Interior point algorithms theory and analysis

CERN Document Server

Ye, Yinyu

2011-01-01

The first comprehensive review of the theory and practice of one of today's most powerful optimization techniques. The explosive growth of research into and development of interior point algorithms over the past two decades has significantly improved the complexity of linear programming and yielded some of today's most sophisticated computing techniques. This book offers a comprehensive and thorough treatment of the theory, analysis, and implementation of this powerful computational tool. Interior Point Algorithms provides detailed coverage of all basic and advanced aspects of the subject.

The Research and Application of SURF Algorithm Based on Feature Point Selection Algorithm

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Zhang Fang Hu

2014-04-01

Full Text Available As the pixel information of depth image is derived from the distance information, when implementing SURF algorithm with KINECT sensor for static sign language recognition, there can be some mismatched pairs in palm area. This paper proposes a feature point selection algorithm, by filtering the SURF feature points step by step based on the number of feature points within adaptive radius r and the distance between the two points, it not only greatly improves the recognition rate, but also ensures the robustness under the environmental factors, such as skin color, illumination intensity, complex background, angle and scale changes. The experiment results show that the improved SURF algorithm can effectively improve the recognition rate, has a good robustness.

Models and algorithms for midterm production planning under uncertainty: application of proximal decomposition methods

International Nuclear Information System (INIS)

Lenoir, A.

2008-01-01

We focus in this thesis, on the optimization process of large systems under uncertainty, and more specifically on solving the class of so-called deterministic equivalents with the help of splitting methods. The underlying application we have in mind is the electricity unit commitment problem under climate, market and energy consumption randomness, arising at EDF. We set the natural time-space-randomness couplings related to this application and we propose two new discretization schemes to tackle the randomness one, each of them based on non-parametric estimation of conditional expectations. This constitute an alternative to the usual scenario tree construction. We use the mathematical model consisting of the sum of two convex functions, a separable one and a coupling one. On the one hand, this simplified model offers a general framework to study decomposition-coordination algorithms by elapsing technicality due to a particular choice of subsystems. On the other hand, the convexity assumption allows to take advantage of monotone operators theory and to identify proximal methods as fixed point algorithms. We underlie the differential properties of the generalized reactions we are looking for a fixed point in order to derive bounds on the speed of convergence. Then we examine two families of decomposition-coordination algorithms resulting from operator splitting methods, namely Forward-Backward and Rachford methods. We suggest some practical method of acceleration of the Rachford class methods. To this end, we analyze the method from a theoretical point of view, furnishing as a byproduct explanations to some numerical observations. Then we propose as a response some improvements. Among them, an automatic updating strategy of scaling factors can correct a potential bad initial choice. The convergence proof is made easier thanks to stability results of some operator composition with respect to graphical convergence provided before. We also submit the idea of introducing

The Homogeneous Interior-Point Algorithm: Nonsymmetric Cones, Warmstarting, and Applications

DEFF Research Database (Denmark)

Skajaa, Anders

algorithms for these problems is still limited. The goal of this thesis is to investigate and shed light on two computational aspects of homogeneous interior-point algorithms for convex conic optimization: The first part studies the possibility of devising a homogeneous interior-point method aimed at solving...... problems involving constraints that require nonsymmetric cones in their formulation. The second part studies the possibility of warmstarting the homogeneous interior-point algorithm for conic problems. The main outcome of the first part is the introduction of a completely new homogeneous interior......-point algorithm designed to solve nonsymmetric convex conic optimization problems. The algorithm is presented in detail and then analyzed. We prove its convergence and complexity. From a theoretical viewpoint, it is fully competitive with other algorithms and from a practical viewpoint, we show that it holds lots...

Optimal Power Flow by Interior Point and Non Interior Point Modern Optimization Algorithms

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Marcin Połomski

2013-03-01

Full Text Available The idea of optimal power flow (OPF is to determine the optimal settings for control variables while respecting various constraints, and in general it is related to power system operational and planning optimization problems. A vast number of optimization methods have been applied to solve the OPF problem, but their performance is highly dependent on the size of a power system being optimized. The development of the OPF recently has tracked significant progress both in numerical optimization techniques and computer techniques application. In recent years, application of interior point methods to solve OPF problem has been paid great attention. This is due to the fact that IP methods are among the fastest algorithms, well suited to solve large-scale nonlinear optimization problems. This paper presents the primal-dual interior point method based optimal power flow algorithm and new variant of the non interior point method algorithm with application to optimal power flow problem. Described algorithms were implemented in custom software. The experiments show the usefulness of computational software and implemented algorithms for solving the optimal power flow problem, including the system model sizes comparable to the size of the National Power System.

Existence and Convergence of Best Proximity Points for Semi Cyclic Contraction Pairs

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Balwant Singh Thakur

2014-02-01

Full Text Available In this article, we introduce the notion of a semi cyclic ϕ-contraction pair of mappings, which contains semi cyclic contraction pairs as a subclass. Existence and convergence results of best proximity points for semi cyclic ϕ- contraction pair of mappings are obtained.

The Pointing Self-calibration Algorithm for Aperture Synthesis Radio Telescopes

Energy Technology Data Exchange (ETDEWEB)

Bhatnagar, S.; Cornwell, T. J., E-mail: sbhatnag@nrao.edu [National Radio Astronomy Observatory, 1003 Lopezville Road, Socorro, NM 87801 (United States)

2017-11-01

This paper is concerned with algorithms for calibration of direction-dependent effects (DDE) in aperture synthesis radio telescopes (ASRT). After correction of direction-independent effects (DIE) using self-calibration, imaging performance can be limited by the imprecise knowledge of the forward gain of the elements in the array. In general, the forward gain pattern is directionally dependent and varies with time due to a number of reasons. Some factors, such as rotation of the primary beam with Parallactic Angle for Azimuth–Elevation mount antennas are known a priori. Some, such as antenna pointing errors and structural deformation/projection effects for aperture-array elements cannot be measured a priori. Thus, in addition to algorithms to correct for DD effects known a priori, algorithms to solve for DD gains are required for high dynamic range imaging. Here, we discuss a mathematical framework for antenna-based DDE calibration algorithms and show that this framework leads to computationally efficient optimal algorithms that scale well in a parallel computing environment. As an example of an antenna-based DD calibration algorithm, we demonstrate the Pointing SelfCal (PSC) algorithm to solve for the antenna pointing errors. Our analysis show that the sensitivity of modern ASRT is sufficient to solve for antenna pointing errors and other DD effects. We also discuss the use of the PSC algorithm in real-time calibration systems and extensions for antenna Shape SelfCal algorithm for real-time tracking and corrections for pointing offsets and changes in antenna shape.

The Pointing Self-calibration Algorithm for Aperture Synthesis Radio Telescopes

Science.gov (United States)

Bhatnagar, S.; Cornwell, T. J.

2017-11-01

This paper is concerned with algorithms for calibration of direction-dependent effects (DDE) in aperture synthesis radio telescopes (ASRT). After correction of direction-independent effects (DIE) using self-calibration, imaging performance can be limited by the imprecise knowledge of the forward gain of the elements in the array. In general, the forward gain pattern is directionally dependent and varies with time due to a number of reasons. Some factors, such as rotation of the primary beam with Parallactic Angle for Azimuth-Elevation mount antennas are known a priori. Some, such as antenna pointing errors and structural deformation/projection effects for aperture-array elements cannot be measured a priori. Thus, in addition to algorithms to correct for DD effects known a priori, algorithms to solve for DD gains are required for high dynamic range imaging. Here, we discuss a mathematical framework for antenna-based DDE calibration algorithms and show that this framework leads to computationally efficient optimal algorithms that scale well in a parallel computing environment. As an example of an antenna-based DD calibration algorithm, we demonstrate the Pointing SelfCal (PSC) algorithm to solve for the antenna pointing errors. Our analysis show that the sensitivity of modern ASRT is sufficient to solve for antenna pointing errors and other DD effects. We also discuss the use of the PSC algorithm in real-time calibration systems and extensions for antenna Shape SelfCal algorithm for real-time tracking and corrections for pointing offsets and changes in antenna shape.

Spline Trajectory Algorithm Development: Bezier Curve Control Point Generation for UAVs

Science.gov (United States)

Howell, Lauren R.; Allen, B. Danette

2016-01-01

A greater need for sophisticated autonomous piloting systems has risen in direct correlation with the ubiquity of Unmanned Aerial Vehicle (UAV) technology. Whether surveying unknown or unexplored areas of the world, collecting scientific data from regions in which humans are typically incapable of entering, locating lost or wanted persons, or delivering emergency supplies, an unmanned vehicle moving in close proximity to people and other vehicles, should fly smoothly and predictably. The mathematical application of spline interpolation can play an important role in autopilots' on-board trajectory planning. Spline interpolation allows for the connection of Three-Dimensional Euclidean Space coordinates through a continuous set of smooth curves. This paper explores the motivation, application, and methodology used to compute the spline control points, which shape the curves in such a way that the autopilot trajectory is able to meet vehicle-dynamics limitations. The spline algorithms developed used to generate these curves supply autopilots with the information necessary to compute vehicle paths through a set of coordinate waypoints.

Genetic Algorithm Based Economic Dispatch with Valve Point Effect

Energy Technology Data Exchange (ETDEWEB)

Park, Jong Nam; Park, Kyung Won; Kim, Ji Hong; Kim, Jin O [Hanyang University (Korea, Republic of)

1999-03-01

This paper presents a new approach on genetic algorithm to economic dispatch problem for valve point discontinuities. Proposed approach in this paper on genetic algorithms improves the performance to solve economic dispatch problem for valve point discontinuities through improved death penalty method, generation-apart elitism, atavism and sexual selection with sexual distinction. Numerical results on a test system consisting of 13 thermal units show that the proposed approach is faster, more robust and powerful than conventional genetic algorithms. (author). 8 refs., 10 figs.

APPLICABILITY ANALYSIS OF CLOTH SIMULATION FILTERING ALGORITHM FOR MOBILE LIDAR POINT CLOUD

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S. Cai

2018-04-01

Full Text Available Classifying the original point clouds into ground and non-ground points is a key step in LiDAR (light detection and ranging data post-processing. Cloth simulation filtering (CSF algorithm, which based on a physical process, has been validated to be an accurate, automatic and easy-to-use algorithm for airborne LiDAR point cloud. As a new technique of three-dimensional data collection, the mobile laser scanning (MLS has been gradually applied in various fields, such as reconstruction of digital terrain models (DTM, 3D building modeling and forest inventory and management. Compared with airborne LiDAR point cloud, there are some different features (such as point density feature, distribution feature and complexity feature for mobile LiDAR point cloud. Some filtering algorithms for airborne LiDAR data were directly used in mobile LiDAR point cloud, but it did not give satisfactory results. In this paper, we explore the ability of the CSF algorithm for mobile LiDAR point cloud. Three samples with different shape of the terrain are selected to test the performance of this algorithm, which respectively yields total errors of 0.44 %, 0.77 % and1.20 %. Additionally, large area dataset is also tested to further validate the effectiveness of this algorithm, and results show that it can quickly and accurately separate point clouds into ground and non-ground points. In summary, this algorithm is efficient and reliable for mobile LiDAR point cloud.

An Implementable First-Order Primal-Dual Algorithm for Structured Convex Optimization

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Feng Ma

2014-01-01

Full Text Available Many application problems of practical interest can be posed as structured convex optimization models. In this paper, we study a new first-order primaldual algorithm. The method can be easily implementable, provided that the resolvent operators of the component objective functions are simple to evaluate. We show that the proposed method can be interpreted as a proximal point algorithm with a customized metric proximal parameter. Convergence property is established under the analytic contraction framework. Finally, we verify the efficiency of the algorithm by solving the stable principal component pursuit problem.

Design and Implementation of Numerical Linear Algebra Algorithms on Fixed Point DSPs

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Gene Frantz

2007-01-01

Full Text Available Numerical linear algebra algorithms use the inherent elegance of matrix formulations and are usually implemented using C/C++ floating point representation. The system implementation is faced with practical constraints because these algorithms usually need to run in real time on fixed point digital signal processors (DSPs to reduce total hardware costs. Converting the simulation model to fixed point arithmetic and then porting it to a target DSP device is a difficult and time-consuming process. In this paper, we analyze the conversion process. We transformed selected linear algebra algorithms from floating point to fixed point arithmetic, and compared real-time requirements and performance between the fixed point DSP and floating point DSP algorithm implementations. We also introduce an advanced code optimization and an implementation by DSP-specific, fixed point C code generation. By using the techniques described in the paper, speed can be increased by a factor of up to 10 compared to floating point emulation on fixed point hardware.

Parallel algorithm for dominant points correspondences in robot binocular stereo vision

Science.gov (United States)

Al-Tammami, A.; Singh, B.

1993-01-01

This paper presents an algorithm to find the correspondences of points representing dominant feature in robot stereo vision. The algorithm consists of two main steps: dominant point extraction and dominant point matching. In the feature extraction phase, the algorithm utilizes the widely used Moravec Interest Operator and two other operators: the Prewitt Operator and a new operator called Gradient Angle Variance Operator. The Interest Operator in the Moravec algorithm was used to exclude featureless areas and simple edges which are oriented in the vertical, horizontal, and two diagonals. It was incorrectly detecting points on edges which are not on the four main directions (vertical, horizontal, and two diagonals). The new algorithm uses the Prewitt operator to exclude featureless areas, so that the Interest Operator is applied only on the edges to exclude simple edges and to leave interesting points. This modification speeds-up the extraction process by approximately 5 times. The Gradient Angle Variance (GAV), an operator which calculates the variance of the gradient angle in a window around the point under concern, is then applied on the interesting points to exclude the redundant ones and leave the actual dominant ones. The matching phase is performed after the extraction of the dominant points in both stereo images. The matching starts with dominant points in the left image and does a local search, looking for corresponding dominant points in the right image. The search is geometrically constrained the epipolar line of the parallel-axes stereo geometry and the maximum disparity of the application environment. If one dominant point in the right image lies in the search areas, then it is the corresponding point of the reference dominant point in the left image. A parameter provided by the GAV is thresholded and used as a rough similarity measure to select the corresponding dominant point if there is more than one point the search area. The correlation is used as

Finite Element Modelling of a Field-Sensed Magnetic Suspended System for Accurate Proximity Measurement Based on a Sensor Fusion Algorithm with Unscented Kalman Filter.

Science.gov (United States)

Chowdhury, Amor; Sarjaš, Andrej

2016-09-15

The presented paper describes accurate distance measurement for a field-sensed magnetic suspension system. The proximity measurement is based on a Hall effect sensor. The proximity sensor is installed directly on the lower surface of the electro-magnet, which means that it is very sensitive to external magnetic influences and disturbances. External disturbances interfere with the information signal and reduce the usability and reliability of the proximity measurements and, consequently, the whole application operation. A sensor fusion algorithm is deployed for the aforementioned reasons. The sensor fusion algorithm is based on the Unscented Kalman Filter, where a nonlinear dynamic model was derived with the Finite Element Modelling approach. The advantage of such modelling is a more accurate dynamic model parameter estimation, especially in the case when the real structure, materials and dimensions of the real-time application are known. The novelty of the paper is the design of a compact electro-magnetic actuator with a built-in low cost proximity sensor for accurate proximity measurement of the magnetic object. The paper successively presents a modelling procedure with the finite element method, design and parameter settings of a sensor fusion algorithm with Unscented Kalman Filter and, finally, the implementation procedure and results of real-time operation.

A density based algorithm to detect cavities and holes from planar points

Science.gov (United States)

Zhu, Jie; Sun, Yizhong; Pang, Yueyong

2017-12-01

Delaunay-based shape reconstruction algorithms are widely used in approximating the shape from planar points. However, these algorithms cannot ensure the optimality of varied reconstructed cavity boundaries and hole boundaries. This inadequate reconstruction can be primarily attributed to the lack of efficient mathematic formulation for the two structures (hole and cavity). In this paper, we develop an efficient algorithm for generating cavities and holes from planar points. The algorithm yields the final boundary based on an iterative removal of the Delaunay triangulation. Our algorithm is mainly divided into two steps, namely, rough and refined shape reconstructions. The rough shape reconstruction performed by the algorithm is controlled by a relative parameter. Based on the rough result, the refined shape reconstruction mainly aims to detect holes and pure cavities. Cavity and hole are conceptualized as a structure with a low-density region surrounded by the high-density region. With this structure, cavity and hole are characterized by a mathematic formulation called as compactness of point formed by the length variation of the edges incident to point in Delaunay triangulation. The boundaries of cavity and hole are then found by locating a shape gradient change in compactness of point set. The experimental comparison with other shape reconstruction approaches shows that the proposed algorithm is able to accurately yield the boundaries of cavity and hole with varying point set densities and distributions.

Computational proximity excursions in the topology of digital images

CERN Document Server

Peters, James F

2016-01-01

This book introduces computational proximity (CP) as an algorithmic approach to finding nonempty sets of points that are either close to each other or far apart. Typically in computational proximity, the book starts with some form of proximity space (topological space equipped with a proximity relation) that has an inherent geometry. In CP, two types of near sets are considered, namely, spatially near sets and descriptivelynear sets. It is shown that connectedness, boundedness, mesh nerves, convexity, shapes and shape theory are principal topics in the study of nearness and separation of physical aswell as abstract sets. CP has a hefty visual content. Applications of CP in computer vision, multimedia, brain activity, biology, social networks, and cosmology are included. The book has been derived from the lectures of the author in a graduate course on the topology of digital images taught over the past several years. Many of the students have provided important insights and valuable suggestions. The topics in ...

Automated detection and classification of the proximal humerus fracture by using deep learning algorithm.

Science.gov (United States)

Chung, Seok Won; Han, Seung Seog; Lee, Ji Whan; Oh, Kyung-Soo; Kim, Na Ra; Yoon, Jong Pil; Kim, Joon Yub; Moon, Sung Hoon; Kwon, Jieun; Lee, Hyo-Jin; Noh, Young-Min; Kim, Youngjun

2018-03-26

Background and purpose - We aimed to evaluate the ability of artificial intelligence (a deep learning algorithm) to detect and classify proximal humerus fractures using plain anteroposterior shoulder radiographs. Patients and methods - 1,891 images (1 image per person) of normal shoulders (n = 515) and 4 proximal humerus fracture types (greater tuberosity, 346; surgical neck, 514; 3-part, 269; 4-part, 247) classified by 3 specialists were evaluated. We trained a deep convolutional neural network (CNN) after augmentation of a training dataset. The ability of the CNN, as measured by top-1 accuracy, area under receiver operating characteristics curve (AUC), sensitivity/specificity, and Youden index, in comparison with humans (28 general physicians, 11 general orthopedists, and 19 orthopedists specialized in the shoulder) to detect and classify proximal humerus fractures was evaluated. Results - The CNN showed a high performance of 96% top-1 accuracy, 1.00 AUC, 0.99/0.97 sensitivity/specificity, and 0.97 Youden index for distinguishing normal shoulders from proximal humerus fractures. In addition, the CNN showed promising results with 65-86% top-1 accuracy, 0.90-0.98 AUC, 0.88/0.83-0.97/0.94 sensitivity/specificity, and 0.71-0.90 Youden index for classifying fracture type. When compared with the human groups, the CNN showed superior performance to that of general physicians and orthopedists, similar performance to orthopedists specialized in the shoulder, and the superior performance of the CNN was more marked in complex 3- and 4-part fractures. Interpretation - The use of artificial intelligence can accurately detect and classify proximal humerus fractures on plain shoulder AP radiographs. Further studies are necessary to determine the feasibility of applying artificial intelligence in the clinic and whether its use could improve care and outcomes compared with current orthopedic assessments.

Fixed-point image orthorectification algorithms for reduced computational cost

Science.gov (United States)

French, Joseph Clinton

Imaging systems have been applied to many new applications in recent years. With the advent of low-cost, low-power focal planes and more powerful, lower cost computers, remote sensing applications have become more wide spread. Many of these applications require some form of geolocation, especially when relative distances are desired. However, when greater global positional accuracy is needed, orthorectification becomes necessary. Orthorectification is the process of projecting an image onto a Digital Elevation Map (DEM), which removes terrain distortions and corrects the perspective distortion by changing the viewing angle to be perpendicular to the projection plane. Orthorectification is used in disaster tracking, landscape management, wildlife monitoring and many other applications. However, orthorectification is a computationally expensive process due to floating point operations and divisions in the algorithm. To reduce the computational cost of on-board processing, two novel algorithm modifications are proposed. One modification is projection utilizing fixed-point arithmetic. Fixed point arithmetic removes the floating point operations and reduces the processing time by operating only on integers. The second modification is replacement of the division inherent in projection with a multiplication of the inverse. The inverse must operate iteratively. Therefore, the inverse is replaced with a linear approximation. As a result of these modifications, the processing time of projection is reduced by a factor of 1.3x with an average pixel position error of 0.2% of a pixel size for 128-bit integer processing and over 4x with an average pixel position error of less than 13% of a pixel size for a 64-bit integer processing. A secondary inverse function approximation is also developed that replaces the linear approximation with a quadratic. The quadratic approximation produces a more accurate approximation of the inverse, allowing for an integer multiplication calculation

A dual exterior point simplex type algorithm for the minimum cost network flow problem

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Geranis George

2009-01-01

Full Text Available A new dual simplex type algorithm for the Minimum Cost Network Flow Problem (MCNFP is presented. The proposed algorithm belongs to a special 'exterior- point simplex type' category. Similarly to the classical network dual simplex algorithm (NDSA, this algorithm starts with a dual feasible tree-solution and reduces the primal infeasibility, iteration by iteration. However, contrary to the NDSA, the new algorithm does not always maintain a dual feasible solution. Instead, the new algorithm might reach a basic point (tree-solution outside the dual feasible area (exterior point - dual infeasible tree.

Study on Huizhou architecture of point cloud registration based on optimized ICP algorithm

Science.gov (United States)

Zhang, Runmei; Wu, Yulu; Zhang, Guangbin; Zhou, Wei; Tao, Yuqian

2018-03-01

In view of the current point cloud registration software has high hardware requirements, heavy workload and moltiple interactive definition, the source of software with better processing effect is not open, a two--step registration method based on normal vector distribution feature and coarse feature based iterative closest point (ICP) algorithm is proposed in this paper. This method combines fast point feature histogram (FPFH) algorithm, define the adjacency region of point cloud and the calculation model of the distribution of normal vectors, setting up the local coordinate system for each key point, and obtaining the transformation matrix to finish rough registration, the rough registration results of two stations are accurately registered by using the ICP algorithm. Experimental results show that, compared with the traditional ICP algorithm, the method used in this paper has obvious time and precision advantages for large amount of point clouds.

A Regularized Algorithm for the Proximal Split Feasibility Problem

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Zhangsong Yao

2014-01-01

Full Text Available The proximal split feasibility problem has been studied. A regularized method has been presented for solving the proximal split feasibility problem. Strong convergence theorem is given.

A curvature-based weighted fuzzy c-means algorithm for point clouds de-noising

Science.gov (United States)

Cui, Xin; Li, Shipeng; Yan, Xiutian; He, Xinhua

2018-04-01

In order to remove the noise of three-dimensional scattered point cloud and smooth the data without damnify the sharp geometric feature simultaneity, a novel algorithm is proposed in this paper. The feature-preserving weight is added to fuzzy c-means algorithm which invented a curvature weighted fuzzy c-means clustering algorithm. Firstly, the large-scale outliers are removed by the statistics of r radius neighboring points. Then, the algorithm estimates the curvature of the point cloud data by using conicoid parabolic fitting method and calculates the curvature feature value. Finally, the proposed clustering algorithm is adapted to calculate the weighted cluster centers. The cluster centers are regarded as the new points. The experimental results show that this approach is efficient to different scale and intensities of noise in point cloud with a high precision, and perform a feature-preserving nature at the same time. Also it is robust enough to different noise model.

Artificial Neural Network In Maximum Power Point Tracking Algorithm Of Photovoltaic Systems

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Modestas Pikutis

2014-05-01

Full Text Available Scientists are looking for ways to improve the efficiency of solar cells all the time. The efficiency of solar cells which are available to the general public is up to 20%. Part of the solar energy is unused and a capacity of solar power plant is significantly reduced – if slow controller or controller which cannot stay at maximum power point of solar modules is used. Various algorithms of maximum power point tracking were created, but mostly algorithms are slow or make mistakes. In the literature more and more oftenartificial neural networks (ANN in maximum power point tracking process are mentioned, in order to improve performance of the controller. Self-learner artificial neural network and IncCond algorithm were used for maximum power point tracking in created solar power plant model. The algorithm for control was created. Solar power plant model is implemented in Matlab/Simulink environment.

Approximate solutions of common fixed-point problems

CERN Document Server

Zaslavski, Alexander J

2016-01-01

This book presents results on the convergence behavior of algorithms which are known as vital tools for solving convex feasibility problems and common fixed point problems. The main goal for us in dealing with a known computational error is to find what approximate solution can be obtained and how many iterates one needs to find it. According to know results, these algorithms should converge to a solution. In this exposition, these algorithms are studied, taking into account computational errors which remain consistent in practice. In this case the convergence to a solution does not take place. We show that our algorithms generate a good approximate solution if computational errors are bounded from above by a small positive constant. Beginning with an introduction, this monograph moves on to study: · dynamic string-averaging methods for common fixed point problems in a Hilbert space · dynamic string methods for common fixed point problems in a metric space · dynamic string-averaging version of the proximal...

A superlinear interior points algorithm for engineering design optimization

Science.gov (United States)

Herskovits, J.; Asquier, J.

1990-01-01

We present a quasi-Newton interior points algorithm for nonlinear constrained optimization. It is based on a general approach consisting of the iterative solution in the primal and dual spaces of the equalities in Karush-Kuhn-Tucker optimality conditions. This is done in such a way to have primal and dual feasibility at each iteration, which ensures satisfaction of those optimality conditions at the limit points. This approach is very strong and efficient, since at each iteration it only requires the solution of two linear systems with the same matrix, instead of quadratic programming subproblems. It is also particularly appropriate for engineering design optimization inasmuch at each iteration a feasible design is obtained. The present algorithm uses a quasi-Newton approximation of the second derivative of the Lagrangian function in order to have superlinear asymptotic convergence. We discuss theoretical aspects of the algorithm and its computer implementation.

Algorithms for solving common fixed point problems

CERN Document Server

Zaslavski, Alexander J

2018-01-01

This book details approximate solutions to common fixed point problems and convex feasibility problems in the presence of perturbations. Convex feasibility problems search for a common point of a finite collection of subsets in a Hilbert space; common fixed point problems pursue a common fixed point of a finite collection of self-mappings in a Hilbert space. A variety of algorithms are considered in this book for solving both types of problems, the study of which has fueled a rapidly growing area of research. This monograph is timely and highlights the numerous applications to engineering, computed tomography, and radiation therapy planning. Totaling eight chapters, this book begins with an introduction to foundational material and moves on to examine iterative methods in metric spaces. The dynamic string-averaging methods for common fixed point problems in normed space are analyzed in Chapter 3. Dynamic string methods, for common fixed point problems in a metric space are introduced and discussed in Chapter ...

The implement of Talmud property allocation algorithm based on graphic point-segment way

Science.gov (United States)

Cen, Haifeng

2017-04-01

Under the guidance of the Talmud allocation scheme's theory, the paper analyzes the algorithm implemented process via the perspective of graphic point-segment way, and designs the point-segment way's Talmud property allocation algorithm. Then it uses Java language to implement the core of allocation algorithm, by using Android programming to build a visual interface.

A Primal-Dual Interior Point-Linear Programming Algorithm for MPC

DEFF Research Database (Denmark)

Edlund, Kristian; Sokoler, Leo Emil; Jørgensen, John Bagterp

2009-01-01

Constrained optimal control problems for linear systems with linear constraints and an objective function consisting of linear and l1-norm terms can be expressed as linear programs. We develop an efficient primal-dual interior point algorithm for solution of such linear programs. The algorithm...

a Threshold-Free Filtering Algorithm for Airborne LIDAR Point Clouds Based on Expectation-Maximization

Science.gov (United States)

Hui, Z.; Cheng, P.; Ziggah, Y. Y.; Nie, Y.

2018-04-01

Filtering is a key step for most applications of airborne LiDAR point clouds. Although lots of filtering algorithms have been put forward in recent years, most of them suffer from parameters setting or thresholds adjusting, which will be time-consuming and reduce the degree of automation of the algorithm. To overcome this problem, this paper proposed a threshold-free filtering algorithm based on expectation-maximization. The proposed algorithm is developed based on an assumption that point clouds are seen as a mixture of Gaussian models. The separation of ground points and non-ground points from point clouds can be replaced as a separation of a mixed Gaussian model. Expectation-maximization (EM) is applied for realizing the separation. EM is used to calculate maximum likelihood estimates of the mixture parameters. Using the estimated parameters, the likelihoods of each point belonging to ground or object can be computed. After several iterations, point clouds can be labelled as the component with a larger likelihood. Furthermore, intensity information was also utilized to optimize the filtering results acquired using the EM method. The proposed algorithm was tested using two different datasets used in practice. Experimental results showed that the proposed method can filter non-ground points effectively. To quantitatively evaluate the proposed method, this paper adopted the dataset provided by the ISPRS for the test. The proposed algorithm can obtain a 4.48 % total error which is much lower than most of the eight classical filtering algorithms reported by the ISPRS.

An efficient algorithm to compute subsets of points in ℤ n

OpenAIRE

Pacheco Martínez, Ana María; Real Jurado, Pedro

2012-01-01

In this paper we show a more efficient algorithm than that in [8] to compute subsets of points non-congruent by isometries. This algorithm can be used to reconstruct the object from the digital image. Both algorithms are compared, highlighting the improvements obtained in terms of CPU time.

Hierarchical Threshold Adaptive for Point Cloud Filter Algorithm of Moving Surface Fitting

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ZHU Xiaoxiao

2018-02-01

Full Text Available In order to improve the accuracy,efficiency and adaptability of point cloud filtering algorithm,a hierarchical threshold adaptive for point cloud filter algorithm of moving surface fitting was proposed.Firstly,the noisy points are removed by using a statistic histogram method.Secondly,the grid index is established by grid segmentation,and the surface equation is set up through the lowest point among the neighborhood grids.The real height and fit are calculated.The difference between the elevation and the threshold can be determined.Finally,in order to improve the filtering accuracy,hierarchical filtering is used to change the grid size and automatically set the neighborhood size and threshold until the filtering result reaches the accuracy requirement.The test data provided by the International Photogrammetry and Remote Sensing Society (ISPRS is used to verify the algorithm.The first and second error and the total error are 7.33%,10.64% and 6.34% respectively.The algorithm is compared with the eight classical filtering algorithms published by ISPRS.The experiment results show that the method has well-adapted and it has high accurate filtering result.

Momentum and Stochastic Momentum for Stochastic Gradient, Newton, Proximal Point and Subspace Descent Methods

KAUST Repository

Loizou, Nicolas

2017-12-27

In this paper we study several classes of stochastic optimization algorithms enriched with heavy ball momentum. Among the methods studied are: stochastic gradient descent, stochastic Newton, stochastic proximal point and stochastic dual subspace ascent. This is the first time momentum variants of several of these methods are studied. We choose to perform our analysis in a setting in which all of the above methods are equivalent. We prove global nonassymptotic linear convergence rates for all methods and various measures of success, including primal function values, primal iterates (in L2 sense), and dual function values. We also show that the primal iterates converge at an accelerated linear rate in the L1 sense. This is the first time a linear rate is shown for the stochastic heavy ball method (i.e., stochastic gradient descent method with momentum). Under somewhat weaker conditions, we establish a sublinear convergence rate for Cesaro averages of primal iterates. Moreover, we propose a novel concept, which we call stochastic momentum, aimed at decreasing the cost of performing the momentum step. We prove linear convergence of several stochastic methods with stochastic momentum, and show that in some sparse data regimes and for sufficiently small momentum parameters, these methods enjoy better overall complexity than methods with deterministic momentum. Finally, we perform extensive numerical testing on artificial and real datasets, including data coming from average consensus problems.

Momentum and Stochastic Momentum for Stochastic Gradient, Newton, Proximal Point and Subspace Descent Methods

KAUST Repository

Loizou, Nicolas; Richtarik, Peter

2017-01-01

In this paper we study several classes of stochastic optimization algorithms enriched with heavy ball momentum. Among the methods studied are: stochastic gradient descent, stochastic Newton, stochastic proximal point and stochastic dual subspace ascent. This is the first time momentum variants of several of these methods are studied. We choose to perform our analysis in a setting in which all of the above methods are equivalent. We prove global nonassymptotic linear convergence rates for all methods and various measures of success, including primal function values, primal iterates (in L2 sense), and dual function values. We also show that the primal iterates converge at an accelerated linear rate in the L1 sense. This is the first time a linear rate is shown for the stochastic heavy ball method (i.e., stochastic gradient descent method with momentum). Under somewhat weaker conditions, we establish a sublinear convergence rate for Cesaro averages of primal iterates. Moreover, we propose a novel concept, which we call stochastic momentum, aimed at decreasing the cost of performing the momentum step. We prove linear convergence of several stochastic methods with stochastic momentum, and show that in some sparse data regimes and for sufficiently small momentum parameters, these methods enjoy better overall complexity than methods with deterministic momentum. Finally, we perform extensive numerical testing on artificial and real datasets, including data coming from average consensus problems.

Proximity Queries between Interval-Based CSG Octrees

International Nuclear Information System (INIS)

Dyllong, Eva; Grimm, Cornelius

2007-01-01

This short paper is concerned with a new algorithm for collision and distance calculation between CSG octrees, a generalization of an octree model created from a Constructive Solid Geometry (CSG) object. The data structure uses interval arithmetic and allows us to extend the tests for classifying points in space as inside, on the boundary, or outside a CSG object to entire sections of the space at once. Tree nodes with additional information about relevant parts of the CSG object are introduced in order to reduce the depth of the required subdivision. The new data structure reduces the input complexity and enables us to reconstruct the CSG object. We present an efficient algorithm for computing the distance between CSG objects encoded by the new data structure. The distance algorithm is based on a distance algorithm for classical octrees but, additionally, it utilizes an elaborated sort sequence and differentiated handling of pairs of octree nodes to enhance its efficiency. Experimental results indicate that, in comparison to common octrees, the new representation has advantages in the field of proximity query

A deterministic algorithm for fitting a step function to a weighted point-set

KAUST Repository

Fournier, Hervé

2013-02-01

Given a set of n points in the plane, each point having a positive weight, and an integer k>0, we present an optimal O(nlogn)-time deterministic algorithm to compute a step function with k steps that minimizes the maximum weighted vertical distance to the input points. It matches the expected time bound of the best known randomized algorithm for this problem. Our approach relies on Coles improved parametric searching technique. As a direct application, our result yields the first O(nlogn)-time algorithm for computing a k-center of a set of n weighted points on the real line. © 2012 Elsevier B.V.

Computational Analysis of Distance Operators for the Iterative Closest Point Algorithm.

Directory of Open Access Journals (Sweden)

Higinio Mora

Full Text Available The Iterative Closest Point (ICP algorithm is currently one of the most popular methods for rigid registration so that it has become the standard in the Robotics and Computer Vision communities. Many applications take advantage of it to align 2D/3D surfaces due to its popularity and simplicity. Nevertheless, some of its phases present a high computational cost thus rendering impossible some of its applications. In this work, it is proposed an efficient approach for the matching phase of the Iterative Closest Point algorithm. This stage is the main bottleneck of that method so that any efficiency improvement has a great positive impact on the performance of the algorithm. The proposal consists in using low computational cost point-to-point distance metrics instead of classic Euclidean one. The candidates analysed are the Chebyshev and Manhattan distance metrics due to their simpler formulation. The experiments carried out have validated the performance, robustness and quality of the proposal. Different experimental cases and configurations have been set up including a heterogeneous set of 3D figures, several scenarios with partial data and random noise. The results prove that an average speed up of 14% can be obtained while preserving the convergence properties of the algorithm and the quality of the final results.

A maximum power point tracking algorithm for buoy-rope-drum wave energy converters

Science.gov (United States)

Wang, J. Q.; Zhang, X. C.; Zhou, Y.; Cui, Z. C.; Zhu, L. S.

2016-08-01

The maximum power point tracking control is the key link to improve the energy conversion efficiency of wave energy converters (WEC). This paper presents a novel variable step size Perturb and Observe maximum power point tracking algorithm with a power classification standard for control of a buoy-rope-drum WEC. The algorithm and simulation model of the buoy-rope-drum WEC are presented in details, as well as simulation experiment results. The results show that the algorithm tracks the maximum power point of the WEC fast and accurately.

A trust region interior point algorithm for optimal power flow problems

Energy Technology Data Exchange (ETDEWEB)

Wang Min [Hefei University of Technology (China). Dept. of Electrical Engineering and Automation; Liu Shengsong [Jiangsu Electric Power Dispatching and Telecommunication Company (China). Dept. of Automation

2005-05-01

This paper presents a new algorithm that uses the trust region interior point method to solve nonlinear optimal power flow (OPF) problems. The OPF problem is solved by a primal/dual interior point method with multiple centrality corrections as a sequence of linearized trust region sub-problems. It is the trust region that controls the linear step size and ensures the validity of the linear model. The convergence of the algorithm is improved through the modification of the trust region sub-problem. Numerical results of standard IEEE systems and two realistic networks ranging in size from 14 to 662 buses are presented. The computational results show that the proposed algorithm is very effective to optimal power flow applications, and favors the successive linear programming (SLP) method. Comparison with the predictor/corrector primal/dual interior point (PCPDIP) method is also made to demonstrate the superiority of the multiple centrality corrections technique. (author)

A homogeneous interior-point algorithm for nonsymmetric convex conic optimization

DEFF Research Database (Denmark)

Skajaa, Anders; Ye, Yinyu

2014-01-01

-centered primal–dual point. Features of the algorithm include that it makes use only of the primal barrier function, that it is able to detect infeasibilities in the problem and that no phase-I method is needed. We prove convergence to TeX -accuracy in TeX iterations. To improve performance, the algorithm employs...

A New Numerical Algorithm for Two-Point Boundary Value Problems

OpenAIRE

Guo, Lihua; Wu, Boying; Zhang, Dazhi

2014-01-01

We present a new numerical algorithm for two-point boundary value problems. We first present the exact solution in the form of series and then prove that the n-term numerical solution converges uniformly to the exact solution. Furthermore, we establish the numerical stability and error analysis. The numerical results show the effectiveness of the proposed algorithm.

A primal-dual exterior point algorithm for linear programming problems

Directory of Open Access Journals (Sweden)

Samaras Nikolaos

2009-01-01

Full Text Available The aim of this paper is to present a new simplex type algorithm for the Linear Programming Problem. The Primal - Dual method is a Simplex - type pivoting algorithm that generates two paths in order to converge to the optimal solution. The first path is primal feasible while the second one is dual feasible for the original problem. Specifically, we use a three-phase-implementation. The first two phases construct the required primal and dual feasible solutions, using the Primal Simplex algorithm. Finally, in the third phase the Primal - Dual algorithm is applied. Moreover, a computational study has been carried out, using randomly generated sparse optimal linear problems, to compare its computational efficiency with the Primal Simplex algorithm and also with MATLAB's Interior Point Method implementation. The algorithm appears to be very promising since it clearly shows its superiority to the Primal Simplex algorithm as well as its robustness over the IPM algorithm.

Symbiotic organisms search algorithm for dynamic economic dispatch with valve-point effects

Science.gov (United States)

Sonmez, Yusuf; Kahraman, H. Tolga; Dosoglu, M. Kenan; Guvenc, Ugur; Duman, Serhat

2017-05-01

In this study, symbiotic organisms search (SOS) algorithm is proposed to solve the dynamic economic dispatch with valve-point effects problem, which is one of the most important problems of the modern power system. Some practical constraints like valve-point effects, ramp rate limits and prohibited operating zones have been considered as solutions. Proposed algorithm was tested on five different test cases in 5 units, 10 units and 13 units systems. The obtained results have been compared with other well-known metaheuristic methods reported before. Results show that proposed algorithm has a good convergence and produces better results than other methods.

Error tolerance in an NMR implementation of Grover's fixed-point quantum search algorithm

International Nuclear Information System (INIS)

Xiao Li; Jones, Jonathan A.

2005-01-01

We describe an implementation of Grover's fixed-point quantum search algorithm on a nuclear magnetic resonance quantum computer, searching for either one or two matching items in an unsorted database of four items. In this algorithm the target state (an equally weighted superposition of the matching states) is a fixed point of the recursive search operator, so that the algorithm always moves towards the desired state. The effects of systematic errors in the implementation are briefly explored

Solving Singular Two-Point Boundary Value Problems Using Continuous Genetic Algorithm

Directory of Open Access Journals (Sweden)

Omar Abu Arqub

2012-01-01

Full Text Available In this paper, the continuous genetic algorithm is applied for the solution of singular two-point boundary value problems, where smooth solution curves are used throughout the evolution of the algorithm to obtain the required nodal values. The proposed technique might be considered as a variation of the finite difference method in the sense that each of the derivatives is replaced by an appropriate difference quotient approximation. This novel approach possesses main advantages; it can be applied without any limitation on the nature of the problem, the type of singularity, and the number of mesh points. Numerical examples are included to demonstrate the accuracy, applicability, and generality of the presented technique. The results reveal that the algorithm is very effective, straightforward, and simple.

On Implementing a Homogeneous Interior-Point Algorithm for Nonsymmetric Conic Optimization

DEFF Research Database (Denmark)

Skajaa, Anders; Jørgensen, John Bagterp; Hansen, Per Christian

Based on earlier work by Nesterov, an implementation of a homogeneous infeasible-start interior-point algorithm for solving nonsymmetric conic optimization problems is presented. Starting each iteration from (the vicinity of) the central path, the method computes (nearly) primal-dual symmetric...... approximate tangent directions followed by a purely primal centering procedure to locate the next central primal-dual point. Features of the algorithm include that it makes use only of the primal barrier function, that it is able to detect infeasibilities in the problem and that no phase-I method is needed...

Design of Automatic Extraction Algorithm of Knowledge Points for MOOCs

Directory of Open Access Journals (Sweden)

Haijian Chen

2015-01-01

Full Text Available In recent years, Massive Open Online Courses (MOOCs are very popular among college students and have a powerful impact on academic institutions. In the MOOCs environment, knowledge discovery and knowledge sharing are very important, which currently are often achieved by ontology techniques. In building ontology, automatic extraction technology is crucial. Because the general methods of text mining algorithm do not have obvious effect on online course, we designed automatic extracting course knowledge points (AECKP algorithm for online course. It includes document classification, Chinese word segmentation, and POS tagging for each document. Vector Space Model (VSM is used to calculate similarity and design the weight to optimize the TF-IDF algorithm output values, and the higher scores will be selected as knowledge points. Course documents of “C programming language” are selected for the experiment in this study. The results show that the proposed approach can achieve satisfactory accuracy rate and recall rate.

Object tracking system using a VSW algorithm based on color and point features

Directory of Open Access Journals (Sweden)

Lim Hye-Youn

2011-01-01

Full Text Available Abstract An object tracking system using a variable search window (VSW algorithm based on color and feature points is proposed. A meanshift algorithm is an object tracking technique that works according to color probability distributions. An advantage of this algorithm based on color is that it is robust to specific color objects; however, a disadvantage is that it is sensitive to non-specific color objects due to illumination and noise. Therefore, to offset this weakness, it presents the VSW algorithm based on robust feature points for the accurate tracking of moving objects. The proposed method extracts the feature points of a detected object which is the region of interest (ROI, and generates a VSW using the given information which is the positions of extracted feature points. The goal of this paper is to achieve an efficient and effective object tracking system that meets the accurate tracking of moving objects. Through experiments, the object tracking system is implemented that it performs more precisely than existing techniques.

On a Hopping-Points SVD and Hough Transform-Based Line Detection Algorithm for Robot Localization and Mapping

Directory of Open Access Journals (Sweden)

Abhijeet Ravankar

2016-05-01

Full Text Available Line detection is an important problem in computer vision, graphics and autonomous robot navigation. Lines detected using a laser range sensor (LRS mounted on a robot can be used as features to build a map of the environment, and later to localize the robot in the map, in a process known as Simultaneous Localization and Mapping (SLAM. We propose an efficient algorithm for line detection from LRS data using a novel hopping-points Singular Value Decomposition (SVD and Hough transform-based algorithm, in which SVD is applied to intermittent LRS points to accelerate the algorithm. A reverse-hop mechanism ensures that the end points of the line segments are accurately extracted. Line segments extracted from the proposed algorithm are used to form a map and, subsequently, LRS data points are matched with the line segments to localize the robot. The proposed algorithm eliminates the drawbacks of point-based matching algorithms like the Iterative Closest Points (ICP algorithm, the performance of which degrades with an increasing number of points. We tested the proposed algorithm for mapping and localization in both simulated and real environments, and found it to detect lines accurately and build maps with good self-localization.

Generation of a statistical shape model with probabilistic point correspondences and the expectation maximization- iterative closest point algorithm

International Nuclear Information System (INIS)

Hufnagel, Heike; Pennec, Xavier; Ayache, Nicholas; Ehrhardt, Jan; Handels, Heinz

2008-01-01

Identification of point correspondences between shapes is required for statistical analysis of organ shapes differences. Since manual identification of landmarks is not a feasible option in 3D, several methods were developed to automatically find one-to-one correspondences on shape surfaces. For unstructured point sets, however, one-to-one correspondences do not exist but correspondence probabilities can be determined. A method was developed to compute a statistical shape model based on shapes which are represented by unstructured point sets with arbitrary point numbers. A fundamental problem when computing statistical shape models is the determination of correspondences between the points of the shape observations of the training data set. In the absence of landmarks, exact correspondences can only be determined between continuous surfaces, not between unstructured point sets. To overcome this problem, we introduce correspondence probabilities instead of exact correspondences. The correspondence probabilities are found by aligning the observation shapes with the affine expectation maximization-iterative closest points (EM-ICP) registration algorithm. In a second step, the correspondence probabilities are used as input to compute a mean shape (represented once again by an unstructured point set). Both steps are unified in a single optimization criterion which depe nds on the two parameters 'registration transformation' and 'mean shape'. In a last step, a variability model which best represents the variability in the training data set is computed. Experiments on synthetic data sets and in vivo brain structure data sets (MRI) are then designed to evaluate the performance of our algorithm. The new method was applied to brain MRI data sets, and the estimated point correspondences were compared to a statistical shape model built on exact correspondences. Based on established measures of ''generalization ability'' and ''specificity'', the estimates were very satisfactory

BPP: a sequence-based algorithm for branch point prediction.

Science.gov (United States)

Zhang, Qing; Fan, Xiaodan; Wang, Yejun; Sun, Ming-An; Shao, Jianlin; Guo, Dianjing

2017-10-15

Although high-throughput sequencing methods have been proposed to identify splicing branch points in the human genome, these methods can only detect a small fraction of the branch points subject to the sequencing depth, experimental cost and the expression level of the mRNA. An accurate computational model for branch point prediction is therefore an ongoing objective in human genome research. We here propose a novel branch point prediction algorithm that utilizes information on the branch point sequence and the polypyrimidine tract. Using experimentally validated data, we demonstrate that our proposed method outperforms existing methods. Availability and implementation: https://github.com/zhqingit/BPP. djguo@cuhk.edu.hk. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Document localization algorithms based on feature points and straight lines

Science.gov (United States)

Skoryukina, Natalya; Shemiakina, Julia; Arlazarov, Vladimir L.; Faradjev, Igor

2018-04-01

The important part of the system of a planar rectangular object analysis is the localization: the estimation of projective transform from template image of an object to its photograph. The system also includes such subsystems as the selection and recognition of text fields, the usage of contexts etc. In this paper three localization algorithms are described. All algorithms use feature points and two of them also analyze near-horizontal and near- vertical lines on the photograph. The algorithms and their combinations are tested on a dataset of real document photographs. Also the method of localization quality estimation is proposed that allows configuring the localization subsystem independently of the other subsystems quality.

Face pose tracking using the four-point algorithm

Science.gov (United States)

Fung, Ho Yin; Wong, Kin Hong; Yu, Ying Kin; Tsui, Kwan Pang; Kam, Ho Chuen

2017-06-01

In this paper, we have developed an algorithm to track the pose of a human face robustly and efficiently. Face pose estimation is very useful in many applications such as building virtual reality systems and creating an alternative input method for the disabled. Firstly, we have modified a face detection toolbox called DLib for the detection of a face in front of a camera. The detected face features are passed to a pose estimation method, known as the four-point algorithm, for pose computation. The theory applied and the technical problems encountered during system development are discussed in the paper. It is demonstrated that the system is able to track the pose of a face in real time using a consumer grade laptop computer.

Outdoor Illegal Construction Identification Algorithm Based on 3D Point Cloud Segmentation

Science.gov (United States)

An, Lu; Guo, Baolong

2018-03-01

Recently, various illegal constructions occur significantly in our surroundings, which seriously restrict the orderly development of urban modernization. The 3D point cloud data technology is used to identify the illegal buildings, which could address the problem above effectively. This paper proposes an outdoor illegal construction identification algorithm based on 3D point cloud segmentation. Initially, in order to save memory space and reduce processing time, a lossless point cloud compression method based on minimum spanning tree is proposed. Then, a ground point removing method based on the multi-scale filtering is introduced to increase accuracy. Finally, building clusters on the ground can be obtained using a region growing method, as a result, the illegal construction can be marked. The effectiveness of the proposed algorithm is verified using a publicly data set collected from the International Society for Photogrammetry and Remote Sensing (ISPRS).

Performance Comparison of Widely-Used Maximum Power Point Tracker Algorithms under Real Environmental Conditions

Directory of Open Access Journals (Sweden)

DURUSU, A.

2014-08-01

Full Text Available Maximum power point trackers (MPPTs play an essential role in extracting power from photovoltaic (PV panels as they make the solar panels to operate at the maximum power point (MPP whatever the changes of environmental conditions are. For this reason, they take an important place in the increase of PV system efficiency. MPPTs are driven by MPPT algorithms and a number of MPPT algorithms are proposed in the literature. The comparison of the MPPT algorithms in literature are made by a sun simulator based test system under laboratory conditions for short durations. However, in this study, the performances of four most commonly used MPPT algorithms are compared under real environmental conditions for longer periods. A dual identical experimental setup is designed to make a comparison between two the considered MPPT algorithms as synchronized. As a result of this study, the ranking among these algorithms are presented and the results show that Incremental Conductance (IC algorithm gives the best performance.

