposed model improves the performance of corporate credit-rating with less computational consumption.
Determining Optimal Replacement Policy with an Availability Constraint via Genetic Algorithms
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Shengliang Zong
2017-01-01
Full Text Available We develop a model and a genetic algorithm for determining an optimal replacement policy for power equipment subject to Poisson shocks. If the time interval of two consecutive shocks is less than a threshold value, the failed equipment can be repaired. We assume that the operating time after repair is stochastically nonincreasing and the repair time is exponentially distributed with a geometric increasing mean. Our objective is to minimize the expected average cost under an availability requirement. Based on this average cost function, we propose the genetic algorithm to locate the optimal replacement policy N to minimize the average cost rate. The results show that the GA is effective and efficient in finding the optimal solutions. The availability of equipment has significance effect on the optimal replacement policy. Many practical systems fit the model developed in this paper.
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A. A. Zolotin
2015-01-01
Full Text Available We consider a task of local posteriori inference description by means of matrix-vector equations in algebraical Bayesian networks that represent a class of probabilistic graphical models. Such equations were generally presented in previous publications, however containing normalizing factors that were provided with algorithmic descriptions of their calculations instead of the desired matrix-vector interpretation. To eliminate this gap, the normalized factors were firstly represented as scalar products. Then, it was successfully shown that one of the components in each scalar product can be expressed as a Kronecker degree of a constant two-dimensional vector. Later on, non-normalized posteriori inference matrixoperator transplantation and further transfer within each scalar product yielded a representation of one of the scalar product components as a sequence of tensor products of two-dimensional vectors. The latter vectors have only two possible values in one case and three values in the other. The choice among those values is determined by the structure of input evidence. The second component of each scalar products is the vector with original data. The calculations performed gave the possibility for constructing corresponding vectors; the paper contains a table with proper examples for some of them. Local posteriori inference representation for matrix-vector equations simplify the development of local posteriori inference algorithms, their verification and further implementation based on available libraries. These equations also give the possibility for application of classical mathematical techniques to the obtained results analysis. Finally, the results obtained make it possible to apply the method of postponed calculations. This method helps avoiding construction of big-size vectors; instead, the vectors components can be calculated just in time they are needed by means of bitwise operations.
2016-12-01
Physics and Industrial Engineering ; 2012; Beijing, China . ICAPIE 1875-3892. 26. Lipowski A, Lipowska D. Roulette-wheel selection via stochastic...Evaluated Genetic Algorithm prepared by Justin L Paul Academy of Applied Science 24 Warren Street Concord, NH 03301 under contract W911SR...Supersonic Bending Body Projectile by a Vector-Evaluated Genetic Algorithm prepared by Justin L Paul Academy of Applied Science 24 Warren Street
Genetic algorithm identification of a H-moving vector hysteresis model
Energy Technology Data Exchange (ETDEWEB)
Cardelli, E. [Department of Industrial Engineering, University of Perugia, I-06125 Perugia (Italy); Center for Electric and Magnetic Applied Research (Italy); Faba, A., E-mail: faba@unipg.it [Department of Industrial Engineering, University of Perugia, I-06125 Perugia (Italy); Center for Electric and Magnetic Applied Research (Italy)
2014-02-15
In this work we present an identification procedure for a vector hysteresis model defined by a H-moving approach. The model parameters are identified by means of a suitable implementation of a genetic algorithm with a set of experimental data. The analytical formulation of the model and the characteristics of the genetic algorithm used are described. A comparison between computed data and experimental measurements for a not oriented grain Si–Fe magnetic steel with a weak lamination anisotropy are reported.
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.
Modified particle filtering algorithm for single acoustic vector sensor DOA tracking.
Li, Xinbo; Sun, Haixin; Jiang, Liangxu; Shi, Yaowu; Wu, Yue
2015-10-16
The conventional direction of arrival (DOA) estimation algorithm with static sources assumption usually estimates the source angles of two adjacent moments independently and the correlation of the moments is not considered. In this article, we focus on the DOA estimation of moving sources and a modified particle filtering (MPF) algorithm is proposed with state space model of single acoustic vector sensor. Although the particle filtering (PF) algorithm has been introduced for acoustic vector sensor applications, it is not suitable for the case that one dimension angle of source is estimated with large deviation, the two dimension angles (pitch angle and azimuth angle) cannot be simultaneously employed to update the state through resampling processing of PF algorithm. To solve the problems mentioned above, the MPF algorithm is proposed in which the state estimation of previous moment is introduced to the particle sampling of present moment to improve the importance function. Moreover, the independent relationship of pitch angle and azimuth angle is considered and the two dimension angles are sampled and evaluated, respectively. Then, the MUSIC spectrum function is used as the "likehood" function of the MPF algorithm, and the modified PF-MUSIC (MPF-MUSIC) algorithm is proposed to improve the root mean square error (RMSE) and the probability of convergence. The theoretical analysis and the simulation results validate the effectiveness and feasibility of the two proposed algorithms.
Modified Particle Filtering Algorithm for Single Acoustic Vector Sensor DOA Tracking
Directory of Open Access Journals (Sweden)
Xinbo Li
2015-10-01
Full Text Available The conventional direction of arrival (DOA estimation algorithm with static sources assumption usually estimates the source angles of two adjacent moments independently and the correlation of the moments is not considered. In this article, we focus on the DOA estimation of moving sources and a modified particle filtering (MPF algorithm is proposed with state space model of single acoustic vector sensor. Although the particle filtering (PF algorithm has been introduced for acoustic vector sensor applications, it is not suitable for the case that one dimension angle of source is estimated with large deviation, the two dimension angles (pitch angle and azimuth angle cannot be simultaneously employed to update the state through resampling processing of PF algorithm. To solve the problems mentioned above, the MPF algorithm is proposed in which the state estimation of previous moment is introduced to the particle sampling of present moment to improve the importance function. Moreover, the independent relationship of pitch angle and azimuth angle is considered and the two dimension angles are sampled and evaluated, respectively. Then, the MUSIC spectrum function is used as the “likehood” function of the MPF algorithm, and the modified PF-MUSIC (MPF-MUSIC algorithm is proposed to improve the root mean square error (RMSE and the probability of convergence. The theoretical analysis and the simulation results validate the effectiveness and feasibility of the two proposed algorithms.
Optimal Synthesis of Universal Space Vector Digital Algorithm for Matrix Converters
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Adrian Popovici
2017-04-01
Full Text Available This paper presents the synthesis of a dynamic space vector modulation for power matrix converters so that it is possible to implement a universal modulator that provides a control algorithm dynamically optimized according to the requirements for the matrix converter.
Joint Smoothed l0-Norm DOA Estimation Algorithm for Multiple Measurement Vectors in MIMO Radar
Liu, Jing; Zhou, Weidong; Juwono, Filbert H.
2017-01-01
Direction-of-arrival (DOA) estimation is usually confronted with a multiple measurement vector (MMV) case. In this paper, a novel fast sparse DOA estimation algorithm, named the joint smoothed l0-norm algorithm, is proposed for multiple measurement vectors in multiple-input multiple-output (MIMO) radar. To eliminate the white or colored Gaussian noises, the new method first obtains a low-complexity high-order cumulants based data matrix. Then, the proposed algorithm designs a joint smoothed function tailored for the MMV case, based on which joint smoothed l0-norm sparse representation framework is constructed. Finally, for the MMV-based joint smoothed function, the corresponding gradient-based sparse signal reconstruction is designed, thus the DOA estimation can be achieved. The proposed method is a fast sparse representation algorithm, which can solve the MMV problem and perform well for both white and colored Gaussian noises. The proposed joint algorithm is about two orders of magnitude faster than the l1-norm minimization based methods, such as l1-SVD (singular value decomposition), RV (real-valued) l1-SVD and RV l1-SRACV (sparse representation array covariance vectors), and achieves better DOA estimation performance. PMID:28481309
Joint Smoothed l₀-Norm DOA Estimation Algorithm for Multiple Measurement Vectors in MIMO Radar.
Liu, Jing; Zhou, Weidong; Juwono, Filbert H
2017-05-08
Direction-of-arrival (DOA) estimation is usually confronted with a multiple measurement vector (MMV) case. In this paper, a novel fast sparse DOA estimation algorithm, named the joint smoothed l 0 -norm algorithm, is proposed for multiple measurement vectors in multiple-input multiple-output (MIMO) radar. To eliminate the white or colored Gaussian noises, the new method first obtains a low-complexity high-order cumulants based data matrix. Then, the proposed algorithm designs a joint smoothed function tailored for the MMV case, based on which joint smoothed l 0 -norm sparse representation framework is constructed. Finally, for the MMV-based joint smoothed function, the corresponding gradient-based sparse signal reconstruction is designed, thus the DOA estimation can be achieved. The proposed method is a fast sparse representation algorithm, which can solve the MMV problem and perform well for both white and colored Gaussian noises. The proposed joint algorithm is about two orders of magnitude faster than the l 1 -norm minimization based methods, such as l 1 -SVD (singular value decomposition), RV (real-valued) l 1 -SVD and RV l 1 -SRACV (sparse representation array covariance vectors), and achieves better DOA estimation performance.
Energy Technology Data Exchange (ETDEWEB)
He, Hongxing; Fang, Hengrui [Department of Physics and Texas Center for Superconductivity, University of Houston, Houston, Texas 77204 (United States); Miller, Mitchell D. [Department of BioSciences, Rice University, Houston, Texas 77005 (United States); Phillips, George N. Jr [Department of BioSciences, Rice University, Houston, Texas 77005 (United States); Department of Chemistry, Rice University, Houston, Texas 77005 (United States); Department of Biochemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706 (United States); Su, Wu-Pei, E-mail: wpsu@uh.edu [Department of Physics and Texas Center for Superconductivity, University of Houston, Houston, Texas 77204 (United States)
2016-07-15
An iterative transform algorithm is proposed to improve the conventional molecular-replacement method for solving the phase problem in X-ray crystallography. Several examples of successful trial calculations carried out with real diffraction data are presented. An iterative transform method proposed previously for direct phasing of high-solvent-content protein crystals is employed for enhancing the molecular-replacement (MR) algorithm in protein crystallography. Target structures that are resistant to conventional MR due to insufficient similarity between the template and target structures might be tractable with this modified phasing method. Trial calculations involving three different structures are described to test and illustrate the methodology. The relationship of the approach to PHENIX Phaser-MR and MR-Rosetta is discussed.
Accelerating Families of Fuzzy K-Means Algorithms for Vector Quantization Codebook Design.
Mata, Edson; Bandeira, Silvio; de Mattos Neto, Paulo; Lopes, Waslon; Madeiro, Francisco
2016-11-23
The performance of signal processing systems based on vector quantization depends on codebook design. In the image compression scenario, the quality of the reconstructed images depends on the codebooks used. In this paper, alternatives are proposed for accelerating families of fuzzy K-means algorithms for codebook design. The acceleration is obtained by reducing the number of iterations of the algorithms and applying efficient nearest neighbor search techniques. Simulation results concerning image vector quantization have shown that the acceleration obtained so far does not decrease the quality of the reconstructed images. Codebook design time savings up to about 40% are obtained by the accelerated versions with respect to the original versions of the algorithms.
Directory of Open Access Journals (Sweden)
Jiří Fejfar
2012-01-01
Full Text Available We are presenting results comparison of three artificial intelligence algorithms in a classification of time series derived from musical excerpts in this paper. Algorithms were chosen to represent different principles of classification – statistic approach, neural networks and competitive learning. The first algorithm is a classical k-Nearest neighbours algorithm, the second algorithm is Multilayer Perceptron (MPL, an example of artificial neural network and the third one is a Learning Vector Quantization (LVQ algorithm representing supervised counterpart to unsupervised Self Organizing Map (SOM.After our own former experiments with unlabelled data we moved forward to the data labels utilization, which generally led to a better accuracy of classification results. As we need huge data set of labelled time series (a priori knowledge of correct class which each time series instance belongs to, we used, with a good experience in former studies, musical excerpts as a source of real-world time series. We are using standard deviation of the sound signal as a descriptor of a musical excerpts volume level.We are describing principle of each algorithm as well as its implementation briefly, giving links for further research. Classification results of each algorithm are presented in a confusion matrix showing numbers of misclassifications and allowing to evaluate overall accuracy of the algorithm. Results are compared and particular misclassifications are discussed for each algorithm. Finally the best solution is chosen and further research goals are given.
A Replacement Algorithm of Non-Maximum Suppression Base on Graph Clustering
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Zhao Xin
2017-01-01
Full Text Available Non-maximum suppression is an important step in many object detection and object counting algorithms. In contrast with the extensive studies of object detection, NMS method has not caused too much attention. Although traditional NMS method has demonstrated promising performance in detection tasks, we observe that it is a hard decision approach, which only uses the confidential scores and Intersection-over-Unions (IoUs to discard proposals. By this way, NMS method would keep many false proposals whose IoU with the ground truth proposal is smaller than the threshold, which indicates that NMS may not suitable for counting the object number in images. To eliminate the limitation on object counting task, we propose a novel algorithm base on graph clustering to replace the NMS method in this paper. Experiments on faster-rcnn and SSD show that our algorithm achieves better performance than that of NMS on the object counting task.
Directory of Open Access Journals (Sweden)
Tiannan Ma
2016-02-01
Full Text Available Icing on power transmission lines is a serious threat to the security and stability of the power grid, and it is necessary to establish a forecasting model to make accurate predictions of icing thickness. In order to improve the forecasting accuracy with regard to icing thickness, this paper proposes a combination model based on a wavelet support vector machine (w-SVM and a quantum fireworks algorithm (QFA for prediction. First, this paper uses the wavelet kernel function to replace the Gaussian wavelet kernel function and improve the nonlinear mapping ability of the SVM. Second, the regular fireworks algorithm is improved by combining it with a quantum optimization algorithm to strengthen optimization performance. Lastly, the parameters of w-SVM are optimized using the QFA model, and the QFA-w-SVM icing thickness forecasting model is established. Through verification using real-world examples, the results show that the proposed method has a higher forecasting accuracy and the model is effective and feasible.
A Novel Integrated Algorithm for Wind Vector Retrieval from Conically Scanning Scatterometers
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Xuetong Xie
2013-11-01
Full Text Available Due to the lower efficiency and the larger wind direction error of traditional algorithms, a novel integrated wind retrieval algorithm is proposed for conically scanning scatterometers. The proposed algorithm has the dual advantages of less computational cost and higher wind direction retrieval accuracy by integrating the wind speed standard deviation (WSSD algorithm and the wind direction interval retrieval (DIR algorithm. It adopts wind speed standard deviation as a criterion for searching possible wind vector solutions and retrieving a potential wind direction interval based on the change rate of the wind speed standard deviation. Moreover, a modified three-step ambiguity removal method is designed to let more wind directions be selected in the process of nudging and filtering. The performance of the new algorithm is illustrated by retrieval experiments using 300 orbits of SeaWinds/QuikSCAT L2A data (backscatter coefficients at 25 km resolution and co-located buoy data. Experimental results indicate that the new algorithm can evidently enhance the wind direction retrieval accuracy, especially in the nadir region. In comparison with the SeaWinds L2B Version 2 25 km selected wind product (retrieved wind fields, an improvement of 5.1° in wind direction retrieval can be made by the new algorithm for that region.
Energy Technology Data Exchange (ETDEWEB)
Bradley, J.N.; Brislawn, C.M.
1992-04-11
This report describes the development of a Wavelet Vector Quantization (WVQ) image compression algorithm for fingerprint raster files. The pertinent work was performed at Los Alamos National Laboratory for the Federal Bureau of Investigation. This document describes a previously-sent package of C-language source code, referred to as LAFPC, that performs the WVQ fingerprint compression and decompression tasks. The particulars of the WVQ algorithm and the associated design procedure are detailed elsewhere; the purpose of this document is to report the results of the design algorithm for the fingerprint application and to delineate the implementation issues that are incorporated in LAFPC. Special attention is paid to the computation of the wavelet transform, the fast search algorithm used for the VQ encoding, and the entropy coding procedure used in the transmission of the source symbols.
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Cheng-Wen Lee
2017-11-01
Full Text Available Accurate electricity forecasting is still the critical issue in many energy management fields. The applications of hybrid novel algorithms with support vector regression (SVR models to overcome the premature convergence problem and improve forecasting accuracy levels also deserve to be widely explored. This paper applies chaotic function and quantum computing concepts to address the embedded drawbacks including crossover and mutation operations of genetic algorithms. Then, this paper proposes a novel electricity load forecasting model by hybridizing chaotic function and quantum computing with GA in an SVR model (named SVRCQGA to achieve more satisfactory forecasting accuracy levels. Experimental examples demonstrate that the proposed SVRCQGA model is superior to other competitive models.
Zhang, Xiaofei; Zhou, Min; Li, Jianfeng
2013-04-19
In this paper, we combine the acoustic vector-sensor array parameter estimation problem with the parallel profiles with linear dependencies (PARALIND) model, which was originally applied to biology and chemistry. Exploiting the PARALIND decomposition approach, we propose a blind coherent two-dimensional direction of arrival (2D-DOA) estimation algorithm for arbitrarily spaced acoustic vector-sensor arrays subject to unknown locations. The proposed algorithm works well to achieve automatically paired azimuth and elevation angles for coherent and incoherent angle estimation of acoustic vector-sensor arrays, as well as the paired correlated matrix of the sources. Our algorithm, in contrast with conventional coherent angle estimation algorithms such as the forward backward spatial smoothing (FBSS) estimation of signal parameters via rotational invariance technique (ESPRIT) algorithm, not only has much better angle estimation performance, even for closely-spaced sources, but is also available for arbitrary arrays. Simulation results verify the effectiveness of our algorithm.
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S. Radhakrishnan
2014-03-01
Full Text Available The fishmeal replaced with Spirulina platensis, Chlorella vulgaris and Azolla pinnata and the formulated diet fed to Macrobrachium rosenbergii postlarvae to assess the enhancement ability of non-enzymatic antioxidants (vitamin C and E, enzymatic antioxidants (superoxide dismutase (SOD and catalase (CAT and lipid peroxidation (LPx were analysed. In the present study, the S. platensis, C. vulgaris and A. pinnata inclusion diet fed groups had significant (P < 0.05 improvement in the levels of vitamins C and E in the hepatopancreas and muscle tissue. Among all the diets, the replacement materials in 50% incorporated feed fed groups showed better performance when compared with the control group in non-enzymatic antioxidant activity. The 50% fishmeal replacement (best performance diet fed groups taken for enzymatic antioxidant study, in SOD, CAT and LPx showed no significant increases when compared with the control group. Hence, the present results revealed that the formulated feed enhanced the vitamins C and E, the result of decreased level of enzymatic antioxidants (SOD, CAT and LPx revealed that these feeds are non-toxic and do not produce any stress to postlarvae. These ingredients can be used as an alternative protein source for sustainable Macrobrachium culture.
DEFF Research Database (Denmark)
Frandsen, Rasmus John Normand; Andersson, Jens A.; Kristensen, Matilde Bylov
2008-01-01
Background: The rapid increase in whole genome fungal sequence information allows large scale functional analyses of target genes. Efficient transformation methods to obtain site-directed gene replacement, targeted over-expression by promoter replacement, in-frame epitope tagging or fusion...
National Research Council Canada - National Science Library
Frandsen, Rasmus J N; Andersson, Jens A; Kristensen, Matilde B; Giese, Henriette
2008-01-01
... markers such as GFP are essential for this process. Construction of vectors for these experiments depends on the directional cloning of two homologous recombination sequences on each side of a selection marker gene...
DEFF Research Database (Denmark)
Boeriis, Morten; van Leeuwen, Theo
2017-01-01
This article revisits the concept of vectors, which, in Kress and van Leeuwen’s Reading Images (2006), plays a crucial role in distinguishing between ‘narrative’, action-oriented processes and ‘conceptual’, state-oriented processes. The use of this concept in image analysis has usually focused...... on the most salient vectors, and this works well, but many images contain a plethora of vectors, which makes their structure quite different from the linguistic transitivity structures with which Kress and van Leeuwen have compared ‘narrative’ images. It can also be asked whether facial expression vectors...... should be taken into account in discussing ‘reactions’, which Kress and van Leeuwen link only to eyeline vectors. Finally, the question can be raised as to whether actions are always realized by vectors. Drawing on a re-reading of Rudolf Arnheim’s account of vectors, these issues are outlined...
Implementation of algorithms based on support vector machine (SVM for electric systems: topic review
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Jefferson Jara Estupiñan
2016-06-01
Full Text Available Objective: To perform a review of implementation of algorithms based on support vectore machine applied to electric systems. Method: A paper search is done mainly on Bibliographic Indexes (BI and Bibliographic Bases with Selection Committee (BBSC about support vector machine. This work shows a qualitative and/or quantitative description about advances and applications in the electrical environment, approaching topics such as: electrical market prediction, demand prediction, non-technical losses (theft, alternative energy source and transformers, among others, in each work the respective citation is done in order to guarantee the copy right and allow to the reader a dynamic movement between the reading and the cited works. Results: A detailed review is done, focused on the searching of implemented algorithms in electric systems and innovating application areas. Conclusion: Support vector machines have a lot of applications due to their multiple benefits, however in the electric energy area; they have not been totally applied, this allow to identify a promising area of researching.
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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.
Study on Immune Relevant Vector Machine Based Intelligent Fault Detection and Diagnosis Algorithm
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Zhong-hua Miao
2013-01-01
Full Text Available An immune relevant vector machine (IRVM based intelligent classification method is proposed by combining the random real-valued negative selection (RRNS algorithm and the relevant vector machine (RVM algorithm. The method proposed is aimed to handle the training problem of missing or incomplete fault sampling data and is inspired by the “self/nonself” recognition principle in the artificial immune systems. The detectors, generated by the RRNS, are treated as the “nonself” training samples and used to train the RVM model together with the “self” training samples. After the training succeeds, the “nonself” detection model, which requires only the “self” training samples, is obtained for the fault detection and diagnosis. It provides a general way solving the problems of this type and can be applied for both fault detection and fault diagnosis. The standard Fisher's Iris flower dataset is used to experimentally testify the proposed method, and the results are compared with those from the support vector data description (SVDD method. Experimental results have shown the validity and practicability of the proposed method.
Optimizing Support Vector Machine Parameters with Genetic Algorithm for Credit Risk Assessment
Manurung, Jonson; Mawengkang, Herman; Zamzami, Elviawaty
2017-12-01
Support vector machine (SVM) is a popular classification method known to have strong generalization capabilities. SVM can solve the problem of classification and linear regression or nonlinear kernel which can be a learning algorithm for the ability of classification and regression. However, SVM also has a weakness that is difficult to determine the optimal parameter value. SVM calculates the best linear separator on the input feature space according to the training data. To classify data which are non-linearly separable, SVM uses kernel tricks to transform the data into a linearly separable data on a higher dimension feature space. The kernel trick using various kinds of kernel functions, such as : linear kernel, polynomial, radial base function (RBF) and sigmoid. Each function has parameters which affect the accuracy of SVM classification. To solve the problem genetic algorithms are proposed to be applied as the optimal parameter value search algorithm thus increasing the best classification accuracy on SVM. Data taken from UCI repository of machine learning database: Australian Credit Approval. The results show that the combination of SVM and genetic algorithms is effective in improving classification accuracy. Genetic algorithms has been shown to be effective in systematically finding optimal kernel parameters for SVM, instead of randomly selected kernel parameters. The best accuracy for data has been upgraded from kernel Linear: 85.12%, polynomial: 81.76%, RBF: 77.22% Sigmoid: 78.70%. However, for bigger data sizes, this method is not practical because it takes a lot of time.
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Jianzhou Wang
2015-01-01
Full Text Available This paper develops an effectively intelligent model to forecast short-term wind speed series. A hybrid forecasting technique is proposed based on recurrence plot (RP and optimized support vector regression (SVR. Wind caused by the interaction of meteorological systems makes itself extremely unsteady and difficult to forecast. To understand the wind system, the wind speed series is analyzed using RP. Then, the SVR model is employed to forecast wind speed, in which the input variables are selected by RP, and two crucial parameters, including the penalties factor and gamma of the kernel function RBF, are optimized by various optimization algorithms. Those optimized algorithms are genetic algorithm (GA, particle swarm optimization algorithm (PSO, and cuckoo optimization algorithm (COA. Finally, the optimized SVR models, including COA-SVR, PSO-SVR, and GA-SVR, are evaluated based on some criteria and a hypothesis test. The experimental results show that (1 analysis of RP reveals that wind speed has short-term predictability on a short-term time scale, (2 the performance of the COA-SVR model is superior to that of the PSO-SVR and GA-SVR methods, especially for the jumping samplings, and (3 the COA-SVR method is statistically robust in multi-step-ahead prediction and can be applied to practical wind farm applications.
An accurate algorithm for estimation of coal reserves based on support vector machine
Energy Technology Data Exchange (ETDEWEB)
Deng, X.; Liu, W.; Wang, R. [Wuhan University, Wuhan (China). School of Geology and Geomatics
2008-09-15
In an effort to improve the limitations of the present methods of estimating coal reserves an accurate algorithm is presented based on the support vector machine model. By building a thick coal and bulk density model from knowledge of drilling data and eliminating the outer points according to the relation between points and polygons, coal reserves were accurately calculated by summing up all the reserves of a small grid. Two examples for different types of coal mine are given and three-dimensional mineral distribution maps are plotted. The examples validate the reliability and advantages of the method proposed. 9 refs., 1 fig., 1 tab.
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Yukai Yao
2015-01-01
Full Text Available We propose an optimized Support Vector Machine classifier, named PMSVM, in which System Normalization, PCA, and Multilevel Grid Search methods are comprehensively considered for data preprocessing and parameters optimization, respectively. The main goals of this study are to improve the classification efficiency and accuracy of SVM. Sensitivity, Specificity, Precision, and ROC curve, and so forth, are adopted to appraise the performances of PMSVM. Experimental results show that PMSVM has relatively better accuracy and remarkable higher efficiency compared with traditional SVM algorithms.
Nanosatellite Attitude Estimation from Vector Measurements Using SVD-Aided UKF Algorithm
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Cilden Demet
2017-03-01
Full Text Available The integrated Singular Value Decomposition (SVD and Unscented Kalman Filter (UKF method can recursively estimate the attitude and attitude rates of a nanosatellite. At first, Wahba’s loss function is minimized using the SVD and the optimal attitude angles are determined on the basis of the magnetometer and Sun sensor measurements. Then, the UKF makes use of the SVD’s attitude estimates as measurement results and provides more accurate attitude information as well as the attitude rate estimates. The elements of “Rotation angle error covariance matrix” calculated for the SVD estimations are used in the UKF as the measurement noise covariance values. The algorithm is compared with the SVD and UKF only methods for estimating the attitude from vector measurements. Possible algorithm switching ideas are discussed especially for the eclipse period, when the Sun sensor measurements are not available.
Optimization of Filter by using Support Vector Regression Machine with Cuckoo Search Algorithm
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M. İlarslan
2014-09-01
Full Text Available Herein, a new methodology using a 3D Electromagnetic (EM simulator-based Support Vector Regression Machine (SVRM models of base elements is presented for band-pass filter (BPF design. SVRM models of elements, which are as fast as analytical equations and as accurate as a 3D EM simulator, are employed in a simple and efficient Cuckoo Search Algorithm (CSA to optimize an ultra-wideband (UWB microstrip BPF. CSA performance is verified by comparing it with other Meta-Heuristics such as Genetic Algorithm (GA and Particle Swarm Optimization (PSO. As an example of the proposed design methodology, an UWB BPF that operates between the frequencies of 3.1 GHz and 10.6 GHz is designed, fabricated and measured. The simulation and measurement results indicate in conclusion the superior performance of this optimization methodology in terms of improved filter response characteristics like return loss, insertion loss, harmonic suppression and group delay.
Nekrasov, A.; Hoogeboom, P.
2005-01-01
A Ka-band backscatter model and an algorithm for measurement of the wind speed and direction over the sea surface by a frequency-modulated continous-wave radar demonstrator system operated in scatterometer mode have been developed. To evaluate the proposed algorithm, a simulation of the wind vector
Nishizuka, N.; Sugiura, K.; Kubo, Y.; Den, M.; Watari, S.; Ishii, M.
2017-02-01
We developed a flare prediction model using machine learning, which is optimized to predict the maximum class of flares occurring in the following 24 hr. Machine learning is used to devise algorithms that can learn from and make decisions on a huge amount of data. We used solar observation data during the period 2010-2015, such as vector magnetograms, ultraviolet (UV) emission, and soft X-ray emission taken by the Solar Dynamics Observatory and the Geostationary Operational Environmental Satellite. We detected active regions (ARs) from the full-disk magnetogram, from which ˜60 features were extracted with their time differentials, including magnetic neutral lines, the current helicity, the UV brightening, and the flare history. After standardizing the feature database, we fully shuffled and randomly separated it into two for training and testing. To investigate which algorithm is best for flare prediction, we compared three machine-learning algorithms: the support vector machine, k-nearest neighbors (k-NN), and extremely randomized trees. The prediction score, the true skill statistic, was higher than 0.9 with a fully shuffled data set, which is higher than that for human forecasts. It was found that k-NN has the highest performance among the three algorithms. The ranking of the feature importance showed that previous flare activity is most effective, followed by the length of magnetic neutral lines, the unsigned magnetic flux, the area of UV brightening, and the time differentials of features over 24 hr, all of which are strongly correlated with the flux emergence dynamics in an AR.
A Non-static Data Layout Enhancing Parallelism and Vectorization in Sparse Grid Algorithms
Buse, Gerrit
2012-06-01
The name sparse grids denotes a highly space-efficient, grid-based numerical technique to approximate high-dimensional functions. Although employed in a broad spectrum of applications from different fields, there have only been few tries to use it in real time visualization (e.g. [1]), due to complex data structures and long algorithm runtime. In this work we present a novel approach inspired by principles of I/0-efficient algorithms. Locally applied coefficient permutations lead to improved cache performance and facilitate the use of vector registers for our sparse grid benchmark problem hierarchization. Based on the compact data structure proposed for regular sparse grids in [2], we developed a new algorithm that outperforms existing implementations on modern multi-core systems by a factor of 37 for a grid size of 127 million points. For larger problems the speedup is even increasing, and with execution times below 1 s, sparse grids are well-suited for visualization applications. Furthermore, we point out how a broad class of sparse grid algorithms can benefit from our approach. © 2012 IEEE.
SNPs selection using support vector regression and genetic algorithms in GWAS.
de Oliveira, Fabrízzio Condé; Borges, Carlos Cristiano Hasenclever; Almeida, Fernanda Nascimento; e Silva, Fabyano Fonseca; da Silva Verneque, Rui; da Silva, Marcos Vinicius G B; Arbex, Wagner
2014-01-01
This paper proposes a new methodology to simultaneously select the most relevant SNPs markers for the characterization of any measurable phenotype described by a continuous variable using Support Vector Regression with Pearson Universal kernel as fitness function of a binary genetic algorithm. The proposed methodology is multi-attribute towards considering several markers simultaneously to explain the phenotype and is based jointly on statistical tools, machine learning and computational intelligence. The suggested method has shown potential in the simulated database 1, with additive effects only, and real database. In this simulated database, with a total of 1,000 markers, and 7 with major effect on the phenotype and the other 993 SNPs representing the noise, the method identified 21 markers. Of this total, 5 are relevant SNPs between the 7 but 16 are false positives. In real database, initially with 50,752 SNPs, we have reduced to 3,073 markers, increasing the accuracy of the model. In the simulated database 2, with additive effects and interactions (epistasis), the proposed method matched to the methodology most commonly used in GWAS. The method suggested in this paper demonstrates the effectiveness in explaining the real phenotype (PTA for milk), because with the application of the wrapper based on genetic algorithm and Support Vector Regression with Pearson Universal, many redundant markers were eliminated, increasing the prediction and accuracy of the model on the real database without quality control filters. The PUK demonstrated that it can replicate the performance of linear and RBF kernels.
Ilhan, Ilhan; Tezel, Gülay
2013-04-01
SNPs (Single Nucleotide Polymorphisms) include millions of changes in human genome, and therefore, are promising tools for disease-gene association studies. However, this kind of studies is constrained by the high expense of genotyping millions of SNPs. For this reason, it is required to obtain a suitable subset of SNPs to accurately represent the rest of SNPs. For this purpose, many methods have been developed to select a convenient subset of tag SNPs, but all of them only provide low prediction accuracy. In the present study, a brand new method is developed and introduced as GA-SVM with parameter optimization. This method benefits from support vector machine (SVM) and genetic algorithm (GA) to predict SNPs and to select tag SNPs, respectively. Furthermore, it also uses particle swarm optimization (PSO) algorithm to optimize C and γ parameters of support vector machine. It is experimentally tested on a wide range of datasets, and the obtained results demonstrate that this method can provide better prediction accuracy in identifying tag SNPs compared to other methods at present. Copyright © 2012 Elsevier Inc. All rights reserved.
Evaluation of Chinese Calligraphy by Using DBSC Vectorization and ICP Algorithm
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Mengdi Wang
2016-01-01
Full Text Available Chinese calligraphy is a charismatic ancient art form with high artistic value in Chinese culture. Virtual calligraphy learning system is a research hotspot in recent years. In such system, a judging mechanism for user’s practice result is quite important. Sometimes, user’s handwritten character is not that standard, the size and position are not fixed, and the whole character may be even askew, which brings difficulty for its evaluation. In this paper, we propose an approach by using DBSCs (disk B-spline curves vectorization and ICP (iterative closest point algorithm, which cannot only evaluate a calligraphic character without knowing what it is, but also deal with the above problems commendably. Firstly we find the promising candidate characters from the database according to the angular difference relations as quickly as possible. Then we check these vectorized candidates by using ICP algorithm based upon the skeleton, hence finding out the best matching character. Finally a comprehensive evaluation involving global (the whole character and local (strokes similarities is implemented, and a final composited evaluation score can be worked out.
Zhang, Xianghong; Tang, Sanyi; Cheke, Robert A
2015-11-01
Dengue fever is increasing in importance in the tropics and subtropics. Endosymbiotic Wolbachia bacteria as novel control methods can reduce the ability of virus transmission. So, many mosquitoes infected with Wolbachia are released in some countries so that strategies for population replacement can be fulfilled. However, not all of these field trails are successful, for example, releases on Tri Nguyen Island, Vietnam in 2013 failed. Thus, we evaluated a series of relevant issues such as (a) why do some releases fail? (b) What affects the success of population replacement? And (c) Whether or not augmentation can block the dengue diseases in field trials. If not, how we can success be achieved? Models with and without augmentation, incorporating the effects of cytoplasmic incompatibility (CI) and fitness effects are proposed to describe the spread of Wolbachia in mosquito populations. Stability analysis revealed that backward bifurcations and multiple attractors may exist, which indicate that initial quantities of infected and uninfected mosquitoes, augmentation methods (timing, quantity, order and frequency) may affect the success of the strategies. The results show that successful population replacement will rely on selection of suitable strains of Wolbachia and careful design of augmentation methods. Copyright © 2015 Elsevier Inc. All rights reserved.
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Jin-peng Liu
2017-07-01
Full Text Available Short-term power load forecasting is an important basis for the operation of integrated energy system, and the accuracy of load forecasting directly affects the economy of system operation. To improve the forecasting accuracy, this paper proposes a load forecasting system based on wavelet least square support vector machine and sperm whale algorithm. Firstly, the methods of discrete wavelet transform and inconsistency rate model (DWT-IR are used to select the optimal features, which aims to reduce the redundancy of input vectors. Secondly, the kernel function of least square support vector machine LSSVM is replaced by wavelet kernel function for improving the nonlinear mapping ability of LSSVM. Lastly, the parameters of W-LSSVM are optimized by sperm whale algorithm, and the short-term load forecasting method of W-LSSVM-SWA is established. Additionally, the example verification results show that the proposed model outperforms other alternative methods and has a strong effectiveness and feasibility in short-term power load forecasting.
On efficient randomized algorithms for finding the PageRank vector
Gasnikov, A. V.; Dmitriev, D. Yu.
2015-03-01
Two randomized methods are considered for finding the PageRank vector; in other words, the solution of the system p T = p T P with a stochastic n × n matrix P, where n ˜ 107-109, is sought (in the class of probability distributions) with accuracy ɛ: ɛ ≫ n -1. Thus, the possibility of brute-force multiplication of P by the column is ruled out in the case of dense objects. The first method is based on the idea of Markov chain Monte Carlo algorithms. This approach is efficient when the iterative process p {/t+1 T} = p {/t T} P quickly reaches a steady state. Additionally, it takes into account another specific feature of P, namely, the nonzero off-diagonal elements of P are equal in rows (this property is used to organize a random walk over the graph with the matrix P). Based on modern concentration-of-measure inequalities, new bounds for the running time of this method are presented that take into account the specific features of P. In the second method, the search for a ranking vector is reduced to finding the equilibrium in the antagonistic matrix game where S n (1) is a unit simplex in ℝ n and I is the identity matrix. The arising problem is solved by applying a slightly modified Grigoriadis-Khachiyan algorithm (1995). This technique, like the Nazin-Polyak method (2009), is a randomized version of Nemirovski's mirror descent method. The difference is that randomization in the Grigoriadis-Khachiyan algorithm is used when the gradient is projected onto the simplex rather than when the stochastic gradient is computed. For sparse matrices P, the method proposed yields noticeably better results.
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Luo Wei
2017-01-01
Full Text Available Power transformer is one of the most important equipment in power system. In order to predict the potential fault of power transformer and identify the fault types correctly, we proposed a transformer fault intelligent diagnosis model based on chemical reaction optimization (CRO algorithm and relevance vector machine(RVM. RVM is a powerful machine learning method, which can solve nonlinear, high-dimensional classification problems with a limited number of samples. CRO algorithm has well global optimization and simple calculation, so it is suitable to solve parameter optimization problems. In this paper, firstly, a multi-layer RVM classification model was built by binary tree recognition strategy. Secondly, CRO algorithm was adopted to optimize the kernel function parameters which could enhance the performance of RVM classifiers. Compared with IEC three-ratio method and the RVM model, the CRO-RVM model not only overcomes the coding defect problem of IEC three-ratio method, but also has higher classification accuracy than the RVM model. Finally, the new method was applied to analyze a transformer fault case, Its predicted result accord well with the real situation. The research provides a practical method for transformer fault intelligent diagnosis and prediction.
A Support Vector Machine Hydrometeor Classification Algorithm for Dual-Polarization Radar
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Nicoletta Roberto
2017-07-01
Full Text Available An algorithm based on a support vector machine (SVM is proposed for hydrometeor classification. The training phase is driven by the output of a fuzzy logic hydrometeor classification algorithm, i.e., the most popular approach for hydrometer classification algorithms used for ground-based weather radar. The performance of SVM is evaluated by resorting to a weather scenario, generated by a weather model; the corresponding radar measurements are obtained by simulation and by comparing results of SVM classification with those obtained by a fuzzy logic classifier. Results based on the weather model and simulations show a higher accuracy of the SVM classification. Objective comparison of the two classifiers applied to real radar data shows that SVM classification maps are spatially more homogenous (textural indices, energy, and homogeneity increases by 21% and 12% respectively and do not present non-classified data. The improvements found by SVM classifier, even though it is applied pixel-by-pixel, can be attributed to its ability to learn from the entire hyperspace of radar measurements and to the accurate training. The reliability of results and higher computing performance make SVM attractive for some challenging tasks such as its implementation in Decision Support Systems for helping pilots to make optimal decisions about changes inthe flight route caused by unexpected adverse weather.
Singh, Sartajvir; Talwar, Rajneesh
2018-02-01
Detection of snow cover changes is vital for avalanche hazard analysis and flood flashes that arise due to variation in temperature. Hence, multitemporal change detection is one of the practical mean to estimate the snow cover changes over larger area using remotely sensed data. There have been some previous studies that examined how accuracy of change detection analysis is affected by different topography effects over Northwestern Indian Himalayas. The present work emphases on the intercomparison of different topography effects on discrimination performance of fuzzy based change vector analysis (FCVA) as change detection algorithm that includes extraction of change-magnitude and change-direction from a specific pixel belongs multiple or partial membership. The qualitative and quantitative analysis of the proposed FCVA algorithm is performed under topographic conditions and topographic correction conditions. The experimental outcomes confirmed that in change category discrimination procedure, FCVA with topographic correction achieved 86.8% overall accuracy and 4.8% decay (82% of overall accuracy) is found in FCVA without topographic correction. This study suggests that by incorporating the topographic correction model over mountainous region satellite imagery, performance of FCVA algorithm can be significantly improved up to great extent in terms of determining actual change categories.
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B Vinoth Kumar
2017-07-01
Full Text Available Quantization Table is responsible for compression / quality trade-off in baseline Joint Photographic Experts Group (JPEG algorithm and therefore it is viewed as an optimization problem. In the literature, it has been found that Classical Differential Evolution (CDE is a promising algorithm to generate the optimal quantization table. However, the searching capability of CDE could be limited due to generation of single trial vector in an iteration which in turn reduces the convergence speed. This paper studies the performance of CDE by employing multiple trial vectors in a single iteration. An extensive performance analysis has been made between CDE and CDE with multiple trial vectors in terms of Optimization process, accuracy, convergence speed and reliability. The analysis report reveals that CDE with multiple trial vectors improves the convergence speed of CDE and the same is confirmed using a statistical hypothesis test (t-test.
Tan, F; Feng, X; Fang, Z; Li, M; Guo, Y; Jiang, L
2007-11-01
Mitochondria are essential cell organelles of eukaryotes. Hence, it is vitally important to develop an automated and reliable method for timely identification of novel mitochondrial proteins. In this study, mitochondrial proteins were encoded by dipeptide composition technology; then, the genetic algorithm-partial least square (GA-PLS) method was used to evaluate the dipeptide composition elements which are more important in recognizing mitochondrial proteins; further, these selected dipeptide composition elements were applied to support vector machine (SVM)-based classifiers to predict the mitochondrial proteins. All the models were trained and validated by the jackknife cross-validation test. The prediction accuracy is 85%, suggesting that it performs reasonably well in predicting the mitochondrial proteins. Our results strongly imply that not all the dipeptide compositions are informative and indispensable for predicting proteins. The source code of MATLAB and the dataset are available on request under liml@scu.edu.cn.
Automatic ultrasonic breast lesions detection using support vector machine based algorithm
Yeh, Chih-Kuang; Miao, Shan-Jung; Fan, Wei-Che; Chen, Yung-Sheng
2007-03-01
It is difficult to automatically detect tumors and extract lesion boundaries in ultrasound images due to the variance in shape, the interference from speckle noise, and the low contrast between objects and background. The enhancement of ultrasonic image becomes a significant task before performing lesion classification, which was usually done with manual delineation of the tumor boundaries in the previous works. In this study, a linear support vector machine (SVM) based algorithm is proposed for ultrasound breast image training and classification. Then a disk expansion algorithm is applied for automatically detecting lesions boundary. A set of sub-images including smooth and irregular boundaries in tumor objects and those in speckle-noised background are trained by the SVM algorithm to produce an optimal classification function. Based on this classification model, each pixel within an ultrasound image is classified into either object or background oriented pixel. This enhanced binary image can highlight the object and suppress the speckle noise; and it can be regarded as degraded paint character (DPC) image containing closure noise, which is well known in perceptual organization of psychology. An effective scheme of removing closure noise using iterative disk expansion method has been successfully demonstrated in our previous works. The boundary detection of ultrasonic breast lesions can be further equivalent to the removal of speckle noise. By applying the disk expansion method to the binary image, we can obtain a significant radius-based image where the radius for each pixel represents the corresponding disk covering the specific object information. Finally, a signal transmission process is used for searching the complete breast lesion region and thus the desired lesion boundary can be effectively and automatically determined. Our algorithm can be performed iteratively until all desired objects are detected. Simulations and clinical images were introduced to
A BioBrick™-Compatible Vector for Allelic Replacement Using the XylE Gene as Selection Marker.
Casanova, Michela; Pasotti, Lorenzo; Zucca, Susanna; Politi, Nicolò; Massaiu, Ilaria; Calvio, Cinzia; Cusella De Angelis, Maria Gabriella; Magni, Paolo
2016-01-01
Circular plasmid-mediated homologous recombination is commonly used for marker-less allelic replacement, exploiting the endogenous recombination machinery of the host. Common limitations of existing methods include high false positive rates due to mutations in counter-selection genes, and limited applicability to specific strains or growth media. Finally, solutions compatible with physical standards, such as the BioBrick™, are not currently available, although they proved to be successful in the design of other replicative or integrative plasmids. We illustrate pBBknock, a novel BioBrick™-compatible vector for allelic replacement in Escherichia coli. It includes a temperature-sensitive replication origin and enables marker-less genome engineering via two homologous recombination events. Chloramphenicol resistance allows positive selection of clones after the first event, whereas a colorimetric assay based on the xylE gene provides a simple way to screen clones in which the second recombination event occurs. Here we successfully use pBBknock to delete the lactate dehydrogenase gene in E. coli W, a popular host used in metabolic engineering. Compared with other plasmid-based solutions, pBBknock has a broader application range, not being limited to specific strains or media. We expect that pBBknock will represent a versatile solution both for practitioners, also among the iGEM competition teams, and for research laboratories that use BioBrick™-based assembly procedures.
Morrell, F. R.; Bailey, M. L.; Motyka, P. R.
1988-01-01
Flight test results of a vector-based fault-tolerant algorithm for a redundant strapdown inertial measurement unit are presented. Because the inertial sensors provide flight-critical information for flight control and navigation, failure detection and isolation is developed in terms of a multi-level structure. Threshold compensation techniques for gyros and accelerometers, developed to enhance the sensitivity of the failure detection process to low-level failures, are presented. Four flight tests, conducted in a commercial transport type environment, were used to determine the ability of the failure detection and isolation algorithm to detect failure signals, such a hard-over, null, or bias shifts. The algorithm provided timely detection and correct isolation of flight control- and low-level failures. The flight tests of the vector-based algorithm demonstrated its capability to provide false alarm free dual fail-operational performance for the skewed array of inertial sensors.
Drought sensitivity mapping using two one-class support vector machine algorithms
Roodposhti, Majid Shadman; Safarrad, Taher; Shahabi, Himan
2017-09-01
This paper investigates the use of standardised precipitation index (SPI) and the enhanced vegetation index (EVI) as indicators of soil moisture. On the other hand, we attempted to produce a drought sensitivity map (DSM) for vegetation cover using two one-class support vector machine (OC-SVM) algorithms. In order to achieve promising results a combination of both 30 years statistical data (1978 to 2008) of synoptic stations and 10 years MODIS imagery archive (2001 to 2010) are used within the boundary of Kermanshah province, Iran. The synoptic data and MODIS imagery were used for extraction of SPI and EVI, respectively. The objective is, therefore, to explore meaningful changes of vegetation in response to drought anomalies, in the first step, and further extraction of reliable spatio-temporal patterns of drought sensitivity using efficient classification technique and spatial criteria, in the next step. To this end, four main criteria including elevation, slope, aspect and geomorphic classes are considered for DSM using two OC-SVM algorithms. Results of the analysis showed distinct spatio-temporal patterns of drought impacts on vegetation cover. The receiver operating characteristics (ROC) curves for the proposed DSM was used along with the simple overlay technique for accuracy assessment phase and the area under curve (AUC = 0.80) value was calculated.
