International Nuclear Information System (INIS)
Peirce, A; Rochinha, F
2012-01-01
We describe a novel approach to the inversion of elasto-static tiltmeter measurements to monitor planar hydraulic fractures propagating within three-dimensional elastic media. The technique combines the extended Kalman filter (EKF), which predicts and updates state estimates using tiltmeter measurement time-series, with a novel implicit level set algorithm (ILSA), which solves the coupled elasto-hydrodynamic equations. The EKF and ILSA are integrated to produce an algorithm to locate the unknown fracture-free boundary. A scaling argument is used to derive a strategy to tune the algorithm parameters to enable measurement information to compensate for unmodeled dynamics. Synthetic tiltmeter data for three numerical experiments are generated by introducing significant changes to the fracture geometry by altering the confining geological stress field. Even though there is no confining stress field in the dynamic model used by the new EKF-ILSA scheme, it is able to use synthetic data to arrive at remarkably accurate predictions of the fracture widths and footprints. These experiments also explore the robustness of the algorithm to noise and to placement of tiltmeter arrays operating in the near-field and far-field regimes. In these experiments, the appropriate parameter choices and strategies to improve the robustness of the algorithm to significant measurement noise are explored. (paper)
Level-set-based reconstruction algorithm for EIT lung images: first clinical results.
Rahmati, Peyman; Soleimani, Manuchehr; Pulletz, Sven; Frerichs, Inéz; Adler, Andy
2012-05-01
We show the first clinical results using the level-set-based reconstruction algorithm for electrical impedance tomography (EIT) data. The level-set-based reconstruction method (LSRM) allows the reconstruction of non-smooth interfaces between image regions, which are typically smoothed by traditional voxel-based reconstruction methods (VBRMs). We develop a time difference formulation of the LSRM for 2D images. The proposed reconstruction method is applied to reconstruct clinical EIT data of a slow flow inflation pressure-volume manoeuvre in lung-healthy and adult lung-injury patients. Images from the LSRM and the VBRM are compared. The results show comparable reconstructed images, but with an improved ability to reconstruct sharp conductivity changes in the distribution of lung ventilation using the LSRM.
Level-set-based reconstruction algorithm for EIT lung images: first clinical results
International Nuclear Information System (INIS)
Rahmati, Peyman; Adler, Andy; Soleimani, Manuchehr; Pulletz, Sven; Frerichs, Inéz
2012-01-01
We show the first clinical results using the level-set-based reconstruction algorithm for electrical impedance tomography (EIT) data. The level-set-based reconstruction method (LSRM) allows the reconstruction of non-smooth interfaces between image regions, which are typically smoothed by traditional voxel-based reconstruction methods (VBRMs). We develop a time difference formulation of the LSRM for 2D images. The proposed reconstruction method is applied to reconstruct clinical EIT data of a slow flow inflation pressure–volume manoeuvre in lung-healthy and adult lung-injury patients. Images from the LSRM and the VBRM are compared. The results show comparable reconstructed images, but with an improved ability to reconstruct sharp conductivity changes in the distribution of lung ventilation using the LSRM. (paper)
Microwave imaging of dielectric cylinder using level set method and conjugate gradient algorithm
International Nuclear Information System (INIS)
Grayaa, K.; Bouzidi, A.; Aguili, T.
2011-01-01
In this paper, we propose a computational method for microwave imaging cylinder and dielectric object, based on combining level set technique and the conjugate gradient algorithm. By measuring the scattered field, we tried to retrieve the shape, localisation and the permittivity of the object. The forward problem is solved by the moment method, while the inverse problem is reformulate in an optimization one and is solved by the proposed scheme. It found that the proposed method is able to give good reconstruction quality in terms of the reconstructed shape and permittivity.
CT liver volumetry using geodesic active contour segmentation with a level-set algorithm
Suzuki, Kenji; Epstein, Mark L.; Kohlbrenner, Ryan; Obajuluwa, Ademola; Xu, Jianwu; Hori, Masatoshi; Baron, Richard
2010-03-01
Automatic liver segmentation on CT images is challenging because the liver often abuts other organs of a similar density. Our purpose was to develop an accurate automated liver segmentation scheme for measuring liver volumes. We developed an automated volumetry scheme for the liver in CT based on a 5 step schema. First, an anisotropic smoothing filter was applied to portal-venous phase CT images to remove noise while preserving the liver structure, followed by an edge enhancer to enhance the liver boundary. By using the boundary-enhanced image as a speed function, a fastmarching algorithm generated an initial surface that roughly estimated the liver shape. A geodesic-active-contour segmentation algorithm coupled with level-set contour-evolution refined the initial surface so as to more precisely fit the liver boundary. The liver volume was calculated based on the refined liver surface. Hepatic CT scans of eighteen prospective liver donors were obtained under a liver transplant protocol with a multi-detector CT system. Automated liver volumes obtained were compared with those manually traced by a radiologist, used as "gold standard." The mean liver volume obtained with our scheme was 1,520 cc, whereas the mean manual volume was 1,486 cc, with the mean absolute difference of 104 cc (7.0%). CT liver volumetrics based on an automated scheme agreed excellently with "goldstandard" manual volumetrics (intra-class correlation coefficient was 0.95) with no statistically significant difference (p(F<=f)=0.32), and required substantially less completion time. Our automated scheme provides an efficient and accurate way of measuring liver volumes.
Fu, Lin; Hu, Xiangyu Y.; Adams, Nikolaus A.
2017-12-01
We propose efficient single-step formulations for reinitialization and extending algorithms, which are critical components of level-set based interface-tracking methods. The level-set field is reinitialized with a single-step (non iterative) "forward tracing" algorithm. A minimum set of cells is defined that describes the interface, and reinitialization employs only data from these cells. Fluid states are extrapolated or extended across the interface by a single-step "backward tracing" algorithm. Both algorithms, which are motivated by analogy to ray-tracing, avoid multiple block-boundary data exchanges that are inevitable for iterative reinitialization and extending approaches within a parallel-computing environment. The single-step algorithms are combined with a multi-resolution conservative sharp-interface method and validated by a wide range of benchmark test cases. We demonstrate that the proposed reinitialization method achieves second-order accuracy in conserving the volume of each phase. The interface location is invariant to reapplication of the single-step reinitialization. Generally, we observe smaller absolute errors than for standard iterative reinitialization on the same grid. The computational efficiency is higher than for the standard and typical high-order iterative reinitialization methods. We observe a 2- to 6-times efficiency improvement over the standard method for serial execution. The proposed single-step extending algorithm, which is commonly employed for assigning data to ghost cells with ghost-fluid or conservative interface interaction methods, shows about 10-times efficiency improvement over the standard method while maintaining same accuracy. Despite their simplicity, the proposed algorithms offer an efficient and robust alternative to iterative reinitialization and extending methods for level-set based multi-phase simulations.
Bieberle, M; Hampel, U
2015-06-13
Tomographic image reconstruction is based on recovering an object distribution from its projections, which have been acquired from all angular views around the object. If the angular range is limited to less than 180° of parallel projections, typical reconstruction artefacts arise when using standard algorithms. To compensate for this, specialized algorithms using a priori information about the object need to be applied. The application behind this work is ultrafast limited-angle X-ray computed tomography of two-phase flows. Here, only a binary distribution of the two phases needs to be reconstructed, which reduces the complexity of the inverse problem. To solve it, a new reconstruction algorithm (LSR) based on the level-set method is proposed. It includes one force function term accounting for matching the projection data and one incorporating a curvature-dependent smoothing of the phase boundary. The algorithm has been validated using simulated as well as measured projections of known structures, and its performance has been compared to the algebraic reconstruction technique and a binary derivative of it. The validation as well as the application of the level-set reconstruction on a dynamic two-phase flow demonstrated its applicability and its advantages over other reconstruction algorithms. © 2015 The Author(s) Published by the Royal Society. All rights reserved.
Muñoz-Esparza, Domingo; Kosović, Branko; Jiménez, Pedro A.; Coen, Janice L.
2018-04-01
The level-set method is typically used to track and propagate the fire perimeter in wildland fire models. Herein, a high-order level-set method using fifth-order WENO scheme for the discretization of spatial derivatives and third-order explicit Runge-Kutta temporal integration is implemented within the Weather Research and Forecasting model wildland fire physics package, WRF-Fire. The algorithm includes solution of an additional partial differential equation for level-set reinitialization. The accuracy of the fire-front shape and rate of spread in uncoupled simulations is systematically analyzed. It is demonstrated that the common implementation used by level-set-based wildfire models yields to rate-of-spread errors in the range 10-35% for typical grid sizes (Δ = 12.5-100 m) and considerably underestimates fire area. Moreover, the amplitude of fire-front gradients in the presence of explicitly resolved turbulence features is systematically underestimated. In contrast, the new WRF-Fire algorithm results in rate-of-spread errors that are lower than 1% and that become nearly grid independent. Also, the underestimation of fire area at the sharp transition between the fire front and the lateral flanks is found to be reduced by a factor of ≈7. A hybrid-order level-set method with locally reduced artificial viscosity is proposed, which substantially alleviates the computational cost associated with high-order discretizations while preserving accuracy. Simulations of the Last Chance wildfire demonstrate additional benefits of high-order accurate level-set algorithms when dealing with complex fuel heterogeneities, enabling propagation across narrow fuel gaps and more accurate fire backing over the lee side of no fuel clusters.
Lei, H.; Lu, Z.; Vesselinov, V. V.; Ye, M.
2017-12-01
Simultaneous identification of both the zonation structure of aquifer heterogeneity and the hydrogeological parameters associated with these zones is challenging, especially for complex subsurface heterogeneity fields. In this study, a new approach, based on the combination of the level set method and a parallel genetic algorithm is proposed. Starting with an initial guess for the zonation field (including both zonation structure and the hydraulic properties of each zone), the level set method ensures that material interfaces are evolved through the inverse process such that the total residual between the simulated and observed state variables (hydraulic head) always decreases, which means that the inversion result depends on the initial guess field and the minimization process might fail if it encounters a local minimum. To find the global minimum, the genetic algorithm (GA) is utilized to explore the parameters that define initial guess fields, and the minimal total residual corresponding to each initial guess field is considered as the fitness function value in the GA. Due to the expensive evaluation of the fitness function, a parallel GA is adapted in combination with a simulated annealing algorithm. The new approach has been applied to several synthetic cases in both steady-state and transient flow fields, including a case with real flow conditions at the chromium contaminant site at the Los Alamos National Laboratory. The results show that this approach is capable of identifying the arbitrary zonation structures of aquifer heterogeneity and the hydrogeological parameters associated with these zones effectively.
Algorithms over partially ordered sets
DEFF Research Database (Denmark)
Baer, Robert M.; Østerby, Ole
1969-01-01
in partially ordered sets, answer the combinatorial question of how many maximal chains might exist in a partially ordered set withn elements, and we give an algorithm for enumerating all maximal chains. We give (in § 3) algorithms which decide whether a partially ordered set is a (lower or upper) semi......-lattice, and whether a lattice has distributive, modular, and Boolean properties. Finally (in § 4) we give Algol realizations of the various algorithms....
Algorithms for detecting and analysing autocatalytic sets.
Hordijk, Wim; Smith, Joshua I; Steel, Mike
2015-01-01
Autocatalytic sets are considered to be fundamental to the origin of life. Prior theoretical and computational work on the existence and properties of these sets has relied on a fast algorithm for detectingself-sustaining autocatalytic sets in chemical reaction systems. Here, we introduce and apply a modified version and several extensions of the basic algorithm: (i) a modification aimed at reducing the number of calls to the computationally most expensive part of the algorithm, (ii) the application of a previously introduced extension of the basic algorithm to sample the smallest possible autocatalytic sets within a reaction network, and the application of a statistical test which provides a probable lower bound on the number of such smallest sets, (iii) the introduction and application of another extension of the basic algorithm to detect autocatalytic sets in a reaction system where molecules can also inhibit (as well as catalyse) reactions, (iv) a further, more abstract, extension of the theory behind searching for autocatalytic sets. (i) The modified algorithm outperforms the original one in the number of calls to the computationally most expensive procedure, which, in some cases also leads to a significant improvement in overall running time, (ii) our statistical test provides strong support for the existence of very large numbers (even millions) of minimal autocatalytic sets in a well-studied polymer model, where these minimal sets share about half of their reactions on average, (iii) "uninhibited" autocatalytic sets can be found in reaction systems that allow inhibition, but their number and sizes depend on the level of inhibition relative to the level of catalysis. (i) Improvements in the overall running time when searching for autocatalytic sets can potentially be obtained by using a modified version of the algorithm, (ii) the existence of large numbers of minimal autocatalytic sets can have important consequences for the possible evolvability of
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 highly efficient 3D level-set grain growth algorithm tailored for ccNUMA architecture
Mießen, C.; Velinov, N.; Gottstein, G.; Barrales-Mora, L. A.
2017-12-01
A highly efficient simulation model for 2D and 3D grain growth was developed based on the level-set method. The model introduces modern computational concepts to achieve excellent performance on parallel computer architectures. Strong scalability was measured on cache-coherent non-uniform memory access (ccNUMA) architectures. To achieve this, the proposed approach considers the application of local level-set functions at the grain level. Ideal and non-ideal grain growth was simulated in 3D with the objective to study the evolution of statistical representative volume elements in polycrystals. In addition, microstructure evolution in an anisotropic magnetic material affected by an external magnetic field was simulated.
Dakua, Sarada Prasad; Abinahed, Julien; Al-Ansari, Abdulla
2015-04-01
Liver segmentation continues to remain a major challenge, largely due to its intense complexity with surrounding anatomical structures (stomach, kidney, and heart), high noise level and lack of contrast in pathological computed tomography (CT) data. We present an approach to reconstructing the liver surface in low contrast CT. The main contributions are: (1) a stochastic resonance-based methodology in discrete cosine transform domain is developed to enhance the contrast of pathological liver images, (2) a new formulation is proposed to prevent the object boundary, resulting from the cellular automata method, from leaking into the surrounding areas of similar intensity, and (3) a level-set method is suggested to generate intermediate segmentation contours from two segmented slices distantly located in a subject sequence. We have tested the algorithm on real datasets obtained from two sources, Hamad General Hospital and medical image computing and computer-assisted interventions grand challenge workshop. Various parameters in the algorithm, such as [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], and [Formula: see text], play imperative roles, thus their values are precisely selected. Both qualitative and quantitative evaluation performed on liver data show promising segmentation accuracy when compared with ground truth data reflecting the potential of the proposed method.
Energy Technology Data Exchange (ETDEWEB)
Suzuki, Kenji; Kohlbrenner, Ryan; Epstein, Mark L.; Obajuluwa, Ademola M.; Xu Jianwu; Hori, Masatoshi [Department of Radiology, University of Chicago, 5841 South Maryland Avenue, Chicago, Illinois 60637 (United States)
2010-05-15
Purpose: Computerized liver extraction from hepatic CT images is challenging because the liver often abuts other organs of a similar density. The purpose of this study was to develop a computer-aided measurement of liver volumes in hepatic CT. Methods: The authors developed a computerized liver extraction scheme based on geodesic active contour segmentation coupled with level-set contour evolution. First, an anisotropic diffusion filter was applied to portal-venous-phase CT images for noise reduction while preserving the liver structure, followed by a scale-specific gradient magnitude filter to enhance the liver boundaries. Then, a nonlinear grayscale converter enhanced the contrast of the liver parenchyma. By using the liver-parenchyma-enhanced image as a speed function, a fast-marching level-set algorithm generated an initial contour that roughly estimated the liver shape. A geodesic active contour segmentation algorithm coupled with level-set contour evolution refined the initial contour to define the liver boundaries more precisely. The liver volume was then calculated using these refined boundaries. Hepatic CT scans of 15 prospective liver donors were obtained under a liver transplant protocol with a multidetector CT system. The liver volumes extracted by the computerized scheme were compared to those traced manually by a radiologist, used as ''gold standard.''Results: The mean liver volume obtained with our scheme was 1504 cc, whereas the mean gold standard manual volume was 1457 cc, resulting in a mean absolute difference of 105 cc (7.2%). The computer-estimated liver volumetrics agreed excellently with the gold-standard manual volumetrics (intraclass correlation coefficient was 0.95) with no statistically significant difference (F=0.77; p(F{<=}f)=0.32). The average accuracy, sensitivity, specificity, and percent volume error were 98.4%, 91.1%, 99.1%, and 7.2%, respectively. Computerized CT liver volumetry would require substantially less
International Nuclear Information System (INIS)
Suzuki, Kenji; Kohlbrenner, Ryan; Epstein, Mark L.; Obajuluwa, Ademola M.; Xu Jianwu; Hori, Masatoshi
2010-01-01
Purpose: Computerized liver extraction from hepatic CT images is challenging because the liver often abuts other organs of a similar density. The purpose of this study was to develop a computer-aided measurement of liver volumes in hepatic CT. Methods: The authors developed a computerized liver extraction scheme based on geodesic active contour segmentation coupled with level-set contour evolution. First, an anisotropic diffusion filter was applied to portal-venous-phase CT images for noise reduction while preserving the liver structure, followed by a scale-specific gradient magnitude filter to enhance the liver boundaries. Then, a nonlinear grayscale converter enhanced the contrast of the liver parenchyma. By using the liver-parenchyma-enhanced image as a speed function, a fast-marching level-set algorithm generated an initial contour that roughly estimated the liver shape. A geodesic active contour segmentation algorithm coupled with level-set contour evolution refined the initial contour to define the liver boundaries more precisely. The liver volume was then calculated using these refined boundaries. Hepatic CT scans of 15 prospective liver donors were obtained under a liver transplant protocol with a multidetector CT system. The liver volumes extracted by the computerized scheme were compared to those traced manually by a radiologist, used as ''gold standard.''Results: The mean liver volume obtained with our scheme was 1504 cc, whereas the mean gold standard manual volume was 1457 cc, resulting in a mean absolute difference of 105 cc (7.2%). The computer-estimated liver volumetrics agreed excellently with the gold-standard manual volumetrics (intraclass correlation coefficient was 0.95) with no statistically significant difference (F=0.77; p(F≤f)=0.32). The average accuracy, sensitivity, specificity, and percent volume error were 98.4%, 91.1%, 99.1%, and 7.2%, respectively. Computerized CT liver volumetry would require substantially less completion time
Considerations and Algorithms for Compression of Sets
DEFF Research Database (Denmark)
Larsson, Jesper
We consider compression of unordered sets of distinct elements. After a discus- sion of the general problem, we focus on compressing sets of fixed-length bitstrings in the presence of statistical information. We survey techniques from previous work, suggesting some adjustments, and propose a novel...... compression algorithm that allows transparent incorporation of various estimates for probability distribution. Our experimental results allow the conclusion that set compression can benefit from incorporat- ing statistics, using our method or variants of previously known techniques....
Set-Membership Proportionate Affine Projection Algorithms
Directory of Open Access Journals (Sweden)
Stefan Werner
2007-01-01
Full Text Available Proportionate adaptive filters can improve the convergence speed for the identification of sparse systems as compared to their conventional counterparts. In this paper, the idea of proportionate adaptation is combined with the framework of set-membership filtering (SMF in an attempt to derive novel computationally efficient algorithms. The resulting algorithms attain an attractive faster converge for both situations of sparse and dispersive channels while decreasing the average computational complexity due to the data discerning feature of the SMF approach. In addition, we propose a rule that allows us to automatically adjust the number of past data pairs employed in the update. This leads to a set-membership proportionate affine projection algorithm (SM-PAPA having a variable data-reuse factor allowing a significant reduction in the overall complexity when compared with a fixed data-reuse factor. Reduced-complexity implementations of the proposed algorithms are also considered that reduce the dimensions of the matrix inversions involved in the update. Simulations show good results in terms of reduced number of updates, speed of convergence, and final mean-squared error.
The Aquarius Level 2 Algorithm
Meissner, T.; Wentz, F. J.; Hilburn, K. A.; Lagerloef, G. S.; Le Vine, D. M.
2012-12-01
The Aquarius L-band radiometer/scatterometer system is designed to provide monthly salinity maps at 150 km spatial scale to an accuracy of 0.2 psu. The sensor was launched on June 10, 2011, aboard the Argentine CONAE SAC-D spacecraft. The L-band radiometers and the scatterometer have been taking science data observations since August 25, 2011. This presentation discusses the current state of the Aquarius Level processing algorithm, which transforms radiometer counts ultimately into sea surface salinity (SSS). We focus on several topics that we have investigated since launch: 1. Updated Pointing A detailed check of the Aquarius pointing angles was performed, which consists in making adjustments of the two pointing angles, azimuth angle and off-nadir angle, for each horn. It has been found that the necessary adjustments for all 3 horns can be explained by a single offset for the antenna pointing if we introduce a constant offset in the roll angle by - 0.51 deg and the pitch angle by + 0.16 deg. 2. Antenna Patterns and Instrument Calibration In March 2012 JPL has produced a set of new antenna patterns using the GRASP software. Compared with the various pre-launch patterns those new patterns lead to an increase in the spillover coefficient by about 1%. We discuss its impact on several components of the Level 2 processing: the antenna pattern correction (APC), the correction for intrusion of galactic and solar radiation that is reflected from the ocean surface into the Aquarius field of view, and the correction of contamination from land surface radiation entering into the sidelobes. We show that the new antenna patterns result in a consistent calibration of all 3 Stokes parameters, which can be best demonstrated during spacecraft pitch maneuvers. 3. Cross Polarization Couplings of the 3rd Stokes Parameter Using the APC values for the cross polarization coupling of the 3rd Stokes parameter into the 1st and 2nd Stokes parameter lead to a spurious image of the 3rd Stokes
Algorithm for finding minimal cut sets in a fault tree
International Nuclear Information System (INIS)
Rosenberg, Ladislav
1996-01-01
This paper presents several algorithms that have been used in a computer code for fault-tree analysing by the minimal cut sets method. The main algorithm is the more efficient version of the new CARA algorithm, which finds minimal cut sets with an auxiliary dynamical structure. The presented algorithm for finding the minimal cut sets enables one to do so by defined requirements - according to the order of minimal cut sets, or to the number of minimal cut sets, or both. This algorithm is from three to six times faster when compared with the primary version of the CARA algorithm
Analysing Music with Point-Set Compression Algorithms
DEFF Research Database (Denmark)
Meredith, David
2016-01-01
Several point-set pattern-discovery and compression algorithms designed for analysing music are reviewed and evaluated. Each algorithm takes as input a point-set representation of a score in which each note is represented as a point in pitch-time space. Each algorithm computes the maximal...... and sections in pieces of classical music. On the first task, the best-performing algorithms achieved success rates of around 84%. In the second task, the best algorithms achieved mean F1 scores of around 0.49, with scores for individual pieces rising as high as 0.71....
Identifying Heterogeneities in Subsurface Environment using the Level Set Method
Energy Technology Data Exchange (ETDEWEB)
Lei, Hongzhuan [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Lu, Zhiming [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Vesselinov, Velimir Valentinov [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2016-08-25
These are slides from a presentation on identifying heterogeneities in subsurface environment using the level set method. The slides start with the motivation, then explain Level Set Method (LSM), the algorithms, some examples are given, and finally future work is explained.