Determination of point of maximum likelihood in failure domain using genetic algorithms

International Nuclear Information System (INIS)

Obadage, A.S.; Harnpornchai, N.

2006-01-01

The point of maximum likelihood in a failure domain yields the highest value of the probability density function in the failure domain. The maximum-likelihood point thus represents the worst combination of random variables that contribute in the failure event. In this work Genetic Algorithms (GAs) with an adaptive penalty scheme have been proposed as a tool for the determination of the maximum likelihood point. The utilization of only numerical values in the GAs operation makes the algorithms applicable to cases of non-linear and implicit single and multiple limit state function(s). The algorithmic simplicity readily extends its application to higher dimensional problems. When combined with Monte Carlo Simulation, the proposed methodology will reduce the computational complexity and at the same time will enhance the possibility in rare-event analysis under limited computational resources. Since, there is no approximation done in the procedure, the solution obtained is considered accurate. Consequently, GAs can be used as a tool for increasing the computational efficiency in the element and system reliability analyses

Generic primal-dual interior point methods based on a new kernel function

NARCIS (Netherlands)

EL Ghami, M.; Roos, C.

2008-01-01

In this paper we present a generic primal-dual interior point methods (IPMs) for linear optimization in which the search direction depends on a univariate kernel function which is also used as proximity measure in the analysis of the algorithm. The proposed kernel function does not satisfy all the

Optimization of dynamic economic dispatch with valve-point effect using chaotic sequence based differential evolution algorithms

International Nuclear Information System (INIS)

He Dakuo; Dong Gang; Wang Fuli; Mao Zhizhong

2011-01-01

A chaotic sequence based differential evolution (DE) approach for solving the dynamic economic dispatch problem (DEDP) with valve-point effect is presented in this paper. The proposed method combines the DE algorithm with the local search technique to improve the performance of the algorithm. DE is the main optimizer, while an approximated model for local search is applied to fine tune in the solution of the DE run. To accelerate convergence of DE, a series of constraints handling rules are adopted. An initial population obtained by using chaotic sequence exerts optimal performance of the proposed algorithm. The combined algorithm is validated for two test systems consisting of 10 and 13 thermal units whose incremental fuel cost function takes into account the valve-point loading effects. The proposed combined method outperforms other algorithms reported in literatures for DEDP considering valve-point effects.

Autonomous vision-based navigation for proximity operations around binary asteroids

Science.gov (United States)

Gil-Fernandez, Jesus; Ortega-Hernando, Guillermo

2018-06-01

Future missions to small bodies demand higher level of autonomy in the Guidance, Navigation and Control system for higher scientific return and lower operational costs. Different navigation strategies have been assessed for ESA's asteroid impact mission (AIM). The main objective of AIM is the detailed characterization of binary asteroid Didymos. The trajectories for the proximity operations shall be intrinsically safe, i.e., no collision in presence of failures (e.g., spacecraft entering safe mode), perturbations (e.g., non-spherical gravity field), and errors (e.g., maneuver execution error). Hyperbolic arcs with sufficient hyperbolic excess velocity are designed to fulfil the safety, scientific, and operational requirements. The trajectory relative to the asteroid is determined using visual camera images. The ground-based trajectory prediction error at some points is comparable to the camera Field Of View (FOV). Therefore, some images do not contain the entire asteroid. Autonomous navigation can update the state of the spacecraft relative to the asteroid at higher frequency. The objective of the autonomous navigation is to improve the on-board knowledge compared to the ground prediction. The algorithms shall fit in off-the-shelf, space-qualified avionics. This note presents suitable image processing and relative-state filter algorithms for autonomous navigation in proximity operations around binary asteroids.

Proximity functions for general right cylinders

International Nuclear Information System (INIS)

Kellerer, A.M.

1981-01-01

Distributions of distances between pairs of points within geometrical objects, or the closely related proximity functions and geometric reduction factors, have applications to dosimetric and microdosimetric calculations. For convex bodies these functions are linked to the chord-length distributions that result from random intersections by straight lines. A synopsis of the most important relations is given. The proximity functions and related functions are derived for right cylinders with arbitrary cross sections. The solution utilizes the fact that the squares of the distances between two random points are sums of independently distributed squares of distances parallel and perpendicular to the axis of the cylinder. Analogous formulas are derived for the proximity functions or geometric reduction factors for a cylinder relative to a point. This requires only a minor modification of the solution

A Flexible VHDL Floating Point Module for Control Algorithm Implementation in Space Applications

Science.gov (United States)

Padierna, A.; Nicoleau, C.; Sanchez, J.; Hidalgo, I.; Elvira, S.

2012-08-01

The implementation of control loops for space applications is an area with great potential. However, the characteristics of this kind of systems, such as its wide dynamic range of numeric values, make inadequate the use of fixed-point algorithms.However, because the generic chips available for the treatment of floating point data are, in general, not qualified to operate in space environments and the possibility of using an IP module in a FPGA/ASIC qualified for space is not viable due to the low amount of logic cells available for these type of devices, it is necessary to find a viable alternative.For these reasons, in this paper a VHDL Floating Point Module is presented. This proposal allows the design and execution of floating point algorithms with acceptable occupancy to be implemented in FPGAs/ASICs qualified for space environments.

Improvement of maximum power point tracking perturb and observe algorithm for a standalone solar photovoltaic system

International Nuclear Information System (INIS)

Awan, M.M.A.; Awan, F.G.

2017-01-01

Extraction of maximum power from PV (Photovoltaic) cell is necessary to make the PV system efficient. Maximum power can be achieved by operating the system at MPP (Maximum Power Point) (taking the operating point of PV panel to MPP) and for this purpose MPPT (Maximum Power Point Trackers) are used. There are many tracking algorithms/methods used by these trackers which includes incremental conductance, constant voltage method, constant current method, short circuit current method, PAO (Perturb and Observe) method, and open circuit voltage method but PAO is the mostly used algorithm because it is simple and easy to implement. PAO algorithm has some drawbacks, one is low tracking speed under rapid changing weather conditions and second is oscillations of PV systems operating point around MPP. Little improvement is achieved in past papers regarding these issues. In this paper, a new method named 'Decrease and Fix' method is successfully introduced as improvement in PAO algorithm to overcome these issues of tracking speed and oscillations. Decrease and fix method is the first successful attempt with PAO algorithm for stability achievement and speeding up of tracking process in photovoltaic system. Complete standalone photovoltaic system's model with improved perturb and observe algorithm is simulated in MATLAB Simulink. (author)

A 3D Printing Model Watermarking Algorithm Based on 3D Slicing and Feature Points

Directory of Open Access Journals (Sweden)

Giao N. Pham

2018-02-01

Full Text Available With the increase of three-dimensional (3D printing applications in many areas of life, a large amount of 3D printing data is copied, shared, and used several times without any permission from the original providers. Therefore, copyright protection and ownership identification for 3D printing data in communications or commercial transactions are practical issues. This paper presents a novel watermarking algorithm for 3D printing models based on embedding watermark data into the feature points of a 3D printing model. Feature points are determined and computed by the 3D slicing process along the Z axis of a 3D printing model. The watermark data is embedded into a feature point of a 3D printing model by changing the vector length of the feature point in OXY space based on the reference length. The x and y coordinates of the feature point will be then changed according to the changed vector length that has been embedded with a watermark. Experimental results verified that the proposed algorithm is invisible and robust to geometric attacks, such as rotation, scaling, and translation. The proposed algorithm provides a better method than the conventional works, and the accuracy of the proposed algorithm is much higher than previous methods.

A modified Symbiotic Organisms Search algorithm for large scale economic dispatch problem with valve-point effects

International Nuclear Information System (INIS)

Secui, Dinu Calin

2016-01-01

This paper proposes a new metaheuristic algorithm, called Modified Symbiotic Organisms Search (MSOS) algorithm, to solve the economic dispatch problem considering the valve-point effects, the prohibited operating zones (POZ), the transmission line losses, multi-fuel sources, as well as other operating constraints of the generating units and power system. The MSOS algorithm introduces, in all of its phases, new relations to update the solutions to improve its capacity of identifying stable and of high-quality solutions in a reasonable time. Furthermore, to increase the capacity of exploring the MSOS algorithm in finding the most promising zones, it is endowed with a chaotic component generated by the Logistic map. The performance of the modified algorithm and of the original algorithm Symbiotic Organisms Search (SOS) is tested on five systems of different characteristics, constraints and dimensions (13-unit, 40-unit, 80-unit, 160-unit and 320-unit). The results obtained by applying the proposed algorithm (MSOS) show that this has a better performance than other techniques of optimization recently used in solving the economic dispatch problem with valve-point effects. - Highlights: • A new modified SOS algorithm (MSOS) is proposed to solve the EcD problem. • Valve-point effects, ramp-rate limits, POZ, multi-fuel sources, transmission losses were considered. • The algorithm is tested on five systems having 13, 40, 80, 160 and 320 thermal units. • MSOS algorithm outperforms many other optimization techniques.

A deterministic algorithm for fitting a step function to a weighted point-set

KAUST Repository

Fournier, Hervé ; Vigneron, Antoine E.

2013-01-01

Given a set of n points in the plane, each point having a positive weight, and an integer k>0, we present an optimal O(nlogn)-time deterministic algorithm to compute a step function with k steps that minimizes the maximum weighted vertical distance

A fully automated algorithm of baseline correction based on wavelet feature points and segment interpolation

Science.gov (United States)

Qian, Fang; Wu, Yihui; Hao, Peng

2017-11-01

Baseline correction is a very important part of pre-processing. Baseline in the spectrum signal can induce uneven amplitude shifts across different wavenumbers and lead to bad results. Therefore, these amplitude shifts should be compensated before further analysis. Many algorithms are used to remove baseline, however fully automated baseline correction is convenient in practical application. A fully automated algorithm based on wavelet feature points and segment interpolation (AWFPSI) is proposed. This algorithm finds feature points through continuous wavelet transformation and estimates baseline through segment interpolation. AWFPSI is compared with three commonly introduced fully automated and semi-automated algorithms, using simulated spectrum signal, visible spectrum signal and Raman spectrum signal. The results show that AWFPSI gives better accuracy and has the advantage of easy use.

Correlation Wave-Front Sensing Algorithms for Shack-Hartmann-Based Adaptive Optics using a Point Source

International Nuclear Information System (INIS)

Poynee, L A

2003-01-01

Shack-Hartmann based Adaptive Optics system with a point-source reference normally use a wave-front sensing algorithm that estimates the centroid (center of mass) of the point-source image 'spot' to determine the wave-front slope. The centroiding algorithm suffers for several weaknesses. For a small number of pixels, the algorithm gain is dependent on spot size. The use of many pixels on the detector leads to significant propagation of read noise. Finally, background light or spot halo aberrations can skew results. In this paper an alternative algorithm that suffers from none of these problems is proposed: correlation of the spot with a ideal reference spot. The correlation method is derived and a theoretical analysis evaluates its performance in comparison with centroiding. Both simulation and data from real AO systems are used to illustrate the results. The correlation algorithm is more robust than centroiding, but requires more computation

Preconditioned alternating projection algorithms for maximum a posteriori ECT reconstruction

International Nuclear Information System (INIS)

Krol, Andrzej; Li, Si; Shen, Lixin; Xu, Yuesheng

2012-01-01

We propose a preconditioned alternating projection algorithm (PAPA) for solving the maximum a posteriori (MAP) emission computed tomography (ECT) reconstruction problem. Specifically, we formulate the reconstruction problem as a constrained convex optimization problem with the total variation (TV) regularization. We then characterize the solution of the constrained convex optimization problem and show that it satisfies a system of fixed-point equations defined in terms of two proximity operators raised from the convex functions that define the TV-norm and the constraint involved in the problem. The characterization (of the solution) via the proximity operators that define two projection operators naturally leads to an alternating projection algorithm for finding the solution. For efficient numerical computation, we introduce to the alternating projection algorithm a preconditioning matrix (the EM-preconditioner) for the dense system matrix involved in the optimization problem. We prove theoretically convergence of the PAPA. In numerical experiments, performance of our algorithms, with an appropriately selected preconditioning matrix, is compared with performance of the conventional MAP expectation-maximization (MAP-EM) algorithm with TV regularizer (EM-TV) and that of the recently developed nested EM-TV algorithm for ECT reconstruction. Based on the numerical experiments performed in this work, we observe that the alternating projection algorithm with the EM-preconditioner outperforms significantly the EM-TV in all aspects including the convergence speed, the noise in the reconstructed images and the image quality. It also outperforms the nested EM-TV in the convergence speed while providing comparable image quality. (paper)

LiveWire interactive boundary extraction algorithm based on Haar wavelet transform and control point set direction search

Science.gov (United States)

Cheng, Jun; Zhang, Jun; Tian, Jinwen

2015-12-01

Based on deep analysis of the LiveWire interactive boundary extraction algorithm, a new algorithm focusing on improving the speed of LiveWire algorithm is proposed in this paper. Firstly, the Haar wavelet transform is carried on the input image, and the boundary is extracted on the low resolution image obtained by the wavelet transform of the input image. Secondly, calculating LiveWire shortest path is based on the control point set direction search by utilizing the spatial relationship between the two control points users provide in real time. Thirdly, the search order of the adjacent points of the starting node is set in advance. An ordinary queue instead of a priority queue is taken as the storage pool of the points when optimizing their shortest path value, thus reducing the complexity of the algorithm from O[n2] to O[n]. Finally, A region iterative backward projection method based on neighborhood pixel polling has been used to convert dual-pixel boundary of the reconstructed image to single-pixel boundary after Haar wavelet inverse transform. The algorithm proposed in this paper combines the advantage of the Haar wavelet transform and the advantage of the optimal path searching method based on control point set direction search. The former has fast speed of image decomposition and reconstruction and is more consistent with the texture features of the image and the latter can reduce the time complexity of the original algorithm. So that the algorithm can improve the speed in interactive boundary extraction as well as reflect the boundary information of the image more comprehensively. All methods mentioned above have a big role in improving the execution efficiency and the robustness of the algorithm.

The algorithm to generate color point-cloud with the registration between panoramic image and laser point-cloud

International Nuclear Information System (INIS)

Zeng, Fanyang; Zhong, Ruofei

2014-01-01

Laser point cloud contains only intensity information and it is necessary for visual interpretation to obtain color information from other sensor. Cameras can provide texture, color, and other information of the corresponding object. Points with color information of corresponding pixels in digital images can be used to generate color point-cloud and is conducive to the visualization, classification and modeling of point-cloud. Different types of digital cameras are used in different Mobile Measurement Systems (MMS).the principles and processes for generating color point-cloud in different systems are not the same. The most prominent feature of the panoramic images is the field of 360 degrees view angle in the horizontal direction, to obtain the image information around the camera as much as possible. In this paper, we introduce a method to generate color point-cloud with panoramic image and laser point-cloud, and deduce the equation of the correspondence between points in panoramic images and laser point-clouds. The fusion of panoramic image and laser point-cloud is according to the collinear principle of three points (the center of the omnidirectional multi-camera system, the image point on the sphere, the object point). The experimental results show that the proposed algorithm and formulae in this paper are correct

A Review of Point-Wise Motion Tracking Algorithms for Fetal Magnetic Resonance Imaging.

Science.gov (United States)

Chikop, Shivaprasad; Koulagi, Girish; Kumbara, Ankita; Geethanath, Sairam

2016-01-01

We review recent feature-based tracking algorithms as applied to fetal magnetic resonance imaging (MRI). Motion in fetal MRI is an active and challenging area of research, but the challenge can be mitigated by strategies related to patient setup, acquisition, reconstruction, and image processing. We focus on fetal motion correction through methods based on tracking algorithms for registration of slices with similar anatomy in multiple volumes. We describe five motion detection algorithms based on corner detection and region-based methods through pseudocodes, illustrating the results of their application to fetal MRI. We compare the performance of these methods on the basis of error in registration and minimum number of feature points required for registration. Harris, a corner detection method, provides similar error when compared to the other methods and has the lowest number of feature points required at that error level. We do not discuss group-wise methods here. Finally, we attempt to communicate the application of available feature extraction methods to fetal MRI.

Inexact proximal Newton methods for self-concordant functions

DEFF Research Database (Denmark)

Li, Jinchao; Andersen, Martin Skovgaard; Vandenberghe, Lieven

2016-01-01

with an application to L1-regularized covariance selection, in which prior constraints on the sparsity pattern of the inverse covariance matrix are imposed. In the numerical experiments the proximal Newton steps are computed by an accelerated proximal gradient method, and multifrontal algorithms for positive definite...... matrices with chordal sparsity patterns are used to evaluate gradients and matrix-vector products with the Hessian of the smooth component of the objective....

New algorithm using only one variable measurement applied to a maximum power point tracker

Energy Technology Data Exchange (ETDEWEB)

Salas, V.; Olias, E.; Lazaro, A.; Barrado, A. [University Carlos III de Madrid (Spain). Dept. of Electronic Technology

2005-05-01

A novel algorithm for seeking the maximum power point of a photovoltaic (PV) array for any temperature and solar irradiation level, needing only the PV current value, is proposed. Satisfactory theoretical and experimental results are presented and were obtained when the algorithm was included on a 100 W 24 V PV buck converter prototype, using an inexpensive microcontroller. The load of the system used was a battery and a resistance. The main advantage of this new maximum power point tracking (MPPT), when is compared with others, is that it only uses the measurement of the photovoltaic current, I{sub PV}. (author)

Correction of Misclassifications Using a Proximity-Based Estimation Method

Directory of Open Access Journals (Sweden)

Shmulevich Ilya

2004-01-01

Full Text Available An estimation method for correcting misclassifications in signal and image processing is presented. The method is based on the use of context-based (temporal or spatial information in a sliding-window fashion. The classes can be purely nominal, that is, an ordering of the classes is not required. The method employs nonlinear operations based on class proximities defined by a proximity matrix. Two case studies are presented. In the first, the proposed method is applied to one-dimensional signals for processing data that are obtained by a musical key-finding algorithm. In the second, the estimation method is applied to two-dimensional signals for correction of misclassifications in images. In the first case study, the proximity matrix employed by the estimation method follows directly from music perception studies, whereas in the second case study, the optimal proximity matrix is obtained with genetic algorithms as the learning rule in a training-based optimization framework. Simulation results are presented in both case studies and the degree of improvement in classification accuracy that is obtained by the proposed method is assessed statistically using Kappa analysis.

Optimization Algorithms for Calculation of the Joint Design Point in Parallel Systems

DEFF Research Database (Denmark)

Enevoldsen, I.; Sørensen, John Dalsgaard

1992-01-01

In large structures it is often necessary to estimate the reliability of the system by use of parallel systems. Optimality criteria-based algorithms for calculation of the joint design point in a parallel system are described and efficient active set strategies are developed. Three possible...

Space Network Time Distribution and Synchronization Protocol Development for Mars Proximity Link

Science.gov (United States)

Woo, Simon S.; Gao, Jay L.; Mills, David

2010-01-01

Time distribution and synchronization in deep space network are challenging due to long propagation delays, spacecraft movements, and relativistic effects. Further, the Network Time Protocol (NTP) designed for terrestrial networks may not work properly in space. In this work, we consider the time distribution protocol based on time message exchanges similar to Network Time Protocol (NTP). We present the Proximity-1 Space Link Interleaved Time Synchronization (PITS) algorithm that can work with the CCSDS Proximity-1 Space Data Link Protocol. The PITS algorithm provides faster time synchronization via two-way time transfer over proximity links, improves scalability as the number of spacecraft increase, lowers storage space requirement for collecting time samples, and is robust against packet loss and duplication which underlying protocol mechanisms provide.

Distributed Solutions for Loosely Coupled Feasibility Problems Using Proximal Splitting Methods

DEFF Research Database (Denmark)

Pakazad, Sina Khoshfetrat; Andersen, Martin Skovgaard; Hansson, Anders

2014-01-01

In this paper,we consider convex feasibility problems (CFPs) where the underlying sets are loosely coupled, and we propose several algorithms to solve such problems in a distributed manner. These algorithms are obtained by applying proximal splitting methods to convex minimization reformulations ...

Using the Chandra Source-Finding Algorithm to Automatically Identify Solar X-ray Bright Points

Science.gov (United States)

Adams, Mitzi L.; Tennant, A.; Cirtain, J. M.

2009-01-01

This poster details a technique of bright point identification that is used to find sources in Chandra X-ray data. The algorithm, part of a program called LEXTRCT, searches for regions of a given size that are above a minimum signal to noise ratio. The algorithm allows selected pixels to be excluded from the source-finding, thus allowing exclusion of saturated pixels (from flares and/or active regions). For Chandra data the noise is determined by photon counting statistics, whereas solar telescopes typically integrate a flux. Thus the calculated signal-to-noise ratio is incorrect, but we find we can scale the number to get reasonable results. For example, Nakakubo and Hara (1998) find 297 bright points in a September 11, 1996 Yohkoh image; with judicious selection of signal-to-noise ratio, our algorithm finds 300 sources. To further assess the efficacy of the algorithm, we analyze a SOHO/EIT image (195 Angstroms) and compare results with those published in the literature (McIntosh and Gurman, 2005). Finally, we analyze three sets of data from Hinode, representing different parts of the decline to minimum of the solar cycle.

An Improvement of a Fuzzy Logic-Controlled Maximum Power Point Tracking Algorithm for Photovoltic Applications

Directory of Open Access Journals (Sweden)

Woonki Na

2017-03-01

Full Text Available This paper presents an improved maximum power point tracking (MPPT algorithm using a fuzzy logic controller (FLC in order to extract potential maximum power from photovoltaic cells. The objectives of the proposed algorithm are to improve the tracking speed, and to simultaneously solve the inherent drawbacks such as slow tracking in the conventional perturb and observe (P and O algorithm. The performances of the conventional P and O algorithm and the proposed algorithm are compared by using MATLAB/Simulink in terms of the tracking speed and steady-state oscillations. Additionally, both algorithms were experimentally validated through a digital signal processor (DSP-based controlled-boost DC-DC converter. The experimental results show that the proposed algorithm performs with a shorter tracking time, smaller output power oscillation, and higher efficiency, compared with the conventional P and O algorithm.

Distributed Autonomous Control of Multiple Spacecraft During Close Proximity Operations

National Research Council Canada - National Science Library

McCamish, Shawn B

2007-01-01

This research contributes to multiple spacecraft control by developing an autonomous distributed control algorithm for close proximity operations of multiple spacecraft systems, including rendezvous...

Quad-Rotor Helicopter Autonomous Navigation Based on Vanishing Point Algorithm

Directory of Open Access Journals (Sweden)

Jialiang Wang

2014-01-01

Full Text Available Quad-rotor helicopter is becoming popular increasingly as they can well implement many flight missions in more challenging environments, with lower risk of damaging itself and its surroundings. They are employed in many applications, from military operations to civilian tasks. Quad-rotor helicopter autonomous navigation based on the vanishing point fast estimation (VPFE algorithm using clustering principle is implemented in this paper. For images collected by the camera of quad-rotor helicopter, the system executes the process of preprocessing of image, deleting noise interference, edge extracting using Canny operator, and extracting straight lines by randomized hough transformation (RHT method. Then system obtains the position of vanishing point and regards it as destination point and finally controls the autonomous navigation of the quad-rotor helicopter by continuous modification according to the calculated navigation error. The experimental results show that the quad-rotor helicopter can implement the destination navigation well in the indoor environment.

A GLOBAL REGISTRATION ALGORITHM OF THE SINGLE-CLOSED RING MULTI-STATIONS POINT CLOUD

Directory of Open Access Journals (Sweden)

R. Yang

2018-04-01

Full Text Available Aimed at the global registration problem of the single-closed ring multi-stations point cloud, a formula in order to calculate the error of rotation matrix was constructed according to the definition of error. The global registration algorithm of multi-station point cloud was derived to minimize the error of rotation matrix. And fast-computing formulas of transformation matrix with whose implementation steps and simulation experiment scheme was given. Compared three different processing schemes of multi-station point cloud, the experimental results showed that the effectiveness of the new global registration method was verified, and it could effectively complete the global registration of point cloud.

Study on characteristic points of boiling curve by using wavelet analysis and genetic algorithm

International Nuclear Information System (INIS)

Wei Huiming; Su Guanghui; Qiu Suizheng; Yang Xingbo

2009-01-01

Based on the wavelet analysis theory of signal singularity detection,the critical heat flux (CHF) and minimum film boiling starting point (q min ) of boiling curves can be detected and analyzed by using the wavelet multi-resolution analysis. To predict the CHF in engineering, empirical relations were obtained based on genetic algorithm. The results of wavelet detection and genetic algorithm prediction are consistent with experimental data very well. (authors)

A maximum power point tracking algorithm for photovoltaic applications

Science.gov (United States)

Nelatury, Sudarshan R.; Gray, Robert

2013-05-01

The voltage and current characteristic of a photovoltaic (PV) cell is highly nonlinear and operating a PV cell for maximum power transfer has been a challenge for a long time. Several techniques have been proposed to estimate and track the maximum power point (MPP) in order to improve the overall efficiency of a PV panel. A strategic use of the mean value theorem permits obtaining an analytical expression for a point that lies in a close neighborhood of the true MPP. But hitherto, an exact solution in closed form for the MPP is not published. This problem can be formulated analytically as a constrained optimization, which can be solved using the Lagrange method. This method results in a system of simultaneous nonlinear equations. Solving them directly is quite difficult. However, we can employ a recursive algorithm to yield a reasonably good solution. In graphical terms, suppose the voltage current characteristic and the constant power contours are plotted on the same voltage current plane, the point of tangency between the device characteristic and the constant power contours is the sought for MPP. It is subject to change with the incident irradiation and temperature and hence the algorithm that attempts to maintain the MPP should be adaptive in nature and is supposed to have fast convergence and the least misadjustment. There are two parts in its implementation. First, one needs to estimate the MPP. The second task is to have a DC-DC converter to match the given load to the MPP thus obtained. Availability of power electronics circuits made it possible to design efficient converters. In this paper although we do not show the results from a real circuit, we use MATLAB to obtain the MPP and a buck-boost converter to match the load. Under varying conditions of load resistance and irradiance we demonstrate MPP tracking in case of a commercially available solar panel MSX-60. The power electronics circuit is simulated by PSIM software.

A Numerical Algorithm for Solving a Four-Point Nonlinear Fractional Integro-Differential Equations

Directory of Open Access Journals (Sweden)

Er Gao

2012-01-01

Full Text Available We provide a new algorithm for a four-point nonlocal boundary value problem of nonlinear integro-differential equations of fractional order q∈(1,2] based on reproducing kernel space method. According to our work, the analytical solution of the equations is represented in the reproducing kernel space which we construct and so the n-term approximation. At the same time, the n-term approximation is proved to converge to the analytical solution. An illustrative example is also presented, which shows that the new algorithm is efficient and accurate.

A Homogeneous and Self-Dual Interior-Point Linear Programming Algorithm for Economic Model Predictive Control

DEFF Research Database (Denmark)

Sokoler, Leo Emil; Frison, Gianluca; Skajaa, Anders

2015-01-01

We develop an efficient homogeneous and self-dual interior-point method (IPM) for the linear programs arising in economic model predictive control of constrained linear systems with linear objective functions. The algorithm is based on a Riccati iteration procedure, which is adapted to the linear...... system of equations solved in homogeneous and self-dual IPMs. Fast convergence is further achieved using a warm-start strategy. We implement the algorithm in MATLAB and C. Its performance is tested using a conceptual power management case study. Closed loop simulations show that 1) the proposed algorithm...

Application of Deconvolution Algorithm of Point Spread Function in Improving Image Quality: An Observer Preference Study on Chest Radiography.

Science.gov (United States)

Chae, Kum Ju; Goo, Jin Mo; Ahn, Su Yeon; Yoo, Jin Young; Yoon, Soon Ho

2018-01-01

To evaluate the preference of observers for image quality of chest radiography using the deconvolution algorithm of point spread function (PSF) (TRUVIEW ART algorithm, DRTECH Corp.) compared with that of original chest radiography for visualization of anatomic regions of the chest. Prospectively enrolled 50 pairs of posteroanterior chest radiographs collected with standard protocol and with additional TRUVIEW ART algorithm were compared by four chest radiologists. This algorithm corrects scattered signals generated by a scintillator. Readers independently evaluated the visibility of 10 anatomical regions and overall image quality with a 5-point scale of preference. The significance of the differences in reader's preference was tested with a Wilcoxon's signed rank test. All four readers preferred the images applied with the algorithm to those without algorithm for all 10 anatomical regions (mean, 3.6; range, 3.2-4.0; p chest anatomical structures applied with the deconvolution algorithm of PSF was superior to the original chest radiography.

Mathematical representation of the normal proximal human femur: application in planning of cam hip surgery.

Science.gov (United States)

Masjedi, Milad; Harris, Simon J; Davda, Kinner; Cobb, Justin P

2013-04-01

Precise modelling of the proximal femur can be used for detecting and planning corrective surgery for subjects with deformed femurs using robotic technology or navigation systems. In this study, the proximal femoral geometry has been modelled mathematically. It is hypothesised that it is possible to fit a quadratic surface or combinations of them onto different bone surfaces with a relatively good fit. Forty-six computed tomography datasets of normal proximal femora were segmented. A least-squares fitting algorithm was used to fit a quadratic surface on the femoral head and neck such that the sum of distances between a set of points on the femoral neck and the quadratic surface was minimised. Furthermore, the position of the head-neck articular margin was also measured. The femoral neck was found to be represented as a good fit to a hyperboloid with an average root mean-squared error of 1.0 ± 0.13 mm while the shape of the femoral articular margin was a reproducible sinusoidal wave form with two peaks. The mathematical description in this study can be used for planning corrective surgery for subjects with cam-type femoroacetabular impingement.

An Approximate Proximal Bundle Method to Minimize a Class of Maximum Eigenvalue Functions

Directory of Open Access Journals (Sweden)

Wei Wang

2014-01-01

Full Text Available We present an approximate nonsmooth algorithm to solve a minimization problem, in which the objective function is the sum of a maximum eigenvalue function of matrices and a convex function. The essential idea to solve the optimization problem in this paper is similar to the thought of proximal bundle method, but the difference is that we choose approximate subgradient and function value to construct approximate cutting-plane model to solve the above mentioned problem. An important advantage of the approximate cutting-plane model for objective function is that it is more stable than cutting-plane model. In addition, the approximate proximal bundle method algorithm can be given. Furthermore, the sequences generated by the algorithm converge to the optimal solution of the original problem.

Building optimal regression tree by ant colony system-genetic algorithm: Application to modeling of melting points

Energy Technology Data Exchange (ETDEWEB)

Hemmateenejad, Bahram, E-mail: hemmatb@sums.ac.ir [Department of Chemistry, Shiraz University, Shiraz (Iran, Islamic Republic of); Medicinal and Natural Products Chemistry Research Center, Shiraz University of Medical Sciences, Shiraz (Iran, Islamic Republic of); Shamsipur, Mojtaba [Department of Chemistry, Razi University, Kermanshah (Iran, Islamic Republic of); Zare-Shahabadi, Vali [Young Researchers Club, Mahshahr Branch, Islamic Azad University, Mahshahr (Iran, Islamic Republic of); Akhond, Morteza [Department of Chemistry, Shiraz University, Shiraz (Iran, Islamic Republic of)

2011-10-17

Highlights: {yields} Ant colony systems help to build optimum classification and regression trees. {yields} Using of genetic algorithm operators in ant colony systems resulted in more appropriate models. {yields} Variable selection in each terminal node of the tree gives promising results. {yields} CART-ACS-GA could model the melting point of organic materials with prediction errors lower than previous models. - Abstract: The classification and regression trees (CART) possess the advantage of being able to handle large data sets and yield readily interpretable models. A conventional method of building a regression tree is recursive partitioning, which results in a good but not optimal tree. Ant colony system (ACS), which is a meta-heuristic algorithm and derived from the observation of real ants, can be used to overcome this problem. The purpose of this study was to explore the use of CART and its combination with ACS for modeling of melting points of a large variety of chemical compounds. Genetic algorithm (GA) operators (e.g., cross averring and mutation operators) were combined with ACS algorithm to select the best solution model. In addition, at each terminal node of the resulted tree, variable selection was done by ACS-GA algorithm to build an appropriate partial least squares (PLS) model. To test the ability of the resulted tree, a set of approximately 4173 structures and their melting points were used (3000 compounds as training set and 1173 as validation set). Further, an external test set containing of 277 drugs was used to validate the prediction ability of the tree. Comparison of the results obtained from both trees showed that the tree constructed by ACS-GA algorithm performs better than that produced by recursive partitioning procedure.

Topology of digital images visual pattern discovery in proximity spaces

CERN Document Server

Peters, James F

2014-01-01

This book carries forward recent work on visual patterns and structures in digital images and introduces a near set-based a topology of digital images. Visual patterns arise naturally in digital images viewed as sets of non-abstract points endowed with some form of proximity (nearness) relation. Proximity relations make it possible to construct uniform topolo- gies on the sets of points that constitute a digital image. In keeping with an interest in gaining an understanding of digital images themselves as a rich source of patterns, this book introduces the basics of digital images from a computer vision perspective. In parallel with a computer vision perspective on digital images, this book also introduces the basics of prox- imity spaces. Not only the traditional view of spatial proximity relations but also the more recent descriptive proximity relations are considered. The beauty of the descriptive proximity approach is that it is possible to discover visual set patterns among sets that are non-overlapping ...

The collapsed cone algorithm for (192)Ir dosimetry using phantom-size adaptive multiple-scatter point kernels.

Science.gov (United States)

Tedgren, Åsa Carlsson; Plamondon, Mathieu; Beaulieu, Luc

2015-07-07

The aim of this work was to investigate how dose distributions calculated with the collapsed cone (CC) algorithm depend on the size of the water phantom used in deriving the point kernel for multiple scatter. A research version of the CC algorithm equipped with a set of selectable point kernels for multiple-scatter dose that had initially been derived in water phantoms of various dimensions was used. The new point kernels were generated using EGSnrc in spherical water phantoms of radii 5 cm, 7.5 cm, 10 cm, 15 cm, 20 cm, 30 cm and 50 cm. Dose distributions derived with CC in water phantoms of different dimensions and in a CT-based clinical breast geometry were compared to Monte Carlo (MC) simulations using the Geant4-based brachytherapy specific MC code Algebra. Agreement with MC within 1% was obtained when the dimensions of the phantom used to derive the multiple-scatter kernel were similar to those of the calculation phantom. Doses are overestimated at phantom edges when kernels are derived in larger phantoms and underestimated when derived in smaller phantoms (by around 2% to 7% depending on distance from source and phantom dimensions). CC agrees well with MC in the high dose region of a breast implant and is superior to TG43 in determining skin doses for all multiple-scatter point kernel sizes. Increased agreement between CC and MC is achieved when the point kernel is comparable to breast dimensions. The investigated approximation in multiple scatter dose depends on the choice of point kernel in relation to phantom size and yields a significant fraction of the total dose only at distances of several centimeters from a source/implant which correspond to volumes of low doses. The current implementation of the CC algorithm utilizes a point kernel derived in a comparatively large (radius 20 cm) water phantom. A fixed point kernel leads to predictable behaviour of the algorithm with the worst case being a source/implant located well within a patient

A Simple Checking Algorithm with Perturb and Observe Maximum Power Point Tracking for Partially Shaded Photovoltaic System

Directory of Open Access Journals (Sweden)

Rozana Alik

2016-03-01

Full Text Available This paper presents a simple checking algorithm for maximum power point tracking (MPPT technique for Photovoltaic (PV system using Perturb and Observe (P&O algorithm. The main benefit of this checking algorithm is the simplicity and efficiency of the system whose duty cycle produced by the MPPT is smoother and changes faster according to maximum power point (MPP. This checking algorithm can determine the maximum power first before the P&O algorithm takes place to identify the voltage at MPP (VMPP, which is needed to calculate the duty cycle for the boost converter. To test the effectiveness of the algorithm, a simulation model of PV system has been carried out using MATLAB/Simulink under different level of irradiation; or in other words partially shaded condition of PV array. The results from the system using the proposed approach prove to have faster response and low ripple. Besides, the results are close to the desired outputs and exhibit an approximately 98.25% of the system efficiency. On the other hand, the system with conventional P&O MPPT seems to be unstable and has higher percentage of error. In summary, the proposed method is useful under varying level of irradiation with higher efficiency of the system.

Effects of Varying Epoch Lengths, Wear Time Algorithms, and Activity Cut-Points on Estimates of Child Sedentary Behavior and Physical Activity from Accelerometer Data.

Science.gov (United States)

Banda, Jorge A; Haydel, K Farish; Davila, Tania; Desai, Manisha; Bryson, Susan; Haskell, William L; Matheson, Donna; Robinson, Thomas N

2016-01-01

To examine the effects of accelerometer epoch lengths, wear time (WT) algorithms, and activity cut-points on estimates of WT, sedentary behavior (SB), and physical activity (PA). 268 7-11 year-olds with BMI ≥ 85th percentile for age and sex wore accelerometers on their right hips for 4-7 days. Data were processed and analyzed at epoch lengths of 1-, 5-, 10-, 15-, 30-, and 60-seconds. For each epoch length, WT minutes/day was determined using three common WT algorithms, and minutes/day and percent time spent in SB, light (LPA), moderate (MPA), and vigorous (VPA) PA were determined using five common activity cut-points. ANOVA tested differences in WT, SB, LPA, MPA, VPA, and MVPA when using the different epoch lengths, WT algorithms, and activity cut-points. WT minutes/day varied significantly by epoch length when using the NHANES WT algorithm (p algorithms. Minutes/day and percent time spent in SB, LPA, MPA, VPA, and MVPA varied significantly by epoch length for all sets of activity cut-points tested with all three WT algorithms (all p algorithms (all p algorithms and activity cut-point definitions to match different epoch lengths may introduce significant errors. Estimates of SB and PA from studies that process and analyze data using different epoch lengths, WT algorithms, and/or activity cut-points are not comparable, potentially leading to very different results, interpretations, and conclusions, misleading research and public policy.

Weak and Strong Convergence of an Algorithm for the Split Common Fixed-Point of Asymptotically Quasi-Nonexpansive Operators

Directory of Open Access Journals (Sweden)

Yazheng Dang

2013-01-01

Full Text Available Inspired by the Moudafi (2010, we propose an algorithm for solving the split common fixed-point problem for a wide class of asymptotically quasi-nonexpansive operators and the weak and strong convergence of the algorithm are shown under some suitable conditions in Hilbert spaces. The algorithm and its convergence results improve and develop previous results for split feasibility problems.

MUSIC ALGORITHM FOR LOCATING POINT-LIKE SCATTERERS CONTAINED IN A SAMPLE ON FLAT SUBSTRATE

Institute of Scientific and Technical Information of China (English)

Dong Heping; Ma Fuming; Zhang Deyue

2012-01-01

In this paper,we consider a MUSIC algorithm for locating point-like scatterers contained in a sample on flat substrate.Based on an asymptotic expansion of the scattering amplitude proposed by Ammari et al.,the reconstruction problem can be reduced to a calculation of Green function corresponding to the background medium.In addition,we use an explicit formulation of Green function in the MUSIC algorithm to simplify the calculation when the cross-section of sample is a half-disc.Numerical experiments are included to demonstrate the feasibility of this method.

Interior point algorithms: guaranteed optimality for fluence map optimization in IMRT

Energy Technology Data Exchange (ETDEWEB)

Aleman, Dionne M [Department of Mechanical and Industrial Engineering, University of Toronto, 5 King' s College Road, Toronto, ON M5S 3G8 (Canada); Glaser, Daniel [Division of Optimization and Systems Theory, Department of Mathematics, Royal Institute of Technology, Stockholm (Sweden); Romeijn, H Edwin [Department of Industrial and Operations Engineering, University of Michigan, Ann Arbor, MI 48109-2117 (United States); Dempsey, James F, E-mail: aleman@mie.utoronto.c, E-mail: romeijn@umich.ed, E-mail: jfdempsey@viewray.co [ViewRay, Inc. 2 Thermo Fisher Way, Village of Oakwood, OH 44146 (United States)

2010-09-21

One of the most widely studied problems of the intensity-modulated radiation therapy (IMRT) treatment planning problem is the fluence map optimization (FMO) problem, the problem of determining the amount of radiation intensity, or fluence, of each beamlet in each beam. For a given set of beams, the fluences of the beamlets can drastically affect the quality of the treatment plan, and thus it is critical to obtain good fluence maps for radiation delivery. Although several approaches have been shown to yield good solutions to the FMO problem, these solutions are not guaranteed to be optimal. This shortcoming can be attributed to either optimization model complexity or properties of the algorithms used to solve the optimization model. We present a convex FMO formulation and an interior point algorithm that yields an optimal treatment plan in seconds, making it a viable option for clinical applications.

Interior point algorithms: guaranteed optimality for fluence map optimization in IMRT

International Nuclear Information System (INIS)

Aleman, Dionne M; Glaser, Daniel; Romeijn, H Edwin; Dempsey, James F

2010-01-01

One of the most widely studied problems of the intensity-modulated radiation therapy (IMRT) treatment planning problem is the fluence map optimization (FMO) problem, the problem of determining the amount of radiation intensity, or fluence, of each beamlet in each beam. For a given set of beams, the fluences of the beamlets can drastically affect the quality of the treatment plan, and thus it is critical to obtain good fluence maps for radiation delivery. Although several approaches have been shown to yield good solutions to the FMO problem, these solutions are not guaranteed to be optimal. This shortcoming can be attributed to either optimization model complexity or properties of the algorithms used to solve the optimization model. We present a convex FMO formulation and an interior point algorithm that yields an optimal treatment plan in seconds, making it a viable option for clinical applications.

Implementation of an algorithm for absorbed dose calculation in high energy photon beams at off axis points

International Nuclear Information System (INIS)

Matos, M.F.; Alvarez, G.D.; Sanz, D.E.

2008-01-01

Full text: A semiempirical algorithm for absorbed dose calculation at off-axis points in irregular beams was implemented. It is well known that semiempirical methods are very useful because of their easy implementation and its helpfulness in dose calculation in the clinic. These methods can be used as independent tools for dosimetric calculation in many applications of quality assurance. However, the applicability of such methods has some limitations, even in homogeneous media, specially at off axis points, near beam fringes or outside the beam. Only methods derived from tissue-air-ratio (TAR) or scatter-maximum-ratio (SMR) have been devised for those situations, many years ago. Despite there have been improvements for these manual methods, like the Sc-Sp ones, no attempt has been made to extend their usage at off axis points. In this work, a semiempirical formalism was introduced, based on the works of Venselaar et al. (1999) and Sanz et al. (2004), aimed to the Sc-Sp separation. This new formalism relies on the separation of primary and secondary components of the beam although in a relative way. The data required by the algorithm are reduced to a minimal, allowing for experimental easy. According to modern recommendations, reference measurements in water phantom are performed at 10 cm depth, keeping away electron contamination. Air measurements are done using a mini phantom instead of the old equilibrium caps. Finally, the calculation at off-axis points are done using data measured on the central beam axis; but correcting the results with the introduction of a measured function which depends on the location of the off axis point. The measurements for testing the algorithm were performed in our Siemens MXE linear accelerator. The algorithm was used to determine specific dose profiles for a great number of different beam configurations, and the results were compared with direct measurements to validate the accuracy of the algorithm. Additionally, the results were

A unified framework of descent algorithms for nonlinear programs and variational inequalities

International Nuclear Information System (INIS)

Patriksson, M.

1993-01-01

We present a framework of algorithms for the solution of continuous optimization and variational inequality problems. In the general algorithm, a search direction finding auxiliary problems is obtained by replacing the original cost function with an approximating monotone cost function. The proposed framework encompasses algorithm classes presented earlier by Cohen, Dafermos, Migdalas, and Tseng, and includes numerous descent and successive approximation type methods, such as Newton methods, Jacobi and Gauss-Siedel type decomposition methods for problems defined over Cartesian product sets, and proximal point methods, among others. The auxiliary problem of the general algorithm also induces equivalent optimization reformulation and descent methods for asymmetric variational inequalities. We study the convergence properties of the general algorithm when applied to unconstrained optimization, nondifferentiable optimization, constrained differentiable optimization, and variational inequalities; the emphasis of the convergence analyses is placed on basic convergence results, convergence using different line search strategies and truncated subproblem solutions, and convergence rate results. This analysis offer a unification of known results; moreover, it provides strengthenings of convergence results for many existing algorithms, and indicates possible improvements of their realizations. 482 refs

The female geriatric proximal humeral fracture: protagonist for straight antegrade nailing?

Science.gov (United States)

Lindtner, Richard A; Kralinger, Franz S; Kapferer, Sebastian; Hengg, Clemens; Wambacher, Markus; Euler, Simon A

2017-10-01

Straight antegrade humeral nailing (SAHN) has become a standard technique for the surgical fixation of proximal humeral fractures, which predominantly affect elderly females. The nail's proximal anchoring point has been demonstrated to be critical to ensure reliable fixation in osteoporotic bone and to prevent iatrogenic damage to the superior rotator cuff bony insertion. Anatomical variations of the proximal humerus, however, may preclude satisfactory anchoring of the nail's proximal end and may bare the risk of rotator cuff violation, even though the nail is inserted as recommended. The aim of this study was to evaluate the anatomical suitability of proximal humeri of geriatric females aged 75 years and older for SAHN. Specifically, we sought to assess the proportion of humeri not anatomically amenable to SAHN for proximal humeral fracture. A total of 303 proximal humeri of 241 females aged 75 years and older (mean age 84.5 ± 5.0 years; range 75-102 years) were analyzed for this study. Multiplanar two-dimensional reformations (true ap, true lateral, and axial) were reconstructed from shoulder computed tomography (CT) data sets. The straight antegrade nail's ideal entry point, "critical point" (CP), and critical distance (CD; distance between ideal entry point and CP) were determined. The rate of proximal humeri not anatomically suitable for SAHN (critical type) was assessed regarding proximal reaming diameters of currently available straight antegrade humeral nails. Overall, 35.6% (108/303) of all proximal humeri were found to be "critical types" (CD straight antegrade nails currently in use. Moreover, 43.2% (131/303) of the humeri were considered "critical types" with regard to the alternatively used larger proximal reaming diameter of 11.5 mm. Mean CD was 9.0 ± 1.7 mm (range 3.5-13.5 mm) and did not correlate with age (r = -0.04, P = 0.54). No significant differences in CD and rate of "critical types" were found between left and right humeri

An algorithm to locate optimal bond breaking points on a potential energy surface for applications in mechanochemistry and catalysis.

Science.gov (United States)

Bofill, Josep Maria; Ribas-Ariño, Jordi; García, Sergio Pablo; Quapp, Wolfgang

2017-10-21

The reaction path of a mechanically induced chemical transformation changes under stress. It is well established that the force-induced structural changes of minima and saddle points, i.e., the movement of the stationary points on the original or stress-free potential energy surface, can be described by a Newton Trajectory (NT). Given a reactive molecular system, a well-fitted pulling direction, and a sufficiently large value of the force, the minimum configuration of the reactant and the saddle point configuration of a transition state collapse at a point on the corresponding NT trajectory. This point is called barrier breakdown point or bond breaking point (BBP). The Hessian matrix at the BBP has a zero eigenvector which coincides with the gradient. It indicates which force (both in magnitude and direction) should be applied to the system to induce the reaction in a barrierless process. Within the manifold of BBPs, there exist optimal BBPs which indicate what is the optimal pulling direction and what is the minimal magnitude of the force to be applied for a given mechanochemical transformation. Since these special points are very important in the context of mechanochemistry and catalysis, it is crucial to develop efficient algorithms for their location. Here, we propose a Gauss-Newton algorithm that is based on the minimization of a positively defined function (the so-called σ-function). The behavior and efficiency of the new algorithm are shown for 2D test functions and for a real chemical example.

A Uniform Energy Consumption Algorithm for Wireless Sensor and Actuator Networks Based on Dynamic Polling Point Selection

Science.gov (United States)

Li, Shuo; Peng, Jun; Liu, Weirong; Zhu, Zhengfa; Lin, Kuo-Chi

2014-01-01

Recent research has indicated that using the mobility of the actuator in wireless sensor and actuator networks (WSANs) to achieve mobile data collection can greatly increase the sensor network lifetime. However, mobile data collection may result in unacceptable collection delays in the network if the path of the actuator is too long. Because real-time network applications require meeting data collection delay constraints, planning the path of the actuator is a very important issue to balance the prolongation of the network lifetime and the reduction of the data collection delay. In this paper, a multi-hop routing mobile data collection algorithm is proposed based on dynamic polling point selection with delay constraints to address this issue. The algorithm can actively update the selection of the actuator's polling points according to the sensor nodes' residual energies and their locations while also considering the collection delay constraint. It also dynamically constructs the multi-hop routing trees rooted by these polling points to balance the sensor node energy consumption and the extension of the network lifetime. The effectiveness of the algorithm is validated by simulation. PMID:24451455

Geographical proximity on the valuations of unlisted agrarian companies: Does distance from company to company and to strategic points matter?

Energy Technology Data Exchange (ETDEWEB)

Occhino, P.; Maté, M.

2017-07-01

This paper is a first attempt to examine the role played by the geography on agrarian firms’ valuations. The geography was evaluated through the physical proximity from agrarian companies to other companies and to some strategic points which ease their accessibility to external economic agents. To get our purpose, we developed an empirical application on a sample of non-listed agrarian Spanish companies located in the region of Murcia over the period 2010-2015. We applied Discount Cash Flow methodology for non-listed companies to get their valuations. With this information, we used spatial econometric techniques to analyse the spatial distribution of agrarian firms’ valuations and model the behavior of this variable. Our results supported the assertion that agrarian firms’ valuations are conditioned by the geography. We found that firms with similar valuations tend to be grouped together in the territory. In addition, we found significant effects on agrarian firms valuations derived from the geographical proximity among closer agrarian companies and from them to external agents and transport facilities.

Geographical proximity on the valuations of unlisted agrarian companies: Does distance from company to company and to strategic points matter?