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Xiaochen Zhang
2017-01-01
Full Text Available To diagnose rotating machinery fault for imbalanced data, a method based on fast clustering algorithm (FCA and support vector machine (SVM was proposed. Combined with variational mode decomposition (VMD and principal component analysis (PCA, sensitive features of the rotating machinery fault were obtained and constituted the imbalanced fault sample set. Next, a fast clustering algorithm was adopted to reduce the number of the majority data from the imbalanced fault sample set. Consequently, the balanced fault sample set consisted of the clustered data and the minority data from the imbalanced fault sample set. After that, SVM was trained with the balanced fault sample set and tested with the imbalanced fault sample set so the fault diagnosis model of the rotating machinery could be obtained. Finally, the gearbox fault data set and the rolling bearing fault data set were adopted to test the fault diagnosis model. The experimental results showed that the fault diagnosis model could effectively diagnose the rotating machinery fault for imbalanced data.
Sokolov, Sergey V.; Shcherban', I. V.; Shcherban', O. G.
2007-01-01
Identification algorithm of the right part of a dynamic system described with non-linear vector stochastic equation is considered. The main benefit of the suggested approach is the possibility of forming in real time and in explicit form the searched function’s right part approximate estimation of the object’s differential equations system.
Zhao, Li; Chen, Chunxia; Li, Bei; Dong, Li; Guo, Yingqiang; Xiao, Xijun; Zhang, Eryong; Qin, Li
2014-01-01
To study the performance of pharmacogenetics-based warfarin dosing algorithms in the initial and the stable warfarin treatment phases in a cohort of Han-Chinese patients undertaking mechanic heart valve replacement. We searched PubMed, Chinese National Knowledge Infrastructure and Wanfang databases for selecting pharmacogenetics-based warfarin dosing models. Patients with mechanic heart valve replacement were consecutively recruited between March 2012 and July 2012. The predicted warfarin dose of each patient was calculated and compared with the observed initial and stable warfarin doses. The percentage of patients whose predicted dose fell within 20% of their actual therapeutic dose (percentage within 20%), and the mean absolute error (MAE) were utilized to evaluate the predictive accuracy of all the selected algorithms. A total of 8 algorithms including Du, Huang, Miao, Wei, Zhang, Lou, Gage, and International Warfarin Pharmacogenetics Consortium (IWPC) model, were tested in 181 patients. The MAE of the Gage, IWPC and 6 Han-Chinese pharmacogenetics-based warfarin dosing algorithms was less than 0.6 mg/day in accuracy and the percentage within 20% exceeded 45% in all of the selected models in both the initial and the stable treatment stages. When patients were stratified according to the warfarin dose range, all of the equations demonstrated better performance in the ideal-dose range (1.88-4.38 mg/day) than the low-dose range (mechanic heart valve replacement.
Predicting Solar Flares Using SDO/HMI Vector Magnetic Data Product and Random Forest Algorithm
Liu, Chang; Deng, Na; Wang, Jason; Wang, Haimin
2017-08-01
Adverse space weather effects can often be traced to solar flares, prediction of which has drawn significant research interests. Many previous forecasting studies used physical parameters derived from photospheric line-of-sight field or ground-based vector field observations. The Helioseismic and Magnetic Imager (HMI) on board the Solar Dynamics Observatory produces full-disk vector magnetograms with continuous high-cadence, while flare prediction efforts utilizing this unprecedented data source are still limited. Here we report results of flare prediction using physical parameters provided by the Space-weather HMI Active Region Patches (SHARP) and related data products. We survey X-ray flares occurred from 2010 May to 2016 December, and categorize their source regions into four classes (B, C, M, and X) according to the maximum GOES magnitude of flares they generated. We then retrieve SHARP related parameters for each selected region at the beginning of its flare date to build a database. Finally, we train a machine-learning algorithm, called random forest (RF), to predict the occurrence of a certain class of flares in a given active region within 24 hours, evaluate the classifier performance using the 10-fold cross validation scheme, and characterize the results using standard performace metrics. Compared to previous works, our experiments indicate that using the HMI parameters and RF is a valid method for flare forecasting with fairly reasonable prediction performance. We also find that the total unsigned quantities of vertical current, current helicity, and flux near polarity inversion line are among the most important parameters for classifying flaring regions into different classes.
Wu, Peilin; Zhang, Qunying; Fei, Chunjiao; Fang, Guangyou
2017-04-01
Aeromagnetic gradients are typically measured by optically pumped magnetometers mounted on an aircraft. Any aircraft, particularly helicopters, produces significant levels of magnetic interference. Therefore, aeromagnetic compensation is essential, and least square (LS) is the conventional method used for reducing interference levels. However, the LSs approach to solving the aeromagnetic interference model has a few difficulties, one of which is in handling multicollinearity. Therefore, we propose an aeromagnetic gradient compensation method, specifically targeted for helicopter use but applicable on any airborne platform, which is based on the ɛ-support vector regression algorithm. The structural risk minimization criterion intrinsic to the method avoids multicollinearity altogether. Local aeromagnetic anomalies can be retained, and platform-generated fields are suppressed simultaneously by constructing an appropriate loss function and kernel function. The method was tested using an unmanned helicopter and obtained improvement ratios of 12.7 and 3.5 in the vertical and horizontal gradient data, respectively. Both of these values are probably better than those that would have been obtained from the conventional method applied to the same data, had it been possible to do so in a suitable comparative context. The validity of the proposed method is demonstrated by the experimental result.
Cognitive Development Optimization Algorithm Based Support Vector Machines for Determining Diabetes
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Utku Kose
2016-03-01
Full Text Available The definition, diagnosis and classification of Diabetes Mellitus and its complications are very important. First of all, the World Health Organization (WHO and other societies, as well as scientists have done lots of studies regarding this subject. One of the most important research interests of this subject is the computer supported decision systems for diagnosing diabetes. In such systems, Artificial Intelligence techniques are often used for several disease diagnostics to streamline the diagnostic process in daily routine and avoid misdiagnosis. In this study, a diabetes diagnosis system, which is formed via both Support Vector Machines (SVM and Cognitive Development Optimization Algorithm (CoDOA has been proposed. Along the training of SVM, CoDOA was used for determining the sigma parameter of the Gauss (RBF kernel function, and eventually, a classification process was made over the diabetes data set, which is related to Pima Indians. The proposed approach offers an alternative solution to the field of Artificial Intelligence-based diabetes diagnosis, and contributes to the related literature on diagnosis processes.
Application of genetic algorithm and support vector machine for probing nanoflare parameters
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H Safari
2012-12-01
Full Text Available Nanoflares are the small impulsive sudden energy releases, due to the explosion of solar background. Thus, determination of their energies and distributions is important . Recent observations and simulation models have shown that the frequency of their energies follows power-law. According to Parker hypothesis, if these exponents are greater than critical value 2, the contributions of nanoflares to the heating of solar corona is more significan. Here, the extreme ultra-violet (EUV emission radiances of corona observed by STEREO/EUVI taken on 11 and 12 Jun 2007 are analyzed. To simulate the EUV irradiance, a simple nanoflare model with three key parameters (the flare rate, the flare duration time, and the exponent of the power- law is applied. Based on genetic algorithm, the lengths of data points are reduced. The resultant light curves are fed to the Support Vector Machine (SVM classifier. The produced light curves of quiet and active regions of the solar corona are classified and the set of power- law exponent, the flare duration time and the flare rate parameters are obtained. The flare duration time is estimated about 80 minutes. The power-low exponents range about 2.5-2.7.
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Zhongwei Li
Full Text Available Welan gum is a kind of novel microbial polysaccharide, which is widely produced during the process of microbial growth and metabolism in different external conditions. Welan gum can be used as the thickener, suspending agent, emulsifier, stabilizer, lubricant, film-forming agent and adhesive usage in agriculture. In recent years, finding optimal experimental conditions to maximize the production is paid growing attentions. In this work, a hybrid computational method is proposed to optimize experimental conditions for producing Welan gum with data collected from experiments records. Support Vector Regression (SVR is used to model the relationship between Welan gum production and experimental conditions, and then adaptive Genetic Algorithm (AGA, for short is applied to search optimized experimental conditions. As results, a mathematic model of predicting production of Welan gum from experimental conditions is obtained, which achieves accuracy rate 88.36%. As well, a class of optimized experimental conditions is predicted for producing Welan gum 31.65g/L. Comparing the best result in chemical experiment 30.63g/L, the predicted production improves it by 3.3%. The results provide potential optimal experimental conditions to improve the production of Welan gum.
Li, Zhongwei; Yuan, Xiang; Cui, Xuerong; Liu, Xin; Wang, Leiquan; Zhang, Weishan; Lu, Qinghua; Zhu, Hu
2017-01-01
Welan gum is a kind of novel microbial polysaccharide, which is widely produced during the process of microbial growth and metabolism in different external conditions. Welan gum can be used as the thickener, suspending agent, emulsifier, stabilizer, lubricant, film-forming agent and adhesive usage in agriculture. In recent years, finding optimal experimental conditions to maximize the production is paid growing attentions. In this work, a hybrid computational method is proposed to optimize experimental conditions for producing Welan gum with data collected from experiments records. Support Vector Regression (SVR) is used to model the relationship between Welan gum production and experimental conditions, and then adaptive Genetic Algorithm (AGA, for short) is applied to search optimized experimental conditions. As results, a mathematic model of predicting production of Welan gum from experimental conditions is obtained, which achieves accuracy rate 88.36%. As well, a class of optimized experimental conditions is predicted for producing Welan gum 31.65g/L. Comparing the best result in chemical experiment 30.63g/L, the predicted production improves it by 3.3%. The results provide potential optimal experimental conditions to improve the production of Welan gum.
Takeuchi, Keigo
2012-01-01
User selection (US) with Zero-forcing beamforming (ZF-BF) is considered in fast fading Gaussian vector broadcast channels (VBCs) with perfect channel state information (CSI) at the transmitter. A novel criterion for US is proposed, which depends on both CSI and the data symbols, while the conventional criteria only depend on CSI. Since the optimization of US based on the proposed criterion is infeasible, a greedy algorithm of data-dependent US is proposed to perform the optimization approximately. An overhead issue arises in fast fading channels: On every update of US, the transmitter may inform each user whether he/she has been selected, using a certain fraction of resources. This overhead results in a significant rate loss for fast fading channels. In order to circumvent this overhead issue, iterative detection and decoding schemes are derived on the basis of belief propagation (BP). The proposed iterative schemes require no information about whether each user has been selected. The proposed US scheme is co...
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Yan Hong Chen
2016-01-01
Full Text Available This paper proposes a new electric load forecasting model by hybridizing the fuzzy time series (FTS and global harmony search algorithm (GHSA with least squares support vector machines (LSSVM, namely GHSA-FTS-LSSVM model. Firstly, the fuzzy c-means clustering (FCS algorithm is used to calculate the clustering center of each cluster. Secondly, the LSSVM is applied to model the resultant series, which is optimized by GHSA. Finally, a real-world example is adopted to test the performance of the proposed model. In this investigation, the proposed model is verified using experimental datasets from the Guangdong Province Industrial Development Database, and results are compared against autoregressive integrated moving average (ARIMA model and other algorithms hybridized with LSSVM including genetic algorithm (GA, particle swarm optimization (PSO, harmony search, and so on. The forecasting results indicate that the proposed GHSA-FTS-LSSVM model effectively generates more accurate predictive results.
Lennington, R. K.; Johnson, J. K.
1979-01-01
An efficient procedure which clusters data using a completely unsupervised clustering algorithm and then uses labeled pixels to label the resulting clusters or perform a stratified estimate using the clusters as strata is developed. Three clustering algorithms, CLASSY, AMOEBA, and ISOCLS, are compared for efficiency. Three stratified estimation schemes and three labeling schemes are also considered and compared.
Predicting Solar Flares Using SDO/HMI Vector Magnetic Data Products and the Random Forest Algorithm
Liu, Chang; Deng, Na; Wang, Jason T. L.; Wang, Haimin
2017-07-01
Adverse space-weather effects can often be traced to solar flares, the prediction of which has drawn significant research interests. The Helioseismic and Magnetic Imager (HMI) produces full-disk vector magnetograms with continuous high cadence, while flare prediction efforts utilizing this unprecedented data source are still limited. Here we report results of flare prediction using physical parameters provided by the Space-weather HMI Active Region Patches (SHARP) and related data products. We survey X-ray flares that occurred from 2010 May to 2016 December and categorize their source regions into four classes (B, C, M, and X) according to the maximum GOES magnitude of flares they generated. We then retrieve SHARP-related parameters for each selected region at the beginning of its flare date to build a database. Finally, we train a machine-learning algorithm, called random forest (RF), to predict the occurrence of a certain class of flares in a given active region within 24 hr, evaluate the classifier performance using the 10-fold cross-validation scheme, and characterize the results using standard performance metrics. Compared to previous works, our experiments indicate that using the HMI parameters and RF is a valid method for flare forecasting with fairly reasonable prediction performance. To our knowledge, this is the first time that RF has been used to make multiclass predictions of solar flares. We also find that the total unsigned quantities of vertical current, current helicity, and flux near the polarity inversion line are among the most important parameters for classifying flaring regions into different classes.
Comparison of strapdown inertial navigation algorithm based on rotation vector and dual quaternion
National Research Council Canada - National Science Library
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...
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S.K. Lahiri
2009-09-01
Full Text Available Soft sensors have been widely used in the industrial process control to improve the quality of the product and assure safety in the production. The core of a soft sensor is to construct a soft sensing model. This paper introduces support vector regression (SVR, a new powerful machine learning methodbased on a statistical learning theory (SLT into soft sensor modeling and proposes a new soft sensing modeling method based on SVR. This paper presents an artificial intelligence based hybrid soft sensormodeling and optimization strategies, namely support vector regression – genetic algorithm (SVR-GA for modeling and optimization of mono ethylene glycol (MEG quality variable in a commercial glycol plant. In the SVR-GA approach, a support vector regression model is constructed for correlating the process data comprising values of operating and performance variables. Next, model inputs describing the process operating variables are optimized using genetic algorithm with a view to maximize the process performance. The SVR-GA is a new strategy for soft sensor modeling and optimization. The major advantage of the strategies is that modeling and optimization can be conducted exclusively from the historic process data wherein the detailed knowledge of process phenomenology (reaction mechanism, kinetics etc. is not required. Using SVR-GA strategy, a number of sets of optimized operating conditions were found. The optimized solutions, when verified in an actual plant, resulted in a significant improvement in the quality.
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Bao Wang
2012-11-01
Full Text Available The accuracy of annual electric load forecasting plays an important role in the economic and social benefits of electric power systems. The least squares support vector machine (LSSVM has been proven to offer strong potential in forecasting issues, particularly by employing an appropriate meta-heuristic algorithm to determine the values of its two parameters. However, these meta-heuristic algorithms have the drawbacks of being hard to understand and reaching the global optimal solution slowly. As a novel meta-heuristic and evolutionary algorithm, the fruit fly optimization algorithm (FOA has the advantages of being easy to understand and fast convergence to the global optimal solution. Therefore, to improve the forecasting performance, this paper proposes a LSSVM-based annual electric load forecasting model that uses FOA to automatically determine the appropriate values of the two parameters for the LSSVM model. By taking the annual electricity consumption of China as an instance, the computational result shows that the LSSVM combined with FOA (LSSVM-FOA outperforms other alternative methods, namely single LSSVM, LSSVM combined with coupled simulated annealing algorithm (LSSVM-CSA, generalized regression neural network (GRNN and regression model.
Sweeney, Elizabeth M; Vogelstein, Joshua T; Cuzzocreo, Jennifer L; Calabresi, Peter A; Reich, Daniel S; Crainiceanu, Ciprian M; Shinohara, Russell T
2014-01-01
Machine learning is a popular method for mining and analyzing large collections of medical data. We focus on a particular problem from medical research, supervised multiple sclerosis (MS) lesion segmentation in structural magnetic resonance imaging (MRI). We examine the extent to which the choice of machine learning or classification algorithm and feature extraction function impacts the performance of lesion segmentation methods. As quantitative measures derived from structural MRI are important clinical tools for research into the pathophysiology and natural history of MS, the development of automated lesion segmentation methods is an active research field. Yet, little is known about what drives performance of these methods. We evaluate the performance of automated MS lesion segmentation methods, which consist of a supervised classification algorithm composed with a feature extraction function. These feature extraction functions act on the observed T1-weighted (T1-w), T2-weighted (T2-w) and fluid-attenuated inversion recovery (FLAIR) MRI voxel intensities. Each MRI study has a manual lesion segmentation that we use to train and validate the supervised classification algorithms. Our main finding is that the differences in predictive performance are due more to differences in the feature vectors, rather than the machine learning or classification algorithms. Features that incorporate information from neighboring voxels in the brain were found to increase performance substantially. For lesion segmentation, we conclude that it is better to use simple, interpretable, and fast algorithms, such as logistic regression, linear discriminant analysis, and quadratic discriminant analysis, and to develop the features to improve performance.
Wu, Na; Qu, Zhiyu; Si, Weijian; Jiao, Shuhong
2016-12-13
In array signal processing systems, the direction of arrival (DOA) and polarization of signals based on uniform linear or rectangular sensor arrays are generally obtained by rotational invariance techniques (ESPRIT). However, since the ESPRIT algorithm relies on the rotational invariant structure of the received data, it cannot be applied to electromagnetic vector sensor arrays (EVSAs) featuring uniform circular patterns. To overcome this limitation, a fourth-order cumulant-based ESPRIT algorithm is proposed in this paper, for joint estimation of DOA and polarization based on a uniform circular EVSA. The proposed algorithm utilizes the fourth-order cumulant to obtain a virtual extended array of a uniform circular EVSA, from which the pairs of rotation invariant sub-arrays are obtained. The ESPRIT algorithm and parameter pair matching are then utilized to estimate the DOA and polarization of the incident signals. The closed-form parameter estimation algorithm can effectively reduce the computational complexity of the joint estimation, which has been demonstrated by numerical simulations.
Energy Technology Data Exchange (ETDEWEB)
Walstrom, Peter Lowell [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2017-08-07
A numerical algorithm for computing the field components B_{r} and B_{z} and their r and z derivatives with open boundaries in cylindrical coordinates for radially thin solenoids with uniform current density is described in this note. An algorithm for computing the vector potential A_{θ} is also described. For the convenience of the reader, derivations of the final expressions from their defining integrals are given in detail, since their derivations are not all easily found in textbooks. Numerical calculations are based on evaluation of complete elliptic integrals using the Bulirsch algorithm cel. The (apparently) new feature of the algorithms described in this note applies to cases where the field point is outside of the bore of the solenoid and the field-point radius approaches the solenoid radius. Since the elliptic integrals of the third kind normally used in computing B_{z} and A_{θ} become infinite in this region of parameter space, fields for points with the axial coordinate z outside of the ends of the solenoid and near the solenoid radius are treated by use of elliptic integrals of the third kind of modified argument, derived by use of an addition theorem. Also, the algorithms also avoid the numerical difficulties the textbook solutions have for points near the axis arising from explicit factors of 1/r or 1/r^{2} in the some of the expressions.
Directory of Open Access Journals (Sweden)
Wenliao Du
2013-01-01
Full Text Available Promptly and accurately dealing with the equipment breakdown is very important in terms of enhancing reliability and decreasing downtime. A novel fault diagnosis method PSO-RVM based on relevance vector machines (RVM with particle swarm optimization (PSO algorithm for plunger pump in truck crane is proposed. The particle swarm optimization algorithm is utilized to determine the kernel width parameter of the kernel function in RVM, and the five two-class RVMs with binary tree architecture are trained to recognize the condition of mechanism. The proposed method is employed in the diagnosis of plunger pump in truck crane. The six states, including normal state, bearing inner race fault, bearing roller fault, plunger wear fault, thrust plate wear fault, and swash plate wear fault, are used to test the classification performance of the proposed PSO-RVM model, which compared with the classical models, such as back-propagation artificial neural network (BP-ANN, ant colony optimization artificial neural network (ANT-ANN, RVM, and support vectors, machines with particle swarm optimization (PSO-SVM, respectively. The experimental results show that the PSO-RVM is superior to the first three classical models, and has a comparative performance to the PSO-SVM, the corresponding diagnostic accuracy achieving as high as 99.17% and 99.58%, respectively. But the number of relevance vectors is far fewer than that of support vector, and the former is about 1/12–1/3 of the latter, which indicates that the proposed PSO-RVM model is more suitable for applications that require low complexity and real-time monitoring.
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Guowu Bian
Full Text Available Wolbachia is a maternally transmitted endosymbiotic bacterium that is estimated to infect up to 65% of insect species. The ability of Wolbachia to both induce pathogen interference and spread into mosquito vector populations makes it possible to develop Wolbachia as a biological control agent for vector-borne disease control. Although Wolbachia induces resistance to dengue virus (DENV, filarial worms, and Plasmodium in mosquitoes, species like Aedes polynesiensis and Aedes albopictus, which carry native Wolbachia infections, are able to transmit dengue and filariasis. In a previous study, the native wPolA in Ae. polynesiensis was replaced with wAlbB from Ae. albopictus, and resulted in the generation of the transinfected "MTB" strain with low susceptibility for filarial worms. In this study, we compare the dynamics of DENV serotype 2 (DENV-2 within the wild type "APM" strain and the MTB strain of Ae. polynesiensis by measuring viral infection in the mosquito whole body, midgut, head, and saliva at different time points post infection. The results show that wAlbB can induce a strong resistance to DENV-2 in the MTB mosquito. Evidence also supports that this resistance is related to a dramatic increase in Wolbachia density in the MTB's somatic tissues, including the midgut and salivary gland. Our results suggests that replacement of a native Wolbachia with a novel infection could serve as a strategy for developing a Wolbachia-based approach to target naturally infected insects for vector-borne disease control.
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A. A. Zolotin
2015-07-01
Full Text Available Posteriori inference is one of the three kinds of probabilistic-logic inferences in the probabilistic graphical models theory and the base for processing of knowledge patterns with probabilistic uncertainty using Bayesian networks. The paper deals with a task of local posteriori inference description in algebraic Bayesian networks that represent a class of probabilistic graphical models by means of matrix-vector equations. The latter are essentially based on the use of tensor product of matrices, Kronecker degree and Hadamard product. Matrix equations for calculating posteriori probabilities vectors within posteriori inference in knowledge patterns with quanta propositions are obtained. Similar equations of the same type have already been discussed within the confines of the theory of algebraic Bayesian networks, but they were built only for the case of posteriori inference in the knowledge patterns on the ideals of conjuncts. During synthesis and development of matrix-vector equations on quanta propositions probability vectors, a number of earlier results concerning normalizing factors in posteriori inference and assignment of linear projective operator with a selector vector was adapted. We consider all three types of incoming evidences - deterministic, stochastic and inaccurate - combined with scalar and interval estimation of probability truth of propositional formulas in the knowledge patterns. Linear programming problems are formed. Their solution gives the desired interval values of posterior probabilities in the case of inaccurate evidence or interval estimates in a knowledge pattern. That sort of description of a posteriori inference gives the possibility to extend the set of knowledge pattern types that we can use in the local and global posteriori inference, as well as simplify complex software implementation by use of existing third-party libraries, effectively supporting submission and processing of matrices and vectors when
DEFF Research Database (Denmark)
Hansen, Kristoffer Lindskov; Møller-Sørensen, Hasse; Kjaergaard, Jesper
2016-01-01
Stenosis of the aortic valve gives rise to more complex blood flows with increased velocities. The angleindependent vector flow ultrasound technique transverse oscillation was employed intra-operatively on the ascending aorta of (I) 20 patients with a healthy aortic valve and 20 patients with aor......Stenosis of the aortic valve gives rise to more complex blood flows with increased velocities. The angleindependent vector flow ultrasound technique transverse oscillation was employed intra-operatively on the ascending aorta of (I) 20 patients with a healthy aortic valve and 20 patients...... with aortic stenosis before (IIa) and after (IIb) valve replacement. The results indicate that aortic stenosis increased flow complexity (p , 0.0001), induced systolic backflow (p , 0.003) and reduced systolic jet width (p , 0.0001). After valve replacement, the systolic backflow and jet width were normalized...... replacement corrects some of these changes. Transverse oscillation may be useful for assessment of aortic stenosis and optimization of valve surgery. (E-mail: lindskov@gmail.com) 2016 World Federation for Ultrasound in Medicine & Biology...
Basic nonlinear filters as vector algorithms for image processing on graphics units.
Margadant, Felix M; Hirt, Felix; Gattiker, Felix
2005-01-01
We present a vector implementation for nonlinear filters that allows an efficient execution on graphics processing units. These filters are popular to suppress shot noise arising in low light conditions. Having them available at the end of the visualization stage makes this setup particularly suitable for handling the postprocessing stages for light microscopy. Without vector acceleration, these filters constitute a bottleneck since real time or frequent update volume rendering has become available on desktop workstations. Even simple averaging operations can push the overall system's performance noticeably below the original frame rate.
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Tiannan Ma
2016-12-01
Full Text Available Accurate forecasting of icing thickness has great significance for ensuring the security and stability of the power grid. In order to improve the forecasting accuracy, this paper proposes an icing forecasting system based on the fireworks algorithm and weighted least square support vector machine (W-LSSVM. The method of the fireworks algorithm is employed to select the proper input features with the purpose of eliminating redundant influence. In addition, the aim of the W-LSSVM model is to train and test the historical data-set with the selected features. The capability of this proposed icing forecasting model and framework is tested through simulation experiments using real-world icing data from the monitoring center of the key laboratory of anti-ice disaster, Hunan, South China. The results show that the proposed W-LSSVM-FA method has a higher prediction accuracy and it may be a promising alternative for icing thickness forecasting.
Energy Technology Data Exchange (ETDEWEB)
Feng Wu; Hao Zhou; Tao Ren; Ligang Zheng; Kefa Cen [Zhejiang University, Hangzhou (China). State Key Laboratory of Clean Energy Utilization
2009-10-15
Support vector regression (SVR) was employed to establish mathematical models for the NOx emissions and carbon burnout of a 300 MW coal-fired utility boiler. Combined with the SVR models, the cellular genetic algorithm for multi-objective optimization (MOCell) was used for multi-objective optimization of the boiler combustion. Meanwhile, the comparison between MOCell and the improved non-dominated sorting genetic algorithm (NSGA-II) shows that MOCell has superior performance to NSGA-II regarding the problem. The field experiments were carried out to verify the accuracy of the results obtained by MOCell, the results were in good agreement with the measurement data. The proposed approach provides an effective tool for multi-objective optimization of coal combustion performance, whose feasibility and validity are experimental validated. A time period of less than 4 s was required for a run of optimization under a PC system, which is suitable for the online application. 19 refs., 8 figs., 2 tabs.
Yamazaki, Yoshiyuki; Hirai, Yukihiko; Miyake, Koichi; Shimada, Takashi
2014-07-01
Enzyme replacement via the cerebrospinal fluid (CSF) has been shown to ameliorate neurological symptoms in model animals with neuropathic metabolic disorders. Gene therapy via the CSF offers a means to achieve a long-term sustainable supply of therapeutic proteins within the central nervous system (CNS) by setting up a continuous source of transgenic products. In the present study, a serotype 1 adeno-associated virus (AAV1) vector was injected into a lateral cerebral ventricle in adult mice to transduce the gene encoding human lysosomal enzyme arylsulfatase A (hASA) into the cells of the CNS. Widespread transduction and stable expression of hASA in the choroid plexus and ependymal cells was observed throughout the ventricles for more than 1 year after vector injection. Although humoral immunity to hASA developed after 6 weeks, which diminished the hASA levels detected in CSF from AAV1-injected mice, hASA levels in CSF were maintained for at least 12 weeks when the mice were tolerized to hASA prior of vector injection. Our results suggest that the cells lining the ventricles could potentially serve as a biological reservoir for long-term continuous secretion of lysosomal enzymes into the CSF following intracerebroventricular injection of an AAV1 vector.
A path algorithm for the support vector domain description and its application to medical imaging
DEFF Research Database (Denmark)
Sjöstrand, Karl; Hansen, Michael Sass; Larsson, Henrik B. W.
2007-01-01
The support vector domain description is a one-class classification method that estimates the distributional support of a data set. A flexible closed boundary function is used to separate trustworthy data on the inside from outliers on the outside. A single regularization parameter determines...
Directory of Open Access Journals (Sweden)
Xin Yi Ng
2015-01-01
Full Text Available This study concerns an attempt to establish a new method for predicting antimicrobial peptides (AMPs which are important to the immune system. Recently, researchers are interested in designing alternative drugs based on AMPs because they have found that a large number of bacterial strains have become resistant to available antibiotics. However, researchers have encountered obstacles in the AMPs designing process as experiments to extract AMPs from protein sequences are costly and require a long set-up time. Therefore, a computational tool for AMPs prediction is needed to resolve this problem. In this study, an integrated algorithm is newly introduced to predict AMPs by integrating sequence alignment and support vector machine- (SVM- LZ complexity pairwise algorithm. It was observed that, when all sequences in the training set are used, the sensitivity of the proposed algorithm is 95.28% in jackknife test and 87.59% in independent test, while the sensitivity obtained for jackknife test and independent test is 88.74% and 78.70%, respectively, when only the sequences that has less than 70% similarity are used. Applying the proposed algorithm may allow researchers to effectively predict AMPs from unknown protein peptide sequences with higher sensitivity.
Energy Technology Data Exchange (ETDEWEB)
Walstrom, Peter Lowell [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2017-08-24
A numerical algorithm for computing the field components B_{r} and B_{z} and their r and z derivatives with open boundaries in cylindrical coordinates for circular current loops is described. An algorithm for computing the vector potential is also described. For the convenience of the reader, derivations of the final expressions from their defining integrals are given in detail, since their derivations (especially for the field derivatives) are not all easily found in textbooks. Numerical calculations are based on evaluation of complete elliptic integrals using the Bulirsch algorithm cel. Since cel can evaluate complete elliptic integrals of a fairly general type, in some cases the elliptic integrals can be evaluated without first reducing them to forms containing standard Legendre forms. The algorithms avoid the numerical difficulties that many of the textbook solutions have for points near the axis because of explicit factors of 1=r or 1=r^{2} in the some of the expressions.
Sabry, A H; W Hasan, W Z; Ab Kadir, M Z A; Radzi, M A M; Shafie, S
2018-01-01
The power system always has several variations in its profile due to random load changes or environmental effects such as device switching effects when generating further transients. Thus, an accurate mathematical model is important because most system parameters vary with time. Curve modeling of power generation is a significant tool for evaluating system performance, monitoring and forecasting. Several numerical techniques compete to fit the curves of empirical data such as wind, solar, and demand power rates. This paper proposes a new modified methodology presented as a parametric technique to determine the system's modeling equations based on the Bode plot equations and the vector fitting (VF) algorithm by fitting the experimental data points. The modification is derived from the familiar VF algorithm as a robust numerical method. This development increases the application range of the VF algorithm for modeling not only in the frequency domain but also for all power curves. Four case studies are addressed and compared with several common methods. From the minimal RMSE, the results show clear improvements in data fitting over other methods. The most powerful features of this method is the ability to model irregular or randomly shaped data and to be applied to any algorithms that estimating models using frequency-domain data to provide state-space or transfer function for the model.
W. Hasan, W. Z.
2018-01-01
The power system always has several variations in its profile due to random load changes or environmental effects such as device switching effects when generating further transients. Thus, an accurate mathematical model is important because most system parameters vary with time. Curve modeling of power generation is a significant tool for evaluating system performance, monitoring and forecasting. Several numerical techniques compete to fit the curves of empirical data such as wind, solar, and demand power rates. This paper proposes a new modified methodology presented as a parametric technique to determine the system’s modeling equations based on the Bode plot equations and the vector fitting (VF) algorithm by fitting the experimental data points. The modification is derived from the familiar VF algorithm as a robust numerical method. This development increases the application range of the VF algorithm for modeling not only in the frequency domain but also for all power curves. Four case studies are addressed and compared with several common methods. From the minimal RMSE, the results show clear improvements in data fitting over other methods. The most powerful features of this method is the ability to model irregular or randomly shaped data and to be applied to any algorithms that estimating models using frequency-domain data to provide state-space or transfer function for the model. PMID:29351554
Directory of Open Access Journals (Sweden)
A H Sabry
Full Text Available The power system always has several variations in its profile due to random load changes or environmental effects such as device switching effects when generating further transients. Thus, an accurate mathematical model is important because most system parameters vary with time. Curve modeling of power generation is a significant tool for evaluating system performance, monitoring and forecasting. Several numerical techniques compete to fit the curves of empirical data such as wind, solar, and demand power rates. This paper proposes a new modified methodology presented as a parametric technique to determine the system's modeling equations based on the Bode plot equations and the vector fitting (VF algorithm by fitting the experimental data points. The modification is derived from the familiar VF algorithm as a robust numerical method. This development increases the application range of the VF algorithm for modeling not only in the frequency domain but also for all power curves. Four case studies are addressed and compared with several common methods. From the minimal RMSE, the results show clear improvements in data fitting over other methods. The most powerful features of this method is the ability to model irregular or randomly shaped data and to be applied to any algorithms that estimating models using frequency-domain data to provide state-space or transfer function for the model.
Directory of Open Access Journals (Sweden)
Elizabeth M Sweeney
Full Text Available Machine learning is a popular method for mining and analyzing large collections of medical data. We focus on a particular problem from medical research, supervised multiple sclerosis (MS lesion segmentation in structural magnetic resonance imaging (MRI. We examine the extent to which the choice of machine learning or classification algorithm and feature extraction function impacts the performance of lesion segmentation methods. As quantitative measures derived from structural MRI are important clinical tools for research into the pathophysiology and natural history of MS, the development of automated lesion segmentation methods is an active research field. Yet, little is known about what drives performance of these methods. We evaluate the performance of automated MS lesion segmentation methods, which consist of a supervised classification algorithm composed with a feature extraction function. These feature extraction functions act on the observed T1-weighted (T1-w, T2-weighted (T2-w and fluid-attenuated inversion recovery (FLAIR MRI voxel intensities. Each MRI study has a manual lesion segmentation that we use to train and validate the supervised classification algorithms. Our main finding is that the differences in predictive performance are due more to differences in the feature vectors, rather than the machine learning or classification algorithms. Features that incorporate information from neighboring voxels in the brain were found to increase performance substantially. For lesion segmentation, we conclude that it is better to use simple, interpretable, and fast algorithms, such as logistic regression, linear discriminant analysis, and quadratic discriminant analysis, and to develop the features to improve performance.
Martins, Maria; Costa, Lino; Frizera, Anselmo; Ceres, Ramón; Santos, Cristina
2014-03-01
Walker devices are often prescribed incorrectly to patients, leading to the increase of dissatisfaction and occurrence of several problems, such as, discomfort and pain. Thus, it is necessary to objectively evaluate the effects that assisted gait can have on the gait patterns of walker users, comparatively to a non-assisted gait. A gait analysis, focusing on spatiotemporal and kinematics parameters, will be issued for this purpose. However, gait analysis yields redundant information that often is difficult to interpret. This study addresses the problem of selecting the most relevant gait features required to differentiate between assisted and non-assisted gait. For that purpose, it is presented an efficient approach that combines evolutionary techniques, based on genetic algorithms, and support vector machine algorithms, to discriminate differences between assisted and non-assisted gait with a walker with forearm supports. For comparison purposes, other classification algorithms are verified. Results with healthy subjects show that the main differences are characterized by balance and joints excursion in the sagittal plane. These results, confirmed by clinical evidence, allow concluding that this technique is an efficient feature selection approach. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.
Cui, Ying; Chen, Qinggang; Li, Yaxiao; Tang, Ling
2017-02-01
Flavonoids exhibit a high affinity for the purified cytosolic NBD (C-terminal nucleotide-binding domain) of P-glycoprotein (P-gp). To explore the affinity of flavonoids for P-gp, quantitative structure-activity relationship (QSAR) models were developed using support vector machines (SVMs). A novel method coupling a modified particle swarm optimization algorithm with random mutation strategy and a genetic algorithm coupled with SVM was proposed to simultaneously optimize the kernel parameters of SVM and determine the subset of optimized features for the first time. Using DRAGON descriptors to represent compounds for QSAR, three subsets (training, prediction and external validation set) derived from the dataset were employed to investigate QSAR. With excluding of the outlier, the correlation coefficient (R(2)) of the whole training set (training and prediction) was 0.924, and the R(2) of the external validation set was 0.941. The root-mean-square error (RMSE) of the whole training set was 0.0588; the RMSE of the cross-validation of the external validation set was 0.0443. The mean Q(2) value of leave-many-out cross-validation was 0.824. With more informations from results of randomization analysis and applicability domain, the proposed model is of good predictive ability, stability.
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Gang Qin
2015-01-01
Full Text Available The acceleration performance of EV, which affects a lot of performances of EV such as start-up, overtaking, driving safety, and ride comfort, has become increasingly popular in recent researches. An improved variable gain PID control algorithm to improve the acceleration performance is proposed in this paper. The results of simulation with Matlab/Simulink demonstrate the effectiveness of the proposed algorithm through the control performance of motor velocity, motor torque, and three-phase current of motor. Moreover, it is investigated that the proposed controller is valid by comparison with the other PID controllers. Furthermore, the AC induction motor experiment set is constructed to verify the effect of proposed controller.
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Min Zhang
2015-01-01
Full Text Available Control charts have been widely utilized for monitoring process variation in numerous applications. Abnormal patterns exhibited by control charts imply certain potentially assignable causes that may deteriorate the process performance. Most of the previous studies are concerned with the recognition of single abnormal control chart patterns (CCPs. This paper introduces an intelligent hybrid model for recognizing the mixture CCPs that includes three main aspects: feature extraction, classifier, and parameters optimization. In the feature extraction, statistical and shape features of observation data are used in the data input to get the effective data for the classifier. A multiclass support vector machine (MSVM applies for recognizing the mixture CCPs. Finally, genetic algorithm (GA is utilized to optimize the MSVM classifier by searching the best values of the parameters of MSVM and kernel function. The performance of the hybrid approach is evaluated by simulation experiments, and simulation results demonstrate that the proposed approach is able to effectively recognize mixture CCPs.
Directory of Open Access Journals (Sweden)
Mustafa Serter Uzer
2013-01-01
Full Text Available This paper offers a hybrid approach that uses the artificial bee colony (ABC algorithm for feature selection and support vector machines for classification. The purpose of this paper is to test the effect of elimination of the unimportant and obsolete features of the datasets on the success of the classification, using the SVM classifier. The developed approach conventionally used in liver diseases and diabetes diagnostics, which are commonly observed and reduce the quality of life, is developed. For the diagnosis of these diseases, hepatitis, liver disorders and diabetes datasets from the UCI database were used, and the proposed system reached a classification accuracies of 94.92%, 74.81%, and 79.29%, respectively. For these datasets, the classification accuracies were obtained by the help of the 10-fold cross-validation method. The results show that the performance of the method is highly successful compared to other results attained and seems very promising for pattern recognition applications.
Martins, F V C; Carrano, E G; Wanner, E F; Takahashi, R H C; Mateus, G R; Nakamura, F G
2014-01-01
Recent works raised the hypothesis that the assignment of a geometry to the decision variable space of a combinatorial problem could be useful both for providing meaningful descriptions of the fitness landscape and for supporting the systematic construction of evolutionary operators (the geometric operators) that make a consistent usage of the space geometric properties in the search for problem optima. This paper introduces some new geometric operators that constitute the realization of searches along the combinatorial space versions of the geometric entities descent directions and subspaces. The new geometric operators are stated in the specific context of the wireless sensor network dynamic coverage and connectivity problem (WSN-DCCP). A genetic algorithm (GA) is developed for the WSN-DCCP using the proposed operators, being compared with a formulation based on integer linear programming (ILP) which is solved with exact methods. That ILP formulation adopts a proxy objective function based on the minimization of energy consumption in the network, in order to approximate the objective of network lifetime maximization, and a greedy approach for dealing with the system's dynamics. To the authors' knowledge, the proposed GA is the first algorithm to outperform the lifetime of networks as synthesized by the ILP formulation, also running in much smaller computational times for large instances.
Morrell, Frederick R.; Bailey, Melvin L.
1987-01-01
A vector-based failure detection and isolation technique for a skewed array of two degree-of-freedom inertial sensors is developed. Failure detection is based on comparison of parity equations with a threshold, and isolation is based on comparison of logic variables which are keyed to pass/fail results of the parity test. A multi-level approach to failure detection is used to ensure adequate coverage for the flight control, display, and navigation avionics functions. Sensor error models are introduced to expose the susceptibility of the parity equations to sensor errors and physical separation effects. The algorithm is evaluated in a simulation of a commercial transport operating in a range of light to severe turbulence environments. A bias-jump failure level of 0.2 deg/hr was detected and isolated properly in the light and moderate turbulence environments, but not detected in the extreme turbulence environment. An accelerometer bias-jump failure level of 1.5 milli-g was detected over all turbulence environments. For both types of inertial sensor, hard-over, and null type failures were detected in all environments without incident. The algorithm functioned without false alarm or isolation over all turbulence environments for the runs tested.
Murugesan, Yahini Prabha; Alsadoon, Abeer; Manoranjan, Paul; Prasad, P W C
2018-02-19
Augmented reality-based surgeries have not been successfully implemented in oral and maxillofacial areas due to limitations in geometric accuracy and image registration. This paper aims to improve the accuracy and depth perception of the augmented video. The proposed system consists of a rotational matrix and translation vector algorithm to reduce the geometric error and improve the depth perception by including 2 stereo cameras and a translucent mirror in the operating room. The results on the mandible/maxilla area show that the new algorithm improves the video accuracy by 0.30-0.40 mm (in terms of overlay error) and the processing rate to 10-13 frames/s compared to 7-10 frames/s in existing systems. The depth perception increased by 90-100 mm. The proposed system concentrates on reducing the geometric error. Thus, this study provides an acceptable range of accuracy with a shorter operating time, which provides surgeons with a smooth surgical flow. Copyright © 2018 John Wiley & Sons, Ltd.
Dai, Wensheng; Wu, Jui-Yu; Lu, Chi-Jie
2014-01-01
Sales forecasting is one of the most important issues in managing information technology (IT) chain store sales since an IT chain store has many branches. Integrating feature extraction method and prediction tool, such as support vector regression (SVR), is a useful method for constructing an effective sales forecasting scheme. Independent component analysis (ICA) is a novel feature extraction technique and has been widely applied to deal with various forecasting problems. But, up to now, only the basic ICA method (i.e., temporal ICA model) was applied to sale forecasting problem. In this paper, we utilize three different ICA methods including spatial ICA (sICA), temporal ICA (tICA), and spatiotemporal ICA (stICA) to extract features from the sales data and compare their performance in sales forecasting of IT chain store. Experimental results from a real sales data show that the sales forecasting scheme by integrating stICA and SVR outperforms the comparison models in terms of forecasting error. The stICA is a promising tool for extracting effective features from branch sales data and the extracted features can improve the prediction performance of SVR for sales forecasting.
Directory of Open Access Journals (Sweden)
Wensheng Dai
2014-01-01
Full Text Available Sales forecasting is one of the most important issues in managing information technology (IT chain store sales since an IT chain store has many branches. Integrating feature extraction method and prediction tool, such as support vector regression (SVR, is a useful method for constructing an effective sales forecasting scheme. Independent component analysis (ICA is a novel feature extraction technique and has been widely applied to deal with various forecasting problems. But, up to now, only the basic ICA method (i.e., temporal ICA model was applied to sale forecasting problem. In this paper, we utilize three different ICA methods including spatial ICA (sICA, temporal ICA (tICA, and spatiotemporal ICA (stICA to extract features from the sales data and compare their performance in sales forecasting of IT chain store. Experimental results from a real sales data show that the sales forecasting scheme by integrating stICA and SVR outperforms the comparison models in terms of forecasting error. The stICA is a promising tool for extracting effective features from branch sales data and the extracted features can improve the prediction performance of SVR for sales forecasting.
Dai, Wensheng
2014-01-01
Sales forecasting is one of the most important issues in managing information technology (IT) chain store sales since an IT chain store has many branches. Integrating feature extraction method and prediction tool, such as support vector regression (SVR), is a useful method for constructing an effective sales forecasting scheme. Independent component analysis (ICA) is a novel feature extraction technique and has been widely applied to deal with various forecasting problems. But, up to now, only the basic ICA method (i.e., temporal ICA model) was applied to sale forecasting problem. In this paper, we utilize three different ICA methods including spatial ICA (sICA), temporal ICA (tICA), and spatiotemporal ICA (stICA) to extract features from the sales data and compare their performance in sales forecasting of IT chain store. Experimental results from a real sales data show that the sales forecasting scheme by integrating stICA and SVR outperforms the comparison models in terms of forecasting error. The stICA is a promising tool for extracting effective features from branch sales data and the extracted features can improve the prediction performance of SVR for sales forecasting. PMID:25165740
Synchronized Scheme of Continuous Space-Vector PWM with the Real-Time Control Algorithms
DEFF Research Database (Denmark)
Oleschuk, V.; Blaabjerg, Frede
2004-01-01
synchronous PWM at higher values of the fundamental frequency has also been described. Results of analysis of the spectral characteristics of the output voltage of the inverter show advantage of synchronous PWM in comparison with conventional asynchronous modulation at low indices of the frequency ratio...... their position inside clock-intervals. In order to provide smooth shock-less pulse-ratio changing and quarter-wave symmetry of the voltage waveforms, special synchronising signals are formed on the boundaries of the 60 clock-intervals. The process of gradual transition from continuous to discontinuous...... between the switching and the fundamental frequency. Special attention has been given to the analysis and comparison of the computational effectiveness of the proposed algorithms of synchronized modulation. 0...
Fernandez, Michael; Caballero, Julio; Fernandez, Leyden; Sarai, Akinori
2011-02-01
Many articles in "in silico" drug design implemented genetic algorithm (GA) for feature selection, model optimization, conformational search, or docking studies. Some of these articles described GA applications to quantitative structure-activity relationships (QSAR) modeling in combination with regression and/or classification techniques. We reviewed the implementation of GA in drug design QSAR and specifically its performance in the optimization of robust mathematical models such as Bayesian-regularized artificial neural networks (BRANNs) and support vector machines (SVMs) on different drug design problems. Modeled data sets encompassed ADMET and solubility properties, cancer target inhibitors, acetylcholinesterase inhibitors, HIV-1 protease inhibitors, ion-channel and calcium entry blockers, and antiprotozoan compounds as well as protein classes, functional, and conformational stability data. The GA-optimized predictors were often more accurate and robust than previous published models on the same data sets and explained more than 65% of data variances in validation experiments. In addition, feature selection over large pools of molecular descriptors provided insights into the structural and atomic properties ruling ligand-target interactions.
Indian Academy of Sciences (India)
positive numbers. The word 'algorithm' was most often associated with this algorithm till 1950. It may however be pOinted out that several non-trivial algorithms such as synthetic (polynomial) division have been found in Vedic Mathematics which are dated much before Euclid's algorithm. A programming language Is used.
Energy Technology Data Exchange (ETDEWEB)
Heo, Min Suk; Kavitha, Muthu Subash [Dept. of Oral and Maxillofacial Radiology and Dental Research Institute, School of Dentistry, Seoul National University, Seoul (Korea, Republic of); Asano, Akira [Graduate School of Engineering, Hiroshima University, Hiroshima (Japan); Taguchi, Akira [Dept. of Oral and Maxillofacial Radiology, Matsumoto Dental University, Nagano (Japan)
2013-09-15
To prevent low bone mineral density (BMD), that is, osteoporosis, in postmenopausal women, it is essential to diagnose osteoporosis more precisely. This study presented an automatic approach utilizing a histogram-based automatic clustering (HAC) algorithm with a support vector machine (SVM) to analyse dental panoramic radiographs (DPRs) and thus improve diagnostic accuracy by identifying postmenopausal women with low BMD or osteoporosis. We integrated our newly-proposed histogram-based automatic clustering (HAC) algorithm with our previously-designed computer-aided diagnosis system. The extracted moment-based features (mean, variance, skewness, and kurtosis) of the mandibular cortical width for the radial basis function (RBF) SVM classifier were employed. We also compared the diagnostic efficacy of the SVM model with the back propagation (BP) neural network model. In this study, DPRs and BMD measurements of 100 postmenopausal women patients (aged >50 years), with no previous record of osteoporosis, were randomly selected for inclusion. The accuracy, sensitivity, and specificity of the BMD measurements using our HAC-SVM model to identify women with low BMD were 93.0% (88.0%-98.0%), 95.8% (91.9%-99.7%) and 86.6% (79.9%-93.3%), respectively, at the lumbar spine; and 89.0% (82.9%-95.1%), 96.0% (92.2%-99.8%) and 84.0% (76.8%-91.2%), respectively, at the femoral neck. Our experimental results predict that the proposed HAC-SVM model combination applied on DPRs could be useful to assist dentists in early diagnosis and help to reduce the morbidity and mortality associated with low BMD and osteoporosis.