An application of the maximal independent set algorithm to course ...
African Journals Online (AJOL)
In this paper, we demonstrated one of the many applications of the Maximal Independent Set Algorithm in the area of course allocation. A program was developed in Pascal and used in implementing a modified version of the algorithm to assign teaching courses to available lecturers in any academic environment and it ...
Parallel clustering algorithm for large-scale biological data sets.
Wang, Minchao; Zhang, Wu; Ding, Wang; Dai, Dongbo; Zhang, Huiran; Xie, Hao; Chen, Luonan; Guo, Yike; Xie, Jiang
2014-01-01
Recent explosion of biological data brings a great challenge for the traditional clustering algorithms. With increasing scale of data sets, much larger memory and longer runtime are required for the cluster identification problems. The affinity propagation algorithm outperforms many other classical clustering algorithms and is widely applied into the biological researches. However, the time and space complexity become a great bottleneck when handling the large-scale data sets. Moreover, the similarity matrix, whose constructing procedure takes long runtime, is required before running the affinity propagation algorithm, since the algorithm clusters data sets based on the similarities between data pairs. Two types of parallel architectures are proposed in this paper to accelerate the similarity matrix constructing procedure and the affinity propagation algorithm. The memory-shared architecture is used to construct the similarity matrix, and the distributed system is taken for the affinity propagation algorithm, because of its large memory size and great computing capacity. An appropriate way of data partition and reduction is designed in our method, in order to minimize the global communication cost among processes. A speedup of 100 is gained with 128 cores. The runtime is reduced from serval hours to a few seconds, which indicates that parallel algorithm is capable of handling large-scale data sets effectively. The parallel affinity propagation also achieves a good performance when clustering large-scale gene data (microarray) and detecting families in large protein superfamilies.
On reinitializing level set functions
Min, Chohong
2010-04-01
In this paper, we consider reinitializing level functions through equation ϕt+sgn(ϕ0)(‖∇ϕ‖-1)=0[16]. The method of Russo and Smereka [11] is taken in the spatial discretization of the equation. The spatial discretization is, simply speaking, the second order ENO finite difference with subcell resolution near the interface. Our main interest is on the temporal discretization of the equation. We compare the three temporal discretizations: the second order Runge-Kutta method, the forward Euler method, and a Gauss-Seidel iteration of the forward Euler method. The fact that the time in the equation is fictitious makes a hypothesis that all the temporal discretizations result in the same result in their stationary states. The fact that the absolute stability region of the forward Euler method is not wide enough to include all the eigenvalues of the linearized semi-discrete system of the second order ENO spatial discretization makes another hypothesis that the forward Euler temporal discretization should invoke numerical instability. Our results in this paper contradict both the hypotheses. The Runge-Kutta and Gauss-Seidel methods obtain the second order accuracy, and the forward Euler method converges with order between one and two. Examining all their properties, we conclude that the Gauss-Seidel method is the best among the three. Compared to the Runge-Kutta, it is twice faster and requires memory two times less with the same accuracy.
A linear-time algorithm for Euclidean feature transform sets
Hesselink, Wim H.
2007-01-01
The Euclidean distance transform of a binary image is the function that assigns to every pixel the Euclidean distance to the background. The Euclidean feature transform is the function that assigns to every pixel the set of background pixels with this distance. We present an algorithm to compute the
An Adaptive Algorithm for Finding Frequent Sets in Landmark Windows
DEFF Research Database (Denmark)
Dang, Xuan-Hong; Ong, Kok-Leong; Lee, Vincent
2012-01-01
We consider a CPU constrained environment for finding approximation of frequent sets in data streams using the landmark window. Our algorithm can detect overload situations, i.e., breaching the CPU capacity, and sheds data in the stream to “keep up”. This is done within a controlled error threshold...
Efficient Algorithms for Segmentation of Item-Set Time Series
Chundi, Parvathi; Rosenkrantz, Daniel J.
We propose a special type of time series, which we call an item-set time series, to facilitate the temporal analysis of software version histories, email logs, stock market data, etc. In an item-set time series, each observed data value is a set of discrete items. We formalize the concept of an item-set time series and present efficient algorithms for segmenting a given item-set time series. Segmentation of a time series partitions the time series into a sequence of segments where each segment is constructed by combining consecutive time points of the time series. Each segment is associated with an item set that is computed from the item sets of the time points in that segment, using a function which we call a measure function. We then define a concept called the segment difference, which measures the difference between the item set of a segment and the item sets of the time points in that segment. The segment difference values are required to construct an optimal segmentation of the time series. We describe novel and efficient algorithms to compute segment difference values for each of the measure functions described in the paper. We outline a dynamic programming based scheme to construct an optimal segmentation of the given item-set time series. We use the item-set time series segmentation techniques to analyze the temporal content of three different data sets—Enron email, stock market data, and a synthetic data set. The experimental results show that an optimal segmentation of item-set time series data captures much more temporal content than a segmentation constructed based on the number of time points in each segment, without examining the item set data at the time points, and can be used to analyze different types of temporal data.
A new level set model for multimaterial flows
Energy Technology Data Exchange (ETDEWEB)
Starinshak, David P. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Karni, Smadar [Univ. of Michigan, Ann Arbor, MI (United States). Dept. of Mathematics; Roe, Philip L. [Univ. of Michigan, Ann Arbor, MI (United States). Dept. of AerospaceEngineering
2014-01-08
We present a new level set model for representing multimaterial flows in multiple space dimensions. Instead of associating a level set function with a specific fluid material, the function is associated with a pair of materials and the interface that separates them. A voting algorithm collects sign information from all level sets and determines material designations. M(M ₋1)/2 level set functions might be needed to represent a general M-material configuration; problems of practical interest use far fewer functions, since not all pairs of materials share an interface. The new model is less prone to producing indeterminate material states, i.e. regions claimed by more than one material (overlaps) or no material at all (vacuums). It outperforms existing material-based level set models without the need for reinitialization schemes, thereby avoiding additional computational costs and preventing excessive numerical diffusion.
A Memory and Computation Efficient Sparse Level-Set Method
Laan, Wladimir J. van der; Jalba, Andrei C.; Roerdink, Jos B.T.M.
Since its introduction, the level set method has become the favorite technique for capturing and tracking moving interfaces, and found applications in a wide variety of scientific fields. In this paper we present efficient data structures and algorithms for tracking dynamic interfaces through the
Fast Sparse Level Sets on Graphics Hardware
Jalba, Andrei C.; Laan, Wladimir J. van der; Roerdink, Jos B.T.M.
The level-set method is one of the most popular techniques for capturing and tracking deformable interfaces. Although level sets have demonstrated great potential in visualization and computer graphics applications, such as surface editing and physically based modeling, their use for interactive
Fuzzy Sets-based Control Rules for Terminating Algorithms
Directory of Open Access Journals (Sweden)
Jose L. VERDEGAY
2002-01-01
Full Text Available In this paper some problems arising in the interface between two different areas, Decision Support Systems and Fuzzy Sets and Systems, are considered. The Model-Base Management System of a Decision Support System which involves some fuzziness is considered, and in that context the questions on the management of the fuzziness in some optimisation models, and then of using fuzzy rules for terminating conventional algorithms are presented, discussed and analyzed. Finally, for the concrete case of the Travelling Salesman Problem, and as an illustration of determination, management and using the fuzzy rules, a new algorithm easy to implement in the Model-Base Management System of any oriented Decision Support System is shown.
On multiple level-set regularization methods for inverse problems
International Nuclear Information System (INIS)
DeCezaro, A; Leitão, A; Tai, X-C
2009-01-01
We analyze a multiple level-set method for solving inverse problems with piecewise constant solutions. This method corresponds to an iterated Tikhonov method for a particular Tikhonov functional G α based on TV–H 1 penalization. We define generalized minimizers for our Tikhonov functional and establish an existence result. Moreover, we prove convergence and stability results of the proposed Tikhonov method. A multiple level-set algorithm is derived from the first-order optimality conditions for the Tikhonov functional G α , similarly as the iterated Tikhonov method. The proposed multiple level-set method is tested on an inverse potential problem. Numerical experiments show that the method is able to recover multiple objects as well as multiple contrast levels
Hybrid approach for detection of dental caries based on the methods FCM and level sets
Chaabene, Marwa; Ben Ali, Ramzi; Ejbali, Ridha; Zaied, Mourad
2017-03-01
This paper presents a new technique for detection of dental caries that is a bacterial disease that destroys the tooth structure. In our approach, we have achieved a new segmentation method that combines the advantages of fuzzy C mean algorithm and level set method. The results obtained by the FCM algorithm will be used by Level sets algorithm to reduce the influence of the noise effect on the working of each of these algorithms, to facilitate level sets manipulation and to lead to more robust segmentation. The sensitivity and specificity confirm the effectiveness of proposed method for caries detection.
A new level set model for cell image segmentation
Ma, Jing-Feng; Hou, Kai; Bao, Shang-Lian; Chen, Chun
2011-02-01
In this paper we first determine three phases of cell images: background, cytoplasm and nucleolus according to the general physical characteristics of cell images, and then develop a variational model, based on these characteristics, to segment nucleolus and cytoplasm from their relatively complicated backgrounds. In the meantime, the preprocessing obtained information of cell images using the OTSU algorithm is used to initialize the level set function in the model, which can speed up the segmentation and present satisfactory results in cell image processing.
Efficient algorithms for collaborative decision making for large scale settings
DEFF Research Database (Denmark)
Assent, Ira
2011-01-01
to bring about more effective and more efficient retrieval systems that support the users' decision making process. We sketch promising research directions for more efficient algorithms for collaborative decision making, especially for large scale systems.......Collaborative decision making is a successful approach in settings where data analysis and querying can be done interactively. In large scale systems with huge data volumes or many users, collaboration is often hindered by impractical runtimes. Existing work on improving collaboration focuses...... on avoiding redundancy for users working on the same task. While this improves the effectiveness of the user work process, the underlying query processing engine is typically considered a "black box" and left unchanged. Research in multiple query processing, on the other hand, ignores the application...
Aeon: Synthesizing Scheduling Algorithms from High-Level Models
Monette, Jean-Noël; Deville, Yves; van Hentenryck, Pascal
This paper describes the aeon system whose aim is to synthesize scheduling algorithms from high-level models. A eon, which is entirely written in comet, receives as input a high-level model for a scheduling application which is then analyzed to generate a dedicated scheduling algorithm exploiting the structure of the model. A eon provides a variety of synthesizers for generating complete or heuristic algorithms. Moreover, synthesizers are compositional, making it possible to generate complex hybrid algorithms naturally. Preliminary experimental results indicate that this approach may be competitive with state-of-the-art search algorithms.
Comparison of Co-Temporal Modeling Algorithms on Sparse Experimental Time Series Data Sets.
Allen, Edward E; Norris, James L; John, David J; Thomas, Stan J; Turkett, William H; Fetrow, Jacquelyn S
2010-01-01
Multiple approaches for reverse-engineering biological networks from time-series data have been proposed in the computational biology literature. These approaches can be classified by their underlying mathematical algorithms, such as Bayesian or algebraic techniques, as well as by their time paradigm, which includes next-state and co-temporal modeling. The types of biological relationships, such as parent-child or siblings, discovered by these algorithms are quite varied. It is important to understand the strengths and weaknesses of the various algorithms and time paradigms on actual experimental data. We assess how well the co-temporal implementations of three algorithms, continuous Bayesian, discrete Bayesian, and computational algebraic, can 1) identify two types of entity relationships, parent and sibling, between biological entities, 2) deal with experimental sparse time course data, and 3) handle experimental noise seen in replicate data sets. These algorithms are evaluated, using the shuffle index metric, for how well the resulting models match literature models in terms of siblings and parent relationships. Results indicate that all three co-temporal algorithms perform well, at a statistically significant level, at finding sibling relationships, but perform relatively poorly in finding parent relationships.
A new level set model for cell image segmentation
International Nuclear Information System (INIS)
Ma Jing-Feng; Chen Chun; Hou Kai; Bao Shang-Lian
2011-01-01
In this paper we first determine three phases of cell images: background, cytoplasm and nucleolus according to the general physical characteristics of cell images, and then develop a variational model, based on these characteristics, to segment nucleolus and cytoplasm from their relatively complicated backgrounds. In the meantime, the preprocessing obtained information of cell images using the OTSU algorithm is used to initialize the level set function in the model, which can speed up the segmentation and present satisfactory results in cell image processing. (cross-disciplinary physics and related areas of science and technology)
Structural level set inversion for microwave breast screening
International Nuclear Information System (INIS)
Irishina, Natalia; Álvarez, Diego; Dorn, Oliver; Moscoso, Miguel
2010-01-01
We present a new inversion strategy for the early detection of breast cancer from microwave data which is based on a new multiphase level set technique. This novel structural inversion method uses a modification of the color level set technique adapted to the specific situation of structural breast imaging taking into account the high complexity of the breast tissue. We only use data of a few microwave frequencies for detecting the tumors hidden in this complex structure. Three level set functions are employed for describing four different types of breast tissue, where each of these four regions is allowed to have a complicated topology and to have an interior structure which needs to be estimated from the data simultaneously with the region interfaces. The algorithm consists of several stages of increasing complexity. In each stage more details about the anatomical structure of the breast interior is incorporated into the inversion model. The synthetic breast models which are used for creating simulated data are based on real MRI images of the breast and are therefore quite realistic. Our results demonstrate the potential and feasibility of the proposed level set technique for detecting, locating and characterizing a small tumor in its early stage of development embedded in such a realistic breast model. Both the data acquisition simulation and the inversion are carried out in 2D
Level-0 trigger algorithms for the ALICE PHOS detector
Wang, D; Wang, Y P; Huang, G M; Kral, J; Yin, Z B; Zhou, D C; Zhang, F; Ullaland, K; Muller, H; Liu, L J
2011-01-01
The PHOS level-0 trigger provides a minimum bias trigger for p-p collisions and information for a level-1 trigger at both p-p and Pb-Pb collisions. There are two level-0 trigger generating algorithms under consideration: the Direct Comparison algorithm and the Weighted Sum algorithm. In order to study trigger algorithms via simulation, a simplified equivalent model is extracted from the trigger electronics to derive the waveform function of the Analog-or signal as input to the trigger algorithms. Simulations shown that the Weighted Sum algorithm can achieve higher trigger efficiency and provide more precise single channel energy information than the direct compare algorithm. An energy resolution of 9.75 MeV can be achieved with the Weighted Sum algorithm at a sampling rate of 40 Msps (mega samples per second) at 1 GeV. The timing performance at a sampling rate of 40 Msps with the Weighted Sum algorithm is better than that at a sampling rate of 20 Msps with both algorithms. The level-0 trigger can be delivered...
ANALYSIS OF PARAMETERIZATION VALUE REDUCTION OF SOFT SETS AND ITS ALGORITHM
Directory of Open Access Journals (Sweden)
Mohammed Adam Taheir Mohammed
2016-02-01
Full Text Available In this paper, the parameterization value reduction of soft sets and its algorithm in decision making are studied and described. It is based on parameterization reduction of soft sets. The purpose of this study is to investigate the inherited disadvantages of parameterization reduction of soft sets and its algorithm. The algorithms presented in this study attempt to reduce the value of least parameters from soft set. Through the analysis, two techniques have been described. Through this study, it is found that parameterization reduction of soft sets and its algorithm has yielded a different and inconsistency in suboptimal result.
Set Theory Correlation Free Algorithm for HRRR Target Tracking
National Research Council Canada - National Science Library
Blasch, Erik
1999-01-01
.... Recently a few fusionists including Mahler 1 and Mori 2 are using a set theory approach for a unified data fusion theory which is a correlation free paradigm 3 This paper uses the set theory approach...
Formal specification level concepts, methods, and algorithms
Soeken, Mathias
2015-01-01
This book introduces a new level of abstraction that closes the gap between the textual specification of embedded systems and the executable model at the Electronic System Level (ESL). Readers will be enabled to operate at this new, Formal Specification Level (FSL), using models which not only allow significant verification tasks in this early stage of the design flow, but also can be extracted semi-automatically from the textual specification in an interactive manner. The authors explain how to use these verification tasks to check conceptual properties, e.g. whether requirements are in conflict, as well as dynamic behavior, in terms of execution traces. • Serves as a single-source reference to a new level of abstraction for embedded systems, known as the Formal Specification Level (FSL); • Provides a variety of use cases which can be adapted to readers’ specific design flows; • Includes a comprehensive illustration of Natural Language Processing (NLP) techniques, along with examples of how to i...
A local level set method based on a finite element method for unstructured meshes
International Nuclear Information System (INIS)
Ngo, Long Cu; Choi, Hyoung Gwon
2016-01-01
A local level set method for unstructured meshes has been implemented by using a finite element method. A least-square weighted residual method was employed for implicit discretization to solve the level set advection equation. By contrast, a direct re-initialization method, which is directly applicable to the local level set method for unstructured meshes, was adopted to re-correct the level set function to become a signed distance function after advection. The proposed algorithm was constructed such that the advection and direct reinitialization steps were conducted only for nodes inside the narrow band around the interface. Therefore, in the advection step, the Gauss–Seidel method was used to update the level set function using a node-by-node solution method. Some benchmark problems were solved by using the present local level set method. Numerical results have shown that the proposed algorithm is accurate and efficient in terms of computational time
Transport and diffusion of material quantities on propagating interfaces via level set methods
Adalsteinsson, D
2003-01-01
We develop theory and numerical algorithms to apply level set methods to problems involving the transport and diffusion of material quantities in a level set framework. Level set methods are computational techniques for tracking moving interfaces; they work by embedding the propagating interface as the zero level set of a higher dimensional function, and then approximate the solution of the resulting initial value partial differential equation using upwind finite difference schemes. The traditional level set method works in the trace space of the evolving interface, and hence disregards any parameterization in the interface description. Consequently, material quantities on the interface which themselves are transported under the interface motion are not easily handled in this framework. We develop model equations and algorithmic techniques to extend the level set method to include these problems. We demonstrate the accuracy of our approach through a series of test examples and convergence studies.
Transport and diffusion of material quantities on propagating interfaces via level set methods
International Nuclear Information System (INIS)
Adalsteinsson, David; Sethian, J.A.
2003-01-01
We develop theory and numerical algorithms to apply level set methods to problems involving the transport and diffusion of material quantities in a level set framework. Level set methods are computational techniques for tracking moving interfaces; they work by embedding the propagating interface as the zero level set of a higher dimensional function, and then approximate the solution of the resulting initial value partial differential equation using upwind finite difference schemes. The traditional level set method works in the trace space of the evolving interface, and hence disregards any parameterization in the interface description. Consequently, material quantities on the interface which themselves are transported under the interface motion are not easily handled in this framework. We develop model equations and algorithmic techniques to extend the level set method to include these problems. We demonstrate the accuracy of our approach through a series of test examples and convergence studies
A local level set method based on a finite element method for unstructured meshes
Energy Technology Data Exchange (ETDEWEB)
Ngo, Long Cu; Choi, Hyoung Gwon [School of Mechanical Engineering, Seoul National University of Science and Technology, Seoul (Korea, Republic of)
2016-12-15
A local level set method for unstructured meshes has been implemented by using a finite element method. A least-square weighted residual method was employed for implicit discretization to solve the level set advection equation. By contrast, a direct re-initialization method, which is directly applicable to the local level set method for unstructured meshes, was adopted to re-correct the level set function to become a signed distance function after advection. The proposed algorithm was constructed such that the advection and direct reinitialization steps were conducted only for nodes inside the narrow band around the interface. Therefore, in the advection step, the Gauss–Seidel method was used to update the level set function using a node-by-node solution method. Some benchmark problems were solved by using the present local level set method. Numerical results have shown that the proposed algorithm is accurate and efficient in terms of computational time.
The Sum-Product Algorithm for Degree-2 Check Nodes and Trapping Sets
Brevik, John O.; O'Sullivan, Michael E.
2014-01-01
The sum-product algorithm for decoding of binary codes is analyzed for bipartite graphs in which the check nodes all have degree $2$. The algorithm simplifies dramatically and may be expressed using linear algebra. Exact results about the convergence of the algorithm are derived and applied to trapping sets.
Kalter, Henry D; Perin, Jamie; Black, Robert E
2016-06-01
Physician assessment historically has been the most common method of analyzing verbal autopsy (VA) data. Recently, the World Health Organization endorsed two automated methods, Tariff 2.0 and InterVA-4, which promise greater objectivity and lower cost. A disadvantage of the Tariff method is that it requires a training data set from a prior validation study, while InterVA relies on clinically specified conditional probabilities. We undertook to validate the hierarchical expert algorithm analysis of VA data, an automated, intuitive, deterministic method that does not require a training data set. Using Population Health Metrics Research Consortium study hospital source data, we compared the primary causes of 1629 neonatal and 1456 1-59 month-old child deaths from VA expert algorithms arranged in a hierarchy to their reference standard causes. The expert algorithms were held constant, while five prior and one new "compromise" neonatal hierarchy, and three former child hierarchies were tested. For each comparison, the reference standard data were resampled 1000 times within the range of cause-specific mortality fractions (CSMF) for one of three approximated community scenarios in the 2013 WHO global causes of death, plus one random mortality cause proportions scenario. We utilized CSMF accuracy to assess overall population-level validity, and the absolute difference between VA and reference standard CSMFs to examine particular causes. Chance-corrected concordance (CCC) and Cohen's kappa were used to evaluate individual-level cause assignment. Overall CSMF accuracy for the best-performing expert algorithm hierarchy was 0.80 (range 0.57-0.96) for neonatal deaths and 0.76 (0.50-0.97) for child deaths. Performance for particular causes of death varied, with fairly flat estimated CSMF over a range of reference values for several causes. Performance at the individual diagnosis level was also less favorable than that for overall CSMF (neonatal: best CCC = 0.23, range 0
Scalable Algorithms for Clustering Large Geospatiotemporal Data Sets on Manycore Architectures
Mills, R. T.; Hoffman, F. M.; Kumar, J.; Sreepathi, S.; Sripathi, V.
2016-12-01
The increasing availability of high-resolution geospatiotemporal data sets from sources such as observatory networks, remote sensing platforms, and computational Earth system models has opened new possibilities for knowledge discovery using data sets fused from disparate sources. Traditional algorithms and computing platforms are impractical for the analysis and synthesis of data sets of this size; however, new algorithmic approaches that can effectively utilize the complex memory hierarchies and the extremely high levels of available parallelism in state-of-the-art high-performance computing platforms can enable such analysis. We describe a massively parallel implementation of accelerated k-means clustering and some optimizations to boost computational intensity and utilization of wide SIMD lanes on state-of-the art multi- and manycore processors, including the second-generation Intel Xeon Phi ("Knights Landing") processor based on the Intel Many Integrated Core (MIC) architecture, which includes several new features, including an on-package high-bandwidth memory. We also analyze the code in the context of a few practical applications to the analysis of climatic and remotely-sensed vegetation phenology data sets, and speculate on some of the new applications that such scalable analysis methods may enable.