International Nuclear Information System (INIS)

Occhino, P.; Maté, M.

2017-01-01

This paper is a first attempt to examine the role played by the geography on agrarian firms’ valuations. The geography was evaluated through the physical proximity from agrarian companies to other companies and to some strategic points which ease their accessibility to external economic agents. To get our purpose, we developed an empirical application on a sample of non-listed agrarian Spanish companies located in the region of Murcia over the period 2010-2015. We applied Discount Cash Flow methodology for non-listed companies to get their valuations. With this information, we used spatial econometric techniques to analyse the spatial distribution of agrarian firms’ valuations and model the behavior of this variable. Our results supported the assertion that agrarian firms’ valuations are conditioned by the geography. We found that firms with similar valuations tend to be grouped together in the territory. In addition, we found significant effects on agrarian firms valuations derived from the geographical proximity among closer agrarian companies and from them to external agents and transport facilities.

Retinal biometrics based on Iterative Closest Point algorithm.

Science.gov (United States)

Hatanaka, Yuji; Tajima, Mikiya; Kawasaki, Ryo; Saito, Koko; Ogohara, Kazunori; Muramatsu, Chisako; Sunayama, Wataru; Fujita, Hiroshi

2017-07-01

The pattern of blood vessels in the eye is unique to each person because it rarely changes over time. Therefore, it is well known that retinal blood vessels are useful for biometrics. This paper describes a biometrics method using the Jaccard similarity coefficient (JSC) based on blood vessel regions in retinal image pairs. The retinal image pairs were rough matched by the center of their optic discs. Moreover, the image pairs were aligned using the Iterative Closest Point algorithm based on detailed blood vessel skeletons. For registration, perspective transform was applied to the retinal images. Finally, the pairs were classified as either correct or incorrect using the JSC of the blood vessel region in the image pairs. The proposed method was applied to temporal retinal images, which were obtained in 2009 (695 images) and 2013 (87 images). The 87 images acquired in 2013 were all from persons already examined in 2009. The accuracy of the proposed method reached 100%.

A Hybrid Maximum Power Point Tracking Approach for Photovoltaic Systems under Partial Shading Conditions Using a Modified Genetic Algorithm and the Firefly Algorithm

Directory of Open Access Journals (Sweden)

Yu-Pei Huang

2018-01-01

Full Text Available This paper proposes a modified maximum power point tracking (MPPT algorithm for photovoltaic systems under rapidly changing partial shading conditions (PSCs. The proposed algorithm integrates a genetic algorithm (GA and the firefly algorithm (FA and further improves its calculation process via a differential evolution (DE algorithm. The conventional GA is not advisable for MPPT because of its complicated calculations and low accuracy under PSCs. In this study, we simplified the GA calculations with the integration of the DE mutation process and FA attractive process. Results from both the simulation and evaluation verify that the proposed algorithm provides rapid response time and high accuracy due to the simplified processing. For instance, evaluation results demonstrate that when compared to the conventional GA, the execution time and tracking accuracy of the proposed algorithm can be, respectively, improved around 69.4% and 4.16%. In addition, in comparison to FA, the tracking speed and tracking accuracy of the proposed algorithm can be improved around 42.9% and 1.85%, respectively. Consequently, the major improvement of the proposed method when evaluated against the conventional GA and FA is tracking speed. Moreover, this research provides a framework to integrate multiple nature-inspired algorithms for MPPT. Furthermore, the proposed method is adaptable to different types of solar panels and different system formats with specifically designed equations, the advantages of which are rapid tracking speed with high accuracy under PSCs.

Application of point-to-point matching algorithms for background correction in on-line liquid chromatography-Fourier transform infrared spectrometry (LC-FTIR).

Science.gov (United States)

Kuligowski, J; Quintás, G; Garrigues, S; de la Guardia, M

2010-03-15

A new background correction method for the on-line coupling of gradient liquid chromatography and Fourier transform infrared spectrometry has been developed. It is based on the use of a point-to-point matching algorithm that compares the absorption spectra of the sample data set with those of a previously recorded reference data set in order to select an appropriate reference spectrum. The spectral range used for the point-to-point comparison is selected with minimal user-interaction, thus facilitating considerably the application of the whole method. The background correction method has been successfully tested on a chromatographic separation of four nitrophenols running acetonitrile (0.08%, v/v TFA):water (0.08%, v/v TFA) gradients with compositions ranging from 35 to 85% (v/v) acetonitrile, giving accurate results for both, baseline resolved and overlapped peaks. Copyright (c) 2009 Elsevier B.V. All rights reserved.

An Effective, Robust And Parallel Implementation Of An Interior Point Algorithm For Limit State Optimization

DEFF Research Database (Denmark)

Dollerup, Niels; Jepsen, Michael S.; Damkilde, Lars

2013-01-01

The artide describes a robust and effective implementation of the interior point optimization algorithm. The adopted method includes a precalculation step, which reduces the number of variables by fulfilling the equilibrium equations a priori. This work presents an improved implementation of the ...

Evaluation of a photovoltaic energy mechatronics system with a built-in quadratic maximum power point tracking algorithm

Energy Technology Data Exchange (ETDEWEB)

Chao, R.M.; Ko, S.H.; Lin, I.H. [Department of Systems and Naval Mechatronics Engineering, National Cheng Kung University, Tainan, Taiwan 701 (China); Pai, F.S. [Department of Electronic Engineering, National University of Tainan (China); Chang, C.C. [Department of Environment and Energy, National University of Tainan (China)

2009-12-15

The historically high cost of crude oil price is stimulating research into solar (green) energy as an alternative energy source. In general, applications with large solar energy output require a maximum power point tracking (MPPT) algorithm to optimize the power generated by the photovoltaic effect. This work aims to provide a stand-alone solution for solar energy applications by integrating a DC/DC buck converter to a newly developed quadratic MPPT algorithm along with its appropriate software and hardware. The quadratic MPPT method utilizes three previously used duty cycles with their corresponding power outputs. It approaches the maximum value by using a second order polynomial formula, which converges faster than the existing MPPT algorithm. The hardware implementation takes advantage of the real-time controller system from National Instruments, USA. Experimental results have shown that the proposed solar mechatronics system can correctly and effectively track the maximum power point without any difficulties. (author)

Fixed-Point Algorithms for the Blind Separation of Arbitrary Complex-Valued Non-Gaussian Signal Mixtures

Directory of Open Access Journals (Sweden)

Douglas Scott C

2007-01-01

Full Text Available We derive new fixed-point algorithms for the blind separation of complex-valued mixtures of independent, noncircularly symmetric, and non-Gaussian source signals. Leveraging recently developed results on the separability of complex-valued signal mixtures, we systematically construct iterative procedures on a kurtosis-based contrast whose evolutionary characteristics are identical to those of the FastICA algorithm of Hyvarinen and Oja in the real-valued mixture case. Thus, our methods inherit the fast convergence properties, computational simplicity, and ease of use of the FastICA algorithm while at the same time extending this class of techniques to complex signal mixtures. For extracting multiple sources, symmetric and asymmetric signal deflation procedures can be employed. Simulations for both noiseless and noisy mixtures indicate that the proposed algorithms have superior finite-sample performance in data-starved scenarios as compared to existing complex ICA methods while performing about as well as the best of these techniques for larger data-record lengths.

An automatic, stagnation point based algorithm for the delineation of Wellhead Protection Areas

Science.gov (United States)

Tosco, Tiziana; Sethi, Rajandrea; di Molfetta, Antonio

2008-07-01

Time-related capture areas are usually delineated using the backward particle tracking method, releasing circles of equally spaced particles around each well. In this way, an accurate delineation often requires both a very high number of particles and a manual capture zone encirclement. The aim of this work was to propose an Automatic Protection Area (APA) delineation algorithm, which can be coupled with any model of flow and particle tracking. The computational time is here reduced, thanks to the use of a limited number of nonequally spaced particles. The particle starting positions are determined coupling forward particle tracking from the stagnation point, and backward particle tracking from the pumping well. The pathlines are postprocessed for a completely automatic delineation of closed perimeters of time-related capture zones. The APA algorithm was tested for a two-dimensional geometry, in homogeneous and nonhomogeneous aquifers, steady state flow conditions, single and multiple wells. Results show that the APA algorithm is robust and able to automatically and accurately reconstruct protection areas with a very small number of particles, also in complex scenarios.

An improved contour symmetry axes extraction algorithm and its application in the location of picking points of apples

Energy Technology Data Exchange (ETDEWEB)

Wang, D.; Song, H.; Yu, X.; Zhang, W.; Qu, W.; Xu, Y.

2015-07-01

The key problem for picking robots is to locate the picking points of fruit. A method based on the moment of inertia and symmetry of apples is proposed in this paper to locate the picking points of apples. Image pre-processing procedures, which are crucial to improving the accuracy of the location, were carried out to remove noise and smooth the edges of apples. The moment of inertia method has the disadvantage of high computational complexity, which should be solved, so convex hull was used to improve this problem. To verify the validity of this algorithm, a test was conducted using four types of apple images containing 107 apple targets. These images were single and unblocked apple images, single and blocked apple images, images containing adjacent apples, and apples in panoramas. The root mean square error values of these four types of apple images were 6.3, 15.0, 21.6 and 18.4, respectively, and the average location errors were 4.9°, 10.2°, 16.3° and 13.8°, respectively. Furthermore, the improved algorithm was effective in terms of average runtime, with 3.7 ms and 9.2 ms for single and unblocked and single and blocked apple images, respectively. For the other two types of apple images, the runtime was determined by the number of apples and blocked apples contained in the images. The results showed that the improved algorithm could extract symmetry axes and locate the picking points of apples more efficiently. In conclusion, the improved algorithm is feasible for extracting symmetry axes and locating the picking points of apples. (Author)

Proximal caries detection: Sirona Sidexis versus Kodak Ektaspeed Plus.

Science.gov (United States)

Khan, Emad A; Tyndall, Donald A; Ludlow, John B; Caplan, Daniel

2005-01-01

This study compared the accuracy of intraoral film and a charge-coupled device (CCD) receptor for proximal caries detection. Four observers evaluated images of the proximal surfaces of 40 extracted posterior teeth. The presence or absence of caries was scored using a five-point confidence scale. The actual status of each surface was determined from ground section histology. Responses were evaluated by means of receiver operating characteristic (ROC) analysis. Areas under ROC curves (Az) were assessed through a paired t-test. The performance of the CCD-based intraoral sensor was not different statistically from Ektaspeed Plus film in detecting proximal caries.

Inter-proximal enamel reduction in contemporary orthodontics.

Science.gov (United States)

Pindoria, J; Fleming, P S; Sharma, P K

2016-12-16

Inter-proximal enamel reduction has gained increasing prominence in recent years being advocated to provide space for orthodontic alignment, to refine contact points and to potentially improve long-term stability. An array of techniques and products are available ranging from hand-held abrasive strips to handpiece mounted burs and discs. The indications for inter-proximal enamel reduction and the importance of formal space analysis, together with the various techniques and armamentarium which may be used to perform it safely in both the labial and buccal segments are outlined.

A Kind of Single-frequency Precise Point Positioning Algorithm Based on the Raw Observations

Directory of Open Access Journals (Sweden)

WANG Li

2015-01-01

Full Text Available A kind of single-frequency precise point positioning (PPP algorithm based on the raw observations is presented in this paper. By this algorithm, the ionospheric delays were corrected efficiently by means of adding the ionospheric delay prior information and the virtual observation equations with the spatial and temporal constraints, and they were estimated as the unknown parameters simultaneously with other positioning parameters. Then, a dataset of 178 International GNSS Service (IGS stations at day 72 in 2012 was used to evaluate the convergence speed, the positioning accuracy and the accuracy of the retrieved ionospheric VTEC. The series of results have shown that the convergence speed and stability of the new algorithm are much better than the traditional PPP algorithm, and the positioning accuracy of about 2-3 cm and 2-3 dm can be achieved respectively for static and kinematic positioning with the single-frequency observations' daily solution. The average bias of ionospheric total electron content retrieved by the single-frequency PPP and dual-frequency PPP is less than 5 TECU. So the ionospheric total electron content can be used as a kind of auxiliary products in GPS positioning.

Sequential unconstrained minimization algorithms for constrained optimization

International Nuclear Information System (INIS)

Byrne, Charles

2008-01-01

The problem of minimizing a function f(x):R J → R, subject to constraints on the vector variable x, occurs frequently in inverse problems. Even without constraints, finding a minimizer of f(x) may require iterative methods. We consider here a general class of iterative algorithms that find a solution to the constrained minimization problem as the limit of a sequence of vectors, each solving an unconstrained minimization problem. Our sequential unconstrained minimization algorithm (SUMMA) is an iterative procedure for constrained minimization. At the kth step we minimize the function G k (x)=f(x)+g k (x), to obtain x k . The auxiliary functions g k (x):D subset of R J → R + are nonnegative on the set D, each x k is assumed to lie within D, and the objective is to minimize the continuous function f:R J → R over x in the set C = D-bar, the closure of D. We assume that such minimizers exist, and denote one such by x-circumflex. We assume that the functions g k (x) satisfy the inequalities 0≤g k (x)≤G k-1 (x)-G k-1 (x k-1 ), for k = 2, 3, .... Using this assumption, we show that the sequence {(x k )} is decreasing and converges to f(x-circumflex). If the restriction of f(x) to D has bounded level sets, which happens if x-circumflex is unique and f(x) is closed, proper and convex, then the sequence {x k } is bounded, and f(x*)=f(x-circumflex), for any cluster point x*. Therefore, if x-circumflex is unique, x* = x-circumflex and {x k } → x-circumflex. When x-circumflex is not unique, convergence can still be obtained, in particular cases. The SUMMA includes, as particular cases, the well-known barrier- and penalty-function methods, the simultaneous multiplicative algebraic reconstruction technique (SMART), the proximal minimization algorithm of Censor and Zenios, the entropic proximal methods of Teboulle, as well as certain cases of gradient descent and the Newton–Raphson method. The proof techniques used for SUMMA can be extended to obtain related results

Image-based point spread function implementation in a fully 3D OSEM reconstruction algorithm for PET.

Science.gov (United States)

Rapisarda, E; Bettinardi, V; Thielemans, K; Gilardi, M C

2010-07-21

The interest in positron emission tomography (PET) and particularly in hybrid integrated PET/CT systems has significantly increased in the last few years due to the improved quality of the obtained images. Nevertheless, one of the most important limits of the PET imaging technique is still its poor spatial resolution due to several physical factors originating both at the emission (e.g. positron range, photon non-collinearity) and at detection levels (e.g. scatter inside the scintillating crystals, finite dimensions of the crystals and depth of interaction). To improve the spatial resolution of the images, a possible way consists of measuring the point spread function (PSF) of the system and then accounting for it inside the reconstruction algorithm. In this work, the system response of the GE Discovery STE operating in 3D mode has been characterized by acquiring (22)Na point sources in different positions of the scanner field of view. An image-based model of the PSF was then obtained by fitting asymmetric two-dimensional Gaussians on the (22)Na images reconstructed with small pixel sizes. The PSF was then incorporated, at the image level, in a three-dimensional ordered subset maximum likelihood expectation maximization (OS-MLEM) reconstruction algorithm. A qualitative and quantitative validation of the algorithm accounting for the PSF has been performed on phantom and clinical data, showing improved spatial resolution, higher contrast and lower noise compared with the corresponding images obtained using the standard OS-MLEM algorithm.

Nearest Neighbour Corner Points Matching Detection Algorithm

Directory of Open Access Journals (Sweden)

Zhang Changlong

2015-01-01

Full Text Available Accurate detection towards the corners plays an important part in camera calibration. To deal with the instability and inaccuracies of present corner detection algorithm, the nearest neighbour corners match-ing detection algorithms was brought forward. First, it dilates the binary image of the photographed pictures, searches and reserves quadrilateral outline of the image. Second, the blocks which accord with chess-board-corners are classified into a class. If too many blocks in class, it will be deleted; if not, it will be added, and then let the midpoint of the two vertex coordinates be the rough position of corner. At last, it precisely locates the position of the corners. The Experimental results have shown that the algorithm has obvious advantages on accuracy and validity in corner detection, and it can give security for camera calibration in traffic accident measurement.

Iterative algorithms for computing the feedback Nash equilibrium point for positive systems

Science.gov (United States)

Ivanov, I.; Imsland, Lars; Bogdanova, B.

2017-03-01

The paper studies N-player linear quadratic differential games on an infinite time horizon with deterministic feedback information structure. It introduces two iterative methods (the Newton method as well as its accelerated modification) in order to compute the stabilising solution of a set of generalised algebraic Riccati equations. The latter is related to the Nash equilibrium point of the considered game model. Moreover, we derive the sufficient conditions for convergence of the proposed methods. Finally, we discuss two numerical examples so as to illustrate the performance of both of the algorithms.

Registration of TLS and MLS Point Cloud Combining Genetic Algorithm with ICP

Directory of Open Access Journals (Sweden)

YAN Li

2018-04-01

Full Text Available Large scene point cloud can be quickly acquired by mobile laser scanning (MLS technology,which needs to be supplemented by terrestrial laser scanning (TLS point cloud because of limited field of view and occlusion.MLS and TLS point cloud are located in geodetic coordinate system and local coordinate system respectively.This paper proposes an automatic registration method combined genetic algorithm (GA and iterative closed point ICP to achieve a uniform coordinate reference frame.The local optimizer is utilized in ICP.The efficiency of ICP is higher than that of GA registration,but it depends on a initial solution.GA is a global optimizer,but it's inefficient.The combining strategy is that ICP is enabled to complete the registration when the GA tends to local search.The rough position measured by a built-in GPS of a terrestrial laser scanner is used in the GA registration to limit its optimizing search space.To improve the GA registration accuracy,a maximum registration model called normalized sum of matching scores (NSMS is presented.The results for measured data show that the NSMS model is effective,the root mean square error (RMSE of GA registration is 1~5 cm and the registration efficiency can be improved by about 50% combining GA with ICP.

Community detection in complex networks using proximate support vector clustering

Science.gov (United States)

Wang, Feifan; Zhang, Baihai; Chai, Senchun; Xia, Yuanqing

2018-03-01

Community structure, one of the most attention attracting properties in complex networks, has been a cornerstone in advances of various scientific branches. A number of tools have been involved in recent studies concentrating on the community detection algorithms. In this paper, we propose a support vector clustering method based on a proximity graph, owing to which the introduced algorithm surpasses the traditional support vector approach both in accuracy and complexity. Results of extensive experiments undertaken on computer generated networks and real world data sets illustrate competent performances in comparison with the other counterparts.

MODIS 250m burned area mapping based on an algorithm using change point detection and Markov random fields.

Science.gov (United States)

Mota, Bernardo; Pereira, Jose; Campagnolo, Manuel; Killick, Rebeca

2013-04-01

Area burned in tropical savannas of Brazil was mapped using MODIS-AQUA daily 250m resolution imagery by adapting one of the European Space Agency fire_CCI project burned area algorithms, based on change point detection and Markov random fields. The study area covers 1,44 Mkm2 and was performed with data from 2005. The daily 1000 m image quality layer was used for cloud and cloud shadow screening. The algorithm addresses each pixel as a time series and detects changes in the statistical properties of NIR reflectance values, to identify potential burning dates. The first step of the algorithm is robust filtering, to exclude outlier observations, followed by application of the Pruned Exact Linear Time (PELT) change point detection technique. Near-infrared (NIR) spectral reflectance changes between time segments, and post change NIR reflectance values are combined into a fire likelihood score. Change points corresponding to an increase in reflectance are dismissed as potential burn events, as are those occurring outside of a pre-defined fire season. In the last step of the algorithm, monthly burned area probability maps and detection date maps are converted to dichotomous (burned-unburned maps) using Markov random fields, which take into account both spatial and temporal relations in the potential burned area maps. A preliminary assessment of our results is performed by comparison with data from the MODIS 1km active fires and the 500m burned area products, taking into account differences in spatial resolution between the two sensors.

A Class of Large-Update and Small-Update Primal-Dual Interior-Point Algorithms for Linear Optimization

NARCIS (Netherlands)

Bai, Y.Q.; Lesaja, G.; Roos, C.; Wang, G.Q.; El Ghami, M.

2008-01-01

In this paper we present a class of polynomial primal-dual interior-point algorithms for linear optimization based on a new class of kernel functions. This class is fairly general and includes the classical logarithmic function, the prototype self-regular function, and non-self-regular kernel

An improved Pattern Search based algorithm to solve the Dynamic Economic Dispatch problem with valve-point effect

International Nuclear Information System (INIS)

Alsumait, J.S.; Qasem, M.; Sykulski, J.K.; Al-Othman, A.K.

2010-01-01

In this paper, an improved algorithm based on Pattern Search method (PS) to solve the Dynamic Economic Dispatch is proposed. The algorithm maintains the essential unit ramp rate constraint, along with all other necessary constraints, not only for the time horizon of operation (24 h), but it preserves these constraints through the transaction period to the next time horizon (next day) in order to avoid the discontinuity of the power system operation. The Dynamic Economic and Emission Dispatch problem (DEED) is also considered. The load balance constraints, operating limits, valve-point loading and network losses are included in the models of both DED and DEED. The numerical results clarify the significance of the improved algorithm and verify its performance.

Development of Quadratic Programming Algorithm Based on Interior Point Method with Estimation Mechanism of Active Constraints

Science.gov (United States)

Hashimoto, Hiroyuki; Takaguchi, Yusuke; Nakamura, Shizuka

Instability of calculation process and increase of calculation time caused by increasing size of continuous optimization problem remain the major issues to be solved to apply the technique to practical industrial systems. This paper proposes an enhanced quadratic programming algorithm based on interior point method mainly for improvement of calculation stability. The proposed method has dynamic estimation mechanism of active constraints on variables, which fixes the variables getting closer to the upper/lower limit on them and afterwards releases the fixed ones as needed during the optimization process. It is considered as algorithm-level integration of the solution strategy of active-set method into the interior point method framework. We describe some numerical results on commonly-used bench-mark problems called “CUTEr” to show the effectiveness of the proposed method. Furthermore, the test results on large-sized ELD problem (Economic Load Dispatching problems in electric power supply scheduling) are also described as a practical industrial application.

A Numerical Algorithm for Solving a Four-Point Nonlinear Fractional Integro-Differential Equations

OpenAIRE

Gao, Er; Song, Songhe; Zhang, Xinjian

2012-01-01

We provide a new algorithm for a four-point nonlocal boundary value problem of nonlinear integro-differential equations of fractional order q∈(1,2] based on reproducing kernel space method. According to our work, the analytical solution of the equations is represented in the reproducing kernel space which we construct and so the n-term approximation. At the same time, the n-term approximation is proved to converge to the analytical solution. An illustrative example is also presented, which sh...

Hybrid SOA-SQP algorithm for dynamic economic dispatch with valve-point effects

Energy Technology Data Exchange (ETDEWEB)

Sivasubramani, S.; Swarup, K.S. [Department of Electrical Engineering, Indian Institute of Technology Madras, Chennai 600036 (India)

2010-12-15

This paper proposes a hybrid technique combining a new heuristic algorithm named seeker optimization algorithm (SOA) and sequential quadratic programming (SQP) method for solving dynamic economic dispatch problem with valve-point effects. The SOA is based on the concept of simulating the act of human searching, where the search direction is based on the empirical gradient (EG) by evaluating the response to the position changes and the step length is based on uncertainty reasoning by using a simple fuzzy rule. In this paper, SOA is used as a base level search, which can give a good direction to the optimal global region and SQP as a local search to fine tune the solution obtained from SOA. Thus SQP guides SOA to find optimal or near optimal solution in the complex search space. Two test systems i.e., 5 unit with losses and 10 unit without losses, have been taken to validate the efficiency of the proposed hybrid method. Simulation results clearly show that the proposed method outperforms the existing method in terms of solution quality. (author)

Uncemented allograft-prosthetic composite reconstruction of the proximal femur

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Li Min

2014-01-01

Full Text Available Background: Allograft-prosthetic composite can be divided into three groups names cemented, uncemented, and partially cemented. Previous studies have mainly reported outcomes in cemented and partially cemented allograft-prosthetic composites, but have rarely focused on the uncemented allograft-prosthetic composites. The objectives of our study were to describe a surgical technique for using proximal femoral uncemented allograft-prosthetic composite and to present the radiographic and clinical results. Materials and Methods: Twelve patients who underwent uncemented allograft-prosthetic composite reconstruction of the proximal femur after bone tumor resection were retrospectively evaluated at an average followup of 24.0 months. Clinical records and radiographs were evaluated. Results: In our series, union occurred in all the patients (100%; range 5-9 months. Until the most recent followup, there were no cases with infection, nonunion of the greater trochanter, junctional bone resorption, dislocation, allergic reaction, wear of acetabulum socket, recurrence, and metastasis. But there were three periprosthetic fractures which were fixed using cerclage wire during surgery. Five cases had bone resorption in and around the greater trochanter. The average Musculoskeletal Tumor Society (MSTS score and Harris hip score (HHS were 26.2 points (range 24-29 points and 80.6 points (range 66.2-92.7 points, respectively. Conclusions: These results showed that uncemented allograft-prosthetic composite could promote bone union through compression at the host-allograft junction and is a good choice for proximal femoral resection. Although this technology has its own merits, long term outcomes are yet not validated.

Characterization results and Markov chain Monte Carlo algorithms including exact simulation for some spatial point processes

DEFF Research Database (Denmark)

Häggström, Olle; Lieshout, Marie-Colette van; Møller, Jesper

1999-01-01

The area-interaction process and the continuum random-cluster model are characterized in terms of certain functional forms of their respective conditional intensities. In certain cases, these two point process models can be derived from a bivariate point process model which in many respects...... is simpler to analyse and simulate. Using this correspondence we devise a two-component Gibbs sampler, which can be used for fast and exact simulation by extending the recent ideas of Propp and Wilson. We further introduce a Swendsen-Wang type algorithm. The relevance of the results within spatial statistics...

Hemiarthroplasty for proximal humeral fracture: restoration of the Gothic arch.

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Krishnan, Sumant G; Bennion, Phillip W; Reineck, John R; Burkhead, Wayne Z

2008-10-01

Proximal humerus fractures are the most common fractures of the shoulder girdle, and initial management of these injuries often determines final outcome. When arthroplasty is used to manage proximal humeral fractures, surgery remains technically demanding, and outcomes have been unpredictable. Recent advances in both technique and prosthetic implants have led to more successful and reproducible results. Key technical points include restoration of the Gothic arch, anatomic tuberosity reconstruction, and minimal soft tissue dissection.

An algorithm for leak point detection of underground pipelines

International Nuclear Information System (INIS)

Lee, Young Sup; Yoon, Dong Jin

2004-01-01

Leak noise is a good source to identify the exact location of a leak point of underground water pipelines. Water leak generates broadband noise from a leak location and can be propagated to both directions of water pipes. However, the necessity of long-range detection of this leak location makes to identify low-frequency acoustic waves rather than high frequency ones. Acoustic wave propagation coupled with surrounding boundaries including cast iron pipes is theoretically analyzed and the wave velocity was confirmed with experiment. The leak locations were identified both by the acoustic emission (AE) method and the cross-correlation method. In a short-range distance, both the AE method and cross-correlation method are effective to detect leak position. However, the detection for a long-range distance required a lower frequency range accelerometers only because higher frequency waves were attenuated very quickly with the increase of propagation paths. Two algorithms for the cross-correlation function were suggested, and a long-range detection has been achieved at real underground water pipelines longer than 300 m.

A Parametric k-Means Algorithm

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Tarpey, Thaddeus

2007-01-01

Summary The k points that optimally represent a distribution (usually in terms of a squared error loss) are called the k principal points. This paper presents a computationally intensive method that automatically determines the principal points of a parametric distribution. Cluster means from the k-means algorithm are nonparametric estimators of principal points. A parametric k-means approach is introduced for estimating principal points by running the k-means algorithm on a very large simulated data set from a distribution whose parameters are estimated using maximum likelihood. Theoretical and simulation results are presented comparing the parametric k-means algorithm to the usual k-means algorithm and an example on determining sizes of gas masks is used to illustrate the parametric k-means algorithm. PMID:17917692

Algorithmic-Reducibility = Renormalization-Group Fixed-Points; ``Noise''-Induced Phase-Transitions (NITs) to Accelerate Algorithmics (``NIT-Picking'') Replacing CRUTCHES!!!: Gauss Modular/Clock-Arithmetic Congruences = Signal X Noise PRODUCTS..

Science.gov (United States)

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!!!

A Robust and Accurate Two-Step Auto-Labeling Conditional Iterative Closest Points (TACICP Algorithm for Three-Dimensional Multi-Modal Carotid Image Registration.

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Hengkai Guo

Full Text Available Atherosclerosis is among the leading causes of death and disability. Combining information from multi-modal vascular images is an effective and efficient way to diagnose and monitor atherosclerosis, in which image registration is a key technique. In this paper a feature-based registration algorithm, Two-step Auto-labeling Conditional Iterative Closed Points (TACICP algorithm, is proposed to align three-dimensional carotid image datasets from ultrasound (US and magnetic resonance (MR. Based on 2D segmented contours, a coarse-to-fine strategy is employed with two steps: rigid initialization step and non-rigid refinement step. Conditional Iterative Closest Points (CICP algorithm is given in rigid initialization step to obtain the robust rigid transformation and label configurations. Then the labels and CICP algorithm with non-rigid thin-plate-spline (TPS transformation model is introduced to solve non-rigid carotid deformation between different body positions. The results demonstrate that proposed TACICP algorithm has achieved an average registration error of less than 0.2mm with no failure case, which is superior to the state-of-the-art feature-based methods.

Proximal supination osteotomy of the first metatarsal for hallux valgus.

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Yasuda, Toshito; Okuda, Ryuzo; Jotoku, Tsuyoshi; Shima, Hiroaki; Hida, Takashi; Neo, Masashi

2015-06-01

Risk factors for hallux valgus recurrence include postoperative round-shaped lateral edge of the first metatarsal head and postoperative incomplete reduction of the sesamoids. To prevent the occurrence of such conditions, we developed a proximal supination osteotomy of the first metatarsal. Our aim was to describe this novel technique and report the outcomes in this report. Sixty-six patients (83 feet) underwent a distal soft tissue procedure combined with a proximal supination osteotomy. After the proximal crescentic osteotomy, the proximal fragment was pushed medially, and the distal fragment was abducted, and then the distal fragment of the first metatarsal was manually supinated. Outcomes were assessed using the American Orthopaedic Foot & Ankle Society (AOFAS) score and radiographic examinations. The average follow-up duration was 34 (range, 25 to 52) months. The mean AOFAS score improved significantly from 58.0 points preoperatively to 93.8 points postoperatively (P hallux valgus and intermetatarsal angle decreased significantly from 38.6 and 18.0 degrees preoperatively to 11.0 and 7.9 degrees postoperatively, respectively (both, P hallux valgus, defined as a hallux valgus angle ≥ 25 degrees. The rates of occurrence of a positive round sign and incomplete reduction of the sesamoids significantly decreased postoperatively, which may have contributed to the low hallux valgus recurrence rates. We conclude that a proximal supination osteotomy was an effective procedure for correction of hallux valgus and can achieve a low rate of hallux valgus recurrence. Level IV, retrospective case series. © The Author(s) 2015.

An anatomical study of the proximal aspect of the medial femoral condyle to define the proximal-distal condylar length

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Chia-Ming Chang

2017-01-01

Full Text Available Objective: Despite its possible role in knee arthroplasty, the proximal-distal condylar length (PDCL of the femur has never been reported in the literature. We conducted an anatomic study of the proximal aspect of the medial femoral condyle to propose a method for measuring the PDCL. Materials and Methods: Inspection of dried bone specimens was carried out to assure the most proximal condylar margin (MPCM as the eligible starting point to measure the PDCL. Simulation surgery was performed on seven pairs of cadaveric knees to verify the clinical application of measuring the PDCL after locating the MPCM. Interobserver reliability of this procedure was also analyzed. Results: Observation of the bone specimens showed that the MPCM is a concavity formed by the junction of the distal end of the supracondylar ridge and the proximal margin of the medial condyle. This anatomically distinctive structure made the MPCM an unambiguous landmark. The cadaveric simulation surgical dissection demonstrated that the MPCM is easily accessed in a surgical setting, making the measurement of the PDCL plausible. The intraclass correlation coefficient was 0.78, indicating good interobserver reliability for this technique. Conclusion: This study has suggested that the PDCL can be measured based on the MPCM in a surgical setting. PDCL measurement might be useful in joint line position management, selection of femoral component sizes, and other applications related to the proximal-distal dimension of the knee. Further investigation is required.

A Penalization-Gradient Algorithm for Variational Inequalities

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Abdellatif Moudafi

2011-01-01

Full Text Available This paper is concerned with the study of a penalization-gradient algorithm for solving variational inequalities, namely, find x̅∈C such that 〈Ax̅,y-x̅〉≥0 for all y∈C, where A:H→H is a single-valued operator, C is a closed convex set of a real Hilbert space H. Given Ψ:H→R  ∪  {+∞} which acts as a penalization function with respect to the constraint x̅∈C, and a penalization parameter βk, we consider an algorithm which alternates a proximal step with respect to ∂Ψ and a gradient step with respect to A and reads as xk=(I+λkβk∂Ψ-1(xk-1-λkAxk-1. Under mild hypotheses, we obtain weak convergence for an inverse strongly monotone operator and strong convergence for a Lipschitz continuous and strongly monotone operator. Applications to hierarchical minimization and fixed-point problems are also given and the multivalued case is reached by replacing the multivalued operator by its Yosida approximate which is always Lipschitz continuous.

Validation of Point Clouds Segmentation Algorithms Through Their Application to Several Case Studies for Indoor Building Modelling

Science.gov (United States)

Macher, H.; Landes, T.; Grussenmeyer, P.

2016-06-01

Laser scanners are widely used for the modelling of existing buildings and particularly in the creation process of as-built BIM (Building Information Modelling). However, the generation of as-built BIM from point clouds involves mainly manual steps and it is consequently time consuming and error-prone. Along the path to automation, a three steps segmentation approach has been developed. This approach is composed of two phases: a segmentation into sub-spaces namely floors and rooms and a plane segmentation combined with the identification of building elements. In order to assess and validate the developed approach, different case studies are considered. Indeed, it is essential to apply algorithms to several datasets and not to develop algorithms with a unique dataset which could influence the development with its particularities. Indoor point clouds of different types of buildings will be used as input for the developed algorithms, going from an individual house of almost one hundred square meters to larger buildings of several thousand square meters. Datasets provide various space configurations and present numerous different occluding objects as for example desks, computer equipments, home furnishings and even wine barrels. For each dataset, the results will be illustrated. The analysis of the results will provide an insight into the transferability of the developed approach for the indoor modelling of several types of buildings.

A three-point Taylor algorithm for three-point boundary value problems

NARCIS (Netherlands)

J.L. López; E. Pérez Sinusía; N.M. Temme (Nico)

2011-01-01

textabstractWe consider second-order linear differential equations $\\varphi(x)y''+f(x)y'+g(x)y=h(x)$ in the interval $(-1,1)$ with Dirichlet, Neumann or mixed Dirichlet-Neumann boundary conditions given at three points of the interval: the two extreme points $x=\\pm 1$ and an interior point

Hybrid external fixation of the proximal tibia: strategies to improve frame stability.

Science.gov (United States)

Roberts, Craig S; Dodds, James C; Perry, Kelvin; Beck, Dennis; Seligson, David; Voor, Michael J

2003-07-01

To determine the specific frame construction strategies that can increase the stability of hybrid (ring with tensioned wires proximally connected by bars to half-pins distally) external fixation of proximal tibia fractures. DESIGN Repeated measures biomechanical testing. Laboratory. Composite fiberglass tibias. Using the Heidelberg and Ilizarov systems, external fixators were tested on composite fiberglass tibias with a 1-cm proximal osteotomy (OTA fracture classification 41-A3.3) in seven frame configurations: unilateral frames with 5-mm diameter half-pins and 6-mm diameter half-pins; hybrid (as described above), with and without a 6-mm anterior proximal half-pin; a "box" hybrid (additional ring group distal to the fracture connected by symmetrically spaced bars to the proximal rings) with and without an anterior, proximal half-pin; and a full, four-ring configuration. Each configuration was loaded in four positions (central, medial, posterior, and posteromedial). Displacement at point of loading of proximal fragment. The "box" hybrid was stiffer than the standard hybrid for all loading positions. The addition of an anterior half-pin stiffened the standard hybrid and the "box" hybrid. The most dramatic improvements in the stability of hybrid frames used for proximal tibial fractures result from addition of an anterior, proximal half-pin.

Detection of uterine MMG contractions using a multiple change point estimator and the K-means cluster algorithm.

Science.gov (United States)

La Rosa, Patricio S; Nehorai, Arye; Eswaran, Hari; Lowery, Curtis L; Preissl, Hubert

2008-02-01

We propose a single channel two-stage time-segment discriminator of uterine magnetomyogram (MMG) contractions during pregnancy. We assume that the preprocessed signals are piecewise stationary having distribution in a common family with a fixed number of parameters. Therefore, at the first stage, we propose a model-based segmentation procedure, which detects multiple change-points in the parameters of a piecewise constant time-varying autoregressive model using a robust formulation of the Schwarz information criterion (SIC) and a binary search approach. In particular, we propose a test statistic that depends on the SIC, derive its asymptotic distribution, and obtain closed-form optimal detection thresholds in the sense of the Neyman-Pearson criterion; therefore, we control the probability of false alarm and maximize the probability of change-point detection in each stage of the binary search algorithm. We compute and evaluate the relative energy variation [root mean squares (RMS)] and the dominant frequency component [first order zero crossing (FOZC)] in discriminating between time segments with and without contractions. The former consistently detects a time segment with contractions. Thus, at the second stage, we apply a nonsupervised K-means cluster algorithm to classify the detected time segments using the RMS values. We apply our detection algorithm to real MMG records obtained from ten patients admitted to the hospital for contractions with gestational ages between 31 and 40 weeks. We evaluate the performance of our detection algorithm in computing the detection and false alarm rate, respectively, using as a reference the patients' feedback. We also analyze the fusion of the decision signals from all the sensors as in the parallel distributed detection approach.

Optimal Point-to-Point Trajectory Tracking of Redundant Manipulators using Generalized Pattern Search

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Thi Rein Myo

2008-11-01

Full Text Available Optimal point-to-point trajectory planning for planar redundant manipulator is considered in this study. The main objective is to minimize the sum of the position error of the end-effector at each intermediate point along the trajectory so that the end-effector can track the prescribed trajectory accurately. An algorithm combining Genetic Algorithm and Pattern Search as a Generalized Pattern Search GPS is introduced to design the optimal trajectory. To verify the proposed algorithm, simulations for a 3-D-O-F planar manipulator with different end-effector trajectories have been carried out. A comparison between the Genetic Algorithm and the Generalized Pattern Search shows that The GPS gives excellent tracking performance.

Disentangling the roles of point-of-sale ban, tobacco retailer density and proximity on cessation and relapse among a cohort of smokers: findings from ITC Canada Survey.

Science.gov (United States)

Fleischer, Nancy L; Lozano, Paula; Wu, Yun-Hsuan; Hardin, James W; Meng, Gang; Liese, Angela D; Fong, Geoffrey T; Thrasher, James F

2018-03-08

To examine how point-of-sale (POS) display bans, tobacco retailer density and tobacco retailer proximity were associated with smoking cessation and relapse in a cohort of smokers in Canada, where provincial POS bans were implemented differentially over time from 2004 to 2010. Data from the 2005 to 2011 administrations of the International Tobacco Control (ITC) Canada Survey, a nationally representative cohort of adult smokers, were linked via residential geocoding with tobacco retailer data to derive for each smoker a measure of retailer density and proximity. An indicator variable identified whether the smoker's province banned POS displays at the time of the interview. Outcomes included cessation for at least 1 month at follow-up among smokers from the previous wave and relapse at follow-up among smokers who had quit at the previous wave. Logistic generalised estimating equation models were used to determine the relationship between living in a province with a POS display ban, tobacco retailer density and tobacco retailer proximity with cessation (n=4388) and relapse (n=866). Provincial POS display bans were not associated with cessation. In adjusted models, POS display bans were associated with lower odds of relapse which strengthened after adjusting for retailer density and proximity, although results were not statistically significant (OR 0.66, 95% CI 0.41 to 1.07, p=0.089). Neither tobacco retailer density nor proximity was associated with cessation or relapse. Banning POS retail displays shows promise as an additional tool to prevent relapse, although these results need to be confirmed in larger longitudinal studies. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

The Type-2 Fuzzy Logic Controller-Based Maximum Power Point Tracking Algorithm and the Quadratic Boost Converter for Pv System

Science.gov (United States)

Altin, Necmi

2018-05-01

An interval type-2 fuzzy logic controller-based maximum power point tracking algorithm and direct current-direct current (DC-DC) converter topology are proposed for photovoltaic (PV) systems. The proposed maximum power point tracking algorithm is designed based on an interval type-2 fuzzy logic controller that has an ability to handle uncertainties. The change in PV power and the change in PV voltage are determined as inputs of the proposed controller, while the change in duty cycle is determined as the output of the controller. Seven interval type-2 fuzzy sets are determined and used as membership functions for input and output variables. The quadratic boost converter provides high voltage step-up ability without any reduction in performance and stability of the system. The performance of the proposed system is validated through MATLAB/Simulink simulations. It is seen that the proposed system provides high maximum power point tracking speed and accuracy even for fast changing atmospheric conditions and high voltage step-up requirements.

Maximum power point tracking-based control algorithm for PMSG wind generation system without mechanical sensors

International Nuclear Information System (INIS)

Hong, Chih-Ming; Chen, Chiung-Hsing; Tu, Chia-Sheng

2013-01-01

Highlights: ► This paper presents MPPT based control for optimal wind energy capture using RBFN. ► MPSO is adopted to adjust the learning rates to improve the learning capability. ► This technique can maintain the system stability and reach the desired performance. ► The EMF in the rotating reference frame is utilized in order to estimate speed. - Abstract: This paper presents maximum-power-point-tracking (MPPT) based control algorithms for optimal wind energy capture using radial basis function network (RBFN) and a proposed torque observer MPPT algorithm. The design of a high-performance on-line training RBFN using back-propagation learning algorithm with modified particle swarm optimization (MPSO) regulating controller for the sensorless control of a permanent magnet synchronous generator (PMSG). The MPSO is adopted in this study to adapt the learning rates in the back-propagation process of the RBFN to improve the learning capability. The PMSG is controlled by the loss-minimization control with MPPT below the base speed, which corresponds to low and high wind speed, and the maximum energy can be captured from the wind. Then the observed disturbance torque is feed-forward to increase the robustness of the PMSG system

Development of procedures for programmable proximity aperture lithography

Energy Technology Data Exchange (ETDEWEB)

Whitlow, H.J., E-mail: harry.whitlow@he-arc.ch [Institut des Microtechnologies Appliquées Arc, Haute Ecole Arc Ingénierie, Eplatures-Grise 17, CH-2300 La Chaux-de-Fonds (Switzerland); Department of Physics, University of Jyväskylä, P.O. Box 35 (YFL), FI-40014 Jyväskylä (Finland); Gorelick, S. [VTT Technical Research Centre of Finland, P.O. Box 1000, Tietotie 3, Espoo, FI-02044 VTT (Finland); Puttaraksa, N. [Department of Physics, University of Jyväskylä, P.O. Box 35 (YFL), FI-40014 Jyväskylä (Finland); Plasma and Beam Physics Research Facility, Department of Physics and Materials Science, Faculty of Science, Chiang Mai University, Chiang Mai 50200 (Thailand); Napari, M.; Hokkanen, M.J.; Norarat, R. [Department of Physics, University of Jyväskylä, P.O. Box 35 (YFL), FI-40014 Jyväskylä (Finland)

2013-07-01

Programmable proximity aperture lithography (PPAL) with MeV ions has been used in Jyväskylä and Chiang Mai universities for a number of years. Here we describe a number of innovations and procedures that have been incorporated into the LabView-based software. The basic operation involves the coordination of the beam blanker and five motor-actuated translators with high accuracy, close to the minimum step size with proper anti-collision algorithms. By using special approaches, such writing calibration patterns, linearisation of position and careful backlash correction the absolute accuracy of the aperture size and position, can be improved beyond the standard afforded by the repeatability of the translator end-point switches. Another area of consideration has been the fluence control procedures. These involve control of the uniformity of the beam where different approaches for fluence measurement such as simultaneous aperture current and the ion current passing through the aperture using a Faraday cup are used. Microfluidic patterns may contain many elements that make-up mixing sections, reaction chambers, separation columns and fluid reservoirs. To facilitate conception and planning we have implemented a .svg file interpreter, that allows the use of scalable vector graphics files produced by standard drawing software for generation of patterns made up of rectangular elements.

Solving discrete zero point problems

NARCIS (Netherlands)

van der Laan, G.; Talman, A.J.J.; Yang, Z.F.

2004-01-01

In this paper an algorithm is proposed to .nd a discrete zero point of a function on the collection of integral points in the n-dimensional Euclidean space IRn.Starting with a given integral point, the algorithm generates a .nite sequence of adjacent integral simplices of varying dimension and

Unsupervised classification of multivariate geostatistical data: Two algorithms

Science.gov (United States)

Romary, Thomas; Ors, Fabien; Rivoirard, Jacques; Deraisme, Jacques

2015-12-01

With the increasing development of remote sensing platforms and the evolution of sampling facilities in mining and oil industry, spatial datasets are becoming increasingly large, inform a growing number of variables and cover wider and wider areas. Therefore, it is often necessary to split the domain of study to account for radically different behaviors of the natural phenomenon over the domain and to simplify the subsequent modeling step. The definition of these areas can be seen as a problem of unsupervised classification, or clustering, where we try to divide the domain into homogeneous domains with respect to the values taken by the variables in hand. The application of classical clustering methods, designed for independent observations, does not ensure the spatial coherence of the resulting classes. Image segmentation methods, based on e.g. Markov random fields, are not adapted to irregularly sampled data. Other existing approaches, based on mixtures of Gaussian random functions estimated via the expectation-maximization algorithm, are limited to reasonable sample sizes and a small number of variables. In this work, we propose two algorithms based on adaptations of classical algorithms to multivariate geostatistical data. Both algorithms are model free and can handle large volumes of multivariate, irregularly spaced data. The first one proceeds by agglomerative hierarchical clustering. The spatial coherence is ensured by a proximity condition imposed for two clusters to merge. This proximity condition relies on a graph organizing the data in the coordinates space. The hierarchical algorithm can then be seen as a graph-partitioning algorithm. Following this interpretation, a spatial version of the spectral clustering algorithm is also proposed. The performances of both algorithms are assessed on toy examples and a mining dataset.

Sensitivity Analysis of the Proximal-Based Parallel Decomposition Methods

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Feng Ma

2014-01-01

Full Text Available The proximal-based parallel decomposition methods were recently proposed to solve structured convex optimization problems. These algorithms are eligible for parallel computation and can be used efficiently for solving large-scale separable problems. In this paper, compared with the previous theoretical results, we show that the range of the involved parameters can be enlarged while the convergence can be still established. Preliminary numerical tests on stable principal component pursuit problem testify to the advantages of the enlargement.

Novel implant for peri-prosthetic proximal tibia fractures.

Science.gov (United States)

Tran, Ton; Chen, Bernard K; Wu, Xinhua; Pun, Chung Lun

2018-03-01

Repair of peri-prosthetic proximal tibia fractures is very challenging in patients with a total knee replacement or arthroplasty. The tibial component of the knee implant severely restricts the fixation points of the tibial implant to repair peri-prosthetic fractures. A novel implant has been designed with an extended flange over the anterior of tibial condyle to provide additional points of fixation, overcoming limitations of existing generic locking plates used for proximal tibia fractures. Furthermore, the screws fixed through the extended flange provide additional support to prevent the problem of subsidence of tibial component of knee implant. The design methodology involved extraction of bone data from CT scans into a flexible CAD format, implant design and structural evaluation and optimisation using FEM as well as prototype development and manufacture by selective laser melting 3D printing technology with Ti6Al4 V powder. A prototype tibia implant was developed based on a patient-specific bone structure, which was regenerated from the CT images of patient's tibia. The design is described in detail and being applied to fit up to 80% of patients, for both left and right sides based on the average dimensions and shape of the bone structure from a wide range of CT images. A novel tibial implant has been developed to repair peri-prosthetic proximal tibia fractures which overcomes significant constraints from the tibial component of existing knee implant. Copyright © 2018 Elsevier Ltd. All rights reserved.

PHOTOJOURNALISM AND PROXIMITY IMAGES: two points of view, two professions?

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Daniel Thierry

2011-06-01

Full Text Available For many decades, classic photojournalistic practice, firmly anchored in a creed established since Lewis Hine (1874-1940, has developed a praxis and a doxa that have barely been affected by the transformations in the various types of journalism. From the search for the “right image” which would be totally transparent by striving to refute its enunciative features from a perspective of maximumobjectivity, to the most seductive photography at supermarkets by photo agencies, the range of images seems to be decidedly framed. However, far from constituting high-powered reportingor excellent photography that is rewarded with numerous international prizes and invitations to the media-artistic world, local press photography remains in the shadows. How does oneoffer a representation of one’s self that can be shared in the local sphere? That is the first question which editors of the local daily and weekly press must grapple with. Using illustrations of the practices, this article proposes an examination of the origins ofthese practices and an analysis grounded on the originality of theauthors of these proximity photographs.

Proximal Humerus

NARCIS (Netherlands)

Diercks, Ron L.; Bain, Gregory; Itoi, Eiji; Di Giacomo, Giovanni; Sugaya, Hiroyuki

2015-01-01

This chapter describes the bony structures of the proximal humerus. The proximal humerus is often regarded as consisting of four parts, which assists in understanding function and, more specially, describes the essential parts in reconstruction after fracture or in joint replacement. These are the

Photovoltaic System Modeling with Fuzzy Logic Based Maximum Power Point Tracking Algorithm

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Hasan Mahamudul

2013-01-01

Full Text Available This paper represents a novel modeling technique of PV module with a fuzzy logic based MPPT algorithm and boost converter in Simulink environment. The prime contributions of this work are simplification of PV modeling technique and implementation of fuzzy based MPPT system to track maximum power efficiently. The main highlighted points of this paper are to demonstrate the precise control of the duty cycle with respect to various atmospheric conditions, illustration of PV characteristic curves, and operation analysis of the converter. The proposed system has been applied for three different PV modules SOLKAR 36 W, BP MSX 60 W, and KC85T 87 W. Finally the resultant data has been compared with the theoretical prediction and company specified value to ensure the validity of the system.