Macro motion vector quantization
Lee, Yoon Y.; Woods, John W.
1995-04-01
A new algorithm is developed for reducing the bit rate required for motion vectors. This algorithm is a generalization of block matching motion estimation in which the search region is represented as a codebook of motion vectors. The new algorithm, called macro motion vector quantization (MMVQ), generalized our earlier MVQ by coding a group of motion vectors. The codebook is a set of macro motion vectors which represent the block locations of the small neighboring blocks in the previous frame. We develop an interative design algorithm for the codebook. Our experiments show that the variances of displaced frame differences (DFDs) are reduced significantly compared to block matching algorithm (BMA) with the macroblock size.
Directory of Open Access Journals (Sweden)
Ping Jiang
2015-01-01
Full Text Available Wind speed/power has received increasing attention around the earth due to its renewable nature as well as environmental friendliness. With the global installed wind power capacity rapidly increasing, wind industry is growing into a large-scale business. Reliable short-term wind speed forecasts play a practical and crucial role in wind energy conversion systems, such as the dynamic control of wind turbines and power system scheduling. In this paper, an intelligent hybrid model for short-term wind speed prediction is examined; the model is based on cross correlation (CC analysis and a support vector regression (SVR model that is coupled with brainstorm optimization (BSO and cuckoo search (CS algorithms, which are successfully utilized for parameter determination. The proposed hybrid models were used to forecast short-term wind speeds collected from four wind turbines located on a wind farm in China. The forecasting results demonstrate that the intelligent hybrid models outperform single models for short-term wind speed forecasting, which mainly results from the superiority of BSO and CS for parameter optimization.
Directory of Open Access Journals (Sweden)
Jieqiong Su
2015-04-01
Full Text Available With decreasing water availability as a result of climate change and human activities, analysis of the influential factors and variation trends of chlorophyll a has become important to prevent reservoir eutrophication and ensure water supply safety. In this paper, a structurally simplified hybrid model of the genetic algorithm (GA and the support vector machine (SVM was developed for the prediction of monthly concentration of chlorophyll a in the Miyun Reservoir of northern China over the period from 2000 to 2010. Based on the influence factor analysis, the four most relevant influence factors of chlorophyll a (i.e., total phosphorus, total nitrogen, permanganate index, and reservoir storage were extracted using the method of feature selection with the GA, which simplified the model structure, making it more practical and efficient for environmental management. The results showed that the developed simplified GA-SVM model could solve nonlinear problems of complex system, and was suitable for the simulation and prediction of chlorophyll a with better performance in accuracy and efficiency in the Miyun Reservoir.
Indian Academy of Sciences (India)
In the description of algorithms and programming languages, what is the role of control abstraction? • What are the inherent limitations of the algorithmic processes? In future articles in this series, we will show that these constructs are powerful and can be used to encode any algorithm. In the next article, we will discuss ...
Directory of Open Access Journals (Sweden)
irfan abbas
2017-01-01
Full Text Available At this time, the players Forex Trading generally still use the data exchange in the form of a Forex Trading figures from different sources. Thus they only receive or know the data rate of a Forex Trading prevailing at the time just so difficult to analyze or predict exchange rate movements future. Forex players usually use the indicators to enable them to analyze and memperdiksi future value. Indicator is a decision making tool. Trading forex is trading currency of a country, the other country's currency. Trading took place globally between the financial centers of the world with the involvement of the world's major banks as the major transaction. Trading Forex offers profitable investment type with a small capital and high profit, with relatively small capital can earn profits doubled. This is due to the forex trading systems exist leverage which the invested capital will be doubled if the predicted results of buy / sell is accurate, but Trading Forex having high risk level, but by knowing the right time to trade (buy or sell, the losses can be avoided. Traders who invest in the foreign exchange market is expected to have the ability to analyze the circumstances and situations in predicting the difference in currency exchange rates. Forex price movements that form the pattern (curve up and down greatly assist traders in making decisions. The movement of the curve used as an indicator in the decision to purchase (buy or sell (sell. This study compares (Comparation type algorithm kernel on Support Vector Machine (SVM to predict the movement of the curve in live time trading forex using the data GBPUSD, 1H. Results of research on the study of the results and discussion can be concluded that the Kernel Dot, Kernel Multiquaric, Kernel Neural inappropriately used for data is non-linear in the case of data forex to follow the pattern of trend curves, because curves generated curved linear (straight and then to type of kernel is the closest curve
Lin, Wei-Qi; Jiang, Jian-Hui; Zhou, Yan-Ping; Wu, Hai-Long; Shen, Guo-Li; Yu, Ru-Qin
2007-01-30
Multilayer feedforward neural networks (MLFNNs) are important modeling techniques widely used in QSAR studies for their ability to represent nonlinear relationships between descriptors and activity. However, the problems of overfitting and premature convergence to local optima still pose great challenges in the practice of MLFNNs. To circumvent these problems, a support vector machine (SVM) based training algorithm for MLFNNs has been developed with the incorporation of particle swarm optimization (PSO). The introduction of the SVM based training mechanism imparts the developed algorithm with inherent capacity for combating the overfitting problem. Moreover, with the implementation of PSO for searching the optimal network weights, the SVM based learning algorithm shows relatively high efficiency in converging to the optima. The proposed algorithm has been evaluated using the Hansch data set. Application to QSAR studies of the activity of COX-2 inhibitors is also demonstrated. The results reveal that this technique provides superior performance to backpropagation (BP) and PSO training neural networks.
Nakai, Kenji; Takahashi, Shin; Suzuki, Atsushi; Hagiwara, Nobuhisa; Futagawa, Keisuke; Shoda, Morio; Shiga, Tsuyoshi; Takahashi, Ken; Okabayashi, Hitoshi; Itoh, Manabu; Kasanuki, Hiroshi
2011-03-01
The noninvasive evaluation of ventricular T-wave alternans (TWA) in patients with lethal ventricular arrhythmias is an important issue. In this study, we propose a novel algorithm to identify T-wave current density alternans (TWCA) using synthesized 187-channel vector-projected body surface mapping (187-ch SAVP-ECG). We recorded 10 min of 187-ch SAVP-ECG using a Mason-Likar lead system in the supine position. A recovery time (RT) dispersion map was obtained by averaging the 187-ch SAVP-ECG. The TWCA value was determined from the relative changes in the averaged current density in the T-wave zone (Tpeak ± 50 ms) for two T-wave types. We registered 20 ECG recordings from normal controls and 11 ECG recordings from nine subjects with long QT syndrome (LQT). We divided LQT syndrome subjects into two groups: group 1 provided 9 ECG recordings without visually apparent TWAs, and group 2 provided 2 ECG recordings with visually apparent TWAs. The QTc interval values in the LQT groups were higher than those in the control (515 ± 60 ms in LQT G-1, 600 ± 27 ms in LQT G-2 vs. 415 ± 19 ms in control, P < 0.001). The RTendc dispersion values among the LQT subjects were higher than those of the control subjects (48 ± 19 ms in LQT G-1, 65 ± 30 ms in LQT G-2 vs. 24 ± 10 ms in control, P < 0.01). The mean TWCA value was significantly higher in the LQT G-2 group with visually apparent TWCAs (0.5 ± 0.2% in control, 2.1 ± 1.2% in LQT G-1, and 32.3 ± 6.9% in LQT G-2). Interestingly, the two-dimensional distribution of TWCA in LQT was inhomogeneous and correlated with the distribution of increased RT dispersion. We conclude that a novel algorithm using 187-ch SAVP-ECG might provide new insights into body surface TWCA.
Tang, Li-Juan; Zhou, Yan-Ping; Jiang, Jian-Hui; Zou, Hong-Yan; Wu, Hai-Long; Shen, Guo-Li; Yu, Ru-Qin
2007-01-01
The support vector machine (SVM) has been receiving increasing interest in an area of QSAR study for its ability in function approximation and remarkable generalization performance. However, selection of support vectors and intensive optimization of kernel width of a nonlinear SVM are inclined to get trapped into local optima, leading to an increased risk of underfitting or overfitting. To overcome these problems, a new nonlinear SVM algorithm is proposed using adaptive kernel transform based on a radial basis function network (RBFN) as optimized by particle swarm optimization (PSO). The new algorithm incorporates a nonlinear transform of the original variables to feature space via a RBFN with one input and one hidden layer. Such a transform intrinsically yields a kernel transform of the original variables. A synergetic optimization of all parameters including kernel centers and kernel widths as well as SVM model coefficients using PSO enables the determination of a flexible kernel transform according to the performance of the total model. The implementation of PSO demonstrates a relatively high efficiency in convergence to a desired optimum. Applications of the proposed algorithm to QSAR studies of binding affinity of HIV-1 reverse transcriptase inhibitors and activity of 1-phenylbenzimidazoles reveal that the new algorithm provides superior performance to the backpropagation neural network and a conventional nonlinear SVM, indicating that this algorithm holds great promise in nonlinear SVM learning.
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Sanjeevikumar Padmanaban
2015-09-01
Full Text Available This paper considered a six-phase (asymmetrical induction motor, kept 30° phase displacement between two set of three-phase open-end stator windings configuration. The drive system consists of four classical three-phase voltage inverters (VSIs and all four dc sources are deliberately kept isolated. Therefore, zero-sequence/homopolar current components cannot flow. The original and effective power sharing algorithm is proposed in this paper with three variables (degree of freedom based on synchronous field oriented control (FOC. A standard three-level space vector pulse width modulation (SVPWM by nearest three vectors (NTVs approach is adopted to regulate each couple of VSIs. The proposed power sharing algorithm is verified by complete numerical simulation modeling (Matlab/Simulink-PLECS software of whole ac drive system by observing the dynamic behaviors in different designed condition. Set of results are provided in this paper, which confirms a good agreement with theoretical development.
Indian Academy of Sciences (India)
, i is referred to as the loop-index, 'stat-body' is any sequence of ... while i ~ N do stat-body; i: = i+ 1; endwhile. The algorithm for sorting the numbers is described in Table 1 and the algorithmic steps on a list of 4 numbers shown in. Figure 1.
Hlihor, Raluca Maria; Diaconu, Mariana; Leon, Florin; Curteanu, Silvia; Tavares, Teresa; Gavrilescu, Maria
2015-05-25
We investigated the bioremoval of Cd(II) in batch mode, using dead and living biomass of Trichoderma viride. Kinetic studies revealed three distinct stages of the biosorption process. The pseudo-second order model and the Langmuir model described well the kinetics and equilibrium of the biosorption process, with a determination coefficient, R(2)>0.99. The value of the mean free energy of adsorption, E, is less than 16 kJ/mol at 25 °C, suggesting that, at low temperature, the dominant process involved in Cd(II) biosorption by dead T. viride is the chemical ion-exchange. With the temperature increasing to 40-50 °C, E values are above 16 kJ/mol, showing that the particle diffusion mechanism could play an important role in Cd(II) biosorption. The studies on T. viride growth in Cd(II) solutions and its bioaccumulation performance showed that the living biomass was able to bioaccumulate 100% Cd(II) from a 50 mg/L solution at pH 6.0. The influence of pH, biomass dosage, metal concentration, contact time and temperature on the bioremoval efficiency was evaluated to further assess the biosorption capability of the dead biosorbent. These complex influences were correlated by means of a modeling procedure consisting in data driven approach in which the principles of artificial intelligence were applied with the help of support vector machines (SVM), combined with genetic algorithms (GA). According to our data, the optimal working conditions for the removal of 98.91% Cd(II) by T. viride were found for an aqueous solution containing 26.11 mg/L Cd(II) as follows: pH 6.0, contact time of 3833 min, 8 g/L biosorbent, temperature 46.5 °C. The complete characterization of bioremoval parameters indicates that T. viride is an excellent material to treat wastewater containing low concentrations of metal. Copyright © 2014 Elsevier B.V. All rights reserved.
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Peng Xie
2017-05-01
Full Text Available The Earth’s surface is uneven, and conventional area calculation methods are based on the assumption that the projection plane area can be obtained without considering the actual undulation of the Earth’s surface and by simplifying the Earth’s shape to be a standard ellipsoid. However, the true surface area is important for investigating and evaluating land resources. In this study, the authors propose a new method based on an efficient vector-raster overlay algorithm (VROA-based method to calculate the surface areas of irregularly shaped land use patches. In this method, a surface area raster file is first generated based on the raster-based digital elevation model (raster-based DEM. Then, a vector-raster overlay algorithm (VROA is used that considers the precise clipping of raster cells using the vector polygon boundary. Xiantao City, Luotian County, and the Shennongjia Forestry District, which are representative of a plain landform, a hilly topography, and a mountain landscape, respectively, are selected to calculate the surface area. Compared with a traditional method based on triangulated irregular networks (TIN-based method, our method significantly reduces the processing time. In addition, our method effectively improves the accuracy compared with another traditional method based on raster-based DEM (raster-based method. Therefore, the method satisfies the requirements of large-scale engineering applications.
Indian Academy of Sciences (India)
Algorithms. 3. Procedures and Recursion. R K Shyamasundar. In this article we introduce procedural abstraction and illustrate its uses. Further, we illustrate the notion of recursion which is one of the most useful features of procedural abstraction. Procedures. Let us consider a variation of the pro blem of summing the first M.
Indian Academy of Sciences (India)
number of elements. We shall illustrate the widely used matrix multiplication algorithm using the two dimensional arrays in the following. Consider two matrices A and B of integer type with di- mensions m x nand n x p respectively. Then, multiplication of. A by B denoted, A x B , is defined by matrix C of dimension m xp where.
Wang, Tian'en; Shen, Jianqi; Lin, Chengjun
2017-06-01
The vector similarity measure (VSM) was recently introduced into the inverse problem for particle analysis based on forward light scattering and its modified version was proposed to adapt for multi-modal particle systems. It is found that the algorithm is stable and efficient but the extracted solutions are usually oscillatory, especially for widely distributed particle systems. In order to improve this situation, an iterative VSM method combined with cubic B-spline functions (B-VSM) is presented. Simulations and experiments show that, compared with the old versions, this modification is more robust and efficient.
DEFF Research Database (Denmark)
Padmanaban, Sanjeevikumar; Grandi, Gabriele; Blaabjerg, Frede
2015-01-01
This paper considered a six-phase (asymmetrical) induction motor, kept 30 phase displacement between two set of three-phase open-end stator windings configuration. The drive system consists of four classical three-phase voltage inverters (VSIs) and all four dc sources are deliberately kept isolated......) by nearest three vectors (NTVs) approach is adopted to regulate each couple of VSIs. The proposed power sharing algorithm is verified by complete numerical simulation modeling (Matlab/ Simulink-PLECS software) of whole ac drive system by observing the dynamic behaviors in different designed condition. Set...
Alantary, Doaa; Yalkowsky, Samuel
2017-05-08
The general solubility equation (GSE) is the state-of-the-art method for estimating the aqueous solubilities of organic compounds. It is an extremely simple equation that expresses aqueous solubility as a function of only two inputs: the octanol-water partition coefficient calculated by readily available softwares like clogP and ACD/logP, and the commonly known melting point of the solute. Recently, Bahadori et al. proposed that their genetic algorithm support vector machine is a "better" predictor. This paper compares the use of the of Bahadori et al. model for the prediction of aqueous solubility to the existing GSE model.
Directory of Open Access Journals (Sweden)
Ying-Yi Hong
2015-01-01
Full Text Available High-impedance faults (HIFs caused by downed conductors in electric power systems are in general difficult to be detected using traditional protection relays due to small fault currents. The energized downed conductor can pose a safety risk to the public and cause a fire hazard. This paper presents a new method for locating the line (feeder section of the HIF with the help of limited measurements in electric power systems. The discrete wavelet transform is used to extract the features of transients caused by HIFs. A modified k-means algorithm associated with genetic algorithms is then utilized to determine the placement of measurement facilities. The signal energies attained by wavelet coefficients serve as inputs to the support vector machine for locating the HIF line section. The simulation results obtained from an 18-busbar distribution system show the applicability of the proposed method.
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Lei Si
2016-01-01
Full Text Available Shearers play an important role in fully mechanized coal mining face and accurately identifying their cutting pattern is very helpful for improving the automation level of shearers and ensuring the safety of coal mining. The least squares support vector machine (LSSVM has been proven to offer strong potential in prediction and classification issues, particularly by employing an appropriate meta-heuristic algorithm to determine the values of its two parameters. However, these meta-heuristic algorithms have the drawbacks of being hard to understand and reaching the global optimal solution slowly. In this paper, an improved fly optimization algorithm (IFOA to optimize the parameters of LSSVM was presented and the LSSVM coupled with IFOA (IFOA-LSSVM was used to identify the shearer cutting pattern. The vibration acceleration signals of five cutting patterns were collected and the special state features were extracted based on the ensemble empirical mode decomposition (EEMD and the kernel function. Some examples on the IFOA-LSSVM model were further presented and the results were compared with LSSVM, PSO-LSSVM, GA-LSSVM and FOA-LSSVM models in detail. The comparison results indicate that the proposed approach was feasible, efficient and outperformed the others. Finally, an industrial application example at the coal mining face was demonstrated to specify the effect of the proposed system.
Oh, Duk-Soon
2017-06-13
A BDDC domain decomposition preconditioner is defined by a coarse component, expressed in terms of primal constraints, a weighted average across the interface between the subdomains, and local components given in terms of solvers of local subdomain problems. BDDC methods for vector field problems discretized with Raviart-Thomas finite elements are introduced. The methods are based on a deluxe type of weighted average and an adaptive selection of primal constraints developed to deal with coefficients with high contrast even inside individual subdomains. For problems with very many subdomains, a third level of the preconditioner is introduced.
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Muhammad Ilyas Syarif
2012-07-01
Full Text Available Efficiency energy and stream data mining on Wireless Sensor Networks (WSNs are a very interesting issue to be discussed. Routing protocols technology and resource-aware can be done to improve energy efficiency. In this paper we try to merge routing protocol technology using routing Distance Vector and Resource-Aware (RA framework on heterogeneity wireless sensor networks by combining sun-SPOT and Imote2 platform wireless sensor networks. RA perform resource monitoring process of the battery, memory and CPU load more optimally and efficiently. The process uses Light-Weight Clustering (LWC and Light Weight Frequent Item (LWF. The results obtained that by adapting Resource-Aware in wireless sensor networks, the lifetime of wireless sensor improve up to Â± 16.62%. Efisiensi energi dan stream data mining pada Wireless Sensor Networks (WSN adalah masalah yang sangat menarik untuk dibahas. Teknologi Routing Protocol dan Resource-Aware dapat dilakukan untuk meningkatkan efisiensi energi. Dalam penelitian ini peneliti mencoba untuk menggabungkan teknologi Routing Protocol menggunakan routing Distance Vector dan Resource-Aware (RA framework pada Wireless Sensor Networks heterogen dengan menggabungkan sun-SPOT dan platform Imote2 Wireless Sensor Networks. RA melakukan proses pemantauan sumber daya dari memori, baterai, dan beban CPU lebih optimal dan efisien. Proses ini menggunakan Light-Weight Clustering (LWC dan Light Weight Frequent Item (LWF. Hasil yang diperoleh bahwa dengan mengadaptasi Resource-Aware dalam Wireless Sensor Networks, masa pakai wireless sensor meningkatkan sampai Â± 16,62%.
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Xing Liu
2016-11-01
Full Text Available A method is proposed for reducing speed ripple of permanent magnet synchronous motors (PMSMs controlled by space vector pulse width modulation (SVPWM. A flux graph and mathematics are used to analyze the speed ripple characteristics of the PMSM. Analysis indicates that the 6P (P refers to pole pairs of the PMSM time harmonic of rotor mechanical speed is the main harmonic component in the SVPWM control PMSM system. To reduce PMSM speed ripple, harmonics are superposed on a SVPWM reference signal. A particle swarm optimization (PSO algorithm is proposed to determine the optimal phase and multiplier coefficient of the superposed harmonics. The results of a Fourier decomposition and an optimized simulation model verified the accuracy of the analysis as well as the effectiveness of the speed ripple reduction methods, respectively.
Balbin, Jessie R.; Padilla, Dionis A.; Fausto, Janette C.; Vergara, Ernesto M.; Garcia, Ramon G.; Delos Angeles, Bethsedea Joy S.; Dizon, Neil John A.; Mardo, Mark Kevin N.
2017-02-01
This research is about translating series of hand gesture to form a word and produce its equivalent sound on how it is read and said in Filipino accent using Support Vector Machine and Mel Frequency Cepstral Coefficient analysis. The concept is to detect Filipino speech input and translate the spoken words to their text form in Filipino. This study is trying to help the Filipino deaf community to impart their thoughts through the use of hand gestures and be able to communicate to people who do not know how to read hand gestures. This also helps literate deaf to simply read the spoken words relayed to them using the Filipino speech to text system.
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Wei Sun
2015-01-01
Full Text Available Electric power is a kind of unstorable energy concerning the national welfare and the people’s livelihood, the stability of which is attracting more and more attention. Because the short-term power load is always interfered by various external factors with the characteristics like high volatility and instability, a single model is not suitable for short-term load forecasting due to low accuracy. In order to solve this problem, this paper proposes a new model based on wavelet transform and the least squares support vector machine (LSSVM which is optimized by fruit fly algorithm (FOA for short-term load forecasting. Wavelet transform is used to remove error points and enhance the stability of the data. Fruit fly algorithm is applied to optimize the parameters of LSSVM, avoiding the randomness and inaccuracy to parameters setting. The result of implementation of short-term load forecasting demonstrates that the hybrid model can be used in the short-term forecasting of the power system.
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Xiang-ming Gao
2017-01-01
Full Text Available Predicting the output power of photovoltaic system with nonstationarity and randomness, an output power prediction model for grid-connected PV systems is proposed based on empirical mode decomposition (EMD and support vector machine (SVM optimized with an artificial bee colony (ABC algorithm. First, according to the weather forecast data sets on the prediction date, the time series data of output power on a similar day with 15-minute intervals are built. Second, the time series data of the output power are decomposed into a series of components, including some intrinsic mode components IMFn and a trend component Res, at different scales using EMD. The corresponding SVM prediction model is established for each IMF component and trend component, and the SVM model parameters are optimized with the artificial bee colony algorithm. Finally, the prediction results of each model are reconstructed, and the predicted values of the output power of the grid-connected PV system can be obtained. The prediction model is tested with actual data, and the results show that the power prediction model based on the EMD and ABC-SVM has a faster calculation speed and higher prediction accuracy than do the single SVM prediction model and the EMD-SVM prediction model without optimization.
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Chen Wang
2016-01-01
Full Text Available Power systems could be at risk when the power-grid collapse accident occurs. As a clean and renewable resource, wind energy plays an increasingly vital role in reducing air pollution and wind power generation becomes an important way to produce electrical power. Therefore, accurate wind power and wind speed forecasting are in need. In this research, a novel short-term wind speed forecasting portfolio has been proposed using the following three procedures: (I data preprocessing: apart from the regular normalization preprocessing, the data are preprocessed through empirical model decomposition (EMD, which reduces the effect of noise on the wind speed data; (II artificially intelligent parameter optimization introduction: the unknown parameters in the support vector machine (SVM model are optimized by the cuckoo search (CS algorithm; (III parameter optimization approach modification: an improved parameter optimization approach, called the SDCS model, based on the CS algorithm and the steepest descent (SD method is proposed. The comparison results show that the simple and effective portfolio EMD-SDCS-SVM produces promising predictions and has better performance than the individual forecasting components, with very small root mean squared errors and mean absolute percentage errors.
Owolabi, Taoreed O.; Akande, Kabiru O.; Olatunji, Sunday O.; Aldhafferi, Nahier; Alqahtani, Abdullah
2017-11-01
Titanium dioxide (TiO2) semiconductor is characterized with a wide band gap and attracts a significant attention for several applications that include solar cell carrier transportation and photo-catalysis. The tunable band gap of this semiconductor coupled with low cost, chemical stability and non-toxicity make it indispensable for these applications. Structural distortion always accompany TiO2 band gap tuning through doping and this present work utilizes the resulting structural lattice distortion to estimate band gap of doped TiO2 using support vector regression (SVR) coupled with novel gravitational search algorithm (GSA) for hyper-parameters optimization. In order to fully capture the non-linear relationship between lattice distortion and band gap, two SVR models were homogeneously hybridized and were subsequently optimized using GSA. GSA-HSVR (hybridized SVR) performs better than GSA-SVR model with performance improvement of 57.2% on the basis of root means square error reduction of the testing dataset. Effect of Co doping and Nitrogen-Iodine co-doping on band gap of TiO2 semiconductor was modeled and simulated. The obtained band gap estimates show excellent agreement with the values reported from the experiment. By implementing the models, band gap of doped TiO2 can be estimated with high level of precision and absorption ability of the semiconductor can be extended to visible region of the spectrum for improved properties and efficiency.
Gangsar, Purushottam; Tiwari, Rajiv
2017-09-01
This paper presents an investigation of vibration and current monitoring for effective fault prediction in induction motor (IM) by using multiclass support vector machine (MSVM) algorithms. Failures of IM may occur due to propagation of a mechanical or electrical fault. Hence, for timely detection of these faults, the vibration as well as current signals was acquired after multiple experiments of varying speeds and external torques from an experimental test rig. Here, total ten different fault conditions that frequently encountered in IM (four mechanical fault, five electrical fault conditions and one no defect condition) have been considered. In the case of stator winding fault, and phase unbalance and single phasing fault, different level of severity were also considered for the prediction. In this study, the identification has been performed of the mechanical and electrical faults, individually and collectively. Fault predictions have been performed using vibration signal alone, current signal alone and vibration-current signal concurrently. The one-versus-one MSVM has been trained at various operating conditions of IM using the radial basis function (RBF) kernel and tested for same conditions, which gives the result in the form of percentage fault prediction. The prediction performance is investigated for the wide range of RBF kernel parameter, i.e. gamma, and selected the best result for one optimal value of gamma for each case. Fault predictions has been performed and investigated for the wide range of operational speeds of the IM as well as external torques on the IM.
Duan, Li; Guo, Long; Liu, Ke; Liu, E-Hu; Li, Ping
2014-04-25
Citrus herbs have been widely used in traditional medicine and cuisine in China and other countries since the ancient time. However, the authentication and quality control of Citrus herbs has always been a challenging task due to their similar morphological characteristics and the diversity of the multi-components existed in the complicated matrix. In the present investigation, we developed a novel strategy to characterize and classify seven Citrus herbs based on chromatographic analysis and chemometric methods. Firstly, the chemical constituents in seven Citrus herbs were globally characterized by liquid chromatography combined with quadrupole time-of-flight mass spectrometry (LC-QTOF-MS). Based on their retention time, UV spectra and MS fragmentation behavior, a total of 75 compounds were identified or tentatively characterized in these herbal medicines. Secondly, a segmental monitoring method based on LC-variable wavelength detection was developed for simultaneous quantification of ten marker compounds in these Citrus herbs. Thirdly, based on the contents of the ten analytes, genetic algorithm optimized support vector machines (GA-SVM) was employed to differentiate and classify the 64 samples covering these seven herbs. The obtained classifier showed good prediction performance and the overall prediction accuracy reached 96.88%. The proposed strategy is expected to provide new insight for authentication and quality control of traditional herbs. Copyright © 2014 Elsevier B.V. All rights reserved.
Ghaedi, M; Dashtian, K; Ghaedi, A M; Dehghanian, N
2016-05-11
The aim of this work is the study of the predictive ability of a hybrid model of support vector regression with genetic algorithm optimization (GA-SVR) for the adsorption of malachite green (MG) onto multi-walled carbon nanotubes (MWCNTs). Various factors were investigated by central composite design and optimum conditions was set as: pH 8, 0.018 g MWCNTs, 8 mg L(-1) dye mixed with 50 mL solution thoroughly for 10 min. The Langmuir, Freundlich, Temkin and D-R isothermal models are applied to fitting the experimental data, and the data was well explained by the Langmuir model with a maximum adsorption capacity of 62.11-80.64 mg g(-1) in a short time at 25 °C. Kinetic studies at various adsorbent dosages and the initial MG concentration show that maximum MG removal was achieved within 10 min of the start of every experiment under most conditions. The adsorption obeys the pseudo-second-order rate equation in addition to the intraparticle diffusion model. The optimal parameters (C of 0.2509, σ(2) of 0.1288 and ε of 0.2018) for the SVR model were obtained based on the GA. For the testing data set, MSE values of 0.0034 and the coefficient of determination (R(2)) values of 0.9195 were achieved.
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Dongxiao Niu
2018-01-01
Full Text Available The electric power industry is of great significance in promoting social and economic development and improving people’s living standards. Power grid construction is a necessary part of infrastructure construction, whose sustainability plays an important role in economic development, environmental protection and social progress. In order to effectively evaluate the sustainability of power grid construction projects, in this paper, we first identified 17 criteria from four dimensions including economy, technology, society and environment to establish the evaluation criteria system. After that, the grey incidence analysis was used to modify the traditional Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS, which made it possible to evaluate the sustainability of electric power construction projects based on visual angle of similarity and nearness. Then, in order to simplify the procedure of experts scoring and computation, on the basis of evaluation results of the improved TOPSIS, the model using Modified Fly Optimization Algorithm (MFOA to optimize the Least Square Support Vector Machine (LSSVM was established. Finally, a numerical example was given to demonstrate the effectiveness of the proposed model.
Hironaka, Kohei; Yamazaki, Yoshiyuki; Hirai, Yukihiko; Yamamoto, Motoko; Miyake, Noriko; Miyake, Koichi; Okada, Takashi; Morita, Akio; Shimada, Takashi
2015-08-18
Metachromatic leukodystrophy (MLD) is a lysosomal storage disease caused by a functional deficiency in human arylsulfatase A (hASA). We recently reported that ependymal cells and the choroid plexus are selectively transduced by intracerebroventricular (ICV) injection of adeno-associated virus serotype 1 (AAV1) vector and serve as a biological reservoir for the secretion of lysosomal enzymes into the cerebrospinal fluid (CSF). In the present study, we examined the feasibility of this AAV-mediated gene therapy to treat MLD model mice. Preliminary experiments showed that the hASA level in the CSF after ICV injection of self-complementary (sc) AAV1 was much higher than in mice injected with single-stranded AAV1 or scAAV9. However, when 18-week-old MLD mice were treated with ICV injection of scAAV1, the concentration of hASA in the CSF gradually decreased and was not detectable at 12 weeks after injection, probably due to the development of anti-hASA antibodies. As a result, the sulfatide levels in brain tissues of treated MLD mice were only slightly reduced compared with those of untreated MLD mice. These results suggest that this approach is potentially promising for treating MLD, but that controlling the immune response appears to be crucial for long-term expression of therapeutic proteins in the CSF.
Hironaka, Kohei; Yamazaki, Yoshiyuki; Hirai, Yukihiko; Yamamoto, Motoko; Miyake, Noriko; Miyake, Koichi; Okada, Takashi; Morita, Akio; Shimada, Takashi
2015-01-01
Metachromatic leukodystrophy (MLD) is a lysosomal storage disease caused by a functional deficiency in human arylsulfatase A (hASA). We recently reported that ependymal cells and the choroid plexus are selectively transduced by intracerebroventricular (ICV) injection of adeno-associated virus serotype 1 (AAV1) vector and serve as a biological reservoir for the secretion of lysosomal enzymes into the cerebrospinal fluid (CSF). In the present study, we examined the feasibility of this AAV-mediated gene therapy to treat MLD model mice. Preliminary experiments showed that the hASA level in the CSF after ICV injection of self-complementary (sc) AAV1 was much higher than in mice injected with single-stranded AAV1 or scAAV9. However, when 18-week-old MLD mice were treated with ICV injection of scAAV1, the concentration of hASA in the CSF gradually decreased and was not detectable at 12 weeks after injection, probably due to the development of anti-hASA antibodies. As a result, the sulfatide levels in brain tissues of treated MLD mice were only slightly reduced compared with those of untreated MLD mice. These results suggest that this approach is potentially promising for treating MLD, but that controlling the immune response appears to be crucial for long-term expression of therapeutic proteins in the CSF. PMID:26283284
Kehely, Anne; Bates, Peter C; Frewer, Paul; Birkett, Martin; Blum, Werner F; Mamessier, Pascale; Ezzat, Shereen; Ho, Ken K Y; Lombardi, Gaetano; Luger, Anton; Marek, Josef; Russell-Jones, David; Sönksen, Peter; Attanasio, Andrea F
2002-05-01
The aim of GH replacement therapy in GH-deficient adults is to optimize response with minimum incidence of adverse reactions, but optimal therapy regimens are still to be established. This two-arm parallel study examined effects of two GH dose algorithms in adults with GH deficiency of adult or childhood onset. Patients on low dose (LD; n = 302) received GH at 3 microg/kg per day for 3 months increasing to 6 microg/kg per day for 3 months, and those on conventional dose (CD; n = 293) started on 6 microg/kg per day for 3 months increasing to 12 microg/kg per day for 3 months. The proportion of patients completing therapy was greater for the LD group than the CD group for the first 3 months (93.0% vs. 88.1%; P = 0.037) and overall for the 6 months (90.7% vs. 84.0%; P = 0.013). Both dose groups showed significant increases in lean body mass and decreases in fat mass for all time points. Percent increase in lean body mass was less with LD than CD over the first 3 months (2.43 +/- 4.33 vs. 3.58 +/- 4.69%; P = 0.006) but not overall for the 6-month period (4.38% +/- 5.34% vs. 5.21% +/- 5.99%; P = 0.141). Percent decrease in fat mass was less with LD than CD for the first 3 months (-2.81% +/- 7.81% vs. -5.53% +/- 8.64%; P only adverse event that occurred significantly less frequently with LD than with CD. Calculated changes based on gender and onset indicated greater changes in males than females for body composition, but there was little difference in GH-related adverse events between males and females. The lower starting dose with dose titration appeared more favorable, but differences in response between genders and onset of GH deficiency need to be taken into account when setting an individual dose regimen.
The Neural Support Vector Machine
Wiering, Marco; van der Ree, Michiel; Embrechts, Mark; Stollenga, Marijn; Meijster, Arnold; Nolte, A; Schomaker, Lambertus
2013-01-01
This paper describes a new machine learning algorithm for regression and dimensionality reduction tasks. The Neural Support Vector Machine (NSVM) is a hybrid learning algorithm consisting of neural networks and support vector machines (SVMs). The output of the NSVM is given by SVMs that take a
Zhang, Haipeng; Fu, Tong; Zhang, Zhiru; Fan, Zhimin; Zheng, Chao; Han, Bing
2014-08-01
To explore the value of application of support vector machine-recursive feature elimination (SVM-RFE) method in Raman spectroscopy for differential diagnosis of benign and malignant breast diseases. Fresh breast tissue samples of 168 patients (all female; ages 22-75) were obtained by routine surgical resection from May 2011 to May 2012 at the Department of Breast Surgery, the First Hospital of Jilin University. Among them, there were 51 normal tissues, 66 benign and 51 malignant breast lesions. All the specimens were assessed by Raman spectroscopy, and the SVM-RFE algorithm was used to process the data and build the mathematical model. Mahalanobis distance and spectral residuals were used as discriminating criteria to evaluate this data-processing method. 1 800 Raman spectra were acquired from the fresh samples of human breast tissues. Based on spectral profiles, the presence of 1 078, 1 267, 1 301, 1 437, 1 653, and 1 743 cm(-1) peaks were identified in the normal tissues; and 1 281, 1 341, 1 381, 1 417, 1 465, 1 530, and 1 637 cm(-1) peaks were found in the benign and malignant tissues. The main characteristic peaks differentiating benign and malignant lesions were 1 340 and 1 480 cm(-1). The accuracy of SVM-RFE in discriminating normal and malignant lesions was 100.0%, while that in the assessment of benign lesions was 93.0%. There are distinct differences among the Raman spectra of normal, benign and malignant breast tissues, and SVM-RFE method can be used to build differentiation model of breast lesions.
Knee replacement is surgery for people with severe knee damage. Knee replacement can relieve pain and allow you to ... Your doctor may recommend it if you have knee pain and medicine and other treatments are not ...
DEFF Research Database (Denmark)
Ohm-Laursen, Line; Nielsen, Morten; Larsen, Stine R
2006-01-01
Antibody diversity is created by imprecise joining of the variability (V), diversity (D) and joining (J) gene segments of the heavy and light chain loci. Analysis of rearrangements is complicated by somatic hypermutations and uncertainty concerning the sources of gene segments and the precise way...... in which they recombine. It has been suggested that D genes with irregular recombination signal sequences (DIR) and chromosome 15 open reading frames (OR15) can replace conventional D genes, that two D genes or inverted D genes may be used and that the repertoire can be further diversified by heavy chain V...... gene (VH) replacement. Safe conclusions require large, well-defined sequence samples and algorithms minimizing stochastic assignment of segments. Two computer programs were developed for analysis of heavy chain joints. JointHMM is a profile hidden Markow model, while JointML is a maximum...
Support vector machine (SVM) was applied for land-cover characterization using MODIS time-series data. Classification performance was examined with respect to training sample size, sample variability, and landscape homogeneity (purity). The results were compared to two convention...
High-Resolution Source Localization Algorithm Based on the Conjugate Gradient
Directory of Open Access Journals (Sweden)
Sylvie Marcos
2007-01-01
Full Text Available This paper proposes a new algorithm for the direction of arrival (DOA estimation of P radiating sources. Unlike the classical subspace-based methods, it does not resort to the eigendecomposition of the covariance matrix of the received data. Indeed, the proposed algorithm involves the building of the signal subspace from the residual vectors of the conjugate gradient (CG method. This approach is based on the same recently developed procedure which uses a noneigenvector basis derived from the auxiliary vectors (AV. The AV basis calculation algorithm is replaced by the residual vectors of the CG algorithm. Then, successive orthogonal gradient vectors are derived to form a basis of the signal subspace. A comprehensive performance comparison of the proposed algorithm with the well-known MUSIC and ESPRIT algorithms and the auxiliary vectors (AV-based algorithm was conducted. It shows clearly the high performance of the proposed CG-based method in terms of the resolution capability of closely spaced uncorrelated and correlated sources with a small number of snapshots and at low signal-to-noise ratio (SNR.
Montuno, Michael A; Kohner, Andrew B; Foote, Kelly D; Okun, Michael S
2013-01-01
Deep brain stimulation (DBS) is an effective technique that has been utilized to treat advanced and medication-refractory movement and psychiatric disorders. In order to avoid implanted pulse generator (IPG) failure and consequent adverse symptoms, a better understanding of IPG battery longevity and management is necessary. Existing methods for battery estimation lack the specificity required for clinical incorporation. Technical challenges prevent higher accuracy longevity estimations, and a better approach to managing end of DBS battery life is needed. The literature was reviewed and DBS battery estimators were constructed by the authors and made available on the web at http://mdc.mbi.ufl.edu/surgery/dbs-battery-estimator. A clinical algorithm for management of DBS battery life was constructed. The algorithm takes into account battery estimations and clinical symptoms. Existing methods of DBS battery life estimation utilize an interpolation of averaged current drains to calculate how long a battery will last. Unfortunately, this technique can only provide general approximations. There are inherent errors in this technique, and these errors compound with each iteration of the battery estimation. Some of these errors cannot be accounted for in the estimation process, and some of the errors stem from device variation, battery voltage dependence, battery usage, battery chemistry, impedance fluctuations, interpolation error, usage patterns, and self-discharge. We present web-based battery estimators along with an algorithm for clinical management. We discuss the perils of using a battery estimator without taking into account the clinical picture. Future work will be needed to provide more reliable management of implanted device batteries; however, implementation of a clinical algorithm that accounts for both estimated battery life and for patient symptoms should improve the care of DBS patients. © 2012 International Neuromodulation Society.
Hoffmann, Banesh
1975-01-01
From his unusual beginning in ""Defining a vector"" to his final comments on ""What then is a vector?"" author Banesh Hoffmann has written a book that is provocative and unconventional. In his emphasis on the unresolved issue of defining a vector, Hoffmann mixes pure and applied mathematics without using calculus. The result is a treatment that can serve as a supplement and corrective to textbooks, as well as collateral reading in all courses that deal with vectors. Major topics include vectors and the parallelogram law; algebraic notation and basic ideas; vector algebra; scalars and scalar p
Newell, Homer E
2006-01-01
When employed with skill and understanding, vector analysis can be a practical and powerful tool. This text develops the algebra and calculus of vectors in a manner useful to physicists and engineers. Numerous exercises (with answers) not only provide practice in manipulation but also help establish students' physical and geometric intuition in regard to vectors and vector concepts.Part I, the basic portion of the text, consists of a thorough treatment of vector algebra and the vector calculus. Part II presents the illustrative matter, demonstrating applications to kinematics, mechanics, and e
Siegel, J.; Siegel, Edward Carl-Ludwig
2011-03-01
Cook-Levin computational-"complexity"(C-C) algorithmic-equivalence reduction-theorem reducibility equivalence to renormalization-(semi)-group phase-transitions critical-phenomena statistical-physics universality-classes fixed-points, is exploited with Gauss modular/clock-arithmetic/model congruences = signal X noise PRODUCT reinterpretation. Siegel-Baez FUZZYICS=CATEGORYICS(SON of ``TRIZ''): Category-Semantics(C-S) tabular list-format truth-table matrix analytics predicts and implements "noise"-induced phase-transitions (NITs) to accelerate versus to decelerate Harel [Algorithmics(1987)]-Sipser[Intro. Theory Computation(1997) algorithmic C-C: "NIT-picking" to optimize optimization-problems optimally(OOPO). Versus iso-"noise" power-spectrum quantitative-only amplitude/magnitude-only variation stochastic-resonance, this "NIT-picking" is "noise" power-spectrum QUALitative-type variation via quantitative critical-exponents variation. Computer-"science" algorithmic C-C models: Turing-machine, finite-state-models/automata, are identified as early-days once-workable but NOW ONLY LIMITING CRUTCHES IMPEDING latter-days new-insights!!!
Estimation of Motion Vector Fields
DEFF Research Database (Denmark)
Larsen, Rasmus
1993-01-01
This paper presents an approach to the estimation of 2-D motion vector fields from time varying image sequences. We use a piecewise smooth model based on coupled vector/binary Markov random fields. We find the maximum a posteriori solution by simulated annealing. The algorithm generate sample...
... problems Bleeding , blood clot , or infection Risks of shoulder replacement surgery are: Allergic reaction to the artificial joint Blood vessel damage during surgery Bone break during surgery Nerve damage during surgery Dislocation of the artificial joint Loosening of the implant ...
... ankle replacement surgery are: Ankle weakness, stiffness, or instability Loosening of the artificial joint over time Skin ... Benjamin Ma, MD, Professor, Chief, Sports Medicine and Shoulder Service, UCSF Department of Orthopaedic Surgery, San Francisco, ...
Directory of Open Access Journals (Sweden)
Vitaly Stepashin
2017-01-01
Full Text Available УДК 343.24The subject. The article deals with the problem of the use of "substitute" penalties.The purpose of the article is to identify criminal and legal criteria for: selecting the replacement punishment; proportionality replacement leave punishment to others (the formalization of replacement; actually increasing the punishment (worsening of legal situation of the convicted.Methodology.The author uses the method of analysis and synthesis, formal legal method.Results. Replacing the punishment more severe as a result of malicious evasion from serving accused designated penalty requires the optimization of the following areas: 1 the selection of a substitute punishment; 2 replacement of proportionality is serving a sentence other (formalization of replacement; 3 ensuring the actual toughening penalties (deterioration of the legal status of the convict. It is important that the first two requirements pro-vide savings of repression in the implementation of the replacement of one form of punishment to others.Replacement of punishment on their own do not have any specifics. However, it is necessary to compare them with the contents of the punishment, which the convict from serving maliciously evaded. First, substitute the punishment should assume a more significant range of restrictions and deprivation of certain rights of the convict. Second, the perfor-mance characteristics of order substitute the punishment should assume guarantee imple-mentation of the new measures.With regard to replacing all forms of punishment are set significant limitations in the application that, in some cases, eliminates the possibility of replacement of the sentence, from serving where there has been willful evasion, a stricter measure of state coercion. It is important in the context of the topic and the possibility of a sentence of imprisonment as a substitute punishment in cases where the original purpose of the strict measures excluded. It is noteworthy that the
Wolstenholme, E Œ
1978-01-01
Elementary Vectors, Third Edition serves as an introductory course in vector analysis and is intended to present the theoretical and application aspects of vectors. The book covers topics that rigorously explain and provide definitions, principles, equations, and methods in vector analysis. Applications of vector methods to simple kinematical and dynamical problems; central forces and orbits; and solutions to geometrical problems are discussed as well. This edition of the text also provides an appendix, intended for students, which the author hopes to bridge the gap between theory and appl
"Analytical" vector-functions I
Todorov, Vladimir Todorov
2017-12-01
In this note we try to give a new (or different) approach to the investigation of analytical vector functions. More precisely a notion of a power xn; n ∈ ℕ+ of a vector x ∈ ℝ3 is introduced which allows to define an "analytical" function f : ℝ3 → ℝ3. Let furthermore f (ξ )= ∑n =0 ∞ anξn be an analytical function of the real variable ξ. Here we replace the power ξn of the number ξ with the power of a vector x ∈ ℝ3 to obtain a vector "power series" f (x )= ∑n =0 ∞ anxn . We research some properties of the vector series as well as some applications of this idea. Note that an "analytical" vector function does not depend of any basis, which may be used in research into some problems in physics.
Adenovirus Vectors for Gene Therapy, Vaccination and Cancer Gene Therapy
Wold, William S. M.; Toth, Karoly
2013-01-01
Adenovirus vectors are the most commonly employed vector for cancer gene therapy. They are also used for gene therapy and as vaccines to express foreign antigens. Adenovirus vectors can be replication-defective; certain essential viral genes are deleted and replaced by a cassette that expresses a foreign therapeutic gene. Such vectors are used for gene therapy, as vaccines, and for cancer therapy. Replication-competent (oncolytic) vectors are employed for cancer gene therapy. Oncolytic vector...
VECTOR MAPS IN MOBILE ROBOTICS
Directory of Open Access Journals (Sweden)
Ales Jelinek
2015-12-01
Full Text Available The aim of this paper is to provide a brief overview of vector map techniques used in mobile robotics and to present current state of the research in this field at the Brno University of Technology. Vector maps are described as a part of the simultaneous localization and mapping (SLAM problem in the environment without artificial landmarks or global navigation system. The paper describes algorithms from data acquisition to map building but particular emphasis is put on segmentation, line extraction and scan matching algorithms. All significant algorithms are illustrated with experimental results.