Algorithms for Learning Preferences for Sets of Objects
Wagstaff, Kiri L.; desJardins, Marie; Eaton, Eric
2010-01-01
A method is being developed that provides for an artificial-intelligence system to learn a user's preferences for sets of objects and to thereafter automatically select subsets of objects according to those preferences. The method was originally intended to enable automated selection, from among large sets of images acquired by instruments aboard spacecraft, of image subsets considered to be scientifically valuable enough to justify use of limited communication resources for transmission to Earth. The method is also applicable to other sets of objects: examples of sets of objects considered in the development of the method include food menus, radio-station music playlists, and assortments of colored blocks for creating mosaics. The method does not require the user to perform the often-difficult task of quantitatively specifying preferences; instead, the user provides examples of preferred sets of objects. This method goes beyond related prior artificial-intelligence methods for learning which individual items are preferred by the user: this method supports a concept of setbased preferences, which include not only preferences for individual items but also preferences regarding types and degrees of diversity of items in a set. Consideration of diversity in this method involves recognition that members of a set may interact with each other in the sense that when considered together, they may be regarded as being complementary, redundant, or incompatible to various degrees. The effects of such interactions are loosely summarized in the term portfolio effect. The learning method relies on a preference representation language, denoted DD-PREF, to express set-based preferences. In DD-PREF, a preference is represented by a tuple that includes quality (depth) functions to estimate how desired a specific value is, weights for each feature preference, the desired diversity of feature values, and the relative importance of diversity versus depth. The system applies statistical
The algorithmic level is the bridge between computation and brain.
Love, Bradley C
2015-04-01
Every scientist chooses a preferred level of analysis and this choice shapes the research program, even determining what counts as evidence. This contribution revisits Marr's (1982) three levels of analysis (implementation, algorithmic, and computational) and evaluates the prospect of making progress at each individual level. After reviewing limitations of theorizing within a level, two strategies for integration across levels are considered. One is top-down in that it attempts to build a bridge from the computational to algorithmic level. Limitations of this approach include insufficient theoretical constraint at the computation level to provide a foundation for integration, and that people are suboptimal for reasons other than capacity limitations. Instead, an inside-out approach is forwarded in which all three levels of analysis are integrated via the algorithmic level. This approach maximally leverages mutual data constraints at all levels. For example, algorithmic models can be used to interpret brain imaging data, and brain imaging data can be used to select among competing models. Examples of this approach to integration are provided. This merging of levels raises questions about the relevance of Marr's tripartite view. Copyright © 2015 Cognitive Science Society, Inc.
Application of the artificial bee colony algorithm for solving the set covering problem.
Crawford, Broderick; Soto, Ricardo; Cuesta, Rodrigo; Paredes, Fernando
2014-01-01
The set covering problem is a formal model for many practical optimization problems. In the set covering problem the goal is to choose a subset of the columns of minimal cost that covers every row. Here, we present a novel application of the artificial bee colony algorithm to solve the non-unicost set covering problem. The artificial bee colony algorithm is a recent swarm metaheuristic technique based on the intelligent foraging behavior of honey bees. Experimental results show that our artificial bee colony algorithm is competitive in terms of solution quality with other recent metaheuristic approaches for the set covering problem.
Sharifahmadian, Ershad
2006-01-01
The set partitioning in hierarchical trees (SPIHT) algorithm is very effective and computationally simple technique for image and signal compression. Here the author modified the algorithm which provides even better performance than the SPIHT algorithm. The enhanced set partitioning in hierarchical trees (ESPIHT) algorithm has performance faster than the SPIHT algorithm. In addition, the proposed algorithm reduces the number of bits in a bit stream which is stored or transmitted. I applied it to compression of multichannel ECG data. Also, I presented a specific procedure based on the modified algorithm for more efficient compression of multichannel ECG data. This method employed on selected records from the MIT-BIH arrhythmia database. According to experiments, the proposed method attained the significant results regarding compression of multichannel ECG data. Furthermore, in order to compress one signal which is stored for a long time, the proposed multichannel compression method can be utilized efficiently.
Relevant test set using feature selection algorithm for early detection ...
African Journals Online (AJOL)
The objective of feature selection is to find the most relevant features for classification. Thus, the dimensionality of the information will be reduced and may improve classification's accuracy. This paper proposed a minimum set of relevant questions that can be used for early detection of dyslexia. In this research, we ...
A compression algorithm for the combination of PDF sets
Carrazza, Stefano; Latorre, Jose I.; Rojo, Juan; Watt, Graeme
2015-01-01
The current PDF4LHC recommendation to estimate uncertainties due to parton distribution functions (PDFs) in theoretical predictions for LHC processes involves the combination of separate predictions computed using PDF sets from different groups, each of which comprises a relatively large number of
Setting the stage for master's level success
Roberts, Donna
Comprehensive reading, writing, research, and study skills play a critical role in a graduate student's success and ability to contribute to a field of study effectively. The literature indicated a need to support graduate student success in the areas of mentoring, navigation, as well as research and writing. The purpose of this two-phased mixed methods explanatory study was to examine factors that characterize student success at the Master's level in the fields of education, sociology and social work. The study was grounded in a transformational learning framework which focused on three levels of learning: technical knowledge, practical or communicative knowledge, and emancipatory knowledge. The study included two data collection points. Phase one consisted of a Master's Level Success questionnaire that was sent via Qualtrics to graduate level students at three colleges and universities in the Central Valley of California: a California State University campus, a University of California campus, and a private college campus. The results of the chi-square indicated that seven questionnaire items were significant with p values less than .05. Phase two in the data collection included semi-structured interview questions that resulted in three themes emerged using Dedoose software: (1) the need for more language and writing support at the Master's level, (2) the need for mentoring, especially for second-language learners, and (3) utilizing the strong influence of faculty in student success. It is recommended that institutions continually assess and strengthen their programs to meet the full range of learners and to support students to degree completion.
An IDS Alerts Aggregation Algorithm Based on Rough Set Theory
Zhang, Ru; Guo, Tao; Liu, Jianyi
2018-03-01
Within a system in which has been deployed several IDS, a great number of alerts can be triggered by a single security event, making real alerts harder to be found. To deal with redundant alerts, we propose a scheme based on rough set theory. In combination with basic concepts in rough set theory, the importance of attributes in alerts was calculated firstly. With the result of attributes importance, we could compute the similarity of two alerts, which will be compared with a pre-defined threshold to determine whether these two alerts can be aggregated or not. Also, time interval should be taken into consideration. Allowed time interval for different types of alerts is computed individually, since different types of alerts may have different time gap between two alerts. In the end of this paper, we apply proposed scheme on DAPRA98 dataset and the results of experiment show that our scheme can efficiently reduce the redundancy of alerts so that administrators of security system could avoid wasting time on useless alerts.
The Algorithm Theoretical Basis Document for Level 1A Processing
Jester, Peggy L.; Hancock, David W., III
2012-01-01
The first process of the Geoscience Laser Altimeter System (GLAS) Science Algorithm Software converts the Level 0 data into the Level 1A Data Products. The Level 1A Data Products are the time ordered instrument data converted from counts to engineering units. This document defines the equations that convert the raw instrument data into engineering units. Required scale factors, bias values, and coefficients are defined in this document. Additionally, required quality assurance and browse products are defined in this document.
Strong convergence of an extragradient-type algorithm for the multiple-sets split equality problem.
Zhao, Ying; Shi, Luoyi
2017-01-01
This paper introduces a new extragradient-type method to solve the multiple-sets split equality problem (MSSEP). Under some suitable conditions, the strong convergence of an algorithm can be verified in the infinite-dimensional Hilbert spaces. Moreover, several numerical results are given to show the effectiveness of our algorithm.
Surface-to-surface registration using level sets
DEFF Research Database (Denmark)
Hansen, Mads Fogtmann; Erbou, Søren G.; Vester-Christensen, Martin
2007-01-01
This paper presents a general approach for surface-to-surface registration (S2SR) with the Euclidean metric using signed distance maps. In addition, the method is symmetric such that the registration of a shape A to a shape B is identical to the registration of the shape B to the shape A. The S2SR...... problem can be approximated by the image registration (IR) problem of the signed distance maps (SDMs) of the surfaces confined to some narrow band. By shrinking the narrow bands around the zero level sets the solution to the IR problem converges towards the S2SR problem. It is our hypothesis...... that this approach is more robust and less prone to fall into local minima than ordinary surface-to-surface registration. The IR problem is solved using the inverse compositional algorithm. In this paper, a set of 40 pelvic bones of Duroc pigs are registered to each other w.r.t. the Euclidean transformation...
A Fast Logdet Divergence Based Metric Learning Algorithm for Large Data Sets Classification
Directory of Open Access Journals (Sweden)
Jiangyuan Mei
2014-01-01
the basis of classifiers, for example, the k-nearest neighbors classifier. Experiments on benchmark data sets demonstrate that the proposed algorithm compares favorably with the state-of-the-art methods.
A comparative study of image low level feature extraction algorithms
Directory of Open Access Journals (Sweden)
M.M. El-gayar
2013-07-01
Full Text Available Feature extraction and matching is at the base of many computer vision problems, such as object recognition or structure from motion. Current methods for assessing the performance of popular image matching algorithms are presented and rely on costly descriptors for detection and matching. Specifically, the method assesses the type of images under which each of the algorithms reviewed herein perform to its maximum or highest efficiency. The efficiency is measured in terms of the number of matches founds by the algorithm and the number of type I and type II errors encountered when the algorithm is tested against a specific pair of images. Current comparative studies asses the performance of the algorithms based on the results obtained in different criteria such as speed, sensitivity, occlusion, and others. This study addresses the limitations of the existing comparative tools and delivers a generalized criterion to determine beforehand the level of efficiency expected from a matching algorithm given the type of images evaluated. The algorithms and the respective images used within this work are divided into two groups: feature-based and texture-based. And from this broad classification only three of the most widely used algorithms are assessed: color histogram, FAST (Features from Accelerated Segment Test, SIFT (Scale Invariant Feature Transform, PCA-SIFT (Principal Component Analysis-SIFT, F-SIFT (fast-SIFT and SURF (speeded up robust features. The performance of the Fast-SIFT (F-SIFT feature detection methods are compared for scale changes, rotation, blur, illumination changes and affine transformations. All the experiments use repeatability measurement and the number of correct matches for the evaluation measurements. SIFT presents its stability in most situations although its slow. F-SIFT is the fastest one with good performance as the same as SURF, SIFT, PCA-SIFT show its advantages in rotation and illumination changes.
A Robust Level-Set Algorithm for Centerline Extraction
Telea, Alexandru; Vilanova, Anna
2003-01-01
We present a robust method for extracting 3D centerlines from volumetric datasets. We start from a 2D skeletonization method to locate voxels centered with respect to three orthogonal slicing directions. Next, we introduce a new detection criterion to extract the centerline voxels from the above
A Practical Algorithm for Reconstructing Level-1 Phylogenetic Networks
K.T. Huber; L.J.J. van Iersel (Leo); S.M. Kelk (Steven); R. Suchecki
2010-01-01
htmlabstractRecently much attention has been devoted to the construction of phylogenetic networks which generalize phylogenetic trees in order to accommodate complex evolutionary processes. Here we present an efficient, practical algorithm for reconstructing level-1 phylogenetic networks - a type of
A practical algorithm for reconstructing level-1 phylogenetic networks
Huber, K.T.; Iersel, van L.J.J.; Kelk, S.M.; Suchecki, R.
2011-01-01
Recently, much attention has been devoted to the construction of phylogenetic networks which generalize phylogenetic trees in order to accommodate complex evolutionary processes. Here, we present an efficient, practical algorithm for reconstructing level-1 phylogenetic networks-a type of network
Adaptable Value-Set Analysis for Low-Level Code
Brauer, Jörg; Hansen, René Rydhof; Kowalewski, Stefan; Larsen, Kim G.; Olesen, Mads Chr.
2012-01-01
This paper presents a framework for binary code analysis that uses only SAT-based algorithms. Within the framework, incremental SAT solving is used to perform a form of weakly relational value-set analysis in a novel way, connecting the expressiveness of the value sets to computational complexity. Another key feature of our framework is that it translates the semantics of binary code into an intermediate representation. This allows for a straightforward translation of the program semantics in...
A deterministic algorithm for fitting a step function to a weighted point-set
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.
Fast parallel DNA-based algorithms for molecular computation: the set-partition problem.
Chang, Weng-Long
2007-12-01
This paper demonstrates that basic biological operations can be used to solve the set-partition problem. In order to achieve this, we propose three DNA-based algorithms, a signed parallel adder, a signed parallel subtractor and a signed parallel comparator, that formally verify our designed molecular solutions for solving the set-partition problem.
An efficient, scalable, and adaptable framework for solving generic systems of level-set PDEs
Directory of Open Access Journals (Sweden)
Kishore R. Mosaliganti
2013-12-01
Full Text Available In the last decade, level-set methods have been actively developed for applications in image registration, segmentation, tracking, and reconstruction. However, the development of a wide variety of level-set PDEs and their numerical discretization schemes, coupled with hybrid combinations of PDE terms, stopping criteria, and reinitialization strategies, has created a software logistics problem. In the absence of an integrative design, current toolkits support only speciﬁc types of level-set implementations which restrict future algorithm development since extensions require signiﬁcant code duplication and effort. In the new NIH/NLM Insight Toolkit (ITK v4 architecture, we implemented a level-set software design that is ﬂexible to different numerical (continuous, discrete, and sparse and grid representations (point, mesh, and image-based. Given that a generic PDE is a summation of different terms, we used a set of linked containers to which level-set terms can be added or deleted at any point in the evolution process. This container-based approach allows the user to explore and customize terms in the level-set equation at compile-time in a ﬂexible manner. The framework is optimized so that repeated computations of common intensity functions (e.g. gradient and Hessians across multiple terms is eliminated. The framework further enables the evolution of multiple level-sets for multi-object segmentation and processing of large datasets. For doing so, we restrict level-set domains to subsets of the image domain and use multithreading strategies to process groups of subdomains or level-set functions. Users can also select from a variety of reinitialization policies and stopping criteria. Finally, we developed a visualization framework that shows the evolution of a level-set in real-time to help guide algorithm development and parameter optimization. We demonstrate the power of our new framework using confocal microscopy images of cells in a
Directory of Open Access Journals (Sweden)
Adacher Ludovica
2017-12-01
Full Text Available In this paper we extend a stochastic discrete optimization algorithm so as to tackle the signal setting problem. Signalized junctions represent critical points of an urban transportation network, and the efficiency of their traffic signal setting influences the overall network performance. Since road congestion usually takes place at or close to junction areas, an improvement in signal settings contributes to improving travel times, drivers’ comfort, fuel consumption efficiency, pollution and safety. In a traffic network, the signal control strategy affects the travel time on the roads and influences drivers’ route choice behavior. The paper presents an algorithm for signal setting optimization of signalized junctions in a congested road network. The objective function used in this work is a weighted sum of delays caused by the signalized intersections. We propose an iterative procedure to solve the problem by alternately updating signal settings based on fixed flows and traffic assignment based on fixed signal settings. To show the robustness of our method, we consider two different assignment methods: one based on user equilibrium assignment, well established in the literature as well as in practice, and the other based on a platoon simulation model with vehicular flow propagation and spill-back. Our optimization algorithm is also compared with others well known in the literature for this problem. The surrogate method (SM, particle swarm optimization (PSO and the genetic algorithm (GA are compared for a combined problem of global optimization of signal settings and traffic assignment (GOSSTA. Numerical experiments on a real test network are reported.
On the multi-level solution algorithm for Markov chains
Energy Technology Data Exchange (ETDEWEB)
Horton, G. [Univ. of Erlangen, Nuernberg (Germany)
1996-12-31
We discuss the recently introduced multi-level algorithm for the steady-state solution of Markov chains. The method is based on the aggregation principle, which is well established in the literature. Recursive application of the aggregation yields a multi-level method which has been shown experimentally to give results significantly faster than the methods currently in use. The algorithm can be reformulated as an algebraic multigrid scheme of Galerkin-full approximation type. The uniqueness of the scheme stems from its solution-dependent prolongation operator which permits significant computational savings in the evaluation of certain terms. This paper describes the modeling of computer systems to derive information on performance, measured typically as job throughput or component utilization, and availability, defined as the proportion of time a system is able to perform a certain function in the presence of component failures and possibly also repairs.
Upper-Lower Bounds Candidate Sets Searching Algorithm for Bayesian Network Structure Learning
Directory of Open Access Journals (Sweden)
Guangyi Liu
2014-01-01
Full Text Available Bayesian network is an important theoretical model in artificial intelligence field and also a powerful tool for processing uncertainty issues. Considering the slow convergence speed of current Bayesian network structure learning algorithms, a fast hybrid learning method is proposed in this paper. We start with further analysis of information provided by low-order conditional independence testing, and then two methods are given for constructing graph model of network, which is theoretically proved to be upper and lower bounds of the structure space of target network, so that candidate sets are given as a result; after that a search and scoring algorithm is operated based on the candidate sets to find the final structure of the network. Simulation results show that the algorithm proposed in this paper is more efficient than similar algorithms with the same learning precision.
Applications and Benefits for Big Data Sets Using Tree Distances and The T-SNE Algorithm
2016-03-01
BENEFITS FOR BIG DATA SETS USING TREE DISTANCES AND THE T-SNE ALGORITHM by Suyoung Lee March 2016 Thesis Advisor: Samuel E. Buttrey...REPORT TYPE AND DATES COVERED Master’s thesis 4. TITLE AND SUBTITLE APPLICATIONS AND BENEFITS FOR BIG DATA SETS USING TREE DISTANCES AND THE T-SNE...public release; distribution is unlimited 12b. DISTRIBUTION CODE 13. ABSTRACT (maximum 200 words ) Modern data sets often consist of unstructured data
Generalization of some hidden subgroup algorithms for input sets of arbitrary size
Poslu, Damla; Say, A. C. Cem
2006-05-01
We consider the problem of generalizing some quantum algorithms so that they will work on input domains whose cardinalities are not necessarily powers of two. When analyzing the algorithms we assume that generating superpositions of arbitrary subsets of basis states whose cardinalities are not necessarily powers of two perfectly is possible. We have taken Ballhysa's model as a template and have extended it to Chi, Kim and Lee's generalizations of the Deutsch-Jozsa algorithm and to Simon's algorithm. With perfectly equal superpositions of input sets of arbitrary size, Chi, Kim and Lee's generalized Deutsch-Jozsa algorithms, both for evenly-distributed and evenly-balanced functions, worked with one-sided error property. For Simon's algorithm the success probability of the generalized algorithm is the same as that of the original for input sets of arbitrary cardinalities with equiprobable superpositions, since the property that the measured strings are all those which have dot product zero with the string we search, for the case where the function is 2-to-1, is not lost.
Pattern-set generation algorithm for the one-dimensional multiple stock sizes cutting stock problem
Cui, Yaodong; Cui, Yi-Ping; Zhao, Zhigang
2015-09-01
A pattern-set generation algorithm (PSG) for the one-dimensional multiple stock sizes cutting stock problem (1DMSSCSP) is presented. The solution process contains two stages. In the first stage, the PSG solves the residual problems repeatedly to generate the patterns in the pattern set, where each residual problem is solved by the column-generation approach, and each pattern is generated by solving a single large object placement problem. In the second stage, the integer linear programming model of the 1DMSSCSP is solved using a commercial solver, where only the patterns in the pattern set are considered. The computational results of benchmark instances indicate that the PSG outperforms existing heuristic algorithms and rivals the exact algorithm in solution quality.
A parametric level-set method for partially discrete tomography
A. Kadu (Ajinkya); T. van Leeuwen (Tristan); K.J. Batenburg (Joost)
2017-01-01
textabstractThis paper introduces a parametric level-set method for tomographic reconstruction of partially discrete images. Such images consist of a continuously varying background and an anomaly with a constant (known) grey-value. We express the geometry of the anomaly using a level-set function,
Novel gene sets improve set-level classification of prokaryotic gene expression data.
Holec, Matěj; Kuželka, Ondřej; Železný, Filip
2015-10-28
Set-level classification of gene expression data has received significant attention recently. In this setting, high-dimensional vectors of features corresponding to genes are converted into lower-dimensional vectors of features corresponding to biologically interpretable gene sets. The dimensionality reduction brings the promise of a decreased risk of overfitting, potentially resulting in improved accuracy of the learned classifiers. However, recent empirical research has not confirmed this expectation. Here we hypothesize that the reported unfavorable classification results in the set-level framework were due to the adoption of unsuitable gene sets defined typically on the basis of the Gene ontology and the KEGG database of metabolic networks. We explore an alternative approach to defining gene sets, based on regulatory interactions, which we expect to collect genes with more correlated expression. We hypothesize that such more correlated gene sets will enable to learn more accurate classifiers. We define two families of gene sets using information on regulatory interactions, and evaluate them on phenotype-classification tasks using public prokaryotic gene expression data sets. From each of the two gene-set families, we first select the best-performing subtype. The two selected subtypes are then evaluated on independent (testing) data sets against state-of-the-art gene sets and against the conventional gene-level approach. The novel gene sets are indeed more correlated than the conventional ones, and lead to significantly more accurate classifiers. The novel gene sets are indeed more correlated than the conventional ones, and lead to significantly more accurate classifiers. Novel gene sets defined on the basis of regulatory interactions improve set-level classification of gene expression data. The experimental scripts and other material needed to reproduce the experiments are available at http://ida.felk.cvut.cz/novelgenesets.tar.gz.
Verhoye, E; Vandecandelaere, P; De Beenhouwer, H; Coppens, G; Cartuyvels, R; Van den Abeele, A; Frans, J; Laffut, W
2015-10-01
Despite thorough analyses of the analytical performance of Clostridium difficile tests and test algorithms, the financial impact at hospital level has not been well described. Such a model should take institution-specific variables into account, such as incidence, request behaviour and infection control policies. To calculate the total hospital costs of different test algorithms, accounting for days on which infected patients with toxigenic strains were not isolated and therefore posed an infectious risk for new/secondary nosocomial infections. A mathematical algorithm was developed to gather the above parameters using data from seven Flemish hospital laboratories (Bilulu Microbiology Study Group) (number of tests, local prevalence and hospital hygiene measures). Measures of sensitivity and specificity for the evaluated tests were taken from the literature. List prices and costs of assays were provided by the manufacturer or the institutions. The calculated cost included reagent costs, personnel costs and the financial burden following due and undue isolations and antibiotic therapies. Five different test algorithms were compared. A dynamic calculation model was constructed to evaluate the cost:benefit ratio of each algorithm for a set of institution- and time-dependent inputted variables (prevalence, cost fluctuations and test performances), making it possible to choose the most advantageous algorithm for its setting. A two-step test algorithm with concomitant glutamate dehydrogenase and toxin testing, followed by a rapid molecular assay was found to be the most cost-effective algorithm. This enabled resolution of almost all cases on the day of arrival, minimizing the number of unnecessary or missing isolations. Copyright © 2015 The Healthcare Infection Society. Published by Elsevier Ltd. All rights reserved.