Maximum Power Point tracking algorithm based on I-V characteristic of PV array under uniform and non-uniform conditions

DEFF Research Database (Denmark)

Kouchaki, Alireza; Iman-Eini, H.; Asaei, B.

2012-01-01

This paper presents a new algorithm based on characteristic equation of solar cells to determine the Maximum Power Point (MPP) of PV modules under partially shaded conditions (PSC). To achieve this goal, an analytic condition is introduced to determine uniform or non-uniform atmospheric condition...

Inter-organizational proximity in the context of logistics – research challenges

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Patrycja Klimas

2015-03-01

Full Text Available Background: One of major areas of modern research econnected with management issues covers inter-organizational networks (including supply chains and cooperation processes aimed at improvement of the effectiveness of their performance to be found in such networks. The logistics is the main factor responsible for effectiveness of the supply chain.  A possible and a quite new direction of research in the area of the performance of processes of the inter-organizational cooperation is the proximity hypothesis that is considered in five dimensions (geographical, organizational, social, cognitive, and institutional. However, according to many authors, there is a lack of research on supply chains conducted from the logistics point of view. The proximity hypothesis in this area of research can be seen as a kind of novum. Therefore, this paper presents the proximity concept from the perspective of the management science, the overview of prior research covering the inter-organizational proximity with supply chain from the logistics point of view as well as the possible future directions of the empirical efforts. Methods: The aim of this paper is to present previous theoretical and empirical results of research covering inter-organizational proximity in logistics and to show current and up-to-date research challenges in this area. The method of the critical analysis of literature is used to realize the goal constructed this way. Results: Knowledge about the influence of the inter-organizational proximity on the performance of supply chains is rather limited, and the research conducted so far, is rather fragmentary and not free of limitations of the conceptual and methodological nature. Additional rationales for further research in this area include knowledge and cognitive gaps indentified in this paper. According to authors the aim of future empirical research should be as follows: (1 unification and update of used conceptual and methodological approaches

A Compound Algorithm for Maximum Power Point Tracking Used in Laser Power Beaming

Science.gov (United States)

Chen, Cheng; Liu, Qiang; Gao, Shan; Teng, Yun; Cheng, Lin; Yu, Chengtao; Peng, Kai

2018-03-01

With the high voltage intelligent substation developing in a pretty high speed, more and more artificial intelligent techniques have been incorporated into the power devices to meet the automation needs. For the sake of the line maintenance staff’s safety, the high voltage isolating switch draws great attention among the most important power devices because of its capability of connecting and disconnecting the high voltage circuit. However, due to the very high level voltage of the high voltage isolating switch’s working environment, the power supply system of the surveillance devices could suffer from great electromagnetic interference. Laser power beaming exhibits its merits in such situation because it can provide steady power from a distance despite the day or the night. Then the energy conversion efficiency arises as a new concern. To make as much use of the laser power as possible, our work mainly focuses on extracting maximum power from the photovoltaic (PV) panel. In this paper, we proposed a neural network based algorithm which relates both the intrinsic and the extrinsic features of the PV panel to the proportion of the voltage at the maximum power point (MPP) to the open circuit voltage of the PV panel. Simulations and experiments were carried out to verify the validness of our algorithm.

Multimodal optimization by using hybrid of artificial bee colony algorithm and BFGS algorithm

Science.gov (United States)

Anam, S.

2017-10-01

Optimization has become one of the important fields in Mathematics. Many problems in engineering and science can be formulated into optimization problems. They maybe have many local optima. The optimization problem with many local optima, known as multimodal optimization problem, is how to find the global solution. Several metaheuristic methods have been proposed to solve multimodal optimization problems such as Particle Swarm Optimization (PSO), Genetics Algorithm (GA), Artificial Bee Colony (ABC) algorithm, etc. The performance of the ABC algorithm is better than or similar to those of other population-based algorithms with the advantage of employing a fewer control parameters. The ABC algorithm also has the advantages of strong robustness, fast convergence and high flexibility. However, it has the disadvantages premature convergence in the later search period. The accuracy of the optimal value cannot meet the requirements sometimes. Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithm is a good iterative method for finding a local optimum. Compared with other local optimization methods, the BFGS algorithm is better. Based on the advantages of the ABC algorithm and the BFGS algorithm, this paper proposes a hybrid of the artificial bee colony algorithm and the BFGS algorithm to solve the multimodal optimization problem. The first step is that the ABC algorithm is run to find a point. In the second step is that the point obtained by the first step is used as an initial point of BFGS algorithm. The results show that the hybrid method can overcome from the basic ABC algorithm problems for almost all test function. However, if the shape of function is flat, the proposed method cannot work well.

A proposed adaptive step size perturbation and observation maximum power point tracking algorithm based on photovoltaic system modeling

Science.gov (United States)

Huang, Yu

Solar energy becomes one of the major alternative renewable energy options for its huge abundance and accessibility. Due to the intermittent nature, the high demand of Maximum Power Point Tracking (MPPT) techniques exists when a Photovoltaic (PV) system is used to extract energy from the sunlight. This thesis proposed an advanced Perturbation and Observation (P&O) algorithm aiming for relatively practical circumstances. Firstly, a practical PV system model is studied with determining the series and shunt resistances which are neglected in some research. Moreover, in this proposed algorithm, the duty ratio of a boost DC-DC converter is the object of the perturbation deploying input impedance conversion to achieve working voltage adjustment. Based on the control strategy, the adaptive duty ratio step size P&O algorithm is proposed with major modifications made for sharp insolation change as well as low insolation scenarios. Matlab/Simulink simulation for PV model, boost converter control strategy and various MPPT process is conducted step by step. The proposed adaptive P&O algorithm is validated by the simulation results and detail analysis of sharp insolation changes, low insolation condition and continuous insolation variation.

Cook-Levin Theorem Algorithmic-Reducibility/Completeness = Wilson Renormalization-(Semi)-Group Fixed-Points; ``Noise''-Induced Phase-Transitions (NITs) to Accelerate Algorithmics (``NIT-Picking'') REPLACING CRUTCHES!!!: Models: Turing-machine, finite-state-models, finite-automata

Science.gov (United States)

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!!!

Integrated Force and Distance Sensing using Elastomer-Embedded Commodity Proximity Sensors.

Energy Technology Data Exchange (ETDEWEB)

Patel, Radhen [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Cox, Rebecca E. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Correll, Nikolaus [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2017-02-01

We describe a combined proximity, contact and force (PCF) sensor based on a commodity infrared distance sensor embedded in a transparent elastomer with applications in robotic manipulation. Prior to contact, the sensor works as a distance sensor (0{6 cm), whereas after contact the material doubles as a spring, with force proportional to the compression of the elastomer (0{5 N). We describe its principle of operation and design parameters, including polymer thickness, mixing ratio, and emitter current, and show that the sensor response has an in ection point at contact that is independent of an object's surface properties, making it a robust detector for contact events. We then demonstrate how arrays of sensors, custom made for a standard Baxter gripper as well as embedded in the nger of the Kinova hand, can be used to (1) improve gripper alignment during grasping, (2) determine contact points with objects, (3) obtain simple 3D models using both proximity and touch, and (4) register point clouds from touch and RGB-D data.

Two General Extension Algorithms of Latin Hypercube Sampling

Directory of Open Access Journals (Sweden)

Zhi-zhao Liu

2015-01-01

Full Text Available For reserving original sampling points to reduce the simulation runs, two general extension algorithms of Latin Hypercube Sampling (LHS are proposed. The extension algorithms start with an original LHS of size m and construct a new LHS of size m+n that contains the original points as many as possible. In order to get a strict LHS of larger size, some original points might be deleted. The relationship of original sampling points in the new LHS structure is shown by a simple undirected acyclic graph. The basic general extension algorithm is proposed to reserve the most original points, but it costs too much time. Therefore, a general extension algorithm based on greedy algorithm is proposed to reduce the extension time, which cannot guarantee to contain the most original points. These algorithms are illustrated by an example and applied to evaluating the sample means to demonstrate the effectiveness.

Research on Scheduling Algorithm for Multi-satellite and Point Target Task on Swinging Mode

Science.gov (United States)

Wang, M.; Dai, G.; Peng, L.; Song, Z.; Chen, G.

2012-12-01

and negative swinging angle and the computation of time window are analyzed and discussed. And many strategies to improve the efficiency of this model are also put forward. In order to solve the model, we bring forward the conception of activity sequence map. By using the activity sequence map, the activity choice and the start time of the activity can be divided. We also bring forward three neighborhood operators to search the result space. The front movement remaining time and the back movement remaining time are used to analyze the feasibility to generate solution from neighborhood operators. Lastly, the algorithm to solve the problem and model is put forward based genetic algorithm. Population initialization, crossover operator, mutation operator, individual evaluation, collision decrease operator, select operator and collision elimination operator is designed in the paper. Finally, the scheduling result and the simulation for a practical example on 5 satellites and 100 point targets with swinging mode is given, and the scheduling performances are also analyzed while the swinging angle in 0, 5, 10, 15, 25. It can be shown by the result that the model and the algorithm are more effective than those ones without swinging mode.

FRAMEWORK FOR COMPARING SEGMENTATION ALGORITHMS

Directory of Open Access Journals (Sweden)

G. Sithole

2015-05-01

Full Text Available The notion of a ‘Best’ segmentation does not exist. A segmentation algorithm is chosen based on the features it yields, the properties of the segments (point sets it generates, and the complexity of its algorithm. The segmentation is then assessed based on a variety of metrics such as homogeneity, heterogeneity, fragmentation, etc. Even after an algorithm is chosen its performance is still uncertain because the landscape/scenarios represented in a point cloud have a strong influence on the eventual segmentation. Thus selecting an appropriate segmentation algorithm is a process of trial and error. Automating the selection of segmentation algorithms and their parameters first requires methods to evaluate segmentations. Three common approaches for evaluating segmentation algorithms are ‘goodness methods’, ‘discrepancy methods’ and ‘benchmarks’. Benchmarks are considered the most comprehensive method of evaluation. This paper shortcomings in current benchmark methods are identified and a framework is proposed that permits both a visual and numerical evaluation of segmentations for different algorithms, algorithm parameters and evaluation metrics. The concept of the framework is demonstrated on a real point cloud. Current results are promising and suggest that it can be used to predict the performance of segmentation algorithms.

Stochastic Reformulations of Linear Systems: Algorithms and Convergence Theory

KAUST Repository

Richtarik, Peter; Taká č, Martin

2017-01-01

We develop a family of reformulations of an arbitrary consistent linear system into a stochastic problem. The reformulations are governed by two user-defined parameters: a positive definite matrix defining a norm, and an arbitrary discrete or continuous distribution over random matrices. Our reformulation has several equivalent interpretations, allowing for researchers from various communities to leverage their domain specific insights. In particular, our reformulation can be equivalently seen as a stochastic optimization problem, stochastic linear system, stochastic fixed point problem and a probabilistic intersection problem. We prove sufficient, and necessary and sufficient conditions for the reformulation to be exact. Further, we propose and analyze three stochastic algorithms for solving the reformulated problem---basic, parallel and accelerated methods---with global linear convergence rates. The rates can be interpreted as condition numbers of a matrix which depends on the system matrix and on the reformulation parameters. This gives rise to a new phenomenon which we call stochastic preconditioning, and which refers to the problem of finding parameters (matrix and distribution) leading to a sufficiently small condition number. Our basic method can be equivalently interpreted as stochastic gradient descent, stochastic Newton method, stochastic proximal point method, stochastic fixed point method, and stochastic projection method, with fixed stepsize (relaxation parameter), applied to the reformulations.

Stochastic Reformulations of Linear Systems: Algorithms and Convergence Theory

KAUST Repository

Richtarik, Peter

2017-06-04

We develop a family of reformulations of an arbitrary consistent linear system into a stochastic problem. The reformulations are governed by two user-defined parameters: a positive definite matrix defining a norm, and an arbitrary discrete or continuous distribution over random matrices. Our reformulation has several equivalent interpretations, allowing for researchers from various communities to leverage their domain specific insights. In particular, our reformulation can be equivalently seen as a stochastic optimization problem, stochastic linear system, stochastic fixed point problem and a probabilistic intersection problem. We prove sufficient, and necessary and sufficient conditions for the reformulation to be exact. Further, we propose and analyze three stochastic algorithms for solving the reformulated problem---basic, parallel and accelerated methods---with global linear convergence rates. The rates can be interpreted as condition numbers of a matrix which depends on the system matrix and on the reformulation parameters. This gives rise to a new phenomenon which we call stochastic preconditioning, and which refers to the problem of finding parameters (matrix and distribution) leading to a sufficiently small condition number. Our basic method can be equivalently interpreted as stochastic gradient descent, stochastic Newton method, stochastic proximal point method, stochastic fixed point method, and stochastic projection method, with fixed stepsize (relaxation parameter), applied to the reformulations.

Worlds largest particle physics laboratory selects Proxim Wireless Mesh

CERN Multimedia

2007-01-01

"Proxim Wireless has announced that the European Organization for Nuclear Research (CERN), the world's largest particle physics laboratory and the birthplace of the World Wide Web, is using it's ORiNOCO AP-4000 mesh access points to extend the range of the laboratory's Wi-Fi network and to provide continuous monitoring of the lab's calorimeters" (1/2 page)

Fast geometric algorithms

International Nuclear Information System (INIS)

Noga, M.T.

1984-01-01

This thesis addresses a number of important problems that fall within the framework of the new discipline of Computational Geometry. The list of topics covered includes sorting and selection, convex hull algorithms, the L 1 hull, determination of the minimum encasing rectangle of a set of points, the Euclidean and L 1 diameter of a set of points, the metric traveling salesman problem, and finding the superrange of star-shaped and monotype polygons. The main theme of all the work was to develop a set of very fast state-of-the-art algorithms that supersede any rivals in terms of speed and ease of implementation. In some cases existing algorithms were refined; for others new techniques were developed that add to the present database of fast adaptive geometric algorithms. What emerges is a collection of techniques that is successful at merging modern tools developed in analysis of algorithms with those of classical geometry

Streaming Algorithms for Line Simplification

DEFF Research Database (Denmark)

Abam, Mohammad; de Berg, Mark; Hachenberger, Peter

2010-01-01

this problem in a streaming setting, where we only have a limited amount of storage, so that we cannot store all the points. We analyze the competitive ratio of our algorithms, allowing resource augmentation: we let our algorithm maintain a simplification with 2k (internal) points and compare the error of our...... simplification to the error of the optimal simplification with k points. We obtain the algorithms with O(1) competitive ratio for three cases: convex paths, where the error is measured using the Hausdorff distance (or Fréchet distance), xy-monotone paths, where the error is measured using the Hausdorff distance...... (or Fréchet distance), and general paths, where the error is measured using the Fréchet distance. In the first case the algorithm needs O(k) additional storage, and in the latter two cases the algorithm needs O(k 2) additional storage....

MM Algorithms for Geometric and Signomial Programming.

Science.gov (United States)

Lange, Kenneth; Zhou, Hua

2014-02-01

This paper derives new algorithms for signomial programming, a generalization of geometric programming. The algorithms are based on a generic principle for optimization called the MM algorithm. In this setting, one can apply the geometric-arithmetic mean inequality and a supporting hyperplane inequality to create a surrogate function with parameters separated. Thus, unconstrained signomial programming reduces to a sequence of one-dimensional minimization problems. Simple examples demonstrate that the MM algorithm derived can converge to a boundary point or to one point of a continuum of minimum points. Conditions under which the minimum point is unique or occurs in the interior of parameter space are proved for geometric programming. Convergence to an interior point occurs at a linear rate. Finally, the MM framework easily accommodates equality and inequality constraints of signomial type. For the most important special case, constrained quadratic programming, the MM algorithm involves very simple updates.

Software Modules for the Proximity-1 Space Link Interleaved Time Synchronization (PITS) Protocol

Science.gov (United States)

Woo, Simon S.; Veregge, John R.; Gao, Jay L.; Clare, Loren P.; Mills, David

2012-01-01

The Proximity-1 Space Link Interleaved Time Synchronization (PITS) protocol provides time distribution and synchronization services for space systems. A software prototype implementation of the PITS algorithm has been developed that also provides the test harness to evaluate the key functionalities of PITS with simulated data source and sink. PITS integrates time synchronization functionality into the link layer of the CCSDS Proximity-1 Space Link Protocol. The software prototype implements the network packet format, data structures, and transmit- and receive-timestamp function for a time server and a client. The software also simulates the transmit and receive-time stamp exchanges via UDP (User Datagram Protocol) socket between a time server and a time client, and produces relative time offsets and delay estimates.

Correlation analysis of alveolar bone loss in buccal/palatal and proximal surfaces in rats

Directory of Open Access Journals (Sweden)

Carolina Barrera de Azambuja

2012-12-01

Full Text Available The aim was to correlate alveolar bone loss in the buccal/palatal and the mesial/distal surfaces of upper molars in rats. Thirty-three, 60-day-old, male Wistar rats were divided in two groups, one treated with alcohol and the other not treated with alcohol. All rats received silk ligatures on the right upper second molars for 4 weeks. The rats were then euthanized and their maxillae were split and defleshed with sodium hypochlorite (9%. The cemento-enamel junction (CEJ was stained with 1% methylene blue and the alveolar bone loss in the buccal/palatal surfaces was measured linearly in 5 points on standardized digital photographs. Measurement of the proximal sites was performed by sectioning the hemimaxillae, restaining the CEJ and measuring the alveolar bone loss linearly in 3 points. A calibrated and blinded examiner performed all the measurements. Intraclass Correlation Coefficient revealed values of 0.96 and 0.89 for buccal/lingual and proximal surfaces, respectively. The Pearson Correlation Coefficient (r between measurements in buccal/palatal and proximal surfaces was 0.35 and 0.05 for the group treated with alcohol, with and without ligatures, respectively. The best correlations between buccal/palatal and proximal surfaces were observed in animals not treated with alcohol, in sites both with and without ligatures (r = 0.59 and 0.65, respectively. A positive correlation was found between alveolar bone loss in buccal/palatal and proximal surfaces. The correlation is stronger in animals that were not treated with alcohol, in sites without ligatures. Areas with and without ligature-induced periodontal destruction allow detection of alveolar bone loss in buccal/palatal and proximal surfaces.

Best Proximity Point Results in Complex Valued Metric Spaces

Directory of Open Access Journals (Sweden)

Binayak S. Choudhury

2014-01-01

complex valued metric spaces. We treat the problem as that of finding the global optimal solution of a fixed point equation although the exact solution does not in general exist. We also define and use the concept of P-property in such spaces. Our results are illustrated with examples.

Common iliac vein thrombosis as a result of proximal venous stenosis following renal transplantation: A case report

Directory of Open Access Journals (Sweden)

Atish Chopra

2016-12-01

Full Text Available Proximal iliac vein stenosis resulting in iliac vein thrombus and venous outflow obstruction in renal transplant patients is an exceedingly rare occurrence. We present a case of a 63-year-old male who underwent deceased donor renal transplantation and presented 12 days later with ipsilateral lower extremity swelling and plateauing serum creatinine. Further work-up demonstrated proximal iliac vein deep venous thrombosis and anticoagulation was initiated. However, propagation of the thrombus developed despite receiving therapeutic anticoagulation. Subsequent venography demonstrated proximal iliac venous stenosis and the patient underwent successful catheter-directed alteplase thrombolysis, inferior vena cava filter placement and iliac vein stenting with salvage of the renal allograft. A diagnostic strategy and management algorithm for iliac vein stenosis and thrombosis in a renal transplant recipient is proposed.

Proximal Alternating Direction Method with Relaxed Proximal Parameters for the Least Squares Covariance Adjustment Problem

Directory of Open Access Journals (Sweden)

Minghua Xu

2014-01-01

Full Text Available We consider the problem of seeking a symmetric positive semidefinite matrix in a closed convex set to approximate a given matrix. This problem may arise in several areas of numerical linear algebra or come from finance industry or statistics and thus has many applications. For solving this class of matrix optimization problems, many methods have been proposed in the literature. The proximal alternating direction method is one of those methods which can be easily applied to solve these matrix optimization problems. Generally, the proximal parameters of the proximal alternating direction method are greater than zero. In this paper, we conclude that the restriction on the proximal parameters can be relaxed for solving this kind of matrix optimization problems. Numerical experiments also show that the proximal alternating direction method with the relaxed proximal parameters is convergent and generally has a better performance than the classical proximal alternating direction method.

Customizing Extensor Reconstruction in Vascularized Toe Joint Transfers to Finger Proximal Interphalangeal Joints: A Strategic Approach for Correcting Extensor Lag.

Science.gov (United States)

Loh, Charles Yuen Yung; Hsu, Chung-Chen; Lin, Cheng-Hung; Chen, Shih-Heng; Lien, Shwu-Huei; Lin, Chih-Hung; Wei, Fu-Chan; Lin, Yu-Te

2017-04-01

Vascularized toe proximal interphalangeal joint transfer allows the restoration of damaged joints. However, extensor lag and poor arc of motion have been reported. The authors present their outcomes of treatment according to a novel reconstructive algorithm that addresses extensor lag and allows for consistent results postoperatively. Vascularized toe joint transfers were performed in a consecutive series of 26 digits in 25 patients. The average age was 30.5 years, with 14 right and 12 left hands. Reconstructed digits included eight index, 10 middle, and eight ring fingers. Simultaneous extensor reconstructions were performed and eight were centralization of lateral bands, five were direct extensor digitorum longus-to-extensor digitorum communis repairs, and 13 were central slip reconstructions. The average length of follow-up was 16.7 months. The average extension lag was 17.9 degrees. The arc of motion was 57.7 degrees (81.7 percent functional use of pretransfer toe proximal interphalangeal joint arc of motion). There was no significant difference in the reconstructed proximal interphalangeal joint arc of motion for the handedness (p = 0.23), recipient digits (p = 0.37), or surgical experience in vascularized toe joint transfer (p = 0.25). The outcomes of different techniques of extensor mechanism reconstruction were similar in terms of extensor lag, arc of motion, and reconstructed finger arc of motion compared with the pretransfer toe proximal interphalangeal joint arc of motion. With this treatment algorithm, consistent outcomes can be produced with minimal extensor lag and maximum use of potential toe proximal interphalangeal joint arc of motion. Therapeutic, IV.

Genetic algorithms optimized fuzzy logic control for the maximum power point tracking in photovoltaic system

Energy Technology Data Exchange (ETDEWEB)

Larbes, C.; Ait Cheikh, S.M.; Obeidi, T.; Zerguerras, A. [Laboratoire des Dispositifs de Communication et de Conversion Photovoltaique, Departement d' Electronique, Ecole Nationale Polytechnique, 10, Avenue Hassen Badi, El Harrach, Alger 16200 (Algeria)

2009-10-15

This paper presents an intelligent control method for the maximum power point tracking (MPPT) of a photovoltaic system under variable temperature and irradiance conditions. First, for the purpose of comparison and because of its proven and good performances, the perturbation and observation (P and O) technique is briefly introduced. A fuzzy logic controller based MPPT (FLC) is then proposed which has shown better performances compared to the P and O MPPT based approach. The proposed FLC has been also improved using genetic algorithms (GA) for optimisation. Different development stages are presented and the optimized fuzzy logic MPPT controller (OFLC) is then simulated and evaluated, which has shown better performances. (author)

Calculating Graph Algorithms for Dominance and Shortest Path

DEFF Research Database (Denmark)

Sergey, Ilya; Midtgaard, Jan; Clarke, Dave

2012-01-01

We calculate two iterative, polynomial-time graph algorithms from the literature: a dominance algorithm and an algorithm for the single-source shortest path problem. Both algorithms are calculated directly from the definition of the properties by fixed-point fusion of (1) a least fixed point...... expressing all finite paths through a directed graph and (2) Galois connections that capture dominance and path length. The approach illustrates that reasoning in the style of fixed-point calculus extends gracefully to the domain of graph algorithms. We thereby bridge common practice from the school...... of program calculation with common practice from the school of static program analysis, and build a novel view on iterative graph algorithms as instances of abstract interpretation...

Dynamic Harmony Search with Polynomial Mutation Algorithm for Valve-Point Economic Load Dispatch

Directory of Open Access Journals (Sweden)

M. Karthikeyan

2015-01-01

mutation (DHSPM algorithm to solve ORPD problem. In DHSPM algorithm the key parameters of HS algorithm like harmony memory considering rate (HMCR and pitch adjusting rate (PAR are changed dynamically and there is no need to predefine these parameters. Additionally polynomial mutation is inserted in the updating step of HS algorithm to favor exploration and exploitation of the search space. The DHSPM algorithm is tested with three power system cases consisting of 3, 13, and 40 thermal units. The computational results show that the DHSPM algorithm is more effective in finding better solutions than other computational intelligence based methods.

Current review and a simplified "five-point management algorithm" for keratoconus

Directory of Open Access Journals (Sweden)

Rohit Shetty

2015-01-01

Full Text Available Keratoconus is a slowly progressive, noninflammatory ectatic corneal disease characterized by changes in corneal collagen structure and organization. Though the etiology remains unknown, novel techniques are continuously emerging for the diagnosis and management of the disease. Demographical parameters are known to affect the rate of progression of the disease. Common methods of vision correction for keratoconus range from spectacles and rigid gas-permeable contact lenses to other specialized lenses such as piggyback, Rose-K or Boston scleral lenses. Corneal collagen cross-linking is effective in stabilizing the progression of the disease. Intra-corneal ring segments can improve vision by flattening the cornea in patients with mild to moderate keratoconus. Topography-guided custom ablation treatment betters the quality of vision by correcting the refractive error and improving the contact lens fit. In advanced keratoconus with corneal scarring, lamellar or full thickness penetrating keratoplasty will be the treatment of choice. With such a wide spectrum of alternatives available, it is necessary to choose the best possible treatment option for each patient. Based on a brief review of the literature and our own studies we have designed a five-point management algorithm for the treatment of keratoconus.

Music analysis and point-set compression

DEFF Research Database (Denmark)

Meredith, David

2015-01-01

COSIATEC, SIATECCompress and Forth’s algorithm are point-set compression algorithms developed for discovering repeated patterns in music, such as themes and motives that would be of interest to a music analyst. To investigate their effectiveness and versatility, these algorithms were evaluated...... on three analytical tasks that depend on the discovery of repeated patterns: classifying folk song melodies into tune families, discovering themes and sections in polyphonic music, and discovering subject and countersubject entries in fugues. Each algorithm computes a compressed encoding of a point......-set representation of a musical object in the form of a list of compact patterns, each pattern being given with a set of vectors indicating its occurrences. However, the algorithms adopt different strategies in their attempts to discover encodings that maximize compression.The best-performing algorithm on the folk...

Proximity credentials: A survey

International Nuclear Information System (INIS)

Wright, L.J.

1987-04-01

Credentials as a means of identifying individuals have traditionally been a photo badge and more recently, the coded credential. Another type of badge, the proximity credential, is making inroads in the personnel identification field. This badge can be read from a distance instead of being veiewed by a guard or inserted into a reading device. This report reviews proximity credentials, identifies the companies marketing or developing proximity credentials, and describes their respective credentials. 3 tabs

Computer-Based Algorithmic Determination of Muscle Movement Onset Using M-Mode Ultrasonography

Science.gov (United States)

2017-05-01

statistical analysis. Given the large number of MO algorithms, poorly performing algorithms were systematically eliminated from further evaluation. First...very large data sets (Kaufman and Rousseeuw 2005). The three algo- rithms with the closest proximity (i.e., highest similarity) to the gold-standard...but lowering the thresholds will likely increase the chances of premature onset detection. Additionally, although theFig. 4. Forest plot of mean

In-Place Algorithms for Computing (Layers of) Maxima

DEFF Research Database (Denmark)

Blunck, Henrik; Vahrenhold, Jan

2010-01-01

We describe space-efficient algorithms for solving problems related to finding maxima among points in two and three dimensions. Our algorithms run in optimal time and occupy only constant extra......We describe space-efficient algorithms for solving problems related to finding maxima among points in two and three dimensions. Our algorithms run in optimal time and occupy only constant extra...

Fast Change Point Detection for Electricity Market Analysis

Energy Technology Data Exchange (ETDEWEB)

Berkeley, UC; Gu, William; Choi, Jaesik; Gu, Ming; Simon, Horst; Wu, Kesheng

2013-08-25

Electricity is a vital part of our daily life; therefore it is important to avoid irregularities such as the California Electricity Crisis of 2000 and 2001. In this work, we seek to predict anomalies using advanced machine learning algorithms. These algorithms are effective, but computationally expensive, especially if we plan to apply them on hourly electricity market data covering a number of years. To address this challenge, we significantly accelerate the computation of the Gaussian Process (GP) for time series data. In the context of a Change Point Detection (CPD) algorithm, we reduce its computational complexity from O($n^{5}$) to O($n^{2}$). Our efficient algorithm makes it possible to compute the Change Points using the hourly price data from the California Electricity Crisis. By comparing the detected Change Points with known events, we show that the Change Point Detection algorithm is indeed effective in detecting signals preceding major events.

Robust non-rigid point set registration using student's-t mixture model.

Directory of Open Access Journals (Sweden)

Zhiyong Zhou

Full Text Available The Student's-t mixture model, which is heavily tailed and more robust than the Gaussian mixture model, has recently received great attention on image processing. In this paper, we propose a robust non-rigid point set registration algorithm using the Student's-t mixture model. Specifically, first, we consider the alignment of two point sets as a probability density estimation problem and treat one point set as Student's-t mixture model centroids. Then, we fit the Student's-t mixture model centroids to the other point set which is treated as data. Finally, we get the closed-form solutions of registration parameters, leading to a computationally efficient registration algorithm. The proposed algorithm is especially effective for addressing the non-rigid point set registration problem when significant amounts of noise and outliers are present. Moreover, less registration parameters have to be set manually for our algorithm compared to the popular coherent points drift (CPD algorithm. We have compared our algorithm with other state-of-the-art registration algorithms on both 2D and 3D data with noise and outliers, where our non-rigid registration algorithm showed accurate results and outperformed the other algorithms.

Proximity to Fast-Food Outlets and Supermarkets as Predictors of Fast-Food Dining Frequency.

Science.gov (United States)

Athens, Jessica K; Duncan, Dustin T; Elbel, Brian

2016-08-01

This study used cross-sectional data to test the independent relationship of proximity to chain fast-food outlets and proximity to full-service supermarkets on the frequency of mealtime dining at fast-food outlets in two major urban areas, using three approaches to define access. Interactions between presence of a supermarket and presence of fast-food outlets as predictors of fast-food dining were also tested. Residential intersections for respondents in point-of-purchase and random-digit-dial telephone surveys of adults in Philadelphia, PA, and Baltimore, MD, were geocoded. The count of fast-food outlets and supermarkets within quarter-mile, half-mile, and 1-mile street network buffers around each respondent's intersection was calculated, as well as distance to the nearest fast-food outlet and supermarket. These variables were regressed on weekly fast-food dining frequency to determine whether proximity to fast food and supermarkets had independent and joint effects on fast-food dining. The effect of access to supermarkets and chain fast-food outlets varied by study population. Among telephone survey respondents, supermarket access was the only significant predictor of fast-food dining frequency. Point-of-purchase respondents were generally unaffected by proximity to either supermarkets or fast-food outlets. However, ≥1 fast-food outlet within a 1-mile buffer was an independent predictor of consuming more fast-food meals among point-of-purchase respondents. At the quarter-mile distance, ≥1 supermarket was predictive of fewer fast-food meals. Supermarket access was associated with less fast-food dining among telephone respondents, whereas access to fast-food outlets were associated with more fast-food visits among survey respondents identified at point-of-purchase. This study adds to the existing literature on geographic determinants of fast-food dining behavior among urban adults in the general population and those who regularly consume fast food. Copyright �

Automatic markerless registration of point clouds with semantic-keypoint-based 4-points congruent sets

Science.gov (United States)

Ge, Xuming

2017-08-01

The coarse registration of point clouds from urban building scenes has become a key topic in applications of terrestrial laser scanning technology. Sampling-based algorithms in the random sample consensus (RANSAC) model have emerged as mainstream solutions to address coarse registration problems. In this paper, we propose a novel combined solution to automatically align two markerless point clouds from building scenes. Firstly, the method segments non-ground points from ground points. Secondly, the proposed method detects feature points from each cross section and then obtains semantic keypoints by connecting feature points with specific rules. Finally, the detected semantic keypoints from two point clouds act as inputs to a modified 4PCS algorithm. Examples are presented and the results compared with those of K-4PCS to demonstrate the main contributions of the proposed method, which are the extension of the original 4PCS to handle heavy datasets and the use of semantic keypoints to improve K-4PCS in relation to registration accuracy and computational efficiency.

A Fast and Accurate Algorithm for l1 Minimization Problems in Compressive Sampling (Preprint)

Science.gov (United States)

2013-01-22

However, updating uk+1 via the formulation of Step 2 in Algorithm 1 can be implemented through the use of the component-wise Gauss - Seidel iteration which...may accelerate the rate of convergence of the algorithm and therefore reduce the total CPU-time consumed. The efficiency of component-wise Gauss - Seidel ...Micchelli, L. Shen, and Y. Xu, A proximity algorithm accelerated by Gauss - Seidel iterations for L1/TV denoising models, Inverse Problems, 28 (2012), p

A new algorithm combining geostatistics with the surrogate data approach to increase the accuracy of comparisons of point radiation measurements with cloud measurements

Science.gov (United States)

Venema, V. K. C.; Lindau, R.; Varnai, T.; Simmer, C.

2009-04-01

Two main groups of statistical methods used in the Earth sciences are geostatistics and stochastic modelling. Geostatistical methods, such as various kriging algorithms, aim at estimating the mean value for every point as well as possible. In case of sparse measurements, such fields have less variability at small scales and a narrower distribution as the true field. This can lead to biases if a nonlinear process is simulated on such a kriged field. Stochastic modelling aims at reproducing the structure of the data. One of the stochastic modelling methods, the so-called surrogate data approach, replicates the value distribution and power spectrum of a certain data set. However, while stochastic methods reproduce the statistical properties of the data, the location of the measurement is not considered. Because radiative transfer through clouds is a highly nonlinear process it is essential to model the distribution (e.g. of optical depth, extinction, liquid water content or liquid water path) accurately as well as the correlations in the cloud field because of horizontal photon transport. This explains the success of surrogate cloud fields for use in 3D radiative transfer studies. However, up to now we could only achieve good results for the radiative properties averaged over the field, but not for a radiation measurement located at a certain position. Therefore we have developed a new algorithm that combines the accuracy of stochastic (surrogate) modelling with the positioning capabilities of kriging. In this way, we can automatically profit from the large geostatistical literature and software. The algorithm is tested on cloud fields from large eddy simulations (LES). On these clouds a measurement is simulated. From the pseudo-measurement we estimated the distribution and power spectrum. Furthermore, the pseudo-measurement is kriged to a field the size of the final surrogate cloud. The distribution, spectrum and the kriged field are the inputs to the algorithm. This

Handbook of floating-point arithmetic

CERN Document Server

Muller, Jean-Michel; de Dinechin, Florent; Jeannerod, Claude-Pierre; Joldes, Mioara; Lefèvre, Vincent; Melquiond, Guillaume; Revol, Nathalie; Torres, Serge

2018-01-01

This handbook is a definitive guide to the effective use of modern floating-point arithmetic, which has considerably evolved, from the frequently inconsistent floating-point number systems of early computing to the recent IEEE 754-2008 standard. Most of computational mathematics depends on floating-point numbers, and understanding their various implementations will allow readers to develop programs specifically tailored for the standard’s technical features. Algorithms for floating-point arithmetic are presented throughout the book and illustrated where possible by example programs which show how these techniques appear in actual coding and design. The volume itself breaks its core topic into four parts: the basic concepts and history of floating-point arithmetic; methods of analyzing floating-point algorithms and optimizing them; implementations of IEEE 754-2008 in hardware and software; and useful extensions to the standard floating-point system, such as interval arithmetic, double- and triple-word arithm...

Fine-scale estimation of carbon monoxide and fine particulate matter concentrations in proximity to a road intersection by using wavelet neural network with genetic algorithm

Science.gov (United States)

Wang, Zhanyong; Lu, Feng; He, Hong-di; Lu, Qing-Chang; Wang, Dongsheng; Peng, Zhong-Ren

2015-03-01

At road intersections, vehicles frequently stop with idling engines during the red-light period and speed up rapidly in the green-light period, which generates higher velocity fluctuation and thus higher emission rates. Additionally, the frequent changes of wind direction further add the highly variable dispersion of pollutants at the street scale. It is, therefore, very difficult to estimate the distribution of pollutant concentrations using conventional deterministic causal models. For this reason, a hybrid model combining wavelet neural network and genetic algorithm (GA-WNN) is proposed for predicting 5-min series of carbon monoxide (CO) and fine particulate matter (PM2.5) concentrations in proximity to an intersection. The proposed model is examined based on the measured data under two situations. As the measured pollutant concentrations are found to be dependent on the distance to the intersection, the model is evaluated in three locations respectively, i.e. 110 m, 330 m and 500 m. Due to the different variation of pollutant concentrations on varied time, the model is also evaluated in peak and off-peak traffic time periods separately. Additionally, the proposed model, together with the back-propagation neural network (BPNN), is examined with the measured data in these situations. The proposed model is found to perform better in predictability and precision for both CO and PM2.5 than BPNN does, implying that the hybrid model can be an effective tool to improve the accuracy of estimating pollutants' distribution pattern at intersections. The outputs of these findings demonstrate the potential of the proposed model to be applicable to forecast the distribution pattern of air pollution in real-time in proximity to road intersection.

Online co-regularized algorithms

NARCIS (Netherlands)

Ruijter, T. de; Tsivtsivadze, E.; Heskes, T.

2012-01-01

We propose an online co-regularized learning algorithm for classification and regression tasks. We demonstrate that by sequentially co-regularizing prediction functions on unlabeled data points, our algorithm provides improved performance in comparison to supervised methods on several UCI benchmarks

Variability of United States Online Rehabilitation Protocols for Proximal Hamstring Tendon Repair.

Science.gov (United States)

Lightsey, Harry M; Kantrowitz, David E; Swindell, Hasani W; Trofa, David P; Ahmad, Christopher S; Lynch, T Sean

2018-02-01

The optimal postoperative rehabilitation protocol following repair of complete proximal hamstring tendon ruptures is the subject of ongoing investigation, with a need for more standardized regimens and evidence-based modalities. To assess the variability across proximal hamstring tendon repair rehabilitation protocols published online by United States (US) orthopaedic teaching programs. Cross-sectional study. Online proximal hamstring physical therapy protocols from US academic orthopaedic programs were reviewed. A web-based search using the search term complete proximal hamstring repair rehabilitation protocol provided an additional 14 protocols. A comprehensive scoring rubric was developed after review of all protocols and was used to assess each protocol for both the presence of various rehabilitation components and the point at which those components were introduced. Of 50 rehabilitation protocols identified, 35 satisfied inclusion criteria and were analyzed. Twenty-five protocols (71%) recommended immediate postoperative bracing: 12 (34%) prescribed knee bracing, 8 (23%) prescribed hip bracing, and 5 (14%) did not specify the type of brace recommended. Fourteen protocols (40%) advised immediate nonweightbearing with crutches, while 16 protocols (46%) permitted immediate toe-touch weightbearing. Advancement to full weightbearing was allowed at a mean of 7.1 weeks (range, 4-12 weeks). Most protocols (80%) recommended gentle knee and hip passive range of motion and active range of motion, starting at a mean 1.4 weeks (range, 0-3 weeks) and 4.0 weeks (range, 0-6 weeks), respectively. However, only 6 protocols (17%) provided specific time points to initiate full hip and knee range of motion: a mean 8.0 weeks (range, 4-12 weeks) and 7.8 weeks (range, 0-12 weeks), respectively. Considerable variability was noted in the inclusion and timing of strengthening, stretching, proprioception, and cardiovascular exercises. Fifteen protocols (43%) required completion of

A quasi-Newton algorithm for large-scale nonlinear equations

Directory of Open Access Journals (Sweden)

Linghua Huang

2017-02-01

Full Text Available Abstract In this paper, the algorithm for large-scale nonlinear equations is designed by the following steps: (i a conjugate gradient (CG algorithm is designed as a sub-algorithm to obtain the initial points of the main algorithm, where the sub-algorithm’s initial point does not have any restrictions; (ii a quasi-Newton algorithm with the initial points given by sub-algorithm is defined as main algorithm, where a new nonmonotone line search technique is presented to get the step length α k $\\alpha_{k}$ . The given nonmonotone line search technique can avoid computing the Jacobian matrix. The global convergence and the 1 + q $1+q$ -order convergent rate of the main algorithm are established under suitable conditions. Numerical results show that the proposed method is competitive with a similar method for large-scale problems.

Diagnostic accuracy of T stage of gastric cancer from the view point of application of laparoscopic proximal gastrectomy.

Science.gov (United States)

Kouzu, Keita; Tsujimoto, Hironori; Hiraki, Shuichi; Nomura, Shinsuke; Yamamoto, Junji; Ueno, Hideki

2018-06-01

The preoperative diagnosis of T stage is important in selecting limited treatments, such as laparoscopic proximal gastrectomy (LPG), which lacks the ability to palpate the tumor. Therefore, the present study examined the accuracy of preoperative diagnosis of the depth of tumor invasion in early gastric cancer from the view point of the indication for LPG. A total of 193 patients with cT1 gastric cancer underwent LPG with gastrointestinal endoscopic examinations and a series of upper gastrointestinal radiographs. The patients with pT1 were classified into the correctly diagnosed group (163 patients, 84.5%), and those with pT2 or deeper were classified into the underestimated group (30 patients, 15.5%). Factors that were associated with underestimation of tumor depth were analyzed. Tumor size in the underestimated group was significantly larger; the lesions were more frequently located in the upper third of the stomach and were more histologically diffuse, scirrhous, with infiltrative growth, and more frequent lymphatic and venous invasion. For upper third lesions, in univariate analysis, histology (diffuse type) was associated with underestimation of tumor depth. Multivariate analysis found that tumor size (≥20 mm) and histology (diffuse type) were independently associated with underestimation of tumor depth. gastric cancer in the upper third of the stomach with diffuse type histology and >20 mm needs particular attention when considering the application of LPG.

Elementary functions algorithms and implementation

CERN Document Server

Muller, Jean-Michel

2016-01-01

This textbook presents the concepts and tools necessary to understand, build, and implement algorithms for computing elementary functions (e.g., logarithms, exponentials, and the trigonometric functions). Both hardware- and software-oriented algorithms are included, along with issues related to accurate floating-point implementation. This third edition has been updated and expanded to incorporate the most recent advances in the field, new elementary function algorithms, and function software. After a preliminary chapter that briefly introduces some fundamental concepts of computer arithmetic, such as floating-point arithmetic and redundant number systems, the text is divided into three main parts. Part I considers the computation of elementary functions using algorithms based on polynomial or rational approximations and using table-based methods; the final chapter in this section deals with basic principles of multiple-precision arithmetic. Part II is devoted to a presentation of “shift-and-add” algorithm...

Multiple intramedullary nailing of proximal phalangeal fractures of hand

Directory of Open Access Journals (Sweden)

Patankar Hemant

2008-01-01

Full Text Available Background: Proximal phalangeal fractures are commonly encountered fractures in the hand. Majority of them are stable and can be treated by non-operative means. However, unstable fractures i.e. those with shortening, displacement, angulation, rotational deformity or segmental fractures need surgical intervention. This prospective study was undertaken to evaluate the functional outcome after surgical stabilization of these fractures with joint-sparing multiple intramedullary nailing technique. Materials and Methods: Thirty-five patients with 35 isolated unstable proximal phalangeal shaft fractures of hand were managed by surgical stabilization with multiple intramedullary nailing technique. Fractures of the thumb were excluded. All the patients were followed up for a minimum of six months. They were assessed radiologically and clinically. The clinical evaluation was based on two criteria. 1. total active range of motion for digital functional assessment as suggested by the American Society for Surgery of Hand and 2. grip strength. Results: All the patients showed radiological union at six weeks. The overall results were excellent in all the patients. Adventitious bursitis was observed at the point of insertion of nails in one patient. Conclusion: Joint-sparing multiple intramedullary nailing of unstable proximal phalangeal fractures of hand provides satisfactory results with good functional outcome and fewer complications.

Proximal methods for the resolution of inverse problems: application to positron emission tomography

International Nuclear Information System (INIS)

Pustelnik, N.

2010-12-01

The objective of this work is to propose reliable, efficient and fast methods for minimizing convex criteria, that are found in inverse problems for imagery. We focus on restoration/reconstruction problems when data is degraded with both a linear operator and noise, where the latter is not assumed to be necessarily additive.The reliability of the method is ensured through the use of proximal algorithms, the convergence of which is guaranteed when a convex criterion is considered. Efficiency is sought through the choice of criteria adapted to the noise characteristics, the linear operators and the image specificities. Of particular interest are regularization terms based on total variation and/or sparsity of signal frame coefficients. As a consequence of the use of frames, two approaches are investigated, depending on whether the analysis or the synthesis formulation is chosen. Fast processing requirements lead us to consider proximal algorithms with a parallel structure. Theoretical results are illustrated on several large size inverse problems arising in image restoration, stereoscopy, multi-spectral imagery and decomposition into texture and geometry components. We focus on a particular application, namely Positron Emission Tomography (PET), which is particularly difficult because of the presence of a projection operator combined with Poisson noise, leading to highly corrupted data. To optimize the quality of the reconstruction, we make use of the spatio-temporal characteristics of brain tissue activity. (author)

Image Registration Algorithm Based on Parallax Constraint and Clustering Analysis

Science.gov (United States)

Wang, Zhe; Dong, Min; Mu, Xiaomin; Wang, Song

2018-01-01

To resolve the problem of slow computation speed and low matching accuracy in image registration, a new image registration algorithm based on parallax constraint and clustering analysis is proposed. Firstly, Harris corner detection algorithm is used to extract the feature points of two images. Secondly, use Normalized Cross Correlation (NCC) function to perform the approximate matching of feature points, and the initial feature pair is obtained. Then, according to the parallax constraint condition, the initial feature pair is preprocessed by K-means clustering algorithm, which is used to remove the feature point pairs with obvious errors in the approximate matching process. Finally, adopt Random Sample Consensus (RANSAC) algorithm to optimize the feature points to obtain the final feature point matching result, and the fast and accurate image registration is realized. The experimental results show that the image registration algorithm proposed in this paper can improve the accuracy of the image matching while ensuring the real-time performance of the algorithm.

Pose estimation for augmented reality applications using genetic algorithm.

Science.gov (United States)

Yu, Ying Kin; Wong, Kin Hong; Chang, Michael Ming Yuen

2005-12-01

This paper describes a genetic algorithm that tackles the pose-estimation problem in computer vision. Our genetic algorithm can find the rotation and translation of an object accurately when the three-dimensional structure of the object is given. In our implementation, each chromosome encodes both the pose and the indexes to the selected point features of the object. Instead of only searching for the pose as in the existing work, our algorithm, at the same time, searches for a set containing the most reliable feature points in the process. This mismatch filtering strategy successfully makes the algorithm more robust under the presence of point mismatches and outliers in the images. Our algorithm has been tested with both synthetic and real data with good results. The accuracy of the recovered pose is compared to the existing algorithms. Our approach outperformed the Lowe's method and the other two genetic algorithms under the presence of point mismatches and outliers. In addition, it has been used to estimate the pose of a real object. It is shown that the proposed method is applicable to augmented reality applications.

Simulation and analysis of an isolated full-bridge DC/DC boost converter operating with a modified perturb and observe maximum power point tracking algorithm

Directory of Open Access Journals (Sweden)

Calebe A. Matias

2017-07-01

Full Text Available The purpose of the present study is to simulate and analyze an isolated full-bridge DC/DC boost converter, for photovoltaic panels, running a modified perturb and observe maximum power point tracking method. The zero voltage switching technique was used in order to minimize the losses of the converter for a wide range of solar operation. The efficiency of the power transfer is higher than 90% for large solar operating points. The panel enhancement due to the maximum power point tracking algorithm is 5.06%.

Quantum multiple scattering: Eigenmode expansion and its applications to proximity resonance

International Nuclear Information System (INIS)

Li Sheng; Heller, Eric J.