Brand, Louis
2006-01-01
The use of vectors not only simplifies treatments of differential geometry, mechanics, hydrodynamics, and electrodynamics, but also makes mathematical and physical concepts more tangible and easy to grasp. This text for undergraduates was designed as a short introductory course to give students the tools of vector algebra and calculus, as well as a brief glimpse into these subjects' manifold applications. The applications are developed to the extent that the uses of the potential function, both scalar and vector, are fully illustrated. Moreover, the basic postulates of vector analysis are brou
Energy Technology Data Exchange (ETDEWEB)
Souza, Claudio Eduardo Scriptori de
1996-02-01
In the Operating Center of Electrical Energy System has been every time more and more important the understanding of the difficulties related to the electrical power behavior. In order to have adequate operation of the system the state estimation process is very important. However before performing the system state estimation owe needs to know if the system is observable otherwise the estimation will no be possible. This work has a main objective, to develop a software that allows one to visualize the whole network in case that network is observable or the observable island of the entire network. As theoretical background the theories and algorithm using the triangular factorization of gain matrix as well as the concepts contained on factorization path developed by Bretas et alli were used. The algorithm developed by him was adapted to the Windows graphical form so that the numerical results of the network observability are shown in the computer screen in graphical form. This algorithm is essentially instead of numerical as the one based on the factorization of gain matrix only. To implement the algorithm previously referred it was used the Borland C++ compiler for windows version 4.0 due to the facilities for sources generation it presents. The results of the tests in the network with 6, 14 and 30 bus leads to: (1) the simplification of observability analysis, using sparse vectors and triangular factorization of the gain matrix; (2) the behavior similarity of the three testes systems with effective clues that the routine developed works well for any systems mainly for systems with bigger quantities of bus and lines; (3) the alternative way of presenting numerical results using the program developed here in graphical forms. (author)
Guilfoyle, R.A.; Smith, L.M.
1994-12-27
A vector comprising a filamentous phage sequence containing a first copy of filamentous phage gene X and other sequences necessary for the phage to propagate is disclosed. The vector also contains a second copy of filamentous phage gene X downstream from a promoter capable of promoting transcription in a bacterial host. In a preferred form of the present invention, the filamentous phage is M13 and the vector additionally includes a restriction endonuclease site located in such a manner as to substantially inactivate the second gene X when a DNA sequence is inserted into the restriction site. 2 figures.
Guilfoyle, Richard A.; Smith, Lloyd M.
1994-01-01
A vector comprising a filamentous phage sequence containing a first copy of filamentous phage gene X and other sequences necessary for the phage to propagate is disclosed. The vector also contains a second copy of filamentous phage gene X downstream from a promoter capable of promoting transcription in a bacterial host. In a preferred form of the present invention, the filamentous phage is M13 and the vector additionally includes a restriction endonuclease site located in such a manner as to substantially inactivate the second gene X when a DNA sequence is inserted into the restriction site.
Algorithms and Algorithmic Languages.
Veselov, V. M.; Koprov, V. M.
This paper is intended as an introduction to a number of problems connected with the description of algorithms and algorithmic languages, particularly the syntaxes and semantics of algorithmic languages. The terms "letter, word, alphabet" are defined and described. The concept of the algorithm is defined and the relation between the algorithm and…
Directory of Open Access Journals (Sweden)
Xingang Fu
2016-04-01
Full Text Available This paper investigates a novel recurrent neural network (NN-based vector control approach for single-phase grid-connected converters (GCCs with L (inductor, LC (inductor-capacitor and LCL (inductor-capacitor-inductor filters and provides their comparison study with the conventional standard vector control method. A single neural network controller replaces two current-loop PI controllers, and the NN training approximates the optimal control for the single-phase GCC system. The Levenberg–Marquardt (LM algorithm was used to train the NN controller based on the complete system equations without any decoupling policies. The proposed NN approach can solve the decoupling problem associated with the conventional vector control methods for L, LC and LCL-filter-based single-phase GCCs. Both simulation study and hardware experiments demonstrate that the neural network vector controller shows much more improved performance than that of conventional vector controllers, including faster response speed and lower overshoot. Especially, NN vector control could achieve very good performance using low switch frequency. More importantly, the neural network vector controller is a damping free controller, which is generally required by a conventional vector controller for an LCL-filter-based single-phase grid-connected converter and, therefore, can overcome the inefficiency problem caused by damping policies.
Active set support vector regression.
Musicant, David R; Feinberg, Alexander
2004-03-01
This paper presents active set support vector regression (ASVR), a new active set strategy to solve a straightforward reformulation of the standard support vector regression problem. This new algorithm is based on the successful ASVM algorithm for classification problems, and consists of solving a finite number of linear equations with a typically large dimensionality equal to the number of points to be approximated. However, by making use of the Sherman-Morrison-Woodbury formula, a much smaller matrix of the order of the original input space is inverted at each step. The algorithm requires no specialized quadratic or linear programming code, but merely a linear equation solver which is publicly available. ASVR is extremely fast, produces comparable generalization error to other popular algorithms, and is available on the web for download.
Robinson, Gilbert de B
2011-01-01
This brief undergraduate-level text by a prominent Cambridge-educated mathematician explores the relationship between algebra and geometry. An elementary course in plane geometry is the sole requirement for Gilbert de B. Robinson's text, which is the result of several years of teaching and learning the most effective methods from discussions with students. Topics include lines and planes, determinants and linear equations, matrices, groups and linear transformations, and vectors and vector spaces. Additional subjects range from conics and quadrics to homogeneous coordinates and projective geom
Directory of Open Access Journals (Sweden)
Jiangqing Liao
2016-11-01
Full Text Available Ultrasonic-assisted extraction (UAE of quercetin and rutin from the stalks of Euonymus alatus (Thunb. Sieb in our laboratory, which aimed at evaluating and optimizing the process parameters, was investigated in this work. In addition, process parameters such as ethanol solution concentration, solvent volume/sample ratio, ultrasound power and extraction time, ultrasound frequency and extraction temperature were also first applied for evaluating the influence of extraction of quercetin and rutin. Optimum process parameters obtained were: ethanol solution 60%, extraction time 30 min, solvent volume/sample ratio 40 mL/g, ultrasound power 200 W, extraction temperature 30 °C and ultrasound frequency 80 kHz. Further a hybrid predictive model, which is based on least squares support vector machine (LS-SVM in combination with improved fruit fly optimization algorithm (IFOA, was first used to predict the UAE process. The established IFOA-LS-SVM model, in which six process parameters and extraction yields of quercetin and rutin were used as input variables and output variables, respectively, successfully predicted the extraction yields of quercetin and rutin with a low error. Moreover, by comparison with SVM, LS-SVM and multiple regression models, IFOA-LS-SVM model has higher accuracy and faster convergence. Results proved that the proposed model is capable of predicting extraction yields of quercetin and rutin in UAE process.
GPU Accelerated Vector Median Filter
Aras, Rifat; Shen, Yuzhong
2011-01-01
Noise reduction is an important step for most image processing tasks. For three channel color images, a widely used technique is vector median filter in which color values of pixels are treated as 3-component vectors. Vector median filters are computationally expensive; for a window size of n x n, each of the n(sup 2) vectors has to be compared with other n(sup 2) - 1 vectors in distances. General purpose computation on graphics processing units (GPUs) is the paradigm of utilizing high-performance many-core GPU architectures for computation tasks that are normally handled by CPUs. In this work. NVIDIA's Compute Unified Device Architecture (CUDA) paradigm is used to accelerate vector median filtering. which has to the best of our knowledge never been done before. The performance of GPU accelerated vector median filter is compared to that of the CPU and MPI-based versions for different image and window sizes, Initial findings of the study showed 100x improvement of performance of vector median filter implementation on GPUs over CPU implementations and further speed-up is expected after more extensive optimizations of the GPU algorithm .
Thomas, E. G. F.
2012-01-01
This paper deals with the theory of integration of scalar functions with respect to a measure with values in a, not necessarily locally convex, topological vector space. It focuses on the extension of such integrals from bounded measurable functions to the class of integrable functions, proving
Inflight parity vector compensation for FDI
Hall, S. R.; Motyka, P.; Gai, E.; Deyst, J. J., Jr.
The performance of a failure detection and isolation (FDI) algorithm applied to a redundant strapdown inertial measurement unit (IMU) is limited by sensor errors such as input axis misalignment, scale factor errors, and biases. This paper presents a technique for improving the performance of FDI algorithms applied to redundant strapdown IMUs. A Kalman filter provides estimates of those linear combinations of sensor errors that affect the parity vector. These estimates are used to form a compensated parity vector which does not include the effects of sensor errors. The compensated parity vector is then used in place of the uncompensated parity vector to make FDI decisions. Simulation results are presented in which the algorithm is tested in a realistic flight environment that includes vehicle maneuvers, the effects of turbulence, and sensor failures. The results show that the algorithm can significantly improve FDI performance, especially during vehicle maneuvers.
An introduction to vectors, vector operators and vector analysis
Joag, Pramod S
2016-01-01
Ideal for undergraduate and graduate students of science and engineering, this book covers fundamental concepts of vectors and their applications in a single volume. The first unit deals with basic formulation, both conceptual and theoretical. It discusses applications of algebraic operations, Levi-Civita notation, and curvilinear coordinate systems like spherical polar and parabolic systems and structures, and analytical geometry of curves and surfaces. The second unit delves into the algebra of operators and their types and also explains the equivalence between the algebra of vector operators and the algebra of matrices. Formulation of eigen vectors and eigen values of a linear vector operator are elaborated using vector algebra. The third unit deals with vector analysis, discussing vector valued functions of a scalar variable and functions of vector argument (both scalar valued and vector valued), thus covering both the scalar vector fields and vector integration.
DEFF Research Database (Denmark)
2012-01-01
for generation of a reference beam, a detector system comprising a first detector arrangement arranged in such a way that the signal beam and the reference beam are incident upon the first detector arrangement with the reference beam propagating at an angle relative to a signal beam, and wherein the first......The present invention relates to a compact, reliable and low-cost vector velocimeter for example for determining velocities of particles suspended in a gas or fluid flow, or for determining velocity, displacement, rotation, or vibration of a solid surface, the vector velocimeter comprising a laser...... assembly for emission of a measurement beam for illumination of an object in a measurement volume with coherent light whereby a signal beam emanating from the object in the measurement volume is formed in response to illumination of the object by the measurement beam, a reference beam generator...
Model Predictive Engine Air-Ratio Control Using Online Sequential Relevance Vector Machine
Directory of Open Access Journals (Sweden)
Hang-cheong Wong
2012-01-01
Full Text Available Engine power, brake-specific fuel consumption, and emissions relate closely to air ratio (i.e., lambda among all the engine variables. An accurate and adaptive model for lambda prediction is essential to effective lambda control for long term. This paper utilizes an emerging technique, relevance vector machine (RVM, to build a reliable time-dependent lambda model which can be continually updated whenever a sample is added to, or removed from, the estimated lambda model. The paper also presents a new model predictive control (MPC algorithm for air-ratio regulation based on RVM. This study shows that the accuracy, training, and updating time of the RVM model are superior to the latest modelling methods, such as diagonal recurrent neural network (DRNN and decremental least-squares support vector machine (DLSSVM. Moreover, the control algorithm has been implemented on a real car to test. Experimental results reveal that the control performance of the proposed relevance vector machine model predictive controller (RVMMPC is also superior to DRNNMPC, support vector machine-based MPC, and conventional proportional-integral (PI controller in production cars. Therefore, the proposed RVMMPC is a promising scheme to replace conventional PI controller for engine air-ratio control.
Interior point decoding for linear vector channels
Energy Technology Data Exchange (ETDEWEB)
Wadayama, T [Nagoya Institute of Technology, Gokiso, Showa-ku, Nagoya, Aichi, 466-8555 (Japan)], E-mail: wadayama@nitech.ac.jp
2008-01-15
In this paper, a novel decoding algorithm for low-density parity-check (LDPC) codes based on convex optimization is presented. The decoding algorithm, called interior point decoding, is designed for linear vector channels. The linear vector channels include many practically important channels such as inter-symbol interference channels and partial response channels. It is shown that the maximum likelihood decoding (MLD) rule for a linear vector channel can be relaxed to a convex optimization problem, which is called a relaxed MLD problem.
Fischer, J.; Doolan, C.
2017-07-01
The effect of acoustic reflections on beamforming maps and their correction is investigated in this paper. By replacing the usual steering vector expression in the beamforming algorithm with an adapted one, the effect of reflections can be reduced. Two formulations of the steering vectors are considered. The first makes use of an experimental Green's function, which is obtained by measuring simultaneously the signal of a speaker and of a 31-channel acoustic array in a hard-walled test-section. The second formulation is based on the assumption that the reflections can be modeled by a set of monopoles located at the image source positions. This numerical model is first validated by comparing the obtained Green's function with the experimental one. Then, the beamforming algorithm is modified by using the different steering vector formulations. In addition, the deconvolution algorithm Clean-SC has been used and implemented with the different formulations. The best results in terms of location and resolution accuracy were obtained when using the experimental Green's function formulation.
Robust Pseudo-Hierarchical Support Vector Clustering
DEFF Research Database (Denmark)
Hansen, Michael Sass; Sjöstrand, Karl; Olafsdóttir, Hildur
2007-01-01
Support vector clustering (SVC) has proven an efficient algorithm for clustering of noisy and high-dimensional data sets, with applications within many fields of research. An inherent problem, however, has been setting the parameters of the SVC algorithm. Using the recent emergence of a method fo...
... activities following total knee replacement include unlimited walking, swimming, golf, driving, light hiking, biking, ballroom dancing, and ... Total Knee Replacement cont. Preparing for Surgery Medical Evaluation If you decide to have total knee replacement ...
Smoking cessation - nicotine replacement; Tobacco - nicotine replacement therapy ... Before you start using a nicotine replacement product, here are some things to know: The more cigarettes you smoke, the higher the dose you may need to ...
TV-L1 optical flow for vector valued images
DEFF Research Database (Denmark)
Rakêt, Lars Lau; Roholm, Lars; Nielsen, Mads
2011-01-01
a generalized algorithm that works on vector valued images, by means of a generalized projection step. We give examples of calculations of flows for a number of multi- dimensional constancy assumptions, e.g. gradient and RGB, and show how the developed methodology expands to any kind of vector valued images....... The resulting algorithms have the same degree of parallelism as the case of one-dimensional images, and we have produced an efficient GPU implementation, that can take vector valued images with vectors of any dimension. Finally we demonstrate how these algorithms generally produce better flows than the original...
DEFF Research Database (Denmark)
Mahnke, Martina; Uprichard, Emma
2014-01-01
changes: it’s not the ocean, it’s the internet we’re talking about, and it’s not a TV show producer, but algorithms that constitute a sort of invisible wall. Building on this assumption, most research is trying to ‘tame the algorithmic tiger’. While this is a valuable and often inspiring approach, we...... would like to emphasize another side to the algorithmic everyday life. We argue that algorithms can instigate and facilitate imagination, creativity, and frivolity, while saying something that is simultaneously old and new, always almost repeating what was before but never quite returning. We show...... this by threading together stimulating quotes and screenshots from Google’s autocomplete algorithms. In doing so, we invite the reader to re-explore Google’s autocomplete algorithms in a creative, playful, and reflexive way, thereby rendering more visible some of the excitement and frivolity that comes from being...
Jakobović, Domagoj; Golub, Marin
1999-01-01
In this paper we introduce an adaptive, 'self-contained' genetic algorithm (GA) with steady-state selection. This variant of GA utilizes empirically based methods for calculating its control parameters. The adaptive algorithm estimates the percentage of the population to be replaced with new individuals (generation gap). It chooses the solutions for crossover and varies the number of mutations, ail regarding the current population state. The state of the population is evaluated by observing s...
The asymptotic probabilistic genetic algorithm
Galushin, P.; Semenkin, E.
2009-01-01
This paper proposes the modification of probabilistic genetic algorithm, which uses genetic operators, not affecting the particular solutions, but the probabilities distribution of solution vector's components. This paper also compares the reliability and efficiency of the base algorithm and proposed modification using the set of test optimization problems and bank loan portfolio problem.
Algorithms Introduction to Algorithms
Indian Academy of Sciences (India)
Home; Journals; Resonance – Journal of Science Education; Volume 1; Issue 1. Algorithms Introduction to Algorithms. R K Shyamasundar. Series Article Volume 1 Issue 1 January 1996 pp 20-27. Fulltext. Click here to view fulltext PDF. Permanent link: http://www.ias.ac.in/article/fulltext/reso/001/01/0020-0027 ...
GAPS IN SUPPORT VECTOR OPTIMIZATION
Energy Technology Data Exchange (ETDEWEB)
STEINWART, INGO [Los Alamos National Laboratory; HUSH, DON [Los Alamos National Laboratory; SCOVEL, CLINT [Los Alamos National Laboratory; LIST, NICOLAS [Los Alamos National Laboratory
2007-01-29
We show that the stopping criteria used in many support vector machine (SVM) algorithms working on the dual can be interpreted as primal optimality bounds which in turn are known to be important for the statistical analysis of SVMs. To this end we revisit the duality theory underlying the derivation of the dual and show that in many interesting cases primal optimality bounds are the same as known dual optimality bounds.
Deep Learning for Person Reidentification Using Support Vector Machines
National Research Council Canada - National Science Library
Mengyu Xu; Zhenmin Tang; Yazhou Yao; Lingxiang Yao; Huafeng Liu; Jingsong Xu
2017-01-01
.... Different from previous works, we represent the pairs of pedestrian images as new resized input and use linear Support Vector Machine to replace softmax activation function for similarity learning...
An improved wave-vector frequency-domain method for nonlinear wave modeling.
Jing, Yun; Tao, Molei; Cannata, Jonathan
2014-03-01
In this paper, a recently developed wave-vector frequency-domain method for nonlinear wave modeling is improved and verified by numerical simulations and underwater experiments. Higher order numeric schemes are proposed that significantly increase the modeling accuracy, thereby allowing for a larger step size and shorter computation time. The improved algorithms replace the left-point Riemann sum in the original algorithm by the trapezoidal or Simpson's integration. Plane waves and a phased array were first studied to numerically validate the model. It is shown that the left-point Riemann sum, trapezoidal, and Simpson's integration have first-, second-, and third-order global accuracy, respectively. A highly focused therapeutic transducer was then used for experimental verifications. Short high-intensity pulses were generated. 2-D scans were conducted at a prefocal plane, which were later used as the input to the numerical model to predict the acoustic field at other planes. Good agreement is observed between simulations and experiments.
Doubly Constrained Robust Blind Beamforming Algorithm
Directory of Open Access Journals (Sweden)
Xin Song
2013-01-01
Full Text Available We propose doubly constrained robust least-squares constant modulus algorithm (LSCMA to solve the problem of signal steering vector mismatches via the Bayesian method and worst-case performance optimization, which is based on the mismatches between the actual and presumed steering vectors. The weight vector is iteratively updated with penalty for the worst-case signal steering vector by the partial Taylor-series expansion and Lagrange multiplier method, in which the Lagrange multipliers can be optimally derived and incorporated at each step. A theoretical analysis for our proposed algorithm in terms of complexity cost, convergence performance, and SINR performance is presented in this paper. In contrast to the linearly constrained LSCMA, the proposed algorithm provides better robustness against the signal steering vector mismatches, yields higher signal captive performance, improves greater array output SINR, and has a lower computational cost. The simulation results confirm the superiority of the proposed algorithm on beampattern control and output SINR enhancement.
... the development of osteoarthritis. It is a common reason people have shoulder replacement surgery. Rheumatoid Arthritis This is ... severe fracture of the shoulder is another common reason people have shoulder replacements. When the head of the ...
Partial knee replacement - slideshow
... page: //medlineplus.gov/ency/presentations/100225.htm Partial knee replacement - series—Normal anatomy To use the sharing ... A.M. Editorial team. Related MedlinePlus Health Topics Knee Replacement A.D.A.M., Inc. is accredited ...
GPU-Accelerated Apriori Algorithm
Directory of Open Access Journals (Sweden)
Jiang Hao
2017-01-01
Full Text Available This paper propose a parallel Apriori algorithm based on GPU (GPUApriori for frequent itemsets mining, and designs a storage structure using bit table (BIT matrix to replace the traditional storage mode. In addition, parallel computing scheme on GPU is discussed. The experimental results show that GPUApriori algorithm can effectively improve the efficiency of frequent itemsets mining.
Chen, Haiyan; Wu, Buyun; Gong, Dehua; Liu, Zhihong
2015-04-02
It is unclear whether the fluid status, as determined by bioimpedance vector analysis (BIVA) combined with serum N-terminal pro-B-type natriuretic peptides (NT-pro-BNP) measurement, is associated with treatment outcome among patients receiving continuous renal replacement therapy (CRRT). Our objective was to answer this question. Patients who were in the intensive care units of a university teaching hospital and who required CRRT were screened for enrollment. For the enrolled patients, BIVA and serum NT-pro BNP measurement were performed just before the start of CRRT and 3 days afterward. According to the BIVA and NT-pro BNP measurement results, the patients were divided into four groups according to fluid status type: type 1, both normal; type 2, normal BIVA results and abnormal NT-pro BNP levels; type 3, abnormal BIVA results and normal NT-pro BNP levels; and type 4, both abnormal. The associations between fluid status and outcome were analyzed. Eighty-nine patients were enrolled, 58 were males, and the mean age was 49.0 ± 17.2 years. The mean score of Acute Physiology and Chronic Health Evaluation II (APACHE II) was 18.8 ± 8.6. The fluid status before CRRT start was as follows: type 1, 21.3% (19 out of 89); type 2, 16.9% (15 out of 89); type 3, 11.2% (10 out of 89); and type 4, 50.6% (45 out of 89). There were significant differences between fluid status types before starting CRRT on baseline values for APACHE II scores, serum creatinine, hemoglobin, platelet count, urine volume, and incidences of oliguria and acute kidney injury (P measurements corresponded to different clinical conditions and treatment outcomes, which implies a value of this method for evaluation of fluid status among patients receiving CRRT.
Fast Quaternion Attitude Estimation from Two Vector Measurements
Markley, F. Landis; Bauer, Frank H. (Technical Monitor)
2001-01-01
Many spacecraft attitude determination methods use exactly two vector measurements. The two vectors are typically the unit vector to the Sun and the Earth's magnetic field vector for coarse "sun-mag" attitude determination or unit vectors to two stars tracked by two star trackers for fine attitude determination. Existing closed-form attitude estimates based on Wahba's optimality criterion for two arbitrarily weighted observations are somewhat slow to evaluate. This paper presents two new fast quaternion attitude estimation algorithms using two vector observations, one optimal and one suboptimal. The suboptimal method gives the same estimate as the TRIAD algorithm, at reduced computational cost. Simulations show that the TRIAD estimate is almost as accurate as the optimal estimate in representative test scenarios.
Aeronautical Information System Replacement -
Department of Transportation — Aeronautical Information System Replacement is a web-enabled, automation means for the collection and distribution of Service B messages, weather information, flight...
Improved stability and performance from sigma-delta modulators using 1-bit vector quantization
DEFF Research Database (Denmark)
Risbo, Lars
1993-01-01
A novel class of sigma-delta modulators is presented. The usual scalar 1-b quantizer in a sigma-delta modulator is replaced by a 1-b vector quantizer with a N-dimensional input state-vector from the linear feedback filter. Generally, the vector quantizer changes the nonlinear dynamics...
Method for transforming a feature vector
Veldhuis, Raymond N.J.; Chen, C.; Kevenaar, Thomas A.M.; Akkermans, Antonius H.M.
2007-01-01
The present invention relates to a method for transforming a feature vector comprising a first and a second feature represented by a first and a second feature value, respectively, into a feature code using an encoder, said feature code usable in an algorithm and having a predetermined number of
(AJST) VARIABLE STRUCTURE UNIT VECTOR CONTROL OF ...
African Journals Online (AJOL)
Administrator
control scheme is proposed for a single power system model dominated by steam powered generators with reheat turbines as used in [2]. However the scheme presented here is unique in adopting a systematic procedure based on the unit vector control algorithm [ 9 ], for the synthesis of the control functions. An analysis ...
Isomorphism Theorem on Vector Spaces over a Ring
Directory of Open Access Journals (Sweden)
Futa Yuichi
2017-10-01
Full Text Available In this article, we formalize in the Mizar system [1, 4] some properties of vector spaces over a ring. We formally prove the first isomorphism theorem of vector spaces over a ring. We also formalize the product space of vector spaces. ℤ-modules are useful for lattice problems such as LLL (Lenstra, Lenstra and Lovász [5] base reduction algorithm and cryptographic systems [6, 2].
Kleinberg, Jon
2006-01-01
Algorithm Design introduces algorithms by looking at the real-world problems that motivate them. The book teaches students a range of design and analysis techniques for problems that arise in computing applications. The text encourages an understanding of the algorithm design process and an appreciation of the role of algorithms in the broader field of computer science.
Wang, Lui; Bayer, Steven E.
1991-01-01
Genetic algorithms are mathematical, highly parallel, adaptive search procedures (i.e., problem solving methods) based loosely on the processes of natural genetics and Darwinian survival of the fittest. Basic genetic algorithms concepts are introduced, genetic algorithm applications are introduced, and results are presented from a project to develop a software tool that will enable the widespread use of genetic algorithm technology.
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...
Radiation Source Replacement Workshop
Energy Technology Data Exchange (ETDEWEB)
Griffin, Jeffrey W.; Moran, Traci L.; Bond, Leonard J.
2010-12-01
This report summarizes a Radiation Source Replacement Workshop in Houston Texas on October 27-28, 2010, which provided a forum for industry and researchers to exchange information and to discuss the issues relating to replacement of AmBe, and potentially other isotope sources used in well logging.
African Journals Online (AJOL)
MJZ
Penicillin allergy. 01. 02.0. Rheumatoid arthritis. 02. 03.9. TB. 01. 02.0. SCD. 01. 02.0. Fused lt. Hip. 01. 02.0. HIV +. 02. 03.9. Nil. 30. 58.7. Table 2. Distribution of operation related variables (n = 51). AVN = Avascular Necrosis. THR = Total Hip Replacement.TKR = Total Knee Replacement, C1 = Consultant 1.
DEFF Research Database (Denmark)
Vissing, S.; Hededal, O.
An algorithm is presented for computing the m smallest eigenvalues and corresponding eigenvectors of the generalized eigenvalue problem (A - λB)Φ = 0 where A and B are real n x n symmetric matrices. In an iteration scheme the matrices A and B are projected simultaneously onto an m-dimensional sub......An algorithm is presented for computing the m smallest eigenvalues and corresponding eigenvectors of the generalized eigenvalue problem (A - λB)Φ = 0 where A and B are real n x n symmetric matrices. In an iteration scheme the matrices A and B are projected simultaneously onto an m......-dimensional subspace in order to establish and solve a symmetric generalized eigenvalue problem in the subspace. The algorithm is described in pseudo code and implemented in the C programming language for lower triangular matrices A and B. The implementation includes procedures for selecting initial iteration vectors...
Energy Technology Data Exchange (ETDEWEB)
Zemach, Charles [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Kurien, Susan [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2016-11-14
These notes present an account of the Local Wave Vector (LWV) model of a turbulent flow defined throughout physical space. The previously-developed Local Wave Number (LWN) model is taken as a point of departure. Some general properties of turbulent fields and appropriate notation are given first. The LWV model is presently restricted to incompressible flows and the incompressibility assumption is introduced at an early point in the discussion. The assumption that the turbulence is homogeneous is also introduced early on. This assumption can be relaxed by generalizing the space diffusion terms of LWN, but the present discussion is focused on a modeling of homogeneous turbulence.
DEFF Research Database (Denmark)
Becciolini, Diego; Franzosi, Diogo Buarque; Foadi, Roshan
2015-01-01
We analyze the Large Hadron Collider (LHC) phenomenology of heavy vector resonances with a $SU(2)_L\\times SU(2)_R$ spectral global symmetry. This symmetry partially protects the electroweak S-parameter from large contributions of the vector resonances. The resulting custodial vector model spectrum...
Browning, Diana L.; Collins, Casey P.; Hocum, Jonah D.; Leap, David J.; Rae, Dustin T.; Trobridge, Grant D.
2016-01-01
Retroviral vector-mediated gene therapy is promising, but genotoxicity has limited its use in the clinic. Genotoxicity is highly dependent on the retroviral vector used, and foamy viral (FV) vectors appear relatively safe. However, internal promoters may still potentially activate nearby genes. We developed insulated FV vectors, using four previously described insulators: a version of the well-studied chicken hypersensitivity site 4 insulator (650cHS4), two synthetic CCCTC-binding factor (CTCF)-based insulators, and an insulator based on the CCAAT box-binding transcription factor/nuclear factor I (7xCTF/NF1). We directly compared these insulators for enhancer-blocking activity, effect on FV vector titer, and fidelity of transfer to both proviral long terminal repeats. The synthetic CTCF-based insulators had the strongest insulating activity, but reduced titers significantly. The 7xCTF/NF1 insulator did not reduce titers but had weak insulating activity. The 650cHS4-insulated FV vector was identified as the overall most promising vector. Uninsulated and 650cHS4-insulated FV vectors were both significantly less genotoxic than gammaretroviral vectors. Integration sites were evaluated in cord blood CD34+ cells and the 650cHS4-insulated FV vector had fewer hotspots compared with an uninsulated FV vector. These data suggest that insulated FV vectors are promising for hematopoietic stem cell gene therapy. PMID:26715244
Young, Frederic; Siegel, Edward
Cook-Levin theorem theorem algorithmic computational-complexity(C-C) algorithmic-equivalence reducibility/completeness equivalence to renormalization-(semi)-group phase-transitions critical-phenomena statistical-physics universality-classes fixed-points, is exploited via Siegel FUZZYICS =CATEGORYICS = ANALOGYICS =PRAGMATYICS/CATEGORY-SEMANTICS ONTOLOGY COGNITION ANALYTICS-Aristotle ``square-of-opposition'' tabular list-format truth-table matrix analytics predicts and implements ''noise''-induced phase-transitions (NITs) to accelerate versus to decelerate Harel [Algorithmics (1987)]-Sipser[Intro.Thy. Computation(`97)] algorithmic C-C: ''NIT-picking''(!!!), to optimize optimization-problems optimally(OOPO). Versus iso-''noise'' power-spectrum quantitative-only amplitude/magnitude-only variation stochastic-resonance, ''NIT-picking'' is ''noise'' power-spectrum QUALitative-type variation via quantitative critical-exponents variation. Computer-''science''/SEANCE algorithmic C-C models: Turing-machine, finite-state-models, finite-automata,..., discrete-maths graph-theory equivalence to physics Feynman-diagrams are identified as early-days once-workable valid but limiting IMPEDING CRUTCHES(!!!), ONLY IMPEDE latter-days new-insights!!!
Joux, Antoine
2009-01-01
Illustrating the power of algorithms, Algorithmic Cryptanalysis describes algorithmic methods with cryptographically relevant examples. Focusing on both private- and public-key cryptographic algorithms, it presents each algorithm either as a textual description, in pseudo-code, or in a C code program.Divided into three parts, the book begins with a short introduction to cryptography and a background chapter on elementary number theory and algebra. It then moves on to algorithms, with each chapter in this section dedicated to a single topic and often illustrated with simple cryptographic applic
Optimal randomized scheduling by replacement
Energy Technology Data Exchange (ETDEWEB)
Saias, I.
1996-05-01
In the replacement scheduling problem, a system is composed of n processors drawn from a pool of p. The processors can become faulty while in operation and faulty processors never recover. A report is issued whenever a fault occurs. This report states only the existence of a fault but does not indicate its location. Based on this report, the scheduler can reconfigure the system and choose another set of n processors. The system operates satisfactorily as long as, upon report of a fault, the scheduler chooses n non-faulty processors. We provide a randomized protocol maximizing the expected number of faults the system can sustain before the occurrence of a crash. The optimality of the protocol is established by considering a closely related dual optimization problem. The game-theoretic technical difficulties that we solve in this paper are very general and encountered whenever proving the optimality of a randomized algorithm in parallel and distributed computation.
Directory of Open Access Journals (Sweden)
Yongjie Luo
2016-05-01
Full Text Available Approximate Message Passing (AMP and Generalized AMP (GAMP algorithms usually suffer from serious convergence issues when the elements of the sensing matrix do not exactly match the zero-mean Gaussian assumption. To stabilize AMP/GAMP in these contexts, we have proposed a new sparse reconstruction algorithm, termed the Random regularized Matching pursuit GAMP (RrMpGAMP. It utilizes a random splitting support operation and some dropout/replacement support operations to make the matching pursuit steps regularized and uses a new GAMP-like algorithm to estimate the non-zero elements in a sparse vector. Moreover, our proposed algorithm can save much memory, be equipped with a comparable computational complexity as GAMP and support parallel computing in some steps. We have analyzed the convergence of this GAMP-like algorithm by the replica method and provided the convergence conditions of it. The analysis also gives an explanation about the broader variance range of the elements of the sensing matrix for this GAMP-like algorithm. Experiments using simulation data and real-world synthetic aperture radar tomography (TomoSAR data show that our method provides the expected performance for scenarios where AMP/GAMP diverges.
Slab replacement maturity guidelines.
2014-04-01
This study investigated the use of maturity method to determine early age strength of concrete in slab : replacement application. Specific objectives were (1) to evaluate effects of various factors on the compressive : maturity-strength relationship ...
... can occur after surgery. Avoiding Problems After Surgery Hip implant dislocation. Recognizing the Signs of a Blood Clot Follow ... Other Precautions To assure proper recovery and prevent dislocation of the ... your hip replacement. Prior to discharge from the hospital, your ...
Knee joint replacement - slideshow
... this page: //medlineplus.gov/ency/presentations/100088.htm Knee joint replacement - series—Normal anatomy To use the ... to slide 4 out of 4 Overview The knee is a complex joint. It contains the distal ...
... a part of the pelvic bone called the acetabulum) The upper end of the thighbone (called the ... Other reasons for replacing the hip joint are: Fractures in the thigh bone. Older adults often have ...
Hougardy, Stefan
2016-01-01
Algorithms play an increasingly important role in nearly all fields of mathematics. This book allows readers to develop basic mathematical abilities, in particular those concerning the design and analysis of algorithms as well as their implementation. It presents not only fundamental algorithms like the sieve of Eratosthenes, the Euclidean algorithm, sorting algorithms, algorithms on graphs, and Gaussian elimination, but also discusses elementary data structures, basic graph theory, and numerical questions. In addition, it provides an introduction to programming and demonstrates in detail how to implement algorithms in C++. This textbook is suitable for students who are new to the subject and covers a basic mathematical lecture course, complementing traditional courses on analysis and linear algebra. Both authors have given this "Algorithmic Mathematics" course at the University of Bonn several times in recent years.
A comparative study on change vector analysis based change ...
Indian Academy of Sciences (India)
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 ...
Empirical evaluation of gradient methods for matrix learning vector quantization
LeKander, M.; Biehl, M.; Vries, H. de
2017-01-01
Generalized Matrix Learning Vector Quantization (GMLVQ) critically relies on the use of an optimization algorithm to train its model parameters. We test various schemes for automated control of learning rates in gradient-based training. We evaluate these algorithms in terms of their achieved
Ramos, A; Talaia, P; Queirós de Melo, F J
2016-01-01
The main goal of this work was to develop an approached model to study dynamic behavior and prediction of the stress distribution in an in vitro Charnley cemented hip arthroplasty. An alternative version of the described pseudo-dynamic procedure is proposed by using the time integration Newmark algorithm. An internal restoring force vector is numerically calculated from the displacement, velocity, and acceleration vectors. A numerical model of hip replacement was developed to analyze the deformation of a dynamically stressed structure for all time steps. The experimental measurement of resulting internal forces generated in the structure (internal restoring force vector) is the second fundamental step of the pseudo-dynamic procedure. These data (as a feedback) are used by the time integration algorithm, which allows updating of the structure's shape for the next displacement, velocity, and acceleration vectors. In the field of Biomechanics, the potentialities of this method contribute to the determination of a dynamically equivalent in vitro stress field of a cemented hip prosthesis; implant fitted in patients with a normal mobility or practice sports. Consequences of the stress distribution in the implant zone that underwent cyclic fatigue loads were also discussed by using a finite element model. Application of this method in Biomechanics appears as a useful tool in the approximate stress field characterization of the peak stress state. Results show a peak value around two times the static situation, more for making possible the prediction of future damage and a programed clinical examination in patients using hip prosthesis.
Tel, G.
We define the notion of total algorithms for networks of processes. A total algorithm enforces that a "decision" is taken by a subset of the processes, and that participation of all processes is required to reach this decision. Total algorithms are an important building block in the design of
Research of DOA Estimation Based on Single MEMS Vector Hydrophone.
Zhang, Wen Dong; Guan, Ling Gang; Zhang, Guo Jun; Xue, Chen Yang; Zhang, Kai Rui; Wang, Jian Ping
2009-01-01
The MEMS vector hydrophone is a novel acoustic sensor with a "four-beam-cilia" structure. Based on the MEMS vector hydrophone with this structure, the paper studies the method of estimated direction of arrival (DOA). According to various research papers, many algorithms can be applied to vector hydrophones. The beam-forming approach and bar graph approach are described in detail. Laboratory tests by means of the a standing-wave tube are performed to validate the theoretical results. Both the theoretical analysis and the results of tests prove that the proposed MEMS vector hydrophone possesses the desired directional function.
Lyapunov Function Synthesis - Algorithm and Software
DEFF Research Database (Denmark)
Leth, Tobias; Sloth, Christoffer; Wisniewski, Rafal
2016-01-01
In this paper we introduce an algorithm for the synthesis of polynomial Lyapunov functions for polynomial vector fields. The Lyapunov function is a continuous piecewisepolynomial defined on simplices, which compose a collection of simplices. The algorithm is elaborated and crucial features are ex...
A quick survey of text categorization algorithms
Dan MUNTEANU
2007-01-01
This paper contains an overview of basic formulations and approaches to text classification. This paper surveys the algorithms used in text categorization: handcrafted rules, decision trees, decision rules, on-line learning, linear classifier, Rocchio’s algorithm, k Nearest Neighbor (kNN), Support Vector Machines (SVM).
Improving Vector Evaluated Particle Swarm Optimisation by incorporating nondominated solutions.
Lim, Kian Sheng; Ibrahim, Zuwairie; Buyamin, Salinda; Ahmad, Anita; Naim, Faradila; Ghazali, Kamarul Hawari; Mokhtar, Norrima
2013-01-01
The Vector Evaluated Particle Swarm Optimisation algorithm is widely used to solve multiobjective optimisation problems. This algorithm optimises one objective using a swarm of particles where their movements are guided by the best solution found by another swarm. However, the best solution of a swarm is only updated when a newly generated solution has better fitness than the best solution at the objective function optimised by that swarm, yielding poor solutions for the multiobjective optimisation problems. Thus, an improved Vector Evaluated Particle Swarm Optimisation algorithm is introduced by incorporating the nondominated solutions as the guidance for a swarm rather than using the best solution from another swarm. In this paper, the performance of improved Vector Evaluated Particle Swarm Optimisation algorithm is investigated using performance measures such as the number of nondominated solutions found, the generational distance, the spread, and the hypervolume. The results suggest that the improved Vector Evaluated Particle Swarm Optimisation algorithm has impressive performance compared with the conventional Vector Evaluated Particle Swarm Optimisation algorithm.
Directory of Open Access Journals (Sweden)
Jean-François Degbomont
2010-10-01
Full Text Available This paper addresses the symbolic representation of non-convex real polyhedra, i.e., sets of real vectors satisfying arbitrary Boolean combinations of linear constraints. We develop an original data structure for representing such sets, based on an implicit and concise encoding of a known structure, the Real Vector Automaton. The resulting formalism provides a canonical representation of polyhedra, is closed under Boolean operators, and admits an efficient decision procedure for testing the membership of a vector.
Rogers, David
1991-01-01
G/SPLINES are a hybrid of Friedman's Multivariable Adaptive Regression Splines (MARS) algorithm with Holland's Genetic Algorithm. In this hybrid, the incremental search is replaced by a genetic search. The G/SPLINE algorithm exhibits performance comparable to that of the MARS algorithm, requires fewer least squares computations, and allows significantly larger problems to be considered.
Vectors and their applications
Pettofrezzo, Anthony J
2005-01-01
Geared toward undergraduate students, this text illustrates the use of vectors as a mathematical tool in plane synthetic geometry, plane and spherical trigonometry, and analytic geometry of two- and three-dimensional space. Its rigorous development includes a complete treatment of the algebra of vectors in the first two chapters.Among the text's outstanding features are numbered definitions and theorems in the development of vector algebra, which appear in italics for easy reference. Most of the theorems include proofs, and coordinate position vectors receive an in-depth treatment. Key concept
Progressive Classification Using Support Vector Machines
Wagstaff, Kiri; Kocurek, Michael
2009-01-01
An algorithm for progressive classification of data, analogous to progressive rendering of images, makes it possible to compromise between speed and accuracy. This algorithm uses support vector machines (SVMs) to classify data. An SVM is a machine learning algorithm that builds a mathematical model of the desired classification concept by identifying the critical data points, called support vectors. Coarse approximations to the concept require only a few support vectors, while precise, highly accurate models require far more support vectors. Once the model has been constructed, the SVM can be applied to new observations. The cost of classifying a new observation is proportional to the number of support vectors in the model. When computational resources are limited, an SVM of the appropriate complexity can be produced. However, if the constraints are not known when the model is constructed, or if they can change over time, a method for adaptively responding to the current resource constraints is required. This capability is particularly relevant for spacecraft (or any other real-time systems) that perform onboard data analysis. The new algorithm enables the fast, interactive application of an SVM classifier to a new set of data. The classification process achieved by this algorithm is characterized as progressive because a coarse approximation to the true classification is generated rapidly and thereafter iteratively refined. The algorithm uses two SVMs: (1) a fast, approximate one and (2) slow, highly accurate one. New data are initially classified by the fast SVM, producing a baseline approximate classification. For each classified data point, the algorithm calculates a confidence index that indicates the likelihood that it was classified correctly in the first pass. Next, the data points are sorted by their confidence indices and progressively reclassified by the slower, more accurate SVM, starting with the items most likely to be incorrectly classified. The user
Battin, R. H.; Vaughan, R. M.
1983-10-01
A fundamental problem in astrodynamics is concerned with the determination of an orbit, having a specified flight time and connecting two position vectors. The present investigation is concerned with a new method for solving this problem, which is frequently referred to as Lambert's problem. This method parallels closely Gauss' classical method but is superior to it. The new algorithm converges rapidly for any given geometry and time of flight. Since there is no need to be concerned with specific starting values for different input parameters, this method appears to be a very attractive alternative to Newton-Raphson schemes for most space guidance applications.
Unitary Quantum Lattice Algorithms for Turbulence
2016-05-23
and is ideally parallelized. The algorithm is benchmarked against exact one dimensional vector inelastic soliton collision solutions. Three...release. 10 Parallelization of QLG algorithms The beauty of the QLG algorithm will not only run on a quantum computer when they become...timings : in strong scaling one fixes the grid and increases the number of cores. For ideal parallelization, the wallclock time will decrease by a
Cervical intervertebral disc replacement.
Cason, Garrick W; Herkowitz, Harry N
2013-02-06
Symptomatic adjacent-level disease after cervical fusion has led to the development and testing of several disc-replacement prostheses. Randomized controlled trials of cervical disc replacement (CDR) compared with anterior cervical discectomy and fusion (ACDF) have demonstrated at least equivalent clinical results for CDR with similar or lower complication rates. Biomechanical, kinematic, and radiographic studies of CDR reveal that the surgical level and adjacent vertebral level motion and center of rotation more closely mimic the native state. Lower intradiscal pressures adjacent to CDR may help decrease the incidence of adjacent spinal-level disease, but long-term follow-up is necessary to evaluate this theory.
THE REPLACEMENT-RENEWAL OF INDUSTRIAL EQUIPMENTS. THE MAPI FORMULAS
Directory of Open Access Journals (Sweden)
Meo Colombo Carlotta
2010-07-01
Full Text Available Since the production has been found to be an economical means for satisfying human wants, this process requires a complex industrial organization together with a large investment in equipments, plants and productive systems. These productive systems are employed to alter the physical environment and create consumer goods. As a result, they are consumed or become obsolete, inadequate, or otherwise candidates for replacement. When replacement is being considered, two assets must be evaluated: the present asset, the defender and its potential replacement, the challenger. Since the success of an industrial organization depends upon profit, replacement should generally occur if an economic advantage will result. Whatever the reason leading to the consideration of replacement, the analysis and decisions must be based upon estimates of what will occur in the future. In this paper we present the Mapi algorithm as a procedure for evaluating investments or for analyzing replacement opportunities.
Indian Academy of Sciences (India)
One consequence of the chiral restoration is the mixing of parity partners. We look for a possible signature of the mixing of vector and axial vector mesons in heavy-ion collisions. We suggest an experimental method for its observation. The dynamical evolution of the heavy-ion collision is described by a transport equation of ...
Indian Academy of Sciences (India)
kfki.hu. Abstract. One consequence of the chiral restoration is the mixing of parity partners. We look for a possible signature of the mixing of vector and axial vector mesons in heavy- ion collisions. We suggest an experimental method for its ...
Support vector machines for spam categorization.
Drucker, H; Wu, D; Vapnik, V N
1999-01-01
We study the use of support vector machines (SVM's) in classifying e-mail as spam or nonspam by comparing it to three other classification algorithms: Ripper, Rocchio, and boosting decision trees. These four algorithms were tested on two different data sets: one data set where the number of features were constrained to the 1000 best features and another data set where the dimensionality was over 7000. SVM's performed best when using binary features. For both data sets, boosting trees and SVM's had acceptable test performance in terms of accuracy and speed. However, SVM's had significantly less training time.
Complex Polynomial Vector Fields
DEFF Research Database (Denmark)
Dias, Kealey
The two branches of dynamical systems, continuous and discrete, correspond to the study of differential equations (vector fields) and iteration of mappings respectively. In holomorphic dynamics, the systems studied are restricted to those described by holomorphic (complex analytic) functions...... or meromorphic (allowing poles as singularities) functions. There already exists a well-developed theory for iterative holomorphic dynamical systems, and successful relations found between iteration theory and flows of vector fields have been one of the main motivations for the recent interest in holomorphic...... vector fields. Since the class of complex polynomial vector fields in the plane is natural to consider, it is remarkable that its study has only begun very recently. There are numerous fundamental questions that are still open, both in the general classification of these vector fields, the decomposition...
Okamoto, Kenichi W; Gould, Fred; Lloyd, Alun L
2016-03-01
Many vector-borne diseases lack effective vaccines and medications, and the limitations of traditional vector control have inspired novel approaches based on using genetic engineering to manipulate vector populations and thereby reduce transmission. Yet both the short- and long-term epidemiological effects of these transgenic strategies are highly uncertain. If neither vaccines, medications, nor transgenic strategies can by themselves suffice for managing vector-borne diseases, integrating these approaches becomes key. Here we develop a framework to evaluate how clinical interventions (i.e., vaccination and medication) can be integrated with transgenic vector manipulation strategies to prevent disease invasion and reduce disease incidence. We show that the ability of clinical interventions to accelerate disease suppression can depend on the nature of the transgenic manipulation deployed (e.g., whether vector population reduction or replacement is attempted). We find that making a specific, individual strategy highly effective may not be necessary for attaining public-health objectives, provided suitable combinations can be adopted. However, we show how combining only partially effective antimicrobial drugs or vaccination with transgenic vector manipulations that merely temporarily lower vector competence can amplify disease resurgence following transient suppression. Thus, transgenic vector manipulation that cannot be sustained can have adverse consequences-consequences which ineffective clinical interventions can at best only mitigate, and at worst temporarily exacerbate. This result, which arises from differences between the time scale on which the interventions affect disease dynamics and the time scale of host population dynamics, highlights the importance of accounting for the potential delay in the effects of deploying public health strategies on long-term disease incidence. We find that for systems at the disease-endemic equilibrium, even modest
A new algorithm for five-hole probe calibration, data reduction, and uncertainty analysis
Reichert, Bruce A.; Wendt, Bruce J.