Lin, Geng; Guan, Jian; Feng, Huibin
2018-06-01
The positive influence dominating set problem is a variant of the minimum dominating set problem, and has lots of applications in social networks. It is NP-hard, and receives more and more attention. Various methods have been proposed to solve the positive influence dominating set problem. However, most of the existing work focused on greedy algorithms, and the solution quality needs to be improved. In this paper, we formulate the minimum positive influence dominating set problem as an integer linear programming (ILP), and propose an ILP based memetic algorithm (ILPMA) for solving the problem. The ILPMA integrates a greedy randomized adaptive construction procedure, a crossover operator, a repair operator, and a tabu search procedure. The performance of ILPMA is validated on nine real-world social networks with nodes up to 36,692. The results show that ILPMA significantly improves the solution quality, and is robust.
White, Thomas J; Redner, Ryan; Skelly, Joan M; Higgins, Stephen T
2015-09-01
To examine (1) whether use of a recommended algorithm (Johnson and Bickel, 2008) improves upon conventional statistical model fit (R(2)) for identifying nonsystematic response sets in delay discounting (DD) data, (2) whether removing such data meaningfully effects research outcomes, and (3) to identify participant characteristics associated with nonsystematic response sets. Discounting of hypothetical monetary rewards was assessed among 349 pregnant women (231 smokers and 118 recent quitters) via a computerized task comparing $1000 at seven future time points with smaller values available immediately. Nonsystematic response sets were identified using the algorithm and conventional statistical model fit (R(2)). The association between DD and quitting was analyzed with and without nonsystematic response sets to examine whether the inclusion or exclusion impacts this relationship. Logistic regression was used to examine whether participant sociodemographics were associated with nonsystematic response sets. The algorithm excluded fewer cases than the R(2) method (14% vs. 16%), and was not correlated with logk as is R(2). The relationship between logk and the clinical outcome (spontaneous quitting) was unaffected by exclusion methods; however, other variables in the model were affected. Lower educational attainment and younger age were associated with nonsystematic response sets. The algorithm eliminated data that were inconsistent with the nature of discounting and retained data that were orderly. Neither method impacted the smoking/DD relationship in this data set. Nonsystematic response sets are more likely among younger and less educated participants, who may need extra training or support in DD studies. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
A deterministic algorithm for fitting a step function to a weighted point-set
Fournier, Hervé
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
Directory of Open Access Journals (Sweden)
Yu Zhou
2017-01-01
Full Text Available The train-set circulation plan problem (TCPP belongs to the rolling stock scheduling (RSS problem and is similar to the aircraft routing problem (ARP in airline operations and the vehicle routing problem (VRP in the logistics field. However, TCPP involves additional complexity due to the maintenance constraint of train-sets: train-sets must conduct maintenance tasks after running for a certain time and distance. The TCPP is nondeterministic polynomial hard (NP-hard. There is no available algorithm that can obtain the optimal global solution, and many factors such as the utilization mode and the maintenance mode impact the solution of the TCPP. This paper proposes a train-set circulation optimization model to minimize the total connection time and maintenance costs and describes the design of an efficient multiple-population genetic algorithm (MPGA to solve this model. A realistic high-speed railway (HSR case is selected to verify our model and algorithm, and, then, a comparison of different algorithms is carried out. Furthermore, a new maintenance mode is proposed, and related implementation requirements are discussed.
Volume Sculpting Using the Level-Set Method
DEFF Research Database (Denmark)
Bærentzen, Jakob Andreas; Christensen, Niels Jørgen
2002-01-01
In this paper, we propose the use of the Level--Set Method as the underlying technology of a volume sculpting system. The main motivation is that this leads to a very generic technique for deformation of volumetric solids. In addition, our method preserves a distance field volume representation....... A scaling window is used to adapt the Level--Set Method to local deformations and to allow the user to control the intensity of the tool. Level--Set based tools have been implemented in an interactive sculpting system, and we show sculptures created using the system....
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Eltahir A.G. Khalil
2013-06-01
Full Text Available Background: Tuberculosis is a major health problem in developing countries. The distinction between tuberculous lymphadenitis, non-specific lymphadenitis and malignant lymph node enlargement has to be made at primary health care levels using easy, simple and cheap methods. Objective: To develop a reliable clinical algorithm for primary care settings to triage cases ofnon-specific, tuberculous and malignant lymphadenopathies. Methods: Calculation of the odd ratios (OR of the chosen predictor variables was carried out using logistic regression. The numerical score values of the predictor variables were weighed against their respective OR. The performance of the score was evaluated by the ROC (ReceiverOperator Characteristic curve. Results: Four predictor variables; Mantoux reading, erythrocytes sedimentation rate (ESR,nocturnal fever and discharging sinuses correlated significantly with TB diagnosis and were included in the reduced model to establish score A. For score B, the reduced model included Mantoux reading, ESR, lymph-node size and lymph-node number as predictor variables for malignant lymph nodes. Score A ranged 0 to 12 and a cut-off point of 6 gave a best sensitivity and specificity of 91% and 90% respectively, whilst score B ranged -3 to 8 and a cut-off point of3 gave a best sensitivity and specificity of 83% and 76% respectively. The calculated area underthe ROC curve was 0.964 (95% CI, 0.949 – 0.980 and -0.856 (95% CI, 0.787 ‑ 0.925 for scores Aand B respectively, indicating good performance. Conclusion: The developed algorithm can efficiently triage cases with tuberculous andmalignant lymphadenopathies for treatment or referral to specialised centres for furtherwork-up.
González-Recio, O; Jiménez-Montero, J A; Alenda, R
2013-01-01
In the next few years, with the advent of high-density single nucleotide polymorphism (SNP) arrays and genome sequencing, genomic evaluation methods will need to deal with a large number of genetic variants and an increasing sample size. The boosting algorithm is a machine-learning technique that may alleviate the drawbacks of dealing with such large data sets. This algorithm combines different predictors in a sequential manner with some shrinkage on them; each predictor is applied consecutively to the residuals from the committee formed by the previous ones to form a final prediction based on a subset of covariates. Here, a detailed description is provided and examples using a toy data set are included. A modification of the algorithm called "random boosting" was proposed to increase predictive ability and decrease computation time of genome-assisted evaluation in large data sets. Random boosting uses a random selection of markers to add a subsequent weak learner to the predictive model. These modifications were applied to a real data set composed of 1,797 bulls genotyped for 39,714 SNP. Deregressed proofs of 4 yield traits and 1 type trait from January 2009 routine evaluations were used as dependent variables. A 2-fold cross-validation scenario was implemented. Sires born before 2005 were used as a training sample (1,576 and 1,562 for production and type traits, respectively), whereas younger sires were used as a testing sample to evaluate predictive ability of the algorithm on yet-to-be-observed phenotypes. Comparison with the original algorithm was provided. The predictive ability of the algorithm was measured as Pearson correlations between observed and predicted responses. Further, estimated bias was computed as the average difference between observed and predicted phenotypes. The results showed that the modification of the original boosting algorithm could be run in 1% of the time used with the original algorithm and with negligible differences in accuracy
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Татьяна Борисовна Шатовская
2015-03-01
Full Text Available In this work results of modified Chameleon algorithm are discussed. Hierarchical multilevel algorithms consist of several stages: building the graph, coarsening, partitioning, recovering. Exploring of clustering quality for different data sets with different combinations of algorithms on different stages of the algorithm is the main aim of the article. And also aim is improving the construction phase through the optimization algorithm of choice k in the building the graph k-nearest neighbors
A level set method for multiple sclerosis lesion segmentation.
Zhao, Yue; Guo, Shuxu; Luo, Min; Shi, Xue; Bilello, Michel; Zhang, Shaoxiang; Li, Chunming
2018-06-01
In this paper, we present a level set method for multiple sclerosis (MS) lesion segmentation from FLAIR images in the presence of intensity inhomogeneities. We use a three-phase level set formulation of segmentation and bias field estimation to segment MS lesions and normal tissue region (including GM and WM) and CSF and the background from FLAIR images. To save computational load, we derive a two-phase formulation from the original multi-phase level set formulation to segment the MS lesions and normal tissue regions. The derived method inherits the desirable ability to precisely locate object boundaries of the original level set method, which simultaneously performs segmentation and estimation of the bias field to deal with intensity inhomogeneity. Experimental results demonstrate the advantages of our method over other state-of-the-art methods in terms of segmentation accuracy. Copyright © 2017 Elsevier Inc. All rights reserved.
Some numerical studies of interface advection properties of level set ...
Indian Academy of Sciences (India)
explicit computational elements moving through an Eulerian grid. ... location. The interface is implicitly defined (captured) as the location of the discontinuity in the ... This level set function is advected with the background flow field and thus ...
Efficient frequent pattern mining algorithm based on node sets in cloud computing environment
Billa, V. N. Vinay Kumar; Lakshmanna, K.; Rajesh, K.; Reddy, M. Praveen Kumar; Nagaraja, G.; Sudheer, K.
2017-11-01
The ultimate goal of Data Mining is to determine the hidden information which is useful in making decisions using the large databases collected by an organization. This Data Mining involves many tasks that are to be performed during the process. Mining frequent itemsets is the one of the most important tasks in case of transactional databases. These transactional databases contain the data in very large scale where the mining of these databases involves the consumption of physical memory and time in proportion to the size of the database. A frequent pattern mining algorithm is said to be efficient only if it consumes less memory and time to mine the frequent itemsets from the given large database. Having these points in mind in this thesis we proposed a system which mines frequent itemsets in an optimized way in terms of memory and time by using cloud computing as an important factor to make the process parallel and the application is provided as a service. A complete framework which uses a proven efficient algorithm called FIN algorithm. FIN algorithm works on Nodesets and POC (pre-order coding) tree. In order to evaluate the performance of the system we conduct the experiments to compare the efficiency of the same algorithm applied in a standalone manner and in cloud computing environment on a real time data set which is traffic accidents data set. The results show that the memory consumption and execution time taken for the process in the proposed system is much lesser than those of standalone system.
Miller, D; Lippert, C; Vollmer, F; Bozinov, O; Benes, L; Schulte, D M; Sure, U
2012-09-01
Freehand three-dimensional ultrasound imaging (3D-US) is increasingly used in image-guided surgery. During image acquisition, a set of B-scans is acquired that is distributed in a non-parallel manner over the area of interest. Reconstructing these images into a regular array allows 3D visualization. However, the reconstruction process may introduce artefacts and may therefore reduce image quality. The aim of the study is to compare different algorithms with respect to image quality and diagnostic value for image guidance in neurosurgery. 3D-US data sets were acquired during surgery of various intracerebral lesions using an integrated ultrasound-navigation device. They were stored for post-hoc evaluation. Five different reconstruction algorithms, a standard multiplanar reconstruction with interpolation (MPR), a pixel nearest neighbour method (PNN), a voxel nearest neighbour method (VNN) and two voxel based distance-weighted algorithms (VNN2 and DW) were tested with respect to image quality and artefact formation. The capability of the algorithm to fill gaps within the sample volume was investigated and a clinical evaluation with respect to the diagnostic value of the reconstructed images was performed. MPR was significantly worse than the other algorithms in filling gaps. In an image subtraction test, VNN2 and DW reliably reconstructed images even if large amounts of data were missing. However, the quality of the reconstruction improved, if data acquisition was performed in a structured manner. When evaluating the diagnostic value of reconstructed axial, sagittal and coronal views, VNN2 and DW were judged to be significantly better than MPR and VNN. VNN2 and DW could be identified as robust algorithms that generate reconstructed US images with a high diagnostic value. These algorithms improve the utility and reliability of 3D-US imaging during intraoperative navigation. Copyright © 2012 John Wiley & Sons, Ltd.
Chaotic logic gate: A new approach in set and design by genetic algorithm
International Nuclear Information System (INIS)
Beyki, Mahmood; Yaghoobi, Mahdi
2015-01-01
How to reconfigure a logic gate is an attractive subject for different applications. Chaotic systems can yield a wide variety of patterns and here we use this feature to produce a logic gate. This feature forms the basis for designing a dynamical computing device that can be rapidly reconfigured to become any wanted logical operator. This logic gate that can reconfigure to any logical operator when placed in its chaotic state is called chaotic logic gate. The reconfiguration realize by setting the parameter values of chaotic logic gate. In this paper we present mechanisms about how to produce a logic gate based on the logistic map in its chaotic state and genetic algorithm is used to set the parameter values. We use three well-known selection methods used in genetic algorithm: tournament selection, Roulette wheel selection and random selection. The results show the tournament selection method is the best method for set the parameter values. Further, genetic algorithm is a powerful tool to set the parameter values of chaotic logic gate
Exploring the level sets of quantum control landscapes
International Nuclear Information System (INIS)
Rothman, Adam; Ho, Tak-San; Rabitz, Herschel
2006-01-01
A quantum control landscape is defined by the value of a physical observable as a functional of the time-dependent control field E(t) for a given quantum-mechanical system. Level sets through this landscape are prescribed by a particular value of the target observable at the final dynamical time T, regardless of the intervening dynamics. We present a technique for exploring a landscape level set, where a scalar variable s is introduced to characterize trajectories along these level sets. The control fields E(s,t) accomplishing this exploration (i.e., that produce the same value of the target observable for a given system) are determined by solving a differential equation over s in conjunction with the time-dependent Schroedinger equation. There is full freedom to traverse a level set, and a particular trajectory is realized by making an a priori choice for a continuous function f(s,t) that appears in the differential equation for the control field. The continuous function f(s,t) can assume an arbitrary form, and thus a level set generally contains a family of controls, where each control takes the quantum system to the same final target value, but produces a distinct control mechanism. In addition, although the observable value remains invariant over the level set, other dynamical properties (e.g., the degree of robustness to control noise) are not specifically preserved and can vary greatly. Examples are presented to illustrate the continuous nature of level-set controls and their associated induced dynamical features, including continuously morphing mechanisms for population control in model quantum systems
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Wen Chen
2011-08-01
Full Text Available A negative selection algorithm based on the hierarchical clustering of self set HC-RNSA is introduced in this paper. Several strategies are applied to improve the algorithm performance. First, the self data set is replaced by the self cluster centers to compare with the detector candidates in each cluster level. As the number of self clusters is much less than the self set size, the detector generation efficiency is improved. Second, during the detector generation process, the detector candidates are restricted to the lower coverage space to reduce detector redundancy. In the article, the problem that the distances between antigens coverage to a constant value in the high dimensional space is analyzed, accordingly the Principle Component Analysis (PCA method is used to reduce the data dimension, and the fractional distance function is employed to enhance the distinctiveness between the self and non-self antigens. The detector generation procedure is terminated when the expected non-self coverage is reached. The theory analysis and experimental results demonstrate that the detection rate of HC-RNSA is higher than that of the traditional negative selection algorithms while the false alarm rate and time cost are reduced.
Application of Fuzzy Sets for the Improvement of Routing Optimization Heuristic Algorithms
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Mattas Konstantinos
2016-12-01
Full Text Available The determination of the optimal circular path has become widely known for its difficulty in producing a solution and for the numerous applications in the scope of organization and management of passenger and freight transport. It is a mathematical combinatorial optimization problem for which several deterministic and heuristic models have been developed in recent years, applicable to route organization issues, passenger and freight transport, storage and distribution of goods, waste collection, supply and control of terminals, as well as human resource management. Scope of the present paper is the development, with the use of fuzzy sets, of a practical, comprehensible and speedy heuristic algorithm for the improvement of the ability of the classical deterministic algorithms to identify optimum, symmetrical or non-symmetrical, circular route. The proposed fuzzy heuristic algorithm is compared to the corresponding deterministic ones, with regard to the deviation of the proposed solution from the best known solution and the complexity of the calculations needed to obtain this solution. It is shown that the use of fuzzy sets reduced up to 35% the deviation of the solution identified by the classical deterministic algorithms from the best known solution.
An algorithm for computing the hull of the solution set of interval linear equations
Czech Academy of Sciences Publication Activity Database
Rohn, Jiří
2011-01-01
Roč. 435, č. 2 (2011), s. 193-201 ISSN 0024-3795 R&D Projects: GA ČR GA201/09/1957; GA ČR GC201/08/J020 Institutional research plan: CEZ:AV0Z10300504 Keywords : interval linear equations * solution set * interval hull * algorithm * absolute value inequality Subject RIV: BA - General Mathematics Impact factor: 0.974, year: 2011
Level-Set Topology Optimization with Aeroelastic Constraints
Dunning, Peter D.; Stanford, Bret K.; Kim, H. Alicia
2015-01-01
Level-set topology optimization is used to design a wing considering skin buckling under static aeroelastic trim loading, as well as dynamic aeroelastic stability (flutter). The level-set function is defined over the entire 3D volume of a transport aircraft wing box. Therefore, the approach is not limited by any predefined structure and can explore novel configurations. The Sequential Linear Programming (SLP) level-set method is used to solve the constrained optimization problems. The proposed method is demonstrated using three problems with mass, linear buckling and flutter objective and/or constraints. A constraint aggregation method is used to handle multiple buckling constraints in the wing skins. A continuous flutter constraint formulation is used to handle difficulties arising from discontinuities in the design space caused by a switching of the critical flutter mode.
Level Set Structure of an Integrable Cellular Automaton
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Taichiro Takagi
2010-03-01
Full Text Available Based on a group theoretical setting a sort of discrete dynamical system is constructed and applied to a combinatorial dynamical system defined on the set of certain Bethe ansatz related objects known as the rigged configurations. This system is then used to study a one-dimensional periodic cellular automaton related to discrete Toda lattice. It is shown for the first time that the level set of this cellular automaton is decomposed into connected components and every such component is a torus.
Zhang, Yuli; Han, Jun; Weng, Xinqian; He, Zhongzhu; Zeng, Xiaoyang
This paper presents an Application Specific Instruction-set Processor (ASIP) for the SHA-3 BLAKE algorithm family by instruction set extensions (ISE) from an RISC (reduced instruction set computer) processor. With a design space exploration for this ASIP to increase the performance and reduce the area cost, we accomplish an efficient hardware and software implementation of BLAKE algorithm. The special instructions and their well-matched hardware function unit improve the calculation of the key section of the algorithm, namely G-functions. Also, relaxing the time constraint of the special function unit can decrease its hardware cost, while keeping the high data throughput of the processor. Evaluation results reveal the ASIP achieves 335Mbps and 176Mbps for BLAKE-256 and BLAKE-512. The extra area cost is only 8.06k equivalent gates. The proposed ASIP outperforms several software approaches on various platforms in cycle per byte. In fact, both high throughput and low hardware cost achieved by this programmable processor are comparable to that of ASIC implementations.
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Renato RIZZO
2012-08-01
Full Text Available This paper deals with Permanent Magnet Brushless Motors. In particular is proposed a new set of control algorithm expressions that is realized taking into account resistive parameters of the motor, differently from simplified models of this type of motors where these parameters are usually neglected. The control is set up and an analysis of the performance is reported in the paper, where the validation of the new expressions is done with reference to a motor prototype particularly compact because is foreseen for application on tram propulsion drives. The results are evidenced in the last part of the paper.
Identifying elementary iterated systems through algorithmic inference: The Cantor set example
Energy Technology Data Exchange (ETDEWEB)
Apolloni, Bruno [Dipartimento di Scienze dell' Informazione, Universita degli Studi di Milano, Via Comelico 39/41, 20135 Milan (Italy)]. E-mail: apolloni@dsi.unimi.it; Bassis, Simone [Dipartimento di Scienze dell' Informazione, Universita degli Studi di Milano, Via Comelico 39/41, 20135 Milan (Italy)]. E-mail: bassis@dsi.unimi.it
2006-10-15
We come back to the old problem of fractal identification within the new framework of algorithmic Inference. The key points are: (i) to identify sufficient statistics to be put in connection with the unknown values of the fractal parameters, and (ii) to manage the timing of the iterated process through spatial statistics. We fill these tasks successfully with the Cantor sets. We are able to compute confidence intervals for both the scaling parameter {theta} and the iteration number n at which we are observing a set. We both check numerically the coverage of these intervals and delineate a general strategy for affording more complex iterated systems.
Matsen, Frederick A
2010-06-01
This article introduces constNJ (constrained neighbor-joining), an algorithm for phylogenetic reconstruction of sets of trees with constrained pairwise rooted subtree-prune-regraft (rSPR) distance. We are motivated by the problem of constructing sets of trees that must fit into a recombination, hybridization, or similar network. Rather than first finding a set of trees that are optimal according to a phylogenetic criterion (e.g., likelihood or parsimony) and then attempting to fit them into a network, constNJ estimates the trees while enforcing specified rSPR distance constraints. The primary input for constNJ is a collection of distance matrices derived from sequence blocks which are assumed to have evolved in a tree-like manner, such as blocks of an alignment which do not contain any recombination breakpoints. The other input is a set of rSPR constraint inequalities for any set of pairs of trees. constNJ is consistent and a strict generalization of the neighbor-joining algorithm; it uses the new notion of maximum agreement partitions (MAPs) to assure that the resulting trees satisfy the given rSPR distance constraints.
A Binary Cat Swarm Optimization Algorithm for the Non-Unicost Set Covering Problem
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Broderick Crawford
2015-01-01
Full Text Available The Set Covering Problem consists in finding a subset of columns in a zero-one matrix such that they cover all the rows of the matrix at a minimum cost. To solve the Set Covering Problem we use a metaheuristic called Binary Cat Swarm Optimization. This metaheuristic is a recent swarm metaheuristic technique based on the cat behavior. Domestic cats show the ability to hunt and are curious about moving objects. Based on this, the cats have two modes of behavior: seeking mode and tracing mode. We are the first ones to use this metaheuristic to solve this problem; our algorithm solves a set of 65 Set Covering Problem instances from OR-Library.
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Shen-yan Chen
2015-01-01
Full Text Available This paper presents an Improved Genetic Algorithm with Two-Level Approximation (IGATA to minimize truss weight by simultaneously optimizing size, shape, and topology variables. On the basis of a previously presented truss sizing/topology optimization method based on two-level approximation and genetic algorithm (GA, a new method for adding shape variables is presented, in which the nodal positions are corresponding to a set of coordinate lists. A uniform optimization model including size/shape/topology variables is established. First, a first-level approximate problem is constructed to transform the original implicit problem to an explicit problem. To solve this explicit problem which involves size/shape/topology variables, GA is used to optimize individuals which include discrete topology variables and shape variables. When calculating the fitness value of each member in the current generation, a second-level approximation method is used to optimize the continuous size variables. With the introduction of shape variables, the original optimization algorithm was improved in individual coding strategy as well as GA execution techniques. Meanwhile, the update strategy of the first-level approximation problem was also improved. The results of numerical examples show that the proposed method is effective in dealing with the three kinds of design variables simultaneously, and the required computational cost for structural analysis is quite small.
A lossless one-pass sorting algorithm for symmetric three-dimensional gamma-ray data sets
International Nuclear Information System (INIS)
Brinkman, M.J.; Manatt, D.R.; Becker, J.A.; Henry, E.A.