2003-01-01

We show that for a general system of N s-wave point scatterers, there are always N eigenmodes. These eigenmodes or eigenchannels play the same role as spherical harmonics for a spherically symmetric target--they give a phase shift only. In other words, the T matrix of the system is of rank N, and the eigenmodes are eigenvectors corresponding to nonzero eigenvalues of the T matrix. The eigenmode expansion approach can give insight to the total scattering cross section; the position, width, and superradiant or subradiant nature of resonance peaks; the unsymmetric Fano line shape of sharp proximity resonance peaks based on the high-energy tail of a broadband; and other properties. Off-resonant eigenmodes for identical proximate scatterers are approximately angular-momentum eigenstates

A Combined Approach to Cartographic Displacement for Buildings Based on Skeleton and Improved Elastic Beam Algorithm

Science.gov (United States)

Liu, Yuangang; Guo, Qingsheng; Sun, Yageng; Ma, Xiaoya

2014-01-01

Scale reduction from source to target maps inevitably leads to conflicts of map symbols in cartography and geographic information systems (GIS). Displacement is one of the most important map generalization operators and it can be used to resolve the problems that arise from conflict among two or more map objects. In this paper, we propose a combined approach based on constraint Delaunay triangulation (CDT) skeleton and improved elastic beam algorithm for automated building displacement. In this approach, map data sets are first partitioned. Then the displacement operation is conducted in each partition as a cyclic and iterative process of conflict detection and resolution. In the iteration, the skeleton of the gap spaces is extracted using CDT. It then serves as an enhanced data model to detect conflicts and construct the proximity graph. Then, the proximity graph is adjusted using local grouping information. Under the action of forces derived from the detected conflicts, the proximity graph is deformed using the improved elastic beam algorithm. In this way, buildings are displaced to find an optimal compromise between related cartographic constraints. To validate this approach, two topographic map data sets (i.e., urban and suburban areas) were tested. The results were reasonable with respect to each constraint when the density of the map was not extremely high. In summary, the improvements include (1) an automated parameter-setting method for elastic beams, (2) explicit enforcement regarding the positional accuracy constraint, added by introducing drag forces, (3) preservation of local building groups through displacement over an adjusted proximity graph, and (4) an iterative strategy that is more likely to resolve the proximity conflicts than the one used in the existing elastic beam algorithm. PMID:25470727

Extreme-Scale Algorithms & Software Resilience (EASIR) Architecture-Aware Algorithms for Scalable Performance and Resilience on Heterogeneous Architectures

Energy Technology Data Exchange (ETDEWEB)

Demmel, James W. [Univ. of California, Berkeley, CA (United States)

2017-09-14

This project addresses both communication-avoiding algorithms, and reproducible floating-point computation. Communication, i.e. moving data, either between levels of memory or processors over a network, is much more expensive per operation than arithmetic (measured in time or energy), so we seek algorithms that greatly reduce communication. We developed many new algorithms for both dense and sparse, and both direct and iterative linear algebra, attaining new communication lower bounds, and getting large speedups in many cases. We also extended this work in several ways: (1) We minimize writes separately from reads, since writes may be much more expensive than reads on emerging memory technologies, like Flash, sometimes doing asymptotically fewer writes than reads. (2) We extend the lower bounds and optimal algorithms to arbitrary algorithms that may be expressed as perfectly nested loops accessing arrays, where the array subscripts may be arbitrary affine functions of the loop indices (eg A(i), B(i,j+k, k+3*m-7, …) etc.). (3) We extend our communication-avoiding approach to some machine learning algorithms, such as support vector machines. This work has won a number of awards. We also address reproducible floating-point computation. We define reproducibility to mean getting bitwise identical results from multiple runs of the same program, perhaps with different hardware resources or other changes that should ideally not change the answer. Many users depend on reproducibility for debugging or correctness. However, dynamic scheduling of parallel computing resources, combined with nonassociativity of floating point addition, makes attaining reproducibility a challenge even for simple operations like summing a vector of numbers, or more complicated operations like the Basic Linear Algebra Subprograms (BLAS). We describe an algorithm that computes a reproducible sum of floating point numbers, independent of the order of summation. The algorithm depends only on a

Geographically Modified PageRank Algorithms: Identifying the Spatial Concentration of Human Movement in a Geospatial Network.

Science.gov (United States)

Chin, Wei-Chien-Benny; Wen, Tzai-Hung

2015-01-01

A network approach, which simplifies geographic settings as a form of nodes and links, emphasizes the connectivity and relationships of spatial features. Topological networks of spatial features are used to explore geographical connectivity and structures. The PageRank algorithm, a network metric, is often used to help identify important locations where people or automobiles concentrate in the geographical literature. However, geographic considerations, including proximity and location attractiveness, are ignored in most network metrics. The objective of the present study is to propose two geographically modified PageRank algorithms-Distance-Decay PageRank (DDPR) and Geographical PageRank (GPR)-that incorporate geographic considerations into PageRank algorithms to identify the spatial concentration of human movement in a geospatial network. Our findings indicate that in both intercity and within-city settings the proposed algorithms more effectively capture the spatial locations where people reside than traditional commonly-used network metrics. In comparing location attractiveness and distance decay, we conclude that the concentration of human movement is largely determined by the distance decay. This implies that geographic proximity remains a key factor in human mobility.

Diversity-Guided Evolutionary Algorithms

DEFF Research Database (Denmark)

Ursem, Rasmus Kjær

2002-01-01

Population diversity is undoubtably a key issue in the performance of evolutionary algorithms. A common hypothesis is that high diversity is important to avoid premature convergence and to escape local optima. Various diversity measures have been used to analyze algorithms, but so far few...... algorithms have used a measure to guide the search. The diversity-guided evolutionary algorithm (DGEA) uses the wellknown distance-to-average-point measure to alternate between phases of exploration (mutation) and phases of exploitation (recombination and selection). The DGEA showed remarkable results...

Perturbation resilience and superiorization of iterative algorithms

International Nuclear Information System (INIS)

Censor, Y; Davidi, R; Herman, G T

2010-01-01

Iterative algorithms aimed at solving some problems are discussed. For certain problems, such as finding a common point in the intersection of a finite number of convex sets, there often exist iterative algorithms that impose very little demand on computer resources. For other problems, such as finding that point in the intersection at which the value of a given function is optimal, algorithms tend to need more computer memory and longer execution time. A methodology is presented whose aim is to produce automatically for an iterative algorithm of the first kind a 'superiorized version' of it that retains its computational efficiency but nevertheless goes a long way toward solving an optimization problem. This is possible to do if the original algorithm is 'perturbation resilient', which is shown to be the case for various projection algorithms for solving the consistent convex feasibility problem. The superiorized versions of such algorithms use perturbations that steer the process in the direction of a superior feasible point, which is not necessarily optimal, with respect to the given function. After presenting these intuitive ideas in a precise mathematical form, they are illustrated in image reconstruction from projections for two different projection algorithms superiorized for the function whose value is the total variation of the image

Residential proximity to agricultural fumigant use and IQ, attention and hyperactivity in 7-year old children.

Science.gov (United States)

Gunier, Robert B; Bradman, Asa; Castorina, Rosemary; Holland, Nina T; Avery, Dylan; Harley, Kim G; Eskenazi, Brenda

2017-10-01

Our objective was to examine the relationship between residential proximity to agricultural fumigant use and neurodevelopment in 7-year old children. Participants were living in the agricultural Salinas Valley, California and enrolled in the Center for the Health Assessment of Mothers and Children Of Salinas (CHAMACOS) study. We administered the Wechsler Intelligence Scale for Children (4th Edition) to assess cognition and the Behavioral Assessment System for Children (2nd Edition) to assess behavior. We estimated agricultural fumigant use within 3, 5 and 8km of residences during pregnancy and from birth to age 7 using California's Pesticide Use Report data. We evaluated the association between prenatal (n = 285) and postnatal (n = 255) residential proximity to agricultural use of methyl bromide, chloropicrin, metam sodium and 1,3-dichloropropene with neurodevelopment. We observed decreases of 2.6 points (95% Confidence Interval (CI): -5.2, 0.0) and 2.4 points (95% CI: -4.7, -0.2) in Full-Scale intelligence quotient for each ten-fold increase in methyl bromide and chloropicrin use within 8km of the child's residences from birth to 7-years of age, respectively. There were no associations between residential proximity to use of other fumigants and cognition or proximity to use of any fumigant and hyperactivity or attention problems. These findings should be explored in larger studies. Copyright © 2017. Published by Elsevier Inc.

Modular endoprosthetic replacement for metastatic tumours of the proximal femur

Directory of Open Access Journals (Sweden)

Carter Simon R

2008-11-01

Full Text Available Abstract Background and aims Endoprosthetic replacements of the proximal femur are commonly required to treat destructive metastases with either impending or actual pathological fractures at this site. Modular prostheses provide an off the shelf availability and can be adapted to most reconstructive situations for proximal femoral replacements. The aim of this study was to assess the clinical and functional outcomes following modular tumour prosthesis reconstruction of the proximal femur in 100 consecutive patients with metastatic tumours and to compare them with the published results of patients with modular and custom made endoprosthetic replacements. Methods 100 consecutive patients who underwent modular tumour prosthetic reconstruction of the proximal femur for metastases using the METS system from 2001 to 2007 were studied. The patient, tumour and treatment factors in relation to overall survival, local control, implant survival and complications were analysed. Functional scores were obtained from surviving patients. Results and conclusion There were 45 male and 55 female patients. The mean age was 60.2 years. The indications were metastases. Seventy five patients presented with pathological fracture or with failed fixation and 25 patients were at a high risk of developing a fracture. The mean follow up was 15.9 months [range 0–77]. Three patients died within 2 weeks following surgery. 69 patients have died and 31 are alive. Of the 69 patients who were dead 68 did not need revision surgery indicating that the implant provided single definitive treatment which outlived the patient. There were three dislocations (2/5 with THR and 1/95 with unipolar femoral heads. 6 patients had deep infections. The estimated five year implant survival (Kaplan-Meier analysis was 83.1% with revision as end point. The mean TESS score was 64% (54%–82%. We conclude that METS modular tumour prosthesis for proximal femur provides versatility; low implant related

Children's proximal societal conditions

DEFF Research Database (Denmark)

Stanek, Anja Hvidtfeldt

2018-01-01

that is above or outside the institutional setting or the children’s everyday life, but something that is represented through societal structures and actual persons participating (in political ways) within the institutional settings, in ways that has meaning to children’s possibilities to participate, learn...... and develop. Understanding school or kindergarten as (part of) the children’s proximal societal conditions for development and learning, means for instance that considerations about an inclusive agenda are no longer simply thoughts about the school – for economic reasons – having space for as many pupils...... as possible (schools for all). Such thoughts can be supplemented by reflections about which version of ‘the societal’ we wish to present our children with, and which version of ‘the societal’ we wish to set up as the condition for children’s participation and development. The point is to clarify or sharpen...

The computation of fixed points and applications

CERN Document Server

Todd, Michael J

1976-01-01

Fixed-point algorithms have diverse applications in economics, optimization, game theory and the numerical solution of boundary-value problems. Since Scarf's pioneering work [56,57] on obtaining approximate fixed points of continuous mappings, a great deal of research has been done in extending the applicability and improving the efficiency of fixed-point methods. Much of this work is available only in research papers, although Scarf's book [58] gives a remarkably clear exposition of the power of fixed-point methods. However, the algorithms described by Scarf have been super~eded by the more sophisticated restart and homotopy techniques of Merrill [~8,~9] and Eaves and Saigal [1~,16]. To understand the more efficient algorithms one must become familiar with the notions of triangulation and simplicial approxi- tion, whereas Scarf stresses the concept of primitive set. These notes are intended to introduce to a wider audience the most recent fixed-point methods and their applications. Our approach is therefore ...

Improved SURF Algorithm and Its Application in Seabed Relief Image Matching

Directory of Open Access Journals (Sweden)

Zhang Hong-Mei

2017-01-01

Full Text Available The matching based on seabed relief image is widely used in underwater relief matching navigation and target recognition, etc. However, being influenced by various factors, some conventional matching algorithms are difficult to obtain an ideal result in the matching of seabed relief image. SURF(Speeded Up Robust Features algorithm is based on feature points pair to achieve matching, and can get good results in the seabed relief image matching. However, in practical applications, the traditional SURF algorithm is easy to get false matching, especially when the area’s features are similar or not obvious, the problem is more seriously. In order to improve the robustness of the algorithm, this paper proposes an improved matching algorithm, which combines the SURF, and RANSAC (Random Sample Consensus algorithms. The new algorithm integrates the two algorithms advantages, firstly, the SURF algorithm is applied to detect and extract the feature points then to pre-match. Secondly, RANSAC algorithm is utilized to eliminate mismatching points, and then the accurate matching is accomplished with the correct matching points. The experimental results show that the improved algorithm overcomes the mismatching problem effectively and have better precision and faster speed than the traditional SURF algorithm.

Algorithmic Verification of Linearizability for Ordinary Differential Equations

KAUST Repository

Lyakhov, Dmitry A.; Gerdt, Vladimir P.; Michels, Dominik L.

2017-01-01

one by a point transformation of the dependent and independent variables. The first algorithm is based on a construction of the Lie point symmetry algebra and on the computation of its derived algebra. The second algorithm exploits the differential

Detection of proximal caries using digital radiographic systems with different resolutions.

Science.gov (United States)

Nikneshan, Sima; Abbas, Fatemeh Mashhadi; Sabbagh, Sedigheh

2015-01-01

Dental radiography is an important tool for detection of caries and digital radiography is the latest advancement in this regard. Spatial resolution is a characteristic of digital receptors used for describing the quality of images. This study was aimed to compare the diagnostic accuracy of two digital radiographic systems with three different resolutions for detection of noncavitated proximal caries. Diagnostic accuracy. Seventy premolar teeth were mounted in 14 gypsum blocks. Digora; Optime and RVG Access were used for obtaining digital radiographs. Six observers evaluated the proximal surfaces in radiographs for each resolution in order to determine the depth of caries based on a 4-point scale. The teeth were then histologically sectioned, and the results of histologic analysis were considered as the gold standard. Data were entered using SPSS version 18 software and the Kruskal-Wallis test was used for data analysis. P detection of proximal caries (P > 0.05). RVG access system had the highest specificity (87.7%) and Digora; Optime at high resolution had the lowest specificity (84.2%). Furthermore, Digora; Optime had higher sensitivity for detection of caries exceeding outer half of enamel. Judgment of oral radiologists for detection of the depth of caries had higher reliability than that of restorative dentistry specialists. The three resolutions of Digora; Optime and RVG access had similar accuracy in detection of noncavitated proximal caries.

Automated Identification of Fiducial Points on 3D Torso Images

Directory of Open Access Journals (Sweden)

Manas M. Kawale

2013-01-01

Full Text Available Breast reconstruction is an important part of the breast cancer treatment process for many women. Recently, 2D and 3D images have been used by plastic surgeons for evaluating surgical outcomes. Distances between different fiducial points are frequently used as quantitative measures for characterizing breast morphology. Fiducial points can be directly marked on subjects for direct anthropometry, or can be manually marked on images. This paper introduces novel algorithms to automate the identification of fiducial points in 3D images. Automating the process will make measurements of breast morphology more reliable, reducing the inter- and intra-observer bias. Algorithms to identify three fiducial points, the nipples, sternal notch, and umbilicus, are described. The algorithms used for localization of these fiducial points are formulated using a combination of surface curvature and 2D color information. Comparison of the 3D coordinates of automatically detected fiducial points and those identified manually, and geodesic distances between the fiducial points are used to validate algorithm performance. The algorithms reliably identified the location of all three of the fiducial points. We dedicate this article to our late colleague and friend, Dr. Elisabeth K. Beahm. Elisabeth was both a talented plastic surgeon and physician-scientist; we deeply miss her insight and her fellowship.

Simultaneous solution algorithms for Eulerian-Eulerian gas-solid flow models: Stability analysis and convergence behaviour of a point and a plane solver

International Nuclear Information System (INIS)

Wilde, Juray de; Vierendeels, Jan; Heynderickx, Geraldine J.; Marin, Guy B.

2005-01-01

Simultaneous solution algorithms for Eulerian-Eulerian gas-solid flow models are presented and their stability analyzed. The integration algorithms are based on dual-time stepping with fourth-order Runge-Kutta in pseudo-time. The domain is solved point or plane wise. The discretization of the inviscid terms is based on a low-Mach limit of the multi-phase preconditioned advection upstream splitting method (MP-AUSMP). The numerical stability of the simultaneous solution algorithms is analyzed in 2D with the Fourier method. Stability results are compared with the convergence behaviour of 3D riser simulations. The impact of the grid aspect ratio, preconditioning, artificial dissipation, and the treatment of the source terms is investigated. A particular advantage of the simultaneous solution algorithms is that they allow a fully implicit treatment of the source terms which are of crucial importance for the Eulerian-Eulerian gas-solid flow models and their solution. The numerical stability of the optimal simultaneous solution algorithm is analyzed for different solids volume fractions and gas-solid slip velocities. Furthermore, the effect of the grid resolution on the convergence behaviour and the simulation results is investigated. Finally, simulations of the bottom zone of a pilot-scale riser with a side solids inlet are experimentally validated

An Optimized Structure on FPGA of Key Point Detection in SIFT Algorithm

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Xu Chenyu

2016-01-01

Full Text Available SIFT algorithm is the most efficient and powerful algorithm to describe the features of images and it has been applied in many fields. In this paper, we propose an optimized method to realize the hardware implementation of the SIFT algorithm. We mainly discuss the structure of Data Generation here. A pipeline architecture is introduced to accelerate this optimized system. Parameters’ setting and approximation’s controlling in different image qualities and hardware resources are the focus of this paper. The results of experiments fully prove that this structure is real-time and effective, and provide consultative opinion to meet the different situations.

Accelerating simulation for the multiple-point statistics algorithm using vector quantization

Science.gov (United States)

Zuo, Chen; Pan, Zhibin; Liang, Hao

2018-03-01

Multiple-point statistics (MPS) is a prominent algorithm to simulate categorical variables based on a sequential simulation procedure. Assuming training images (TIs) as prior conceptual models, MPS extracts patterns from TIs using a template and records their occurrences in a database. However, complex patterns increase the size of the database and require considerable time to retrieve the desired elements. In order to speed up simulation and improve simulation quality over state-of-the-art MPS methods, we propose an accelerating simulation for MPS using vector quantization (VQ), called VQ-MPS. First, a variable representation is presented to make categorical variables applicable for vector quantization. Second, we adopt a tree-structured VQ to compress the database so that stationary simulations are realized. Finally, a transformed template and classified VQ are used to address nonstationarity. A two-dimensional (2D) stationary channelized reservoir image is used to validate the proposed VQ-MPS. In comparison with several existing MPS programs, our method exhibits significantly better performance in terms of computational time, pattern reproductions, and spatial uncertainty. Further demonstrations consist of a 2D four facies simulation, two 2D nonstationary channel simulations, and a three-dimensional (3D) rock simulation. The results reveal that our proposed method is also capable of solving multifacies, nonstationarity, and 3D simulations based on 2D TIs.

Sequential function approximation on arbitrarily distributed point sets

Science.gov (United States)

Wu, Kailiang; Xiu, Dongbin

2018-02-01

We present a randomized iterative method for approximating unknown function sequentially on arbitrary point set. The method is based on a recently developed sequential approximation (SA) method, which approximates a target function using one data point at each step and avoids matrix operations. The focus of this paper is on data sets with highly irregular distribution of the points. We present a nearest neighbor replacement (NNR) algorithm, which allows one to sample the irregular data sets in a near optimal manner. We provide mathematical justification and error estimates for the NNR algorithm. Extensive numerical examples are also presented to demonstrate that the NNR algorithm can deliver satisfactory convergence for the SA method on data sets with high irregularity in their point distributions.

What's the point? Golden and Labrador retrievers living in kennels do not understand human pointing gestures.

Science.gov (United States)

D'Aniello, Biagio; Alterisio, Alessandra; Scandurra, Anna; Petremolo, Emanuele; Iommelli, Maria Rosaria; Aria, Massimo

2017-07-01

In many studies that have investigated whether dogs' capacities to understand human pointing gestures are aspects of evolutionary or developmental social competences, family-owned dogs have been compared to shelter dogs. However, for most of these studies, the origins of shelter dogs were unknown. Some shelter dogs may have lived with families before entering shelters, and from these past experiences, they may have learned to understand human gestures. Furthermore, there is substantial variation in the methodology and analytic approaches used in such studies (e.g. different pointing protocols, different treatment of trials with no-choice response and indoor vs. outdoor experimental arenas). Such differences in methodologies and analysis techniques used make it difficult to compare results obtained from different studies and may account for the divergent results obtained. We thus attempted to control for several parameters by carrying out a test on dynamic proximal and distal pointing. We studied eleven kennel dogs of known origin that were born and raised in a kennels with limited human interaction. This group was compared to a group of eleven dogs comparable in terms of breed, sex and age that had lived with human families since they were puppies. Our results demonstrate that pet dogs outperform kennel dogs in their comprehension of proximal and distal pointing, regardless of whether trials where no-choice was made were considered as errors or were excluded from statistical analysis, meaning that dogs living in kennels do not understand pointing gestures. Even if genetic effects of the domestication process on human-dog relationships cannot be considered as negligible, our data suggest that dogs need to learn human pointing gestures and thus underscore the importance of ontogenetic processes.

In-Place Algorithms for Computing (Layers of) Maxima

DEFF Research Database (Denmark)

Blunck, Henrik; Vahrenhold, Jan

2006-01-01

We describe space-efficient algorithms for solving problems related to finding maxima among points in two and three dimensions. Our algorithms run in optimal O(n log2 n) time and require O(1) space in addition to the representation of the input.......We describe space-efficient algorithms for solving problems related to finding maxima among points in two and three dimensions. Our algorithms run in optimal O(n log2 n) time and require O(1) space in addition to the representation of the input....

Efficient triangulation of Poisson-disk sampled point sets

KAUST Repository

Guo, Jianwei

2014-05-06

In this paper, we present a simple yet efficient algorithm for triangulating a 2D input domain containing a Poisson-disk sampled point set. The proposed algorithm combines a regular grid and a discrete clustering approach to speedup the triangulation. Moreover, our triangulation algorithm is flexible and performs well on more general point sets such as adaptive, non-maximal Poisson-disk sets. The experimental results demonstrate that our algorithm is robust for a wide range of input domains and achieves significant performance improvement compared to the current state-of-the-art approaches. © 2014 Springer-Verlag Berlin Heidelberg.

PROXIMITY MANAGEMENT IN CRISIS CONDITIONS

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Ion Dorin BUMBENECI

2010-01-01

Full Text Available The purpose of this study is to evaluate the level of assimilation for the terms "Proximity Management" and "Proximity Manager", both in the specialized literature and in practice. The study has two parts: the theoretical research of the two terms, and an evaluation of the use of Proximity management in 32 companies in Gorj, Romania. The object of the evaluation resides in 27 companies with less than 50 employees and 5 companies with more than 50 employees.

Computing half-plane and strip discrepancy of planar point sets

NARCIS (Netherlands)

Berg, de M.

1996-01-01

We present efficient algorithms for two problems concerning the discrepancy of a set S of n points in the unit square in the plane. First, we describe an algorithm for maintaining the half-plane discrepancy of S under insertions and deletions of points. The algorithm runs in O(nlogn) worst-case time

Variability of United States Online Rehabilitation Protocols for Proximal Hamstring Tendon Repair

Science.gov (United States)

Lightsey, Harry M.; Kantrowitz, David E.; Swindell, Hasani W.; Trofa, David P.; Ahmad, Christopher S.; Lynch, T. Sean

2018-01-01

Background: The optimal postoperative rehabilitation protocol following repair of complete proximal hamstring tendon ruptures is the subject of ongoing investigation, with a need for more standardized regimens and evidence-based modalities. Purpose: To assess the variability across proximal hamstring tendon repair rehabilitation protocols published online by United States (US) orthopaedic teaching programs. Study Design: Cross-sectional study. Methods: Online proximal hamstring physical therapy protocols from US academic orthopaedic programs were reviewed. A web-based search using the search term complete proximal hamstring repair rehabilitation protocol provided an additional 14 protocols. A comprehensive scoring rubric was developed after review of all protocols and was used to assess each protocol for both the presence of various rehabilitation components and the point at which those components were introduced. Results: Of 50 rehabilitation protocols identified, 35 satisfied inclusion criteria and were analyzed. Twenty-five protocols (71%) recommended immediate postoperative bracing: 12 (34%) prescribed knee bracing, 8 (23%) prescribed hip bracing, and 5 (14%) did not specify the type of brace recommended. Fourteen protocols (40%) advised immediate nonweightbearing with crutches, while 16 protocols (46%) permitted immediate toe-touch weightbearing. Advancement to full weightbearing was allowed at a mean of 7.1 weeks (range, 4-12 weeks). Most protocols (80%) recommended gentle knee and hip passive range of motion and active range of motion, starting at a mean 1.4 weeks (range, 0-3 weeks) and 4.0 weeks (range, 0-6 weeks), respectively. However, only 6 protocols (17%) provided specific time points to initiate full hip and knee range of motion: a mean 8.0 weeks (range, 4-12 weeks) and 7.8 weeks (range, 0-12 weeks), respectively. Considerable variability was noted in the inclusion and timing of strengthening, stretching, proprioception, and cardiovascular exercises

Algorithmic Verification of Linearizability for Ordinary Differential Equations

KAUST Repository

Lyakhov, Dmitry A.

2017-07-19

For a nonlinear ordinary differential equation solved with respect to the highest order derivative and rational in the other derivatives and in the independent variable, we devise two algorithms to check if the equation can be reduced to a linear one by a point transformation of the dependent and independent variables. The first algorithm is based on a construction of the Lie point symmetry algebra and on the computation of its derived algebra. The second algorithm exploits the differential Thomas decomposition and allows not only to test the linearizability, but also to generate a system of nonlinear partial differential equations that determines the point transformation and the coefficients of the linearized equation. The implementation of both algorithms is discussed and their application is illustrated using several examples.

A New Multi-Step Iterative Algorithm for Approximating Common Fixed Points of a Finite Family of Multi-Valued Bregman Relatively Nonexpansive Mappings

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Wiyada Kumam

2016-05-01

Full Text Available In this article, we introduce a new multi-step iteration for approximating a common fixed point of a finite class of multi-valued Bregman relatively nonexpansive mappings in the setting of reflexive Banach spaces. We prove a strong convergence theorem for the proposed iterative algorithm under certain hypotheses. Additionally, we also use our results for the solution of variational inequality problems and to find the zero points of maximal monotone operators. The theorems furnished in this work are new and well-established and generalize many well-known recent research works in this field.

Morphological analysis of the proximal femur by computed tomography in Japanese subjects

International Nuclear Information System (INIS)

Hagiwara, Masashi

1995-01-01

In order to evaluate the morphological features of the proximal femur in the Japanese, 100 femora of normal Japanese subjects (normal group) and 60 femora of 43 Japanese patients with secondary osteoarthrosis of the hip (OA group) were analyzed using CT images. The scans for the dried bones (normal group) were done at a setting of 80 kV and 20 mA, for 2 sec duration. The scans were reconstructed using the soft tissue algorithm built into the GE-9800 scanner. The patient scans (OA group) were done at 120 kV and 170 mA also for 2 sec duration, and reconstructed using the same bone algorithm. The results were as follows: Thinning of the femoral cortex occurred in normal females over 60 years of age. The canal flare index at the proximal part of the femoral diaphysis was negatively correlated with the canal diameter at the isthmus. The index at the upper part was greater than that at the lower part. The two groups showed no statistical difference in this index. In the metaphysis, the canal flare index at the anterior portion was twice that at the posterior portion. In absolute terms, the OA group had a reduced flare or curve along the medial portion. In cross-section, the canal shape of the diaphysis was more elliptical in the OA group than in the normal group. The longitudinal axis of the canal was directed more sagittally in the OA group than in the normal group. (author)

Proximal tubular hypertrophy and enlarged glomerular and proximal tubular urinary space in obese subjects with proteinuria.

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Ana Tobar

Full Text Available BACKGROUND: Obesity is associated with glomerular hyperfiltration, increased proximal tubular sodium reabsorption, glomerular enlargement and renal hypertrophy. A single experimental study reported an increased glomerular urinary space in obese dogs. Whether proximal tubular volume is increased in obese subjects and whether their glomerular and tubular urinary spaces are enlarged is unknown. OBJECTIVE: To determine whether proximal tubules and glomerular and tubular urinary space are enlarged in obese subjects with proteinuria and glomerular hyperfiltration. METHODS: Kidney biopsies from 11 non-diabetic obese with proteinuria and 14 non-diabetic lean patients with a creatinine clearance above 50 ml/min and with mild or no interstitial fibrosis were retrospectively analyzed using morphometric methods. The cross-sectional area of the proximal tubular epithelium and lumen, the volume of the glomerular tuft and of Bowman's space and the nuclei number per tubular profile were estimated. RESULTS: Creatinine clearance was higher in the obese than in the lean group (P=0.03. Proteinuria was similarly increased in both groups. Compared to the lean group, the obese group displayed a 104% higher glomerular tuft volume (P=0.001, a 94% higher Bowman's space volume (P=0.003, a 33% higher cross-sectional area of the proximal tubular epithelium (P=0.02 and a 54% higher cross-sectional area of the proximal tubular lumen (P=0.01. The nuclei number per proximal tubular profile was similar in both groups, suggesting that the increase in tubular volume is due to hypertrophy and not to hyperplasia. CONCLUSIONS: Obesity-related glomerular hyperfiltration is associated with proximal tubular epithelial hypertrophy and increased glomerular and tubular urinary space volume in subjects with proteinuria. The expanded glomerular and urinary space is probably a direct consequence of glomerular hyperfiltration. These effects may be involved in the pathogenesis of obesity

Fractures of the proximal humerus

DEFF Research Database (Denmark)

Brorson, Stig

2013-01-01

Fractures of the proximal humerus have been diagnosed and managed since the earliest known surgical texts. For more than four millennia the preferred treatment was forceful traction, closed reduction, and immobilization with linen soaked in combinations of oil, honey, alum, wine, or cerate......, classification of proximal humeral fractures remains a challenge for the conduct, reporting, and interpretation of clinical trials. The evidence for the benefits of surgery in complex fractures of the proximal humerus is weak. In three systematic reviews I studied the outcome after locking plate osteosynthesis...

Geographically Modified PageRank Algorithms: Identifying the Spatial Concentration of Human Movement in a Geospatial Network.

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Wei-Chien-Benny Chin

Full Text Available A network approach, which simplifies geographic settings as a form of nodes and links, emphasizes the connectivity and relationships of spatial features. Topological networks of spatial features are used to explore geographical connectivity and structures. The PageRank algorithm, a network metric, is often used to help identify important locations where people or automobiles concentrate in the geographical literature. However, geographic considerations, including proximity and location attractiveness, are ignored in most network metrics. The objective of the present study is to propose two geographically modified PageRank algorithms-Distance-Decay PageRank (DDPR and Geographical PageRank (GPR-that incorporate geographic considerations into PageRank algorithms to identify the spatial concentration of human movement in a geospatial network. Our findings indicate that in both intercity and within-city settings the proposed algorithms more effectively capture the spatial locations where people reside than traditional commonly-used network metrics. In comparing location attractiveness and distance decay, we conclude that the concentration of human movement is largely determined by the distance decay. This implies that geographic proximity remains a key factor in human mobility.

A Minimum Path Algorithm Among 3D-Polyhedral Objects

Science.gov (United States)

Yeltekin, Aysin

1989-03-01

In this work we introduce a minimum path theorem for 3D case. We also develop an algorithm based on the theorem we prove. The algorithm will be implemented on the software package we develop using C language. The theorem we introduce states that; "Given the initial point I, final point F and S be the set of finite number of static obstacles then an optimal path P from I to F, such that PA S = 0 is composed of straight line segments which are perpendicular to the edge segments of the objects." We prove the theorem as well as we develop the following algorithm depending on the theorem to find the minimum path among 3D-polyhedral objects. The algorithm generates the point Qi on edge ei such that at Qi one can find the line which is perpendicular to the edge and the IF line. The algorithm iteratively provides a new set of initial points from Qi and exploits all possible paths. Then the algorithm chooses the minimum path among the possible ones. The flowchart of the program as well as the examination of its numerical properties are included.

Robotics in hostile environment I. S. I. S. robot - automatic positioning and docking with proximity and force feed back sensors

Energy Technology Data Exchange (ETDEWEB)

Gery, D

1987-01-01

Recent improvements in control command systems and the development of tactile proximity and force feed back sensors make it possible to robotize complex inspection and maintenance operations in hostile environment, which could have not been possible by classical remotely operated manipulators. We describe the I.S.I.S. robot characteristics, the control command system software principles and the tactile and force-torque sensors which have been developed for the different sequences of an hostile environment inspection and repair: access trajectories generation with obstacles shunning, final positioning and docking using parametric algorithms taking into account measurement of the end of arm proximity and force-torque sensors.

Stability and the proximity theorem in Casimir actuated nano devices

Science.gov (United States)

Esquivel-Sirvent, R.; Reyes, L.; Bárcenas, J.

2006-10-01

A brief description of the stability problem in micro and nano electromechanical devices (MEMS/NEMS) actuated by Casimir forces is given. To enhance the stability, we propose the use of curved surfaces and recalculate the stability conditions by means of the proximity force approximation. The use of curved surfaces changes the bifurcation point, and the radius of curvature becomes a control parameter, allowing a rescaling of the elastic restitution constant and/or of the typical dimensions of the device.

Autodriver algorithm

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.

Development and experimentation of LQR/APF guidance and control for autonomous proximity maneuvers of multiple spacecraft

Science.gov (United States)

Bevilacqua, R.; Lehmann, T.; Romano, M.

2011-04-01

This work introduces a novel control algorithm for close proximity multiple spacecraft autonomous maneuvers, based on hybrid linear quadratic regulator/artificial potential function (LQR/APF), for applications including autonomous docking, on-orbit assembly and spacecraft servicing. Both theoretical developments and experimental validation of the proposed approach are presented. Fuel consumption is sub-optimized in real-time through re-computation of the LQR at each sample time, while performing collision avoidance through the APF and a high level decisional logic. The underlying LQR/APF controller is integrated with a customized wall-following technique and a decisional logic, overcoming problems such as local minima. The algorithm is experimentally tested on a four spacecraft simulators test bed at the Spacecraft Robotics Laboratory of the Naval Postgraduate School. The metrics to evaluate the control algorithm are: autonomy of the system in making decisions, successful completion of the maneuver, required time, and propellant consumption.

Fast algorithm of adaptive Fourier series

Science.gov (United States)

Gao, You; Ku, Min; Qian, Tao

2018-05-01

Adaptive Fourier decomposition (AFD, precisely 1-D AFD or Core-AFD) was originated for the goal of positive frequency representations of signals. It achieved the goal and at the same time offered fast decompositions of signals. There then arose several types of AFDs. AFD merged with the greedy algorithm idea, and in particular, motivated the so-called pre-orthogonal greedy algorithm (Pre-OGA) that was proven to be the most efficient greedy algorithm. The cost of the advantages of the AFD type decompositions is, however, the high computational complexity due to the involvement of maximal selections of the dictionary parameters. The present paper offers one formulation of the 1-D AFD algorithm by building the FFT algorithm into it. Accordingly, the algorithm complexity is reduced, from the original $\\mathcal{O}(M N^2)$ to $\\mathcal{O}(M N\\log_2 N)$, where $N$ denotes the number of the discretization points on the unit circle and $M$ denotes the number of points in $[0,1)$. This greatly enhances the applicability of AFD. Experiments are carried out to show the high efficiency of the proposed algorithm.

Initial outcome and efficacy of S3 proximal humerus locking plate in the treatment of proximal humerus fractures

International Nuclear Information System (INIS)

Zhang Zhiming; Zhu Xuesong; Bao Zhaohua; Yang Huilin

2012-01-01

Objective: to explore the initial outcome and efficacy of S 3 proximal humerus locking plate in the treatment of proximal humerus fractures. Methods: Twenty-two patients with proximal humerus fracture were treated with the S 3 proximal humerus locking plate. Most of the fractures were complex, two-part (n=4), three-part (n=11) and four-part (n=7) fractures according to the Neer classification of the proximal humerus fractures. Results: All patients were followed up for 3∼15 months. There were no complications related to the implant including loosening or breakage of the plate. Good and excellent results were documented in 17 patients fair results in 4 patients according the Neer scores of shoulder. Conclusion: New design concepts of S 3 proximal humerus plate provide the subchondral support and the internal fixation support. With the addition of the proper exercise of the shoulder joint, the outcomes would be satisfied. (authors)

An improved artificial physical optimization algorithm for dynamic dispatch of generators with valve-point effects and wind power

International Nuclear Information System (INIS)

Yuan, Xiaohui; Ji, Bin; Zhang, Shuangquan; Tian, Hao; Chen, Zhihuan

2014-01-01

Highlights: • Dynamic load economic dispatch with wind power (DLEDW) model is established. • Markov chains combined with scenario analysis method are used to predict wind power. • Chance constrained technique is used to simulate the impacts of wind forecast error. • Improved artificial physical optimization algorithm is proposed to solve DLEDW. • Heuristic search strategies are applied to handle the constraints of DLEDW. - Abstract: Wind power, a kind of promising renewable energy resource, has recently been getting more attractive because of various environmental and economic considerations. But the penetration of wind power with its fluctuation nature has made the operation of power system more intractable. To coordinate the reliability and operation cost, this paper established a stochastic model of dynamic load economic dispatch with wind integration (DLEDW). In this model, constraints such as ramping up/down capacity, prohibited operating zone are considered and effects of valve-point are taken into account. Markov chains combined with scenario analysis method is used to generate predictive values of wind power and chance constrained programming (CCP) is applied to simulate the impacts of wind power fluctuation on system operation. An improved artificial physical optimization algorithm is presented to solve the DLEDW problem. Heuristic strategies based on the priority list and stochastic simulation techniques are proposed to handle the constraints. In addition, a local chaotic mutation strategy is applied to overcome the disadvantage of premature convergence of artificial physical optimization algorithm. Two test systems with and without wind power integration are used to verify the feasibility and effectiveness of the proposed method and the results are compared with those of gravitational search algorithm, particle swarm optimization and standard artificial physical optimization. The simulation results demonstrate that the proposed method has a

Visibility of noisy point cloud data

KAUST Repository

Mehra, Ravish

2010-06-01

We present a robust algorithm for estimating visibility from a given viewpoint for a point set containing concavities, non-uniformly spaced samples, and possibly corrupted with noise. Instead of performing an explicit surface reconstruction for the points set, visibility is computed based on a construction involving convex hull in a dual space, an idea inspired by the work of Katz et al. [26]. We derive theoretical bounds on the behavior of the method in the presence of noise and concavities, and use the derivations to develop a robust visibility estimation algorithm. In addition, computing visibility from a set of adaptively placed viewpoints allows us to generate locally consistent partial reconstructions. Using a graph based approximation algorithm we couple such reconstructions to extract globally consistent reconstructions. We test our method on a variety of 2D and 3D point sets of varying complexity and noise content. © 2010 Elsevier Ltd. All rights reserved.

First-Principles Study of Charge Diffusion between Proximate Solid-State Qubits and Its Implications on Sensor Applications

Science.gov (United States)

Chou, Jyh-Pin; Bodrog, Zoltán; Gali, Adam

2018-03-01

Solid-state qubits from paramagnetic point defects in solids are promising platforms to realize quantum networks and novel nanoscale sensors. Recent advances in materials engineering make it possible to create proximate qubits in solids that might interact with each other, leading to electron spin or charge fluctuation. Here we develop a method to calculate the tunneling-mediated charge diffusion between point defects from first principles and apply it to nitrogen-vacancy (NV) qubits in diamond. The calculated tunneling rates are in quantitative agreement with previous experimental data. Our results suggest that proximate neutral and negatively charged NV defect pairs can form a NV-NV molecule. A tunneling-mediated model for the source of decoherence of the near-surface NV qubits is developed based on our findings on the interacting qubits in diamond.

Use of the MULTINEST algorithm for gravitational wave data analysis

International Nuclear Information System (INIS)

Feroz, Farhan; Hobson, Michael P; Gair, Jonathan R; Porter, Edward K

2009-01-01

We describe an application of the MULTINEST algorithm to gravitational wave data analysis. MULTINEST is a multimodal nested sampling algorithm designed to efficiently evaluate the Bayesian evidence and return posterior probability densities for likelihood surfaces containing multiple secondary modes. The algorithm employs a set of 'live' points which are updated by partitioning the set into multiple overlapping ellipsoids and sampling uniformly from within them. This set of 'live' points climbs up the likelihood surface through nested iso-likelihood contours and the evidence and posterior distributions can be recovered from the point set evolution. The algorithm is model independent in the sense that the specific problem being tackled enters only through the likelihood computation, and does not change how the 'live' point set is updated. In this paper, we consider the use of the algorithm for gravitational wave data analysis by searching a simulated LISA data set containing two non-spinning supermassive black hole binary signals. The algorithm is able to rapidly identify all the modes of the solution and recover the true parameters of the sources to high precision.

Trabecular bone analysis in CT and X-ray images of the proximal femur for the assessment of local bone quality.

Science.gov (United States)

Fritscher, Karl; Grunerbl, Agnes; Hanni, Markus; Suhm, Norbert; Hengg, Clemens; Schubert, Rainer

2009-10-01

Currently, conventional X-ray and CT images as well as invasive methods performed during the surgical intervention are used to judge the local quality of a fractured proximal femur. However, these approaches are either dependent on the surgeon's experience or cannot assist diagnostic and planning tasks preoperatively. Therefore, in this work a method for the individual analysis of local bone quality in the proximal femur based on model-based analysis of CT- and X-ray images of femur specimen will be proposed. A combined representation of shape and spatial intensity distribution of an object and different statistical approaches for dimensionality reduction are used to create a statistical appearance model in order to assess the local bone quality in CT and X-ray images. The developed algorithms are tested and evaluated on 28 femur specimen. It will be shown that the tools and algorithms presented herein are highly adequate to automatically and objectively predict bone mineral density values as well as a biomechanical parameter of the bone that can be measured intraoperatively.

Preliminary study on leadership proximity

Directory of Open Access Journals (Sweden)

Ghinea Valentina Mihaela

2017-07-01

Full Text Available In general, it is agreed that effective leadership requires a certain degree of proximity, either physical or mental, which enables leaders to maintain control over their followers and communicate their vision. Although we agree with the leadership proximity principles which states that leaders are able to efficiently serve only those people with whom they interact frequently, in this article we focus instead on the disadvantages of being too close and the way in which close proximity can actually hurt the effectiveness of leadership. The main effects that we discuss regard the way in which proximity and familiarity allow followers to see the weaknesses and faults of the leader much more easily and thus diminish the leader’s heroic aura, and the emotional bias that results from a leader being too familiar with his followers which will impede the process of rational decision making. As a result, we argue that there exists a functional proximity which allows the leader the necessary space in which to perform effective identity work and to hide the backstage aspects of leadership, while also allowing him an emotional buffer zone which will enable him to maintain the ability to see clearly and make rational decisions.

An adaptive clustering algorithm for image matching based on corner feature

Science.gov (United States)

Wang, Zhe; Dong, Min; Mu, Xiaomin; Wang, Song

2018-04-01

The traditional image matching algorithm always can not balance the real-time and accuracy better, to solve the problem, an adaptive clustering algorithm for image matching based on corner feature is proposed in this paper. The method is based on the similarity of the matching pairs of vector pairs, and the adaptive clustering is performed on the matching point pairs. Harris corner detection is carried out first, the feature points of the reference image and the perceived image are extracted, and the feature points of the two images are first matched by Normalized Cross Correlation (NCC) function. Then, using the improved algorithm proposed in this paper, the matching results are clustered to reduce the ineffective operation and improve the matching speed and robustness. Finally, the Random Sample Consensus (RANSAC) algorithm is used to match the matching points after clustering. The experimental results show that the proposed algorithm can effectively eliminate the most wrong matching points while the correct matching points are retained, and improve the accuracy of RANSAC matching, reduce the computation load of whole matching process at the same time.

Algorithmic foundation of multi-scale spatial representation

CERN Document Server

Li, Zhilin

2006-01-01

With the widespread use of GIS, multi-scale representation has become an important issue in the realm of spatial data handling. However, no book to date has systematically tackled the different aspects of this discipline. Emphasizing map generalization, Algorithmic Foundation of Multi-Scale Spatial Representation addresses the mathematical basis of multi-scale representation, specifically, the algorithmic foundation.Using easy-to-understand language, the author focuses on geometric transformations, with each chapter surveying a particular spatial feature. After an introduction to the essential operations required for geometric transformations as well as some mathematical and theoretical background, the book describes algorithms for a class of point features/clusters. It then examines algorithms for individual line features, such as the reduction of data points, smoothing (filtering), and scale-driven generalization, followed by a discussion of algorithms for a class of line features including contours, hydrog...

A Method Based on Dial's Algorithm for Multi-time Dynamic Traffic Assignment

Directory of Open Access Journals (Sweden)

Rongjie Kuang

2014-03-01

Full Text Available Due to static traffic assignment has poor performance in reflecting actual case and dynamic traffic assignment may incurs excessive compute cost, method of multi-time dynamic traffic assignment combining static and dynamic traffic assignment balances factors of precision and cost effectively. A method based on Dial's logit algorithm is proposed in the article to solve the dynamic stochastic user equilibrium problem in dynamic traffic assignment. Before that, a fitting function that can proximately reflect overloaded traffic condition of link is proposed and used to give corresponding model. Numerical example is given to illustrate heuristic procedure of method and to compare results with one of same example solved by other literature's algorithm. Results show that method based on Dial's algorithm is preferable to algorithm from others.

PROXIMAL DISABILITY AND SPINAL DEFORMITY INDEX IN PATIENTS WITH PROXIMAL FEMUR FRACTURES

Directory of Open Access Journals (Sweden)

Sylvio Mistro Neto

2015-12-01

Full Text Available Objective : To evaluate the quality of life related to the spine in patients with proximal femoral fractures. Methods : Study conducted in a tertiary public hospital in patients with proximal femoral fractures caused by low-energy trauma, through the Oswestry Disability Index questionnaire to asses complaints related to the spine at the time of life prior to the femoral fracture. The thoracic and lumbar spine of patients were also evaluated applying the radiographic index described by Gennant (Spinal Deformity Index, which assesses the number and severity of fractures. Results : Seventeen subjects completed the study. All had some degree of vertebral fracture. Patients were classified in the categories of severe and very severe disability in the questionnaire about quality of life. It was found that the higher SDI, the better the quality of life. Conclusion : There is a strong association of disability related to the spine in patients with proximal femoral fracture, and this complaint must be systematically evaluated in patients with appendicular fracture.

a Voxel-Based Filtering Algorithm for Mobile LIDAR Data

Science.gov (United States)

Qin, H.; Guan, G.; Yu, Y.; Zhong, L.

2018-04-01

This paper presents a stepwise voxel-based filtering algorithm for mobile LiDAR data. In the first step, to improve computational efficiency, mobile LiDAR points, in xy-plane, are first partitioned into a set of two-dimensional (2-D) blocks with a given block size, in each of which all laser points are further organized into an octree partition structure with a set of three-dimensional (3-D) voxels. Then, a voxel-based upward growing processing is performed to roughly separate terrain from non-terrain points with global and local terrain thresholds. In the second step, the extracted terrain points are refined by computing voxel curvatures. This voxel-based filtering algorithm is comprehensively discussed in the analyses of parameter sensitivity and overall performance. An experimental study performed on multiple point cloud samples, collected by different commercial mobile LiDAR systems, showed that the proposed algorithm provides a promising solution to terrain point extraction from mobile point clouds.

A simple algorithm for computing the smallest enclosing circle

DEFF Research Database (Denmark)

Skyum, Sven

1991-01-01

Presented is a simple O(n log n) algorithm for computing the smallest enclosing circle of a convex polygon. It can be easily extended to algorithms that compute the farthest-and the closest-point Voronoi diagram of a convex polygon within the same time bound.......Presented is a simple O(n log n) algorithm for computing the smallest enclosing circle of a convex polygon. It can be easily extended to algorithms that compute the farthest-and the closest-point Voronoi diagram of a convex polygon within the same time bound....

Cortical thickness estimation of the proximal femur from multi-view dual-energy X-ray absorptiometry (DXA)

Science.gov (United States)

Tsaousis, N.; Gee, A. H.; Treece, G. M.; Poole, K. E. S.

2013-02-01

Hip fracture is the leading cause of acute orthopaedic hospital admission amongst the elderly, with around a third of patients not surviving one year post-fracture. Although various preventative therapies are available, patient selection is difficult. The current state-of-the-art risk assessment tool (FRAX) ignores focal structural defects, such as cortical bone thinning, a critical component in characterizing hip fragility. Cortical thickness can be measured using CT, but this is expensive and involves a significant radiation dose. Instead, Dual-Energy X-ray Absorptiometry (DXA) is currently the preferred imaging modality for assessing hip fracture risk and is used routinely in clinical practice. Our ambition is to develop a tool to measure cortical thickness using multi-view DXA instead of CT. In this initial study, we work with digitally reconstructed radiographs (DRRs) derived from CT data as a surrogate for DXA scans: this enables us to compare directly the thickness estimates with the gold standard CT results. Our approach involves a model-based femoral shape reconstruction followed by a data-driven algorithm to extract numerous cortical thickness point estimates. In a series of experiments on the shaft and trochanteric regions of 48 proximal femurs, we validated our algorithm and established its performance limits using 20 views in the range 0°-171°: estimation errors were 0:19 +/- 0:53mm (mean +/- one standard deviation). In a more clinically viable protocol using four views in the range 0°-51°, where no other bony structures obstruct the projection of the femur, measurement errors were -0:07 +/- 0:79 mm.

General Algorithm (High level)

Indian Academy of Sciences (India)

First page Back Continue Last page Overview Graphics. General Algorithm (High level). Iteratively. Use Tightness Property to remove points of P1,..,Pi. Use random sampling to get a Random Sample (of enough points) from the next largest cluster, Pi+1. Use the Random Sampling Procedure to approximate ci+1 using the ...

A Parallel Butterfly Algorithm

KAUST Repository

Poulson, Jack; Demanet, Laurent; Maxwell, Nicholas; Ying, Lexing

2014-01-01

The butterfly algorithm is a fast algorithm which approximately evaluates a discrete analogue of the integral transform (Equation Presented.) at large numbers of target points when the kernel, K(x, y), is approximately low-rank when restricted to subdomains satisfying a certain simple geometric condition. In d dimensions with O(Nd) quasi-uniformly distributed source and target points, when each appropriate submatrix of K is approximately rank-r, the running time of the algorithm is at most O(r2Nd logN). A parallelization of the butterfly algorithm is introduced which, assuming a message latency of α and per-process inverse bandwidth of β, executes in at most (Equation Presented.) time using p processes. This parallel algorithm was then instantiated in the form of the open-source DistButterfly library for the special case where K(x, y) = exp(iΦ(x, y)), where Φ(x, y) is a black-box, sufficiently smooth, real-valued phase function. Experiments on Blue Gene/Q demonstrate impressive strong-scaling results for important classes of phase functions. Using quasi-uniform sources, hyperbolic Radon transforms, and an analogue of a three-dimensional generalized Radon transform were, respectively, observed to strong-scale from 1-node/16-cores up to 1024-nodes/16,384-cores with greater than 90% and 82% efficiency, respectively. © 2014 Society for Industrial and Applied Mathematics.