1994-01-01
A new algorithm for five-hole probe calibration and data reduction using a non-nulling method is developed. The significant features of the algorithm are: (1) two components of the unit vector in the flow direction replace pitch and yaw angles as flow direction variables; and (2) symmetry rules are developed that greatly simplify Taylor's series representations of the calibration data. In data reduction, four pressure coefficients allow total pressure, static pressure, and flow direction to be calculated directly. The new algorithm's simplicity permits an analytical treatment of the propagation of uncertainty in five-hole probe measurement. The objectives of the uncertainty analysis are to quantify uncertainty of five-hole results (e.g., total pressure, static pressure, and flow direction) and determine the dependence of the result uncertainty on the uncertainty of all underlying experimental and calibration measurands. This study outlines a general procedure that other researchers may use to determine five-hole probe result uncertainty and provides guidance to improve measurement technique. The new algorithm is applied to calibrate and reduce data from a rake of five-hole probes. Here, ten individual probes are mounted on a single probe shaft and used simultaneously. Use of this probe is made practical by the simplicity afforded by this algorithm.
Emergency Heart Valve Replacement
Stinson, Edward B.; Shumway, Norman E.
1968-01-01
Sixteen patients with terminal cardiac failure due to valvular heart disease had emergency operation for value replacement. Four patients did not survive, because of irreversible myocardial or secondary organ involvement. The remainder, however, had immediate reversal of heart failure after operation, and all became fully active following discharge. Recognition of refractory decompensation in valvular heart disease demands prompt consideration of surgical intervention. PMID:5724875
... Artificial discs are usually made of metal or plastic-like (biopolymer) materials, or a combination of the two. These materials have been used in the body for many years. Total disc replacements have been used in Europe since the late 1980s. The most commonly used ...
Prioritizing equipment for replacement.
Capuano, Mike
2010-01-01
It is suggested that clinical engineers take the lead in formulating evaluation processes to recommend equipment replacement. Their skill, knowledge, and experience, combined with access to equipment databases, make them a logical choice. Based on ideas from Fennigkoh's scheme, elements such as age, vendor support, accumulated maintenance cost, and function/risk were used.6 Other more subjective criteria such as cost benefits and efficacy of newer technology were not used. The element of downtime was also omitted due to the data element not being available. The resulting Periop Master Equipment List and its rationale was presented to the Perioperative Services Program Council. They deemed the criteria to be robust and provided overwhelming acceptance of the list. It was quickly put to use to estimate required capital funding, justify items already thought to need replacement, and identify high-priority ranked items for replacement. Incorporating prioritization criteria into an existing equipment database would be ideal. Some commercially available systems do have the basic elements of this. Maintaining replacement data can be labor-intensive regardless of the method used. There is usually little time to perform the tasks necessary for prioritizing equipment. However, where appropriate, a clinical engineering department might be able to conduct such an exercise as shown in the following case study.
Fluorescent Lamp Replacement Study
2017-07-01
C -1 D FLUORESCENT LAMP SPECIFICATION SHEETS . . . . . . . . . . . . . . . . . . . . . . . . . . D -1 E LED WAVES’ LED ...friendly products, advances in efficiency, and lower production costs for lamps . The conversion of fluorescent bulbs to LED technology has many benefits...repeatedly turned on and off. (5) LEDs can be used in existing fluorescent lighting fixtures using LED retrofit kits or replacement lamps . (6
Aggression Replacement Training.
Glick, Barry; Goldstein, Arnold P.
1987-01-01
Describes aggression replacement training (ART), a multimodal, psychoeducational intervention for assaultive, hostile adolescents and children who are either institutionalized or pose severe, disruptive behaviors in communities. Presents the research evaluating ART efficacy, planned efforts in program development, and ART's relevance for…
MPEG-2 Compressed-Domain Algorithms for Video Analysis
Directory of Open Access Journals (Sweden)
Hesseler Wolfgang
2006-01-01
Full Text Available This paper presents new algorithms for extracting metadata from video sequences in the MPEG-2 compressed domain. Three algorithms for efficient low-level metadata extraction in preprocessing stages are described. The first algorithm detects camera motion using the motion vector field of an MPEG-2 video. The second method extends the idea of motion detection to a limited region of interest, yielding an efficient algorithm to track objects inside video sequences. The third algorithm performs a cut detection using macroblock types and motion vectors.
A modified multitarget adaptive array algorithm for wireless CDMA system.
Liu, Yun-hui; Yang, Yu-hang
2004-11-01
The paper presents a modified least squares despread respread multitarget constant modulus algorithm (LS-DRMTCMA). The cost function of the original algorithm was modified by the minimum bit error rate (MBER) criterion. The novel algorithm tries to optimize weight vectors by directly minimizing bit error rate (BER) of code division multiple access (CDMA) mobile communication system. In order to achieve adaptive update of weight vectors, a stochastic gradient adaptive algorithm was developed by a kernel density estimator of possibility density function based on samples. Simulation results showed that the modified algorithm remarkably improves the BER performance, capacity and near-far effect resistance of a given CDMA communication system.
Retrotransposon vectors for gene delivery in plants
Directory of Open Access Journals (Sweden)
Hou Yi
2010-08-01
Full Text Available Abstract Background Retrotransposons are abundant components of plant genomes, and although some plant retrotransposons have been used as insertional mutagens, these mobile genetic elements have not been widely exploited for plant genome manipulation. In vertebrates and yeast, retrotransposons and retroviruses are routinely altered to carry additional genes that are copied into complementary (cDNA through reverse transcription. Integration of cDNA results in gene delivery; recombination of cDNA with homologous chromosomal sequences can create targeted gene modifications. Plant retrotransposon-based vectors, therefore, may provide new opportunities for plant genome engineering. Results A retrotransposon vector system was developed for gene delivery in plants based on the Tnt1 element from Nicotiana tabacum. Mini-Tnt1 transfer vectors were constructed that lack coding sequences yet retain the 5' and 3' long terminal repeats (LTRs and adjacent cis sequences required for reverse transcription. The internal coding region of Tnt1 was replaced with a neomycin phosphotransferase gene to monitor replication by reverse transcription. Two different mini-Tnt1 s were developed: one with the native 5' LTR and the other with a chimeric 5' LTR that had the first 233 bp replaced by the CaMV 35 S promoter. After transfer into tobacco protoplasts, both vectors undergo retrotransposition using GAG and POL proteins provided in trans by endogenous Tnt1 elements. The transposition frequencies of mini-Tnt1 vectors are comparable with native Tnt1 elements, and like the native elements, insertion sites are within or near coding sequences. In this paper, we provide evidence that template switching occurs during mini-Tnt1 reverse transcription, indicating that multiple copies of Tnt1 mRNA are packaged into virus-like particles. Conclusions Our data demonstrate that mini-Tnt1 vectors can replicate efficiently in tobacco cells using GAG and POL proteins provided in trans by
An algorithm for finding block-triangular forms
Dietzenbacher, Erik
In this paper, an algorithm is constructed for finding the block triangular form of a nonnegative matrix. The algorithm is based on the zero elements of the left and right Perron vectors of the matrix and, subsequently, certain submatrices. The construction of the algorithm Is motivated by the
Algorithms for Global Positioning
DEFF Research Database (Denmark)
Borre, Kai; Strang, Gilbert
and replaces the authors' previous work, Linear Algebra, Geodesy, and GPS (1997). An initial discussion of the basic concepts, characteristics and technical aspects of different satellite systems is followed by the necessary mathematical content which is presented in a detailed and self-contained fashion....... At the heart of the matter are the positioning algorithms on which GPS technology relies, the discussion of which will affirm the mathematical contents of the previous chapters. Numerous ready-to-use MATLAB codes are included for the reader. This comprehensive guide will be invaluable for engineers...... and academic researchers who wish to master the theory and practical application of GPS technology....
Choi, Soo-Min; Hochberg, Yonit; Kuflik, Eric; Lee, Hyun Min; Mambrini, Yann; Murayama, Hitoshi; Pierre, Mathias
2017-10-01
Strongly Interacting Massive Particles (SIMPs) have recently been proposed as light thermal dark matter relics. Here we consider an explicit realization of the SIMP mechanism in the form of vector SIMPs arising from an SU(2) X hidden gauge theory, where the accidental custodial symmetry protects the stability of the dark matter. We propose several ways of equilibrating the dark and visible sectors in this setup. In particular, we show that a light dark Higgs portal can maintain thermal equilibrium between the two sectors, as can a massive dark vector portal with its generalized Chern-Simons couplings to the vector SIMPs, all while remaining consistent with experimental constraints.
Schwalm, W. A.; Schwalm, M. K.; Giona, M.
1998-03-01
Space is filled with triangulating graph \\calG to serve as a quadrature grid. A discrete analog of the theory of differential forms is constructed using the associated simplical complex. The role of a basis for Λ^p at a point is played by the set of (p+1) -simplices containing a given vertex. Vector difference operations analogous to div, grad and curl, together with corresponding vector identities and exact difference analogs of the Stokes-type theorems, are obtained in terms of the boundary partial and coboundary d. Difference versions of the full vector Maxwell electromagnetic equations are analyzed on a random structure.
Fluorescent Lamp Replacement Study
2017-07-01
recycling , and can be disposed safely in a landfill. (2) LEDs offer reduced maintenance costs and fewer bulb replacements, significantly reducing...housings, plastic grates, old wiring) and the new LED technology (cardboard packaging) were broken down and separated into the appropriate container for... recycling . Several fixtures, ballasts and energy efficient fluorescent bulbs that were determined to be in pristine condition were returned to ATC
Evanski, P M; Waugh, T R; Orofino, C F; Anzel, S H
1976-10-01
Between March 9, 1972 and December 31, 1973, a total of 103 UCI knee replacements were performed. Follow-up data are available on 83 knees with an average follow-up of 33 months. Patient evaluation of the end results indicates that 78.3 per cent were better, 9.6 per cent unchanged, and 12.1 per cent worse. Patient evaluation of their own knee function averaged 55 per cent preoperatively and 79 per cent postoperatively. Patients were also evaluated on a 100 point Modified Larson Analysis Form. The average preoperative score was 46, and the average postoperative score was 70. There were six (5.8%) biological complications in the 103 knee replacement. Biological complications included infections, wound healing problems and unexplained pain. Mechanical complications were seen in 18 (17.4%) knees, and included knee instability, tibial component loosening or deformation, and patellar problems. Additional surgery was required in 18 (17.4%) knees. Failure of the procedure eventually requiring removal of the prosthesis and fusion or amputation occurred in 4 (3.9%) knees. The intermediate-term results of UCI knee replacement have been clinically satisfactory. We currently recommend consideration of this procedure for patients with disabling arthritis of the knee.
Herbert, Timothy J; van Schoonhoven, Joerg
2007-03-01
Recent years have seen an increasing awareness of the anatomical and biomechanical significance of the distal radioulnar joint (DRUJ). With this has come a more critical approach to surgical management of DRUJ disorders and a realization that all forms of "excision arthroplasty" can only restore forearm rotation at the expense of forearm stability. This, in turn, has led to renewed interest in prosthetic replacement of the ulnar head, a procedure that had previously fallen into disrepute because of material failures with early implants, in particular, the Swanson silicone ulnar head replacement. In response to these early failures, a new prosthesis was developed in the early 1990s, using materials designed to withstand the loads across the DRUJ associated with normal functional use of the upper limb. Released onto the market in 1995 (Herbert ulnar head prosthesis), clinical experience during the last 10 years has shown that this prosthesis is able to restore forearm function after ulnar head excision and that the materials (ceramic head and noncemented titanium stem), even with normal use of the limb, are showing no signs of failure in the medium to long term. As experience with the use of an ulnar head prosthesis grows, so does its acceptance as a viable and attractive alternative to more traditional operations, such as the Darrach and Sauve-Kapandji procedures. This article discusses the current indications and contraindications for ulnar head replacement and details the surgical procedure, rehabilitation, and likely outcomes.
Energy Technology Data Exchange (ETDEWEB)
Huang, Qiu; Peng, Qiyu; Huang, Bin; Cheryauka, Arvi; Gullberg, Grant T.
2008-05-15
The measurement of flow obtained using continuous wave Doppler ultrasound is formulated as a directional projection of a flow vector field. When a continuous ultrasound wave bounces against a flowing particle, a signal is backscattered. This signal obtains a Doppler frequency shift proportional to the speed of the particle along the ultrasound beam. This occurs for each particle along the beam, giving rise to a Doppler velocity spectrum. The first moment of the spectrum provides the directional projection of the flow along theultrasound beam. Signals reflected from points further away from the detector will have lower amplitude than signals reflected from points closer to the detector. The effect is very much akin to that modeled by the attenuated Radon transform in emission computed tomography.A least-squares method was adopted to reconstruct a 2D vector field from directional projection measurements. Attenuated projections of only the longitudinal projections of the vector field were simulated. The components of the vector field were reconstructed using the gradient algorithm to minimize a least-squares criterion. This result was compared with the reconstruction of longitudinal projections of the vector field without attenuation. Ifattenuation is known, the algorithm was able to accurately reconstruct both components of the full vector field from only one set of directional projection measurements. A better reconstruction was obtained with attenuation than without attenuation implying that attenuation provides important information for the reconstruction of flow vector fields.This confirms previous work where we showed that knowledge of the attenuation distribution helps in the reconstruction of MRI diffusion tensor fields from fewer than the required measurements. In the application of ultrasound the attenuation distribution is obtained with pulse wave transmission computed tomography and flow information is obtained with continuous wave Doppler.
Minnesota Department of Natural Resources — This vector dataset is a detailed (1-acre minimum), hierarchically organized vegetation cover map produced by computer classification of combined two-season pairs of...
Kansas Data Access and Support Center — The Kansas Tagged Vector Contour (TVC) dataset consists of digitized contours from the 7.5 minute topographic quadrangle maps. Coverage for the state is incomplete....
OPTIMAL DATA REPLACEMENT TECHNIQUE FOR COOPERATIVE CACHING IN MANET
Directory of Open Access Journals (Sweden)
P. Kuppusamy
2014-09-01
Full Text Available A cooperative caching approach improves data accessibility and reduces query latency in Mobile Ad hoc Network (MANET. Maintaining the cache is challenging issue in large MANET due to mobility, cache size and power. The previous research works on caching primarily have dealt with LRU, LFU and LRU-MIN cache replacement algorithms that offered low query latency and greater data accessibility in sparse MANET. This paper proposes Memetic Algorithm (MA to locate the better replaceable data based on neighbours interest and fitness value of cached data to store the newly arrived data. This work also elects ideal CH using Meta heuristic search Ant Colony Optimization algorithm. The simulation results shown that proposed algorithm reduces the latency, control overhead and increases the packet delivery rate than existing approach by increasing nodes and speed respectively.
Learning interactive learning strategy with genetic algorithm
Hanzel, Jan
2014-01-01
The main goal of this thesis was to develop an algoritem for learning the best strategy in the case of interactive learning between a human and a robot. We presented the definition and formalization of a learning strategy. A learning strategy specifies the behaviour of a student and a teacher in a interactive learning process. We also presented a genetic algorithm to resolve our optimisation problem. We tryed to inpruve vectors which are used to present learning strategies. The vectors were...
Graphics and visualization principles & algorithms
Theoharis, T; Platis, Nikolaos; Patrikalakis, Nicholas M
2008-01-01
Computer and engineering collections strong in applied graphics and analysis of visual data via computer will find Graphics & Visualization: Principles and Algorithms makes an excellent classroom text as well as supplemental reading. It integrates coverage of computer graphics and other visualization topics, from shadow geneeration and particle tracing to spatial subdivision and vector data visualization, and it provides a thorough review of literature from multiple experts, making for a comprehensive review essential to any advanced computer study.-California Bookw
Study on Fast MUSIC Algorithm with Typical Array
Directory of Open Access Journals (Sweden)
Zhang Xing-liang
2012-06-01
Full Text Available Because MUSIC (MUltiple SIgnal Classification algorithm needs a large number of multiplications and trigonometric function evaluations, it is weak in the real time processing. This paper is aim at resolving above problem. Firstly, by analyzing the structural features of the uniform circular array and the uniform linear array, some properties of steering vector are extracted. Then, the properties of Hermite matrix are employed to decompose the complex multiplication, and then two real vectors are constructed to reduce the number of multiplications. Finally, with the properties of steering vector, a new algorithm based on look-up-table is proposed. The new algorithm neither has any trigonometric function evaluation, nor requires much memory space. The result of simulation experiments shows that the new algorithm raises the rate of MUSIC algorithm more than 50 times, while ensures the same estimated results. Therefore, the new algorithm has a wide application prospect.
Syngeneic AAV pseudo-vectors potentiates full vector transduction
An excessive amount of empty capsids are generated during regular AAV vector production process. These pseudo-vectors often remain in final vectors used for animal studies or clinical trials. The potential effects of these pseudo-vectors on AAV transduction have been a major concern. In the current ...
Vector and axial vector mesons at finite temperature
mallik, S.; Sarkar, Sourav
2002-01-01
We consider the thermal correlation functions of vector and axial-vector currents and evaluate corrections to the vector and axial-vector meson pole terms to one loop in chiral perturbation theory. As expected, the pole positions do not shift to leading order in temperature. But the residues decrease with temperature.
Human action recognition with group lasso regularized-support vector machine
Luo, Huiwu; Lu, Huanzhang; Wu, Yabei; Zhao, Fei
2016-05-01
The bag-of-visual-words (BOVW) and Fisher kernel are two popular models in human action recognition, and support vector machine (SVM) is the most commonly used classifier for the two models. We show two kinds of group structures in the feature representation constructed by BOVW and Fisher kernel, respectively, since the structural information of feature representation can be seen as a prior for the classifier and can improve the performance of the classifier, which has been verified in several areas. However, the standard SVM employs L2-norm regularization in its learning procedure, which penalizes each variable individually and cannot express the structural information of feature representation. We replace the L2-norm regularization with group lasso regularization in standard SVM, and a group lasso regularized-support vector machine (GLRSVM) is proposed. Then, we embed the group structural information of feature representation into GLRSVM. Finally, we introduce an algorithm to solve the optimization problem of GLRSVM by alternating directions method of multipliers. The experiments evaluated on KTH, YouTube, and Hollywood2 datasets show that our method achieves promising results and improves the state-of-the-art methods on KTH and YouTube datasets.
More About Vector Adaptive/Predictive Coding Of Speech
Jedrey, Thomas C.; Gersho, Allen
1992-01-01
Report presents additional information about digital speech-encoding and -decoding system described in "Vector Adaptive/Predictive Encoding of Speech" (NPO-17230). Summarizes development of vector adaptive/predictive coding (VAPC) system and describes basic functions of algorithm. Describes refinements introduced enabling receiver to cope with errors. VAPC algorithm implemented in integrated-circuit coding/decoding processors (codecs). VAPC and other codecs tested under variety of operating conditions. Tests designed to reveal effects of various background quiet and noisy environments and of poor telephone equipment. VAPC found competitive with and, in some respects, superior to other 4.8-kb/s codecs and other codecs of similar complexity.
Elements of mathematics topological vector spaces
Bourbaki, Nicolas
2003-01-01
This is a softcover reprint of the English translation of 1987 of the second edition of Bourbaki's Espaces Vectoriels Topologiques (1981). This second edition is a brand new book and completely supersedes the original version of nearly 30 years ago. But a lot of the material has been rearranged, rewritten, or replaced by a more up-to-date exposition, and a good deal of new material has been incorporated in this book, all reflecting the progress made in the field during the last three decades. Table of Contents. Chapter I: Topological vector spaces over a valued field. Chapter II: Convex sets and locally convex spaces. Chapter III: Spaces of continuous linear mappings. Chapter IV: Duality in topological vector spaces. Chapter V: Hilbert spaces (elementary theory). Finally, there are the usual "historical note", bibliography, index of notation, index of terminology, and a list of some important properties of Banach spaces. (Based on Math Reviews, 1983).
DEFF Research Database (Denmark)
Sköld, Martin; Karlsson, Christer
2012-01-01
Purpose – It is argued in this article that too little is known about product platforms and how to deal with them from a manager's point of view. Specifically, little information exists regarding when old established platforms are replaced by new generations in R&D and production environments...... to challenge their existing knowledge about platform architectures. Issues on technologies, architectures, components and processes as well as on segments, applications and functions are identified. Practical implications – Practical implications are summarized and discussed in relation to a framework...
Toleration, Synthesis or Replacement?
DEFF Research Database (Denmark)
Holtermann, Jakob v. H.; Madsen, Mikael Rask
2016-01-01
, in order to answer is not yet another partisan suggestion, but rather an attempt at making intelligible both the oppositions and the possibilities of synthesis between normative and empirical approaches to law. Based on our assessment and rational reconstruction of current arguments and positions, we...... therefore outline a taxonomy consisting of the following three basic, ideal-types in terms of the epistemological understanding of the interface of law and empirical studies: toleration, synthesis and replacement. This tripartite model proves useful with a view to teasing out and better articulating...
Extended Mixed Vector Equilibrium Problems
Directory of Open Access Journals (Sweden)
Mijanur Rahaman
2014-01-01
Full Text Available We study extended mixed vector equilibrium problems, namely, extended weak mixed vector equilibrium problem and extended strong mixed vector equilibrium problem in Hausdorff topological vector spaces. Using generalized KKM-Fan theorem (Ben-El-Mechaiekh et al.; 2005, some existence results for both problems are proved in noncompact domain.
Energy Technology Data Exchange (ETDEWEB)
Reed, Gary
2010-09-30
This report represents the final report for the Eastern Illinois University power plant replacement study. It contains all related documentation from consideration of possible solutions to the final recommended option. Included are the economic justifications associated with the chosen solution along with application for environmental permitting for the selected project for construction. This final report will summarize the results of execution of an EPC (energy performance contract) investment grade audit (IGA) which lead to an energy services agreement (ESA). The project includes scope of work to design and install energy conservation measures which are guaranteed by the contractor to be self-funding over its twenty year contract duration. The cost recovery is derived from systems performance improvements leading to energy savings. The prime focus of this EPC effort is to provide a replacement solution for Eastern Illinois University's aging and failing circa 1925 central steam production plant. Twenty-three ECMs were considered viable whose net impact will provide sufficient savings to successfully support the overall project objectives.
2005-01-01
Executive Summary Objective The aim of this review was to assess the effectiveness, in terms of pain reduction and functional improvement, and costing of total knee replacement (TKR) for people with osteoarthritis for whom less invasive treatments (such as physiotherapy, analgesics, anti-inflammatory drugs, intra-articular steroids, hyaluronic acids, and arthroscopic surgery) have failed. Clinical Need Osteoarthritis affects an estimated 10% to 12% of Canadian adults. The therapeutic goals of osteoarthritis treatment are to improve joint mobility and reduce pain. Stepwise treatment options include exercise, weight loss, physiotherapy, analgesics, anti-inflammatory drugs, intra-articular steroids and hyaluronic acids, arthroscopic surgery, and, in severe cases, total joint replacement with follow-up rehabilitation. These treatments are delivered by a range of health care professionals, including physiotherapists, occupational therapists, family physicians, internists, rheumatologists, and orthopedic surgeons. TKR is an end-of-line treatment for patients with severe pain and functional limitations. More women than men undergo knee replacement, and most patients are between 55 and 84 years old. The Technology TKR is a surgical procedure in which an artificial joint or prosthesis replaces a damaged knee joint. The primary indication for TKR is pain, followed by functional limitation. Usually, a person’s daily activities must be substantially affected by pain and functional limitations for him or her to be considered a candidate for TKR. There are 3 different types of knee replacement prostheses. Non-constrained prostheses use the patient’s ligaments and muscles to provide the stability for the prosthesis. Semi-constrained prostheses provide some stability for the knee and do not rely entirely on the patient’s ligaments and muscles to provide the stability. Constrained prostheses are for patients whose ligaments and muscles are not able to provide stability for
Energy Technology Data Exchange (ETDEWEB)
Reed, Gary
2010-09-30
This report represents the final report for the Eastern Illinois University power plant replacement study. It contains all related documentation from consideration of possible solutions to the final recommended option. Included are the economic justifications associated with the chosen solution along with application for environmental permitting for the selected project for construction. This final report will summarize the results of execution of an EPC (energy performance contract) investment grade audit (IGA) which lead to an energy services agreement (ESA). The project includes scope of work to design and install energy conservation measures which are guaranteed by the contractor to be self-funding over its twenty year contract duration. The cost recovery is derived from systems performance improvements leading to energy savings. The prime focus of this EPC effort is to provide a replacement solution for Eastern Illinois University’s aging and failing circa 1925 central steam production plant. Twenty-three ECMs were considered viable whose net impact will provide sufficient savings to successfully support the overall project objectives.
Human Resources Division
2001-01-01
The French Ministry of Foreign Affairs has informed the Organization that it is shortly to replace all diplomatic cards, special cards and employment permits ('attestations de fonctions') now held by members of the personnel and their families. Between 2 July and 31 December 2001, these cards are to be replaced by secure, computerized equivalents. The old cards may continue to be used until 31 December 2001. For the purposes of the handover, members of the personnel are asked to go to the cards office (33/1-015), taking the following documents for themselves and members of their families already in possession of a French card : A recent identity photograph in 4.5 cm x 3.5 cm format, The French card in their possession, an A4 photocopy of the same French card, certified by the cards office as being a true copy. Those members of the personnel whose cards (and/or cards belonging to members of their families) are shortly due to expire, or have recently done so, are also requested to take these items to the c...
HR/SOC
2001-01-01
The French Ministry of Foreign Affairs has informed the Organization that it is shortly to replace all diplomatic cards, special cards and employment permits ('attestations de fonctions') now held by members of the personnel and their families. Between 2 July and 31 December 2001, these cards are to be replaced by secure, computerized equivalents. The old cards may continue to be used until 31 December 2001. For the purposes of the handover, members of the personnel must go personally to the cards office (33/1-015), in order to fill in a 'fiche individuelle' form, taking the following documents for themselves and members of their families already in possession of a French card : A recent identity photograph in 4.5 cm x 3.5 cm format. The French card in their possession. An A4 photocopy of the same French card, certified by the cards office as being a true copy. Those members of the personnel whose cards (and/or cards belonging to members of their families) are shortly due to expire, or have recently done...
Human Resources Division; Cards.Service@cern.ch
2001-01-01
The French Ministry of Foreign Affairs is currently replacing all diplomatic cards, special cards and employment permits («attestations de fonctions») held by members of the personnel and their families. These cards are replaced by secure, computerized equivalents. The old cards may no longer be used after 31 December 2001. For the purposes of the handover, members of the personnel must go personally to the cards office (33/1-015) between 8h30 and 12h30, in order to fill in a «fiche individuelle» form, taking the following documents for themselves and members of their families already in possession of a French card : A recent identity photograph in 4.5 cm x 3.5 cm format, the French card in their possession, an A4 photocopy of the same French card, certified by the cards office as being a true copy. Those members of the personnel whose cards (and/or cards belonging to members of their families) are shortly due to expire, or have recently done so, are also requested...
Human Resources Division
2001-01-01
The French Ministry of Foreign Affairs has informed the Organization that it is shortly to replace all diplomatic cards, special cards and employment permits ('attestations de fonctions') now held by members of the personnel and their families. Between 2 July and 31 December 2001, these cards are to be replaced by secure, computerized equivalents. A 'personnel office' stamped photocopy of the old cards may continue to be used until 31 December 2001. For the purposes of the handover, members of the personnel must go personally to the cards office (33/1-015), between 8:30 and 12:30, in order to fill a 'fiche individuelle' form (in black ink only), which has to be personally signed by themselves and another separately signed by members of their family, taking the following documents for themselves and members of their families already in possession of a French card : A recent identity photograph in 4.5 cm x 3.5 cm format (signed on the back) The French card in their possession an A4 photocopy of the same Fre...
Vital, J-M; Boissière, L
2014-02-01
Total disc replacement (TDR) (partial disc replacement will not be described) has been used in the lumbar spine since the 1980s, and more recently in the cervical spine. Although the biomechanical concepts are the same and both are inserted through an anterior approach, lumbar TDR is conventionally indicated for chronic low back pain, whereas cervical TDR is used for soft discal hernia resulting in cervicobrachial neuralgia. The insertion technique must be rigorous, with precise centering in the disc space, taking account of vascular anatomy, which is more complex in the lumbar region, particularly proximally to L5-S1. All of the numerous studies, including prospective randomized comparative trials, have demonstrated non-inferiority to fusion, or even short-term superiority regarding speed of improvement. The main implant-related complication is bridging heterotopic ossification with resulting loss of range of motion and increased rates of adjacent segment degeneration, although with an incidence lower than after arthrodesis. A sufficiently long follow-up, which has not yet been reached, will be necessary to establish definitively an advantage for TDR, particularly in the cervical spine. Copyright © 2014 Elsevier Masson SAS. All rights reserved.
Topic Evolutionary Tweet Stream Clustering Algorithm and TCV Rank Summarization
National Research Council Canada - National Science Library
K.Selvaraj; S.Balaji
2015-01-01
... and more. our proposed work consists three components tweet stream clustering to cluster tweet using k-means cluster algorithm and second tweet cluster vector technique to generate rank summarization using...
A Wavelet Kernel-Based Primal Twin Support Vector Machine for Economic Development Prediction
Directory of Open Access Journals (Sweden)
Fang Su
2013-01-01
Full Text Available Economic development forecasting allows planners to choose the right strategies for the future. This study is to propose economic development prediction method based on the wavelet kernel-based primal twin support vector machine algorithm. As gross domestic product (GDP is an important indicator to measure economic development, economic development prediction means GDP prediction in this study. The wavelet kernel-based primal twin support vector machine algorithm can solve two smaller sized quadratic programming problems instead of solving a large one as in the traditional support vector machine algorithm. Economic development data of Anhui province from 1992 to 2009 are used to study the prediction performance of the wavelet kernel-based primal twin support vector machine algorithm. The comparison of mean error of economic development prediction between wavelet kernel-based primal twin support vector machine and traditional support vector machine models trained by the training samples with the 3–5 dimensional input vectors, respectively, is given in this paper. The testing results show that the economic development prediction accuracy of the wavelet kernel-based primal twin support vector machine model is better than that of traditional support vector machine.
Linear feature detection algorithm for astronomical surveys - I. Algorithm description
Bektešević, Dino; Vinković, Dejan
2017-11-01
Computer vision algorithms are powerful tools in astronomical image analyses, especially when automation of object detection and extraction is required. Modern object detection algorithms in astronomy are oriented towards detection of stars and galaxies, ignoring completely the detection of existing linear features. With the emergence of wide-field sky surveys, linear features attract scientific interest as possible trails of fast flybys of near-Earth asteroids and meteors. In this work, we describe a new linear feature detection algorithm designed specifically for implementation in big data astronomy. The algorithm combines a series of algorithmic steps that first remove other objects (stars and galaxies) from the image and then enhance the line to enable more efficient line detection with the Hough algorithm. The rate of false positives is greatly reduced thanks to a step that replaces possible line segments with rectangles and then compares lines fitted to the rectangles with the lines obtained directly from the image. The speed of the algorithm and its applicability in astronomical surveys are also discussed.
New Space Vector Selection Scheme for VSI Supplied Dual Three-Phase Induction Machine
Directory of Open Access Journals (Sweden)
MILICEVIC, D.
2013-02-01
Full Text Available This paper presents a novel space vector selection scheme applicable for the control of dual three-phase induction motor drives supplied from a six-phase voltage source inverter (VSI. The vector selection method is based on the vector space decomposition technique (VSD. Unique vector selection pattern simplifies problems related to complicated implementation of standard VSD in commercially available digital signals processors (DSP. The proposed vector selection scheme is verified through a theoretical analysis, computer simulations and practical experimental results conducted on a dual three-phase test rig prototype with control algorithm implemented in Texas Instrument?s TMS320F2808 DSP.
Hu, T C
2002-01-01
Newly enlarged, updated second edition of a valuable text presents algorithms for shortest paths, maximum flows, dynamic programming and backtracking. Also discusses binary trees, heuristic and near optimums, matrix multiplication, and NP-complete problems. 153 black-and-white illus. 23 tables.Newly enlarged, updated second edition of a valuable, widely used text presents algorithms for shortest paths, maximum flows, dynamic programming and backtracking. Also discussed are binary trees, heuristic and near optimums, matrix multiplication, and NP-complete problems. New to this edition: Chapter 9
Bunyavirus-Vector Interactions
Directory of Open Access Journals (Sweden)
Kate McElroy Horne
2014-11-01
Full Text Available The Bunyaviridae family is comprised of more than 350 viruses, of which many within the Hantavirus, Orthobunyavirus, Nairovirus, Tospovirus, and Phlebovirus genera are significant human or agricultural pathogens. The viruses within the Orthobunyavirus, Nairovirus, and Phlebovirus genera are transmitted by hematophagous arthropods, such as mosquitoes, midges, flies, and ticks, and their associated arthropods not only serve as vectors but also as virus reservoirs in many cases. This review presents an overview of several important emerging or re-emerging bunyaviruses and describes what is known about bunyavirus-vector interactions based on epidemiological, ultrastructural, and genetic studies of members of this virus family.
Free topological vector spaces
Gabriyelyan, Saak S.; Morris, Sidney A.
2016-01-01
We define and study the free topological vector space $\\mathbb{V}(X)$ over a Tychonoff space $X$. We prove that $\\mathbb{V}(X)$ is a $k_\\omega$-space if and only if $X$ is a $k_\\omega$-space. If $X$ is infinite, then $\\mathbb{V}(X)$ contains a closed vector subspace which is topologically isomorphic to $\\mathbb{V}(\\mathbb{N})$. It is proved that if $X$ is a $k$-space, then $\\mathbb{V}(X)$ is locally convex if and only if $X$ is discrete and countable. If $X$ is a metrizable space it is shown ...
Eisenman, Richard L
2005-01-01
This outstanding text and reference applies matrix ideas to vector methods, using physical ideas to illustrate and motivate mathematical concepts but employing a mathematical continuity of development rather than a physical approach. The author, who taught at the U.S. Air Force Academy, dispenses with the artificial barrier between vectors and matrices--and more generally, between pure and applied mathematics.Motivated examples introduce each idea, with interpretations of physical, algebraic, and geometric contexts, in addition to generalizations to theorems that reflect the essential structur
Energy Technology Data Exchange (ETDEWEB)
Rejon-Barrera, Fernando [Institute for Theoretical Physics, University of Amsterdam,Science Park 904, Postbus 94485, 1090 GL, Amsterdam (Netherlands); Robbins, Daniel [Department of Physics, Texas A& M University,TAMU 4242, College Station, TX 77843 (United States)
2016-01-22
We work out all of the details required for implementation of the conformal bootstrap program applied to the four-point function of two scalars and two vectors in an abstract conformal field theory in arbitrary dimension. This includes a review of which tensor structures make appearances, a construction of the projectors onto the required mixed symmetry representations, and a computation of the conformal blocks for all possible operators which can be exchanged. These blocks are presented as differential operators acting upon the previously known scalar conformal blocks. Finally, we set up the bootstrap equations which implement crossing symmetry. Special attention is given to the case of conserved vectors, where several simplifications occur.
Multithreading in vector processors
Energy Technology Data Exchange (ETDEWEB)
Evangelinos, Constantinos; Kim, Changhoan; Nair, Ravi
2018-01-16
In one embodiment, a system includes a processor having a vector processing mode and a multithreading mode. The processor is configured to operate on one thread per cycle in the multithreading mode. The processor includes a program counter register having a plurality of program counters, and the program counter register is vectorized. Each program counter in the program counter register represents a distinct corresponding thread of a plurality of threads. The processor is configured to execute the plurality of threads by activating the plurality of program counters in a round robin cycle.
Applying Genetic Algorithms To Query Optimization in Document Retrieval.
Horng, Jorng-Tzong; Yeh, Ching-Chang
2000-01-01
Proposes a novel approach to automatically retrieve keywords and then uses genetic algorithms to adapt the keyword weights. Discusses Chinese text retrieval, term frequency rating formulas, vector space models, bigrams, the PAT-tree structure for information retrieval, query vectors, and relevance feedback. (Author/LRW)
DEFF Research Database (Denmark)
Nielsen, Ole Haagen; Coskun, Mehmet; Weiss, Günter
2016-01-01
PURPOSE OF REVIEW: Approximately, one-third of the world's population suffers from anemia, and at least half of these cases are because of iron deficiency. With the introduction of new intravenous iron preparations over the last decade, uncertainty has arisen when these compounds should...... be administered and under which circumstances oral therapy is still an appropriate and effective treatment. RECENT FINDINGS: Numerous guidelines are available, but none go into detail about therapeutic start and end points or how iron-deficiency anemia should be best treated depending on the underlying cause...... of iron deficiency or in regard to concomitant underlying or additional diseases. SUMMARY: The study points to major issues to be considered in revisions of future guidelines for the true optimal iron replacement therapy, including how to assess the need for treatment, when to start and when to stop...
On mesh rezoning algorithms for parallel platforms
Energy Technology Data Exchange (ETDEWEB)
Plaskacz, E.J.
1995-07-01
A mesh rezoning algorithm for finite element simulations in a parallel-distributed environment is described. The cornerstones of the algorithm are: the parallel computation of distortion norms on the element and subdomain level, the exchange of the individual subdomain norms to form a subdomain distortion vector, the classification of subdomains and the rezoning behavior prescribed within each subdomain as a response to its own classification and the classification of neighboring subdomains.
Jordan, Raymond W.
1992-01-01
A valve with an O-ring, a disk seal, and a replaceable valve seat is presented. A groove in the bottom on the valve seat flange forms an inner and outer drip ledge with the inner and outer periphery of the flange. If leakage occurs at the valve seat O-ring, fluid droplets will form on the out drip ledge. If leakage occurs at the disk seal, fluid droplets will form on the inner drip ledge. A visual inspection of these drip ledges through an access port, or by a borescope placed in an inspection port, can discriminate between a leak which originates in the O-ring and a leak which originates in the disk seal. When conventional replaceable valve seats leak, fluid droplets form at the bottom on the valve seat. In the present invention, such a valve seat is modified by machining a groove on the bottom surface of the valve seat flange. This groove and the inner and outer surfaces of the flange intersect and form drip ledges. If leakage occurs at the valve seat seal, shown as an O-ring in the preferred embodiment, fluid droplets will form on the outer drip ledge. If leakage occurs at the valve disk seal, fluid droplets will form on the inner drip ledge. The drip ledges can be inspected either through an access port or by passing a borescope through a small inspection port in the valve case. Visual inspection of the bottom on the drip ledge will positively identify the required repair action.
Experimental Evaluation of Integral Transformations for Engineering Drawings Vectorization
Directory of Open Access Journals (Sweden)
Vaský Jozef
2014-12-01
Full Text Available The concept of digital manufacturing supposes application of digital technologies in the whole product life cycle. Direct digital manufacturing includes such information technology processes, where products are directly manufactured from 3D CAD model. In digital manufacturing, engineering drawing is replaced by CAD product model. In the contemporary practice, lots of engineering paper-based drawings are still archived. They could be digitalized by scanner and stored to one of the raster graphics format and after that vectorized for interactive editing in the specific software system for technical drawing or for archiving in some of the standard vector graphics file format. The vector format is suitable for 3D model generating, too.The article deals with using of selected integral transformations (Fourier, Hough in the phase of digitalized raster engineering drawings vectorization.
Delgado, Juan A.; Altuve, Miguel; Nabhan Homsi, Masun
2015-12-01
This paper introduces a robust method based on the Support Vector Machine (SVM) algorithm to detect the presence of Fetal QRS (fQRS) complexes in electrocardiogram (ECG) recordings provided by the PhysioNet/CinC challenge 2013. ECG signals are first segmented into contiguous frames of 250 ms duration and then labeled in six classes. Fetal segments are tagged according to the position of fQRS complex within each one. Next, segment features extraction and dimensionality reduction are obtained by applying principal component analysis on Haar-wavelet transform. After that, two sub-datasets are generated to separate representative segments from atypical ones. Imbalanced class problem is dealt by applying sampling without replacement on each sub-dataset. Finally, two SVMs are trained and cross-validated using the two balanced sub-datasets separately. Experimental results show that the proposed approach achieves high performance rates in fetal heartbeats detection that reach up to 90.95% of accuracy, 92.16% of sensitivity, 88.51% of specificity, 94.13% of positive predictive value and 84.96% of negative predictive value. A comparative study is also carried out to show the performance of other two machine learning algorithms for fQRS complex estimation, which are K-nearest neighborhood and Bayesian network.
Directory of Open Access Journals (Sweden)
Hailun Wang
2017-01-01
Full Text Available Support vector regression algorithm is widely used in fault diagnosis of rolling bearing. A new model parameter selection method for support vector regression based on adaptive fusion of the mixed kernel function is proposed in this paper. We choose the mixed kernel function as the kernel function of support vector regression. The mixed kernel function of the fusion coefficients, kernel function parameters, and regression parameters are combined together as the parameters of the state vector. Thus, the model selection problem is transformed into a nonlinear system state estimation problem. We use a 5th-degree cubature Kalman filter to estimate the parameters. In this way, we realize the adaptive selection of mixed kernel function weighted coefficients and the kernel parameters, the regression parameters. Compared with a single kernel function, unscented Kalman filter (UKF support vector regression algorithms, and genetic algorithms, the decision regression function obtained by the proposed method has better generalization ability and higher prediction accuracy.
Directory of Open Access Journals (Sweden)
Anna Bourmistrova
2011-02-01
Full Text Available The autodriver algorithm is an intelligent method to eliminate the need of steering by a driver on a well-defined road. The proposed method performs best on a four-wheel steering (4WS vehicle, though it is also applicable to two-wheel-steering (TWS vehicles. The algorithm is based on coinciding the actual vehicle center of rotation and road center of curvature, by adjusting the kinematic center of rotation. The road center of curvature is assumed prior information for a given road, while the dynamic center of rotation is the output of dynamic equations of motion of the vehicle using steering angle and velocity measurements as inputs. We use kinematic condition of steering to set the steering angles in such a way that the kinematic center of rotation of the vehicle sits at a desired point. At low speeds the ideal and actual paths of the vehicle are very close. With increase of forward speed the road and tire characteristics, along with the motion dynamics of the vehicle cause the vehicle to turn about time-varying points. By adjusting the steering angles, our algorithm controls the dynamic turning center of the vehicle so that it coincides with the road curvature center, hence keeping the vehicle on a given road autonomously. The position and orientation errors are used as feedback signals in a closed loop control to adjust the steering angles. The application of the presented autodriver algorithm demonstrates reliable performance under different driving conditions.
DEFF Research Database (Denmark)
Gustavson, Fred G.; Reid, John K.; Wasniewski, Jerzy
2007-01-01
variables, and the speed is usually better than that of the LAPACK algorithm that uses full storage (n2 variables). Included are subroutines for rearranging a matrix whose upper or lower-triangular part is packed by columns to this format and for the inverse rearrangement. Also included is a kernel...
Image coding through predictive vector quantization
Narayan, Ajai; Ramabadran, Tenkasi V.
1993-01-01
This paper describes a predictive vector quantizer (PVQ) for coding grayscale images. The method described can be regarded as an extension of an existing speech coding algorithm in 1- dimension to 2-dimensional images. The method applies vector quantization (VQ) to innovations generated by the well known scalar differential pulse code modulation (DPCM) method. It tries to exploit the advantages of both the simplicity of DPCM and the high compressibility of VQ. Two types of code books, viz., random and deterministic, are used in the implementation. Performance results of the method with both types of codebooks are presented for industrial radiographic images. The results are also compared with reconstructions obtained using the discrete cosine transform (DCT) method.
phenix.mr_rosetta: molecular replacement and model rebuilding with Phenix and Rosetta.
Terwilliger, Thomas C; Dimaio, Frank; Read, Randy J; Baker, David; Bunkóczi, Gábor; Adams, Paul D; Grosse-Kunstleve, Ralf W; Afonine, Pavel V; Echols, Nathaniel
2012-06-01
The combination of algorithms from the structure-modeling field with those of crystallographic structure determination can broaden the range of templates that are useful for structure determination by the method of molecular replacement. Automated tools in phenix.mr_rosetta simplify the application of these combined approaches by integrating Phenix crystallographic algorithms and Rosetta structure-modeling algorithms and by systematically generating and evaluating models with a combination of these methods. The phenix.mr_rosetta algorithms can be used to automatically determine challenging structures. The approaches used in phenix.mr_rosetta are described along with examples that show roles that structure-modeling can play in molecular replacement.
Analysing Music with Point-Set Compression Algorithms
DEFF Research Database (Denmark)
Meredith, David
2016-01-01
Several point-set pattern-discovery and compression algorithms designed for analysing music are reviewed and evaluated. Each algorithm takes as input a point-set representation of a score in which each note is represented as a point in pitch-time space. Each algorithm computes the maximal...... translatable patterns (MTPs) in this input and the translational equivalence classes (TECs) of these MTPs, where each TEC contains all the occurrences of a given MTP. Each TEC is encoded as a ⟨pattern,vector set⟩ pair, in which the vector set gives all the vectors by which the pattern can be translated...... and sections in pieces of classical music. On the first task, the best-performing algorithms achieved success rates of around 84%. In the second task, the best algorithms achieved mean F1 scores of around 0.49, with scores for individual pieces rising as high as 0.71....
Support Vector Components Analysis
van der Ree, Michiel; Roerdink, Johannes; Phillips, Christophe; Garraux, Gaetan; Salmon, Eric; Wiering, Marco
2017-01-01
In this paper we propose a novel method for learning a distance metric in the process of training Support Vector Machines (SVMs) with the radial basis function kernel. A transformation matrix is adapted in such a way that the SVM dual objective of a classification problem is optimized. By using a
Sesquilinear uniform vector integral
Indian Academy of Sciences (India)
1Faculty of Mathematics and Computer Science, University of Bucharest, Bucharest,. Academiei Str., 14, 010014, Romania. 2Technical University of Civil ... an integral of scalar functions with respect to vector measures, Dunford and his school introduced the spectral operators, thus founding the present operator theory (see ...
Indian Academy of Sciences (India)
Home; Journals; Resonance – Journal of Science Education; Volume 5; Issue 3. Orthogonalisation of Vectors - Matrix Decomposition and Approximation Problems. Rajendra Bhatia. General Article Volume 5 ... Author Affiliations. Rajendra Bhatia1. Indian Statistical Institute 7, SJS Sansanwal Marg, New Delhi 110 016, India.
Treiman, Jay S
2014-01-01
Calculus with Vectors grew out of a strong need for a beginning calculus textbook for undergraduates who intend to pursue careers in STEM. fields. The approach introduces vector-valued functions from the start, emphasizing the connections between one-variable and multi-variable calculus. The text includes early vectors and early transcendentals and includes a rigorous but informal approach to vectors. Examples and focused applications are well presented along with an abundance of motivating exercises. All three-dimensional graphs have rotatable versions included as extra source materials and may be freely downloaded and manipulated with Maple Player; a free Maple Player App is available for the iPad on iTunes. The approaches taken to topics such as the derivation of the derivatives of sine and cosine, the approach to limits, and the use of "tables" of integration have been modified from the standards seen in other textbooks in order to maximize the ease with which students may comprehend the material. Additio...
Centers for Disease Control (CDC) Podcasts
2011-04-18
This podcast discusses emerging vector-borne pathogens, their role as prominent contributors to emerging infectious diseases, how they're spread, and the ineffectiveness of mosquito control methods. Created: 4/18/2011 by National Center for Emerging Zoonotic and Infectious Diseases (NCEZID). Date Released: 4/27/2011.