1992-01-01
An algorithm for three-dimensional sorting and storing of the large data sets expected from the next generation of large gamma-ray detector arrays (i.e., EUROGAM, GAMMASPHERE) is presented. The algorithm allows the storage of realistic data sets on standard mass storage media. A discussion of an efficient implementation of the algorithm is provided with a proposed technique for exploiting its inherently parallel nature. (author). 5 refs., 2 figs
A lossless one-pass sorting algorithm for symmetric three-dimensional gamma-ray data sets
Energy Technology Data Exchange (ETDEWEB)
Brinkman, M J; Manatt, D R; Becker, J A; Henry, E A [Lawrence Livermore National Lab., CA (United States)
1992-08-01
An algorithm for three-dimensional sorting and storing of the large data sets expected from the next generation of large gamma-ray detector arrays (i.e., EUROGAM, GAMMASPHERE) is presented. The algorithm allows the storage of realistic data sets on standard mass storage media. A discussion of an efficient implementation of the algorithm is provided with a proposed technique for exploiting its inherently parallel nature. (author). 5 refs., 2 figs.
A deep level set method for image segmentation
Tang, Min; Valipour, Sepehr; Zhang, Zichen Vincent; Cobzas, Dana; MartinJagersand
2017-01-01
This paper proposes a novel image segmentation approachthat integrates fully convolutional networks (FCNs) with a level setmodel. Compared with a FCN, the integrated method can incorporatesmoothing and prior information to achieve an accurate segmentation.Furthermore, different than using the level set model as a post-processingtool, we integrate it into the training phase to fine-tune the FCN. Thisallows the use of unlabeled data during training in a semi-supervisedsetting. Using two types o...
Solution Algorithm for a New Bi-Level Discrete Network Design Problem
Directory of Open Access Journals (Sweden)
Qun Chen
2013-12-01
Full Text Available A new discrete network design problem (DNDP was pro-posed in this paper, where the variables can be a series of integers rather than just 0-1. The new DNDP can determine both capacity improvement grades of reconstruction roads and locations and capacity grades of newly added roads, and thus complies with the practical projects where road capacity can only be some discrete levels corresponding to the number of lanes of roads. This paper designed a solution algorithm combining branch-and-bound with Hooke-Jeeves algorithm, where feasible integer solutions are recorded in searching the process of Hooke-Jeeves algorithm, lend -ing itself to determine the upper bound of the upper-level problem. The thresholds for branch cutting and ending were set for earlier convergence. Numerical examples are given to demonstrate the efficiency of the proposed algorithm.
Directory of Open Access Journals (Sweden)
A. P. Karpenko
2016-01-01
Full Text Available We consider a class of algorithms for multi-objective optimization - Pareto-approximation algorithms, which suppose a preliminary building of finite-dimensional approximation of a Pareto set, thereby also a Pareto front of the problem. The article gives an overview of population and non-population algorithms of the Pareto-approximation, identifies their strengths and weaknesses, and presents a canonical algorithm "predator-prey", showing its shortcomings. We offer a number of modifications of the canonical algorithm "predator-prey" with the aim to overcome the drawbacks of this algorithm, present the results of a broad study of the efficiency of these modifications of the algorithm. The peculiarity of the study is the use of the quality indicators of the Pareto-approximation, which previous publications have not used. In addition, we present the results of the meta-optimization of the modified algorithm, i.e. determining the optimal values of some free parameters of the algorithm. The study of efficiency of the modified algorithm "predator-prey" has shown that the proposed modifications allow us to improve the following indicators of the basic algorithm: cardinality of a set of the archive solutions, uniformity of archive solutions, and computation time. By and large, the research results have shown that the modified and meta-optimized algorithm enables achieving exactly the same approximation as the basic algorithm, but with the number of preys being one order less. Computational costs are proportionally reduced.
A Level Set Discontinuous Galerkin Method for Free Surface Flows
DEFF Research Database (Denmark)
Grooss, Jesper; Hesthaven, Jan
2006-01-01
We present a discontinuous Galerkin method on a fully unstructured grid for the modeling of unsteady incompressible fluid flows with free surfaces. The surface is modeled by embedding and represented by a levelset. We discuss the discretization of the flow equations and the level set equation...
Level Sets and Voronoi based Feature Extraction from any Imagery
DEFF Research Database (Denmark)
Sharma, O.; Anton, François; Mioc, Darka
2012-01-01
Polygon features are of interest in many GEOProcessing applications like shoreline mapping, boundary delineation, change detection, etc. This paper presents a unique new GPU-based methodology to automate feature extraction combining level sets, or mean shift based segmentation together with Voron...
Level set methods for inverse scattering—some recent developments
International Nuclear Information System (INIS)
Dorn, Oliver; Lesselier, Dominique
2009-01-01
We give an update on recent techniques which use a level set representation of shapes for solving inverse scattering problems, completing in that matter the exposition made in (Dorn and Lesselier 2006 Inverse Problems 22 R67) and (Dorn and Lesselier 2007 Deformable Models (New York: Springer) pp 61–90), and bringing it closer to the current state of the art
Level-Set Methodology on Adaptive Octree Grids
Gibou, Frederic; Guittet, Arthur; Mirzadeh, Mohammad; Theillard, Maxime
2017-11-01
Numerical simulations of interfacial problems in fluids require a methodology capable of tracking surfaces that can undergo changes in topology and capable to imposing jump boundary conditions in a sharp manner. In this talk, we will discuss recent advances in the level-set framework, in particular one that is based on adaptive grids.
Schmidl, Marius
2017-04-01
We present a comprehensive training data set covering a large range of atmospheric conditions, including disperse volcanic ash and desert dust layers. These data sets contain all information required for the development of volcanic ash detection algorithms based on artificial neural networks, urgently needed since volcanic ash in the airspace is a major concern of aviation safety authorities. Selected parts of the data are used to train the volcanic ash detection algorithm VADUGS. They contain atmospheric and surface-related quantities as well as the corresponding simulated satellite data for the channels in the infrared spectral range of the SEVIRI instrument on board MSG-2. To get realistic results, ECMWF, IASI-based, and GEOS-Chem data are used to calculate all parameters describing the environment, whereas the software package libRadtran is used to perform radiative transfer simulations returning the brightness temperatures for each atmospheric state. As optical properties are a prerequisite for radiative simulations accounting for aerosol layers, the development also included the computation of optical properties for a set of different aerosol types from different sources. A description of the developed software and the used methods is given, besides an overview of the resulting data sets.
Discretisation Schemes for Level Sets of Planar Gaussian Fields
Beliaev, D.; Muirhead, S.
2018-01-01
Smooth random Gaussian functions play an important role in mathematical physics, a main example being the random plane wave model conjectured by Berry to give a universal description of high-energy eigenfunctions of the Laplacian on generic compact manifolds. Our work is motivated by questions about the geometry of such random functions, in particular relating to the structure of their nodal and level sets. We study four discretisation schemes that extract information about level sets of planar Gaussian fields. Each scheme recovers information up to a different level of precision, and each requires a maximum mesh-size in order to be valid with high probability. The first two schemes are generalisations and enhancements of similar schemes that have appeared in the literature (Beffara and Gayet in Publ Math IHES, 2017. https://doi.org/10.1007/s10240-017-0093-0; Mischaikow and Wanner in Ann Appl Probab 17:980-1018, 2007); these give complete topological information about the level sets on either a local or global scale. As an application, we improve the results in Beffara and Gayet (2017) on Russo-Seymour-Welsh estimates for the nodal set of positively-correlated planar Gaussian fields. The third and fourth schemes are, to the best of our knowledge, completely new. The third scheme is specific to the nodal set of the random plane wave, and provides global topological information about the nodal set up to `visible ambiguities'. The fourth scheme gives a way to approximate the mean number of excursion domains of planar Gaussian fields.
Fuzzy algorithms to generate level controllers for nuclear power plant steam generators
International Nuclear Information System (INIS)
Moon, Byung Soo; Park, Jae Chang; Kim, Dong Hwa; Kim, Byung Koo
1993-01-01
In this paper, we present two sets of fuzzy algorithms for the steam generater level control; one for the high power operations where the flow error is available and the other for the low power operations where the flow error is not available. These are converted to a PID type controller for the high power case and to a quadratic function form of a controller for the low power case. These controllers are implemented on the Compact Nuclear Simulator at Korea Atomic Energy Research Institute and tested by a set of four simulation experiments for each. For both cases, the results show that the total variation of the level error and of the flow error are about 50% of those by the PI controllers with about one half of the control action. For the high power case, this is mainly due to the fact that a combination of two PD type controllers in the velocity algorithm form rather than a combination of two PI type controllers in the position algorithm form is used. For the low power case, the controller is essentially a PID type with a very small integral component where the average values for the derivative component input and for the controller output are used. (Author)
An Algorithm for Glaucoma Screening in Clinical Settings and Its Preliminary Performance Profile
Directory of Open Access Journals (Sweden)
S-Farzad Mohammadi
2013-01-01
Full Text Available Purpose: To devise and evaluate a screening algorithm for glaucoma in clinical settings. Methods: Screening included examination of the optic disc for vertical cupping (≥0.4 and asymmetry (≥0.15, Goldmann applanation tonometry (≥21 mmHg, adjusted or unadjusted for central corneal thickness, and automated perimetry. In the diagnostic step, retinal nerve fiber layer imaging was performed using scanning laser polarimetry. Performance of the screening protocol was assessed in an eye hospital-based program in which 124 non-physician personnel aged 40 years or above were examined. A single ophthalmologist carried out the examinations and in equivocal cases, a glaucoma subspecialist′s opinion was sought. Results: Glaucoma was diagnosed in six cases (prevalence 4.8%; 95% confidence interval, 0.01-0.09 of whom five were new. The likelihood of making a definite diagnosis of glaucoma for those who were screened positively was 8.5 times higher than the estimated baseline risk for the reference population; the positive predictive value of the screening protocol was 30%. Screening excluded 80% of the initial population. Conclusion: Application of a formal screening protocol (such as our algorithm or its equivalent in clinical settings can be helpful in detecting new cases of glaucoma. Preliminary performance assessment of the algorithm showed its applicability and effectiveness in detecting glaucoma among subjects without any visual complaint.
PENGGUNAAN HIBRIDISASI GENETICS ALGORITHMS DAN FUZZY SETS UNTUK MEMPRODUKSI PAKET SOAL
Directory of Open Access Journals (Sweden)
Rolly Intan
2005-01-01
Full Text Available At least, two important factors, discrimination and difficulty, should be considered in determing whether a problem should be in a packet of problems produced for students entrance examination at a university. The higher the discrimination degree of a problem, the better the problem is used to make a selection of participants based on their intellectual capability. How to provide a packet of entrance examination problems satisfying a determined pattern of discrimination and difficulty is a major problem in this paper for which an algorithm, it can be proved that the beneficiary of applying fuzzy sets and fuzzy relation in determing the first chromosome in the process of GA is that the process can reach tolerable solutions faster. Maximum number of generation is still needed as a threshold to overcome the problem of run time system overflow. Generally, the problems in the form of passages tend to have lower fitnest cost. Abstract in Bahasa Indonesia : Proses penyusunan paket soal (misalnya soal untuk test seleksi masuk universitas yang diambil dari suatu bank soal, minimal harus memperhatikan dua aspek penting yaitu: tingkat kesulitan dan tingkat diskriminan soal. Semakin tinggi tingkat diskriminan suatu soal, semakin baik soal tersebut dipakai untuk menyeleksi kemampuan peserta test. Permasalahan yang dihadapi adalah bagaimana agar pembuat soal dapat memilih dan menentukan kombinasi soal-soal yang tepat (optimum sehingga dapat memenuhi tingkat kesulitan dan diskriminan yang dikehendaki. Untuk menyelesaikan masalah ini, diperkenalkan suatu algoritma yang disusun dengan menggunakan hibridisasi metode Genetics Algorithm dan fuzzy sets. Dari hasil pengujian, didapatkan bahwa penggunaan fuzzy sets dan fuzzy relations dalam pemilihan kromoson awal akan lebih mempercepat pencapaian tolerable solutions. Tetap dibutuhkan treshould maksimum jumlah generasi yang dilakukan untuk mencegah run time sistem overflow. Soal bacaan cenderung memiliki nilai Fitnest
Indian Academy of Sciences (India)
polynomial) division have been found in Vedic Mathematics which are dated much before Euclid's algorithm. A programming language Is used to describe an algorithm for execution on a computer. An algorithm expressed using a programming.
A learning algorithm for adaptive canonical correlation analysis of several data sets.
Vía, Javier; Santamaría, Ignacio; Pérez, Jesús
2007-01-01
Canonical correlation analysis (CCA) is a classical tool in statistical analysis to find the projections that maximize the correlation between two data sets. In this work we propose a generalization of CCA to several data sets, which is shown to be equivalent to the classical maximum variance (MAXVAR) generalization proposed by Kettenring. The reformulation of this generalization as a set of coupled least squares regression problems is exploited to develop a neural structure for CCA. In particular, the proposed CCA model is a two layer feedforward neural network with lateral connections in the output layer to achieve the simultaneous extraction of all the CCA eigenvectors through deflation. The CCA neural model is trained using a recursive least squares (RLS) algorithm. Finally, the convergence of the proposed learning rule is proved by means of stochastic approximation techniques and their performance is analyzed through simulations.
Mapping topographic structure in white matter pathways with level set trees.
Directory of Open Access Journals (Sweden)
Brian P Kent
Full Text Available Fiber tractography on diffusion imaging data offers rich potential for describing white matter pathways in the human brain, but characterizing the spatial organization in these large and complex data sets remains a challenge. We show that level set trees--which provide a concise representation of the hierarchical mode structure of probability density functions--offer a statistically-principled framework for visualizing and analyzing topography in fiber streamlines. Using diffusion spectrum imaging data collected on neurologically healthy controls (N = 30, we mapped white matter pathways from the cortex into the striatum using a deterministic tractography algorithm that estimates fiber bundles as dimensionless streamlines. Level set trees were used for interactive exploration of patterns in the endpoint distributions of the mapped fiber pathways and an efficient segmentation of the pathways that had empirical accuracy comparable to standard nonparametric clustering techniques. We show that level set trees can also be generalized to model pseudo-density functions in order to analyze a broader array of data types, including entire fiber streamlines. Finally, resampling methods show the reliability of the level set tree as a descriptive measure of topographic structure, illustrating its potential as a statistical descriptor in brain imaging analysis. These results highlight the broad applicability of level set trees for visualizing and analyzing high-dimensional data like fiber tractography output.
Level-1 pixel based tracking trigger algorithm for LHC upgrade
Moon, Chang-Seong
2015-01-01
The Pixel Detector is the innermost detector of the tracking system of the Compact Muon Solenoid (CMS) experiment at CERN Large Hadron Collider (LHC). It precisely determines the interaction point (primary vertex) of the events and the possible secondary vertexes due to heavy flavours ($b$ and $c$ quarks); it is part of the overall tracking system that allows reconstructing the tracks of the charged particles in the events and combined with the magnetic field to measure their impulsion. The pixel detector allows measuring the tracks in the region closest to the interaction point. The Level-1 (real-time) pixel based tracking trigger is a novel trigger system that is currently being studied for the LHC upgrade. An important goal is developing real-time track reconstruction algorithms able to cope with very high rates and high flux of data in a very harsh environment. The pixel detector has an especially crucial role in precisely identifying the primary vertex of the rare physics events from the large pile-up (P...
Energy Technology Data Exchange (ETDEWEB)
Jacobsson Svärd, Staffan, E-mail: staffan.jacobsson_svard@physics.uu.se; Holcombe, Scott; Grape, Sophie
2015-05-21
A fuel assembly operated in a nuclear power plant typically contains 100–300 fuel rods, depending on fuel type, which become strongly radioactive during irradiation in the reactor core. For operational and security reasons, it is of interest to experimentally deduce rod-wise information from the fuel, preferably by means of non-destructive measurements. The tomographic SPECT technique offers such possibilities through its two-step application; (1) recording the gamma-ray flux distribution around the fuel assembly, and (2) reconstructing the assembly's internal source distribution, based on the recorded radiation field. In this paper, algorithms for performing the latter step and extracting quantitative relative rod-by-rod data are accounted for. As compared to application of SPECT in nuclear medicine, nuclear fuel assemblies present a much more heterogeneous distribution of internal attenuation to gamma radiation than the human body, typically with rods containing pellets of heavy uranium dioxide surrounded by cladding of a zirconium alloy placed in water or air. This inhomogeneity severely complicates the tomographic quantification of the rod-wise relative source content, and the deduction of conclusive data requires detailed modelling of the attenuation to be introduced in the reconstructions. However, as shown in this paper, simplified models may still produce valuable information about the fuel. Here, a set of reconstruction algorithms for SPECT on nuclear fuel assemblies are described and discussed in terms of their quantitative performance for two applications; verification of fuel assemblies' completeness in nuclear safeguards, and rod-wise fuel characterization. It is argued that a request not to base the former assessment on any a priori information brings constraints to which reconstruction methods that may be used in that case, whereas the use of a priori information on geometry and material content enables highly accurate quantitative
Gradient augmented level set method for phase change simulations
Anumolu, Lakshman; Trujillo, Mario F.
2018-01-01
A numerical method for the simulation of two-phase flow with phase change based on the Gradient-Augmented-Level-set (GALS) strategy is presented. Sharp capturing of the vaporization process is enabled by: i) identification of the vapor-liquid interface, Γ (t), at the subgrid level, ii) discontinuous treatment of thermal physical properties (except for μ), and iii) enforcement of mass, momentum, and energy jump conditions, where the gradients of the dependent variables are obtained at Γ (t) and are consistent with their analytical expression, i.e. no local averaging is applied. Treatment of the jump in velocity and pressure at Γ (t) is achieved using the Ghost Fluid Method. The solution of the energy equation employs the sub-grid knowledge of Γ (t) to discretize the temperature Laplacian using second-order one-sided differences, i.e. the numerical stencil completely resides within each respective phase. To carefully evaluate the benefits or disadvantages of the GALS approach, the standard level set method is implemented and compared against the GALS predictions. The results show the expected trend that interface identification and transport are predicted noticeably better with GALS over the standard level set. This benefit carries over to the prediction of the Laplacian and temperature gradients in the neighborhood of the interface, which are directly linked to the calculation of the vaporization rate. However, when combining the calculation of interface transport and reinitialization with two-phase momentum and energy, the benefits of GALS are to some extent neutralized, and the causes for this behavior are identified and analyzed. Overall the additional computational costs associated with GALS are almost the same as those using the standard level set technique.
An evolutionary algorithm for tomographic reconstructions in limited data sets problems
International Nuclear Information System (INIS)
Turcanu, Catrinel; Craciunescu, Teddy
2000-01-01
The paper proposes a new method for tomographic reconstructions. Unlike nuclear medicine applications, in physical science problems we are often confronted with limited data sets: constraints in the number of projections or limited angle views. The problem of image reconstruction from projections may be considered as a problem of finding an image (solution) having projections that match the experimental ones. In our approach, we choose a statistical correlation coefficient to evaluate the fitness of any potential solution. The optimization process is carried out by an evolutionary algorithm. Our algorithm has some problem-oriented characteristics. One of them is that a chromosome, representing a potential solution, is not linear but coded as a matrix of pixels corresponding to a two-dimensional image. This kind of internal representation reflects the genuine manifestation and slight differences between two points situated in the original problem space give rise to similar differences once they become coded. Another particular feature is a newly built crossover operator: the grid-based crossover, suitable for high dimension two-dimensional chromosomes. Except for the population size and the dimension of the cutting grid for the grid-based crossover, all the other parameters of the algorithm are independent of the geometry of the tomographic reconstruction. The performances of the method are evaluated in comparison with a traditional tomographic method, based on the maximization of the entropy of the image, that proved to work well with limited data sets. The test phantom is typical for an application with limited data sets: the determination of the neutron energy spectra with time resolution in case of short-pulsed neutron emission. The qualitative judgement and also the quantitative one, based on some figures of merit, point out that the proposed method ensures an improved reconstruction of shapes, sizes and resolution in the image, even in the presence of noise
Iterative algorithm of discrete Fourier transform for processing randomly sampled NMR data sets
International Nuclear Information System (INIS)
Stanek, Jan; Kozminski, Wiktor
2010-01-01
Spectra obtained by application of multidimensional Fourier Transformation (MFT) to sparsely sampled nD NMR signals are usually corrupted due to missing data. In the present paper this phenomenon is investigated on simulations and experiments. An effective iterative algorithm for artifact suppression for sparse on-grid NMR data sets is discussed in detail. It includes automated peak recognition based on statistical methods. The results enable one to study NMR spectra of high dynamic range of peak intensities preserving benefits of random sampling, namely the superior resolution in indirectly measured dimensions. Experimental examples include 3D 15 N- and 13 C-edited NOESY-HSQC spectra of human ubiquitin.
Level sets and extrema of random processes and fields
Azais, Jean-Marc
2009-01-01
A timely and comprehensive treatment of random field theory with applications across diverse areas of study Level Sets and Extrema of Random Processes and Fields discusses how to understand the properties of the level sets of paths as well as how to compute the probability distribution of its extremal values, which are two general classes of problems that arise in the study of random processes and fields and in related applications. This book provides a unified and accessible approach to these two topics and their relationship to classical theory and Gaussian processes and fields, and the most modern research findings are also discussed. The authors begin with an introduction to the basic concepts of stochastic processes, including a modern review of Gaussian fields and their classical inequalities. Subsequent chapters are devoted to Rice formulas, regularity properties, and recent results on the tails of the distribution of the maximum. Finally, applications of random fields to various areas of mathematics a...
Skull defect reconstruction based on a new hybrid level set.
Zhang, Ziqun; Zhang, Ran; Song, Zhijian
2014-01-01
Skull defect reconstruction is an important aspect of surgical repair. Historically, a skull defect prosthesis was created by the mirroring technique, surface fitting, or formed templates. These methods are not based on the anatomy of the individual patient's skull, and therefore, the prosthesis cannot precisely correct the defect. This study presented a new hybrid level set model, taking into account both the global optimization region information and the local accuracy edge information, while avoiding re-initialization during the evolution of the level set function. Based on the new method, a skull defect was reconstructed, and the skull prosthesis was produced by rapid prototyping technology. This resulted in a skull defect prosthesis that well matched the skull defect with excellent individual adaptation.
Level-set techniques for facies identification in reservoir modeling
Iglesias, Marco A.; McLaughlin, Dennis
2011-03-01
In this paper we investigate the application of level-set techniques for facies identification in reservoir models. The identification of facies is a geometrical inverse ill-posed problem that we formulate in terms of shape optimization. The goal is to find a region (a geologic facies) that minimizes the misfit between predicted and measured data from an oil-water reservoir. In order to address the shape optimization problem, we present a novel application of the level-set iterative framework developed by Burger in (2002 Interfaces Free Bound. 5 301-29 2004 Inverse Problems 20 259-82) for inverse obstacle problems. The optimization is constrained by (the reservoir model) a nonlinear large-scale system of PDEs that describes the reservoir dynamics. We reformulate this reservoir model in a weak (integral) form whose shape derivative can be formally computed from standard results of shape calculus. At each iteration of the scheme, the current estimate of the shape derivative is utilized to define a velocity in the level-set equation. The proper selection of this velocity ensures that the new shape decreases the cost functional. We present results of facies identification where the velocity is computed with the gradient-based (GB) approach of Burger (2002) and the Levenberg-Marquardt (LM) technique of Burger (2004). While an adjoint formulation allows the straightforward application of the GB approach, the LM technique requires the computation of the large-scale Karush-Kuhn-Tucker system that arises at each iteration of the scheme. We efficiently solve this system by means of the representer method. We present some synthetic experiments to show and compare the capabilities and limitations of the proposed implementations of level-set techniques for the identification of geologic facies.