A Parallel Butterfly Algorithm

KAUST Repository

Poulson, Jack

2014-02-04

The butterfly algorithm is a fast algorithm which approximately evaluates a discrete analogue of the integral transform (Equation Presented.) at large numbers of target points when the kernel, K(x, y), is approximately low-rank when restricted to subdomains satisfying a certain simple geometric condition. In d dimensions with O(Nd) quasi-uniformly distributed source and target points, when each appropriate submatrix of K is approximately rank-r, the running time of the algorithm is at most O(r2Nd logN). A parallelization of the butterfly algorithm is introduced which, assuming a message latency of α and per-process inverse bandwidth of β, executes in at most (Equation Presented.) time using p processes. This parallel algorithm was then instantiated in the form of the open-source DistButterfly library for the special case where K(x, y) = exp(iΦ(x, y)), where Φ(x, y) is a black-box, sufficiently smooth, real-valued phase function. Experiments on Blue Gene/Q demonstrate impressive strong-scaling results for important classes of phase functions. Using quasi-uniform sources, hyperbolic Radon transforms, and an analogue of a three-dimensional generalized Radon transform were, respectively, observed to strong-scale from 1-node/16-cores up to 1024-nodes/16,384-cores with greater than 90% and 82% efficiency, respectively. © 2014 Society for Industrial and Applied Mathematics.

Present status on numerical algorithms and benchmark tests for point kinetics and quasi-static approximate kinetics

International Nuclear Information System (INIS)

Ise, Takeharu

1976-12-01

Review studies have been made on algorithms of numerical analysis and benchmark tests on point kinetics and quasistatic approximate kinetics computer codes to perform efficiently benchmark tests on space-dependent neutron kinetics codes. Point kinetics methods have now been improved since they can be directly applied to the factorization procedures. Methods based on Pade rational function give numerically stable solutions and methods on matrix-splitting are interested in the fact that they are applicable to the direct integration methods. An improved quasistatic (IQ) approximation is the best and the most practical method; it is numerically shown that the IQ method has a high stability and precision and the computation time which is about one tenth of that of the direct method. IQ method is applicable to thermal reactors as well as fast reactors and especially fitted for fast reactors to which many time steps are necessary. Two-dimensional diffusion kinetics codes are most practicable though there exist also three-dimensional diffusion kinetics code as well as two-dimensional transport kinetics code. On developing a space-dependent kinetics code, in any case, it is desirable to improve the method so as to have a high computing speed for solving static diffusion and transport equations. (auth.)

Linear programming mathematics, theory and algorithms

CERN Document Server

1996-01-01

Linear Programming provides an in-depth look at simplex based as well as the more recent interior point techniques for solving linear programming problems. Starting with a review of the mathematical underpinnings of these approaches, the text provides details of the primal and dual simplex methods with the primal-dual, composite, and steepest edge simplex algorithms. This then is followed by a discussion of interior point techniques, including projective and affine potential reduction, primal and dual affine scaling, and path following algorithms. Also covered is the theory and solution of the linear complementarity problem using both the complementary pivot algorithm and interior point routines. A feature of the book is its early and extensive development and use of duality theory. Audience: The book is written for students in the areas of mathematics, economics, engineering and management science, and professionals who need a sound foundation in the important and dynamic discipline of linear programming.

Use of the MULTINEST algorithm for gravitational wave data analysis

Energy Technology Data Exchange (ETDEWEB)

Feroz, Farhan; Hobson, Michael P [Astrophysics Group, Cavendish Laboratory, JJ Thomson Avenue, Cambridge CB3 0HE (United Kingdom); Gair, Jonathan R [Institute of Astronomy, Madingley Road, Cambridge CB3 0HA (United Kingdom); Porter, Edward K [APC, UMR 7164, Universite Paris 7 Denis Diderot, 10, rue Alice Domon et Leonie Duquet, 75205 Paris Cedex 13 (France)

2009-11-07

We describe an application of the MULTINEST algorithm to gravitational wave data analysis. MULTINEST is a multimodal nested sampling algorithm designed to efficiently evaluate the Bayesian evidence and return posterior probability densities for likelihood surfaces containing multiple secondary modes. The algorithm employs a set of 'live' points which are updated by partitioning the set into multiple overlapping ellipsoids and sampling uniformly from within them. This set of 'live' points climbs up the likelihood surface through nested iso-likelihood contours and the evidence and posterior distributions can be recovered from the point set evolution. The algorithm is model independent in the sense that the specific problem being tackled enters only through the likelihood computation, and does not change how the 'live' point set is updated. In this paper, we consider the use of the algorithm for gravitational wave data analysis by searching a simulated LISA data set containing two non-spinning supermassive black hole binary signals. The algorithm is able to rapidly identify all the modes of the solution and recover the true parameters of the sources to high precision.

Multi-point probe for testing electrical properties and a method of producing a multi-point probe

DEFF Research Database (Denmark)

2011-01-01

A multi-point probe for testing electrical properties of a number of specific locations of a test sample comprises a supporting body defining a first surface, a first multitude of conductive probe arms (101-101'''), each of the probe arms defining a proximal end and a distal end. The probe arms...... of contact with the supporting body, and a maximum thickness perpendicular to its perpendicular bisector and its line of contact with the supporting body. Each of the probe arms has a specific area or point of contact (111-111''') at its distal end for contacting a specific location among the number...... of specific locations of the test sample. At least one of the probe arms has an extension defining a pointing distal end providing its specific area or point of contact located offset relative to its perpendicular bisector....

Proximal Probes Facility

Data.gov (United States)

Federal Laboratory Consortium — The Proximal Probes Facility consists of laboratories for microscopy, spectroscopy, and probing of nanostructured materials and their functional properties. At the...

Dental flossing as a diagnostic method for proximal gingivitis: a validation study.

Science.gov (United States)

Grellmann, Alessandra Pascotini; Kantorski, Karla Zanini; Ardenghi, Thiago Machado; Moreira, Carlos Heitor Cunha; Danesi, Cristiane Cademartori; Zanatta, Fabricio Batistin

2016-05-20

This study evaluated the clinical diagnosis of proximal gingivitis by comparing two methods: dental flossing and the gingival bleeding index (GBI). One hundred subjects (aged at least 18 years, with 15% of positive proximal sites for GBI, without proximal attachment loss) were randomized into five evaluation protocols. Each protocol consisted of two assessments with a 10-minute interval between them: first GBI/second floss, first floss/second GBI, first GBI/second GBI, first tooth floss/second floss, and first gum floss-second floss. The dental floss was slid against the tooth surface (TF) and the gingival tissue (GF). The evaluated proximal sites should present teeth with established point of contact and probing depth ≤ 3mm. One trained and calibrated examiner performed all the assessments. The mean percentages of agreement and disagreement were calculated for the sites with gingival bleeding in both evaluation methods (GBI and flossing). The primary outcome was the percentage of disagreement between the assessments in the different protocols. The data were analyzed by one-way ANOVA, McNemar, chi-square and Tukey's post hoc tests, with a 5% significance level. When gingivitis was absent in the first assessment (negative GBI), bleeding was detected in the second assessment by TF and GF in 41.7% (p gingivitis in the second assessment (negative GBI), TF and GF detected bleeding in the first assessment in 38.9% (p = 0.004) and 58.3% (p gingivitis than GBI.

Comparison of Nonequilibrium Solution Algorithms Applied to Chemically Stiff Hypersonic Flows

Science.gov (United States)

Palmer, Grant; Venkatapathy, Ethiraj

1995-01-01

Three solution algorithms, explicit under-relaxation, point implicit, and lower-upper symmetric Gauss-Seidel, are used to compute nonequilibrium flow around the Apollo 4 return capsule at the 62-km altitude point in its descent trajectory. By varying the Mach number, the efficiency and robustness of the solution algorithms were tested for different levels of chemical stiffness.The performance of the solution algorithms degraded as the Mach number and stiffness of the flow increased. At Mach 15 and 30, the lower-upper symmetric Gauss-Seidel method produces an eight order of magnitude drop in the energy residual in one-third to one-half the Cray C-90 computer time as compared to the point implicit and explicit under-relaxation methods. The explicit under-relaxation algorithm experienced convergence difficulties at Mach 30 and above. At Mach 40 the performance of the lower-upper symmetric Gauss-Seidel algorithm deteriorates to the point that it is out performed by the point implicit method. The effects of the viscous terms are investigated. Grid dependency questions are explored.

Neighborhoods and manageable proximity

Directory of Open Access Journals (Sweden)

Stavros Stavrides

2011-08-01

Full Text Available The theatricality of urban encounters is above all a theatricality of distances which allow for the encounter. The absolute “strangeness” of the crowd (Simmel 1997: 74 expressed, in its purest form, in the absolute proximity of a crowded subway train, does not generally allow for any movements of approach, but only for nervous hostile reactions and submissive hypnotic gestures. Neither forced intersections in the course of pedestrians or vehicles, nor the instantaneous crossing of distances by the technology of live broadcasting and remote control give birth to places of encounter. In the forced proximity of the metropolitan crowd which haunted the city of the 19th and 20th century, as well as in the forced proximity of the tele-presence which haunts the dystopic prospect of the future “omnipolis” (Virilio 1997: 74, the necessary distance, which is the stage of an encounter between different instances of otherness, is dissipated.

Digital contrast subtraction radiography for proximal caries diagnosis

International Nuclear Information System (INIS)

Kang, Byung Cheol; Yoon, Suk Ja

2002-01-01

To determine whether subtraction images utilizing contrast media can improve the diagnostic performance of proximal caries diagnosis compared to conventional periapical radiographic images. Thirty-six teeth with 57 proximal surfaces were radiographied using a size no.2 RVG-ui sensor (Trophy Radiology, Marne-la-Vallee, France). The teeth immersed in water-soluble contrast media and subtraction images were taken. Each tooth was then sectioned for histologic examination. The digital radiographic images and subtraction images were examined and interpreted by three dentists for proximal caries. The results of the proximal caries diagnosis were then verified with the results of the histologic examination. The proximal caries sensitivity using digital subtraction radiography was significantly higher than simply examining a single digital radiograph. The sensitivity of the proximal dentinal carious lesion when analyzed with the subtraction radiograph and the radiograph together was higher than with the subtraction radiograph or the radiograph alone. The use of subtraction radiography with contrast media may be useful for detecting proximal dentinal carious lesions.

Distribution majorization of corner points by reinforcement learning for moving object detection

Science.gov (United States)

Wu, Hao; Yu, Hao; Zhou, Dongxiang; Cheng, Yongqiang

2018-04-01

Corner points play an important role in moving object detection, especially in the case of free-moving camera. Corner points provide more accurate information than other pixels and reduce the computation which is unnecessary. Previous works only use intensity information to locate the corner points, however, the information that former and the last frames provided also can be used. We utilize the information to focus on more valuable area and ignore the invaluable area. The proposed algorithm is based on reinforcement learning, which regards the detection of corner points as a Markov process. In the Markov model, the video to be detected is regarded as environment, the selections of blocks for one corner point are regarded as actions and the performance of detection is regarded as state. Corner points are assigned to be the blocks which are seperated from original whole image. Experimentally, we select a conventional method which uses marching and Random Sample Consensus algorithm to obtain objects as the main framework and utilize our algorithm to improve the result. The comparison between the conventional method and the same one with our algorithm show that our algorithm reduce 70% of the false detection.

Evaluating progressive-rendering algorithms in appearance design tasks.

Science.gov (United States)

Jiawei Ou; Karlik, Ondrej; Křivánek, Jaroslav; Pellacini, Fabio

2013-01-01

Progressive rendering is becoming a popular alternative to precomputational approaches to appearance design. However, progressive algorithms create images exhibiting visual artifacts at early stages. A user study investigated these artifacts' effects on user performance in appearance design tasks. Novice and expert subjects performed lighting and material editing tasks with four algorithms: random path tracing, quasirandom path tracing, progressive photon mapping, and virtual-point-light rendering. Both the novices and experts strongly preferred path tracing to progressive photon mapping and virtual-point-light rendering. None of the participants preferred random path tracing to quasirandom path tracing or vice versa; the same situation held between progressive photon mapping and virtual-point-light rendering. The user workflow didn’t differ significantly with the four algorithms. The Web Extras include a video showing how four progressive-rendering algorithms converged (at http://youtu.be/ck-Gevl1e9s), the source code used, and other supplementary materials.

Calculus Rules for V-Proximal Subdifferentials in Smooth Banach Spaces

Directory of Open Access Journals (Sweden)

Messaoud Bounkhel

2016-01-01

Full Text Available In 2010, Bounkhel et al. introduced new proximal concepts (analytic proximal subdifferential, geometric proximal subdifferential, and proximal normal cone in reflexive smooth Banach spaces. They proved, in p-uniformly convex and q-uniformly smooth Banach spaces, the density theorem for the new concepts of proximal subdifferential and various important properties for both proximal subdifferential concepts and the proximal normal cone concept. In this paper, we establish calculus rules (fuzzy sum rule and chain rule for both proximal subdifferentials and we prove the Bishop-Phelps theorem for the proximal normal cone. The limiting concept for both proximal subdifferentials and for the proximal normal cone is defined and studied. We prove that both limiting constructions coincide with the Mordukhovich constructions under some assumptions on the space. Applications to nonconvex minimisation problems and nonconvex variational inequalities are established.

Inferring Person-to-person Proximity Using WiFi Signals

DEFF Research Database (Denmark)

Sapiezynski, Piotr; Stopczynski, Arkadiusz; Wind, David Kofoed

2017-01-01

scale is a technical challenge and many commonly used approaches—including RFID badges or Bluetooth scanning—offer only limited scalability. Here we show that it is possible, in a scalable and robust way, to accurately infer person-to-person physical proximity from the lists of WiFi access points...... measured by smartphones carried by the two individuals. Based on a longitudinal dataset of approximately 800 participants with ground-truth interactions collected over a year, we show that our model performs better than the current state-of-the-art. Our results demonstrate the value of WiFi signals...

Photovoltaic Cells Mppt Algorithm and Design of Controller Monitoring System

Science.gov (United States)

Meng, X. Z.; Feng, H. B.

2017-10-01

This paper combined the advantages of each maximum power point tracking (MPPT) algorithm, put forward a kind of algorithm with higher speed and higher precision, based on this algorithm designed a maximum power point tracking controller with ARM. The controller, communication technology and PC software formed a control system. Results of the simulation and experiment showed that the process of maximum power tracking was effective, and the system was stable.

Calculation of nondiffused proximity functions from cloud-chamber data

International Nuclear Information System (INIS)

Zaider, M.

1987-01-01

To a large extent the cloud chamber is an ideal microdosimetric device: by measuring the positions of ionizing events in charged-particle tracks one can generate - with a flexibility matched only by Monte-Carlo simulations-any microdosimetric quantity of interest, ranging from lineal energy spectra (in volumes of practically arbitrary shape and size) to proximity functions, that is, distributions of distances between energy transfer points in the track. Cloud-chamber data analyzed in such ways have been indeed reported for a variety of radiations. In view of these clear advantages it is certainly surprising that, within the microdosimetric community, only one group (at Harwell, UK) is actively involved in such work and that, furthermore, cloud-chamber results are used essentially only as a testing ground for Monte-Carlo calculations. It appears that this reluctance can be traced to the fact that the tracks are distorted by the diffusion of droplets during their growth. This diffusion - which is of the order of several nanometers (in unit-density material), although rather insignificant vis-a-vis conventional microdosimetry, can be a serious limitation in view of modern theories of radiation action which emphasize energy deposition events at the nanometer level. The purpose of this research activity is to show that, using a rather straight-forward mathematical procedure, one can unfold the effect of diffusion from proximity functions. Since the nondiffused proximity function can be used to calculate other microdosimetric quantities an important limitation of the cloud-chamber data can thus be avoided

Sim3C: simulation of Hi-C and Meta3C proximity ligation sequencing technologies.

Science.gov (United States)

DeMaere, Matthew Z; Darling, Aaron E

2018-02-01

Chromosome conformation capture (3C) and Hi-C DNA sequencing methods have rapidly advanced our understanding of the spatial organization of genomes and metagenomes. Many variants of these protocols have been developed, each with their own strengths. Currently there is no systematic means for simulating sequence data from this family of sequencing protocols, potentially hindering the advancement of algorithms to exploit this new datatype. We describe a computational simulator that, given simple parameters and reference genome sequences, will simulate Hi-C sequencing on those sequences. The simulator models the basic spatial structure in genomes that is commonly observed in Hi-C and 3C datasets, including the distance-decay relationship in proximity ligation, differences in the frequency of interaction within and across chromosomes, and the structure imposed by cells. A means to model the 3D structure of randomly generated topologically associating domains is provided. The simulator considers several sources of error common to 3C and Hi-C library preparation and sequencing methods, including spurious proximity ligation events and sequencing error. We have introduced the first comprehensive simulator for 3C and Hi-C sequencing protocols. We expect the simulator to have use in testing of Hi-C data analysis algorithms, as well as more general value for experimental design, where questions such as the required depth of sequencing, enzyme choice, and other decisions can be made in advance in order to ensure adequate statistical power with respect to experimental hypothesis testing.

Inverse consistent non-rigid image registration based on robust point set matching

Science.gov (United States)

2014-01-01

Background Robust point matching (RPM) has been extensively used in non-rigid registration of images to robustly register two sets of image points. However, except for the location at control points, RPM cannot estimate the consistent correspondence between two images because RPM is a unidirectional image matching approach. Therefore, it is an important issue to make an improvement in image registration based on RPM. Methods In our work, a consistent image registration approach based on the point sets matching is proposed to incorporate the property of inverse consistency and improve registration accuracy. Instead of only estimating the forward transformation between the source point sets and the target point sets in state-of-the-art RPM algorithms, the forward and backward transformations between two point sets are estimated concurrently in our algorithm. The inverse consistency constraints are introduced to the cost function of RPM and the fuzzy correspondences between two point sets are estimated based on both the forward and backward transformations simultaneously. A modified consistent landmark thin-plate spline registration is discussed in detail to find the forward and backward transformations during the optimization of RPM. The similarity of image content is also incorporated into point matching in order to improve image matching. Results Synthetic data sets, medical images are employed to demonstrate and validate the performance of our approach. The inverse consistent errors of our algorithm are smaller than RPM. Especially, the topology of transformations is preserved well for our algorithm for the large deformation between point sets. Moreover, the distance errors of our algorithm are similar to that of RPM, and they maintain a downward trend as whole, which demonstrates the convergence of our algorithm. The registration errors for image registrations are evaluated also. Again, our algorithm achieves the lower registration errors in same iteration number

Greedy algorithm with weights for decision tree construction

KAUST Repository

Moshkov, Mikhail

2010-01-01

An approximate algorithm for minimization of weighted depth of decision trees is considered. A bound on accuracy of this algorithm is obtained which is unimprovable in general case. Under some natural assumptions on the class NP, the considered algorithm is close (from the point of view of accuracy) to best polynomial approximate algorithms for minimization of weighted depth of decision trees.

Greedy algorithm with weights for decision tree construction

KAUST Repository

Moshkov, Mikhail

2010-12-01

An approximate algorithm for minimization of weighted depth of decision trees is considered. A bound on accuracy of this algorithm is obtained which is unimprovable in general case. Under some natural assumptions on the class NP, the considered algorithm is close (from the point of view of accuracy) to best polynomial approximate algorithms for minimization of weighted depth of decision trees.

Sub-quadratic decoding of one-point hermitian codes

DEFF Research Database (Denmark)

Nielsen, Johan Sebastian Rosenkilde; Beelen, Peter

2015-01-01

We present the first two sub-quadratic complexity decoding algorithms for one-point Hermitian codes. The first is based on a fast realization of the Guruswami-Sudan algorithm using state-of-the-art algorithms from computer algebra for polynomial-ring matrix minimization. The second is a power...... decoding algorithm: an extension of classical key equation decoding which gives a probabilistic decoding algorithm up to the Sudan radius. We show how the resulting key equations can be solved by the matrix minimization algorithms from computer algebra, yielding similar asymptotic complexities....

Parkinson's Disease Prevalence and Proximity to Agricultural Cultivated Fields

Science.gov (United States)

Yitshak Sade, Maayan; Zlotnik, Yair; Kloog, Itai; Novack, Victor; Peretz, Chava; Ifergane, Gal

2015-01-01

The risk for developing Parkinson's disease (PD) is a combination of multiple environmental and genetic factors. The Negev (Southern Israel) contains approximately 252.5 km2 of agricultural cultivated fields (ACF). We aimed to estimate the prevalence and incidence of PD and to examine possible geographical clustering and associations with agricultural exposures. We screened all “Clalit” Health Services members in the Negev (70% of the population) between the years 2000 and 2012. Individual demographic, clinical, and medication prescription data were available. We used a refined medication tracer algorithm to identify PD patients. We used mixed Poisson models to calculate the smoothed standardized incidence rates (SIRs) for each locality. We identified ACF and calculate the size and distance of the fields from each locality. We identified 3,792 cases of PD. SIRs were higher than expected in Jewish rural localities (median SIR [95% CI]: 1.41 [1.28; 1.53] in 2001–2004, 1.62 [1.48; 1.76] in 2005–2008, and 1.57 [1.44; 1.80] in 2009–2012). Highest SIR was observed in localities located in proximity to large ACF (SIR 1.54, 95% CI 1.32; 1.79). In conclusion, in this population based study we found that PD SIRs were higher than expected in rural localities. Furthermore, it appears that proximity to ACF and the field size contribute to PD risk. PMID:26357584

RFID Location Algorithm

Directory of Open Access Journals (Sweden)

Wang Zi Min

2016-01-01

Full Text Available With the development of social services, people’s living standards improve further requirements, there is an urgent need for a way to adapt to the complex situation of the new positioning technology. In recent years, RFID technology have a wide range of applications in all aspects of life and production, such as logistics tracking, car alarm, security and other items. The use of RFID technology to locate, it is a new direction in the eyes of the various research institutions and scholars. RFID positioning technology system stability, the error is small and low-cost advantages of its location algorithm is the focus of this study.This article analyzes the layers of RFID technology targeting methods and algorithms. First, RFID common several basic methods are introduced; Secondly, higher accuracy to political network location method; Finally, LANDMARC algorithm will be described. Through this it can be seen that advanced and efficient algorithms play an important role in increasing RFID positioning accuracy aspects.Finally, the algorithm of RFID location technology are summarized, pointing out the deficiencies in the algorithm, and put forward a follow-up study of the requirements, the vision of a better future RFID positioning technology.

Improving GPU-accelerated adaptive IDW interpolation algorithm using fast kNN search.

Science.gov (United States)

Mei, Gang; Xu, Nengxiong; Xu, Liangliang

2016-01-01

This paper presents an efficient parallel Adaptive Inverse Distance Weighting (AIDW) interpolation algorithm on modern Graphics Processing Unit (GPU). The presented algorithm is an improvement of our previous GPU-accelerated AIDW algorithm by adopting fast k-nearest neighbors (kNN) search. In AIDW, it needs to find several nearest neighboring data points for each interpolated point to adaptively determine the power parameter; and then the desired prediction value of the interpolated point is obtained by weighted interpolating using the power parameter. In this work, we develop a fast kNN search approach based on the space-partitioning data structure, even grid, to improve the previous GPU-accelerated AIDW algorithm. The improved algorithm is composed of the stages of kNN search and weighted interpolating. To evaluate the performance of the improved algorithm, we perform five groups of experimental tests. The experimental results indicate: (1) the improved algorithm can achieve a speedup of up to 1017 over the corresponding serial algorithm; (2) the improved algorithm is at least two times faster than our previous GPU-accelerated AIDW algorithm; and (3) the utilization of fast kNN search can significantly improve the computational efficiency of the entire GPU-accelerated AIDW algorithm.

Emergency Department Management of Suspected Calf-Vein Deep Venous Thrombosis: A Diagnostic Algorithm

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Levi Kitchen

2016-06-01

Full Text Available Introduction: Unilateral leg swelling with suspicion of deep venous thrombosis (DVT is a common emergency department (ED presentation. Proximal DVT (thrombus in the popliteal or femoral veins can usually be diagnosed and treated at the initial ED encounter. When proximal DVT has been ruled out, isolated calf-vein deep venous thrombosis (IC-DVT often remains a consideration. The current standard for the diagnosis of IC-DVT is whole-leg vascular duplex ultrasonography (WLUS, a test that is unavailable in many hospitals outside normal business hours. When WLUS is not available from the ED, recommendations for managing suspected IC-DVT vary. The objectives of the study is to use current evidence and recommendations to (1 propose a diagnostic algorithm for IC-DVT when definitive testing (WLUS is unavailable; and (2 summarize the controversy surrounding IC-DVT treatment. Discussion: The Figure combines D-dimer testing with serial CUS or a single deferred FLUS for the diagnosis of IC-DVT. Such an algorithm has the potential to safely direct the management of suspected IC-DVT when definitive testing is unavailable. Whether or not to treat diagnosed IC-DVT remains widely debated and awaiting further evidence. Conclusion: When IC-DVT is not ruled out in the ED, the suggested algorithm, although not prospectively validated by a controlled study, offers an approach to diagnosis that is consistent with current data and recommendations. When IC-DVT is diagnosed, current references suggest that a decision between anticoagulation and continued follow-up outpatient testing can be based on shared decision-making. The risks of proximal progression and life-threatening embolization should be balanced against the generally more benign natural history of such thrombi, and an individual patient’s risk factors for both thrombus propagation and complications of anticoagulation. [West J Emerg Med. 2016;17(4384-390.

Emergency Department Management of Suspected Calf-Vein Deep Venous Thrombosis: A Diagnostic Algorithm.

Science.gov (United States)

Kitchen, Levi; Lawrence, Matthew; Speicher, Matthew; Frumkin, Kenneth

2016-07-01

Unilateral leg swelling with suspicion of deep venous thrombosis (DVT) is a common emergency department (ED) presentation. Proximal DVT (thrombus in the popliteal or femoral veins) can usually be diagnosed and treated at the initial ED encounter. When proximal DVT has been ruled out, isolated calf-vein deep venous thrombosis (IC-DVT) often remains a consideration. The current standard for the diagnosis of IC-DVT is whole-leg vascular duplex ultrasonography (WLUS), a test that is unavailable in many hospitals outside normal business hours. When WLUS is not available from the ED, recommendations for managing suspected IC-DVT vary. The objectives of the study is to use current evidence and recommendations to (1) propose a diagnostic algorithm for IC-DVT when definitive testing (WLUS) is unavailable; and (2) summarize the controversy surrounding IC-DVT treatment. The Figure combines D-dimer testing with serial CUS or a single deferred FLUS for the diagnosis of IC-DVT. Such an algorithm has the potential to safely direct the management of suspected IC-DVT when definitive testing is unavailable. Whether or not to treat diagnosed IC-DVT remains widely debated and awaiting further evidence. When IC-DVT is not ruled out in the ED, the suggested algorithm, although not prospectively validated by a controlled study, offers an approach to diagnosis that is consistent with current data and recommendations. When IC-DVT is diagnosed, current references suggest that a decision between anticoagulation and continued follow-up outpatient testing can be based on shared decision-making. The risks of proximal progression and life-threatening embolization should be balanced against the generally more benign natural history of such thrombi, and an individual patient's risk factors for both thrombus propagation and complications of anticoagulation.

DEVELOPMENT OF 2D HUMAN BODY MODELING USING THINNING ALGORITHM

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K. Srinivasan

2010-11-01

Full Text Available Monitoring the behavior and activities of people in Video surveillance has gained more applications in Computer vision. This paper proposes a new approach to model the human body in 2D view for the activity analysis using Thinning algorithm. The first step of this work is Background subtraction which is achieved by the frame differencing algorithm. Thinning algorithm has been used to find the skeleton of the human body. After thinning, the thirteen feature points like terminating points, intersecting points, shoulder, elbow, and knee points have been extracted. Here, this research work attempts to represent the body model in three different ways such as Stick figure model, Patch model and Rectangle body model. The activities of humans have been analyzed with the help of 2D model for the pre-defined poses from the monocular video data. Finally, the time consumption and efficiency of our proposed algorithm have been evaluated.

A note on the linear memory Baum-Welch algorithm

DEFF Research Database (Denmark)

Jensen, Jens Ledet

2009-01-01

We demonstrate the simplicity and generality of the recently introduced linear space Baum-Welch algorithm for hidden Markov models. We also point to previous literature on the subject.......We demonstrate the simplicity and generality of the recently introduced linear space Baum-Welch algorithm for hidden Markov models. We also point to previous literature on the subject....

Optical proximity correction for anamorphic extreme ultraviolet lithography

Science.gov (United States)

Clifford, Chris; Lam, Michael; Raghunathan, Ananthan; Jiang, Fan; Fenger, Germain; Adam, Kostas

2017-10-01

The change from isomorphic to anamorphic optics in high numerical aperture (NA) extreme ultraviolet (EUV) scanners necessitates changes to the mask data preparation flow. The required changes for each step in the mask tape out process are discussed, with a focus on optical proximity correction (OPC). When necessary, solutions to new problems are demonstrated, and verified by rigorous simulation. Additions to the OPC model include accounting for anamorphic effects in the optics, mask electromagnetics, and mask manufacturing. The correction algorithm is updated to include awareness of anamorphic mask geometry for mask rule checking (MRC). OPC verification through process window conditions is enhanced to test different wafer scale mask error ranges in the horizontal and vertical directions. This work will show that existing models and methods can be updated to support anamorphic optics without major changes. Also, the larger mask size in the Y direction can result in better model accuracy, easier OPC convergence, and designs which are more tolerant to mask errors.

A Feedback Optimal Control Algorithm with Optimal Measurement Time Points

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Felix Jost

2017-02-01

Full Text Available Nonlinear model predictive control has been established as a powerful methodology to provide feedback for dynamic processes over the last decades. In practice it is usually combined with parameter and state estimation techniques, which allows to cope with uncertainty on many levels. To reduce the uncertainty it has also been suggested to include optimal experimental design into the sequential process of estimation and control calculation. Most of the focus so far was on dual control approaches, i.e., on using the controls to simultaneously excite the system dynamics (learning as well as minimizing a given objective (performing. We propose a new algorithm, which sequentially solves robust optimal control, optimal experimental design, state and parameter estimation problems. Thus, we decouple the control and the experimental design problems. This has the advantages that we can analyze the impact of measurement timing (sampling independently, and is practically relevant for applications with either an ethical limitation on system excitation (e.g., chemotherapy treatment or the need for fast feedback. The algorithm shows promising results with a 36% reduction of parameter uncertainties for the Lotka-Volterra fishing benchmark example.

Bouc–Wen hysteresis model identification using Modified Firefly Algorithm

International Nuclear Information System (INIS)

Zaman, Mohammad Asif; Sikder, Urmita

2015-01-01

The parameters of Bouc–Wen hysteresis model are identified using a Modified Firefly Algorithm. The proposed algorithm uses dynamic process control parameters to improve its performance. The algorithm is used to find the model parameter values that results in the least amount of error between a set of given data points and points obtained from the Bouc–Wen model. The performance of the algorithm is compared with the performance of conventional Firefly Algorithm, Genetic Algorithm and Differential Evolution algorithm in terms of convergence rate and accuracy. Compared to the other three optimization algorithms, the proposed algorithm is found to have good convergence rate with high degree of accuracy in identifying Bouc–Wen model parameters. Finally, the proposed method is used to find the Bouc–Wen model parameters from experimental data. The obtained model is found to be in good agreement with measured data. - Highlights: • We describe a new method to find the Bouc–Wen hysteresis model parameters. • We propose a Modified Firefly Algorithm. • We compare our method with existing methods to find that the proposed method performs better. • We use our model to fit experimental results. Good agreement is found

Bouc–Wen hysteresis model identification using Modified Firefly Algorithm

Energy Technology Data Exchange (ETDEWEB)

Zaman, Mohammad Asif, E-mail: zaman@stanford.edu [Department of Electrical Engineering, Stanford University (United States); Sikder, Urmita [Department of Electrical Engineering and Computer Sciences, University of California, Berkeley (United States)

2015-12-01

The parameters of Bouc–Wen hysteresis model are identified using a Modified Firefly Algorithm. The proposed algorithm uses dynamic process control parameters to improve its performance. The algorithm is used to find the model parameter values that results in the least amount of error between a set of given data points and points obtained from the Bouc–Wen model. The performance of the algorithm is compared with the performance of conventional Firefly Algorithm, Genetic Algorithm and Differential Evolution algorithm in terms of convergence rate and accuracy. Compared to the other three optimization algorithms, the proposed algorithm is found to have good convergence rate with high degree of accuracy in identifying Bouc–Wen model parameters. Finally, the proposed method is used to find the Bouc–Wen model parameters from experimental data. The obtained model is found to be in good agreement with measured data. - Highlights: • We describe a new method to find the Bouc–Wen hysteresis model parameters. • We propose a Modified Firefly Algorithm. • We compare our method with existing methods to find that the proposed method performs better. • We use our model to fit experimental results. Good agreement is found.

Giant proximity effect in ferromagnetic bilayers

Science.gov (United States)

Ramos, Silvia; Charlton, Tim; Quintanilla, Jorge; Suter, Andreas; Moodera, Jagadeesh; Prokscha, Thomas; Salman, Zaher; Forgan, Ted

2013-03-01

The proximity effect is a phenomenon where an ordered state leaks from a material into an adjacent one over some finite distance, ξ. For superconductors, this distance is ~ the coherence length. Nevertheless much longer-range, ``giant'' proximity effects have been observed in cuprate junctions. This surprising effect can be understood as a consequence of critical opalescence. Since this occurs near all second order phase transitions, giant proximity effects should be very general and, in particular, they should be present in magnetic systems. The ferromagnetic proximity effect has the advantage that its order parameter (magnetization) can be observed directly. We investigate the above phenomenon in Co/EuS bilayer films, where both materials undergo ferromagnetic transitions but at rather different temperatures (bulk TC of 1400K for Co and 16.6K for EuS). A dramatic increase in the range of the proximity effect is expected near the TC of EuS. We present the results of our measurements of the magnetization profiles as a function of temperature, carried out using the complementary techniques of low energy muon rotation and polarized neutron reflectivity. Work supported by EPSRC, STFC and ONR grant N00014-09-1-0177 and NSF grant DMR 0504158.

PCX, Interior-Point Linear Programming Solver

International Nuclear Information System (INIS)

Czyzyk, J.

2004-01-01

1 - Description of program or function: PCX solves linear programming problems using the Mehrota predictor-corrector interior-point algorithm. PCX can be called as a subroutine or used in stand-alone mode, with data supplied from an MPS file. The software incorporates modules that can be used separately from the linear programming solver, including a pre-solve routine and data structure definitions. 2 - Methods: The Mehrota predictor-corrector method is a primal-dual interior-point method for linear programming. The starting point is determined from a modified least squares heuristic. Linear systems of equations are solved at each interior-point iteration via a sparse Cholesky algorithm native to the code. A pre-solver is incorporated in the code to eliminate inefficiencies in the user's formulation of the problem. 3 - Restriction on the complexity of the problem: There are no size limitations built into the program. The size of problem solved is limited by RAM and swap space on the user's computer

Prototype Implementation of Two Efficient Low-Complexity Digital Predistortion Algorithms

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Timo I. Laakso

2008-01-01

Full Text Available Predistortion (PD lineariser for microwave power amplifiers (PAs is an important topic of research. With larger and larger bandwidth as it appears today in modern WiMax standards as well as in multichannel base stations for 3GPP standards, the relatively simple nonlinear effect of a PA becomes a complex memory-including function, severely distorting the output signal. In this contribution, two digital PD algorithms are investigated for the linearisation of microwave PAs in mobile communications. The first one is an efficient and low-complexity algorithm based on a memoryless model, called the simplicial canonical piecewise linear (SCPWL function that describes the static nonlinear characteristic of the PA. The second algorithm is more general, approximating the pre-inverse filter of a nonlinear PA iteratively using a Volterra model. The first simpler algorithm is suitable for compensation of amplitude compression and amplitude-to-phase conversion, for example, in mobile units with relatively small bandwidths. The second algorithm can be used to linearise PAs operating with larger bandwidths, thus exhibiting memory effects, for example, in multichannel base stations. A measurement testbed which includes a transmitter-receiver chain with a microwave PA is built for testing and prototyping of the proposed PD algorithms. In the testing phase, the PD algorithms are implemented using MATLAB (floating-point representation and tested in record-and-playback mode. The iterative PD algorithm is then implemented on a Field Programmable Gate Array (FPGA using fixed-point representation. The FPGA implementation allows the pre-inverse filter to be tested in a real-time mode. Measurement results show excellent linearisation capabilities of both the proposed algorithms in terms of adjacent channel power suppression. It is also shown that the fixed-point FPGA implementation of the iterative algorithm performs as well as the floating-point implementation.

Event-triggered Decision Propagation in Proximity Networks

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Soumik eSarkar

2014-12-01

Full Text Available This paper proposes a novel event-triggered formulation as an extension of the recently develo-ped generalized gossip algorithm for decision/awareness propagation in mobile sensor networksmodeled as proximity networks. The key idea is to expend energy for communication (messagetransmission and reception only when there is any event of interest in the region of surveillance.The idea is implemented by using an agent’s belief about presence of a hotspot as feedback tochange its probability of (communication activity. In the original formulation, the evolution ofnetwork topology and the dynamics of decision propagation were completely decoupled whichis no longer the case as a consequence of this feedback policy. Analytical results and numeri-cal experiments are presented to show a significant gain in energy savings with no change inthe first moment characteristics of decision propagation. However, numerical experiments showthat the second moment characteristics may change and theoretical results are provided forupper and lower bounds for second moment characteristics. Effects of false alarms on networkformation and communication activity are also investigated.

Brief report: Using global positioning system (GPS) enabled cell phones to examine adolescent travel patterns and time in proximity to alcohol outlets.

Science.gov (United States)

Byrnes, Hilary F; Miller, Brenda A; Morrison, Christopher N; Wiebe, Douglas J; Remer, Lillian G; Wiehe, Sarah E

2016-07-01

As adolescents gain freedom to explore new environments unsupervised, more time in proximity to alcohol outlets may increase risks for alcohol and marijuana use. This pilot study: 1) Describes variations in adolescents' proximity to outlets by time of day and day of the week, 2) Examines variations in outlet proximity by drinking and marijuana use status, and 3) Tests feasibility of obtaining real-time data to study adolescent proximity to outlets. U.S. adolescents (N = 18) aged 16-17 (50% female) carried GPS-enabled smartphones for one week with their locations tracked. The geographic areas where adolescents spend time, activity spaces, were created by connecting GPS points sequentially and adding spatial buffers around routes. Proximity to outlets was greater during after school and evening hours. Drinkers and marijuana users were in proximity to outlets 1½ to 2 times more than non-users. Findings provide information about where adolescents spend time and times of greatest risk, informing prevention efforts. Copyright © 2016 The Foundation for Professionals in Services for Adolescents. Published by Elsevier Ltd. All rights reserved.

Extracting Corresponding Point Based on Texture Synthesis for Nearly Flat Textureless Object Surface

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Min Mao

2015-01-01

Full Text Available Since the image feature points are always gathered at the range with significant intensity change, such as textured portions or edges of an image, which can be detected by the state-of-the-art intensity based point-detectors, there is nearly no point in the areas of low textured detected by classical interest-point detectors. In this paper we describe a novel algorithm based on affine transform and graph cut for interest point detecting and matching from wide baseline image pairs with weakly textured object. The detection and matching mechanism can be separated into three steps: firstly, the information on the large textureless areas will be enhanced by adding textures through the proposed texture synthesis algorithm TSIQ. Secondly, the initial interest-point set is detected by classical interest-point detectors. Finally, graph cuts are used to find the globally optimal set of matching points on stereo pairs. The efficacy of the proposed algorithm is verified by three kinds of experiments, that is, the influence of point detecting from synthetic texture with different texture sample, the stability under the different geometric transformations, and the performance to improve the quasi-dense matching algorithm, respectively.

Fast algorithm for Morphological Filters

International Nuclear Information System (INIS)

Lou Shan; Jiang Xiangqian; Scott, Paul J

2011-01-01

In surface metrology, morphological filters, which evolved from the envelope filtering system (E-system) work well for functional prediction of surface finish in the analysis of surfaces in contact. The naive algorithms are time consuming, especially for areal data, and not generally adopted in real practice. A fast algorithm is proposed based on the alpha shape. The hull obtained by rolling the alpha ball is equivalent to the morphological opening/closing in theory. The algorithm depends on Delaunay triangulation with time complexity O(nlogn). In comparison to the naive algorithms it generates the opening and closing envelope without combining dilation and erosion. Edge distortion is corrected by reflective padding for open profiles/surfaces. Spikes in the sample data are detected and points interpolated to prevent singularities. The proposed algorithm works well both for morphological profile and area filters. Examples are presented to demonstrate the validity and superiority on efficiency of this algorithm over the naive algorithm.

Quantum Proximity Resonances

International Nuclear Information System (INIS)

Heller, E.J.

1996-01-01

It is well known that at long wavelengths λ an s-wave scatterer can have a scattering cross section σ on the order of λ 2 , much larger than its physical size, as measured by the range of its potential. Very interesting phenomena can arise when two or more identical scatterers are placed close together, well within one wavelength. We show that, for a pair of identical scatterers, an extremely narrow p-wave open-quote open-quote proximity close-quote close-quote resonance develops from a broader s-wave resonance of the individual scatterers. A new s-wave resonance of the pair also appears. The relation of these proximity resonances (so called because they appear when the scatterers are close together) to the Thomas and Efimov effects is discussed. copyright 1996 The American Physical Society

Multi-scale Clustering of Points Synthetically Considering Lines and Polygons Distribution

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YU Li

2015-10-01

Full Text Available Considering the complexity and discontinuity of spatial data distribution, a clustering algorithm of points was proposed. To accurately identify and express the spatial correlation among points,lines and polygons, a Voronoi diagram that is generated by all spatial features is introduced. According to the distribution characteristics of point's position, an area threshold used to control clustering granularity was calculated. Meanwhile, judging scale convergence by constant area threshold, the algorithm classifies spatial features based on multi-scale, with an O(n log n running time.Results indicate that spatial scale converges self-adaptively according with distribution of points.Without the custom parameters, the algorithm capable to discover arbitrary shape clusters which be bound by lines and polygons, and is robust for outliers.

A Doubly Stochastic Change Point Detection Algorithm for Noisy Biological Signals

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Nathan Gold

2018-01-01

Full Text Available Experimentally and clinically collected time series data are often contaminated with significant confounding noise, creating short, noisy time series. This noise, due to natural variability and measurement error, poses a challenge to conventional change point detection methods. We propose a novel and robust statistical method for change point detection for noisy biological time sequences. Our method is a significant improvement over traditional change point detection methods, which only examine a potential anomaly at a single time point. In contrast, our method considers all suspected anomaly points and considers the joint probability distribution of the number of change points and the elapsed time between two consecutive anomalies. We validate our method with three simulated time series, a widely accepted benchmark data set, two geological time series, a data set of ECG recordings, and a physiological data set of heart rate variability measurements of fetal sheep model of human labor, comparing it to three existing methods. Our method demonstrates significantly improved performance over the existing point-wise detection methods.

Early results for treatment of two- and three-part fractures of the proximal humerus using Contours PHP (proximal humeral plate).

Science.gov (United States)

Biazzo, Alessio; Cardile, Carlo; Brunelli, Luca; Ragni, Paolo; Clementi, Daniele

2017-04-28

The management of displaced 2- and 3-part fractures of the proximal humerus is controversial, both in younger and in elderly patients. The purpose of this paper is to evaluate the functional results of the Contours Proximal Humerus Plate (OrthofixR, Bussolengo,Verona, Italy), for the treatment of displaced 2- and 3-part fractures of the proximal humerus. We retrospectively reviewed 55 patients with proximal humerus fractures, who underwent osteosynthesis with Contours Proximal Humerus Plate from December 2011 to March 2015. We had 21 patients with 2-part fractures and with an average age of 67.1 years and 34 patients with 3-part fractures, with average age of 63.6 years. The average union time was 3 months. The mean Constant score was 67 for 2-part fracture group and 64.9 for 3-part fracture group. The difference was not statistically significant (p = 0.18). The overall complication rate was 14.5 %. Six patients underwent additional surgery (10.9%). The most frequent major complication was secondary loss of reduction following varus collapse of the fracture (2 cases). In these patients, there was loss of medial hinge integrity due to impaction and osteoporosis. The placement of the main locking screw in the calcar area to provide inferomedial support is the rational of the Contours Proximal Humerus Plate. Osteosynthesis with Contours Proximal Humerus Plate is a safe system for treating displaced 2- and 3-part fractures of the proximal humerus, with good functional results and complication rates comparable to those reported in the literature.

An automated and robust image processing algorithm for glaucoma diagnosis from fundus images using novel blood vessel tracking and bend point detection.

Science.gov (United States)

M, Soorya; Issac, Ashish; Dutta, Malay Kishore

2018-02-01

Glaucoma is an ocular disease which can cause irreversible blindness. The disease is currently identified using specialized equipment operated by optometrists manually. The proposed work aims to provide an efficient imaging solution which can help in automating the process of Glaucoma diagnosis using computer vision techniques from digital fundus images. The proposed method segments the optic disc using a geometrical feature based strategic framework which improves the detection accuracy and makes the algorithm invariant to illumination and noise. Corner thresholding and point contour joining based novel methods are proposed to construct smooth contours of Optic Disc. Based on a clinical approach as used by ophthalmologist, the proposed algorithm tracks blood vessels inside the disc region and identifies the points at which first vessel bend from the optic disc boundary and connects them to obtain the contours of Optic Cup. The proposed method has been compared with the ground truth marked by the medical experts and the similarity parameters, used to determine the performance of the proposed method, have yield a high similarity of segmentation. The proposed method has achieved a macro-averaged f-score of 0.9485 and accuracy of 97.01% in correctly classifying fundus images. The proposed method is clinically significant and can be used for Glaucoma screening over a large population which will work in a real time. Copyright © 2017 Elsevier B.V. All rights reserved.

Solving Optimization Problems via Vortex Optimization Algorithm and Cognitive Development Optimization Algorithm

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Ahmet Demir

2017-01-01

Full Text Available In the fields which require finding the most appropriate value, optimization became a vital approach to employ effective solutions. With the use of optimization techniques, many different fields in the modern life have found solutions to their real-world based problems. In this context, classical optimization techniques have had an important popularity. But after a while, more advanced optimization problems required the use of more effective techniques. At this point, Computer Science took an important role on providing software related techniques to improve the associated literature. Today, intelligent optimization techniques based on Artificial Intelligence are widely used for optimization problems. The objective of this paper is to provide a comparative study on the employment of classical optimization solutions and Artificial Intelligence solutions for enabling readers to have idea about the potential of intelligent optimization techniques. At this point, two recently developed intelligent optimization algorithms, Vortex Optimization Algorithm (VOA and Cognitive Development Optimization Algorithm (CoDOA, have been used to solve some multidisciplinary optimization problems provided in the source book Thomas' Calculus 11th Edition and the obtained results have compared with classical optimization solutions. 

LSAH: a fast and efficient local surface feature for point cloud registration

Science.gov (United States)

Lu, Rongrong; Zhu, Feng; Wu, Qingxiao; Kong, Yanzi

2018-04-01

Point cloud registration is a fundamental task in high level three dimensional applications. Noise, uneven point density and varying point cloud resolutions are the three main challenges for point cloud registration. In this paper, we design a robust and compact local surface descriptor called Local Surface Angles Histogram (LSAH) and propose an effectively coarse to fine algorithm for point cloud registration. The LSAH descriptor is formed by concatenating five normalized sub-histograms into one histogram. The five sub-histograms are created by accumulating a different type of angle from a local surface patch respectively. The experimental results show that our LSAH is more robust to uneven point density and point cloud resolutions than four state-of-the-art local descriptors in terms of feature matching. Moreover, we tested our LSAH based coarse to fine algorithm for point cloud registration. The experimental results demonstrate that our algorithm is robust and efficient as well.

An Approximate Redistributed Proximal Bundle Method with Inexact Data for Minimizing Nonsmooth Nonconvex Functions

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Jie Shen

2015-01-01

Full Text Available We describe an extension of the redistributed technique form classical proximal bundle method to the inexact situation for minimizing nonsmooth nonconvex functions. The cutting-planes model we construct is not the approximation to the whole nonconvex function, but to the local convexification of the approximate objective function, and this kind of local convexification is modified dynamically in order to always yield nonnegative linearization errors. Since we only employ the approximate function values and approximate subgradients, theoretical convergence analysis shows that an approximate stationary point or some double approximate stationary point can be obtained under some mild conditions.

Proximal Hamstring Tendinosis and Partial Ruptures.

Science.gov (United States)

Startzman, Ashley N; Fowler, Oliver; Carreira, Dominic

2017-07-01

Proximal hamstring tendinosis and partial hamstring origin ruptures are painful conditions of the proximal thigh and hip that may occur in the acute, chronic, or acute on chronic setting. Few publications exist related to their diagnosis and management. This systematic review discusses the incidence, treatment, and prognosis of proximal hamstring tendinosis and partial hamstring ruptures. Conservative treatment measures include nonsteroidal anti-inflammatory drugs, physical therapy, rest, and ice. If these measures fail, platelet-rich plasma or shockwave therapy may be considered. When refractory to conservative management, these injuries may be treated with surgical debridement and hamstring reattachment. [Orthopedics. 2017; 40(4):e574-e582.]. Copyright 2017, SLACK Incorporated.

Where genetic algorithms excel.

Science.gov (United States)

Baum, E B; Boneh, D; Garrett, C

2001-01-01

We analyze the performance of a genetic algorithm (GA) we call Culling, and a variety of other algorithms, on a problem we refer to as the Additive Search Problem (ASP). We show that the problem of learning the Ising perceptron is reducible to a noisy version of ASP. Noisy ASP is the first problem we are aware of where a genetic-type algorithm bests all known competitors. We generalize ASP to k-ASP to study whether GAs will achieve "implicit parallelism" in a problem with many more schemata. GAs fail to achieve this implicit parallelism, but we describe an algorithm we call Explicitly Parallel Search that succeeds. We also compute the optimal culling point for selective breeding, which turns out to be independent of the fitness function or the population distribution. We also analyze a mean field theoretic algorithm performing similarly to Culling on many problems. These results provide insight into when and how GAs can beat competing methods.