Application of Hybrid Quantum Tabu Search with Support Vector Regression (SVR for Load Forecasting
Directory of Open Access Journals (Sweden)
Cheng-Wen Lee
2016-10-01
Full Text Available Hybridizing chaotic evolutionary algorithms with support vector regression (SVR to improve forecasting accuracy is a hot topic in electricity load forecasting. Trapping at local optima and premature convergence are critical shortcomings of the tabu search (TS algorithm. This paper investigates potential improvements of the TS algorithm by applying quantum computing mechanics to enhance the search information sharing mechanism (tabu memory to improve the forecasting accuracy. This article presents an SVR-based load forecasting model that integrates quantum behaviors and the TS algorithm with the support vector regression model (namely SVRQTS to obtain a more satisfactory forecasting accuracy. Numerical examples demonstrate that the proposed model outperforms the alternatives.
Crisp Clustering Algorithm for 3D Geospatial Vector Data Quantization
DEFF Research Database (Denmark)
Azri, Suhaibah; Anton, François; Ujang, Uznir
2015-01-01
In the next few years, 3D data is expected to be an intrinsic part of geospatial data. However, issues on 3D spatial data management are still in the research stage. One of the issues is performance deterioration during 3D data retrieval. Thus, a practical 3D index structure is required for effic...
Hybrid viral vectors for vaccine and antibody production in plants.
Yusibov, Vidadi; Streatfield, Stephen J; Kushnir, Natasha; Roy, Gourgopal; Padmanaban, Annamalai
2013-01-01
Plants have a demonstrated potential for large-scale, rapid production of recombinant proteins for diverse product applications, including subunit vaccines and monoclonal antibodies. In this field, the accent has recently shifted from the engineering of "edible" vaccines based on stable expression of target protein in transgenic or transplastomic plants to the development of purified formulated vaccines that are delivered via injection. The injectable vaccines are commonly produced using transient expression of target gene delivered into genetically unmodified plant host via viral or bacterial vectors. Most viral vectors are based on plant RNA viruses, where nonessential sequences are replaced with the gene of interest. Utilization of viral hybrids that consist of genes and regulatory elements of different virus species, or transcomplementation systems (vector/transgene) had a substantial impact on the level of target protein expression. Development and introduction of agroviral hybrid vectors that combine genetic elements of bacterial binary plasmids and plant viral vectors, and agroinfiltration as a tool of the vector delivery have resulted in significant progress in large-scale production of recombinant vaccines and monoclonal antibodies in plants. This article presents an overview of plant hybrid viral vector expression systems developed so far.
Evaluating automatically parallelized versions of the support vector machine
Codreanu, Valeriu; Droge, Bob; Williams, David; Yasar, Burhan; Yang, Fo; Liu, Baoquan; Dong, Feng; Surinta, Olarik; Schomaker, Lambertus; Roerdink, Jos; Wiering, Marco
2014-01-01
The support vector machine (SVM) is a supervised learning algorithm used for recognizing patterns in data. It is a very popular technique in machine learning and has been successfully used in applications such as image classification, protein classification, and handwriting recognition. However, the
Support Vector Machines: Relevance Feedback and Information Retrieval.
Drucker, Harris; Shahrary, Behzad; Gibbon, David C.
2002-01-01
Compares support vector machines (SVMs) to Rocchio, Ide regular and Ide dec-hi algorithms in information retrieval (IR) of text documents using relevancy feedback. If the preliminary search is so poor that one has to search through many documents to find at least one relevant document, then SVM is preferred. Includes nine tables. (Contains 24…
Support vector machine: a tool for mapping mineral prospectivity
Zuo, R.; Carranza, E.J.M
2011-01-01
In this contribution, we describe an application of support vector machine (SVM), a supervised learning algorithm, to mineral prospectivity mapping. The free R package e1071 is used to construct a SVM with sigmoid kernel function to map prospectivity for Au deposits in western Meguma Terrain of Nova
Landslide susceptibility mapping using support vector machine and ...
Indian Academy of Sciences (India)
learning algorithm; Eng. Geol. 123 225–234. Micheletti N 2011 Landslide susceptibility mapping using adaptive support vector machines and feature selection,. A Master Thesis submitted to University of Lausanne. Faculty of Geosciences and Environment for the Degree of Master of Science in Environmental Geosciences,.
Using of support vector machines for link spam detection
Sharapov, Ruslan V.; Sharapova, Ekaterina V.
2011-10-01
In this article we described methods of link spam detection with using of machine learning. We analyzed main factors of link spam, which helps to find them. There is algorithm of link spam detection, based on support vector machines. The methods of link spam detection shows good results
Minimal order observers for linear functions of the state vector
Srinathkumar, S.
1978-01-01
The problem of estimating linear functions of a state vector in a multi-input/output system is considered. A simple lower bound on the observer order with arbitrary eigenvalues is established. Algorithms to construct minimal-order stable (or arbitrary dynamics) observers are also outlined.
McMurray, Michael A.; Thorner, Jeremy W.
2015-01-01
Septins are guanine nucleotide-binding proteins that form hetero-oligomeric complexes, which assemble into filaments and higher-order structures at sites of cell division and morphogenesis in eukaryotes. Dynamic changes in the organization of septin-containing structures occur concomitantly with progression through the mitotic cell cycle and during cell differentiation. Septins also undergo stage-specific post-translational modifications, which have been implicated in regulating their dynamics, in some cases via purported effects on septin turnover. In our recent study, the fate of two of the five septins expressed in mitotic cells of budding yeast (Saccharomyces cerevisiae) was tracked using two complementary fluorescence-based methods for pulse-chase analysis. During mitotic growth, previously-made molecules of both septins (Cdc10 and Cdc12) persisted through multiple successive divisions and were incorporated equivalently with newly synthesized molecules into hetero-oligomers and higher-order structures. Similarly, in cells undergoing meiosis and the developmental program of sporulation, pre-existing copies of Cdc10 were incorporated into new structures. In marked contrast, Cdc12 was irreversibly excluded from septin complexes and replaced by another septin, Spr3. Here, we discuss the broader implications of these results and related findings with regard to how septin dynamics is coordinated with the mitotic cell cycle and in the yeast life cycle, and how these observations may relate to control of the dynamics of other complex multi-subunit assemblies. PMID:19164941
DEFF Research Database (Denmark)
Markham, Annette
layered set of accounts to help build our understanding of how individuals relate to their devices, search systems, and social network sites. This work extends critical analyses of the power of algorithms in implicating the social self by offering narrative accounts from multiple perspectives. It also......This paper takes an actor network theory approach to explore some of the ways that algorithms co-construct identity and relational meaning in contemporary use of social media. Based on intensive interviews with participants as well as activity logging and data tracking, the author presents a richly...... contributes an innovative method for blending actor network theory with symbolic interaction to grapple with the complexity of everyday sensemaking practices within networked global information flows....
Implementation of the "Non-Local Bayes" (NL-Bayes Image Denoising Algorithm
Directory of Open Access Journals (Sweden)
Marc Lebrun
2013-06-01
Full Text Available This article presents a detailed implementation of the Non-Local Bayes (NL-Bayes image denoising algorithm. In a nutshell, NL-Bayes is an improved variant of NL-means. In the NL-means algorithm, each patch is replaced by a weighted mean of the most similar patches present in a neighborhood. Images being mostly self-similar, such instances of similar patches are generally found, and averaging them increases the SNR. The NL-Bayes strategy improves on NL-means by evaluating for each group of similar patches a Gaussian vector model. To each patch is therefore associated a mean (which would be the result of NL-means, but also a covariance matrix estimating the variability of the patch group. This permits to compute an optimal (in the sense of Bayesian minimal mean square error estimate of each noisy patch in the group, by a simple matrix inversion. The implementation proceeds in two identical iterations, but the second iteration uses the denoised image of the first iteration to estimate better the mean and covariance of the patch Gaussian models. A discussion of the algorithm shows that it is close in spirit to several state of the art algorithms (TSID, BM3D, BM3D-SAPCA, and that its structure is actually close to BM3D. Thorough experimental comparison made in this paper also shows that the algorithm achieves the best state of the art on color images in terms of PSNR and image quality. On grey level images, it reaches a performance similar to the more complex BM3D-SAPCA (no color version is available for this last algorithm.
Joint replacement in Zambia: A review of Hip & Knee Replacement ...
African Journals Online (AJOL)
Background: Incidence of major joint replacement surgery is on the rise in Africa but this trend has not been matched by proper audits in the form of National Joint Registries. Objective: This paper presents the short-term findings from a joint replacement register started at the Zambian-Italian Orthopaedic Hospital (ZIOH) in ...
Parallel algorithms for numerical linear algebra
van der Vorst, H
1990-01-01
This is the first in a new series of books presenting research results and developments concerning the theory and applications of parallel computers, including vector, pipeline, array, fifth/future generation computers, and neural computers.All aspects of high-speed computing fall within the scope of the series, e.g. algorithm design, applications, software engineering, networking, taxonomy, models and architectural trends, performance, peripheral devices.Papers in Volume One cover the main streams of parallel linear algebra: systolic array algorithms, message-passing systems, algorithms for p
Optimizing connected component labeling algorithms
Energy Technology Data Exchange (ETDEWEB)
Wu, Kesheng; Otoo, Ekow; Shoshani, Arie
2005-01-16
This paper presents two new strategies that can be used to greatly improve the speed of connected component labeling algorithms. To assign a label to a new object, most connected component labeling algorithms use a scanning step that examines some of its neighbors. The first strategy exploits the dependencies among them to reduce the number of neighbors examined. When considering 8-connected components in a 2D image, this can reduce the number of neighbors examined from four to one in many cases. The second strategy uses an array to store the equivalence information among the labels. This replaces the pointer based rooted trees used to store the same equivalence information. It reduces the memory required and also produces consecutive final labels. Using an array instead of the pointer based rooted trees speeds up the connected component labeling algorithms by a factor of 5 {approx} 100 in our tests on random binary images.
Scope of Support Vector Machine in Steganography
Tanwar, Rohit; Malhotrab, Sona
2017-08-01
Steganography is a technique used for secure transmission of data. Using audio as a cover file opens path for many extra features. In order to overcome the limitations of conventional LSB technique, various variants were proposed by different authors. In order to achieve robustness, use of various optimization techniques has been tradition. In this paper the focus is put on use of Genetic Algorithm and Particle Swarm Intelligence in steganography. To list detailed scope, merits and de-merits of the two optimization techniques is the main constituent of this paper. In spite of analyzing the two techniques, the motivation and applicability of machine learning algorithm in the problem statement is also discussed. This paper will guide the path in using Support Vector Machine for optimizing the data hiding.
Rudakov, A N
1990-01-01
This volume is devoted to the use of helices as a method for studying exceptional vector bundles, an important and natural concept in algebraic geometry. The work arises out of a series of seminars organised in Moscow by A. N. Rudakov. The first article sets up the general machinery, and later ones explore its use in various contexts. As to be expected, the approach is concrete; the theory is considered for quadrics, ruled surfaces, K3 surfaces and P3(C).
Anisotropic vector Preisach particle
Fuezi, J
2000-01-01
The static 2D vector magnetic behaviour of an anisotropic silicon iron sheet is modelled by a particle which depicts its space-averaged behaviour. The magnitude of magnetization is governed by a classical Preisach operator with the projection of field strength on the magnetization direction as input. Its orientation is determined by the equilibrium between the field strength orientation and the anisotropy of the sheet.
Interruption of vector transmission by native vectors and the art of the possible
Directory of Open Access Journals (Sweden)
Roberto Salvatella
2014-02-01
Full Text Available In a recent article in the Reader’s Opinion, advantages and disadvantages of the certification processes of interrupted Chagas disease transmission (American trypanosomiasis by native vector were discussed. Such concept, accepted by those authors for the case of endemic situations with introduced vectors, has been built on a long and laborious process by endemic countries and Subregional Initiatives for Prevention, Control and Treatment of Chagas, with Technical Secretariat of the Pan American Health Organization/World Health Organization, to create a horizon target and goal to concentrate priorities and resource allocation and actions. With varying degrees of sucess, which are not replaceable for a certificate of good practice, has allowed during 23 years to safeguard the effective control of transmission of Trypanosoma cruzi not to hundreds of thousands, but millions of people at risk conditions, truly “the art of the possible.”
Morgan, Eric René; Booth, Mark; Norman, Rachel; Mideo, Nicole; McCallum, Hamish; Fenton, Andy
2017-01-01
Many important and rapidly emerging pathogens of humans, livestock and wildlife are ‘vector-borne’. However, the term ‘vector’ has been applied to diverse agents in a broad range of epidemiological systems. In this perspective, we briefly review some common definitions, identify the strengths and weaknesses of each and consider the functional differences between vectors and other hosts from a range of ecological, evolutionary and public health perspectives. We then consider how the use of designations can afford insights into our understanding of epidemiological and evolutionary processes that are not otherwise apparent. We conclude that from a medical and veterinary perspective, a combination of the ‘haematophagous arthropod’ and ‘mobility’ definitions is most useful because it offers important insights into contact structure and control and emphasizes the opportunities for pathogen shifts among taxonomically similar species with similar feeding modes and internal environments. From a population dynamics and evolutionary perspective, we suggest that a combination of the ‘micropredator’ and ‘sequential’ definition is most appropriate because it captures the key aspects of transmission biology and fitness consequences for the pathogen and vector itself. However, we explicitly recognize that the value of a definition always depends on the research question under study. This article is part of the themed issue ‘Opening the black box: re-examining the ecology and evolution of parasite transmission’. PMID:28289253
Lentiviral Vector Mediated Transgenesis.
Barde, Isabelle; Verp, Sonia; Offner, Sandra; Trono, Didier
2011-03-01
The genetic manipulation of rodents through the generation of fully transgenic animals or via the modification of selective cells or organs is a procedure of paramount importance for biomedical research, either to address fundamental questions or to develop preclinical models of human diseases. Lentiviral vectors occupy the front stage in this scene, as they can mediate the integration and stable expression of transgenes both in vitro and in vivo. Widely used to modify a variety of cells, including re-implantable somatic and embryonic stem cells, lentiviral vectors can also be directly administered in vivo, for instance in the brain. However, perhaps their most spectacular research application is in the generation of transgenic animals. Compared with the three-decade-old DNA pronuclear injection technique, lentivector-mediated transgenesis is simple, cheap, and highly efficient. Furthermore, it can take full advantage of the great diversity of lentiviral vectors developed for other applications, and thus allows for ubiquitous or tissue-specific or constitutive or externally controllable transgene expression, as well as RNAi-mediated gene knockdown. Curr. Protoc. Mouse Biol. 1:169-184. © 2011 by John Wiley & Sons, Inc. Copyright © 2011 John Wiley & Sons, Inc.
Reece-Hoyes, John S; Walhout, Albertha J M
2018-01-02
Generating stocks of Entry and Destination vectors for use in the Gateway recombinatorial cloning system requires transforming them into Escherichia coli strain DB3.1, where they can replicate because this strain is immune to the effects of the ccdB gene carried in the Gateway cassette. However, mutations in the ccdB gene can arise at low frequency, and these mutant plasmids will consequently allow growth of standard cloning strains of E. coli (e.g., DH5α). Therefore, after making new stocks of Gateway plasmids, their ability to grow in cloning strains of E. coli must be tested. This involves obtaining multiple stocks of vector, each arising from a single plasmid grown in a single DB3.1 bacterial colony, and transforming each stock into both DB3.1 and the preferred cloning strain of E. coli in a controlled fashion. Only vector stocks that effectively kill the standard cloning strain (i.e., no or few colonies are obtained after transformation) should be used in Gateway cloning reactions. The sequence can be performed in 3 d. © 2018 Cold Spring Harbor Laboratory Press.
A Turn-Projected State-Based Conflict Resolution Algorithm
Butler, Ricky W.; Lewis, Timothy A.
2013-01-01
State-based conflict detection and resolution (CD&R) algorithms detect conflicts and resolve them on the basis on current state information without the use of additional intent information from aircraft flight plans. Therefore, the prediction of the trajectory of aircraft is based solely upon the position and velocity vectors of the traffic aircraft. Most CD&R algorithms project the traffic state using only the current state vectors. However, the past state vectors can be used to make a better prediction of the future trajectory of the traffic aircraft. This paper explores the idea of using past state vectors to detect traffic turns and resolve conflicts caused by these turns using a non-linear projection of the traffic state. A new algorithm based on this idea is presented and validated using a fast-time simulator developed for this study.
Bridge health monitoring metrics : updating the bridge deficiency algorithm.
2009-10-01
As part of its bridge management system, the Alabama Department of Transportation (ALDOT) must decide how best to spend its bridge replacement funds. In making these decisions, ALDOT managers currently use a deficiency algorithm to rank bridges that ...
Minimally invasive aortic valve replacement
DEFF Research Database (Denmark)
Foghsgaard, Signe; Schmidt, Thomas Andersen; Kjaergard, Henrik K
2009-01-01
In this descriptive prospective study, we evaluate the outcomes of surgery in 98 patients who were scheduled to undergo minimally invasive aortic valve replacement. These patients were compared with a group of 50 patients who underwent scheduled aortic valve replacement through a full sternotomy...
Conjugate gradient algorithms using multiple recursions
Energy Technology Data Exchange (ETDEWEB)
Barth, T.; Manteuffel, T.
1996-12-31
Much is already known about when a conjugate gradient method can be implemented with short recursions for the direction vectors. The work done in 1984 by Faber and Manteuffel gave necessary and sufficient conditions on the iteration matrix A, in order for a conjugate gradient method to be implemented with a single recursion of a certain form. However, this form does not take into account all possible recursions. This became evident when Jagels and Reichel used an algorithm of Gragg for unitary matrices to demonstrate that the class of matrices for which a practical conjugate gradient algorithm exists can be extended to include unitary and shifted unitary matrices. The implementation uses short double recursions for the direction vectors. This motivates the study of multiple recursion algorithms.
Casanova, Henri; Robert, Yves
2008-01-01
""…The authors of the present book, who have extensive credentials in both research and instruction in the area of parallelism, present a sound, principled treatment of parallel algorithms. … This book is very well written and extremely well designed from an instructional point of view. … The authors have created an instructive and fascinating text. The book will serve researchers as well as instructors who need a solid, readable text for a course on parallelism in computing. Indeed, for anyone who wants an understandable text from which to acquire a current, rigorous, and broad vi
Approximate Nearest Neighbor Search for a Dataset of Normalized Vectors
Terasawa, Kengo; Tanaka, Yuzuru
This paper describes a novel algorithm for approximate nearest neighbor searching. For solving this problem especially in high dimensional spaces, one of the best-known algorithm is Locality-Sensitive Hashing (LSH). This paper presents a variant of the LSH algorithm that outperforms previously proposed methods when the dataset consists of vectors normalized to unit length, which is often the case in pattern recognition. The LSH scheme is based on a family of hash functions that preserves the locality of points. This paper points out that for our special case problem we can design efficient hash functions that map a point on the hypersphere into the closest vertex of the randomly rotated regular polytope. The computational analysis confirmed that the proposed method could improve the exponent ρ, the main indicator of the performance of the LSH algorithm. The practical experiments also supported the efficiency of our algorithm both in time and in space.
A Motion Estimation Algorithm Using DTCWT and ARPS
Directory of Open Access Journals (Sweden)
Unan Y. Oktiawati
2013-09-01
Full Text Available In this paper, a hybrid motion estimation algorithm utilizing the Dual Tree Complex Wavelet Transform (DTCWT and the Adaptive Rood Pattern Search (ARPS block is presented. The proposed algorithm first transforms each video sequence with DTCWT. The frame n of the video sequence is used as a reference input and the frame n+2 is used to find the motion vector. Next, the ARPS block search algorithm is carried out and followed by an inverse DTCWT. The motion compensation is then carried out on each inversed frame n and motion vector. The results show that PSNR can be improved for mobile device without depriving its quality. The proposed algorithm also takes less memory usage compared to the DCT-based algorithm. The main contribution of this work is a hybrid wavelet-based motion estimation algorithm for mobile devices. Other contribution is the visual quality scoring system as used in section 6.
Scalar - vector soliton fiber lasers
Wu, Zhichao; Li, Lei; Luo, Yiyang; Tang, Dingyuan; Shen, Deyuan; Tang, Ming; Fu, Songnian; Zhao, Luming
2016-01-01
Rapid progress in passively mode-locked fiber lasers is currently driven by the recent discovery of vector feature of mode-locking pulses, namely, the group velocity-locked vector solitons, the phase locked vector solitons, and the high-order vector solitons. Those vector solitons are fundamentally different from the previously known scalar solitons. Here, we report a fiber laser where the mode-locked pulse evolves as a vector soliton in the strong birefringent segment and is transformed into a regular scalar soliton after the polarizer within the laser cavity. The existence of solutions in a polarization-dependent cavity comprising a periodic combination of two distinct nonlinear waves is novel and likely to be applicable to various other nonlinear systems. For very large local birefringence, our laser approaches the working regime of vector soliton lasers, while it approaches scalar soliton fiber lasers under the conditions of very small birefringence.
Vectors and strategies for nonviral cancer gene therapy.
Pahle, Jessica; Walther, Wolfgang
2016-01-01
This review presents recent developments in the use of nonviral vectors and transfer technologies in cancer gene therapy. Tremendous progress has been made in developing cancer gene therapy in ways that could be applicable to treatments. Numerous efforts are focused on methods of attacking known and novel targets more efficiently and specifically. In parallel to progress in nonviral vector design and delivery technologies, important achievements have been accomplished for suicide, gene replacement, gene suppression and immunostimulatory therapies. New nonviral cancer gene therapies have been developed based on emerging RNAi (si/shRNA-, miRNA) or ODN. This review provides an overview of recent gene therapeutic strategies in which nonviral vectors have been used experimentally and in clinical trials. Furthermore, we present current developments in nonviral vector systems in association with important chemical and physical gene delivery technologies and their potential for the future. Nonviral gene therapy has maintained its position as an approach for treating cancer. This is reflected by the fact that more than 17% of all gene therapy trials employ nonviral approaches. Thus, nonviral vectors have emerged as a clinical alternative to viral vectors for the appropriate expression and delivery of therapeutic genes.
Application of Bred Vectors To Data Assimilation
Corazza, M.; Kalnay, E.; Patil, Dj
subspace. The presence of low-dimensional regions in the perturbations of the basic flow has important implications for data assimilation. At any given time, there is a difference between the true atmospheric state and the model forecast. Assuming that model er- rors are not the dominant source of errors, in a region of low BV-dimensionality the difference between the true state and the forecast should lie substantially in the low dimensional unstable subspace of the few bred vectors that contribute most strongly to the low BV-dimension. This information should yield a substantial improvement in the forecast: the data assimilation algorithm should correct the model state by moving it closer to the observations along the unstable subspace, since this is where the true state most likely lies. Preliminary experiments have been conducted with the quasi-geostrophic data assim- ilation system testing whether it is possible to add "errors of the day" based on bred vectors to the standard (constant) 3D-Var background error covariance in order to capture these important errors. The results are extremely encouraging, indicating a significant reduction (about 40%) in the analysis errors at a very low computational cost. References: 2 Corazza, M., E. Kalnay, DJ Patil, R. Morss, M Cai, I. Szunyogh, BR Hunt, E Ott and JA Yorke, 2001: Use of the breeding technique to estimate the structure of the analysis "errors of the day". Submitted to Nonlinear Processes in Geophysics. Hamill, T.M., Snyder, C., and Morss, R.E., 2000: A Comparison of Probabilistic Fore- casts from Bred, Singular-Vector and Perturbed Observation Ensembles, Mon. Wea. Rev., 128, 18351851. Kalnay, E., and Z. Toth, 1994: Removing growing errors in the analysis cycle. Preprints of the Tenth Conference on Numerical Weather Prediction, Amer. Meteor. Soc., 1994, 212-215. Morss, R. E., 1999: Adaptive observations: Idealized sampling strategies for improv- ing numerical weather prediction. PHD thesis, Massachussetts Institute
Fast image mosaic algorithm based on the improved Harris-SIFT algorithm
Jiang, Zetao; Liu, Min
2015-08-01
This paper proposes a fast image mosaic algorithm based on the improved Harris-SIFT algorithm, according to such problems as more memory consumption, greater redundancy quantity of feature points, slower operation speed, and so on, resulting from using the SIFT algorithm in the image matching stage of the image mosaic process. Firstly in the matching stage of the algorithm, the corner point is extracted by using the multi-scale Harris, feature descriptor is constructed by the 88-dimensional vector based on the SIFT feature, the coarse matching is carried out by the nearest neighbor matching method, and then the precise matching point pair and image transformation matrix are obtained by the RANSAC method. The seamless mosaic can be achieved by using the weighted average image fusion. The experimental results show that this algorithm can not only achieve precise seamless mosaic but also improve operation efficiency, compared with the traditional algorithm.
Rodríguez, Yeinzon; Navarro, Andrés A.
2017-03-01
An alternative for the construction of fundamental theories is the introduction of Galileons. These are fields whose action leads to non higher than second-order equations of motion. As this is a necessary but not sufficient condition to make the Hamiltonian bounded from below, as long as the action is not degenerate, the Galileon construction is a way to avoid pathologies both at the classical and quantum levels. Galileon actions are, therefore, of great interest in many branches of physics, specially in high energy physics and cosmology. This proceedings contribution presents the generalities of the construction of both scalar and vector Galileons following two different but complimentary routes.
Architecture and Vector Control
DEFF Research Database (Denmark)
von Seidlein, Lorenz; Knols, Bart GJ; Kirby, Matthew
2012-01-01
of vector-borne diseases have no access to electricity. Many houses in the hot, humid regions of Asia have adapted to the environment, they are built of porous materials and are elevated on stilts features which allow a comfortable climate even in the presence of bednets and screens. In contrast, many...... buildings in Africa and Asia in respect to their indoor climate characteristics and finally, show how state-of-the-art 3D modelling can predict climate characteristics and help to optimize buildings....
INNOPLANT Total Hip Replacement System.
Harper, Tisha A M
2017-07-01
Total hip replacement is a salvage procedure that is done to alleviate discomfort secondary to osteoarthritis in the hip, which is most often a result of hip dysplasia. Commercially available total hip replacement implants for small animal patients are classified as cemented or cementless. The INNOPLANT Total Hip Replacement system includes modular, screw-in cementless components that were developed to improve implant stability by maintaining as much normal anatomic structure, and by extension biomechanics of the coxofemoral joint, as possible. As a newer system, there are few data and no long-term studies available in the veterinary literature. Copyright © 2017 Elsevier Inc. All rights reserved.
Parton-shower matching systematics in vector-boson-fusion WW production
Energy Technology Data Exchange (ETDEWEB)
Rauch, Michael [Karlsruhe Institute of Technology, Institute for Theoretical Physics, Karlsruhe (Germany); Plaetzer, Simon [Durham University, Institute for Particle Physics Phenomenology, Durham (United Kingdom); University of Manchester, School of Physics and Astronomy, Manchester (United Kingdom)
2017-05-15
We perform a detailed analysis of next-to-leading order plus parton-shower matching in vector-boson-fusion WW production including leptonic decays. The study is performed in the Herwig 7 framework interfaced to VBFNLO 3, using the angular-ordered and dipole-based parton-shower algorithms combined with the subtractive and multiplicative-matching algorithms. (orig.)
The Role of the Harmonic Vector Average in Motion Integration
Directory of Open Access Journals (Sweden)
Alan eJohnston
2013-10-01
Full Text Available The local speeds of object contours vary systematically with the cosine of the angle between the normal component of the local velocity and the global object motion direction. An array of Gabor elements whose speed changes with local spatial orientation in accordance with this pattern can appear to move as a single surface. The apparent direction of motion of plaids and Gabor arrays has variously been proposed to result from feature tracking, vector addition and vector averaging in addition to the geometrically correct global velocity as indicated by the intersection of constraints (IOC solution. Here a new combination rule, the harmonic vector average (HVA, is introduced, as well as a new algorithm for computing the IOC solution. The vector sum can be discounted as an integration strategy as it increases with the number of elements. The vector average over local vectors that vary in direction always provides an underestimate of the true global speed. The harmonic vector average however provides the correct global speed and direction for an unbiased sample of local velocities with respect to the global motion direction, as is the case for a simple closed contour. The HVA over biased samples provides an aggregate velocity estimate that can still be combined through an IOC computation to give an accurate estimate of the global velocity, which is not true of the vector average. Psychophysical results for type II Gabor arrays show perceived direction and speed falls close to the intersection of constraints direction for Gabor arrays having a wide range of orientations but the IOC prediction fails as the mean orientation shifts away from the global motion direction and the orientation range narrows. In this case perceived velocity generally defaults to the harmonic vector average.
Sequential and Adaptive Learning Algorithms for M-Estimation
Directory of Open Access Journals (Sweden)
Guang Deng
2008-05-01
Full Text Available The M-estimate of a linear observation model has many important engineering applications such as identifying a linear system under non-Gaussian noise. Batch algorithms based on the EM algorithm or the iterative reweighted least squares algorithm have been widely adopted. In recent years, several sequential algorithms have been proposed. In this paper, we propose a family of sequential algorithms based on the Bayesian formulation of the problem. The basic idea is that in each step we use a Gaussian approximation for the posterior and a quadratic approximation for the log-likelihood function. The maximum a posteriori (MAP estimation leads naturally to algorithms similar to the recursive least squares (RLSs algorithm. We discuss the quality of the estimate, issues related to the initialization and estimation of parameters, and robustness of the proposed algorithm. We then develop LMS-type algorithms by replacing the covariance matrix with a scaled identity matrix under the constraint that the determinant of the covariance matrix is preserved. We have proposed two LMS-type algorithms which are effective and low-cost replacement of RLS-type of algorithms working under Gaussian and impulsive noise, respectively. Numerical examples show that the performance of the proposed algorithms are very competitive to that of other recently published algorithms.
Directory of Open Access Journals (Sweden)
Zhan-bo Chen
2014-01-01
Full Text Available In order to improve the performance prediction accuracy of hydraulic excavator, the regression least squares support vector machine is applied. First, the mathematical model of the regression least squares support vector machine is studied, and then the algorithm of the regression least squares support vector machine is designed. Finally, the performance prediction simulation of hydraulic excavator based on regression least squares support vector machine is carried out, and simulation results show that this method can predict the performance changing rules of hydraulic excavator correctly.
Vector wave propagation method.
Fertig, M; Brenner, K-H
2010-04-01
In this paper, we extend the scalar wave propagation method (WPM) to vector fields. The WPM [Appl. Opt.32, 4984 (1993)] was introduced in order to overcome the major limitations of the beam propagation method (BPM). With the WPM, the range of application can be extended from the simulation of waveguides to simulation of other optical elements like lenses, prisms and gratings. In that reference it was demonstrated that the wave propagation scheme provides valid results for propagation angles up to 85 degrees and that it is not limited to small index variations in the axis of propagation. Here, we extend the WPM to three-dimensional vectorial fields (VWPMs) by considering the polarization dependent Fresnel coefficients for transmission in each propagation step. The continuity of the electric field is maintained in all three dimensions by an enhanced propagation vector and the transfer matrix. We verify the validity of the method by transmission through a prism and by comparison with the focal distribution from vectorial Debye theory. Furthermore, a two-dimensional grating is simulated and compared with the results from three-dimensional RCWA. Especially for 3D problems, the runtime of the VWPM exhibits special advantage over the RCWA.
Engineered AAV vectors for improved central nervous system gene delivery.
A Kotterman, Melissa; Schaffer, David V
2015-01-01
Adeno-associated viruses (AAV) are non-pathogenic members of the Parvoviridae family that are being harnessed as delivery vehicles for both basic research and increasingly successful clinical gene therapy. To address a number of delivery shortcomings with natural AAV variants, we have developed and implemented directed evolution-a high-throughput molecular engineering approach to generate novel biomolecules with enhanced function-to create novel AAV vectors that are designed to preferentially transduce specific cell types in the central nervous system (CNS), including astrocytes, neural stem cells, and cells within the retina. These novel AAV vectors-which have enhanced infectivity in vitro and enhanced infectivity and selectivity in vivo-can enable more efficient studies to further our understanding of neurogenesis, development, aging, and disease. Furthermore, such engineered vectors may aid gene or cell replacement therapies to treat neurodegenerative disease or injury.
Slab replacement maturity guidelines : [summary].
2014-04-01
Concrete sets in hours at moderate temperatures, : but the bonds that make concrete strong continue : to mature over days to years. However, for : replacement concrete slabs on highways, it is : crucial that concrete develop enough strength : within ...
Optimality Conditions in Vector Optimization
Jiménez, Manuel Arana; Lizana, Antonio Rufián
2011-01-01
Vector optimization is continuously needed in several science fields, particularly in economy, business, engineering, physics and mathematics. The evolution of these fields depends, in part, on the improvements in vector optimization in mathematical programming. The aim of this Ebook is to present the latest developments in vector optimization. The contributions have been written by some of the most eminent researchers in this field of mathematical programming. The Ebook is considered essential for researchers and students in this field.
Quantitative Measurements using Ultrasound Vector Flow Imaging
DEFF Research Database (Denmark)
Jensen, Jørgen Arendt
2016-01-01
L/stroke (true: 1.15 mL/stroke, bias: 12.2%). Measurements down to 160 mm were obtained with a relative standard deviation and bias of less than 10% for the lateral component for stationary, parabolic flow. The method can, thus, find quantitative velocities, angles, and volume flows at sites currently......Duplex Vector Flow Imaging (VFI) imaging is introduced as a replacement for spectral Doppler, as it automatically can yield fully quantitative flow estimates without angle correction. Continuous VFI data over 9 s for 10 pulse cycles were acquired by a 3 MHz convex probe connected to the SARUS...... scanner for pulsating flow mimicking the femoral artery from a CompuFlow 1000 pump (Shelley Medical). Data were used in four estimators based on directional transverse oscillation for velocity, flow angle, volume flow, and turbulence estimation and their respective precisions. An adaptive lag scheme gave...
Analysis of Torque Ripple Reduction in Induction Motor DTC Drive with Multiple Voltage Vectors
Directory of Open Access Journals (Sweden)
ROSIC, M. M.
2015-02-01
Full Text Available This paper shows an analysis of torque ripple reduction in modified DTC algorithm by using multiple voltage vectors with the appropriate multilevel hysteresis controller. A short theoretical background of classical and proposed DTC algorithm was given at the beginning. Experimental results of the proposed DTC algorithm, implemented on digital signal processor F2812, were analysed in comparison with classical DTC. It is shown that the torque ripple can be reduced by selecting voltage vectors with an appropriate intensity. Motor current oversampling was used to analyse the estimated torque behaviour during one DSP sampling period. Furthermore, the analysis of torque ripple reduction with oversampled torque values was conducted in relation to the number of available voltage vectors. The analysis shows that the proposed DTC algorithm allows significant torque ripple reduction while retaining the simplicity, small computational burden and good dynamic characteristics of the classical DTC.
A Performance Evaluation of Lightning-NO Algorithms in CMAQ
In the Community Multiscale Air Quality (CMAQv5.2) model, we have implemented two algorithms for lightning NO production; one algorithm is based on the hourly observed cloud-to-ground lightning strike data from National Lightning Detection Network (NLDN) to replace the previous m...
Energy Technology Data Exchange (ETDEWEB)
Fontana, W.
1990-12-13
In this paper complex adaptive systems are defined by a self- referential loop in which objects encode functions that act back on these objects. A model for this loop is presented. It uses a simple recursive formal language, derived from the lambda-calculus, to provide a semantics that maps character strings into functions that manipulate symbols on strings. The interaction between two functions, or algorithms, is defined naturally within the language through function composition, and results in the production of a new function. An iterated map acting on sets of functions and a corresponding graph representation are defined. Their properties are useful to discuss the behavior of a fixed size ensemble of randomly interacting functions. This function gas'', or Turning gas'', is studied under various conditions, and evolves cooperative interaction patterns of considerable intricacy. These patterns adapt under the influence of perturbations consisting in the addition of new random functions to the system. Different organizations emerge depending on the availability of self-replicators.
Directory of Open Access Journals (Sweden)
Congying Han
2013-01-01
is proved that the new algorithm can terminate at an ε-optimal solution within O(1/ε iterations. Moreover, no line search is needed in this algorithm, and the global convergence can be proved under mild conditions. Numerical results are reported for solving quadratic programs arising from the training of support vector machines, which show that the new algorithm is efficient.
DEFF Research Database (Denmark)
2000-01-01
Using a pulsed ultrasound field, the two-dimensional velocity vector can be determined with the invention. The method uses a transversally modulated ultrasound field for probing the moving medium under investigation. A modified autocorrelation approach is used in the velocity estimation. The new...... estimator automatically compensates for the axial velocity, when determining the transverse velocity by using fourth order moments rather than second order moments. The estimation is optimized by using a lag different from one in the estimation process, and noise artifacts are reduced by using averaging...... of RF samples. Further, compensation for the axial velocity can be introduced, and the velocity estimation is done at a fixed depth in tissue to reduce spatial velocity dispersion....
Multistage vector (MSV) therapeutics
Wolfram, Joy; Shen, Haifa; Ferrari, Mauro
2015-01-01
One of the greatest challenges in the field of medicine is obtaining controlled distribution of systemically administered therapeutic agents within the body. Indeed, biological barriers such as physical compartmentalization, pressure gradients, and excretion pathways adversely affect localized delivery of drugs to pathological tissue. The diverse nature of these barriers requires the use of multifunctional drug delivery vehicles that can overcome a wide range of sequential obstacles. In this review, we explore the role of multifunctionality in nanomedicine by primarily focusing on multistage vectors (MSVs). The MSV is an example of a promising therapeutic platform that incorporates several components, including a microparticle, nanoparticles, and small molecules. In particular, these components are activated in a sequential manner in order to successively address transport barriers. PMID:26264836
Vector-Tensor and Vector-Vector Decay Amplitude Analysis of B0->phi K*0
Aubert, B; Abrams, G S; Adye, T; Ahmed, S; Alam, M S; Albert, J; Aleksan, R; Allen, M T; Allison, J; Altenburg, D D; Andreotti, M; Angelini, C; Anulli, F; Arnaud, N; Asgeirsson, D J; Aston, D; Azzolini, V; Baak, M A; Back, J J; Baldini-Ferroli, R; Band, H R; Banerjee, Sw; Bard, D J; Barlow, N R; Barlow, R J; Barrett, M; Bartoldus, R; Batignani, G; Battaglia, M; Bauer, J M; Bechtle, P; Beck, T W; Behera, P K; Bellini, F; Benayoun, M; Benelli, G; Berger, N; Bernard, D; Berryhill, J W; Best, D S; Bettarini, S; Bettoni, D; Bevan, A J; Bhimji, W; Bhuyan, B; Bianchi, F; Biasini, M; Biesiada, J; Blanc, F; Blaylock, G; Blinov, V E; Bloom, P C; Blount, N L; Bomben, M; Bondioli, M; Bonneaud, G R; Bosisio, L; Boutigny, D; Bowerman, D A; Boyd, J T; Bozzi, C; Brandenburg, G; Brandt, T; Brau, J E; Briand, H; Brown, C M; Brown, D N; Bruinsma, M; Brunet, S; Bucci, F; Buchanan, C; Bugg, W; Bukin, A D; Bula, R; Burchat, P R; Burke, J P; Button-Shafer, J; Buzzo, A; Bóna, M; Cahn, R N; Calabrese, R; Calcaterra, A; Calderini, G; Campagnari, C; Carpinelli, M; Cartaro, C; Cavallo, N; Cavoto, G; Cenci, R; Chai, X; Chaisanguanthum, K S; Chao, M; Charles, E; Charles, M J; Chauveau, J; Chavez, C A; Chen, A; Chen, C; Chen, E; Chen, J C; Chen, S; Chen, X; Chen, X R; Cheng, B; Cheng, C H; Chia, Y M; Cibinetto, G; Clark, P J; Clarke, C K; Claus, R; Cochran, J; Coleman, J P; Contri, R; Convery, M R; Corwin, L A; Cossutti, F; Cottingham, W N; Couderc, F; Covarelli, R; Cowan, G; Cowan, R; Crawley, H B; Cremaldi, L; Cunha, A; Curry, S; Côté, D; D'Orazio, A; Dahmes, B; Dallapiccola, C; Danielson, N; Dasu, S; Datta, M; Dauncey, P D; David, P; Davier, M; Davis, C L; De Nardo, Gallieno; De Sangro, R; Del Amo-Sánchez, P; Del Buono, L; Del Re, D; Della Ricca, G; Denig, A G; Di Lodovico, F; Di Marco, E; Dingfelder, J C; Dittongo, S; Dong, L; Dorfan, J; Druzhinin, V P; Dubitzky, R S; Dubois-Felsmann, G P; Dujmic, D; Dunwoodie, W M; Dvoretskii, A; Ebert, M; Eckhart, E A; Eckmann, R; Edgar, C L; Edwards, A J; Egede, U; Eigen, G; Eisner, A M; Elmer, P; Emery, S; Ernst, J A; Eschenburg, V; Eschrich, I; Eyges, V; Fabozzi, F; Faccini, R; Fang, F; Feltresi, E; Ferrarotto, F; Ferroni, F; Field, R C; Finocchiaro, G; Flacco, C J; Flack, R L; Flächer, H U; Flood, K T; Ford, K E; Ford, W T; Forster, I J; Forti, F; Fortin, D; Foulkes, S D; Franek, B; Frey, R; Fritsch, M; Fry, J R; Fulsom, B G; Gabathuler, E; Gaidot, A; Gallo, F; Gamba, D; Gamet, R; Gan, K K; Ganzhur, S F; Gao, Y; Gary, J W; Gaspero, M; Gatto, C; Gaz, A; George, K A; Gill, M S; Giorgi, M A; Gladney, L; Glanzman, T; Godang, R; Golubev, V B; Gowdy, S J; Gradl, W; Graham, M T; Graugès-Pous, E; Grenier, P; Gritsan, A V; Grosdidier, G; Groysman, Y; Guo, Z J; Hadavand, H K; Haire, M; Halyo, V; Hamano, K; Hamel de Monchenault, G; Hamon, O; Harrison, P F; Harrison, T J; Hart, A J; Hartfiel, B L; Hast, C; Hauke, A; Hawkes, C M; Hearty, C; Held, T; Hertzbach, S S; Heusch, C A; Hill, E J; Hirschauer, J F; Hitlin, D G; Hollar, J J; Hong, T M; Honscheid, K; Hopkins, D A; Hrynóva, T; Hufnagel, D; Hulsbergen, W D; Hutchcroft, D E; Höcker, A; Igonkina, O; Innes, W R; Izen, J M; Jackson, P D; Jackson, P S; Jacobsen, R G; Jain, V; Jasper, H; Jawahery, A; Jessop, C P; Judd, D; Kadyk, J A; Kagan, H; Karyotakis, Yu; Kass, R; Kelsey, M H; Kerth, L T; Khan, A; Kim, H; Kim, P; Kirkby, D; Klose, V; Knecht, N S; Koch, H; Kolb, J A; Kolomensky, Yu G; Kovalskyi, D; Kowalewski, R V; Kozanecki, Witold; Kreisel, A; Krishnamurthy, M; Kroeger, R; Kroseberg, J; Kukartsev, G; Kutter, P E; Kyberd, P; La Vaissière, C de; Lacker, H M; Lae, C K; Lafferty, G D; Lanceri, L; Lange, D J; Lankford, A J; Latham, T E; Latour, E; Lau, Y P; Lazzaro, A; Le Diberder, F R; Lee, C L; Lees, J P; Legendre, M; Leith, D W G S; Lepeltier, V; Leruste, P; Lewandowski, B; Li Gioi, L; Li, S; Li, X; Lista, L; Liu, H; Lo Vetere, M; LoSecco, J M; Lockman, W S; Lombardo, V; Long, O; Lopes-Pegna, D; Lopez-March, N; Lou, X C; Lu, M; Luitz, S; Lund, P; Luppi, E; Lusiani, A; Lutz, A M; Lynch, G; Lynch, H L; Lü, C; Lüth, V; MacFarlane, D B; Macri, M M; Mader, W F; Majewski, S A; Malcles, J; Mallik, U; Mancinelli, G; Mandelkern, M A; Marchiori, G; Margoni, M; Marks, J; Marsiske, H; Martínez-Vidal, F; Mattison, T S; Mazur, M A; Mazzoni, M A; McKenna, J A; McMahon, T R; Mclachlin, S E; Meadows, B T; Mellado, B; Menges, W; Merkel, J; Messner, R; Meyer, N T; Meyer, W T; Mihályi, A; Mir, L M; Mishra, K; Mohanty, G B; Monge, M R; Monorchio, D; Moore, T B; Morandin, M; Morganti, M; Morganti, S; Morii, M; Muheim, F; Müller, D R; Nagel, M; Naisbit, M T; Narsky, I; Nash, J A; Nauenberg, U; Neal, H; Negrini, M; Neri, N; Nesom, G; Nicholson, H; Nikolich, M B; Nogowski, R; Nugent, I M; O'Grady, C P; Ocariz, J; Ofte, I; Olaiya, E O; Olivas, A; Olsen, J; Onuchin, A P; Orimoto, T J; Oyanguren, A; Ozcan, V E; Paar, H P; Pacetti, S; Palano, A; Palombo, F; Pan, B; Pan, Y; Panduro, W; Paoloni, E; Paolucci, P; Pappagallo, M; Park, W; Passaggio, S; Patel, P M; Patrignani, C; Patteri, P; Payne, D J; Pelizaeus, M; Perazzo, A; Perl, M; Peruzzi, I M; Peters, K; Petersen, B A; Petrella, A; Petzold, A; Piatenko, T; Piccolo, D; Piccolo, M; Piemontese, L; Pierini, M; Piredda, G; Playfer, S; Poireau, V; Polci, F; Pompili, A; Porter, F C; Posocco, M; Potter, C T; Prell, S; Prencipe, E; Prepost, R; Pripstein, M; Pruvot, S; Pulliam, T; Purohit, M V; Qi, N D; Rahatlou, S; Rahimi, A M; Rahmat, R; Rama, M; Ratcliff, B N; Raven, G; Regensburger, J J; Ricciardi, S; Richman, J D; Ritchie, J L; Rizzo, G; Roberts, D A; Robertson, A I; Robertson, S H; Robutti, E; Rodier, S; Roe, N A; Ronan, M T; Roney, J M; Rong, G; Roodman, A; Roos, L; Rosenberg, E I; Rotondo, M; Roudeau, P; Rubin, A E; Ruddick, W O; Röthel, W; Sacco, R; Saeed, M A; Safai-Tehrani, F; Saleem, M; Salnikov, A A; Salvatore, F; Sanders, D A; Santroni, A; Saremi, S; Satpathy, A; Schalk, T; Schenk, S; Schilling, C J; Schindler, R H; Schofield, K C; Schott, G; Schröder, T; Schröder, H; Schubert, J; Schubert, K R; Schumm, B A; Schune, M H; Schwiening, J; Schwierz, R; Schwitters, R F; Sciacca, C; Sciolla, G; Seiden, A; Sekula, S J; Serednyakov, S I; Serrano, J; Sharma, V; Shen, B C; Sherwood, D J; Simard, M; Simi, G; Simonetto, F; Sinev, N B; Skovpen, Yu I; Smith, A J S; Smith, J G; Snoek, H L; Snyder, A; Sobie, R J; Soffer, A; Sokoloff, M D; Solodov, E P; Spaan, B; Spanier, S M; Spitznagel, M; Spradlin, P; Steinke, M; Stelzer, J; Stocchi, A; Stoker, D P; Stroili, R; Strom, D; Strube, J; Stugu, B; Stängle, H; Su, D; Sullivan, M K; Summers, D J; Sundermann, J E; Suzuki, K; Swain, S K; Taras, P; Taylor, F; Telnov, A V; Teodorescu, L; Ter-Antonian, R; Therin, G; Thiebaux, C; Thompson, J M; Tisserand, V; Todyshev, Y K; Toki, W H; Torrence, E; Tosi, S; Touramanis, C; Ulmer, K A; Uwer, U; Van Bakel, N; Vasseur, G; Vavra, J; Vazquez, A; Verderi, M; Viaud, F B; Vitale, L; Voci, C; Voena, C; Volk, A; Wagner, A P; Wagner, S R; Wagoner, D E; Waldi, R; Walker, D; Walsh, J J; Wang, K; Wang, P; Wang, W F; Wappler, F R; Watson, A T; Weaver, M; Weinstein, A J R; Wenzel, W A; Wilden, L; Williams, D C; Williams, J C; Wilson, F F; Wilson, J R; Wilson, M G; Wilson, R J; Winklmeier, F; Wisniewski, W J; Wittgen, M; Wong, Q K; Wormser, G; Wren, A C; Wright, D H; Wright, D M; Wu, J; Wu, S L; Wulsin, H W; Xie, Y; Yamamoto, R K; Yarritu, A K; Ye, S; Yi, J I; Yi, K; Young, C C; Yu, Z; Yéche, C; Zain, S B; Zallo, A; Zeng, Q; Zghiche, A; Zhang, J; Zhang, L; Zhao, H W; Zhu, Y S; Ziegler, V; Zito, M; Çuhadar-Dönszelmann, T; al, et
2007-01-01
We perform an amplitude analysis of the decays B0->phi K^*_2(1430)0, phi K^*(892)0, and phi(K pi)^0_S-wave with a sample of about 384 million BBbar pairs recorded with the BABAR detector. The fractions of longitudinal polarization f_L of the vector-tensor and vector-vector decay modes are measured to be 0.853 +0.061-0.069 +-0.036 and 0.506 +-0.040 +-0.015, respectively. Overall, twelve parameters are measured for the vector-vector decay and seven parameters for the vector-tensor decay, including the branching fractions and parameters sensitive to CP-violation.