Level-set techniques for facies identification in reservoir modeling
International Nuclear Information System (INIS)
Iglesias, Marco A; McLaughlin, Dennis
2011-01-01
In this paper we investigate the application of level-set techniques for facies identification in reservoir models. The identification of facies is a geometrical inverse ill-posed problem that we formulate in terms of shape optimization. The goal is to find a region (a geologic facies) that minimizes the misfit between predicted and measured data from an oil–water reservoir. In order to address the shape optimization problem, we present a novel application of the level-set iterative framework developed by Burger in (2002 Interfaces Free Bound. 5 301–29; 2004 Inverse Problems 20 259–82) for inverse obstacle problems. The optimization is constrained by (the reservoir model) a nonlinear large-scale system of PDEs that describes the reservoir dynamics. We reformulate this reservoir model in a weak (integral) form whose shape derivative can be formally computed from standard results of shape calculus. At each iteration of the scheme, the current estimate of the shape derivative is utilized to define a velocity in the level-set equation. The proper selection of this velocity ensures that the new shape decreases the cost functional. We present results of facies identification where the velocity is computed with the gradient-based (GB) approach of Burger (2002) and the Levenberg–Marquardt (LM) technique of Burger (2004). While an adjoint formulation allows the straightforward application of the GB approach, the LM technique requires the computation of the large-scale Karush–Kuhn–Tucker system that arises at each iteration of the scheme. We efficiently solve this system by means of the representer method. We present some synthetic experiments to show and compare the capabilities and limitations of the proposed implementations of level-set techniques for the identification of geologic facies
Level Set Approach to Anisotropic Wet Etching of Silicon
Directory of Open Access Journals (Sweden)
Branislav Radjenović
2010-05-01
Full Text Available In this paper a methodology for the three dimensional (3D modeling and simulation of the profile evolution during anisotropic wet etching of silicon based on the level set method is presented. Etching rate anisotropy in silicon is modeled taking into account full silicon symmetry properties, by means of the interpolation technique using experimentally obtained values for the etching rates along thirteen principal and high index directions in KOH solutions. The resulting level set equations are solved using an open source implementation of the sparse field method (ITK library, developed in medical image processing community, extended for the case of non-convex Hamiltonians. Simulation results for some interesting initial 3D shapes, as well as some more practical examples illustrating anisotropic etching simulation in the presence of masks (simple square aperture mask, convex corner undercutting and convex corner compensation, formation of suspended structures are shown also. The obtained results show that level set method can be used as an effective tool for wet etching process modeling, and that is a viable alternative to the Cellular Automata method which now prevails in the simulations of the wet etching process.
Variational Level Set Method for Two-Stage Image Segmentation Based on Morphological Gradients
Directory of Open Access Journals (Sweden)
Zemin Ren
2014-01-01
Full Text Available We use variational level set method and transition region extraction techniques to achieve image segmentation task. The proposed scheme is done by two steps. We first develop a novel algorithm to extract transition region based on the morphological gradient. After this, we integrate the transition region into a variational level set framework and develop a novel geometric active contour model, which include an external energy based on transition region and fractional order edge indicator function. The external energy is used to drive the zero level set toward the desired image features, such as object boundaries. Due to this external energy, the proposed model allows for more flexible initialization. The fractional order edge indicator function is incorporated into the length regularization term to diminish the influence of noise. Moreover, internal energy is added into the proposed model to penalize the deviation of the level set function from a signed distance function. The results evolution of the level set function is the gradient flow that minimizes the overall energy functional. The proposed model has been applied to both synthetic and real images with promising results.
Perrenet, J.C.; Kaasenbrood, E.J.S.
2006-01-01
In a former, mainly quantitative, study we defined four levels of abstraction in Computer Science students' thinking about the concept of algorithm. We constructed a list of questions about algorithms to measure the answering level as an indication for the thinking level. The answering level
Reevaluation of steam generator level trip set point
Energy Technology Data Exchange (ETDEWEB)
Shim, Yoon Sub; Soh, Dong Sub; Kim, Sung Oh; Jung, Se Won; Sung, Kang Sik; Lee, Joon [Korea Atomic Energy Research Institute, Taejon (Korea, Republic of)
1994-06-01
The reactor trip by the low level of steam generator water accounts for a substantial portion of reactor scrams in a nuclear plant and the feasibility of modification of the steam generator water level trip system of YGN 1/2 was evaluated in this study. The study revealed removal of the reactor trip function from the SG water level trip system is not possible because of plant safety but relaxation of the trip set point by 9 % is feasible. The set point relaxation requires drilling of new holes for level measurement to operating steam generators. Characteristics of negative neutron flux rate trip and reactor trip were also reviewed as an additional work. Since the purpose of the trip system modification for reduction of a reactor scram frequency is not to satisfy legal requirements but to improve plant performance and the modification yields positive and negative aspects, the decision of actual modification needs to be made based on the results of this study and also the policy of a plant owner. 37 figs, 6 tabs, 14 refs. (Author).
Utility of an Algorithm to Increase the Accuracy of Medication History in an Obstetrical Setting.
Corbel, Aline; Baud, David; Chaouch, Aziz; Beney, Johnny; Csajka, Chantal; Panchaud, Alice
2016-01-01
In an obstetrical setting, inaccurate medication histories at hospital admission may result in failure to identify potentially harmful treatments for patients and/or their fetus(es). This prospective study was conducted to assess average concordance rates between (1) a medication list obtained with a one-page structured medication history algorithm developed for the obstetrical setting and (2) the medication list reported in medical records and obtained by open-ended questions based on standard procedures. Both lists were converted into concordance rate using a best possible medication history approach as the reference (information obtained by patients, prescribers and community pharmacists' interviews). The algorithm-based method obtained a higher average concordance rate than the standard method, with respectively 90.2% [CI95% 85.8-94.3] versus 24.6% [CI95%15.3-34.4] concordance rates (phistory in our obstetric population, without using substantial resources. Its implementation is an effective first step to the medication reconciliation process, which has been recognized as a very important component of patients' drug safety.
Level set method for image segmentation based on moment competition
Min, Hai; Wang, Xiao-Feng; Huang, De-Shuang; Jin, Jing; Wang, Hong-Zhi; Li, Hai
2015-05-01
We propose a level set method for image segmentation which introduces the moment competition and weakly supervised information into the energy functional construction. Different from the region-based level set methods which use force competition, the moment competition is adopted to drive the contour evolution. Here, a so-called three-point labeling scheme is proposed to manually label three independent points (weakly supervised information) on the image. Then the intensity differences between the three points and the unlabeled pixels are used to construct the force arms for each image pixel. The corresponding force is generated from the global statistical information of a region-based method and weighted by the force arm. As a result, the moment can be constructed and incorporated into the energy functional to drive the evolving contour to approach the object boundary. In our method, the force arm can take full advantage of the three-point labeling scheme to constrain the moment competition. Additionally, the global statistical information and weakly supervised information are successfully integrated, which makes the proposed method more robust than traditional methods for initial contour placement and parameter setting. Experimental results with performance analysis also show the superiority of the proposed method on segmenting different types of complicated images, such as noisy images, three-phase images, images with intensity inhomogeneity, and texture images.
Faenza, Y.; Oriolo, G.; Stauffer, G.
2011-01-01
We propose an algorithm for solving the maximum weighted stable set problem on claw-free graphs that runs in O(n^3)-time, drastically improving the previous best known complexity bound. This algorithm is based on a novel decomposition theorem for claw-free graphs, which is also intioduced in the present paper. Despite being weaker than the well-known structure result for claw-free graphs given by Chudnovsky and Seymour, our decomposition theorem is, on the other hand, algorithmic, i.e. it is ...
A Variational Level Set Model Combined with FCMS for Image Clustering Segmentation
Directory of Open Access Journals (Sweden)
Liming Tang
2014-01-01
Full Text Available The fuzzy C means clustering algorithm with spatial constraint (FCMS is effective for image segmentation. However, it lacks essential smoothing constraints to the cluster boundaries and enough robustness to the noise. Samson et al. proposed a variational level set model for image clustering segmentation, which can get the smooth cluster boundaries and closed cluster regions due to the use of level set scheme. However it is very sensitive to the noise since it is actually a hard C means clustering model. In this paper, based on Samson’s work, we propose a new variational level set model combined with FCMS for image clustering segmentation. Compared with FCMS clustering, the proposed model can get smooth cluster boundaries and closed cluster regions due to the use of level set scheme. In addition, a block-based energy is incorporated into the energy functional, which enables the proposed model to be more robust to the noise than FCMS clustering and Samson’s model. Some experiments on the synthetic and real images are performed to assess the performance of the proposed model. Compared with some classical image segmentation models, the proposed model has a better performance for the images contaminated by different noise levels.
Classon, Johan; Andersson, Viktor
2016-01-01
This thesis describes the implementation and evaluation of a genetic algorithm (GA) for procedurally generating levels with controllable difficulty for a motion-based 2D platform game. Manually creating content can be time-consuming, and it may be desirable to automate this process with an algorithm, using Procedural Content Generation (PCG). An algorithm was implemented and then refined with an iterative method by conducting user tests. The resulting algorithm is considered a success and sho...
Indian Academy of Sciences (India)
to as 'divide-and-conquer'. Although there has been a large effort in realizing efficient algorithms, there are not many universally accepted algorithm design paradigms. In this article, we illustrate algorithm design techniques such as balancing, greedy strategy, dynamic programming strategy, and backtracking or traversal of ...
Transport equations, Level Set and Eulerian mechanics. Application to fluid-structure coupling
International Nuclear Information System (INIS)
Maitre, E.
2008-11-01
My works were devoted to numerical analysis of non-linear elliptic-parabolic equations, to neutron transport equation and to the simulation of fabrics draping. More recently I developed an Eulerian method based on a level set formulation of the immersed boundary method to deal with fluid-structure coupling problems arising in bio-mechanics. Some of the more efficient algorithms to solve the neutron transport equation make use of the splitting of the transport operator taking into account its characteristics. In the present work we introduced a new algorithm based on this splitting and an adaptation of minimal residual methods to infinite dimensional case. We present the case where the velocity space is of dimension 1 (slab geometry) and 2 (plane geometry) because the splitting is simpler in the former
Farahi, Maria; Rabbani, Hossein; Talebi, Ardeshir; Sarrafzadeh, Omid; Ensafi, Shahab
2015-12-01
Visceral Leishmaniasis is a parasitic disease that affects liver, spleen and bone marrow. According to World Health Organization report, definitive diagnosis is possible just by direct observation of the Leishman body in the microscopic image taken from bone marrow samples. We utilize morphological and CV level set method to segment Leishman bodies in digital color microscopic images captured from bone marrow samples. Linear contrast stretching method is used for image enhancement and morphological method is applied to determine the parasite regions and wipe up unwanted objects. Modified global and local CV level set methods are proposed for segmentation and a shape based stopping factor is used to hasten the algorithm. Manual segmentation is considered as ground truth to evaluate the proposed method. This method is tested on 28 samples and achieved 10.90% mean of segmentation error for global model and 9.76% for local model.
A level-set method for two-phase flows with soluble surfactant
Xu, Jian-Jun; Shi, Weidong; Lai, Ming-Chih
2018-01-01
A level-set method is presented for solving two-phase flows with soluble surfactant. The Navier-Stokes equations are solved along with the bulk surfactant and the interfacial surfactant equations. In particular, the convection-diffusion equation for the bulk surfactant on the irregular moving domain is solved by using a level-set based diffusive-domain method. A conservation law for the total surfactant mass is derived, and a re-scaling procedure for the surfactant concentrations is proposed to compensate for the surfactant mass loss due to numerical diffusion. The whole numerical algorithm is easy for implementation. Several numerical simulations in 2D and 3D show the effects of surfactant solubility on drop dynamics under shear flow.
Directory of Open Access Journals (Sweden)
Yi Han
2013-01-01
Full Text Available This paper presents a shuffled frog leaping algorithm (SFLA for the single-mode resource-constrained project scheduling problem where activities can be divided into equant units and interrupted during processing. Each activity consumes 0–3 types of resources which are renewable and temporarily not available due to resource vacations in each period. The presence of scarce resources and precedence relations between activities makes project scheduling a difficult and important task in project management. A recent popular metaheuristic shuffled frog leaping algorithm, which is enlightened by the predatory habit of frog group in a small pond, is adopted to investigate the project makespan improvement on Patterson benchmark sets which is composed of different small and medium size projects. Computational results demonstrate the effectiveness and efficiency of SFLA in reducing project makespan and minimizing activity splitting number within an average CPU runtime, 0.521 second. This paper exposes all the scheduling sequences for each project and shows that of the 23 best known solutions have been improved.
Omar, A. H.; Tackett, J. L.; Vaughan, M. A.; Kar, J.; Trepte, C. R.; Winker, D. M.
2016-12-01
This presentation describes several enhancements planned for the version 4 aerosol subtyping and lidar ratio selection algorithms of the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument. The CALIOP subtyping algorithm determines the most likely aerosol type from CALIOP measurements (attenuated backscatter, estimated particulate depolarization ratios δe, layer altitude), and surface type. The aerosol type, so determined, is associated with a lidar ratio (LR) from a discrete set of values. Some of these lidar ratios have been updated in the version 4 algorithms. In particular, the dust and polluted dust will be adjusted to reflect the latest measurements and model studies of these types. Version 4 eliminates the confusion between smoke and clean marine aerosols seen in version 3 by modifications to the elevated layer flag definitions used to identify smoke aerosols over the ocean. In the subtyping algorithms pure dust is determined by high estimated particulate depolarization ratios [δe > 0.20]. Mixtures of dust and other aerosol types are determined by intermediate values of the estimated depolarization ratio [0.075limited to mixtures of dust and smoke, the so called polluted dust aerosol type. To differentiate between mixtures of dust and smoke, and dust and marine aerosols, a new aerosol type will be added in the version 4 data products. In the revised classification algorithms, polluted dust will still defined as dust + smoke/pollution but in the marine boundary layer instances of moderate depolarization will be typed as dusty marine aerosols with a lower lidar ratio than polluted dust. The dusty marine type introduced in version 4 is modeled as a mixture of dust + marine aerosol. To account for fringes, the version 4 Level 2 algorithms implement Subtype Coalescence Algorithm for AeRosol Fringes (SCAARF) routine to detect and classify fringe of aerosol plumes that are detected at 20 km or 80 km horizontal resolution at the plume base. These
Griffiths, Thomas L; Lieder, Falk; Goodman, Noah D
2015-04-01
Marr's levels of analysis-computational, algorithmic, and implementation-have served cognitive science well over the last 30 years. But the recent increase in the popularity of the computational level raises a new challenge: How do we begin to relate models at different levels of analysis? We propose that it is possible to define levels of analysis that lie between the computational and the algorithmic, providing a way to build a bridge between computational- and algorithmic-level models. The key idea is to push the notion of rationality, often used in defining computational-level models, deeper toward the algorithmic level. We offer a simple recipe for reverse-engineering the mind's cognitive strategies by deriving optimal algorithms for a series of increasingly more realistic abstract computational architectures, which we call "resource-rational analysis." Copyright © 2015 Cognitive Science Society, Inc.
Thermogram breast cancer prediction approach based on Neutrosophic sets and fuzzy c-means algorithm.
Gaber, Tarek; Ismail, Gehad; Anter, Ahmed; Soliman, Mona; Ali, Mona; Semary, Noura; Hassanien, Aboul Ella; Snasel, Vaclav
2015-08-01
The early detection of breast cancer makes many women survive. In this paper, a CAD system classifying breast cancer thermograms to normal and abnormal is proposed. This approach consists of two main phases: automatic segmentation and classification. For the former phase, an improved segmentation approach based on both Neutrosophic sets (NS) and optimized Fast Fuzzy c-mean (F-FCM) algorithm was proposed. Also, post-segmentation process was suggested to segment breast parenchyma (i.e. ROI) from thermogram images. For the classification, different kernel functions of the Support Vector Machine (SVM) were used to classify breast parenchyma into normal or abnormal cases. Using benchmark database, the proposed CAD system was evaluated based on precision, recall, and accuracy as well as a comparison with related work. The experimental results showed that our system would be a very promising step toward automatic diagnosis of breast cancer using thermograms as the accuracy reached 100%.
Energy Technology Data Exchange (ETDEWEB)
Romanov, A.; Edstrom, D.; Emanov, F. A.; Koop, I. A.; Perevedentsev, E. A.; Rogovsky, Yu. A.; Shwartz, D. B.; Valishev, A.
2017-03-28
Precise beam based measurement and correction of magnetic optics is essential for the successful operation of accelerators. The LOCO algorithm is a proven and reliable tool, which in some situations can be improved by using a broader class of experimental data. The standard data sets for LOCO include the closed orbit responses to dipole corrector variation, dispersion, and betatron tunes. This paper discusses the benefits from augmenting the data with four additional classes of experimental data: the beam shape measured with beam profile monitors; responses of closed orbit bumps to focusing field variations; betatron tune responses to focusing field variations; BPM-to-BPM betatron phase advances and beta functions in BPMs from turn-by-turn coordinates of kicked beam. All of the described features were implemented in the Sixdsimulation software that was used to correct the optics of the VEPP-2000 collider, the VEPP-5 injector booster ring, and the FAST linac.
SU-F-J-180: A Reference Data Set for Testing Two Dimension Registration Algorithms
International Nuclear Information System (INIS)
Dankwa, A; Castillo, E; Guerrero, T
2016-01-01
Purpose: To create and characterize a reference data set for testing image registration algorithms that transform portal image (PI) to digitally reconstructed radiograph (DRR). Methods: Anterior-posterior (AP) and Lateral (LAT) projection and DRR image pairs from nine cases representing four different anatomical sites (head and neck, thoracic, abdominal, and pelvis) were selected for this study. Five experts will perform manual registration by placing landmarks points (LMPs) on the DRR and finding their corresponding points on the PI using computer assisted manual point selection tool (CAMPST), a custom-made MATLAB software tool developed in house. The landmark selection process will be repeated on both the PI and the DRR in order to characterize inter- and -intra observer variations associated with the point selection process. Inter and an intra observer variation in LMPs was done using Bland-Altman (B&A) analysis and one-way analysis of variance. We set our limit such that the absolute value of the mean difference between the readings should not exceed 3mm. Later on in this project we will test different two dimension (2D) image registration algorithms and quantify the uncertainty associated with their registration. Results: Using one-way analysis of variance (ANOVA) there was no variations within the readers. When Bland-Altman analysis was used the variation within the readers was acceptable. The variation was higher in the PI compared to the DRR.ConclusionThe variation seen for the PI is because although the PI has a much better spatial resolution the poor resolution on the DRR makes it difficult to locate the actual corresponding anatomical feature on the PI. We hope this becomes more evident when all the readers complete the point selection. The reason for quantifying inter- and -intra observer variation tells us to what degree of accuracy a manual registration can be done. Research supported by William Beaumont Hospital Research Start Up Fund.
SU-F-J-180: A Reference Data Set for Testing Two Dimension Registration Algorithms
Energy Technology Data Exchange (ETDEWEB)
Dankwa, A; Castillo, E; Guerrero, T [William Beaumont Hospital, Rochester Hills, MI (United States)
2016-06-15
Purpose: To create and characterize a reference data set for testing image registration algorithms that transform portal image (PI) to digitally reconstructed radiograph (DRR). Methods: Anterior-posterior (AP) and Lateral (LAT) projection and DRR image pairs from nine cases representing four different anatomical sites (head and neck, thoracic, abdominal, and pelvis) were selected for this study. Five experts will perform manual registration by placing landmarks points (LMPs) on the DRR and finding their corresponding points on the PI using computer assisted manual point selection tool (CAMPST), a custom-made MATLAB software tool developed in house. The landmark selection process will be repeated on both the PI and the DRR in order to characterize inter- and -intra observer variations associated with the point selection process. Inter and an intra observer variation in LMPs was done using Bland-Altman (B&A) analysis and one-way analysis of variance. We set our limit such that the absolute value of the mean difference between the readings should not exceed 3mm. Later on in this project we will test different two dimension (2D) image registration algorithms and quantify the uncertainty associated with their registration. Results: Using one-way analysis of variance (ANOVA) there was no variations within the readers. When Bland-Altman analysis was used the variation within the readers was acceptable. The variation was higher in the PI compared to the DRR.ConclusionThe variation seen for the PI is because although the PI has a much better spatial resolution the poor resolution on the DRR makes it difficult to locate the actual corresponding anatomical feature on the PI. We hope this becomes more evident when all the readers complete the point selection. The reason for quantifying inter- and -intra observer variation tells us to what degree of accuracy a manual registration can be done. Research supported by William Beaumont Hospital Research Start Up Fund.
A variational approach to multi-phase motion of gas, liquid and solid based on the level set method
Yokoi, Kensuke
2009-07-01
We propose a simple and robust numerical algorithm to deal with multi-phase motion of gas, liquid and solid based on the level set method [S. Osher, J.A. Sethian, Front propagating with curvature-dependent speed: Algorithms based on Hamilton-Jacobi formulation, J. Comput. Phys. 79 (1988) 12; M. Sussman, P. Smereka, S. Osher, A level set approach for capturing solution to incompressible two-phase flow, J. Comput. Phys. 114 (1994) 146; J.A. Sethian, Level Set Methods and Fast Marching Methods, Cambridge University Press, 1999; S. Osher, R. Fedkiw, Level Set Methods and Dynamics Implicit Surface, Applied Mathematical Sciences, vol. 153, Springer, 2003]. In Eulerian framework, to simulate interaction between a moving solid object and an interfacial flow, we need to define at least two functions (level set functions) to distinguish three materials. In such simulations, in general two functions overlap and/or disagree due to numerical errors such as numerical diffusion. In this paper, we resolved the problem using the idea of the active contour model [M. Kass, A. Witkin, D. Terzopoulos, Snakes: active contour models, International Journal of Computer Vision 1 (1988) 321; V. Caselles, R. Kimmel, G. Sapiro, Geodesic active contours, International Journal of Computer Vision 22 (1997) 61; G. Sapiro, Geometric Partial Differential Equations and Image Analysis, Cambridge University Press, 2001; R. Kimmel, Numerical Geometry of Images: Theory, Algorithms, and Applications, Springer-Verlag, 2003] introduced in the field of image processing.