A Sweepline Algorithm for Generalized Delaunay Triangulations

DEFF Research Database (Denmark)

Skyum, Sven

We give a deterministic O(n log n) sweepline algorithm to construct the generalized Voronoi diagram for n points in the plane or rather its dual the generalized Delaunay triangulation. The algorithm uses no transformations and it is developed solely from the sweepline paradigm together...

Searching for the majority: algorithms of voluntary control.

Directory of Open Access Journals (Sweden)

Jin Fan

Full Text Available Voluntary control of information processing is crucial to allocate resources and prioritize the processes that are most important under a given situation; the algorithms underlying such control, however, are often not clear. We investigated possible algorithms of control for the performance of the majority function, in which participants searched for and identified one of two alternative categories (left or right pointing arrows as composing the majority in each stimulus set. We manipulated the amount (set size of 1, 3, and 5 and content (ratio of left and right pointing arrows within a set of the inputs to test competing hypotheses regarding mental operations for information processing. Using a novel measure based on computational load, we found that reaction time was best predicted by a grouping search algorithm as compared to alternative algorithms (i.e., exhaustive or self-terminating search. The grouping search algorithm involves sampling and resampling of the inputs before a decision is reached. These findings highlight the importance of investigating the implications of voluntary control via algorithms of mental operations.

Detection algorithm of infrared small target based on improved SUSAN operator

Science.gov (United States)

Liu, Xingmiao; Wang, Shicheng; Zhao, Jing

2010-10-01

The methods of detecting small moving targets in infrared image sequences that contain moving nuisance objects and background noise is analyzed in this paper. A novel infrared small target detection algorithm based on improved SUSAN operator is put forward. The algorithm selects double templates for the infrared small target detection: one size is greater than the small target point size and another size is equal to the small target point size. First, the algorithm uses the big template to calculate the USAN of each pixel in the image and detect the small target, the edge of the image and isolated noise pixels; Then the algorithm uses the another template to calculate the USAN of pixels detected in the first step and improves the principles of SUSAN algorithm based on the characteristics of the small target so that the algorithm can only detect small targets and don't sensitive to the edge pixels of the image and isolated noise pixels. So the interference of the edge of the image and isolate noise points are removed and the candidate target points can be identified; At last, the target is detected by utilizing the continuity and consistency of target movement. The experimental results indicate that the improved SUSAN detection algorithm can quickly and effectively detect the infrared small targets.

A novel clustering algorithm based on quantum games

International Nuclear Information System (INIS)

Li Qiang; He Yan; Jiang Jingping

2009-01-01

Enormous successes have been made by quantum algorithms during the last decade. In this paper, we combine the quantum game with the problem of data clustering, and then develop a quantum-game-based clustering algorithm, in which data points in a dataset are considered as players who can make decisions and implement quantum strategies in quantum games. After each round of a quantum game, each player's expected payoff is calculated. Later, he uses a link-removing-and-rewiring (LRR) function to change his neighbors and adjust the strength of links connecting to them in order to maximize his payoff. Further, algorithms are discussed and analyzed in two cases of strategies, two payoff matrixes and two LRR functions. Consequently, the simulation results have demonstrated that data points in datasets are clustered reasonably and efficiently, and the clustering algorithms have fast rates of convergence. Moreover, the comparison with other algorithms also provides an indication of the effectiveness of the proposed approach.

Proximal Participation: A Pathway into Work

Science.gov (United States)

Chan, Selena

2013-01-01

In a longitudinal case study of apprentices, the term proximal participation was coined to describe the entry process of young people, with unclear career destinations, into the trade of baking. This article unravels the significance of proximal participation in the decision-making processes of young people who enter a trade through initial…

A guidance and control algorithm for scent tracking micro-robotic vehicle swarms

International Nuclear Information System (INIS)

Dohner, J.L.

1998-03-01

Cooperative micro-robotic scent tracking vehicles are designed to collectively sniff out locations of high scent concentrations in unknown, geometrically complex environments. These vehicles are programmed with guidance and control algorithms that allow inter cooperation among vehicles. In this paper a cooperative guidance and control algorithm for scent tracking micro-robotic vehicles is presented. This algorithm is comprised of a sensory compensation sub-algorithm using point source cancellation, a guidance sub-algorithm using gradient descent tracking, and a control sub-algorithm using proportional feedback. The concepts of social rank and point source cancellation are new concepts introduced within. Simulation results for cooperative vehicles swarms are given. Limitations are discussed

A guidance and control algorithm for scent tracking micro-robotic vehicle swarms

Energy Technology Data Exchange (ETDEWEB)

Dohner, J.L. [Sandia National Labs., Albuquerque, NM (United States). Structural Dynamics Dept.

1998-03-01

Cooperative micro-robotic scent tracking vehicles are designed to collectively sniff out locations of high scent concentrations in unknown, geometrically complex environments. These vehicles are programmed with guidance and control algorithms that allow inter cooperation among vehicles. In this paper a cooperative guidance and control algorithm for scent tracking micro-robotic vehicles is presented. This algorithm is comprised of a sensory compensation sub-algorithm using point source cancellation, a guidance sub-algorithm using gradient descent tracking, and a control sub-algorithm using proportional feedback. The concepts of social rank and point source cancellation are new concepts introduced within. Simulation results for cooperative vehicles swarms are given. Limitations are discussed.

A Framework To Support Management Of HIVAIDS Using K-Means And Random Forest Algorithm

Directory of Open Access Journals (Sweden)

Gladys Iseu

2017-06-01

Full Text Available Healthcare industry generates large amounts of complex data about patients hospital resources disease management electronic patient records and medical devices among others. The availability of these huge amounts of medical data creates a need for powerful mining tools to support health care professionals in diagnosis treatment and management of HIVAIDS. Several data mining techniques have been used in management of different data sets. Data mining techniques have been categorized into regression algorithms segmentation algorithms association algorithms sequence analysis algorithms and classification algorithms. In the medical field there has not been a specific study that has incorporated two or more data mining algorithms hence limiting decision making levels by medical practitioners. This study identified the extent to which K-means algorithm cluster patient characteristics it has also evaluated the extent to which random forest algorithm can classify the data for informed decision making as well as design a framework to support medical decision making in the treatment of HIVAIDS related diseases in Kenya. The paper further used random forest classification algorithm to compute proximities between pairs of cases that can be used in clustering locating outliers or by scaling to give interesting views of the data.

Experiments with conjugate gradient algorithms for homotopy curve tracking

Science.gov (United States)

Irani, Kashmira M.; Ribbens, Calvin J.; Watson, Layne T.; Kamat, Manohar P.; Walker, Homer F.

1991-01-01

There are algorithms for finding zeros or fixed points of nonlinear systems of equations that are globally convergent for almost all starting points, i.e., with probability one. The essence of all such algorithms is the construction of an appropriate homotopy map and then tracking some smooth curve in the zero set of this homotopy map. HOMPACK is a mathematical software package implementing globally convergent homotopy algorithms with three different techniques for tracking a homotopy zero curve, and has separate routines for dense and sparse Jacobian matrices. The HOMPACK algorithms for sparse Jacobian matrices use a preconditioned conjugate gradient algorithm for the computation of the kernel of the homotopy Jacobian matrix, a required linear algebra step for homotopy curve tracking. Here, variants of the conjugate gradient algorithm are implemented in the context of homotopy curve tracking and compared with Craig's preconditioned conjugate gradient method used in HOMPACK. The test problems used include actual large scale, sparse structural mechanics problems.

A Parallel Particle Swarm Optimization Algorithm Accelerated by Asynchronous Evaluations

Science.gov (United States)

Venter, Gerhard; Sobieszczanski-Sobieski, Jaroslaw

2005-01-01

A parallel Particle Swarm Optimization (PSO) algorithm is presented. Particle swarm optimization is a fairly recent addition to the family of non-gradient based, probabilistic search algorithms that is based on a simplified social model and is closely tied to swarming theory. Although PSO algorithms present several attractive properties to the designer, they are plagued by high computational cost as measured by elapsed time. One approach to reduce the elapsed time is to make use of coarse-grained parallelization to evaluate the design points. Previous parallel PSO algorithms were mostly implemented in a synchronous manner, where all design points within a design iteration are evaluated before the next iteration is started. This approach leads to poor parallel speedup in cases where a heterogeneous parallel environment is used and/or where the analysis time depends on the design point being analyzed. This paper introduces an asynchronous parallel PSO algorithm that greatly improves the parallel e ciency. The asynchronous algorithm is benchmarked on a cluster assembled of Apple Macintosh G5 desktop computers, using the multi-disciplinary optimization of a typical transport aircraft wing as an example.

Ultimate and proximate explanations of strong reciprocity.

Science.gov (United States)

Vromen, Jack

2017-08-23

Strong reciprocity (SR) has recently been subject to heated debate. In this debate, the "West camp" (West et al. in Evol Hum Behav 32(4):231-262, 2011), which is critical of the case for SR, and the "Laland camp" (Laland et al. in Science, 334(6062):1512-1516, 2011, Biol Philos 28(5):719-745, 2013), which is sympathetic to the case of SR, seem to take diametrically opposed positions. The West camp criticizes advocates of SR for conflating proximate and ultimate causation. SR is said to be a proximate mechanism that is put forward by its advocates as an ultimate explanation of human cooperation. The West camp thus accuses advocates of SR for not heeding Mayr's original distinction between ultimate and proximate causation. The Laland camp praises advocates of SR for revising Mayr's distinction. Advocates of SR are said to replace Mayr's uni-directional view on the relation between ultimate and proximate causes by the bi-directional one of reciprocal causation. The paper argues that both the West camp and the Laland camp misrepresent what advocates of SR are up to. The West camp is right that SR is a proximate cause of human cooperation. But rather than putting forward SR as an ultimate explanation, as the West camp argues, advocates of SR believe that SR itself is in need of ultimate explanation. Advocates of SR tend to take gene-culture co-evolutionary theory as the correct meta-theoretical framework for advancing ultimate explanations of SR. Appearances notwithstanding, gene-culture coevolutionary theory does not imply Laland et al.'s notion of reciprocal causation. "Reciprocal causation" suggests that proximate and ultimate causes interact simultaneously, while advocates of SR assume that they interact sequentially. I end by arguing that the best way to understand the debate is by disambiguating Mayr's ultimate-proximate distinction. I propose to reserve "ultimate" and "proximate" for different sorts of explanations, and to use other terms for distinguishing

Combined fixation, intern and external, in proximal complex fractures of the tibia

International Nuclear Information System (INIS)

Quintero Laverde, Jaime; Lozano Ortiz, Victor Hugo; Rojas Duque, Guillermo

2002-01-01

Between August of 1997 and December of 2001, they were treated in the orthopedics department and traumatology of the Hospital Clinica San Rafael, 16 patients with proximal complex fractures of the tibia, using internal fixation with plate in the lateral column and an unilateral external fixer, for the medial column. It carries out a clinical and radiological pursuit with average of 27 months (minimum 4.5, maximum 40 months). In 15 patients (93,7%) it was obtained a primary consolidation and 1 case (6,2%) it presented retard in the consolidation being necessary the placement of bony implants. in 2 cases (12,5%) there was superficial infection, one in the itinerary of the nails and another in area of superficial necrosis in soft fabrics in a closed fracture. single 1 case (6,2) it presented deep infection, which, it improve with bony curettage and antibiotics. In the final radiographic evaluation, 2 cases (12,5%) they presented depression of the lateral plate; according to the functional scale of Rasmussen excellent results were obtained (27 to 30 points) in 11 cases (68,7%) and good (20 to 26 points) in 5 cases (31,2%). The radiographic results and functional global they suggest that the combination of a technique less invasive in this area criticizes, it represents a good alternative for the treatment of the proximal complex fractures of the tibia

Prosthetic replacement for proximal humeral fractures.

Science.gov (United States)

Kontakis, George; Tosounidis, Theodoros; Galanakis, Ioannis; Megas, Panagiotis

2008-12-01

The ideal management of complex proximal humeral fractures continues to be debatable. Evolution of proximal humeral fracture management, during the past decade, led to the implementation of many innovations in surgical treatment. Even though the pendulum of treatment seems to swing towards new trends such as locked plating, hemiarthroplasty remains a valid and reliable option that serves the patient's needs well. Hemiarthroplasty is indicated for complex proximal humeral fractures in elderly patients with poor bone stock and when internal fixation is difficult or unreliable. Hemiarthroplasty provides a better result when it is performed early post-injury. Stem height, retroversion and tuberosity positioning are technical aspects of utmost importance. Additionally reverse total shoulder arthroplasty is an alternative new modality that can be used as a primary solution in selected patients with proximal humeral fracture treatment. Failed hemiarthroplasty and fracture sequelae can be successfully managed with reverse total shoulder arthroplasty. Individual decision-making and tailored treatment that takes into consideration the personality of the fracture and the patient's characteristics should be used.

Reconstructing rotations and rigid body motions from exact point correspondences through reflections

NARCIS (Netherlands)

Fontijne, D.; Dorst, L.; Dorst, L.; Lasenby, J.

2011-01-01

We describe a new algorithm to reconstruct a rigid body motion from point correspondences. The algorithm works by constructing a series of reflections which align the points with their correspondences one by one. This is naturally and efficiently implemented in the conformal model of geometric

Real-time estimation of prostate tumor rotation and translation with a kV imaging system based on an iterative closest point algorithm

International Nuclear Information System (INIS)

Tehrani, Joubin Nasehi; O’Brien, Ricky T; Keall, Paul; Poulsen, Per Rugaard

2013-01-01

Previous studies have shown that during cancer radiotherapy a small translation or rotation of the tumor can lead to errors in dose delivery. Current best practice in radiotherapy accounts for tumor translations, but is unable to address rotation due to a lack of a reliable real-time estimate. We have developed a method based on the iterative closest point (ICP) algorithm that can compute rotation from kilovoltage x-ray images acquired during radiation treatment delivery. A total of 11 748 kilovoltage (kV) images acquired from ten patients (one fraction for each patient) were used to evaluate our tumor rotation algorithm. For each kV image, the three dimensional coordinates of three fiducial markers inside the prostate were calculated. The three dimensional coordinates were used as input to the ICP algorithm to calculate the real-time tumor rotation and translation around three axes. The results show that the root mean square error was improved for real-time calculation of tumor displacement from a mean of 0.97 mm with the stand alone translation to a mean of 0.16 mm by adding real-time rotation and translation displacement with the ICP algorithm. The standard deviation (SD) of rotation for the ten patients was 2.3°, 0.89° and 0.72° for rotation around the right–left (RL), anterior–posterior (AP) and superior–inferior (SI) directions respectively. The correlation between all six degrees of freedom showed that the highest correlation belonged to the AP and SI translation with a correlation of 0.67. The second highest correlation in our study was between the rotation around RL and rotation around AP, with a correlation of −0.33. Our real-time algorithm for calculation of rotation also confirms previous studies that have shown the maximum SD belongs to AP translation and rotation around RL. ICP is a reliable and fast algorithm for estimating real-time tumor rotation which could create a pathway to investigational clinical treatment studies requiring

Detecting structural breaks in time series via genetic algorithms

DEFF Research Database (Denmark)

Doerr, Benjamin; Fischer, Paul; Hilbert, Astrid

2016-01-01

of the time series under consideration is available. Therefore, a black-box optimization approach is our method of choice for detecting structural breaks. We describe a genetic algorithm framework which easily adapts to a large number of statistical settings. To evaluate the usefulness of different crossover...... and mutation operations for this problem, we conduct extensive experiments to determine good choices for the parameters and operators of the genetic algorithm. One surprising observation is that use of uniform and one-point crossover together gave significantly better results than using either crossover...... operator alone. Moreover, we present a specific fitness function which exploits the sparse structure of the break points and which can be evaluated particularly efficiently. The experiments on artificial and real-world time series show that the resulting algorithm detects break points with high precision...

An Efficient Algorithm for the Maximum Distance Problem

Directory of Open Access Journals (Sweden)

Gabrielle Assunta Grün

2001-12-01

Full Text Available Efficient algorithms for temporal reasoning are essential in knowledge-based systems. This is central in many areas of Artificial Intelligence including scheduling, planning, plan recognition, and natural language understanding. As such, scalability is a crucial consideration in temporal reasoning. While reasoning in the interval algebra is NP-complete, reasoning in the less expressive point algebra is tractable. In this paper, we explore an extension to the work of Gerevini and Schubert which is based on the point algebra. In their seminal framework, temporal relations are expressed as a directed acyclic graph partitioned into chains and supported by a metagraph data structure, where time points or events are represented by vertices, and directed edges are labelled with < or ≤. They are interested in fast algorithms for determining the strongest relation between two events. They begin by developing fast algorithms for the case where all points lie on a chain. In this paper, we are interested in a generalization of this, namely we consider the problem of finding the maximum ``distance'' between two vertices in a chain ; this problem arises in real world applications such as in process control and crew scheduling. We describe an O(n time preprocessing algorithm for the maximum distance problem on chains. It allows queries for the maximum number of < edges between two vertices to be answered in O(1 time. This matches the performance of the algorithm of Gerevini and Schubert for determining the strongest relation holding between two vertices in a chain.

Point-point and point-line moving-window correlation spectroscopy and its applications

Science.gov (United States)

Zhou, Qun; Sun, Suqin; Zhan, Daqi; Yu, Zhiwu

2008-07-01

In this paper, we present a new extension of generalized two-dimensional (2D) correlation spectroscopy. Two new algorithms, namely point-point (P-P) correlation and point-line (P-L) correlation, have been introduced to do the moving-window 2D correlation (MW2D) analysis. The new method has been applied to a spectral model consisting of two different processes. The results indicate that P-P correlation spectroscopy can unveil the details and re-constitute the entire process, whilst the P-L can provide general feature of the concerned processes. Phase transition behavior of dimyristoylphosphotidylethanolamine (DMPE) has been studied using MW2D correlation spectroscopy. The newly proposed method verifies that the phase transition temperature is 56 °C, same as the result got from a differential scanning calorimeter. To illustrate the new method further, a lysine and lactose mixture has been studied under thermo perturbation. Using the P-P MW2D, the Maillard reaction of the mixture was clearly monitored, which has been very difficult using conventional display of FTIR spectra.

Patients on hemodialysis are better served by a proximal arteriovenous fistula for long-term venous access.

LENUS (Irish Health Repository)

Sultan, Sherif

2012-11-01

Patients with end-stage renal disease should have arteriovenous fistula (AVF) formation 3 to 6 months prior to commencing hemodialysis (HD). However, this is not always possible with strained health care resources. We aim to compare autologous proximal AVF (PAVF) with distal AVF (DAVF) in patients already on HD. Primary end point is 4-year functional primary. Secondary end point is freedom from major adverse clinical events (MACEs). From January 2003 to June 2009, out of 495 AVF formations, 179 (36%) patients were already on HD. These patients had 200 AVF formations (49 DAVF vs 151 PAVF) in arms in which no previous fistula had been formed. No synthetic graft was used. Four-year primary functional patency significantly improved with PAVF (68.9% ± SD 8.8%) compared to DAVF (7.3% ± SD 4.9%; P < .0001). Five-year freedom from MACE was 85% with PAVF compared to 40% with DAVF (P < .005). Proximal AVF bestows long-term functional access with fewer complications compared to DAVF for patients already on HD.

Reducing the time requirement of k-means algorithm.

Science.gov (United States)

Osamor, Victor Chukwudi; Adebiyi, Ezekiel Femi; Oyelade, Jelilli Olarenwaju; Doumbia, Seydou

2012-01-01

Traditional k-means and most k-means variants are still computationally expensive for large datasets, such as microarray data, which have large datasets with large dimension size d. In k-means clustering, we are given a set of n data points in d-dimensional space R(d) and an integer k. The problem is to determine a set of k points in R(d), called centers, so as to minimize the mean squared distance from each data point to its nearest center. In this work, we develop a novel k-means algorithm, which is simple but more efficient than the traditional k-means and the recent enhanced k-means. Our new algorithm is based on the recently established relationship between principal component analysis and the k-means clustering. We provided the correctness proof for this algorithm. Results obtained from testing the algorithm on three biological data and six non-biological data (three of these data are real, while the other three are simulated) also indicate that our algorithm is empirically faster than other known k-means algorithms. We assessed the quality of our algorithm clusters against the clusters of a known structure using the Hubert-Arabie Adjusted Rand index (ARI(HA)). We found that when k is close to d, the quality is good (ARI(HA)>0.8) and when k is not close to d, the quality of our new k-means algorithm is excellent (ARI(HA)>0.9). In this paper, emphases are on the reduction of the time requirement of the k-means algorithm and its application to microarray data due to the desire to create a tool for clustering and malaria research. However, the new clustering algorithm can be used for other clustering needs as long as an appropriate measure of distance between the centroids and the members is used. This has been demonstrated in this work on six non-biological data.

Parkinson’s Disease Prevalence and Proximity to Agricultural Cultivated Fields

Directory of Open Access Journals (Sweden)

Maayan Yitshak Sade

2015-01-01

Full Text Available The risk for developing Parkinson’s disease (PD is a combination of multiple environmental and genetic factors. The Negev (Southern Israel contains approximately 252.5 km2 of agricultural cultivated fields (ACF. We aimed to estimate the prevalence and incidence of PD and to examine possible geographical clustering and associations with agricultural exposures. We screened all “Clalit” Health Services members in the Negev (70% of the population between the years 2000 and 2012. Individual demographic, clinical, and medication prescription data were available. We used a refined medication tracer algorithm to identify PD patients. We used mixed Poisson models to calculate the smoothed standardized incidence rates (SIRs for each locality. We identified ACF and calculate the size and distance of the fields from each locality. We identified 3,792 cases of PD. SIRs were higher than expected in Jewish rural localities (median SIR [95% CI]: 1.41 [1.28; 1.53] in 2001–2004, 1.62 [1.48; 1.76] in 2005–2008, and 1.57 [1.44; 1.80] in 2009–2012. Highest SIR was observed in localities located in proximity to large ACF (SIR 1.54, 95% CI 1.32; 1.79. In conclusion, in this population based study we found that PD SIRs were higher than expected in rural localities. Furthermore, it appears that proximity to ACF and the field size contribute to PD risk.

A review of cooperative and uncooperative spacecraft pose determination techniques for close-proximity operations

Science.gov (United States)

Opromolla, Roberto; Fasano, Giancarmine; Rufino, Giancarlo; Grassi, Michele

2017-08-01

The capability of an active spacecraft to accurately estimate its relative position and attitude (pose) with respect to an active/inactive, artificial/natural space object (target) orbiting in close-proximity is required to carry out various activities like formation flying, on-orbit servicing, active debris removal, and space exploration. According to the specific mission scenario, the pose determination task involves both theoretical and technological challenges related to the search for the most suitable algorithmic solution and sensor architecture, respectively. As regards the latter aspect, electro-optical sensors represent the best option as their use is compatible with mass and power limitation of micro and small satellites, and their measurements can be processed to estimate all the pose parameters. Overall, the degree of complexity of the challenges related to pose determination largely varies depending on the nature of the targets, which may be actively/passively cooperative, uncooperative but known, or uncooperative and unknown space objects. In this respect, while cooperative pose determination has been successfully demonstrated in orbit, the uncooperative case is still under study by universities, research centers, space agencies and private companies. However, in both the cases, the demand for space applications involving relative navigation maneuvers, also in close-proximity, for which pose determination capabilities are mandatory, is significantly increasing. In this framework, a review of state-of-the-art techniques and algorithms developed in the last decades for cooperative and uncooperative pose determination by processing data provided by electro-optical sensors is herein presented. Specifically, their main advantages and drawbacks in terms of achieved performance, computational complexity, and sensitivity to variability of pose and target geometry, are highlighted.

An algorithmic characterization of P-matricity

OpenAIRE

Ben Gharbia , Ibtihel; Gilbert , Jean Charles

2013-01-01

International audience; It is shown that a matrix M is a P-matrix if and only if, whatever is the vector q, the Newton-min algorithm does not cycle between two points when it is used to solve the linear complementarity problem 0 ≤ x ⊥ (Mx+q) ≥ 0.; Nous montrons dans cet article qu'une matrice M est une P-matrice si, et seulement si, quel que soit le vecteur q, l'algorithme de Newton-min ne fait pas de cycle de deux points lorsqu'il est utilisé pour résoudre le problème de compl\\émentarité lin...

a Gross Error Elimination Method for Point Cloud Data Based on Kd-Tree

Science.gov (United States)

Kang, Q.; Huang, G.; Yang, S.

2018-04-01

Point cloud data has been one type of widely used data sources in the field of remote sensing. Key steps of point cloud data's pro-processing focus on gross error elimination and quality control. Owing to the volume feature of point could data, existed gross error elimination methods need spend massive memory both in space and time. This paper employed a new method which based on Kd-tree algorithm to construct, k-nearest neighbor algorithm to search, settled appropriate threshold to determine with result turns out a judgement that whether target point is or not an outlier. Experimental results show that, our proposed algorithm will help to delete gross error in point cloud data and facilitate to decrease memory consumption, improve efficiency.

A GROSS ERROR ELIMINATION METHOD FOR POINT CLOUD DATA BASED ON KD-TREE

Directory of Open Access Journals (Sweden)

Q. Kang

2018-04-01

Full Text Available Point cloud data has been one type of widely used data sources in the field of remote sensing. Key steps of point cloud data’s pro-processing focus on gross error elimination and quality control. Owing to the volume feature of point could data, existed gross error elimination methods need spend massive memory both in space and time. This paper employed a new method which based on Kd-tree algorithm to construct, k-nearest neighbor algorithm to search, settled appropriate threshold to determine with result turns out a judgement that whether target point is or not an outlier. Experimental results show that, our proposed algorithm will help to delete gross error in point cloud data and facilitate to decrease memory consumption, improve efficiency.

Robust MST-Based Clustering Algorithm.

Science.gov (United States)

Liu, Qidong; Zhang, Ruisheng; Zhao, Zhili; Wang, Zhenghai; Jiao, Mengyao; Wang, Guangjing

2018-06-01

Minimax similarity stresses the connectedness of points via mediating elements rather than favoring high mutual similarity. The grouping principle yields superior clustering results when mining arbitrarily-shaped clusters in data. However, it is not robust against noises and outliers in the data. There are two main problems with the grouping principle: first, a single object that is far away from all other objects defines a separate cluster, and second, two connected clusters would be regarded as two parts of one cluster. In order to solve such problems, we propose robust minimum spanning tree (MST)-based clustering algorithm in this letter. First, we separate the connected objects by applying a density-based coarsening phase, resulting in a low-rank matrix in which the element denotes the supernode by combining a set of nodes. Then a greedy method is presented to partition those supernodes through working on the low-rank matrix. Instead of removing the longest edges from MST, our algorithm groups the data set based on the minimax similarity. Finally, the assignment of all data points can be achieved through their corresponding supernodes. Experimental results on many synthetic and real-world data sets show that our algorithm consistently outperforms compared clustering algorithms.

A polylogarithmic competitive algorithm for the k-server problem

NARCIS (Netherlands)

Bansal, N.; Buchbinder, N.; Madry, A.; Naor, J.

2011-01-01

We give the first polylogarithmic-competitive randomized online algorithm for the $k$-server problem on an arbitrary finite metric space. In particular, our algorithm achieves a competitive ratio of O(log^3 n log^2 k log log n) for any metric space on n points. Our algorithm improves upon the

Proximity sensor system development. CRADA final report

Energy Technology Data Exchange (ETDEWEB)

Haley, D.C. [Oak Ridge National Lab., TN (United States); Pigoski, T.M. [Merrit Systems, Inc. (United States)

1998-01-01

Lockheed Martin Energy Research Corporation (LMERC) and Merritt Systems, Inc. (MSI) entered into a Cooperative Research and Development Agreement (CRADA) for the development and demonstration of a compact, modular proximity sensing system suitable for application to a wide class of manipulator systems operated in support of environmental restoration and waste management activities. In teleoperated modes, proximity sensing provides the manipulator operator continuous information regarding the proximity of the manipulator to objects in the workspace. In teleoperated and robotic modes, proximity sensing provides added safety through the implementation of active whole arm collision avoidance capabilities. Oak Ridge National Laboratory (ORNL), managed by LMERC for the United States Department of Energy (DOE), has developed an application specific integrated circuit (ASIC) design for the electronics required to support a modular whole arm proximity sensing system based on the use of capacitive sensors developed at Sandia National Laboratories. The use of ASIC technology greatly reduces the size of the electronics required to support the selected sensor types allowing deployment of many small sensor nodes over a large area of the manipulator surface to provide maximum sensor coverage. The ASIC design also provides a communication interface to support sensor commands from and sensor data transmission to a distributed processing system which allows modular implementation and operation of the sensor system. MSI is a commercial small business specializing in proximity sensing systems based upon infrared and acoustic sensors.

Proximity sensor system development. CRADA final report

International Nuclear Information System (INIS)

Haley, D.C.; Pigoski, T.M.

1998-01-01

Lockheed Martin Energy Research Corporation (LMERC) and Merritt Systems, Inc. (MSI) entered into a Cooperative Research and Development Agreement (CRADA) for the development and demonstration of a compact, modular proximity sensing system suitable for application to a wide class of manipulator systems operated in support of environmental restoration and waste management activities. In teleoperated modes, proximity sensing provides the manipulator operator continuous information regarding the proximity of the manipulator to objects in the workspace. In teleoperated and robotic modes, proximity sensing provides added safety through the implementation of active whole arm collision avoidance capabilities. Oak Ridge National Laboratory (ORNL), managed by LMERC for the United States Department of Energy (DOE), has developed an application specific integrated circuit (ASIC) design for the electronics required to support a modular whole arm proximity sensing system based on the use of capacitive sensors developed at Sandia National Laboratories. The use of ASIC technology greatly reduces the size of the electronics required to support the selected sensor types allowing deployment of many small sensor nodes over a large area of the manipulator surface to provide maximum sensor coverage. The ASIC design also provides a communication interface to support sensor commands from and sensor data transmission to a distributed processing system which allows modular implementation and operation of the sensor system. MSI is a commercial small business specializing in proximity sensing systems based upon infrared and acoustic sensors

Locking plate fixation for proximal humerus fractures.

LENUS (Irish Health Repository)

Burke, Neil G

2012-02-01

Locking plates are increasingly used to surgically treat proximal humerus fractures. Knowledge of the bone quality of the proximal humerus is important. Studies have shown the medial and dorsal aspects of the proximal humeral head to have the highest bone strength, and this should be exploited by fixation techniques, particularly in elderly patients with osteoporosis. The goals of surgery for proximal humeral fractures should involve minimal soft tissue dissection and achieve anatomic reduction of the head complex with sufficient stability to allow for early shoulder mobilization. This article reviews various treatment options, in particular locking plate fixation. Locking plate fixation is associated with a high complication rate, such as avascular necrosis (7.9%), screw cutout (11.6%), and revision surgery (13.7%). These complications are frequently due to the varus deformation of the humeral head. Strategic screw placement in the humeral head would minimize the possibility of loss of fracture reduction and potential hardware complications. Locking plate fixation is a good surgical option for the management of proximal humerus fractures. Complications can be avoided by using better bone stock and by careful screw placement in the humeral head.

Proximal collagenous gastroenteritides:

DEFF Research Database (Denmark)

Nielsen, Ole Haagen; Riis, Lene Buhl; Danese, Silvio

2014-01-01

AIM: While collagenous colitis represents the most common form of the collagenous gastroenteritides, the collagenous entities affecting the proximal part of the gastrointestinal tract are much less recognized and possibly overlooked. The aim was to summarize the latest information through a syste...

Promoting proximal formative assessment with relational discourse

Science.gov (United States)

Scherr, Rachel E.; Close, Hunter G.; McKagan, Sarah B.

2012-02-01

The practice of proximal formative assessment - the continual, responsive attention to students' developing understanding as it is expressed in real time - depends on students' sharing their ideas with instructors and on teachers' attending to them. Rogerian psychology presents an account of the conditions under which proximal formative assessment may be promoted or inhibited: (1) Normal classroom conditions, characterized by evaluation and attention to learning targets, may present threats to students' sense of their own competence and value, causing them to conceal their ideas and reducing the potential for proximal formative assessment. (2) In contrast, discourse patterns characterized by positive anticipation and attention to learner ideas increase the potential for proximal formative assessment and promote self-directed learning. We present an analysis methodology based on these principles and demonstrate its utility for understanding episodes of university physics instruction.

Bayesian analysis of Markov point processes

DEFF Research Database (Denmark)

Berthelsen, Kasper Klitgaard; Møller, Jesper

2006-01-01

Recently Møller, Pettitt, Berthelsen and Reeves introduced a new MCMC methodology for drawing samples from a posterior distribution when the likelihood function is only specified up to a normalising constant. We illustrate the method in the setting of Bayesian inference for Markov point processes...... a partially ordered Markov point process as the auxiliary variable. As the method requires simulation from the "unknown" likelihood, perfect simulation algorithms for spatial point processes become useful....

Automated Extraction of 3D Trees from Mobile LiDAR Point Clouds

Directory of Open Access Journals (Sweden)

Y. Yu

2014-06-01

Full Text Available This paper presents an automated algorithm for extracting 3D trees directly from 3D mobile light detection and ranging (LiDAR data. To reduce both computational and spatial complexities, ground points are first filtered out from a raw 3D point cloud via blockbased elevation filtering. Off-ground points are then grouped into clusters representing individual objects through Euclidean distance clustering and voxel-based normalized cut segmentation. Finally, a model-driven method is proposed to achieve the extraction of 3D trees based on a pairwise 3D shape descriptor. The proposed algorithm is tested using a set of mobile LiDAR point clouds acquired by a RIEGL VMX-450 system. The results demonstrate the feasibility and effectiveness of the proposed algorithm.

Modulation Algorithms for Manipulating Nuclear Spin States

OpenAIRE

Liu, Boyang; Zhang, Ming; Dai, Hong-Yi

2013-01-01

We exploit the impact of exact frequency modulation on transition time of steering nuclear spin states from theoretical point of view. 1-stage and 2-stage Frequency-Amplitude-Phase modulation (FAPM) algorithms are proposed in contrast with 1-stage and 3-stage Amplitude-Phase modulation (APM) algorithms. The sufficient conditions are further present for transiting nuclear spin states within the specified time by these four modulation algorithms. It is demonstrated that transition time performa...

Psychological responses to the proximity of climate change

Science.gov (United States)

Brügger, Adrian; Dessai, Suraje; Devine-Wright, Patrick; Morton, Thomas A.; Pidgeon, Nicholas F.

2015-12-01

A frequent suggestion to increase individuals' willingness to take action on climate change and to support relevant policies is to highlight its proximal consequences, that is, those that are close in space and time. But previous studies that have tested this proximizing approach have not revealed the expected positive effects on individual action and support for addressing climate change. We present three lines of psychological reasoning that provide compelling arguments as to why highlighting proximal impacts of climate change might not be as effective a way to increase individual mitigation and adaptation efforts as is often assumed. Our contextualization of the proximizing approach within established psychological research suggests that, depending on the particular theoretical perspective one takes on this issue, and on specific individual characteristics suggested by these perspectives, proximizing can bring about the intended positive effects, can have no (visible) effect or can even backfire. Thus, the effects of proximizing are much more complex than is commonly assumed. Revealing this complexity contributes to a refined theoretical understanding of the role that psychological distance plays in the context of climate change and opens up further avenues for future research and for interventions.

An improved ASIFT algorithm for indoor panorama image matching

Science.gov (United States)

Fu, Han; Xie, Donghai; Zhong, Ruofei; Wu, Yu; Wu, Qiong

2017-07-01

The generation of 3D models for indoor objects and scenes is an attractive tool for digital city, virtual reality and SLAM purposes. Panoramic images are becoming increasingly more common in such applications due to their advantages to capture the complete environment in one single image with large field of view. The extraction and matching of image feature points are important and difficult steps in three-dimensional reconstruction, and ASIFT is a state-of-the-art algorithm to implement these functions. Compared with the SIFT algorithm, more feature points can be generated and the matching accuracy of ASIFT algorithm is higher, even for the panoramic images with obvious distortions. However, the algorithm is really time-consuming because of complex operations and performs not very well for some indoor scenes under poor light or without rich textures. To solve this problem, this paper proposes an improved ASIFT algorithm for indoor panoramic images: firstly, the panoramic images are projected into multiple normal perspective images. Secondly, the original ASIFT algorithm is simplified from the affine transformation of tilt and rotation with the images to the only tilt affine transformation. Finally, the results are re-projected to the panoramic image space. Experiments in different environments show that this method can not only ensure the precision of feature points extraction and matching, but also greatly reduce the computing time.

Critical Proximity as a Methodological Move in Techno-Anthropology

DEFF Research Database (Denmark)

Birkbak, Andreas; Petersen, Morten Krogh; Elgaard Jensen, Torben

2015-01-01

proximity.’ Critical proximity offers an alternative to critical distance, especially with respect to avoiding premature references to abstract panoramas such as democratization and capitalist exploitation in the quest to conduct ‘critical’ analysis. Critical proximity implies, instead, granting the beings...

A threshold auto-adjustment algorithm of feature points extraction based on grid

Science.gov (United States)

Yao, Zili; Li, Jun; Dong, Gaojie

2018-02-01

When dealing with high-resolution digital images, detection of feature points is usually the very first important step. Valid feature points depend on the threshold. If the threshold is too low, plenty of feature points will be detected, and they may be aggregated in the rich texture regions, which consequently not only affects the speed of feature description, but also aggravates the burden of following processing; if the threshold is set high, the feature points in poor texture area will lack. To solve these problems, this paper proposes a threshold auto-adjustment method of feature extraction based on grid. By dividing the image into numbers of grid, threshold is set in every local grid for extracting the feature points. When the number of feature points does not meet the threshold requirement, the threshold will be adjusted automatically to change the final number of feature points The experimental results show that feature points produced by our method is more uniform and representative, which avoids the aggregation of feature points and greatly reduces the complexity of following work.

Hiding Techniques for Dynamic Encryption Text based on Corner Point

Science.gov (United States)

Abdullatif, Firas A.; Abdullatif, Alaa A.; al-Saffar, Amna

2018-05-01

Hiding technique for dynamic encryption text using encoding table and symmetric encryption method (AES algorithm) is presented in this paper. The encoding table is generated dynamically from MSB of the cover image points that used as the first phase of encryption. The Harris corner point algorithm is applied on cover image to generate the corner points which are used to generate dynamic AES key to second phase of text encryption. The embedded process in the LSB for the image pixels except the Harris corner points for more robust. Experimental results have demonstrated that the proposed scheme have embedding quality, error-free text recovery, and high value in PSNR.

Infiltrating/sealing proximal caries lesions

DEFF Research Database (Denmark)

Martignon, S; Ekstrand, K R; Gomez, J

2012-01-01

This randomized split-mouth controlled clinical trial aimed at assessing the therapeutic effects of infiltration vs. sealing for controlling caries progression on proximal surfaces. Out of 90 adult students/patients assessed at university clinics and agreeing to participate, 39, each with 3...... differences in lesion progression between infiltration and placebo (P = 0.0012) and between sealing and placebo (P = 0.0269). The study showed that infiltration and sealing are significantly better than placebo treatment for controlling caries progression on proximal lesions. No significant difference...

Unconventional Algorithms: Complementarity of Axiomatics and Construction

Directory of Open Access Journals (Sweden)

Gordana Dodig Crnkovic

2012-10-01

Full Text Available In this paper, we analyze axiomatic and constructive issues of unconventional computations from a methodological and philosophical point of view. We explain how the new models of algorithms and unconventional computations change the algorithmic universe, making it open and allowing increased flexibility and expressive power that augment creativity. At the same time, the greater power of new types of algorithms also results in the greater complexity of the algorithmic universe, transforming it into the algorithmic multiverse and demanding new tools for its study. That is why we analyze new powerful tools brought forth by local mathematics, local logics, logical varieties and the axiomatic theory of algorithms, automata and computation. We demonstrate how these new tools allow efficient navigation in the algorithmic multiverse. Further work includes study of natural computation by unconventional algorithms and constructive approaches.

The registration of non-cooperative moving targets laser point cloud in different view point

Science.gov (United States)

Wang, Shuai; Sun, Huayan; Guo, Huichao

2018-01-01

Non-cooperative moving target multi-view cloud registration is the key technology of 3D reconstruction of laser threedimension imaging. The main problem is that the density changes greatly and noise exists under different acquisition conditions of point cloud. In this paper, firstly, the feature descriptor is used to find the most similar point cloud, and then based on the registration algorithm of region segmentation, the geometric structure of the point is extracted by the geometric similarity between point and point, The point cloud is divided into regions based on spectral clustering, feature descriptors are created for each region, searching to find the most similar regions in the most similar point of view cloud, and then aligning the pair of point clouds by aligning their minimum bounding boxes. Repeat the above steps again until registration of all point clouds is completed. Experiments show that this method is insensitive to the density of point clouds and performs well on the noise of laser three-dimension imaging.

Verification of the Solar Dynamics Observatory High Gain Antenna Pointing Algorithm Using Flight Data

Science.gov (United States)

Bourkland, Kristin L.; Liu, Kuo-Chia

2011-01-01

presentehat shows the readback delay does not have a negative impact on gimbal control. The decision was made to consider implementing two of the jitter mitigation techniques on board the spacecraft: stagger stepping and the NSR. Flight data from two sets of handovers, one set without jitter mitigation and the other with mitigation enabled, were examined. The trajectory of the predicted handover was compared with the measured trajectory for the two cases, showing that tracking was not negatively impacted with the addition of the jitter mitigation techniques. Additionally, the individual gimbal steps were examined, and it was confirmed that the stagger stepping and NSRs worked as designed. An Image Quality Test was performed to determine the amount of cumulative jitter from the reaction wheels, HGAs, and instruments during various combinations of typical operations. In this paper, the flight results are examined from a test where the HGAs are following the path of a nominal handover with stagger stepping on and HMI NSRs enabled. In this case, the reaction wheels are moving at low speed and the instruments are taking pictures in their standard sequence. The flight data shows the level of jitter that the instruments see when their shutters are open. The HGA-induced jitter is well within the jitter requirement when the stagger step and NSR mitigation options are enabled. The SDO HGA pointing algorithm was designed to achieve nominal antenna pointing at the ground station, perform slews during handover season, and provide three HGA-induced jitter mitigation options without compromising pointing objectives. During the commissioning phase, flight data sets were collected to verify the HGA pointing algorithm and demonstrate its jitter mitigation capabilities.

IMAGE TO POINT CLOUD METHOD OF 3D-MODELING

Directory of Open Access Journals (Sweden)

A. G. Chibunichev

2012-07-01

Full Text Available This article describes the method of constructing 3D models of objects (buildings, monuments based on digital images and a point cloud obtained by terrestrial laser scanner. The first step is the automated determination of exterior orientation parameters of digital image. We have to find the corresponding points of the image and point cloud to provide this operation. Before the corresponding points searching quasi image of point cloud is generated. After that SIFT algorithm is applied to quasi image and real image. SIFT algorithm allows to find corresponding points. Exterior orientation parameters of image are calculated from corresponding points. The second step is construction of the vector object model. Vectorization is performed by operator of PC in an interactive mode using single image. Spatial coordinates of the model are calculated automatically by cloud points. In addition, there is automatic edge detection with interactive editing available. Edge detection is performed on point cloud and on image with subsequent identification of correct edges. Experimental studies of the method have demonstrated its efficiency in case of building facade modeling.

An Asynchronous IEEE Floating-Point Arithmetic Unit

Directory of Open Access Journals (Sweden)

Joel R. Noche

2007-12-01

Full Text Available An asynchronous floating-point arithmetic unit is designed and tested at the transistor level usingCadence software. It uses CMOS (complementary metal oxide semiconductor and DCVS (differentialcascode voltage switch logic in a 0.35 µm process using a 3.3 V supply voltage, with dual-rail data andsingle-rail control signals using four-phase handshaking.Using 17,085 transistors, the unit handles single-precision (32-bit addition/subtraction, multiplication,division, and remainder using the IEEE 754-1985 Standard for Binary Floating-Point Arithmetic, withrounding and other operations to be handled by separate hardware or software. Division and remainderare done using a restoring subtractive algorithm; multiplication uses an additive algorithm. Exceptionsare noted by flags (and not trap handlers and the output is in single-precision.Previous work on asynchronous floating-point arithmetic units have mostly focused on single operationssuch as division. This is the first work to the authors' knowledge that can perform floating-point addition,multiplication, division, and remainder using a common datapath.

Proximal femoral fractures

DEFF Research Database (Denmark)

Palm, Henrik; Teixidor, Jordi

2015-01-01

searched the homepages of the national heath authorities and national orthopedic societies in West Europe and found 11 national or regional (in case of no national) guidelines including any type of proximal femoral fracture surgery. RESULTS: Pathway consensus is outspread (internal fixation for un...

Self-Similarity Based Corresponding-Point Extraction from Weakly Textured Stereo Pairs

Directory of Open Access Journals (Sweden)

Min Mao

2014-01-01

Full Text Available For the areas of low textured in image pairs, there is nearly no point that can be detected by traditional methods. The information in these areas will not be extracted by classical interest-point detectors. In this paper, a novel weakly textured point detection method is presented. The points with weakly textured characteristic are detected by the symmetry concept. The proposed approach considers the gray variability of the weakly textured local regions. The detection mechanism can be separated into three steps: region-similarity computation, candidate point searching, and refinement of weakly textured point set. The mechanism of radius scale selection and texture strength conception are used in the second step and the third step, respectively. The matching algorithm based on sparse representation (SRM is used for matching the detected points in different images. The results obtained on image sets with different objects show high robustness of the method to background and intraclass variations as well as to different photometric and geometric transformations; the points detected by this method are also the complement of points detected by classical detectors from the literature. And we also verify the efficacy of SRM by comparing with classical algorithms under the occlusion and corruption situations for matching the weakly textured points. Experiments demonstrate the effectiveness of the proposed weakly textured point detection algorithm.

Calorimetry end-point predictions

International Nuclear Information System (INIS)

Fox, M.A.

1981-01-01

This paper describes a portion of the work presently in progress at Rocky Flats in the field of calorimetry. In particular, calorimetry end-point predictions are outlined. The problems associated with end-point predictions and the progress made in overcoming these obstacles are discussed. The two major problems, noise and an accurate description of the heat function, are dealt with to obtain the most accurate results. Data are taken from an actual calorimeter and are processed by means of three different noise reduction techniques. The processed data are then utilized by one to four algorithms, depending on the accuracy desired to determined the end-point

Object Detection and Tracking using Modified Diamond Search Block Matching Motion Estimation Algorithm

Directory of Open Access Journals (Sweden)

Apurva Samdurkar

2018-06-01

Full Text Available Object tracking is one of the main fields within computer vision. Amongst various methods/ approaches for object detection and tracking, the background subtraction approach makes the detection of object easier. To the detected object, apply the proposed block matching algorithm for generating the motion vectors. The existing diamond search (DS and cross diamond search algorithms (CDS are studied and experiments are carried out on various standard video data sets and user defined data sets. Based on the study and analysis of these two existing algorithms a modified diamond search pattern (MDS algorithm is proposed using small diamond shape search pattern in initial step and large diamond shape (LDS in further steps for motion estimation. The initial search pattern consists of five points in small diamond shape pattern and gradually grows into a large diamond shape pattern, based on the point with minimum cost function. The algorithm ends with the small shape pattern at last. The proposed MDS algorithm finds the smaller motion vectors and fewer searching points than the existing DS and CDS algorithms. Further, object detection is carried out by using background subtraction approach and finally, MDS motion estimation algorithm is used for tracking the object in color video sequences. The experiments are carried out by using different video data sets containing a single object. The results are evaluated and compared by using the evaluation parameters like average searching points per frame and average computational time per frame. The experimental results show that the MDS performs better than DS and CDS on average search point and average computation time.

An efficient and robust algorithm for parallel groupwise registration of bone surfaces

NARCIS (Netherlands)

van de Giessen, Martijn; Vos, Frans M.; Grimbergen, Cornelis A.; van Vliet, Lucas J.; Streekstra, Geert J.

2012-01-01

In this paper a novel groupwise registration algorithm is proposed for the unbiased registration of a large number of densely sampled point clouds. The method fits an evolving mean shape to each of the example point clouds thereby minimizing the total deformation. The registration algorithm

Proximity correction of high-dosed frame with PROXECCO

Science.gov (United States)

Eisenmann, Hans; Waas, Thomas; Hartmann, Hans

1994-05-01

Usefulness of electron beam lithography is strongly related to the efficiency and quality of methods used for proximity correction. This paper addresses the above issue by proposing an extension to the new proximity correction program PROXECCO. The combination of a framing step with PROXECCO produces a pattern with a very high edge accuracy and still allows usage of the fast correction procedure. Making a frame with a higher dose imitates a fine resolution correction where the coarse part is disregarded. So after handling the high resolution effect by means of framing, an additional coarse correction is still needed. Higher doses have a higher contribution to the proximity effect. This additional proximity effect is taken into account with the help of the multi-dose input of PROXECCO. The dose of the frame is variable, depending on the deposited energy coming from backscattering of the proximity. Simulation proves the very high edge accuracy of the applied method.

Algorithm to find high density EEG scalp coordinates and analysis of their correspondence to structural and functional regions of the brain.

Science.gov (United States)

Giacometti, Paolo; Perdue, Katherine L; Diamond, Solomon G

2014-05-30

Interpretation and analysis of electroencephalography (EEG) measurements relies on the correspondence of electrode scalp coordinates to structural and functional regions of the brain. An algorithm is introduced for automatic calculation of the International 10-20, 10-10, and 10-5 scalp coordinates of EEG electrodes on a boundary element mesh of a human head. The EEG electrode positions are then used to generate parcellation regions of the cerebral cortex based on proximity to the EEG electrodes. The scalp electrode calculation method presented in this study effectively and efficiently identifies EEG locations without prior digitization of coordinates. The average of electrode proximity parcellations of the cortex were tabulated with respect to structural and functional regions of the brain in a population of 20 adult subjects. Parcellations based on electrode proximity and EEG sensitivity were compared. The parcellation regions based on sensitivity and proximity were found to have 44.0 ± 11.3% agreement when demarcated by the International 10-20, 32.4 ± 12.6% by the 10-10, and 24.7 ± 16.3% by the 10-5 electrode positioning system. The EEG positioning algorithm is a fast and easy method of locating EEG scalp coordinates without the need for digitized electrode positions. The parcellation method presented summarizes the EEG scalp locations with respect to brain regions without computation of a full EEG forward model solution. The reference table of electrode proximity versus cortical regions may be used by experimenters to select electrodes that correspond to anatomical and functional regions of interest. Copyright © 2014 Elsevier B.V. All rights reserved.