Ranking Support Vector Machine with Kernel Approximation.
Chen, Kai; Li, Rongchun; Dou, Yong; Liang, Zhengfa; Lv, Qi
2017-01-01
Learning to rank algorithm has become important in recent years due to its successful application in information retrieval, recommender system, and computational biology, and so forth. Ranking support vector machine (RankSVM) is one of the state-of-art ranking models and has been favorably used. Nonlinear RankSVM (RankSVM with nonlinear kernels) can give higher accuracy than linear RankSVM (RankSVM with a linear kernel) for complex nonlinear ranking problem. However, the learning methods for nonlinear RankSVM are still time-consuming because of the calculation of kernel matrix. In this paper, we propose a fast ranking algorithm based on kernel approximation to avoid computing the kernel matrix. We explore two types of kernel approximation methods, namely, the Nyström method and random Fourier features. Primal truncated Newton method is used to optimize the pairwise L2-loss (squared Hinge-loss) objective function of the ranking model after the nonlinear kernel approximation. Experimental results demonstrate that our proposed method gets a much faster training speed than kernel RankSVM and achieves comparable or better performance over state-of-the-art ranking algorithms.
Computerized Interactive Gaming via Supporting Vector Machines
Directory of Open Access Journals (Sweden)
Y. Jiang
2008-01-01
Full Text Available Computerized interactive gaming requires automatic processing of large volume of random data produced by players on spot, such as shooting, football kicking, and boxing. This paper describes a supporting vector machine-based artificial intelligence algorithm as one of the possible solutions to the problem of random data processing and the provision of interactive indication for further actions. In comparison with existing techniques, such as rule-based and neural networks, and so forth, our SVM-based interactive gaming algorithm has the features of (i high-speed processing, providing instant response to the players, (ii winner selection and control by one parameter, which can be predesigned and adjusted according to the needs of interaction and game design or specific level of difficulties, and (iii detection of interaction points is adaptive to the input changes, and no labelled training data is required. Experiments on numerical simulation support that the proposed algorithm is robust to random noise, accurate in picking up winning data, and convenient for all interactive gaming designs.
Vorst, H.A. van der; Ye, Q.
1999-01-01
In this paper, a strategy is proposed for alternative computations of the residual vectors in Krylov subspace methods, which improves the agreement of the computed residuals and the true residuals to the level of O(u)kAkkxk. Building on earlier ideas on residual replacement and on insights in
Hierarchical Vector Quantization with Application to Speech Waveform Coding.
Shoham, Yair
Digital voice communication has long been of great engineering concern due to the vital role of voice communication in human society. Recently, a new and theoretically powerful coding technique, Vector Quantization (VQ), has been used in enhancing existing speech coders and in developing new coding algorithms. VQ operates on a vector of source samples as an elementary unit. The basic coding operation is that of pattern matching, where a finite set of codevectors (the codebook) is searched for the best approximation to the input source vector. However, the applicability of VQ to speech coding is limited by the computational complexity, associated with the codebook search, which grows exponentially with the source dimension and the coding rate. A fundamental property of speech is that it is composed of long highly correlated segments, due to its quasi-periodicity and short -term stationarity. These features of speech cannot be directly exploited by vector quantization because of the complexity problem. Thus, to be able to efficiently exploit the redundancy in speech by a VQ-based coding scheme, a special technique is needed, capable of handling very high dimensional vectors. Such a technique, called Hierarchical Vector Quantization (HVQ) is developed in this work. HVQ is based on representing the source by a multi -level tree-structure of low dimensional vectors. The bottom level of the tree contains the data vectors which are subvectors of the main high dimensional input. Vectors at higher levels contain suitably defined signal parameters which are extracted from the lower levels. These parameters, called features, are used as side-information in coding the data vectors. This technique partially exploits the correlation and structure of the main input vector while actually performing low dimensional, low complexity vector quantization. In this work HVQ, is used in quantizing the coefficients of a specially structured transform coder. This coder employs variable
Vector Radix 2 × 2 Sliding Fast Fourier Transform
Directory of Open Access Journals (Sweden)
Keun-Yung Byun
2016-01-01
Full Text Available The two-dimensional (2D discrete Fourier transform (DFT in the sliding window scenario has been successfully used for numerous applications requiring consecutive spectrum analysis of input signals. However, the results of conventional sliding DFT algorithms are potentially unstable because of the accumulated numerical errors caused by recursive strategy. In this letter, a stable 2D sliding fast Fourier transform (FFT algorithm based on the vector radix (VR 2 × 2 FFT is presented. In the VR-2 × 2 FFT algorithm, each 2D DFT bin is hierarchically decomposed into four sub-DFT bins until the size of the sub-DFT bins is reduced to 2 × 2; the output DFT bins are calculated using the linear combination of the sub-DFT bins. Because the sub-DFT bins for the overlapped input signals between the previous and current window are the same, the proposed algorithm reduces the computational complexity of the VR-2 × 2 FFT algorithm by reusing previously calculated sub-DFT bins in the sliding window scenario. Moreover, because the resultant DFT bins are identical to those of the VR-2 × 2 FFT algorithm, numerical errors do not arise; therefore, unconditional stability is guaranteed. Theoretical analysis shows that the proposed algorithm has the lowest computational requirements among the existing stable sliding DFT algorithms.
Estrogen and Progestin (Hormone Replacement Therapy)
... Estrogen and progestin are two female sex hormones. Hormone replacement therapy works by replacing estrogen hormone that is no ... menopausal women. Progestin is added to estrogen in hormone replacement therapy to reduce the risk of uterine cancer in ...
Improved Runtime Analysis of the Simple Genetic Algorithm
DEFF Research Database (Denmark)
Oliveto, Pietro S.; Witt, Carsten
2013-01-01
A runtime analysis of the Simple Genetic Algorithm (SGA) for the OneMax problem has recently been presented proving that the algorithm requires exponential time with overwhelming probability. This paper presents an improved analysis which overcomes some limitations of our previous one. Firstly...... improvement towards the reusability of the techniques in future systematic analyses of GAs. Finally, we consider the more natural SGA using selection with replacement rather than without replacement although the results hold for both algorithmic versions. Experiments are presented to explore the limits...
Improved time complexity analysis of the Simple Genetic Algorithm
DEFF Research Database (Denmark)
Oliveto, Pietro S.; Witt, Carsten
2015-01-01
A runtime analysis of the Simple Genetic Algorithm (SGA) for the OneMax problem has recently been presented proving that the algorithm with population size μ≤n1/8−ε requires exponential time with overwhelming probability. This paper presents an improved analysis which overcomes some limitations...... this is a major improvement towards the reusability of the techniques in future systematic analyses of GAs. Finally, we consider the more natural SGA using selection with replacement rather than without replacement although the results hold for both algorithmic versions. Experiments are presented to explore...
Eisen, Lars; Beaty, Barry J; Morrison, Amy C; Scott, Thomas W
2009-11-01
Despite tremendous efforts by public health organizations in dengue-endemic countries, it has proven difficult to achieve effective and sustainable control of the primary dengue virus vector Aedes aegypti (L.) and to effectively disrupt dengue outbreaks. This problem has multiple root causes, including uncontrolled urbanization, increased global spread of dengue viruses, and vector and dengue control programs not being provided adequate resources. In this forum article, we give an overview of the basic elements of a vector and dengue control program and describe a continuous improvement cyclical model to systematically and incrementally improve control program performance by regular efforts to identify ineffective methods and inferior technology, and then replacing them with better performing alternatives. The first step includes assessments of the overall resource allocation among vector/dengue control program activities, the efficacy of currently used vector control methods, and the appropriateness of technology used to support the program. We expect this will reveal that 1) some currently used vector control methods are not effective, 2) resource allocations often are skewed toward reactive vector control measures, and 3) proactive approaches commonly are underfunded and therefore poorly executed. Next steps are to conceptualize desired changes to vector control methods or technologies used and then to operationally determine in pilot studies whether these changes are likely to improve control program performance. This should be followed by a shift in resource allocation to replace ineffective methods and inferior technology with more effective and operationally tested alternatives. The cyclical and self-improving nature of the continuous improvement model will produce locally appropriate management strategies that continually are adapted to counter changes in vector population or dengue virus transmission dynamics. We discuss promising proactive vector control
Mechanical Valve Replacement: Early Results
Directory of Open Access Journals (Sweden)
Habib Cakir
2012-02-01
Full Text Available Aim: Valve diseases in developing countries like Turkey which often occur as a complication of rheumatic fever are a serious disease. Surgical treatment of valve diseases should be done before irreversible damage to the myocardium occurred. In this study, we aimed to present the early results of mechanical valve replacement operations. Method: A hundred patients with mechanical valve replacement surgery were retrospectively evaluated in Seyhan Application Center attached to our clinic between July 2007 and August 2011. Results: Fifty patients were male and 50 were women. The mean age of patients was 47.88 (18-78. Isolated aortic valve replacement (AVR was performed to 23 patients, isolated mitral valve replacement (MVR was 32, double valve replacement (AVR + MVR was 12, MVR + aortic valve valvuloplasty was 1, AVR + mitral kommissurotomi was 1, AVR + coronary artery bypass graft surgery (CABG was 17, MVR + CABG was 8, MVR + atrial septal defect closure was 2 and Bentall procedure.was 4 patients. In addition, ablation procedure was performed to 5 patients intraoperatively because of preoperative atrial fibrillation. Two patients (2 % died in early postoperative period. Conclusion: Mechanical prosthetic valves are used for surgical treatment of valve disease with low mortality and morbidity in a large group of patients like women that not to think to get pregnant, non advanced age group and patients have less risky for anticoagulation drug in our clinic. [Cukurova Med J 2012; 37(1.000: 49-54
Transcriptional Silencing of Retroviral Vectors
DEFF Research Database (Denmark)
Lund, Anders Henrik; Duch, M.; Pedersen, F.S.
1996-01-01
Although retroviral vector systems have been found to efficiently transduce a variety of cell types in vitro, the use of vectors based on murine leukemia virus in preclinical models of somatic gene therapy has led to the identification of transcriptional silencing in vivo as an important problem...
DEFF Research Database (Denmark)
Davis, Christopher James; Kedlaya, Kiran
2014-01-01
We study the kernel and cokernel of the Frobenius map on the p-typical Witt vectors of a commutative ring, not necessarily of characteristic p. We give many equivalent conditions to surjectivity of the Frobenius map on both finite and infinite length Witt vectors. In particular, surjectivity on f...
Vectors on the Basketball Court
Bergman, Daniel
2010-01-01
An Idea Bank published in the April/May 2009 issue of "The Science Teacher" describes an experiential physics lesson on vectors and vector addition (Brown 2009). Like its football predecessor, the basketball-based investigation presented in this Idea Bank addresses National Science Education Standards Content B, Physical Science, 9-12 (NRC 1996)…
CSIR Research Space (South Africa)
Helbig, M
2012-06-01
Full Text Available constraint violations on the performance of the Dynamic Vector Evaluated Particle Swarm Optimisation (DVEPSO) algorithm when solving DMOOPs. Furthermore, the performance of DVEPSO is compared against the performance of three other state-of-the-art dynamic...
Solution of partial differential equations on vector and parallel computers
Ortega, J. M.; Voigt, R. G.
1985-01-01
The present status of numerical methods for partial differential equations on vector and parallel computers was reviewed. The relevant aspects of these computers are discussed and a brief review of their development is included, with particular attention paid to those characteristics that influence algorithm selection. Both direct and iterative methods are given for elliptic equations as well as explicit and implicit methods for initial boundary value problems. The intent is to point out attractive methods as well as areas where this class of computer architecture cannot be fully utilized because of either hardware restrictions or the lack of adequate algorithms. Application areas utilizing these computers are briefly discussed.
A New Conic Approach to Semisupervised Support Vector Machines
Directory of Open Access Journals (Sweden)
Ye Tian
2016-01-01
Full Text Available We propose a completely positive programming reformulation of the 2-norm soft margin S3VM model. Then, we construct a sequence of computable cones of nonnegative quadratic forms over a union of second-order cones to approximate the underlying completely positive cone. An ϵ-optimal solution can be found in finite iterations using semidefinite programming techniques by our method. Moreover, in order to obtain a good lower bound efficiently, an adaptive scheme is adopted in our approximation algorithm. The numerical results show that the proposed algorithm can achieve more accurate classifications than other well-known conic relaxations of semisupervised support vector machine models in the literature.
A Simpler Approach to Coefficient Regularized Support Vector Machines Regression
Directory of Open Access Journals (Sweden)
Hongzhi Tong
2014-01-01
Full Text Available We consider a kind of support vector machines regression (SVMR algorithms associated with lq (1≤q<∞ coefficient-based regularization and data-dependent hypothesis space. Compared with former literature, we provide here a simpler convergence analysis for those algorithms. The novelty of our analysis lies in the estimation of the hypothesis error, which is implemented by setting a stepping stone between the coefficient regularized SVMR and the classical SVMR. An explicit learning rate is then derived under very mild conditions.
Incremental Learning Algorithm of Least Square Twin KSVC
Directory of Open Access Journals (Sweden)
Wang Yaru
2016-01-01
Full Text Available In view of the batch implementations of standard support vector machine must be retrained from scratch every time when the training set is incremental modified, an incremental learning algorithm based on least squares twin multi-class classification support vector machine (ILST-KSVC is proposed by solving two inverse matrix. The method will be applied on online environment to update initial data, which avoided cumbersome double counting. ILST-KSVC inherited the advantages of the basic algorithm and has some merits of Least square twin support vector machine for excellent performance on training speed and support vector classification regression for K-class’s well classification accuracy. The result will be confirmed no matter in low dimension or in high dimension in UCI datasets.
Fault Detection of Bearing Systems through EEMD and Optimization Algorithm.
Lee, Dong-Han; Ahn, Jong-Hyo; Koh, Bong-Hwan
2017-10-28
This study proposes a fault detection and diagnosis method for bearing systems using ensemble empirical mode decomposition (EEMD) based feature extraction, in conjunction with particle swarm optimization (PSO), principal component analysis (PCA), and Isomap. First, a mathematical model is assumed to generate vibration signals from damaged bearing components, such as the inner-race, outer-race, and rolling elements. The process of decomposing vibration signals into intrinsic mode functions (IMFs) and extracting statistical features is introduced to develop a damage-sensitive parameter vector. Finally, PCA and Isomap algorithm are used to classify and visualize this parameter vector, to separate damage characteristics from healthy bearing components. Moreover, the PSO-based optimization algorithm improves the classification performance by selecting proper weightings for the parameter vector, to maximize the visualization effect of separating and grouping of parameter vectors in three-dimensional space.
Fault Detection of Bearing Systems through EEMD and Optimization Algorithm
Directory of Open Access Journals (Sweden)
Dong-Han Lee
2017-10-01
Full Text Available This study proposes a fault detection and diagnosis method for bearing systems using ensemble empirical mode decomposition (EEMD based feature extraction, in conjunction with particle swarm optimization (PSO, principal component analysis (PCA, and Isomap. First, a mathematical model is assumed to generate vibration signals from damaged bearing components, such as the inner-race, outer-race, and rolling elements. The process of decomposing vibration signals into intrinsic mode functions (IMFs and extracting statistical features is introduced to develop a damage-sensitive parameter vector. Finally, PCA and Isomap algorithm are used to classify and visualize this parameter vector, to separate damage characteristics from healthy bearing components. Moreover, the PSO-based optimization algorithm improves the classification performance by selecting proper weightings for the parameter vector, to maximize the visualization effect of separating and grouping of parameter vectors in three-dimensional space.
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.
Molecular replacement: tricks and treats
Energy Technology Data Exchange (ETDEWEB)
Abergel, Chantal, E-mail: chantal.abergel@igs.cnrs-mrs.fr [IGS UMR 7256, CNRS, Aix-Marseille Université, IMM, FR3479, 163 Avenue de Luminy – case 934, 13288 Marseille CEDEX 09 (France)
2013-11-01
To be successful, molecular replacement relies on the quality of the model and of the crystallographic data. Some tricks that could be applied to the models or to the crystal to increase the success rate of MR are discussed here. Molecular replacement is the method of choice for X-ray crystallographic structure determination provided that suitable structural homologues are available in the PDB. Presently, there are ∼80 000 structures in the PDB (8074 were deposited in the year 2012 alone), of which ∼70% have been solved by molecular replacement. For successful molecular replacement the model must cover at least 50% of the total structure and the C{sub α} r.m.s.d. between the core model and the structure to be solved must be less than 2 Å. Here, an approach originally implemented in the CaspR server (http://www.igs.cnrs-mrs.fr/Caspr2/index.cgi) based on homology modelling to search for a molecular-replacement solution is discussed. How the use of as much information as possible from different sources can improve the model(s) is briefly described. The combination of structural information with distantly related sequences is crucial to optimize the multiple alignment that will define the boundaries of the core domains. PDB clusters (sequences with ≥30% identical residues) can also provide information on the eventual changes in conformation and will help to explore the relative orientations assumed by protein subdomains. Normal-mode analysis can also help in generating series of conformational models in the search for a molecular-replacement solution. Of course, finding a correct solution is only the first step and the accuracy of the identified solution is as important as the data quality to proceed through refinement. Here, some possible reasons for failure are discussed and solutions are proposed using a set of successful examples.
Renal replacement therapy in ICU
Directory of Open Access Journals (Sweden)
C Deepa
2012-01-01
Full Text Available Diagnosing and managing critically ill patients with renal dysfunction is a part of the daily routine of an intensivist. Acute kidney insufficiency substantially contributes to the morbidity and mortality of critically ill patients. Renal replacement therapy (RRT not only does play a significant role in the treatment of patients with renal failure, acute as well as chronic, but also has spread its domains to the treatment of many other disease conditions such as myaesthenia gravis, septic shock and acute on chronic liver failure. This article briefly outlines the role of renal replacement therapy in ICU.
An Efficient Audio Classification Approach Based on Support Vector Machines
Lhoucine Bahatti; Omar Bouattane; My Elhoussine Echhibat; Mohamed Hicham Zaggaf
2016-01-01
In order to achieve an audio classification aimed to identify the composer, the use of adequate and relevant features is important to improve performance especially when the classification algorithm is based on support vector machines. As opposed to conventional approaches that often use timbral features based on a time-frequency representation of the musical signal using constant window, this paper deals with a new audio classification method which improves the features extraction according ...
Emerging vector borne diseases – incidence through vectors
Directory of Open Access Journals (Sweden)
Sara eSavic
2014-12-01
Full Text Available Vector borne diseases use to be a major public health concern only in tropical and subtropical areas, but today they are an emerging threat for the continental and developed countries also. Nowdays, in intercontinetal countries, there is a struggle with emerging diseases which have found their way to appear through vectors. Vector borne zoonotic diseases occur when vectors, animal hosts, climate conditions, pathogens and susceptible human population exist at the same time, at the same place. Global climate change is predicted to lead to an increase in vector borne infectious diseases and disease outbreaks. It could affect the range and popultion of pathogens, host and vectors, transmission season, etc. Reliable surveilance for diseases that are most likely to emerge is required. Canine vector borne diseases represent a complex group of diseases including anaplasmosis, babesiosis, bartonellosis, borreliosis, dirofilariosis, erlichiosis, leishmaniosis. Some of these diseases cause serious clinical symptoms in dogs and some of them have a zoonotic potential with an effect to public health. It is expected from veterinarians in coordination with medical doctors to play a fudamental role at primeraly prevention and then treatment of vector borne diseases in dogs. The One Health concept has to be integrated into the struggle against emerging diseases.During a four year period, from 2009-2013, a total number of 551 dog samples were analysed for vector borne diseases (borreliosis, babesiosis, erlichiosis, anaplasmosis, dirofilariosis and leishmaniasis in routine laboratory work. The analysis were done by serological tests – ELISA for borreliosis, dirofilariosis and leishmaniasis, modified Knott test for dirofilariosis and blood smear for babesiosis, erlichiosis and anaplasmosis. This number of samples represented 75% of total number of samples that were sent for analysis for different diseases in dogs. Annually, on avarege more then half of the samples
Word Vectorization Using Relations among Words for Neural Network
Hotta, Hajime; Kittaka, Masanobu; Hagiwara, Masafumi
In this paper, we propose a new vectorization method for a new generation of computational intelligence including neural networks and natural language processing. In recent years, various techniques of word vectorization have been proposed, many of which rely on the preparation of dictionaries. However, these techniques don't consider the symbol grounding problem for unknown types of data, which is one of the most fundamental issues on artificial intelligence. In order to avoid the symbol-grounding problem, pattern processing based methods, such as neural networks, are often used in various studies on self-directive systems and algorithms, and the merit of neural network is not exception in the natural language processing. The proposed method is a converter from one word input to one real-valued vector, whose algorithm is inspired by neural network architecture. The merits of the method are as follows: (1) the method requires no specific knowledge of linguistics e.g. word classes or grammatical one; (2) the method is a sequence learning technique and it can learn additional knowledge. The experiment showed the efficiency of word vectorization in terms of similarity measurement.
DEFF Research Database (Denmark)
Padmanaban, Sanjeevi Kumar; Grandi, Gabriele; Ojo, Joseph Olorunfemi
2016-01-01
In this paper, a six-phase (asymmetrical) machine is investigated, 300 phase displacement is set between two three-phase stator windings keeping deliberately in open-end configuration. Power supply consists of four classical three-phase voltage inverters (VSIs), each one connected to the open......-winding terminals. An original synchronous field oriented control (FOC) algorithm with three variables as degree of freedom is proposed, allowing power sharing among the four VSIs in symmetric/asymmetric conditions. A standard three-level space vector pulse width modulation (SVPWM) by nearest three vector (NTV......) approach was adopted for each couple of VSIs to operate as multilevel output voltage generators. The proposed power sharing algorithm is verified for the ac drive system by observing the dynamic behaviours in different set conditions by complete simulation modelling in software (Matlab...
Kaltwasser, Marcus; Wiegert, Thomas; Schumann, Wolfgang
2002-01-01
Here we describe the construction and application of six new tagging vectors allowing the fusion of two different types of tagging sequences, epitope and localization tags, to any Bacillus subtilis protein. These vectors are based on the backbone of pMUTIN2 and replace the lacZ gene with tagging sequences. Fusion of the tagging sequences occurs by PCR amplification of the 3′ terminal part of the gene of interest (about 300 bp), insertion into the tagging vector in such a way that a fusion pro...
Korshever, N G; Sidelnikov, S A
2015-01-01
The algorithm of constructing mode of multi-vector evaluation of intersectoral interaction concerning issues of population health care is substantiated and implemented. The items ofevaluation included identification of informative vectors and criteria including their gradation, coefficients of significance and model versions.
MPATH: A Loop-free Multipath Routing Algorithm
2000-10-01
algorithms in that it uses the invariants, introduced in [19], to ensure multiple loop- free paths of unequal cost. Another family of routing algorithms...infinity prob- lem of the distance vector algorithms. OSPF [12] and algorithms in [16], [13] are some that belong to this family , which exchange com- plete...NTU (Fig. 2), which first updates the neigh- bor distance tables and then updates T ik with links (m; n; d), where d = Dink D i mk and m = p i nk
Separation analysis, a tool for analyzing multigrid algorithms
Costiner, Sorin; Taasan, Shlomo
1995-01-01
The separation of vectors by multigrid (MG) algorithms is applied to the study of convergence and to the prediction of the performance of MG algorithms. The separation operator for a two level cycle algorithm is derived. It is used to analyze the efficiency of the cycle when mixing of eigenvectors occurs. In particular cases the separation analysis reduces to Fourier type analysis. The separation operator of a two level cycle for a Schridubger eigenvalue problem, is derived and analyzed in a Fourier basis. Separation analysis gives information on how to choose performance relaxations and inter-level transfers. Separation analysis is a tool for analyzing and designing algorithms, and for optimizing their performance.
When do support vector machines work fast?
Energy Technology Data Exchange (ETDEWEB)
Steinwart, I. (Ingo); Scovel, James C.
2004-01-01
The authors establish learning rates to the Bayes risk for support vector machines (SVM's) with hinge loss. Since a theorem of Devroyte states that no learning algorithm can learn with a uniform rate to the Bayes risk for all probability distributions they have to restrict the class of considered distributions: in order to obtain fast rates they assume a noise condition recently proposed by Tsybakov and an approximation condition in terms of the distribution and the reproducing kernel Hilbert space used by the SVM. for Gaussian RBF kernels with varying widths they propose a geometric noise assumption on the distribution which ensures the approximation condition. This geometric assumption is not in terms of smoothness but describes the concentration of the marginal distribution near the decision boundary. In particular they are able to describe nontrivial classes of distributions for which SVM's using a Gaussian kernel can learn with almost linear rate.
Artificial Neural Network for Displacement Vectors Determination
Directory of Open Access Journals (Sweden)
P. Bohmann
1997-09-01
Full Text Available An artificial neural network (NN for displacement vectors (DV determination is presented in this paper. DV are computed in areas which are essential for image analysis and computer vision, in areas where are edges, lines, corners etc. These special features are found by edges operators with the following filtration. The filtration is performed by a threshold function. The next step is DV computation by 2D Hamming artificial neural network. A method of DV computation is based on the full search block matching algorithms. The pre-processing (edges finding is the reason why the correlation function is very simple, the process of DV determination needs less computation and the structure of the NN is simpler.
Algorithm for Autonomous Landing
Kuwata, Yoshiaki
2011-01-01
Because of their small size, high maneuverability, and easy deployment, micro aerial vehicles (MAVs) are used for a wide variety of both civilian and military missions. One of their current drawbacks is the vast array of sensors (such as GPS, altimeter, radar, and the like) required to make a landing. Due to the MAV s small payload size, this is a major concern. Replacing the imaging sensors with a single monocular camera is sufficient to land a MAV. By applying optical flow algorithms to images obtained from the camera, time-to-collision can be measured. This is a measurement of position and velocity (but not of absolute distance), and can avoid obstacles as well as facilitate a landing on a flat surface given a set of initial conditions. The key to this approach is to calculate time-to-collision based on some image on the ground. By holding the angular velocity constant, horizontal speed decreases linearly with the height, resulting in a smooth landing. Mathematical proofs show that even with actuator saturation or modeling/ measurement uncertainties, MAVs can land safely. Landings of this nature may have a higher velocity than is desirable, but this can be compensated for by a cushioning or dampening system, or by using a system of legs to grab onto a surface. Such a monocular camera system can increase vehicle payload size (or correspondingly reduce vehicle size), increase speed of descent, and guarantee a safe landing by directly correlating speed to height from the ground.
Online Sequential Projection Vector Machine with Adaptive Data Mean Update
Directory of Open Access Journals (Sweden)
Lin Chen
2016-01-01
Full Text Available We propose a simple online learning algorithm especial for high-dimensional data. The algorithm is referred to as online sequential projection vector machine (OSPVM which derives from projection vector machine and can learn from data in one-by-one or chunk-by-chunk mode. In OSPVM, data centering, dimension reduction, and neural network training are integrated seamlessly. In particular, the model parameters including (1 the projection vectors for dimension reduction, (2 the input weights, biases, and output weights, and (3 the number of hidden nodes can be updated simultaneously. Moreover, only one parameter, the number of hidden nodes, needs to be determined manually, and this makes it easy for use in real applications. Performance comparison was made on various high-dimensional classification problems for OSPVM against other fast online algorithms including budgeted stochastic gradient descent (BSGD approach, adaptive multihyperplane machine (AMM, primal estimated subgradient solver (Pegasos, online sequential extreme learning machine (OSELM, and SVD + OSELM (feature selection based on SVD is performed before OSELM. The results obtained demonstrated the superior generalization performance and efficiency of the OSPVM.
Online Sequential Projection Vector Machine with Adaptive Data Mean Update.
Chen, Lin; Jia, Ji-Ting; Zhang, Qiong; Deng, Wan-Yu; Wei, Wei
2016-01-01
We propose a simple online learning algorithm especial for high-dimensional data. The algorithm is referred to as online sequential projection vector machine (OSPVM) which derives from projection vector machine and can learn from data in one-by-one or chunk-by-chunk mode. In OSPVM, data centering, dimension reduction, and neural network training are integrated seamlessly. In particular, the model parameters including (1) the projection vectors for dimension reduction, (2) the input weights, biases, and output weights, and (3) the number of hidden nodes can be updated simultaneously. Moreover, only one parameter, the number of hidden nodes, needs to be determined manually, and this makes it easy for use in real applications. Performance comparison was made on various high-dimensional classification problems for OSPVM against other fast online algorithms including budgeted stochastic gradient descent (BSGD) approach, adaptive multihyperplane machine (AMM), primal estimated subgradient solver (Pegasos), online sequential extreme learning machine (OSELM), and SVD + OSELM (feature selection based on SVD is performed before OSELM). The results obtained demonstrated the superior generalization performance and efficiency of the OSPVM.
Model Checking Vector Addition Systems with one zero-test
Bonet, Rémi; Leroux, Jérôme; Zeitoun, Marc
2012-01-01
We design a variation of the Karp-Miller algorithm to compute, in a forward manner, a finite representation of the cover (i.e., the downward closure of the reachability set) of a vector addition system with one zero-test. This algorithm yields decision procedures for several problems for these systems, open until now, such as place-boundedness or LTL model-checking. The proof techniques to handle the zero-test are based on two new notions of cover: the refined and the filtered cover. The refined cover is a hybrid between the reachability set and the classical cover. It inherits properties of the reachability set: equality of two refined covers is undecidable, even for usual Vector Addition Systems (with no zero-test), but the refined cover of a Vector Addition System is a recursive set. The second notion of cover, called the filtered cover, is the central tool of our algorithms. It inherits properties of the classical cover, and in particular, one can effectively compute a finite representation of this set, e...
DEFF Research Database (Denmark)
issues of theoretical algorithmics and applications in various fields including graph algorithms, computational geometry, scheduling, approximation algorithms, network algorithms, data storage and manipulation, combinatorics, sorting, searching, online algorithms, optimization, etc.......This book constitutes the refereed proceedings of the 10th Scandinavian Workshop on Algorithm Theory, SWAT 2006, held in Riga, Latvia, in July 2006. The 36 revised full papers presented together with 3 invited papers were carefully reviewed and selected from 154 submissions. The papers address all...
Renal replacement therapy in Europe
DEFF Research Database (Denmark)
Noordzij, Marlies; Kramer, Anneke; Abad Diez, José M
2014-01-01
BACKGROUND: This article provides a summary of the 2011 ERA-EDTA Registry Annual Report (available at www.era-edta-reg.org). METHODS: Data on renal replacement therapy (RRT) for end-stage renal disease (ESRD) from national and regional renal registries in 30 countries in Europe and bordering the ...
Stable piecewise polynomial vector fields
Directory of Open Access Journals (Sweden)
Claudio Pessoa
2012-09-01
Full Text Available Let $N={y>0}$ and $S={y<0}$ be the semi-planes of $mathbb{R}^2$ having as common boundary the line $D={y=0}$. Let $X$ and $Y$ be polynomial vector fields defined in $N$ and $S$, respectively, leading to a discontinuous piecewise polynomial vector field $Z=(X,Y$. This work pursues the stability and the transition analysis of solutions of $Z$ between $N$ and $S$, started by Filippov (1988 and Kozlova (1984 and reformulated by Sotomayor-Teixeira (1995 in terms of the regularization method. This method consists in analyzing a one parameter family of continuous vector fields $Z_{epsilon}$, defined by averaging $X$ and $Y$. This family approaches $Z$ when the parameter goes to zero. The results of Sotomayor-Teixeira and Sotomayor-Machado (2002 providing conditions on $(X,Y$ for the regularized vector fields to be structurally stable on planar compact connected regions are extended to discontinuous piecewise polynomial vector fields on $mathbb{R}^2$. Pertinent genericity results for vector fields satisfying the above stability conditions are also extended to the present case. A procedure for the study of discontinuous piecewise vector fields at infinity through a compactification is proposed here.
Chikungunya Virus–Vector Interactions
Directory of Open Access Journals (Sweden)
Lark L. Coffey
2014-11-01
Full Text Available Chikungunya virus (CHIKV is a mosquito-borne alphavirus that causes chikungunya fever, a severe, debilitating disease that often produces chronic arthralgia. Since 2004, CHIKV has emerged in Africa, Indian Ocean islands, Asia, Europe, and the Americas, causing millions of human infections. Central to understanding CHIKV emergence is knowledge of the natural ecology of transmission and vector infection dynamics. This review presents current understanding of CHIKV infection dynamics in mosquito vectors and its relationship to human disease emergence. The following topics are reviewed: CHIKV infection and vector life history traits including transmission cycles, genetic origins, distribution, emergence and spread, dispersal, vector competence, vector immunity and microbial interactions, and co-infection by CHIKV and other arboviruses. The genetics of vector susceptibility and host range changes, population heterogeneity and selection for the fittest viral genomes, dual host cycling and its impact on CHIKV adaptation, viral bottlenecks and intrahost diversity, and adaptive constraints on CHIKV evolution are also discussed. The potential for CHIKV re-emergence and expansion into new areas and prospects for prevention via vector control are also briefly reviewed.
Chikungunya Virus–Vector Interactions
Coffey, Lark L.; Failloux, Anna-Bella; Weaver, Scott C.
2014-01-01
Chikungunya virus (CHIKV) is a mosquito-borne alphavirus that causes chikungunya fever, a severe, debilitating disease that often produces chronic arthralgia. Since 2004, CHIKV has emerged in Africa, Indian Ocean islands, Asia, Europe, and the Americas, causing millions of human infections. Central to understanding CHIKV emergence is knowledge of the natural ecology of transmission and vector infection dynamics. This review presents current understanding of CHIKV infection dynamics in mosquito vectors and its relationship to human disease emergence. The following topics are reviewed: CHIKV infection and vector life history traits including transmission cycles, genetic origins, distribution, emergence and spread, dispersal, vector competence, vector immunity and microbial interactions, and co-infection by CHIKV and other arboviruses. The genetics of vector susceptibility and host range changes, population heterogeneity and selection for the fittest viral genomes, dual host cycling and its impact on CHIKV adaptation, viral bottlenecks and intrahost diversity, and adaptive constraints on CHIKV evolution are also discussed. The potential for CHIKV re-emergence and expansion into new areas and prospects for prevention via vector control are also briefly reviewed. PMID:25421891
Bonding over Dentin Replacement Materials.
Meraji, Naghmeh; Camilleri, Josette
2017-08-01
Dentin replacement materials are necessary in large cavities to protect the pulp and reduce the bulk of filling material. These materials are layered with a composite resin restorative material. Microleakage caused by poor bonding of composite resin to underlying dentin replacement material will result in pulp damage. The aim of this study was to characterize the interface between dentin replacement materials and composite resin and to measure the shear bond strength after dynamic aging. Biodentine (Septodont, Saint Maur-des-Fosses, France), Theracal LC (Bisco, Schaumburg, IL), and Fuji IX (GC, Tokyo, Japan) were used as dentin replacement materials. They were then overlaid with a total-etch and bonding agent or a self-etch primer and composite resin or a glass ionomer cement. All combinations were thermocycled for 3000 cycles. The interface was characterized using scanning electron microscopy and elemental mapping. Furthermore, the shear bond strength was assessed. The Biodentine surface was modified by etching. The Theracal LC and Fuji IX microstructure was unchanged upon the application of acid etch. The Biodentine and glass ionomer interface showed an evident wide open space, and glass particles from the glass ionomer adhered to the Biodentine surface. Elemental migration was shown with aluminum, barium, fluorine, and ytterbium present in Biodentine from the overlying composite resin. Calcium was more stable. The bond strength between Theracal LC and composite using a total-etch technique followed by self-etch primer achieved the best bond strength values. Biodentine exhibited the weakest bond with complete failure of bonding shown after demolding and thermocycling. Dynamic aging is necessary to have clinically valid data. Bonding composite resin to water-based dentin replacement materials is still challenging, and further alternatives for restoration of teeth using such materials need to be developed. Copyright © 2017 American Association of Endodontists
Emerging Vector-Borne Diseases - Incidence through Vectors.
Savić, Sara; Vidić, Branka; Grgić, Zivoslav; Potkonjak, Aleksandar; Spasojevic, Ljubica
2014-01-01
Vector-borne diseases use to be a major public health concern only in tropical and subtropical areas, but today they are an emerging threat for the continental and developed countries also. Nowadays, in intercontinental countries, there is a struggle with emerging diseases, which have found their way to appear through vectors. Vector-borne zoonotic diseases occur when vectors, animal hosts, climate conditions, pathogens, and susceptible human population exist at the same time, at the same place. Global climate change is predicted to lead to an increase in vector-borne infectious diseases and disease outbreaks. It could affect the range and population of pathogens, host and vectors, transmission season, etc. Reliable surveillance for diseases that are most likely to emerge is required. Canine vector-borne diseases represent a complex group of diseases including anaplasmosis, babesiosis, bartonellosis, borreliosis, dirofilariosis, ehrlichiosis, and leishmaniosis. Some of these diseases cause serious clinical symptoms in dogs and some of them have a zoonotic potential with an effect to public health. It is expected from veterinarians in coordination with medical doctors to play a fundamental role at primarily prevention and then treatment of vector-borne diseases in dogs. The One Health concept has to be integrated into the struggle against emerging diseases. During a 4-year period, from 2009 to 2013, a total number of 551 dog samples were analyzed for vector-borne diseases (borreliosis, babesiosis, ehrlichiosis, anaplasmosis, dirofilariosis, and leishmaniasis) in routine laboratory work. The analysis was done by serological tests - ELISA for borreliosis, dirofilariosis, and leishmaniasis, modified Knott test for dirofilariosis, and blood smear for babesiosis, ehrlichiosis, and anaplasmosis. This number of samples represented 75% of total number of samples that were sent for analysis for different diseases in dogs. Annually, on average more then half of the samples
New Predicted Spiral Search Block Matching Algorithm - PSSBMA
Directory of Open Access Journals (Sweden)
J. Pika
2002-04-01
Full Text Available This article describes the modification of the full search algorithmESBMA (Exhaustive Search Block Matching Algorithm, which leads up to40% speed increase. The modification is based on the ESBMA motion fieldanalysis results. The major modifications to the ESBMA are: -Introduction of sub-optimality by thresholding the matching criterion(MAEthr; - Respecting constraints on motion vectors resulting from"head and shoulder" scenes by changing the position of the searchstart; - Respecting the dependence of motion vectors (MV by predictionintroduction.
On flexible CAD of adaptive control and identification algorithms
DEFF Research Database (Denmark)
Christensen, Anders; Ravn, Ole
1988-01-01
SLLAB is a MATLAB-family software package for solving control and identification problems. This paper concerns the planning of a general-purpose subroutine structure for solving identification and adaptive control problems. A general-purpose identification algorithm is suggested, which allows...... a total redesign of the system within each sample. The necessary design parameters are evaluated and a decision vector is defined, from which the identification algorithm can be generated by the program. Using the decision vector, a decision-node tree structure is built up, where the nodes define...
Vector control of induction machines
Robyns, Benoit
2012-01-01
After a brief introduction to the main law of physics and fundamental concepts inherent in electromechanical conversion, ""Vector Control of Induction Machines"" introduces the standard mathematical models for induction machines - whichever rotor technology is used - as well as several squirrel-cage induction machine vector-control strategies. The use of causal ordering graphs allows systematization of the design stage, as well as standardization of the structure of control devices. ""Vector Control of Induction Machines"" suggests a unique approach aimed at reducing parameter sensitivity for
Vector boson scattering at CLIC
Energy Technology Data Exchange (ETDEWEB)
Kilian, Wolfgang; Fleper, Christian [Department Physik, Universitaet Siegen, 57068 Siegen (Germany); Reuter, Juergen [DESY Theory Group, 22603 Hamburg (Germany); Sekulla, Marco [Institut fuer Theoretische Physik, Karlsruher Institut fuer Technologie, 76131 Karlsruhe (Germany)
2016-07-01
Linear colliders operating in a range of multiple TeV are able to investigate the details of vector boson scattering and electroweak symmetry breaking. We calculate cross sections with the Monte Carlo generator WHIZARD for vector boson scattering processes at the future linear e{sup +} e{sup -} collider CLIC. By finding suitable cuts, the vector boson scattering signal processes are isolated from the background. Finally, we are able to determine exclusion sensitivities on the non-Standard Model parameters of the relevant dimension eight operators.
Patients Unicondylar Knee Replacement vs. Total Knee Replacement
Directory of Open Access Journals (Sweden)
Hedra Eskander
2017-02-01
Full Text Available The aim of this review article is to analyse the clinical effectiveness of total knee replacement (TKR compared to unicondylar knee replacement (UKR on patients. In terms of survival rates, revision rates and postoperative complications. The keywords used were: knee arthroplasty. Nearly three thousand articles were found on 25 August 2016. Of those, only twenty-five were selected and reviewed because they were strictly focused on the topic of this article. Compared with those who have TKR, patients who undergo UKR have higher revision rates at 5, 10 and 15 years. The reported overall risk of postoperative complications for patients undergoing TKR is 11%, compared with 4.3% for patients undergoing UKR. In conclusion, UKR have higher revision rates than TKR. However, an increased risk of postoperative complications after TKR.
Vector independent transmission of the vector-borne bluetongue virus.
van der Sluijs, Mirjam Tineke Willemijn; de Smit, Abraham J; Moormann, Rob J M
2016-01-01
Bluetongue is an economically important disease of ruminants. The causative agent, Bluetongue virus (BTV), is mainly transmitted by insect vectors. This review focuses on vector-free BTV transmission, and its epizootic and economic consequences. Vector-free transmission can either be vertical, from dam to fetus, or horizontal via direct contract. For several BTV-serotypes, vertical (transplacental) transmission has been described, resulting in severe congenital malformations. Transplacental transmission had been mainly associated with live vaccine strains. Yet, the European BTV-8 strain demonstrated a high incidence of transplacental transmission in natural circumstances. The relevance of transplacental transmission for the epizootiology is considered limited, especially in enzootic areas. However, transplacental transmission can have a substantial economic impact due to the loss of progeny. Inactivated vaccines have demonstrated to prevent transplacental transmission. Vector-free horizontal transmission has also been demonstrated. Since direct horizontal transmission requires close contact of animals, it is considered only relevant for within-farm spreading of BTV. The genetic determinants which enable vector-free transmission are present in virus strains circulating in the field. More research into the genetic changes which enable vector-free transmission is essential to better evaluate the risks associated with outbreaks of new BTV serotypes and to design more appropriate control measures.
Introduction to matrices and vectors
Schwartz, Jacob T
2001-01-01
In this concise undergraduate text, the first three chapters present the basics of matrices - in later chapters the author shows how to use vectors and matrices to solve systems of linear equations. 1961 edition.
All optical vector magnetometer Project
National Aeronautics and Space Administration — This Phase I research project will investigate a novel method of operating an atomic magnetometer to simultaneously measure total magnetic fields and vector magnetic...
GRE Enzymes for Vector Analysis
U.S. Environmental Protection Agency — Microbial enzyme data that were collected during the 2004-2006 EMAP-GRE program. These data were then used by Moorhead et al (2016) in their ecoenzyme vector...
1987-11-01
Phrases: N/A ] 19 RCT lontilue on revrm if necozsary and identify by block number) •"SA Fubini type theorem is obtained for vector bimasure integrals...Abstract A Fubini type theorem is obtained for vector bimeasure integrals. AMS (1980) subject classification: Primary 28B05; Secondary 60G12...Ylinen [11]. In the works mentioned above the authors consistently impose, in their definition of integrability. a Fubini type condition which cannot
A Spectral Algorithm for Envelope Reduction of Sparse Matrices
Barnard, Stephen T.; Pothen, Alex; Simon, Horst D.
1993-01-01
The problem of reordering a sparse symmetric matrix to reduce its envelope size is considered. A new spectral algorithm for computing an envelope-reducing reordering is obtained by associating a Laplacian matrix with the given matrix and then sorting the components of a specified eigenvector of the Laplacian. This Laplacian eigenvector solves a continuous relaxation of a discrete problem related to envelope minimization called the minimum 2-sum problem. The permutation vector computed by the spectral algorithm is a closest permutation vector to the specified Laplacian eigenvector. Numerical results show that the new reordering algorithm usually computes smaller envelope sizes than those obtained from the current standard algorithms such as Gibbs-Poole-Stockmeyer (GPS) or SPARSPAK reverse Cuthill-McKee (RCM), in some cases reducing the envelope by more than a factor of two.
New developments in astrodynamics algorithms for autonomous rendezvous
Klumpp, Allan R.
1991-01-01
A the core of any autonomous rendezvous guidance system must be two algorithms for solving Lambert's and Kepler's problems, the two fundamental problems in classical astrodynamics. Lambert's problem is to determine the trajectory connecting specified initial and terminal position vectors in a specified transfer time. The solution is the initial and terminal velocity vectors. Kepler's problem is to determine the trajectory that stems from a given initial state (position and velocity). The solution is the state of an earlier or later specified time. To be suitable for flight software, astrodynamics algorithms must be totally reliable, compact, and fast. Although solving Lambert's and Kepler's problems has challenged some of the world's finest minds for over two centuries, only in the last year have algorithms appeared that satisfy all three requirements just stated. This paper presents an evaluation of the most highly regarded Lambert and Kepler algorithms.
Robust Unsupervised Lagrangian Support Vector Machines for Supply Chain Management
Zhao, Kun; Liu, Yong-Sheng; Deng, Nai-Yang
Support Vector Machines (SVMs) have been dominant learning techniques for more than ten years, and mostly applied to supervised learning problems. These years two-class unsupervised and semi-supervised classification algorithms based on Bounded C-SVMs, Bounded ν-SVMs, Lagrangian SVMs (LSVMs) and robust version to Bounded C - SVMs respectively, and which are relaxed to Semi-definite Programming (SDP), get good classification results. The time consumed of method based on robust version to BC-SVMs is too long. So it seems necessary to find a faster method, which has almost accurate results as above at least. Therefore we proposed robust version to unsupervised and semi-supervised classification algorithms based on Lagrangian Support Vector Machines and its application on evaluation of supply chain management performance. Numerical results confirm the robustness of the proposed method and show that our new unsupervised and semi-supervised classification algorithms based on LSVMs often obtain almost the same accurate results as other algorithms,while considerably faster than them.