Yang, Guo Sheng; Wang, Xiao Yang; Li, Xue Dong
2018-03-01
With the establishment of the integrated model of relay protection and the scale of the power system expanding, the global setting and optimization of relay protection is an extremely difficult task. This paper presents a kind of application in relay protection of global optimization improved particle swarm optimization algorithm and the inverse time current protection as an example, selecting reliability of the relay protection, selectivity, quick action and flexibility as the four requires to establish the optimization targets, and optimizing protection setting values of the whole system. Finally, in the case of actual power system, the optimized setting value results of the proposed method in this paper are compared with the particle swarm algorithm. The results show that the improved quantum particle swarm optimization algorithm has strong search ability, good robustness, and it is suitable for optimizing setting value in the relay protection of the whole power system.
Demons versus level-set motion registration for coronary 18F-sodium fluoride PET
Rubeaux, Mathieu; Joshi, Nikhil; Dweck, Marc R.; Fletcher, Alison; Motwani, Manish; Thomson, Louise E.; Germano, Guido; Dey, Damini; Berman, Daniel S.; Newby, David E.; Slomka, Piotr J.
2016-03-01
Ruptured coronary atherosclerotic plaques commonly cause acute myocardial infarction. It has been recently shown that active microcalcification in the coronary arteries, one of the features that characterizes vulnerable plaques at risk of rupture, can be imaged using cardiac gated 18F-sodium fluoride (18F-NaF) PET. We have shown in previous work that a motion correction technique applied to cardiac-gated 18F-NaF PET images can enhance image quality and improve uptake estimates. In this study, we further investigated the applicability of different algorithms for registration of the coronary artery PET images. In particular, we aimed to compare demons vs. level-set nonlinear registration techniques applied for the correction of cardiac motion in coronary 18F-NaF PET. To this end, fifteen patients underwent 18F-NaF PET and prospective coronary CT angiography (CCTA). PET data were reconstructed in 10 ECG gated bins; subsequently these gated bins were registered using demons and level-set methods guided by the extracted coronary arteries from CCTA, to eliminate the effect of cardiac motion on PET images. Noise levels, target-to-background ratios (TBR) and global motion were compared to assess image quality. Compared to the reference standard of using only diastolic PET image (25% of the counts from PET acquisition), cardiac motion registration using either level-set or demons techniques almost halved image noise due to the use of counts from the full PET acquisition and increased TBR difference between 18F-NaF positive and negative lesions. The demons method produces smoother deformation fields, exhibiting no singularities (which reflects how physically plausible the registration deformation is), as compared to the level-set method, which presents between 4 and 8% of singularities, depending on the coronary artery considered. In conclusion, the demons method produces smoother motion fields as compared to the level-set method, with a motion that is physiologically
Acute stroke: automatic perfusion lesion outlining using level sets.
Mouridsen, Kim; Nagenthiraja, Kartheeban; Jónsdóttir, Kristjana Ýr; Ribe, Lars R; Neumann, Anders B; Hjort, Niels; Østergaard, Leif
2013-11-01
To develop a user-independent algorithm for the delineation of hypoperfused tissue on perfusion-weighted images and evaluate its performance relative to a standard threshold method in simulated data, as well as in acute stroke patients. The study was approved by the local ethics committee, and patients gave written informed consent prior to their inclusion in the study. The algorithm identifies hypoperfused tissue in mean transit time maps by simultaneously minimizing the mean square error between individual and mean perfusion values inside and outside a smooth boundary. In 14 acute stroke patients, volumetric agreement between automated outlines and manual outlines determined in consensus among four neuroradiologists was assessed with Bland-Altman analysis, while spatial agreement was quantified by using lesion overlap relative to mean lesion volume (Dice coefficient). Performance improvement relative to a standard threshold approach was tested with the Wilcoxon signed rank test. The mean difference in lesion volume between automated outlines and manual outlines was -9.0 mL ± 44.5 (standard deviation). The lowest mean volume difference for the threshold approach was -25.8 mL ± 88.2. A significantly higher Dice coefficient was observed with the algorithm (0.71; interquartile range [IQR], 0.42-0.75) compared with the threshold approach (0.50; IQR, 0.27- 0.57; P , .001). The corresponding agreement among experts was 0.79 (IQR, 0.69-0.83). The perfusion lesions outlined by the automated algorithm agreed well with those defined manually in consensus by four experts and were superior to those obtained by using the standard threshold approach. This user-independent algorithm may improve the assessment of perfusion images as part of acute stroke treatment. http://radiology.rsna.org/lookup/suppl/doi:10.1148/radiol.13121622/-/DC1. RSNA, 2013
Measurement of thermally ablated lesions in sonoelastographic images using level set methods
Castaneda, Benjamin; Tamez-Pena, Jose Gerardo; Zhang, Man; Hoyt, Kenneth; Bylund, Kevin; Christensen, Jared; Saad, Wael; Strang, John; Rubens, Deborah J.; Parker, Kevin J.
2008-03-01
The capability of sonoelastography to detect lesions based on elasticity contrast can be applied to monitor the creation of thermally ablated lesion. Currently, segmentation of lesions depicted in sonoelastographic images is performed manually which can be a time consuming process and prone to significant intra- and inter-observer variability. This work presents a semi-automated segmentation algorithm for sonoelastographic data. The user starts by planting a seed in the perceived center of the lesion. Fast marching methods use this information to create an initial estimate of the lesion. Subsequently, level set methods refine its final shape by attaching the segmented contour to edges in the image while maintaining smoothness. The algorithm is applied to in vivo sonoelastographic images from twenty five thermal ablated lesions created in porcine livers. The estimated area is compared to results from manual segmentation and gross pathology images. Results show that the algorithm outperforms manual segmentation in accuracy, inter- and intra-observer variability. The processing time per image is significantly reduced.
Segmentation of teeth in CT volumetric dataset by panoramic projection and variational level set
International Nuclear Information System (INIS)
Hosntalab, Mohammad; Aghaeizadeh Zoroofi, Reza; Abbaspour Tehrani-Fard, Ali; Shirani, Gholamreza
2008-01-01
Quantification of teeth is of clinical importance for various computer assisted procedures such as dental implant, orthodontic planning, face, jaw and cosmetic surgeries. In this regard, segmentation is a major step. In this paper, we propose a method for segmentation of teeth in volumetric computed tomography (CT) data using panoramic re-sampling of the dataset in the coronal view and variational level set. The proposed method consists of five steps as follows: first, we extract a mask in a CT images using Otsu thresholding. Second, the teeth are segmented from other bony tissues by utilizing anatomical knowledge of teeth in the jaws. Third, the proposed method is followed by estimating the arc of the upper and lower jaws and panoramic re-sampling of the dataset. Separation of upper and lower jaws and initial segmentation of teeth are performed by employing the horizontal and vertical projections of the panoramic dataset, respectively. Based the above mentioned procedures an initial mask for each tooth is obtained. Finally, we utilize the initial mask of teeth and apply a Variational level set to refine initial teeth boundaries to final contours. The proposed algorithm was evaluated in the presence of 30 multi-slice CT datasets including 3,600 images. Experimental results reveal the effectiveness of the proposed method. In the proposed algorithm, the variational level set technique was utilized to trace the contour of the teeth. In view of the fact that, this technique is based on the characteristic of the overall region of the teeth image, it is possible to extract a very smooth and accurate tooth contour using this technique. In the presence of the available datasets, the proposed technique was successful in teeth segmentation compared to previous techniques. (orig.)
Segmentation of teeth in CT volumetric dataset by panoramic projection and variational level set
Energy Technology Data Exchange (ETDEWEB)
Hosntalab, Mohammad [Islamic Azad University, Faculty of Engineering, Science and Research Branch, Tehran (Iran); Aghaeizadeh Zoroofi, Reza [University of Tehran, Control and Intelligent Processing Center of Excellence, School of Electrical and Computer Engineering, College of Engineering, Tehran (Iran); Abbaspour Tehrani-Fard, Ali [Islamic Azad University, Faculty of Engineering, Science and Research Branch, Tehran (Iran); Sharif University of Technology, Department of Electrical Engineering, Tehran (Iran); Shirani, Gholamreza [Faculty of Dentistry Medical Science of Tehran University, Oral and Maxillofacial Surgery Department, Tehran (Iran)
2008-09-15
Quantification of teeth is of clinical importance for various computer assisted procedures such as dental implant, orthodontic planning, face, jaw and cosmetic surgeries. In this regard, segmentation is a major step. In this paper, we propose a method for segmentation of teeth in volumetric computed tomography (CT) data using panoramic re-sampling of the dataset in the coronal view and variational level set. The proposed method consists of five steps as follows: first, we extract a mask in a CT images using Otsu thresholding. Second, the teeth are segmented from other bony tissues by utilizing anatomical knowledge of teeth in the jaws. Third, the proposed method is followed by estimating the arc of the upper and lower jaws and panoramic re-sampling of the dataset. Separation of upper and lower jaws and initial segmentation of teeth are performed by employing the horizontal and vertical projections of the panoramic dataset, respectively. Based the above mentioned procedures an initial mask for each tooth is obtained. Finally, we utilize the initial mask of teeth and apply a Variational level set to refine initial teeth boundaries to final contours. The proposed algorithm was evaluated in the presence of 30 multi-slice CT datasets including 3,600 images. Experimental results reveal the effectiveness of the proposed method. In the proposed algorithm, the variational level set technique was utilized to trace the contour of the teeth. In view of the fact that, this technique is based on the characteristic of the overall region of the teeth image, it is possible to extract a very smooth and accurate tooth contour using this technique. In the presence of the available datasets, the proposed technique was successful in teeth segmentation compared to previous techniques. (orig.)
Fluoroscopy in paediatric fractures - Setting a local diagnostic reference level
International Nuclear Information System (INIS)
Pillai, A.; McAuley, A.; McMurray, K.; Jain, M.
2006-01-01
Background: The ionizing radiations (Medical Exposure) Regulation 2000 has made it mandatory to establish diagnostic reference levels (DRLs) for all typical radiological examinations. Objectives: We attempt to provide dose data for some common fluoroscopic procedures used in orthopaedic trauma that may be used as the basis for setting DRLs for paediatric patients. Materials and methods: The dose area product (DAP) in 865 paediatric trauma examinations was analysed. Median DAP values and screening times for each procedure type along with quartile values for each range are presented. Results: In the upper limb, elbow examinations had maximum exposure with a median DAP value of 1.21 cGy cm 2 . Median DAP values for forearm and wrist examinations were 0.708 and 0.538 cGy cm 2 , respectively. In lower limb, tibia and fibula examinations had a median DAP value of 3.23 cGy cm 2 followed by ankle examinations with a median DAP of 3.10 cGy cm 2 . The rounded third quartile DAP value for each distribution can be used as a provisional DRL for the specific procedure type. (authors)
International Nuclear Information System (INIS)
Smarda, M; Alexopoulou, E; Mazioti, A; Kordolaimi, S; Ploussi, A; Efstathopoulos, E; Priftis, K
2015-01-01
Purpose of the study is to determine the appropriate iterative reconstruction (IR) algorithm level that combines image quality and diagnostic confidence, for pediatric patients undergoing high-resolution computed tomography (HRCT). During the last 2 years, a total number of 20 children up to 10 years old with a clinical presentation of chronic bronchitis underwent HRCT in our department's 64-detector row CT scanner using the iDose IR algorithm, with almost similar image settings (80kVp, 40-50 mAs). CT images were reconstructed with all iDose levels (level 1 to 7) as well as with filtered-back projection (FBP) algorithm. Subjective image quality was evaluated by 2 experienced radiologists in terms of image noise, sharpness, contrast and diagnostic acceptability using a 5-point scale (1=excellent image, 5=non-acceptable image). Artifacts existance was also pointed out. All mean scores from both radiologists corresponded to satisfactory image quality (score ≤3), even with the FBP algorithm use. Almost excellent (score <2) overall image quality was achieved with iDose levels 5 to 7, but oversmoothing artifacts appearing with iDose levels 6 and 7 affected the diagnostic confidence. In conclusion, the use of iDose level 5 enables almost excellent image quality without considerable artifacts affecting the diagnosis. Further evaluation is needed in order to draw more precise conclusions. (paper)
Indian Academy of Sciences (India)
ticians but also forms the foundation of computer science. Two ... with methods of developing algorithms for solving a variety of problems but ... applications of computers in science and engineer- ... numerical calculus are as important. We will ...
Some free boundary problems in potential flow regime usinga based level set method
Energy Technology Data Exchange (ETDEWEB)
Garzon, M.; Bobillo-Ares, N.; Sethian, J.A.
2008-12-09
Recent advances in the field of fluid mechanics with moving fronts are linked to the use of Level Set Methods, a versatile mathematical technique to follow free boundaries which undergo topological changes. A challenging class of problems in this context are those related to the solution of a partial differential equation posed on a moving domain, in which the boundary condition for the PDE solver has to be obtained from a partial differential equation defined on the front. This is the case of potential flow models with moving boundaries. Moreover the fluid front will possibly be carrying some material substance which will diffuse in the front and be advected by the front velocity, as for example the use of surfactants to lower surface tension. We present a Level Set based methodology to embed this partial differential equations defined on the front in a complete Eulerian framework, fully avoiding the tracking of fluid particles and its known limitations. To show the advantages of this approach in the field of Fluid Mechanics we present in this work one particular application: the numerical approximation of a potential flow model to simulate the evolution and breaking of a solitary wave propagating over a slopping bottom and compare the level set based algorithm with previous front tracking models.
A level set method for cupping artifact correction in cone-beam CT
International Nuclear Information System (INIS)
Xie, Shipeng; Li, Haibo; Ge, Qi; Li, Chunming
2015-01-01
Purpose: To reduce cupping artifacts and improve the contrast-to-noise ratio in cone-beam computed tomography (CBCT). Methods: A level set method is proposed to reduce cupping artifacts in the reconstructed image of CBCT. The authors derive a local intensity clustering property of the CBCT image and define a local clustering criterion function of the image intensities in a neighborhood of each point. This criterion function defines an energy in terms of the level set functions, which represent a segmentation result and the cupping artifacts. The cupping artifacts are estimated as a result of minimizing this energy. Results: The cupping artifacts in CBCT are reduced by an average of 90%. The results indicate that the level set-based algorithm is practical and effective for reducing the cupping artifacts and preserving the quality of the reconstructed image. Conclusions: The proposed method focuses on the reconstructed image without requiring any additional physical equipment, is easily implemented, and provides cupping correction through a single-scan acquisition. The experimental results demonstrate that the proposed method successfully reduces the cupping artifacts
LaHood, Benjamin R; Andrew, Nicholas H; Goggin, Michael
Cataract surgery is the most commonly performed surgical procedure in many developed countries. Postoperative endophthalmitis is a rare complication with potentially devastating visual outcomes. Currently, there is no global consensus regarding antibiotic prophylaxis in cataract surgery despite growing evidence of the benefits of prophylactic intracameral cefuroxime at the conclusion of surgery. The decision about which antibiotic regimen to use is further complicated in patients reporting penicillin allergy. Historic statistics suggesting crossreactivity of penicillins and cephalosporins have persisted into modern surgery. It is important for ophthalmologists to consider all available antibiotic options and have an up-to-date knowledge of antibiotic crossreactivity when faced with the dilemma of choosing appropriate antibiotic prophylaxis for patients undergoing cataract surgery with a history of penicillin allergy. Each option carries risks, and the choice may have medicolegal implications in the event of an adverse outcome. We assess the options for antibiotic prophylaxis in cataract surgery in the setting of penicillin allergy and provide an algorithm to assist decision-making for individual patients. Crown Copyright © 2017. Published by Elsevier Inc. All rights reserved.
Expediting Combinatorial Data Set Analysis by Combining Human and Algorithmic Analysis.
Stein, Helge Sören; Jiao, Sally; Ludwig, Alfred
2017-01-09
A challenge in combinatorial materials science remains the efficient analysis of X-ray diffraction (XRD) data and its correlation to functional properties. Rapid identification of phase-regions and proper assignment of corresponding crystal structures is necessary to keep pace with the improved methods for synthesizing and characterizing materials libraries. Therefore, a new modular software called htAx (high-throughput analysis of X-ray and functional properties data) is presented that couples human intelligence tasks used for "ground-truth" phase-region identification with subsequent unbiased verification by an algorithm to efficiently analyze which phases are present in a materials library. Identified phases and phase-regions may then be correlated to functional properties in an expedited manner. For the functionality of htAx to be proven, two previously published XRD benchmark data sets of the materials systems Al-Cr-Fe-O and Ni-Ti-Cu are analyzed by htAx. The analysis of ∼1000 XRD patterns takes less than 1 day with htAx. The proposed method reliably identifies phase-region boundaries and robustly identifies multiphase structures. The method also addresses the problem of identifying regions with previously unpublished crystal structures using a special daisy ternary plot.
Clustering for Binary Data Sets by Using Genetic Algorithm-Incremental K-means
Saharan, S.; Baragona, R.; Nor, M. E.; Salleh, R. M.; Asrah, N. M.
2018-04-01
This research was initially driven by the lack of clustering algorithms that specifically focus in binary data. To overcome this gap in knowledge, a promising technique for analysing this type of data became the main subject in this research, namely Genetic Algorithms (GA). For the purpose of this research, GA was combined with the Incremental K-means (IKM) algorithm to cluster the binary data streams. In GAIKM, the objective function was based on a few sufficient statistics that may be easily and quickly calculated on binary numbers. The implementation of IKM will give an advantage in terms of fast convergence. The results show that GAIKM is an efficient and effective new clustering algorithm compared to the clustering algorithms and to the IKM itself. In conclusion, the GAIKM outperformed other clustering algorithms such as GCUK, IKM, Scalable K-means (SKM) and K-means clustering and paves the way for future research involving missing data and outliers.
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.
Xu, Shaoping; Hu, Lingyan; Yang, Xiaohui
2016-01-01
The performance of conventional denoising algorithms is usually controlled by one or several parameters whose optimal settings depend on the contents of the processed images and the characteristics of the noises. Among these parameters, noise level is a fundamental parameter that is always assumed to be known by most of the existing denoising algorithms (so-called nonblind denoising algorithms), which largely limits the applicability of these nonblind denoising algorithms in many applications. Moreover, these nonblind algorithms do not always achieve the best denoised images in visual quality even when fed with the actual noise level parameter. To address these shortcomings, in this paper we propose a new quality-aware features-based noise level estimator (NLE), which consists of quality-aware features extraction and optimal noise level parameter prediction. First, considering that image local contrast features convey important structural information that is closely related to image perceptual quality, we utilize the marginal statistics of two local contrast operators, i.e., the gradient magnitude and the Laplacian of Gaussian (LOG), to extract quality-aware features. The proposed quality-aware features have very low computational complexity, making them well suited for time-constrained applications. Then we propose a learning-based framework where the noise level parameter is estimated based on the quality-aware features. Based on the proposed NLE, we develop a blind block matching and three-dimensional filtering (BBM3D) denoising algorithm which is capable of effectively removing additive white Gaussian noise, even coupled with impulse noise. The noise level parameter of the BBM3D algorithm is automatically tuned according to the quality-aware features, guaranteeing the best performance. As such, the classical block matching and three-dimensional algorithm can be transformed into a blind one in an unsupervised manner. Experimental results demonstrate that the
Topology optimization of hyperelastic structures using a level set method
Chen, Feifei; Wang, Yiqiang; Wang, Michael Yu; Zhang, Y. F.
2017-12-01
Soft rubberlike materials, due to their inherent compliance, are finding widespread implementation in a variety of applications ranging from assistive wearable technologies to soft material robots. Structural design of such soft and rubbery materials necessitates the consideration of large nonlinear deformations and hyperelastic material models to accurately predict their mechanical behaviour. In this paper, we present an effective level set-based topology optimization method for the design of hyperelastic structures that undergo large deformations. The method incorporates both geometric and material nonlinearities where the strain and stress measures are defined within the total Lagrange framework and the hyperelasticity is characterized by the widely-adopted Mooney-Rivlin material model. A shape sensitivity analysis is carried out, in the strict sense of the material derivative, where the high-order terms involving the displacement gradient are retained to ensure the descent direction. As the design velocity enters into the shape derivative in terms of its gradient and divergence terms, we develop a discrete velocity selection strategy. The whole optimization implementation undergoes a two-step process, where the linear optimization is first performed and its optimized solution serves as the initial design for the subsequent nonlinear optimization. It turns out that this operation could efficiently alleviate the numerical instability and facilitate the optimization process. To demonstrate the validity and effectiveness of the proposed method, three compliance minimization problems are studied and their optimized solutions present significant mechanical benefits of incorporating the nonlinearities, in terms of remarkable enhancement in not only the structural stiffness but also the critical buckling load.
Segmenting the Parotid Gland using Registration and Level Set Methods
DEFF Research Database (Denmark)
Hollensen, Christian; Hansen, Mads Fogtmann; Højgaard, Liselotte
. The method was evaluated on a test set consisting of 8 corresponding data sets. The attained total volume Dice coefficient and mean Haussdorff distance were 0.61 ± 0.20 and 15.6 ± 7.4 mm respectively. The method has improvement potential which could be exploited in order for clinical introduction....
Multiatlas segmentation of thoracic and abdominal anatomy with level set-based local search.
Schreibmann, Eduard; Marcus, David M; Fox, Tim
2014-07-08
Segmentation of organs at risk (OARs) remains one of the most time-consuming tasks in radiotherapy treatment planning. Atlas-based segmentation methods using single templates have emerged as a practical approach to automate the process for brain or head and neck anatomy, but pose significant challenges in regions where large interpatient variations are present. We show that significant changes are needed to autosegment thoracic and abdominal datasets by combining multi-atlas deformable registration with a level set-based local search. Segmentation is hierarchical, with a first stage detecting bulk organ location, and a second step adapting the segmentation to fine details present in the patient scan. The first stage is based on warping multiple presegmented templates to the new patient anatomy using a multimodality deformable registration algorithm able to cope with changes in scanning conditions and artifacts. These segmentations are compacted in a probabilistic map of organ shape using the STAPLE algorithm. Final segmentation is obtained by adjusting the probability map for each organ type, using customized combinations of delineation filters exploiting prior knowledge of organ characteristics. Validation is performed by comparing automated and manual segmentation using the Dice coefficient, measured at an average of 0.971 for the aorta, 0.869 for the trachea, 0.958 for the lungs, 0.788 for the heart, 0.912 for the liver, 0.884 for the kidneys, 0.888 for the vertebrae, 0.863 for the spleen, and 0.740 for the spinal cord. Accurate atlas segmentation for abdominal and thoracic regions can be achieved with the usage of a multi-atlas and perstructure refinement strategy. To improve clinical workflow and efficiency, the algorithm was embedded in a software service, applying the algorithm automatically on acquired scans without any user interaction.
SMOS/SMAP Synergy for SMAP Level 2 Soil Moisture Algorithm Evaluation
Bindlish, Rajat; Jackson, Thomas J.; Zhao, Tianjie; Cosh, Michael; Chan, Steven; O'Neill, Peggy; Njoku, Eni; Colliander, Andreas; Kerr, Yann
2011-01-01
ancillary data) were used to correct for surface temperature effects and to derive microwave emissivity. ECMWF data were also used for precipitation forecasts, presence of snow, and frozen ground. Vegetation options are described below. One year of soil moisture observations from a set of four watersheds in the U.S. were used to evaluate four different retrieval methodologies: (1) SMOS soil moisture estimates (version 400), (2) SeA soil moisture estimates using the SMOS/SMAP data with SMOS estimated vegetation optical depth, which is part of the SMOS level 2 product, (3) SeA soil moisture estimates using the SMOS/SMAP data and the MODIS-based vegetation climatology data, and (4) SeA soil moisture estimates using the SMOS/SMAP data and actual MODIS observations. The use of SMOS real-world global microwave observations and the analyses described here will help in the development and selection of different land surface parameters and ancillary observations needed for the SMAP soil moisture algorithms. These investigations will greatly improve the quality and reliability of this SMAP product at launch.