Novel Adaptive Bacteria Foraging Algorithms for Global Optimization

Directory of Open Access Journals (Sweden)

Ahmad N. K. Nasir

2014-01-01

Full Text Available This paper presents improved versions of bacterial foraging algorithm (BFA. The chemotaxis feature of bacteria through random motion is an effective strategy for exploring the optimum point in a search area. The selection of small step size value in the bacteria motion leads to high accuracy in the solution but it offers slow convergence. On the contrary, defining a large step size in the motion provides faster convergence but the bacteria will be unable to locate the optimum point hence reducing the fitness accuracy. In order to overcome such problems, novel linear and nonlinear mathematical relationships based on the index of iteration, index of bacteria, and fitness cost are adopted which can dynamically vary the step size of bacteria movement. The proposed algorithms are tested with several unimodal and multimodal benchmark functions in comparison with the original BFA. Moreover, the application of the proposed algorithms in modelling of a twin rotor system is presented. The results show that the proposed algorithms outperform the predecessor algorithm in all test functions and acquire better model for the twin rotor system.

Dual pathology proximal median nerve compression of the forearm.

LENUS (Irish Health Repository)

Murphy, Siun M

2013-12-01

We report an unusual case of synchronous pathology in the forearm- the coexistence of a large lipoma of the median nerve together with an osteochondroma of the proximal ulna, giving rise to a dual proximal median nerve compression. Proximal median nerve compression neuropathies in the forearm are uncommon compared to the prevalence of distal compression neuropathies (eg Carpal Tunnel Syndrome). Both neural fibrolipomas (Refs. 1,2) and osteochondromas of the proximal ulna (Ref. 3) in isolation are rare but well documented. Unlike that of a distal compression, a proximal compression of the median nerve will often have a definite cause. Neural fibrolipoma, also called fibrolipomatous hamartoma are rare, slow-growing, benign tumours of peripheral nerves, most often occurring in the median nerve of younger patients. To our knowledge, this is the first report of such dual pathology in the same forearm, giving rise to a severe proximal compression of the median nerve. In this case, the nerve was being pushed anteriorly by the osteochondroma, and was being compressed from within by the intraneural lipoma. This unusual case highlights the advantage of preoperative imaging as part of the workup of proximal median nerve compression.

Giant proximity effect and critical opalescence in EuS

Science.gov (United States)

Charlton, Timothy; Ramos, Silvia; Quintanilla, Jorge; Suter, Andreas; Moodera, Jagadeesh

2015-03-01

The proximity effect is a type of wetting phenomenon where an ordered state, usually magnetism or superconductivity, ``leaks'' from one material into an adjacent one over some finite distance. For superconductors, the characteristic range is of the order of the coherence length, usually hundreds of nm. Nevertheless much longer, ``giant'' proximity effects have been observed in cuprate perovskite junctions. Such giant proximity effects can be understood by taking into account the divergence of the pairing susceptibility in the non-superconducting material when it is itself close to a superconducting instability: a superconducting version of critical opalescence. Since critical opalescence occurs in all second order phase transitions, giant proximity effects are expected to be general, therefor there must be a giant ferromagnetic proximity effect. Compared to its superconducting counterpart, the giant ferromagnetic proximity effect has the advantage that the order parameter (magnetization) can be observed directly. We have fabricated Co/EuS thin films and measured the magnetization profiles as a function of temperature using the complementary techniques of low energy muon relaxation and polarized neutron reflectivity. Details of the proximity effect near TCEuS will be presented.

Strong Proximities on Smooth Manifolds and Vorono\\" i Diagrams

OpenAIRE

Peters, J. F.; Guadagni, C.

2015-01-01

This article introduces strongly near smooth manifolds. The main results are (i) second countability of the strongly hit and far-miss topology on a family $\\mathcal{B}$ of subsets on the Lodato proximity space of regular open sets to which singletons are added, (ii) manifold strong proximity, (iii) strong proximity of charts in manifold atlases implies that the charts have nonempty intersection. The application of these results is given in terms of the nearness of atlases and charts of proxim...

Shortest path problem on a grid network with unordered intermediate points

Science.gov (United States)

Saw, Veekeong; Rahman, Amirah; Eng Ong, Wen

2017-10-01

We consider a shortest path problem with single cost factor on a grid network with unordered intermediate points. A two stage heuristic algorithm is proposed to find a feasible solution path within a reasonable amount of time. To evaluate the performance of the proposed algorithm, computational experiments are performed on grid maps of varying size and number of intermediate points. Preliminary results for the problem are reported. Numerical comparisons against brute forcing show that the proposed algorithm consistently yields solutions that are within 10% of the optimal solution and uses significantly less computation time.

75 FR 5009 - Proximity Detection Systems for Underground Mines

Science.gov (United States)

2010-02-01

... Proximity Detection Systems for Underground Mines AGENCY: Mine Safety and Health Administration, Labor... information regarding whether the use of proximity detection systems would reduce the risk of accidents where... . Information on MSHA-approved proximity detection systems is available on the Internet at http://www.msha.gov...

Comparative Study of Evolutionary Multi-objective Optimization Algorithms for a Non-linear Greenhouse Climate Control Problem

DEFF Research Database (Denmark)

Ghoreishi, Newsha; Sørensen, Jan Corfixen; Jørgensen, Bo Nørregaard

2015-01-01

Non-trivial real world decision-making processes usually involve multiple parties having potentially conflicting interests over a set of issues. State-of-the-art multi-objective evolutionary algorithms (MOEA) are well known to solve this class of complex real-world problems. In this paper, we...... compare the performance of state-of-the-art multi-objective evolutionary algorithms to solve a non-linear multi-objective multi-issue optimisation problem found in Greenhouse climate control. The chosen algorithms in the study includes NSGAII, eNSGAII, eMOEA, PAES, PESAII and SPEAII. The performance...... of all aforementioned algorithms is assessed and compared using performance indicators to evaluate proximity, diversity and consistency. Our insights to this comparative study enhanced our understanding of MOEAs performance in order to solve a non-linear complex climate control problem. The empirical...

Bimalleolar ankle fracture with proximal fibular fracture

NARCIS (Netherlands)

Colenbrander, R. J.; Struijs, P. A. A.; Ultee, J. M.

2005-01-01

A 56-year-old female patient suffered a bimalleolar ankle fracture with an additional proximal fibular fracture. This is an unusual fracture type, seldom reported in literature. It was operatively treated by open reduction and internal fixation of the lateral malleolar fracture. The proximal fibular

[Partial replantation following proximal limb injury].

Science.gov (United States)

Dubert, T; Malikov, S A; Dinh, A; Kupatadze, D D; Oberlin, C; Alnot, J Y; Nabokov, B B

2000-11-01

Proximal replantation is a technically feasible but life-threatening procedure. Indications must be restricted to patients in good condition with a good functional prognosis. The goal of replantation must be focused not only on reimplanting the amputated limb but also on achieving a good functional outcome. For the lower limb, simple terminalization remains the best choice in many cases. When a proximal amputation is not suitable for replantation, the main aim of the surgical procedure must be to reconstruct a stump long enough to permit fitting a prosthesis preserving the function of the adjacent joint. If the proximal stump beyond the last joint is very short, it may be possible to restore some length by partial replantation of spared tissues from the amputated part. We present here the results we obtained following this policy. This series included 16 cases of partial replantations, 14 involving the lower limb and 2 the upper limb. All were osteocutaneous microsurgical transfers. For the lower limb, all transfers recovered protective sensitivity following tibial nerve repair. The functional calcaeoplantar unit was used in 13 cases. The transfer of this specialized weight bearing tissue provided a stable distal surface making higher support unnecessary. In one case, we raised a 13-cm vascularized tibial segment covered with foot skin for additional length. For the upper limb, the osteocutaneous transfer, based on the radial artery, was not reinnervated, but this lack of sensitivity did not impair prosthesis fitting. One vascular failure was finally amputated. This was the only unsuccessful result. For all other patients, the surgical procedure facilitated prosthesis fitting and preserved the proximal joint function despite an initially very proximal amputation. The advantages of partial replantation are obvious compared with simple terminalization or secondary reconstruction. There is no secondary donor site and, because there is no major muscle mass in the

A MARKED POINT PROCESS MODEL FOR VEHICLE DETECTION IN AERIAL LIDAR POINT CLOUDS

Directory of Open Access Journals (Sweden)

A. Börcs

2012-07-01

Full Text Available In this paper we present an automated method for vehicle detection in LiDAR point clouds of crowded urban areas collected from an aerial platform. We assume that the input cloud is unordered, but it contains additional intensity and return number information which are jointly exploited by the proposed solution. Firstly, the 3-D point set is segmented into ground, vehicle, building roof, vegetation and clutter classes. Then the points with the corresponding class labels and intensity values are projected to the ground plane, where the optimal vehicle configuration is described by a Marked Point Process (MPP model of 2-D rectangles. Finally, the Multiple Birth and Death algorithm is utilized to find the configuration with the highest confidence.

Interest point detection for hyperspectral imagery

Science.gov (United States)

Dorado-Muñoz, Leidy P.; Vélez-Reyes, Miguel; Roysam, Badrinath; Mukherjee, Amit

2009-05-01

This paper presents an algorithm for automated extraction of interest points (IPs)in multispectral and hyperspectral images. Interest points are features of the image that capture information from its neighbours and they are distinctive and stable under transformations such as translation and rotation. Interest-point operators for monochromatic images were proposed more than a decade ago and have since been studied extensively. IPs have been applied to diverse problems in computer vision, including image matching, recognition, registration, 3D reconstruction, change detection, and content-based image retrieval. Interest points are helpful in data reduction, and reduce the computational burden of various algorithms (like registration, object detection, 3D reconstruction etc) by replacing an exhaustive search over the entire image domain by a probe into a concise set of highly informative points. An interest operator seeks out points in an image that are structurally distinct, invariant to imaging conditions, stable under geometric transformation, and interpretable which are good candidates for interest points. Our approach extends ideas from Lowe's keypoint operator that uses local extrema of Difference of Gaussian (DoG) operator at multiple scales to detect interest point in gray level images. The proposed approach extends Lowe's method by direct conversion of scalar operations such as scale-space generation, and extreme point detection into operations that take the vector nature of the image into consideration. Experimental results with RGB and hyperspectral images which demonstrate the potential of the method for this application and the potential improvements of a fully vectorial approach over band-by-band approaches described in the literature.

Proximal Pole Scaphoid Nonunion Reconstruction With 1,2 Intercompartmental Supraretinacular Artery Vascularized Graft and Compression Screw Fixation.

Science.gov (United States)

Morris, Mark S; Zhu, Andy F; Ozer, Kagan; Lawton, Jeffrey N

2018-02-06

To review the incidence of union of patients with proximal pole scaphoid fracture nonunions treated using a 1,2 intercompartmental supraretinacular artery (1,2 ICSRA) vascularized graft and a small compression screw. This is a retrospective case series of 12 patients. Calculations of the size of the proximal pole fragment relative to the total scaphoid were performed using posteroanterior view scaphoid radiographs with the wrist in ulnar deviation and flat on the cassette. Analyses were repeated 3 times per subject, and the average ratio of proximal pole fragment relative to the entire scaphoid was calculated. We reviewed medical records, radiographs, and computed tomography (CT) scans of these 12 patients. The CT scans that were performed after an average of 12 weeks were ultimately used to confirm union of the scaphoid fractures. One patient was unable to have a CT so was excluded from the final calculation. All 11 (100%) scaphoid fractures that were assessed by CT were found to be healed at the 12-week assessment point. The mean proximal pole fragment size was 18% (range, 7%-27%) of the entire scaphoid. The 1,2 ICSRA vascularized graft and compression screw was an effective treatment for patients with proximal pole scaphoid fractures. Therapeutic IV. Copyright © 2018 American Society for Surgery of the Hand. Published by Elsevier Inc. All rights reserved.

Algorithm for Extracting Digital Terrain Models under Forest Canopy from Airborne LiDAR Data

Directory of Open Access Journals (Sweden)

Almasi S. Maguya

2014-07-01

Full Text Available Extracting digital elevationmodels (DTMs from LiDAR data under forest canopy is a challenging task. This is because the forest canopy tends to block a portion of the LiDAR pulses from reaching the ground, hence introducing gaps in the data. This paper presents an algorithm for DTM extraction from LiDAR data under forest canopy. The algorithm copes with the challenge of low data density by generating a series of coarse DTMs by using the few ground points available and using trend surfaces to interpolate missing elevation values in the vicinity of the available points. This process generates a cloud of ground points from which the final DTM is generated. The algorithm has been compared to two other algorithms proposed in the literature in three different test sites with varying degrees of difficulty. Results show that the algorithm presented in this paper is more tolerant to low data density compared to the other two algorithms. The results further show that with decreasing point density, the differences between the three algorithms dramatically increased from about 0.5m to over 10m.

KNOWLEDGE-BASED OBJECT DETECTION IN LASER SCANNING POINT CLOUDS

Directory of Open Access Journals (Sweden)

F. Boochs

2012-07-01

Full Text Available Object identification and object processing in 3D point clouds have always posed challenges in terms of effectiveness and efficiency. In practice, this process is highly dependent on human interpretation of the scene represented by the point cloud data, as well as the set of modeling tools available for use. Such modeling algorithms are data-driven and concentrate on specific features of the objects, being accessible to numerical models. We present an approach that brings the human expert knowledge about the scene, the objects inside, and their representation by the data and the behavior of algorithms to the machine. This “understanding” enables the machine to assist human interpretation of the scene inside the point cloud. Furthermore, it allows the machine to understand possibilities and limitations of algorithms and to take this into account within the processing chain. This not only assists the researchers in defining optimal processing steps, but also provides suggestions when certain changes or new details emerge from the point cloud. Our approach benefits from the advancement in knowledge technologies within the Semantic Web framework. This advancement has provided a strong base for applications based on knowledge management. In the article we will present and describe the knowledge technologies used for our approach such as Web Ontology Language (OWL, used for formulating the knowledge base and the Semantic Web Rule Language (SWRL with 3D processing and topologic built-ins, aiming to combine geometrical analysis of 3D point clouds, and specialists’ knowledge of the scene and algorithmic processing.

Knowledge-Based Object Detection in Laser Scanning Point Clouds

Science.gov (United States)

Boochs, F.; Karmacharya, A.; Marbs, A.

2012-07-01

Object identification and object processing in 3D point clouds have always posed challenges in terms of effectiveness and efficiency. In practice, this process is highly dependent on human interpretation of the scene represented by the point cloud data, as well as the set of modeling tools available for use. Such modeling algorithms are data-driven and concentrate on specific features of the objects, being accessible to numerical models. We present an approach that brings the human expert knowledge about the scene, the objects inside, and their representation by the data and the behavior of algorithms to the machine. This "understanding" enables the machine to assist human interpretation of the scene inside the point cloud. Furthermore, it allows the machine to understand possibilities and limitations of algorithms and to take this into account within the processing chain. This not only assists the researchers in defining optimal processing steps, but also provides suggestions when certain changes or new details emerge from the point cloud. Our approach benefits from the advancement in knowledge technologies within the Semantic Web framework. This advancement has provided a strong base for applications based on knowledge management. In the article we will present and describe the knowledge technologies used for our approach such as Web Ontology Language (OWL), used for formulating the knowledge base and the Semantic Web Rule Language (SWRL) with 3D processing and topologic built-ins, aiming to combine geometrical analysis of 3D point clouds, and specialists' knowledge of the scene and algorithmic processing.

A fingerprint classification algorithm based on combination of local and global information

Science.gov (United States)

Liu, Chongjin; Fu, Xiang; Bian, Junjie; Feng, Jufu

2011-12-01

Fingerprint recognition is one of the most important technologies in biometric identification and has been wildly applied in commercial and forensic areas. Fingerprint classification, as the fundamental procedure in fingerprint recognition, can sharply decrease the quantity for fingerprint matching and improve the efficiency of fingerprint recognition. Most fingerprint classification algorithms are based on the number and position of singular points. Because the singular points detecting method only considers the local information commonly, the classification algorithms are sensitive to noise. In this paper, we propose a novel fingerprint classification algorithm combining the local and global information of fingerprint. Firstly we use local information to detect singular points and measure their quality considering orientation structure and image texture in adjacent areas. Furthermore the global orientation model is adopted to measure the reliability of singular points group. Finally the local quality and global reliability is weighted to classify fingerprint. Experiments demonstrate the accuracy and effectivity of our algorithm especially for the poor quality fingerprint images.

Research on the target coverage algorithms for 3D curved surface

International Nuclear Information System (INIS)

Sun, Shunyuan; Sun, Li; Chen, Shu

2016-01-01

To solve the target covering problems in three-dimensional space, putting forward a deployment strategies of the target points innovatively, and referencing to the differential evolution (DE) algorithm to optimize the location coordinates of the sensor nodes to realize coverage of all the target points in 3-D surface with minimal sensor nodes. Firstly, building the three-dimensional perception model of sensor nodes, and putting forward to the blind area existing in the process of the sensor nodes sensing the target points in 3-D surface innovatively, then proving the feasibility of solving the target coverage problems in 3-D surface with DE algorithm theoretically, and reflecting the fault tolerance of the algorithm.

A Direct Search Algorithm for Global Optimization

Directory of Open Access Journals (Sweden)

Enrique Baeyens

2016-06-01

Full Text Available A direct search algorithm is proposed for minimizing an arbitrary real valued function. The algorithm uses a new function transformation and three simplex-based operations. The function transformation provides global exploration features, while the simplex-based operations guarantees the termination of the algorithm and provides global convergence to a stationary point if the cost function is differentiable and its gradient is Lipschitz continuous. The algorithm’s performance has been extensively tested using benchmark functions and compared to some well-known global optimization algorithms. The results of the computational study show that the algorithm combines both simplicity and efficiency and is competitive with the heuristics-based strategies presently used for global optimization.

Human body motion tracking based on quantum-inspired immune cloning algorithm

Science.gov (United States)

Han, Hong; Yue, Lichuan; Jiao, Licheng; Wu, Xing

2009-10-01

In a static monocular camera system, to gain a perfect 3D human body posture is a great challenge for Computer Vision technology now. This paper presented human postures recognition from video sequences using the Quantum-Inspired Immune Cloning Algorithm (QICA). The algorithm included three parts. Firstly, prior knowledge of human beings was used, the key joint points of human could be detected automatically from the human contours and skeletons which could be thinning from the contours; And due to the complexity of human movement, a forecasting mechanism of occlusion joint points was addressed to get optimum 2D key joint points of human body; And then pose estimation recovered by optimizing between the 2D projection of 3D human key joint points and 2D detection key joint points using QICA, which recovered the movement of human body perfectly, because this algorithm could acquire not only the global optimal solution, but the local optimal solution.

Proximity effect in superconductor/ferromagnet hetero-structures as a function of interface properties

Science.gov (United States)

Sarmiento, Julio; Patino, Edgar J.

2014-03-01

Superconductor/ferromagnet heterostructures are currently a subject of strong research due to novel phenomena resulting from the proximity effect. Among the most investigated ones are the oscillations of the critical temperature as function of the ferromagnet thickness. The oscillatory behavior of Tc is theoretically explained as to be result of the generation of the FFLO (Fulde-Ferrel-Larkin-Ovchinnikov) state of Cooper pairs under the presence of the exchange field of the ferromagnet. With the advancement of experimental techniques for S/F bilayers growth new questions regarding the effect of the interface transparency can to be addressed. For instance the influence of the interface roughness on the proximity effect. For studying this phenomenon Nb/Co and Nb/Cu/Co samples were sputtered on SiO2 substrates with different roughness. Characterization of these samples show a significant variation of Tc with the interface roughness. This results point towards a possible relationship between transparency and roughness of the interface. Proyecto Semilla Facultad de Ciencias Universidad de los Andes.

Agent-based Algorithm for Spatial Distribution of Objects

KAUST Repository

Collier, Nathan

2012-06-02

In this paper we present an agent-based algorithm for the spatial distribution of objects. The algorithm is a generalization of the bubble mesh algorithm, initially created for the point insertion stage of the meshing process of the finite element method. The bubble mesh algorithm treats objects in space as bubbles, which repel and attract each other. The dynamics of each bubble are approximated by solving a series of ordinary differential equations. We present numerical results for a meshing application as well as a graph visualization application.

Proximity effect at Millikelvin temperatures

International Nuclear Information System (INIS)

Mota, A.C.

1986-01-01

Proximity effects have been studied extensively for the past 25 years. Typically, they are in films several thousand angstroms thick at temperatures not so far below T/sub CNS/, the transition temperature of the NS system. Interesting is, however, the proximity effect at temperatures much lower than T/sub CNS/. In this case, the Cooper-pair amplitudes are not small and very long pair penetration lengths into the normal metal can be expected. Thus, we have observed pair penetration lengths. For these investigations very suitable specimens are commercial wires of one filament of NbTi or Nb embedded in a copper matrix. The reasons are the high transmission coefficient at the interface between the copper and the superconductor and the fact that the copper in these commercial wires is rather clean with electron free paths between 5 to 10 μm long. In this paper, the magnetic properties of thick proximity systems in the range of temperatures between T/sub CNS/ and 5 x 10/sup -4/ T/sub CNS/ in both low and high magnetic fields are discussed

Adaptive Ridge Point Refinement for Seeds Detection in X-Ray Coronary Angiogram

Directory of Open Access Journals (Sweden)

Ruoxiu Xiao

2015-01-01

Full Text Available Seed point is prerequired condition for tracking based method for extracting centerline or vascular structures from the angiogram. In this paper, a novel seed point detection method for coronary artery segmentation is proposed. Vessels on the image are first enhanced according to the distribution of Hessian eigenvalue in multiscale space; consequently, centerlines of tubular vessels are also enhanced. Ridge point is extracted as candidate seed point, which is then refined according to its mathematical definition. The theoretical feasibility of this method is also proven. Finally, all the detected ridge points are checked using a self-adaptive threshold to improve the robustness of results. Clinical angiograms are used to evaluate the performance of the proposed algorithm, and the results show that the proposed algorithm can detect a large set of true seed points located on most branches of vessels. Compared with traditional seed point detection algorithms, the proposed method can detect a larger number of seed points with higher precision. Considering that the proposed method can achieve accurate seed detection without any human interaction, it can be utilized for several clinical applications, such as vessel segmentation, centerline extraction, and topological identification.

New approach for measuring 3D space by using Advanced SURF Algorithm

Energy Technology Data Exchange (ETDEWEB)

Youm, Minkyo; Min, Byungil; Suh, Kyungsuk [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of); Lee, Backgeun [Sungkyunkwan Univ., Suwon (Korea, Republic of)

2013-05-15

The nuclear disasters compared to natural disaster create a more extreme condition for analyzing and evaluating. In this paper, measuring 3D space and modeling was studied by simple pictures in case of small sand dune. The suggested method can be used for the acquisition of spatial information by robot at the disaster area. As a result, these data are helpful for identify the damaged part, degree of damage and determination of recovery sequences. In this study we are improving computer vision algorithm for 3-D geo spatial information measurement. And confirm by test. First, we can get noticeable improvement of 3-D geo spatial information result by SURF algorithm and photogrammetry surveying. Second, we can confirm not only decrease algorithm running time, but also increase matching points through epi polar line filtering. From the study, we are extracting 3-D model by open source algorithm and delete miss match point by filtering method. However on characteristic of SURF algorithm, it can't find match point if structure don't have strong feature. So we will need more study about find feature point if structure don't have strong feature.

Algorithms for reconstructing images for industrial applications

International Nuclear Information System (INIS)

Lopes, R.T.; Crispim, V.R.

1986-01-01

Several algorithms for reconstructing objects from their projections are being studied in our Laboratory, for industrial applications. Such algorithms are useful locating the position and shape of different composition of materials in the object. A Comparative study of two algorithms is made. The two investigated algorithsm are: The MART (Multiplicative - Algebraic Reconstruction Technique) and the Convolution Method. The comparison are carried out from the point view of the quality of the image reconstructed, number of views and cost. (Author) [pt

Dual pathology proximal median nerve compression of the forearm.

Science.gov (United States)

Murphy, Siun M; Browne, Katherine; Tuite, David J; O'Shaughnessy, Michael

2013-12-01

We report an unusual case of synchronous pathology in the forearm- the coexistence of a large lipoma of the median nerve together with an osteochondroma of the proximal ulna, giving rise to a dual proximal median nerve compression. Proximal median nerve compression neuropathies in the forearm are uncommon compared to the prevalence of distal compression neuropathies (eg Carpal Tunnel Syndrome). Both neural fibrolipomas (Refs. 1,2) and osteochondromas of the proximal ulna (Ref. 3) in isolation are rare but well documented. Unlike that of a distal compression, a proximal compression of the median nerve will often have a definite cause. Neural fibrolipoma, also called fibrolipomatous hamartoma are rare, slow-growing, benign tumours of peripheral nerves, most often occurring in the median nerve of younger patients. To our knowledge, this is the first report of such dual pathology in the same forearm, giving rise to a severe proximal compression of the median nerve. In this case, the nerve was being pushed anteriorly by the osteochondroma, and was being compressed from within by the intraneural lipoma. This unusual case highlights the advantage of preoperative imaging as part of the workup of proximal median nerve compression. Copyright © 2013 British Association of Plastic, Reconstructive and Aesthetic Surgeons. Published by Elsevier Ltd. All rights reserved.

An interior-point method for the Cartesian P*(k-linear complementarity problem over symmetric cones

Directory of Open Access Journals (Sweden)

B Kheirfam

2014-06-01

Full Text Available A novel primal-dual path-following interior-point algorithm for the Cartesian P*(k-linear complementarity problem over symmetric cones is presented. The algorithm is based on a reformulation of the central path for finding the search directions. For a full Nesterov-Todd step feasible interior-point algorithm based on the new search directions, the complexity bound of the algorithm with small-update approach is the best-available bound.

Improved Power Decoding of One-Point Hermitian Codes

DEFF Research Database (Denmark)

Puchinger, Sven; Bouw, Irene; Rosenkilde, Johan Sebastian Heesemann

2017-01-01

We propose a new partial decoding algorithm for one-point Hermitian codes that can decode up to the same number of errors as the Guruswami–Sudan decoder. Simulations suggest that it has a similar failure probability as the latter one. The algorithm is based on a recent generalization of the power...... decoding algorithm for Reed–Solomon codes and does not require an expensive root-finding step. In addition, it promises improvements for decoding interleaved Hermitian codes....

Localization method of picking point of apple target based on smoothing contour symmetry axis algorithm%基于平滑轮廓对称轴法的苹果目标采摘点定位方法

Institute of Scientific and Technical Information of China (English)

王丹丹; 徐越; 宋怀波; 何东健

2015-01-01

果实采摘点的精确定位是采摘机器人必须解决的关键问题。鉴于苹果目标具有良好对称性的特点，利用转动惯量所具有的平移、旋转不变性及其在对称轴方向取得极值的特性，提出了一种基于轮廓对称轴法的苹果目标采摘点定位方法。为了解决分割后苹果目标边缘不够平滑而导致定位精度偏低的问题，提出了一种苹果目标轮廓平滑方法。为了验证算法的有效性，对随机选取的20幅无遮挡的单果苹果图像分别利用轮廓平滑和未进行轮廓平滑的算法进行试验，试验结果表明，未进行轮廓平滑算法的平均定位误差为20.678°，而轮廓平滑后算法平均定位误差为4.542°，比未进行轮廓平滑算法平均定位误差降低了78.035%，未进行轮廓平滑算法的平均运行时间为10.2 ms，而轮廓平滑后算法的平均运行时间为7.5 ms，比未进行轮廓平滑算法平均运行时间降低了25.839%，表明平滑轮廓算法可以提高定位精度和运算效率。利用平滑轮廓对称轴算法可以较好地找到苹果目标的对称轴并实现采摘点定位，表明将该方法应用于苹果目标的对称轴提取及采摘点定位是可行的。%The localization of picking points of fruits is one of the key problems for picking robots, and it is the first step of implementation of the picking task for picking robots. In view of a good symmetry of apples, and characteristics of shift, rotation invariance, and reaching the extreme values in symmetry axis direction which moment of inertia possesses, a new method based on a contour symmetry axis was proposed to locate the picking point of apples. In order to solve the problem of low localization accuracy which results from the rough edge of apples after segmentation, a method of smoothing contour algorithm was presented. The steps of the algorithm were as follow, first, the image was transformed from RGB color space into

TH-E-BRE-04: An Online Replanning Algorithm for VMAT

Energy Technology Data Exchange (ETDEWEB)

Ahunbay, E; Li, X [Medical College of Wisconsin, Milwaukee, WI (United States); Moreau, M [Elekta, Inc, Verona, WI (Italy)

2014-06-15

Purpose: To develop a fast replanning algorithm based on segment aperture morphing (SAM) for online replanning of volumetric modulated arc therapy (VMAT) with flattening filtered (FF) and flattening filter free (FFF) beams. Methods: A software tool was developed to interface with a VMAT planning system ((Monaco, Elekta), enabling the output of detailed beam/machine parameters of original VMAT plans generated based on planning CTs for FF or FFF beams. A SAM algorithm, previously developed for fixed-beam IMRT, was modified to allow the algorithm to correct for interfractional variations (e.g., setup error, organ motion and deformation) by morphing apertures based on the geometric relationship between the beam's eye view of the anatomy from the planning CT and that from the daily CT for each control point. The algorithm was tested using daily CTs acquired using an in-room CT during daily IGRT for representative prostate cancer cases along with their planning CTs. The algorithm allows for restricted MLC leaf travel distance between control points of the VMAT delivery to prevent SAM from increasing leaf travel, and therefore treatment delivery time. Results: The VMAT plans adapted to the daily CT by SAM were found to improve the dosimetry relative to the IGRT repositioning plans for both FF and FFF beams. For the adaptive plans, the changes in leaf travel distance between control points were < 1cm for 80% of the control points with no restriction. When restricted to the original plans' maximum travel distance, the dosimetric effect was minimal. The adaptive plans were delivered successfully with similar delivery times as the original plans. The execution of the SAM algorithm was < 10 seconds. Conclusion: The SAM algorithm can quickly generate deliverable online-adaptive VMAT plans based on the anatomy of the day for both FF and FFF beams.

TH-E-BRE-04: An Online Replanning Algorithm for VMAT

International Nuclear Information System (INIS)

Ahunbay, E; Li, X; Moreau, M

2014-01-01

Purpose: To develop a fast replanning algorithm based on segment aperture morphing (SAM) for online replanning of volumetric modulated arc therapy (VMAT) with flattening filtered (FF) and flattening filter free (FFF) beams. Methods: A software tool was developed to interface with a VMAT planning system ((Monaco, Elekta), enabling the output of detailed beam/machine parameters of original VMAT plans generated based on planning CTs for FF or FFF beams. A SAM algorithm, previously developed for fixed-beam IMRT, was modified to allow the algorithm to correct for interfractional variations (e.g., setup error, organ motion and deformation) by morphing apertures based on the geometric relationship between the beam's eye view of the anatomy from the planning CT and that from the daily CT for each control point. The algorithm was tested using daily CTs acquired using an in-room CT during daily IGRT for representative prostate cancer cases along with their planning CTs. The algorithm allows for restricted MLC leaf travel distance between control points of the VMAT delivery to prevent SAM from increasing leaf travel, and therefore treatment delivery time. Results: The VMAT plans adapted to the daily CT by SAM were found to improve the dosimetry relative to the IGRT repositioning plans for both FF and FFF beams. For the adaptive plans, the changes in leaf travel distance between control points were < 1cm for 80% of the control points with no restriction. When restricted to the original plans' maximum travel distance, the dosimetric effect was minimal. The adaptive plans were delivered successfully with similar delivery times as the original plans. The execution of the SAM algorithm was < 10 seconds. Conclusion: The SAM algorithm can quickly generate deliverable online-adaptive VMAT plans based on the anatomy of the day for both FF and FFF beams

Promoter proximal polyadenylation sites reduce transcription activity

DEFF Research Database (Denmark)

Andersen, Pia Kjølhede; Lykke-Andersen, Søren; Jensen, Torben Heick

2012-01-01

Gene expression relies on the functional communication between mRNA processing and transcription. We previously described the negative impact of a point-mutated splice donor (SD) site on transcription. Here we demonstrate that this mutation activates an upstream cryptic polyadenylation (CpA) site......, which in turn causes reduced transcription. Functional depletion of U1 snRNP in the context of the wild-type SD triggers the same CpA event accompanied by decreased RNA levels. Thus, in accordance with recent findings, U1 snRNP can shield premature pA sites. The negative impact of unshielded pA sites...... on transcription requires promoter proximity, as demonstrated using artificial constructs and supported by a genome-wide data set. Importantly, transcription down-regulation can be recapitulated in a gene context devoid of splice sites by placing a functional bona fide pA site/transcription terminator within ∼500...

Knee point search using cascading top-k sorting with minimized time complexity.

Science.gov (United States)

Wang, Zheng; Tseng, Shian-Shyong

2013-01-01

Anomaly detection systems and many other applications are frequently confronted with the problem of finding the largest knee point in the sorted curve for a set of unsorted points. This paper proposes an efficient knee point search algorithm with minimized time complexity using the cascading top-k sorting when a priori probability distribution of the knee point is known. First, a top-k sort algorithm is proposed based on a quicksort variation. We divide the knee point search problem into multiple steps. And in each step an optimization problem of the selection number k is solved, where the objective function is defined as the expected time cost. Because the expected time cost in one step is dependent on that of the afterwards steps, we simplify the optimization problem by minimizing the maximum expected time cost. The posterior probability of the largest knee point distribution and the other parameters are updated before solving the optimization problem in each step. An example of source detection of DNS DoS flooding attacks is provided to illustrate the applications of the proposed algorithm.

A study of Hough Transform-based fingerprint alignment algorithms

CSIR Research Space (South Africa)

Mlambo, CS

2014-10-01

Full Text Available the implementation of each algorithm. The comparison is performed by considering the alignment results computed using each group of algorithms when varying number of minutiae points, rotation angle, and translation. In addition, the memory usage, computing time...

MOVING WINDOW SEGMENTATION FRAMEWORK FOR POINT CLOUDS

Directory of Open Access Journals (Sweden)

G. Sithole

2012-07-01

Full Text Available As lidar point clouds become larger streamed processing becomes more attractive. This paper presents a framework for the streamed segmentation of point clouds with the intention of segmenting unstructured point clouds in real-time. The framework is composed of two main components. The first component segments points within a window shifting over the point cloud. The second component stitches the segments within the windows together. In this fashion a point cloud can be streamed through these two components in sequence, thus producing a segmentation. The algorithm has been tested on airborne lidar point cloud and some results of the performance of the framework are presented.

Fixed-Point Configurable Hardware Components

Directory of Open Access Journals (Sweden)

Rocher Romuald

2006-01-01

Full Text Available To reduce the gap between the VLSI technology capability and the designer productivity, design reuse based on IP (intellectual properties is commonly used. In terms of arithmetic accuracy, the generated architecture can generally only be configured through the input and output word lengths. In this paper, a new kind of method to optimize fixed-point arithmetic IP has been proposed. The architecture cost is minimized under accuracy constraints defined by the user. Our approach allows exploring the fixed-point search space and the algorithm-level search space to select the optimized structure and fixed-point specification. To significantly reduce the optimization and design times, analytical models are used for the fixed-point optimization process.

MIMIC: An Innovative Methodology for Determining Mobile Laser Scanning System Point Density

Directory of Open Access Journals (Sweden)

Conor Cahalane

2014-08-01

Full Text Available Understanding how various Mobile Mapping System (MMS laser hardware configurations and operating parameters exercise different influence on point density is important for assessing system performance, which in turn facilitates system design and MMS benchmarking. Point density also influences data processing, as objects that can be recognised using automated algorithms generally require a minimum point density. Although obtaining the necessary point density impacts on hardware costs, survey time and data storage requirements, a method for accurately and rapidly assessing MMS performance is lacking for generic MMSs. We have developed a method for quantifying point clouds collected by an MMS with respect to known objects at specified distances using 3D surface normals, 2D geometric formulae and line drawing algorithms. These algorithms were combined in a system called the Mobile Mapping Point Density Calculator (MIMIC and were validated using point clouds captured by both a single scanner and a dual scanner MMS. Results from MIMIC were promising: when considering the number of scan profiles striking the target, the average error equated to less than 1 point per scan profile. These tests highlight that MIMIC is capable of accurately calculating point density for both single and dual scanner MMSs.

Improving Accuracy and Simplifying Training in Fingerprinting-Based Indoor Location Algorithms at Room Level

Directory of Open Access Journals (Sweden)

Mario Muñoz-Organero

2016-01-01

Full Text Available Fingerprinting-based algorithms are popular in indoor location systems based on mobile devices. Comparing the RSSI (Received Signal Strength Indicator from different radio wave transmitters, such as Wi-Fi access points, with prerecorded fingerprints from located points (using different artificial intelligence algorithms, fingerprinting-based systems can locate unknown points with a few meters resolution. However, training the system with already located fingerprints tends to be an expensive task both in time and in resources, especially if large areas are to be considered. Moreover, the decision algorithms tend to be of high memory and CPU consuming in such cases and so does the required time for obtaining the estimated location for a new fingerprint. In this paper, we study, propose, and validate a way to select the locations for the training fingerprints which reduces the amount of required points while improving the accuracy of the algorithms when locating points at room level resolution. We present a comparison of different artificial intelligence decision algorithms and select those with better results. We do a comparison with other systems in the literature and draw conclusions about the improvements obtained in our proposal. Moreover, some techniques such as filtering nonstable access points for improving accuracy are introduced, studied, and validated.

The complexity of interior point methods for solving discounted turn-based stochastic games

DEFF Research Database (Denmark)

Hansen, Thomas Dueholm; Ibsen-Jensen, Rasmus

2013-01-01

for general 2TBSGs. This implies that a number of interior point methods can be used to solve 2TBSGs. We consider two such algorithms: the unified interior point method of Kojima, Megiddo, Noma, and Yoshise, and the interior point potential reduction algorithm of Kojima, Megiddo, and Ye. The algorithms run...... states and discount factor γ we get κ=Θ(n(1−γ)2) , −δ=Θ(n√1−γ) , and 1/θ=Θ(n(1−γ)2) in the worst case. The lower bounds for κ, − δ, and 1/θ are all obtained using the same family of deterministic games....

K-means Clustering: Lloyd's algorithm

Indian Academy of Sciences (India)

First page Back Continue Last page Overview Graphics. K-means Clustering: Lloyd's algorithm. Refines clusters iteratively. Cluster points using Voronoi partitioning of the centers; Centroids of the clusters determine the new centers. Bad example k = 3, n =4.

Effect of age on proximal esophageal response to swallowing

Directory of Open Access Journals (Sweden)

Roberto Oliveira Dantas

2010-12-01

Full Text Available CONTEXT: It has been demonstrated that the ageing process affects esophageal motility. OBJECTIVES: To evaluate the effect of the age on the proximal esophageal response to wet swallows. METHOD: We measured the proximal esophageal response to swallows of a 5 mL bolus of water in 69 healthy volunteers, 20 of them aged 18-30 years (group I, 27 aged 31-50 years (group II, and 22 aged 51-74 years (group III. We used the manometric method with continuous perfusion. The proximal esophageal contractions were recorded 5 cm from a pharyngeal recording site located 1 cm above the upper esophageal sphincter. The time between the onset of the pharyngeal and of the proximal esophageal recording (pharyngeal-esophageal time and the amplitude, duration and area under the curve of the proximal esophageal contraction were measured. RESULTS: The pharyngeal-esophageal time was shorter in group I subjects than in group II and III subjects (P<0.05. The duration of proximal esophageal contractions was longer in group I than in groups II and III (P<0.001. There was no differences between groups in the amplitude or area under the curve of contractions. There were no differences between groups II and III for any of the measurements. CONCLUSION: We conclude that the age may affects the response of the proximal esophagus to wet swallows.

Fault Diagnosis of Supervision and Homogenization Distance Based on Local Linear Embedding Algorithm

Directory of Open Access Journals (Sweden)

Guangbin Wang

2015-01-01

Full Text Available In view of the problems of uneven distribution of reality fault samples and dimension reduction effect of locally linear embedding (LLE algorithm which is easily affected by neighboring points, an improved local linear embedding algorithm of homogenization distance (HLLE is developed. The method makes the overall distribution of sample points tend to be homogenization and reduces the influence of neighboring points using homogenization distance instead of the traditional Euclidean distance. It is helpful to choose effective neighboring points to construct weight matrix for dimension reduction. Because the fault recognition performance improvement of HLLE is limited and unstable, the paper further proposes a new local linear embedding algorithm of supervision and homogenization distance (SHLLE by adding the supervised learning mechanism. On the basis of homogenization distance, supervised learning increases the category information of sample points so that the same category of sample points will be gathered and the heterogeneous category of sample points will be scattered. It effectively improves the performance of fault diagnosis and maintains stability at the same time. A comparison of the methods mentioned above was made by simulation experiment with rotor system fault diagnosis, and the results show that SHLLE algorithm has superior fault recognition performance.

Nearby Search Indekos Based Android Using A Star (A*) Algorithm

Science.gov (United States)

Siregar, B.; Nababan, EB; Rumahorbo, JA; Andayani, U.; Fahmi, F.

2018-03-01

Indekos or rented room is a temporary residence for months or years. Society of academicians who come from out of town need a temporary residence, such as Indekos or rented room during their education, teaching, or duties. They are often found difficulty in finding a Indekos because lack of information about the Indekos. Besides, new society of academicians don’t recognize the areas around the campus and desire the shortest path from Indekos to get to the campus. The problem can be solved by implementing A Star (A*) algorithm. This algorithm is one of the shortest path algorithm to a finding shortest path from campus to the Indekos application, where the faculties in the campus as the starting point of the finding. Determination of the starting point used in this study aims to allow students to determine the starting point in finding the Indekos. The mobile based application facilitates the finding anytime and anywhere. Based on the experimental results, A* algorithm can find the shortest path with 86,67% accuracy.

A reconstruction algorithms for helical cone-beam SPECT

International Nuclear Information System (INIS)

Weng, Y.; Zeng, G.L.; Gullberg, G.T.

1993-01-01

Cone-beam SPECT provides improved sensitivity for imaging small organs like the brain and heart. However, current cone-beam tomography with the focal point traversing a planar orbit does not acquire sufficient data to give an accurate reconstruction. In this paper, the authors employ a data-acquisition method which obtains complete data for cone-beam SPECT by simultaneously rotating the gamma camera and translating the patient bed, so that cone-beam projections can be obtained with the focal point traversing a helix surrounding the patient. An implementation of Grangeat's algorithm for helical cone-beam projections is developed. The algorithm requires a rebinning step to convert cone-beam data to parallel-beam data which are then reconstructed using the 3D Radon inversion. A fast new rebinning scheme is developed which uses all of the detected data to reconstruct the image and properly normalizes any multiply scanned data. This algorithm is shown to produce less artifacts than the commonly used Feldkamp algorithm when applied to either a circular planar orbit or a helical orbit acquisition. The algorithm can easily be extended to any arbitrary orbit

A sparse matrix based full-configuration interaction algorithm

International Nuclear Information System (INIS)

Rolik, Zoltan; Szabados, Agnes; Surjan, Peter R.

2008-01-01

We present an algorithm related to the full-configuration interaction (FCI) method that makes complete use of the sparse nature of the coefficient vector representing the many-electron wave function in a determinantal basis. Main achievements of the presented sparse FCI (SFCI) algorithm are (i) development of an iteration procedure that avoids the storage of FCI size vectors; (ii) development of an efficient algorithm to evaluate the effect of the Hamiltonian when both the initial and the product vectors are sparse. As a result of point (i) large disk operations can be skipped which otherwise may be a bottleneck of the procedure. At point (ii) we progress by adopting the implementation of the linear transformation by Olsen et al. [J. Chem Phys. 89, 2185 (1988)] for the sparse case, getting the algorithm applicable to larger systems and faster at the same time. The error of a SFCI calculation depends only on the dropout thresholds for the sparse vectors, and can be tuned by controlling the amount of system memory passed to the procedure. The algorithm permits to perform FCI calculations on single node workstations for systems previously accessible only by supercomputers

Large-Scale Parallel Viscous Flow Computations using an Unstructured Multigrid Algorithm

Science.gov (United States)

Mavriplis, Dimitri J.

1999-01-01

The development and testing of a parallel unstructured agglomeration multigrid algorithm for steady-state aerodynamic flows is discussed. The agglomeration multigrid strategy uses a graph algorithm to construct the coarse multigrid levels from the given fine grid, similar to an algebraic multigrid approach, but operates directly on the non-linear system using the FAS (Full Approximation Scheme) approach. The scalability and convergence rate of the multigrid algorithm are examined on the SGI Origin 2000 and the Cray T3E. An argument is given which indicates that the asymptotic scalability of the multigrid algorithm should be similar to that of its underlying single grid smoothing scheme. For medium size problems involving several million grid points, near perfect scalability is obtained for the single grid algorithm, while only a slight drop-off in parallel efficiency is observed for the multigrid V- and W-cycles, using up to 128 processors on the SGI Origin 2000, and up to 512 processors on the Cray T3E. For a large problem using 25 million grid points, good scalability is observed for the multigrid algorithm using up to 1450 processors on a Cray T3E, even when the coarsest grid level contains fewer points than the total number of processors.

Track length estimation applied to point detectors

International Nuclear Information System (INIS)

Rief, H.; Dubi, A.; Elperin, T.

1984-01-01

The concept of the track length estimator is applied to the uncollided point flux estimator (UCF) leading to a new algorithm of calculating fluxes at a point. It consists essentially of a line integral of the UCF, and although its variance is unbounded, the convergence rate is that of a bounded variance estimator. In certain applications, involving detector points in the vicinity of collimated beam sources, it has a lower variance than the once-more-collided point flux estimator, and its application is more straightforward

A Line-Based Adaptive-Weight Matching Algorithm Using Loopy Belief Propagation

Directory of Open Access Journals (Sweden)

Hui Li

2015-01-01

Full Text Available In traditional adaptive-weight stereo matching, the rectangular shaped support region requires excess memory consumption and time. We propose a novel line-based stereo matching algorithm for obtaining a more accurate disparity map with low computation complexity. This algorithm can be divided into two steps: disparity map initialization and disparity map refinement. In the initialization step, a new adaptive-weight model based on the linear support region is put forward for cost aggregation. In this model, the neural network is used to evaluate the spatial proximity, and the mean-shift segmentation method is used to improve the accuracy of color similarity; the Birchfield pixel dissimilarity function and the census transform are adopted to establish the dissimilarity measurement function. Then the initial disparity map is obtained by loopy belief propagation. In the refinement step, the disparity map is optimized by iterative left-right consistency checking method and segmentation voting method. The parameter values involved in this algorithm are determined with many simulation experiments to further improve the matching effect. Simulation results indicate that this new matching method performs well on standard stereo benchmarks and running time of our algorithm is remarkably lower than that of algorithm with rectangle-shaped support region.

Development of a hardware-in-the-loop testbed to demonstrate multiple spacecraft operations in proximity

Science.gov (United States)

Eun, Youngho; Park, Sang-Young; Kim, Geuk-Nam

2018-06-01

This paper presents a new state-of-the-art ground-based hardware-in-the-loop test facility, which was developed to verify and demonstrate autonomous guidance, navigation, and control algorithms for space proximity operations and formation flying maneuvers. The test facility consists of two complete spaceflight simulators, an aluminum-based operational arena, and a set of infrared motion tracking cameras; thus, the testbed is capable of representing space activities under circumstances prevailing on the ground. The spaceflight simulators have a maximum of five-degree-of-freedom in a quasi-momentum-free environment, which is produced by a set of linear/hemispherical air-bearings and a horizontally leveled operational arena. The tracking system measures the real-time three-dimensional position and attitude to provide state variables to the agents. The design of the testbed is illustrated in detail for every element throughout the paper. The practical hardware characteristics of the active/passive measurement units and internal actuators are identified in detail from various perspectives. These experimental results support the successful development of the entire facility and enable us to implement and verify the spacecraft proximity operation strategy in the near future.

SkyAlign: a portable, work-efficient skyline algorithm for multicore and GPU architectures

DEFF Research Database (Denmark)

Bøgh, Kenneth Sejdenfaden; Chester, Sean; Assent, Ira

2016-01-01

The skyline operator determines points in a multidimensional dataset that offer some optimal trade-off. State-of-the-art CPU skyline algorithms exploit quad-tree partitioning with complex branching to minimise the number of point-to-point comparisons. Branch-phobic GPU skyline algorithms rely on ...... native multicore state of the art on challenging workloads by an increasing margin as more cores and sockets are utilised....

High precision target center determination from a point cloud

Directory of Open Access Journals (Sweden)

K. Kregar

2013-10-01

Full Text Available Many applications of terrestrial laser scanners (TLS require the determination of a specific point from a point cloud. In this paper procedure of high precision planar target center acquisition from point cloud is presented. The process is based on an image matching algorithm but before we can deal with raster image to fit a target on it, we need to properly determine the best fitting plane and project points on it. The main emphasis of this paper is in the precision estimation and propagation through the whole procedure which allows us to obtain precision assessment of final results (target center coordinates. Theoretic precision estimations – obtained through the procedure were rather high so we compared them with the empiric precision estimations obtained as standard deviations of results of 60 independently scanned targets. An χ2-test confirmed that theoretic precisions are overestimated. The problem most probably lies in the overestimated precisions of the plane parameters due to vast redundancy of points. However, empirical precisions also confirmed that the proposed procedure can ensure a submillimeter precision level. The algorithm can automatically detect grossly erroneous results to some extent. It can operate when the incidence angles of a laser beam are as high as 80°, which is desirable property if one is going to use planar targets as tie points in scan registration. The proposed algorithm will also contribute to improve TLS calibration procedures.