Dynamic algorithms for the Dyck languages
DEFF Research Database (Denmark)
Frandsen, Gudmund Skovbjerg; Husfeldt, Thore; Miltersen, Peter Bro
1995-01-01
We study Dynamic Membership problems for the Dyck languages, the class of strings of properly balanced parentheses. We also study the Dynamic Word problem for the free group. We present deterministic algorithms and data structures which maintain a string under replacements of symbols, insertions......, and deletions of symbols, and language membership queries. Updates and queries are handled in polylogarithmic time. We also give both Las Vegas- and Monte Carlo-type randomised algorithms to achieve better running times, and present lower bounds on the complexity for variants of the problems....
[MINIMALLY INVASIVE AORTIC VALVE REPLACEMENT].
Tabata, Minoru
2016-03-01
Minimally invasive aortic valve replacement (MIAVR) is defined as aortic valve replacement avoiding full sternotomy. Common approaches include a partial sternotomy right thoracotomy, and a parasternal approach. MIAVR has been shown to have advantages over conventional AVR such as shorter length of stay and smaller amount of blood transfusion and better cosmesis. However, it is also known to have disadvantages such as longer cardiopulmonary bypass and aortic cross-clamp times and potential complications related to peripheral cannulation. Appropriate patient selection is very important. Since the procedure is more complex than conventional AVR, more intensive teamwork in the operating room is essential. Additionally, a team approach during postoperative management is critical to maximize the benefits of MIAVR.
Skiena, Steven S
2008-01-01
Explaining designing algorithms, and analyzing their efficacy and efficiency, this book covers combinatorial algorithms technology, stressing design over analysis. It presents instruction on methods for designing and analyzing computer algorithms. It contains the catalog of algorithmic resources, implementations and a bibliography
Stationary algorithmic probability
National Research Council Canada - National Science Library
Müller, Markus
2010-01-01
...,sincetheiractualvaluesdependonthechoiceoftheuniversal referencecomputer.Inthispaper,weanalyzeanaturalapproachtoeliminatethismachine- dependence. Our method is to assign algorithmic probabilities to the different...
DEFF Research Database (Denmark)
Bucher, Taina
2017-01-01
This article reflects the kinds of situations and spaces where people and algorithms meet. In what situations do people become aware of algorithms? How do they experience and make sense of these algorithms, given their often hidden and invisible nature? To what extent does an awareness....... Examining how algorithms make people feel, then, seems crucial if we want to understand their social power....
Hamiltonian Algorithm Sound Synthesis
大矢, 健一
2013-01-01
Hamiltonian Algorithm (HA) is an algorithm for searching solutions is optimization problems. This paper introduces a sound synthesis technique using Hamiltonian Algorithm and shows a simple example. "Hamiltonian Algorithm Sound Synthesis" uses phase transition effect in HA. Because of this transition effect, totally new waveforms are produced.
The German Replacement Army (Ersatzheer)
1944-04-01
Erziehungs - und 13ildungswesens des Heeres, In EB), who is responsible to him. Training in the Replacement Army is conducted in training units...These schools are controlled by the Army Inspector of Training and Education (Inspekteur des Erziehungs - und Bildungswesens des Heeres). (3...letters Ue> on their shoulder straps. These schools are likewise controlled by the Army Inspector of Training and Education (In.spekteur des Erziehungs
Mitral valve repair versus replacement
Keshavamurthy, Suresh; Gillinov, A. Marc
2015-01-01
Degenerative, ischemic, rheumatic and infectious (endocarditis) processes are responsible for mitral valve disease in adults. Mitral valve repair has been widely regarded as the optimal surgical procedure to treat mitral valve dysfunction of all etiologies. The supporting evidence for repair over replacement is strongest in degenerative mitral regurgitation. The aim of the present review is to summarize the data in each category of mitral insufficiency and to provide recommendations based upon this data. PMID:26309824
Directory of Open Access Journals (Sweden)
C. Fernandez-Lozano
2013-01-01
Full Text Available Given the background of the use of Neural Networks in problems of apple juice classification, this paper aim at implementing a newly developed method in the field of machine learning: the Support Vector Machines (SVM. Therefore, a hybrid model that combines genetic algorithms and support vector machines is suggested in such a way that, when using SVM as a fitness function of the Genetic Algorithm (GA, the most representative variables for a specific classification problem can be selected.
Fernandez-Lozano, C.; Canto, C.; Gestal, M.; Andrade-Garda, J. M.; Rabuñal, J. R.; Dorado, J.; Pazos, A.
2013-01-01
Given the background of the use of Neural Networks in problems of apple juice classification, this paper aim at implementing a newly developed method in the field of machine learning: the Support Vector Machines (SVM). Therefore, a hybrid model that combines genetic algorithms and support vector machines is suggested in such a way that, when using SVM as a fitness function of the Genetic Algorithm (GA), the most representative variables for a specific classification problem can be selected. PMID:24453933
Energy Technology Data Exchange (ETDEWEB)
Geist, G.A. [Oak Ridge National Lab., TN (United States). Computer Science and Mathematics Div.; Howell, G.W. [Florida Inst. of Tech., Melbourne, FL (United States). Dept. of Applied Mathematics; Watkins, D.S. [Washington State Univ., Pullman, WA (United States). Dept. of Pure and Applied Mathematics
1997-11-01
The BR algorithm, a new method for calculating the eigenvalues of an upper Hessenberg matrix, is introduced. It is a bulge-chasing algorithm like the QR algorithm, but, unlike the QR algorithm, it is well adapted to computing the eigenvalues of the narrowband, nearly tridiagonal matrices generated by the look-ahead Lanczos process. This paper describes the BR algorithm and gives numerical evidence that it works well in conjunction with the Lanczos process. On the biggest problems run so far, the BR algorithm beats the QR algorithm by a factor of 30--60 in computing time and a factor of over 100 in matrix storage space.
LHC, LSI2, Point 4
2013-01-01
CERN engineers have been working through the night this week to move the final replacement dipole magnets into position on the Large Hadron Collider (LHC). Though there are several still to go, the teams expect to have completed the task by the end of this month. Dipole magnets bend the paths of particles as they travel around the circular accelerator. Of the LHC's 1232 dipoles – each 15 metres long and weighing 35 tonnes – 15 are being replaced as part of the long shutdown of CERN's accelerator complex. These 15 magnets suffered wear and tear during the LHC's first 4-year run. Three quadrupole-magnet assemblies – which help to focus particles into a tight beam – have also been replaced. Moving such heavy magnets requires specially adapted cranes and trailers both above and below ground. There are several access points on the LHC. Some, such as the 100-metre vertical access shaft down to the ALICE experiment, are equipped with lifts to allow technical personnel and visitors down to the caverns. Other ...
Results of Austin Moore replacement.
Directory of Open Access Journals (Sweden)
Jadhav A
1996-04-01
Full Text Available Forty cases of Austin Moore Replacement done for transcervical fractures of the femur in patients were reviewed after a period of 12 to 48 months postoperatively (mean 26 mth. 30 cases (75% had mild to severe pain of non-infective origin, starting as early as 6 months postoperatively. This was irrespective of the make, size or position (varus/valgus of the prosthesis. Though the Aufranc and Sweet clinical scoring was satisfactory in 65% cases, radiological evidence of complications like sinking, protrusion, etc. were seen in majority of the cases. Calcar resorption was seen in 34 cases (85% as early as 4 months postoperatively. Results of THR and bipolar replacement done for transcervical fractures in recent literature show 85% pain-free cases at 5 years. We feel that Austin Moore Replacement should be reserved for patients more than 65 years of age and those who are less active or debilitated because of other factors, because of increased acetabular wear with time in the younger individual. This is corroborated by unsatisfactory results in patients less than 65 years of age (p < 0.05.
The caudal septum replacement graft.
Foda, Hossam M T
2008-01-01
To describe a technique for reconstructing the lost tip support in cases involving caudal septal and premaxillary deficiencies. The study included 120 patients with aesthetic and functional nasal problems resulting from the loss of caudal septal and premaxillary support. An external rhinoplasty approach was performed to reconstruct the lost support using a cartilaginous caudal septum replacement graft and premaxillary augmentation with Mersilene mesh. The majority of cases (75%) involved revisions in patients who had previously undergone 1 or more nasal surgical procedures. A caudal septum replacement graft was combined with premaxillary augmentation in 93 patients (77.5%). The mean follow-up period was 3 years (range, 1-12 years). The technique succeeded in correcting the external nasal deformities in all patients and resulted in a significant improvement in breathing in 74 patients (86%) with preoperative nasal obstruction. There were no cases of infection, displacement, or extrusion. The caudal septum replacement graft proved to be very effective in restoring the lost tip support in patients with caudal septal deficiency. Combining the graft with premaxillary augmentation using Mersilene mesh helped increase support and stability over long-term follow-up.
Experimental realization of Shor's quantum factoring algorithm using qubit recycling
Martín-López, Enrique; Laing, Anthony; Lawson, Thomas; Alvarez, Roberto; Zhou, Xiao-Qi; O'Brien, Jeremy L.
2012-11-01
Quantum computational algorithms exploit quantum mechanics to solve problems exponentially faster than the best classical algorithms. Shor's quantum algorithm for fast number factoring is a key example and the prime motivator in the international effort to realize a quantum computer. However, due to the substantial resource requirement, to date there have been only four small-scale demonstrations. Here, we address this resource demand and demonstrate a scalable version of Shor's algorithm in which the n-qubit control register is replaced by a single qubit that is recycled n times: the total number of qubits is one-third of that required in the standard protocol. Encoding the work register in higher-dimensional states, we implement a two-photon compiled algorithm to factor N = 21. The algorithmic output is distinguishable from noise, in contrast to previous demonstrations. These results point to larger-scale implementations of Shor's algorithm by harnessing scalable resource reductions applicable to all physical architectures.
Algorithmic trading on Forex market with help of a Twitter
Brvar, Anže
2015-01-01
In this thesis we study the performance of electronic trading algorithms with a help of machine learning methods. We compare the performance of developed trading algorithms that trade based on posts (tweets) on Twitter with those that trade based on historic foreign exchange values and technical indicators. Besides the well known methods for text transformation to attribute notation we also use word2vec word vectors. We evaluate all the developed text transformation methods and their paramete...
White matter lesion segmentation using robust parameter estimation algorithms
Yang, Faguo; Zhu, Litao; Jiang, Tianzi
2003-05-01
White matter lesions are common brain abnormalities. In this paper, we introduce an automatic algorithm for segmentation of white matter lesions from brain MRI images. The intensities of each tissue is assumed to be Gaussian distributed, whose parameters (mean vector and covariance matrix) are estimated using a tissue distribution model. And then a measure is defined to indicate in how much content a voxel belongs to the lesions. Experimental results demonstrate that our algorithm works well.
Study on torque algorithm of switched reluctance motor
Li, Xiaoguang; Sun, Huiqin; Xue, Zhihong; Li, Kenan; Tianzi XUE
2016-01-01
To solve the torque ripple problem of switched reluctance motor under the traditional control method, a direct torque control method for switched reluctance motor is proposed. Direct torque algorithm controls flux magnitude and direction by querying appropriate voltage vector in switch list. Taking torque as direct control variable can reduce the torque ripple of the motor, which broadens the application fields of switched reluctance motor. Starting with the theory of direct torque algorithm,...
TEACHING ALGORITHMIZATION AND PROGRAMMING USING PYTHON LANGUAGE
Directory of Open Access Journals (Sweden)
M. Lvov
2014-07-01
Full Text Available The article describes requirements to educational programming languages and considers the use of Python as the first programming language. The issues of introduction of this programming language into teaching and replacing Pascal by Python are examined. The advantages of such approach are regarded. The comparison of popular programming languages is represented from the point of view of their convenience of use for teaching algorithmization and programming. Python supports lots of programming paradigms: structural, object-oriented, functional, imperative and aspect-oriented, and learning can be started without any preparation. There is one more advantage of the language: all algorithms are written easily and structurally in Python. Therefore, due to all mentioned above, it is possible to affirm that Python pretends to become a decent replacement for educational programming language PASCAL both at schools and on the first courses of higher education establishments.
Improving Vector Evaluated Particle Swarm Optimisation Using Multiple Nondominated Leaders
Lim, Kian Sheng; Buyamin, Salinda; Ahmad, Anita; Shapiai, Mohd Ibrahim; Naim, Faradila; Mubin, Marizan; Kim, Dong Hwa
2014-01-01
The vector evaluated particle swarm optimisation (VEPSO) algorithm was previously improved by incorporating nondominated solutions for solving multiobjective optimisation problems. However, the obtained solutions did not converge close to the Pareto front and also did not distribute evenly over the Pareto front. Therefore, in this study, the concept of multiple nondominated leaders is incorporated to further improve the VEPSO algorithm. Hence, multiple nondominated solutions that are best at a respective objective function are used to guide particles in finding optimal solutions. The improved VEPSO is measured by the number of nondominated solutions found, generational distance, spread, and hypervolume. The results from the conducted experiments show that the proposed VEPSO significantly improved the existing VEPSO algorithms. PMID:24883386
Algorithmically specialized parallel computers
Snyder, Lawrence; Gannon, Dennis B
1985-01-01
Algorithmically Specialized Parallel Computers focuses on the concept and characteristics of an algorithmically specialized computer.This book discusses the algorithmically specialized computers, algorithmic specialization using VLSI, and innovative architectures. The architectures and algorithms for digital signal, speech, and image processing and specialized architectures for numerical computations are also elaborated. Other topics include the model for analyzing generalized inter-processor, pipelined architecture for search tree maintenance, and specialized computer organization for raster
Vectors expressing chimeric Japanese encephalitis dengue 2 viruses.
Wei, Y; Wang, S; Wang, X
2014-01-01
Vectors based on self-replicating RNAs (replicons) of flaviviruses are becoming powerful tool for expression of heterologous genes in mammalian cells and development of novel antiviral and anticancer vaccines. We constructed two vectors expressing chimeric viruses consisting of attenuated SA14-14-2 strain of Japanese encephalitis virus (JEV) in which the PrM/M-E genes were replaced fully or partially with those of dengue 2 virus (DENV-2). These vectors, named pJED2 and pJED2-1770 were transfected to BHK-21 cells and produced chimeric viruses JED2V and JED2-1770V, respectively. The chimeric viruses could be passaged in C6/36 but not BHK-21 cells. The chimeric viruses produced in C6/36 cells CPE 4-5 days after infection and RT-PCR, sequencing, immunofluorescence assay (IFA) and Western blot analysis confirmed the chimeric nature of produced viruses. The immunogenicity of chimeric viruses in mice was proved by detecting DENV-2 E protein-specific serum IgG antibodies with neutralization titer of 10. Successful preparation of infectious clones of chimeric JEV-DENV-2 viruses showed that JEV-based expression vectors are fully functional.
Implementation of a new fuzzy vector control of induction motor.
Rafa, Souad; Larabi, Abdelkader; Barazane, Linda; Manceur, Malik; Essounbouli, Najib; Hamzaoui, Abdelaziz
2014-05-01
The aim of this paper is to present a new approach to control an induction motor using type-1 fuzzy logic. The induction motor has a nonlinear model, uncertain and strongly coupled. The vector control technique, which is based on the inverse model of the induction motors, solves the coupling problem. Unfortunately, in practice this is not checked because of model uncertainties. Indeed, the presence of the uncertainties led us to use human expertise such as the fuzzy logic techniques. In order to maintain the decoupling and to overcome the problem of the sensitivity to the parametric variations, the field-oriented control is replaced by a new block control. The simulation results show that the both control schemes provide in their basic configuration, comparable performances regarding the decoupling. However, the fuzzy vector control provides the insensitivity to the parametric variations compared to the classical one. The fuzzy vector control scheme is successfully implemented in real-time using a digital signal processor board dSPACE 1104. The efficiency of this technique is verified as well as experimentally at different dynamic operating conditions such as sudden loads change, parameter variations, speed changes, etc. The fuzzy vector control is found to be a best control for application in an induction motor. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.
Signal detection using support vector machines in the presence of ultrasonic speckle
Kotropoulos, Constantine L.; Pitas, Ioannis
2002-04-01
Support Vector Machines are a general algorithm based on guaranteed risk bounds of statistical learning theory. They have found numerous applications, such as in classification of brain PET images, optical character recognition, object detection, face verification, text categorization and so on. In this paper we propose the use of support vector machines to segment lesions in ultrasound images and we assess thoroughly their lesion detection ability. We demonstrate that trained support vector machines with a Radial Basis Function kernel segment satisfactorily (unseen) ultrasound B-mode images as well as clinical ultrasonic images.
Akbari, Omar S.; Chen, Chun-Hong; Marshall, John M.; Huang, Haixia; Antoshechkin, Igor; Hay, Bruce A.
2014-01-01
Insects act as vectors for diseases of plants, animals, and humans. Replacement of wild insect populations with genetically modified individuals unable to transmit disease provides a potentially self-perpetuating method of disease prevention. Population replacement requires a gene drive mechanism in order to spread linked genes mediating disease refractoriness through wild populations. We previously reported the creation of synthetic Medea selfish genetic elements able to drive population rep...
DEFF Research Database (Denmark)
Fuerstenberg, S; Beug, H; Introna, M
1990-01-01
into protein. Using the Escherichia coli beta-galactosidase gene cloned into the vector as a test construct, expression of enzyme activity could be detected in 90 to 95% of transfected target cells and in 80 to 85% of subsequently infected cells. In addition, a cDNA encoding the avian erythrocyte band 3 anion......A retrovirus vector was constructed from the genome of avian erythroblastosis virus ES4. The v-erbA sequences of avian erythroblastosis virus were replaced by those coding for neomycin phosphotransferase, creating a gag-neo fusion protein which provides G418 resistance as a selectable marker. The v......-erbB sequences following the splice acceptor were replaced by a cloning linker allowing insertion of foreign genes. The vector has been tested in conjunction with several helper viruses for the transmission of G418 resistance, titer, stability, transcription, and the transduction and expression of foreign genes...
Engineered AAV vectors for improved central nervous system gene delivery
A Kotterman, Melissa; Schaffer, David V
2015-01-01
Adeno-associated viruses (AAV) are non-pathogenic members of the Parvoviridae family that are being harnessed as delivery vehicles for both basic research and increasingly successful clinical gene therapy. To address a number of delivery shortcomings with natural AAV variants, we have developed and implemented directed evolution—a high-throughput molecular engineering approach to generate novel biomolecules with enhanced function—to create novel AAV vectors that are designed to preferentially transduce specific cell types in the central nervous system (CNS), including astrocytes, neural stem cells, and cells within the retina. These novel AAV vectors—which have enhanced infectivity in vitro and enhanced infectivity and selectivity in vivo—can enable more efficient studies to further our understanding of neurogenesis, development, aging, and disease. Furthermore, such engineered vectors may aid gene or cell replacement therapies to treat neurodegenerative disease or injury. PMID:27606332
D. Pylarinos; Theofilatos, K.; K. Siderakis; E. Thalassinakis
2013-01-01
A number of 387 discharge portraying waveforms recorded on 18 different 150 kV post insulators installed at two different Substations in Crete, Greece are considered in this paper. Twenty different features are extracted from each waveform and two feature selection algorithms (t-test and mRMR) are employed. Genetic algorithms are used to classify waveforms in two different classes related to the portrayed discharges. Five different data sets are employed (1. the original feature vector, 2. ti...
Reduced-Complexity Deterministic Annealing for Vector Quantizer Design
Directory of Open Access Journals (Sweden)
Ortega Antonio
2005-01-01
Full Text Available This paper presents a reduced-complexity deterministic annealing (DA approach for vector quantizer (VQ design by using soft information processing with simplified assignment measures. Low-complexity distributions are designed to mimic the Gibbs distribution, where the latter is the optimal distribution used in the standard DA method. These low-complexity distributions are simple enough to facilitate fast computation, but at the same time they can closely approximate the Gibbs distribution to result in near-optimal performance. We have also derived the theoretical performance loss at a given system entropy due to using the simple soft measures instead of the optimal Gibbs measure. We use thederived result to obtain optimal annealing schedules for the simple soft measures that approximate the annealing schedule for the optimal Gibbs distribution. The proposed reduced-complexity DA algorithms have significantly improved the quality of the final codebooks compared to the generalized Lloyd algorithm and standard stochastic relaxation techniques, both with and without the pairwise nearest neighbor (PNN codebook initialization. The proposed algorithms are able to evade the local minima and the results show that they are not sensitive to the choice of the initial codebook. Compared to the standard DA approach, the reduced-complexity DA algorithms can operate over 100 times faster with negligible performance difference. For example, for the design of a 16-dimensional vector quantizer having a rate of 0.4375 bit/sample for Gaussian source, the standard DA algorithm achieved 3.60 dB performance in 16 483 CPU seconds, whereas the reduced-complexity DA algorithm achieved the same performance in 136 CPU seconds. Other than VQ design, the DA techniques are applicable to problems such as classification, clustering, and resource allocation.
VectorBase: a home for invertebrate vectors of human pathogens
Lawson, Daniel; Arensburger, Peter; Atkinson, Peter; Besansky, Nora J.; Bruggner, Robert V.; Butler, Ryan; Campbell, Kathryn S.; Christophides, George K.; Christley, Scott; Dialynas, Emmanuel; Emmert, David; Hammond, Martin; Hill, Catherine A.; Kennedy, Ryan C.; Lobo, Neil F.; MacCallum, M. Robert; Madey, Greg; Megy, Karine; Redmond, Seth; Russo, Susan; Severson, David W.; Stinson, Eric O.; Topalis, Pantelis; Zdobnov, Evgeny M.; Birney, Ewan; Gelbart, William M.; Kafatos, Fotis C.; Louis, Christos; Collins, Frank H.
2007-01-01
VectorBase () is a web-accessible data repository for information about invertebrate vectors of human pathogens. VectorBase annotates and maintains vector genomes providing an integrated resource for the research community. Currently, VectorBase contains genome information for two organisms: Anopheles gambiae, a vector for the Plasmodium protozoan agent causing malaria, and Aedes aegypti, a vector for the flaviviral agents causing Yellow fever and Dengue fever. PMID:17145709
Giacosa, Francesco; Sammet, Julia; Janowski, Stanislaus
2017-06-01
We calculate two- and three-body decays of the (lightest) vector glueball into (pseudo)scalar, (axial-)vector, as well as pseudovector and excited vector mesons in the framework of a model of QCD. While absolute values of widths cannot be predicted because the corresponding coupling constants are unknown, some interesting branching ratios can be evaluated by setting the mass of the yet hypothetical vector glueball to 3.8 GeV as predicted by quenched lattice QCD. We find that the decay mode ω π π should be one of the largest (both through the decay chain O →b1π →ω π π and through the direct coupling O →ω π π ). Similarly, the (direct and indirect) decay into π K K*(892 ) is sizable. Moreover, the decays into ρ π and K*(892 )K are, although subleading, possible and could play a role in explaining the ρ π puzzle of the charmonium state ψ (2 S ) thanks to a (small) mixing with the vector glueball. The vector glueball can be directly formed at the ongoing BESIII experiment as well as at the future PANDA experiment at the FAIR facility. If the width is sufficiently small (≲100 MeV ) it should not escape future detection. It should be stressed that the employed model is based on some inputs and simplifying assumptions: the value of glueball mass (at present, the quenched lattice value is used), the lack of mixing of the glueball with other quarkonium states, and the use of few interaction terms. It then represents a first step toward the identification of the main decay channels of the vector glueball, but shall be improved when corresponding experimental candidates and/or new lattice results will be available.
A novel image retrieval algorithm based on PHOG and LSH
Wu, Hongliang; Wu, Weimin; Peng, Jiajin; Zhang, Junyuan
2017-08-01
PHOG can describe the local shape of the image and its relationship between the spaces. The using of PHOG algorithm to extract image features in image recognition and retrieval and other aspects have achieved good results. In recent years, locality sensitive hashing (LSH) algorithm has been superior to large-scale data in solving near-nearest neighbor problems compared with traditional algorithms. This paper presents a novel image retrieval algorithm based on PHOG and LSH. First, we use PHOG to extract the feature vector of the image, then use L different LSH hash table to reduce the dimension of PHOG texture to index values and map to different bucket, and finally extract the corresponding value of the image in the bucket for second image retrieval using Manhattan distance. This algorithm can adapt to the massive image retrieval, which ensures the high accuracy of the image retrieval and reduces the time complexity of the retrieval. This algorithm is of great significance.
Quantum Algorithm for K-Nearest Neighbors Classification Based on the Metric of Hamming Distance
Ruan, Yue; Xue, Xiling; Liu, Heng; Tan, Jianing; Li, Xi
2017-11-01
K-nearest neighbors (KNN) algorithm is a common algorithm used for classification, and also a sub-routine in various complicated machine learning tasks. In this paper, we presented a quantum algorithm (QKNN) for implementing this algorithm based on the metric of Hamming distance. We put forward a quantum circuit for computing Hamming distance between testing sample and each feature vector in the training set. Taking advantage of this method, we realized a good analog for classical KNN algorithm by setting a distance threshold value t to select k - n e a r e s t neighbors. As a result, QKNN achieves O( n 3) performance which is only relevant to the dimension of feature vectors and high classification accuracy, outperforms Llyod's algorithm (Lloyd et al. 2013) and Wiebe's algorithm (Wiebe et al. 2014).
The biological control of disease vectors.
Okamoto, Kenichi W; Amarasekare, Priyanga
2012-09-21
Vector-borne diseases are common in nature and can have a large impact on humans, livestock and crops. Biological control of vectors using natural enemies or competitors can reduce vector density and hence disease transmission. However, the indirect interactions inherent in host-vector disease systems make it difficult to use traditional pest control theory to guide biological control of disease vectors. This necessitates a conceptual framework that explicitly considers a range of indirect interactions between the host-vector disease system and the vector's biological control agent. Here we conduct a comparative analysis of the efficacy of different types of biological control agents in controlling vector-borne diseases. We report three key findings. First, highly efficient predators and parasitoids of the vector prove to be effective biological control agents, but highly virulent pathogens of the vector also require a high transmission rate to be effective. Second, biocontrol agents can successfully reduce long-term host disease incidence even though they may fail to reduce long-term vector densities. Third, inundating a host-vector disease system with a natural enemy of the vector has little or no effect on reducing disease incidence, but inundating the system with a competitor of the vector has a large effect on reducing disease incidence. The comparative framework yields predictions that are useful in developing biological control strategies for vector-borne diseases. We discuss how these predictions can inform ongoing biological control efforts for host-vector disease systems. Copyright © 2012. Published by Elsevier Ltd.
Distribution agnostic structured sparsity recovery algorithms
Al-Naffouri, Tareq Y.
2013-05-01
We present an algorithm and its variants for sparse signal recovery from a small number of its measurements in a distribution agnostic manner. The proposed algorithm finds Bayesian estimate of a sparse signal to be recovered and at the same time is indifferent to the actual distribution of its non-zero elements. Termed Support Agnostic Bayesian Matching Pursuit (SABMP), the algorithm also has the capability of refining the estimates of signal and required parameters in the absence of the exact parameter values. The inherent feature of the algorithm of being agnostic to the distribution of the data grants it the flexibility to adapt itself to several related problems. Specifically, we present two important extensions to this algorithm. One extension handles the problem of recovering sparse signals having block structures while the other handles multiple measurement vectors to jointly estimate the related unknown signals. We conduct extensive experiments to show that SABMP and its variants have superior performance to most of the state-of-the-art algorithms and that too at low-computational expense. © 2013 IEEE.
Zika Virus Mosquito Vectors: Competence, Biology, and Vector Control.
Kauffman, Elizabeth B; Kramer, Laura D
2017-12-16
Zika virus (ZIKV) (Flaviviridae, Flavivirus) has become one of the most medically important mosquito-borne viruses because of its ability to cause microcephaly in utero and Guillain-Barré syndrome in adults. This virus emerged from its sylvatic cycle in Africa to cause an outbreak in Yap, Federated States of Micronesia in 2007, French Polynesia in 2014, and most recently South America in 2015. The rapid expansion of ZIKV in the Americas largely has been due to the biology and behavior of its vector, Aedes aegypti. Other arboviruses transmitted by Ae. aegypti include the 2 flaviviruses dengue virus and yellow fever virus and the alphavirus chikungunya virus, which are also (re)emerging viruses in the Americas. This mosquito vector is highly domesticated, living in close association with humans in urban households. Its eggs are desiccation resistant, and the larvae develop rapidly in subtropical and tropical environments. Climate warming is facilitating range expansion of Ae. aegypti, adding to the threat this mosquito poses to human health, especially in light of the difficulty controlling it. Aedes albopictus, another highly invasive arbovirus vector that has only been implicated in one country (Gabon), is an important vector of ZIKV, but because of its wide geographic distribution may become a more important vector in the future. This article discusses the historical background of ZIKV and the biology and ecology of these 2 vectors. © The Author(s) 2017. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail: journals.permissions@oup.com.
Singh, R.; Verma, H. K.
2013-12-01
This paper presents a teaching-learning-based optimization (TLBO) algorithm to solve parameter identification problems in the designing of digital infinite impulse response (IIR) filter. TLBO based filter modelling is applied to calculate the parameters of unknown plant in simulations. Unlike other heuristic search algorithms, TLBO algorithm is an algorithm-specific parameter-less algorithm. In this paper big bang-big crunch (BB-BC) optimization and PSO algorithms are also applied to filter design for comparison. Unknown filter parameters are considered as a vector to be optimized by these algorithms. MATLAB programming is used for implementation of proposed algorithms. Experimental results show that the TLBO is more accurate to estimate the filter parameters than the BB-BC optimization algorithm and has faster convergence rate when compared to PSO algorithm. TLBO is used where accuracy is more essential than the convergence speed.
Generalized Selection Weighted Vector Filters
Directory of Open Access Journals (Sweden)
Rastislav Lukac
2004-09-01
Full Text Available This paper introduces a class of nonlinear multichannel filters capable of removing impulsive noise in color images. The here-proposed generalized selection weighted vector filter class constitutes a powerful filtering framework for multichannel signal processing. Previously defined multichannel filters such as vector median filter, basic vector directional filter, directional-distance filter, weighted vector median filters, and weighted vector directional filters are treated from a global viewpoint using the proposed framework. Robust order-statistic concepts and increased degree of freedom in filter design make the proposed method attractive for a variety of applications. Introduced multichannel sigmoidal adaptation of the filter parameters and its modifications allow to accommodate the filter parameters to varying signal and noise statistics. Simulation studies reported in this paper indicate that the proposed filter class is computationally attractive, yields excellent performance, and is able to preserve fine details and color information while efficiently suppressing impulsive noise. This paper is an extended version of the paper by Lukac et al. presented at the 2003 IEEE-EURASIP Workshop on Nonlinear Signal and Image Processing (NSIP '03 in Grado, Italy.
A generalized nonlocal vector calculus
Alali, Bacim; Liu, Kuo; Gunzburger, Max
2015-10-01
A nonlocal vector calculus was introduced in Du et al. (Math Model Meth Appl Sci 23:493-540, 2013) that has proved useful for the analysis of the peridynamics model of nonlocal mechanics and nonlocal diffusion models. A formulation is developed that provides a more general setting for the nonlocal vector calculus that is independent of particular nonlocal models. It is shown that general nonlocal calculus operators are integral operators with specific integral kernels. General nonlocal calculus properties are developed, including nonlocal integration by parts formula and Green's identities. The nonlocal vector calculus introduced in Du et al. (Math Model Meth Appl Sci 23:493-540, 2013) is shown to be recoverable from the general formulation as a special example. This special nonlocal vector calculus is used to reformulate the peridynamics equation of motion in terms of the nonlocal gradient operator and its adjoint. A new example of nonlocal vector calculus operators is introduced, which shows the potential use of the general formulation for general nonlocal models.
Robotically assisted mitral valve replacement.
Gao, Changqing; Yang, Ming; Xiao, Cangsong; Wang, Gang; Wu, Yang; Wang, Jiali; Li, Jiachun
2012-04-01
In the present study, we determined the safety and efficacy of robotic mitral valve replacement using robotic technology. From January 2007 through March 2011, more than 400 patients underwent various types of robotic cardiac surgery in our department. Of these, 22 consecutive patients underwent robotically assisted mitral valve replacement. Of the 22 patients with isolated rheumatic mitral valve stenosis (9 men and 13 women), the mean age was 44.7 ± 19.8 years (range, 32-65). Preoperatively, all patients underwent a complete workup, including coronary angiography and transthoracic echocardiography. Of the 22 patients, 15 had concomitant atrial fibrillation. The surgical approach was through 4 right-side chest ports with femoral perfusion. Aortic occlusion was performed with a Chitwood crossclamp, and antegrade cardioplegia was administered directly by way of the anterior chest. Using 3 port incisions in the right side of the chest and a 2.5- to 3.0-cm working port, all the procedures were completed with the da Vinci S robot. All patients underwent successful robotic surgery. Of the 22 patients, 16 received a mechanical valve and 6 a tissue valve. The mean cardiopulmonary bypass time and aortic crossclamp time was 137.1 ± 21.9 minutes (range, 105-168) and 99.3 ± 17.9 minutes (range, 80-133), respectively. No operative deaths, stroke, or other complications occurred, and no incisional conversions were required. After surgery, all the patients were followed up echocardiographically. Robotically assisted mitral valve replacement can be performed safely in patients with isolated mitral valve stenosis, and surgical results are excellent. Copyright Â© 2012 The American Association for Thoracic Surgery. Published by Mosby, Inc. All rights reserved.
Zainuddin, Zarita; Lai, Kee Huong; Ong, Pauline
2013-04-01
Artificial neural networks (ANNs) are powerful mathematical models that are used to solve complex real world problems. Wavelet neural networks (WNNs), which were developed based on the wavelet theory, are a variant of ANNs. During the training phase of WNNs, several parameters need to be initialized; including the type of wavelet activation functions, translation vectors, and dilation parameter. The conventional k-means and fuzzy c-means clustering algorithms have been used to select the translation vectors. However, the solution vectors might get trapped at local minima. In this regard, the evolutionary harmony search algorithm, which is capable of searching for near-optimum solution vectors, both locally and globally, is introduced to circumvent this problem. In this paper, the conventional k-means and fuzzy c-means clustering algorithms were hybridized with the metaheuristic harmony search algorithm. In addition to obtaining the estimation of the global minima accurately, these hybridized algorithms also offer more than one solution to a particular problem, since many possible solution vectors can be generated and stored in the harmony memory. To validate the robustness of the proposed WNNs, the real world problem of epileptic seizure detection was presented. The overall classification accuracy from the simulation showed that the hybridized metaheuristic algorithms outperformed the standard k-means and fuzzy c-means clustering algorithms.
[Enzyme replacement therapy for hypophosphatasia].
Ozono, Keiichi
2014-02-01
Hypophosphatasia is caused by abnormal tissue-nonspecific alkaline phosphatase (ALP), leading to impaired calcification in bone. Patients with severe hypophosphatasia have difficulties in respiratory function from early days after birth and the rate of lethality is extremely high. Enzyme replacement therapy using bone-targeting recombinant ALP, which has 10 aspartic acids in the C-terminal tail has developed. The efficacy of ERT was firstly observed in model mice of hypophosphatasia. In clinical trial including perinatal and infantile types of hypophosphatasia, efficacy and safety have been reported. Expanded clinical trial is underway and the results of the clinical trial might be reported by the end of the next year.
Characterization of digital medical images utilizing support vector machines
Directory of Open Access Journals (Sweden)
Zafiropoulos Elias P
2004-03-01
Full Text Available Abstract Background In this paper we discuss an efficient methodology for the image analysis and characterization of digital images containing skin lesions using Support Vector Machines and present the results of a preliminary study. Methods The methodology is based on the support vector machines algorithm for data classification and it has been applied to the problem of the recognition of malignant melanoma versus dysplastic naevus. Border and colour based features were extracted from digital images of skin lesions acquired under reproducible conditions, using basic image processing techniques. Two alternative classification methods, the statistical discriminant analysis and the application of neural networks were also applied to the same problem and the results are compared. Results The SVM (Support Vector Machines algorithm performed quite well achieving 94.1% correct classification, which is better than the performance of the other two classification methodologies. The method of discriminant analysis classified correctly 88% of cases (71% of Malignant Melanoma and 100% of Dysplastic Naevi, while the neural networks performed approximately the same. Conclusion The use of a computer-based system, like the one described in this paper, is intended to avoid human subjectivity and to perform specific tasks according to a number of criteria. However the presence of an expert dermatologist is considered necessary for the overall visual assessment of the skin lesion and the final diagnosis.
Generalized space vector control for current source inverters and rectifiers
Directory of Open Access Journals (Sweden)
Roseline J. Anitha
2016-06-01
Full Text Available Current source inverters (CSI is one of the widely used converter topology in medium voltage drive applications due to its simplicity, motor friendly waveforms and reliable short circuit protection. The current source inverters are usually fed by controlled current source rectifiers (CSR with a large inductor to provide a constant supply current. A generalized control applicable for both CSI and CSR and their extension namely current source multilevel inverters (CSMLI are dealt in this paper. As space vector pulse width modulation (SVPWM features the advantages of flexible control, faster dynamic response, better DC utilization and easy digital implementation it is considered for this work. This paper generalizes SVPWM that could be applied for CSI, CSR and CSMLI. The intense computation involved in framing a generalized space vector control are discussed in detail. The algorithm includes determination of band, region, subregions and vectors. The algorithm is validated by simulation using MATLAB /SIMULINK for CSR 5, 7, 13 level CSMLI and for CSR fed CSI.
Adaptive cockroach swarm algorithm
Obagbuwa, Ibidun C.; Abidoye, Ademola P.
2017-07-01
An adaptive cockroach swarm optimization (ACSO) algorithm is proposed in this paper to strengthen the existing cockroach swarm optimization (CSO) algorithm. The ruthless component of CSO algorithm is modified by the employment of blend crossover predator-prey evolution method which helps algorithm prevent any possible population collapse, maintain population diversity and create adaptive search in each iteration. The performance of the proposed algorithm on 16 global optimization benchmark function problems was evaluated and compared with the existing CSO, cuckoo search, differential evolution, particle swarm optimization and artificial bee colony algorithms.
Deciding to have knee or hip replacement
... medlineplus.gov/ency/patientinstructions/000368.htm Deciding to have knee or hip replacement To use the sharing ... date. Why you may not be Able to Have Replacement Surgery Your provider may recommend against knee ...
Long-life slab replacement concrete.
2015-03-01
This research was initiated following reports of high incidence of cracking on FDOT concrete pavement replacement : slab projects. Field slabs were instrumented for data acquisition from high-early-strength concrete pavement : replacement slabs place...
Long-life slab replacement concrete : [summary].
2015-04-01
Concrete slab replacement projects in Florida have demonstrated a high incidence of : replacement slab cracking. Causes of cracking have not been reliably determined. University of South Florida researchers : sought to identify the factors or : param...
A new hybrid imperialist competitive algorithm on data clustering
Indian Academy of Sciences (India)
Modified imperialist competitive algorithm; simulated annealing; k-means; data clustering. 1. Introduction. Clustering is one of the unsupervised learning branches where a set of patterns, usually vectors in a multi-dimensional space, are grouped into clusters in such a way that patterns in the same cluster are similar in some ...
Application of ANN and fuzzy logic algorithms for streamflow ...
Indian Academy of Sciences (India)
The present study focusses on development of models using ANN and fuzzy logic (FL) algorithm for predicting the streamflow for catchment of Savitri River Basin. The input vector to these models were daily rainfall, mean daily evaporation, mean daily temperature and lag streamflow used. In the present study, 20 years ...
Implementing the conjugate gradient algorithm on multi-core systems
Wiggers, W.A.; Bakker, Vincent; Kokkeler, Andre B.J.; Smit, Gerardus Johannes Maria; Nurmi, J.; Takala, J.; Vainio, O.
2007-01-01
In linear solvers, like the conjugate gradient algorithm, sparse-matrix vector multiplication is an important kernel. Due to the sparseness of the matrices, the solver runs relatively slow. For digital optical tomography (DOT), a large set of linear equations have to be solved which currently takes
(AJST) THE LINEAR ORDERING PROBLEM: AN ALGORITHM FOR ...
African Journals Online (AJOL)
ABSTRACT:- In this paper we describe and implement an algorithm for the exact solution of the ... is a minimal equation system for n. LO. P . Facets Induced by Dicycles. These are inequalities which excludes dicycles into the solution vector. If C is a dicycle in Dn, n≥3, ..... Note: The broken lines correspond to fractional.
A Lanczos algorithm for vibration, suckling and termal analysis
Bostic, Susan W.
1993-01-01
This paper reviews an eigensolver algorithm based on the Lanczos Method for vibration, buckling and thermal analysis. The original code was written for inclusion in the Computational Mechanics Testbed (COMET), a general purpose finite element code. A portable version of the Lanczos code that is optimized for high-performance supercomputers has been developed. Special features of the algorithm include the capability to compute rigid body modes, thermal modes and Lanczos vectors that are derived from the applied load vector. The latter is necessary when using the Lanczos vectors as reduced-basis vectors in transient structural response and transient heat conduction calculations. The modularity of the code allows the user the option of including the most up-to-date utilities, such as the equation solver best suited for the application. The algorithm is discussed in detail and results of several applications are presented. Timing results for a vibration application indicate that the Lanczos algorithm is twenty times faster than the subspace iteration method which has been extensively used in the past.
Synthetic Aperture Vector Flow Imaging
DEFF Research Database (Denmark)
Oddershede, Niels
2008-01-01
Current ultrasonic blood flow velocity measurement systems are subject to a number of limitations, including limited frame rate, aliasing artifacts, and that only the velocity component along the ultrasound beam is estimated. This dissertation aims at solving some of these problems. The main part...... of the thesis considers a method for estimating the two-dimensional velocity vector within the image plane. This method, called synthetic aperture vector flow imaging, is first shortly reviewed. The main contribution of this work is partly an analysis of the method with respect to focusing effects, motion...... estimation. The method can be used for increasing the frame rate of color flow maps or alternatively for a new imaging modality entitled quadroplex imaging, featuring a color flow map and two independent spectrograms at a high frame rate. The second is an alternative method for ultrasonic vector velocity...
Gauge Theories of Vector Particles
Glashow, S. L.; Gell-Mann, M.
1961-04-24
The possibility of generalizing the Yang-Mills trick is examined. Thus we seek theories of vector bosons invariant under continuous groups of coordinate-dependent linear transformations. All such theories may be expressed as superpositions of certain "simple" theories; we show that each "simple theory is associated with a simple Lie algebra. We may introduce mass terms for the vector bosons at the price of destroying the gauge-invariance for coordinate-dependent gauge functions. The theories corresponding to three particular simple Lie algebras - those which admit precisely two commuting quantum numbers - are examined in some detail as examples. One of them might play a role in the physics of the strong interactions if there is an underlying super-symmetry, transcending charge independence, that is badly broken. The intermediate vector boson theory of weak interactions is discussed also. The so-called "schizon" model cannot be made to conform to the requirements of partial gauge-invariance.
DEFF Research Database (Denmark)
Holbek, Simon
ultrasonic vector flow estimation and bring it a step closer to a clinical application. A method for high frame rate 3-D vector flow estimation in a plane using the transverse oscillation method combined with a 1024 channel 2-D matrix array is presented. The proposed method is validated both through phantom......For the last decade, the field of ultrasonic vector flow imaging has gotten an increasingly attention, as the technique offers a variety of new applications for screening and diagnostics of cardiovascular pathologies. The main purpose of this PhD project was therefore to advance the field of 3-D...... hampers the task of real-time processing. In a second study, some of the issue with the 2-D matrix array are solved by introducing a 2-D row-column (RC) addressing array with only 62 + 62 elements. It is investigated both through simulations and via experimental setups in various flow conditions...
Toward lattice fractional vector calculus
Tarasov, Vasily E.
2014-09-01
An analog of fractional vector calculus for physical lattice models is suggested. We use an approach based on the models of three-dimensional lattices with long-range inter-particle interactions. The lattice analogs of fractional partial derivatives are represented by kernels of lattice long-range interactions, where the Fourier series transformations of these kernels have a power-law form with respect to wave vector components. In the continuum limit, these lattice partial derivatives give derivatives of non-integer order with respect to coordinates. In the three-dimensional description of the non-local continuum, the fractional differential operators have the form of fractional partial derivatives of the Riesz type. As examples of the applications of the suggested lattice fractional vector calculus, we give lattice models with long-range interactions for the fractional Maxwell equations of non-local continuous media and for the fractional generalization of the Mindlin and Aifantis continuum models of gradient elasticity.
Directory of Open Access Journals (Sweden)
Ivaniš Predrag
2004-01-01
Full Text Available This paper presents combination of Channel Optimized Vector Quantization based on LBG algorithm and sub channel power allocation for MIMO systems with Singular Value Decomposition and limited number of active sub channels. Proposed algorithm is designed to enable maximal throughput with bit error rate bellow some tar- get level in case of backward channel capacity limitation. Presence of errors effect in backward channel is also considered.
Obesity in total hip replacement.
Andrew, J G; Palan, J; Kurup, H V; Gibson, P; Murray, D W; Beard, D J
2008-04-01
A prospective, multi-centre study was carried out on 1421 total hip replacements between January 1999 and July 2007 to examine if obesity has an effect on clinical outcomes. The patients were categorised into three groups: non-obese (body mass index (BMI) 40 kg/m(2)). The primary outcome measure was the change in Oxford hip score at five years. Secondary outcome measures included dislocation and revision rates, increased haemorrhage, deep infection, deep-vein thrombosis and pulmonary embolism, mean operating time and length of hospital stay. Radiological analysis assessing heterotopic ossification, femoral osteolysis and femoral stem positioning was performed. Data were incomplete for 362 hips (25.5%) There was no difference in the change in the Oxford hip score, complication rates or radiological changes at five years between the groups. The morbidly obese group was significantly younger and required a significantly longer operating time. Obese and morbidly obese patients have as much to gain from total hip replacement as non-obese patients.
REMINDER REPLACEMENT OF FRENCH CARDS
Human Resources Division; Cards.Service@cern.ch
2001-01-01
The French Ministry of Foreign Affairs is currently replacing all diplomatic cards, special cards and employment permits («attestations de fonctions») held by members of the personnel and their families. These cards are replaced by secure, computerized equivalents. The old cards may no longer be used after 31 December 2001. For the purposes of the handover, members of the personnel must go personally to the cards office (33/1-015) between 8h30 and 12h30, in order to fill in a «fiche individuelle» form, taking the following documents for themselves and members of their families already in possession of a French card : A recent identity photograph in 4.5 cm x 3.5 cm format, the French card in their possession, an A4 photocopy of the same French card, certified by the cards office as being a true copy. Those members of the personnel whose cards (and/or cards belonging to members of their families) are shortly due to expire, or have recently done so, are also requested...
Learning with Support Vector Machines
Campbell, Colin
2010-01-01
Support Vectors Machines have become a well established tool within machine learning. They work well in practice and have now been used across a wide range of applications from recognizing hand-written digits, to face identification, text categorisation, bioinformatics, and database marketing. In this book we give an introductory overview of this subject. We start with a simple Support Vector Machine for performing binary classification before considering multi-class classification and learning in the presence of noise. We show that this framework can be extended to many other scenarios such a