Reisner, A. T.; Khitrov, M. Y.; Chen, L.; Blood, A.; Wilkins, K.; Doyle, W.; Wilcox, S.; Denison, T.; Reifman, J.
2013-01-01
Summary Background Advanced decision-support capabilities for prehospital trauma care may prove effective at improving patient care. Such functionality would be possible if an analysis platform were connected to a transport vital-signs monitor. In practice, there are technical challenges to implementing such a system. Not only must each individual component be reliable, but, in addition, the connectivity between components must be reliable. Objective We describe the development, validation, and deployment of the Automated Processing of Physiologic Registry for Assessment of Injury Severity (APPRAISE) platform, intended to serve as a test bed to help evaluate the performance of decision-support algorithms in a prehospital environment. Methods We describe the hardware selected and the software implemented, and the procedures used for laboratory and field testing. Results The APPRAISE platform met performance goals in both laboratory testing (using a vital-sign data simulator) and initial field testing. After its field testing, the platform has been in use on Boston MedFlight air ambulances since February of 2010. Conclusion These experiences may prove informative to other technology developers and to healthcare stakeholders seeking to invest in connected electronic systems for prehospital as well as in-hospital use. Our experiences illustrate two sets of important questions: are the individual components reliable (e.g., physical integrity, power, core functionality, and end-user interaction) and is the connectivity between components reliable (e.g., communication protocols and the metadata necessary for data interpretation)? While all potential operational issues cannot be fully anticipated and eliminated during development, thoughtful design and phased testing steps can reduce, if not eliminate, technical surprises. PMID:24155791
Algorithms and programs for processing of satellite data on ozone layer and UV radiation levels
International Nuclear Information System (INIS)
Borkovskij, N.B.; Ivanyukovich, V.A.
2012-01-01
Some algorithms and programs for automatic retrieving and processing ozone layer satellite data are discussed. These techniques are used for reliable short-term UV-radiation levels forecasting. (authors)
Seldner, K.
1977-01-01
An algorithm was developed to optimally control the traffic signals at each intersection using a discrete time traffic model applicable to heavy or peak traffic. Off line optimization procedures were applied to compute the cycle splits required to minimize the lengths of the vehicle queues and delay at each intersection. The method was applied to an extensive traffic network in Toledo, Ohio. Results obtained with the derived optimal settings are compared with the control settings presently in use.
Indian Academy of Sciences (India)
algorithm design technique called 'divide-and-conquer'. One of ... Turtle graphics, September. 1996. 5. ... whole list named 'PO' is a pointer to the first element of the list; ..... Program for computing matrices X and Y and placing the result in C *).
Indian Academy of Sciences (India)
algorithm that it is implicitly understood that we know how to generate the next natural ..... Explicit comparisons are made in line (1) where maximum and minimum is ... It can be shown that the function T(n) = 3/2n -2 is the solution to the above ...
PixTrig: a Level 2 track finding algorithm based on pixel detector
Baratella, A; Morettini, P; Parodi, F
2000-01-01
This note describes an algorithm for track search at Level 2 based on pixel detector. Using three pixel clusters we can produce a reconstruction of the track parameter in both z and R-phi plane. These track segments can be used as seed for more sophisticated track finding algorithms or used directly, especially when impact parameter resolution is crucial. The algorithm efficiency is close to 90% for pt > 1 GeV/c and the processing time is small enough to allow a complete detector reconstruction (non RoI guided) within the Level 2 processing.
Goal oriented Mathematics Survey at Preparatory Level- Revised set ...
African Journals Online (AJOL)
This cross sectional study design on mathematical syllabi at preparatory levels of the high schools was to investigate the efficiency of the subject at preparatory level education serving as a basis for several streams, like Natural science, Technology, Computer Science, Health Science and Agriculture found at tertiary levels.
Directory of Open Access Journals (Sweden)
T. Nakamura
2012-07-01
Full Text Available Nowadays, for the estimation of traffic demand or people flow, modelling route choice activity in road networks is an important task and many algorithms have been developed to generate route choice sets. However, developing an algorithm based on a small amount of data that can be applied generally within a metropolitan area is difficult. This is because the characteristics of road networks vary widely. On the other hand, recently, the collection of people movement data has lately become much easier, especially through mobile phones. Lately, most mobile phones include GPS functionality. Given this background, we propose a data-oriented algorithm to generate route choice sets using mobile phone GPS data. GPS data contain a number of measurement errors; hence, they must be adjusted to account for these errors before use in advanced people movement analysis. However, this is time-consuming and expensive, because an enormous amount of daily data can be obtained. Hence, the objective of this study is to develop an algorithm that can easily manage GPS data. Specifically, at first movement data from all GPS data are selected by calculating the speed. Next, the nearest roads in the road network are selected from the GPS location and count such data for each road. Then An algorithm based on the GSP (Gateway Shortest Path algorithm is proposed, which searches the shortest path through a given gateway. In the proposed algorithm, the road for which the utilization volume calculated by GPS data is large is selected as the gateway. Thus, route choice sets that are based on trends in real GPS data are generated. To evaluate the proposed method, GPS data from 0.7 million people a year in Japan and DRM (Digital Road Map as the road network are used. DRM is one of the most detailed road networks in Japan. Route choice sets using the proposed algorithm are generated and the cover rate of the utilization volume of each road under evaluation is calculated. As a
Level set segmentation of bovine corpora lutea in ex situ ovarian ultrasound images
Directory of Open Access Journals (Sweden)
Adams Gregg P
2008-08-01
Full Text Available Abstract Background The objective of this study was to investigate the viability of level set image segmentation methods for the detection of corpora lutea (corpus luteum, CL boundaries in ultrasonographic ovarian images. It was hypothesized that bovine CL boundaries could be located within 1–2 mm by a level set image segmentation methodology. Methods Level set methods embed a 2D contour in a 3D surface and evolve that surface over time according to an image-dependent speed function. A speed function suitable for segmentation of CL's in ovarian ultrasound images was developed. An initial contour was manually placed and contour evolution was allowed to proceed until the rate of change of the area was sufficiently small. The method was tested on ovarian ultrasonographic images (n = 8 obtained ex situ. A expert in ovarian ultrasound interpretation delineated CL boundaries manually to serve as a "ground truth". Accuracy of the level set segmentation algorithm was determined by comparing semi-automatically determined contours with ground truth contours using the mean absolute difference (MAD, root mean squared difference (RMSD, Hausdorff distance (HD, sensitivity, and specificity metrics. Results and discussion The mean MAD was 0.87 mm (sigma = 0.36 mm, RMSD was 1.1 mm (sigma = 0.47 mm, and HD was 3.4 mm (sigma = 2.0 mm indicating that, on average, boundaries were accurate within 1–2 mm, however, deviations in excess of 3 mm from the ground truth were observed indicating under- or over-expansion of the contour. Mean sensitivity and specificity were 0.814 (sigma = 0.171 and 0.990 (sigma = 0.00786, respectively, indicating that CLs were consistently undersegmented but rarely did the contour interior include pixels that were judged by the human expert not to be part of the CL. It was observed that in localities where gradient magnitudes within the CL were strong due to high contrast speckle, contour expansion stopped too early. Conclusion The
Xu, Shaoping; Zeng, Xiaoxia; Jiang, Yinnan; Tang, Yiling
2018-01-01
We proposed a noniterative principal component analysis (PCA)-based noise level estimation (NLE) algorithm that addresses the problem of estimating the noise level with a two-step scheme. First, we randomly extracted a number of raw patches from a given noisy image and took the smallest eigenvalue of the covariance matrix of the raw patches as the preliminary estimation of the noise level. Next, the final estimation was directly obtained with a nonlinear mapping (rectification) function that was trained on some representative noisy images corrupted with different known noise levels. Compared with the state-of-art NLE algorithms, the experiment results show that the proposed NLE algorithm can reliably infer the noise level and has robust performance over a wide range of image contents and noise levels, showing a good compromise between speed and accuracy in general.
Validation Study of a Predictive Algorithm to Evaluate Opioid Use Disorder in a Primary Care Setting
Sharma, Maneesh; Lee, Chee; Kantorovich, Svetlana; Tedtaotao, Maria; Smith, Gregory A.
2017-01-01
Background: Opioid abuse in chronic pain patients is a major public health issue. Primary care providers are frequently the first to prescribe opioids to patients suffering from pain, yet do not always have the time or resources to adequately evaluate the risk of opioid use disorder (OUD). Purpose: This study seeks to determine the predictability of aberrant behavior to opioids using a comprehensive scoring algorithm (“profile”) incorporating phenotypic and, more uniquely, genotypic risk factors. Methods and Results: In a validation study with 452 participants diagnosed with OUD and 1237 controls, the algorithm successfully categorized patients at high and moderate risk of OUD with 91.8% sensitivity. Regardless of changes in the prevalence of OUD, sensitivity of the algorithm remained >90%. Conclusion: The algorithm correctly stratifies primary care patients into low-, moderate-, and high-risk categories to appropriately identify patients in need for additional guidance, monitoring, or treatment changes. PMID:28890908
Automated Algorithms for Quantum-Level Accuracy in Atomistic Simulations: LDRD Final Report.
Energy Technology Data Exchange (ETDEWEB)
Thompson, Aidan Patrick; Schultz, Peter Andrew; Crozier, Paul; Moore, Stan Gerald; Swiler, Laura Painton; Stephens, John Adam; Trott, Christian Robert; Foiles, Stephen Martin; Tucker, Garritt J. (Drexel University)
2014-09-01
This report summarizes the result of LDRD project 12-0395, titled "Automated Algorithms for Quantum-level Accuracy in Atomistic Simulations." During the course of this LDRD, we have developed an interatomic potential for solids and liquids called Spectral Neighbor Analysis Poten- tial (SNAP). The SNAP potential has a very general form and uses machine-learning techniques to reproduce the energies, forces, and stress tensors of a large set of small configurations of atoms, which are obtained using high-accuracy quantum electronic structure (QM) calculations. The local environment of each atom is characterized by a set of bispectrum components of the local neighbor density projected on to a basis of hyperspherical harmonics in four dimensions. The SNAP coef- ficients are determined using weighted least-squares linear regression against the full QM training set. This allows the SNAP potential to be fit in a robust, automated manner to large QM data sets using many bispectrum components. The calculation of the bispectrum components and the SNAP potential are implemented in the LAMMPS parallel molecular dynamics code. Global optimization methods in the DAKOTA software package are used to seek out good choices of hyperparameters that define the overall structure of the SNAP potential. FitSnap.py, a Python-based software pack- age interfacing to both LAMMPS and DAKOTA is used to formulate the linear regression problem, solve it, and analyze the accuracy of the resultant SNAP potential. We describe a SNAP potential for tantalum that accurately reproduces a variety of solid and liquid properties. Most significantly, in contrast to existing tantalum potentials, SNAP correctly predicts the Peierls barrier for screw dislocation motion. We also present results from SNAP potentials generated for indium phosphide (InP) and silica (SiO 2 ). We describe efficient algorithms for calculating SNAP forces and energies in molecular dynamics simulations using massively parallel computers
Indian Academy of Sciences (India)
will become clear in the next article when we discuss a simple logo like programming language. ... Rod B may be used as an auxiliary store. The problem is to find an algorithm which performs this task. ... No disks are moved from A to Busing C as auxiliary rod. • move _disk (A, C);. (No + l)th disk is moved from A to C directly ...
Lesion removal and lesion addition algorithms in lung volumetric data sets for perception studies
Madsen, Mark T.; Berbaum, Kevin S.; Ellingson, Andrew; Thompson, Brad H.; Mullan, Brian F.
2006-03-01
Image perception studies of medical images provide important information about how radiologists interpret images and insights for reducing reading errors. In the past, perception studies have been difficult to perform using clinical imaging studies because of the problems associated with obtaining images demonstrating proven abnormalities and appropriate normal control images. We developed and evaluated interactive software that allows the seamless removal of abnormal areas from CT lung image sets. We have also developed interactive software for capturing lung lesions in a database where they can be added to lung CT studies. The efficacy of the software to remove abnormal areas of lung CT studies was evaluated psychophysically by having radiologists select the one altered image from a display of four. The software for adding lesions was evaluated by having radiologists classify displayed CT slices with lesions as real or artificial scaled to 3 levels of confidence. The results of these experiments demonstrated that the radiologist had difficulty in distinguishing the raw clinical images from those that had been altered. We conclude that this software can be used to create experimental normal control and "proven" lesion data sets for volumetric CT of the lung fields. We also note that this software can be easily adapted to work with other tissue besides lung and that it can be adapted to other digital imaging modalities.
Directory of Open Access Journals (Sweden)
Zhang Jing
2015-06-01
Full Text Available The connected dominating set (CDS has become a well-known approach for constructing a virtual backbone in wireless sensor networks. Then traffic can forwarded by the virtual backbone and other nodes turn off their radios to save energy. Furthermore, a smaller CDS incurs fewer interference problems. However, constructing a minimum CDS is an NP-hard problem, and thus most researchers concentrate on how to derive approximate algorithms. In this paper, a novel algorithm based on the induced tree of the crossed cube (ITCC is presented. The ITCC is to find a maximal independent set (MIS, which is based on building an induced tree of the crossed cube network, and then to connect the MIS nodes to form a CDS. The priority of an induced tree is determined according to a new parameter, the degree of the node in the square of a graph. This paper presents the proof that the ITCC generates a CDS with a lower approximation ratio. Furthermore, it is proved that the cardinality of the induced trees is a Fibonacci sequence, and an upper bound to the number of the dominating set is established. The simulations show that the algorithm provides the smallest CDS size compared with some other traditional algorithms.
Du, Yuncheng; Budman, Hector M; Duever, Thomas A
2016-06-01
Accurate automated quantitative analysis of living cells based on fluorescence microscopy images can be very useful for fast evaluation of experimental outcomes and cell culture protocols. In this work, an algorithm is developed for fast differentiation of normal and apoptotic viable Chinese hamster ovary (CHO) cells. For effective segmentation of cell images, a stochastic segmentation algorithm is developed by combining a generalized polynomial chaos expansion with a level set function-based segmentation algorithm. This approach provides a probabilistic description of the segmented cellular regions along the boundary, from which it is possible to calculate morphological changes related to apoptosis, i.e., the curvature and length of a cell's boundary. These features are then used as inputs to a support vector machine (SVM) classifier that is trained to distinguish between normal and apoptotic viable states of CHO cell images. The use of morphological features obtained from the stochastic level set segmentation of cell images in combination with the trained SVM classifier is more efficient in terms of differentiation accuracy as compared with the original deterministic level set method.
International Nuclear Information System (INIS)
Park, Gee Yong; Seong, Poong Hyun
1994-01-01
In order to reduce the load of tuning works by trial-and-error for obtaining the best control performance of conventional fuzzy control algorithm, a fuzzy control algorithm with learning function is investigated in this work. This fuzzy control algorithm can make its rule base and tune the membership functions automatically by use of learning function which needs the data from the control actions of the plant operator or other controllers. Learning process in fuzzy control algorithm is to find the optimal values of parameters, which consist of the membership functions and the rule base, by gradient descent method. Learning speed of gradient descent is significantly improved in this work with the addition of modified momentum. This control algorithm is applied to the steam generator level control by computer simulations. The simulation results confirm the good performance of this control algorithm for level control and show that the fuzzy learning algorithm has the generalization capability for the relation of inputs and outputs and it also has the excellent capability of disturbance rejection
A three-step algorithm for CANDECOMP/PARAFAC analysis of large data sets with multicollinearity
Kiers, H.A.L.
1998-01-01
Fitting the CANDECOMP/PARAFAC model by the standard alternating least squares algorithm often requires very many iterations. One case in point is that of analysing data with mild to severe multicollinearity. If, in addition, the size of the data is large, the computation of one CANDECOMP/PARAFAC
Development of fuzzy algorithm with learning function for nuclear steam generator level control
International Nuclear Information System (INIS)
Park, Gee Yong; Seong, Poong Hyun
1993-01-01
A fuzzy algorithm with learning function is applied to the steam generator level control of nuclear power plant. This algorithm can make its rule base and membership functions suited for steam generator level control by use of the data obtained from the control actions of a skilled operator or of other controllers (i.e., PID controller). The rule base of fuzzy controller with learning function is divided into two parts. One part of the rule base is provided to level control of steam generator at low power level (0 % - 30 % of full power) and the other to level control at high power level (30 % - 100 % of full power). Response time of steam generator level control at low power range with this rule base is shown to be shorter than that of fuzzy controller with direct inference. (Author)
Trusting Politicians and Institutions in a Multi-Level Setting
DEFF Research Database (Denmark)
Hansen, Sune Welling; Kjær, Ulrik
Trust in government and in politicians is a very crucial prerequisite for democratic processes. This goes not only for the national level of government but also for the regional and local. We make use of a large scale survey among citizens in Denmark to evaluate trust in politicians at different...... formation processes can negatively influence trust in the mayor and the councilors. Reaching out for the local power by being disloyal to one’s own party or by breaking deals already made can sometimes secure the mayoralty but it comes with a prize: lower trust among the electorate....
High-level waste tank farm set point document
International Nuclear Information System (INIS)
Anthony, J.A. III.
1995-01-01
Setpoints for nuclear safety-related instrumentation are required for actions determined by the design authorization basis. Minimum requirements need to be established for assuring that setpoints are established and held within specified limits. This document establishes the controlling methodology for changing setpoints of all classifications. The instrumentation under consideration involve the transfer, storage, and volume reduction of radioactive liquid waste in the F- and H-Area High-Level Radioactive Waste Tank Farms. The setpoint document will encompass the PROCESS AREA listed in the Safety Analysis Report (SAR) (DPSTSA-200-10 Sup 18) which includes the diversion box HDB-8 facility. In addition to the PROCESS AREAS listed in the SAR, Building 299-H and the Effluent Transfer Facility (ETF) are also included in the scope
High-level waste tank farm set point document
Energy Technology Data Exchange (ETDEWEB)
Anthony, J.A. III
1995-01-15
Setpoints for nuclear safety-related instrumentation are required for actions determined by the design authorization basis. Minimum requirements need to be established for assuring that setpoints are established and held within specified limits. This document establishes the controlling methodology for changing setpoints of all classifications. The instrumentation under consideration involve the transfer, storage, and volume reduction of radioactive liquid waste in the F- and H-Area High-Level Radioactive Waste Tank Farms. The setpoint document will encompass the PROCESS AREA listed in the Safety Analysis Report (SAR) (DPSTSA-200-10 Sup 18) which includes the diversion box HDB-8 facility. In addition to the PROCESS AREAS listed in the SAR, Building 299-H and the Effluent Transfer Facility (ETF) are also included in the scope.
A set of particle locating algorithms not requiring face belonging to cell connectivity data
Sani, M.; Saidi, M. S.
2009-10-01
Existing efficient directed particle locating (host determination) algorithms rely on the face belonging to cell relationship (F2C) to find the next cell on the search path and the cell in which the target is located. Recently, finite volume methods have been devised which do not need F2C. Therefore, existing search algorithms are not directly applicable (unless F2C is included). F2C is a major memory burden in grid description. If the memory benefit from these finite volume methods are desirable new search algorithms should be devised. In this work two new algorithms (line of sight and closest cell) are proposed which do not need F2C. They are based on the structure of the sparse coefficient matrix involved (stored for example in the compressed row storage, CRS, format) to determine the next cell. Since F2C is not available, testing a cell for the presence of the target is not possible. Therefore, the proposed methods may wrongly mark a nearby cell as the host in some rare cases. The issue of importance of finding the correct host cell (not wrongly hitting its neighbor) is addressed. Quantitative measures are introduced to assess the efficiency of the methods and comparison is made for typical grid types used in computational fluid dynamics. In comparison, the closest cell method, having a lower computational cost than the family of line of sight and the existing efficient maximum dot product methods, gives a very good performance with tolerable and harmless wrong hits. If more accuracy is needed, the method of approximate line of sight then closest cell (LS-A-CC) is recommended.
Parasyris, Antonios E.; Spanoudaki, Katerina; Kampanis, Nikolaos A.
2016-04-01
Groundwater level monitoring networks provide essential information for water resources management, especially in areas with significant groundwater exploitation for agricultural and domestic use. Given the high maintenance costs of these networks, development of tools, which can be used by regulators for efficient network design is essential. In this work, a monitoring network optimisation tool is presented. The network optimisation tool couples geostatistical modelling based on the Spartan family variogram with a genetic algorithm method and is applied to Mires basin in Crete, Greece, an area of high socioeconomic and agricultural interest, which suffers from groundwater overexploitation leading to a dramatic decrease of groundwater levels. The purpose of the optimisation tool is to determine which wells to exclude from the monitoring network because they add little or no beneficial information to groundwater level mapping of the area. Unlike previous relevant investigations, the network optimisation tool presented here uses Ordinary Kriging with the recently-established non-differentiable Spartan variogram for groundwater level mapping, which, based on a previous geostatistical study in the area leads to optimal groundwater level mapping. Seventy boreholes operate in the area for groundwater abstraction and water level monitoring. The Spartan variogram gives overall the most accurate groundwater level estimates followed closely by the power-law model. The geostatistical model is coupled to an integer genetic algorithm method programmed in MATLAB 2015a. The algorithm is used to find the set of wells whose removal leads to the minimum error between the original water level mapping using all the available wells in the network and the groundwater level mapping using the reduced well network (error is defined as the 2-norm of the difference between the original mapping matrix with 70 wells and the mapping matrix of the reduced well network). The solution to the
Multi-phase flow monitoring with electrical impedance tomography using level set based method
International Nuclear Information System (INIS)
Liu, Dong; Khambampati, Anil Kumar; Kim, Sin; Kim, Kyung Youn
2015-01-01
Highlights: • LSM has been used for shape reconstruction to monitor multi-phase flow using EIT. • Multi-phase level set model for conductivity is represented by two level set functions. • LSM handles topological merging and breaking naturally during evolution process. • To reduce the computational time, a narrowband technique was applied. • Use of narrowband and optimization approach results in efficient and fast method. - Abstract: In this paper, a level set-based reconstruction scheme is applied to multi-phase flow monitoring using electrical impedance tomography (EIT). The proposed scheme involves applying a narrowband level set method to solve the inverse problem of finding the interface between the regions having different conductivity values. The multi-phase level set model for the conductivity distribution inside the domain is represented by two level set functions. The key principle of the level set-based method is to implicitly represent the shape of interface as the zero level set of higher dimensional function and then solve a set of partial differential equations. The level set-based scheme handles topological merging and breaking naturally during the evolution process. It also offers several advantages compared to traditional pixel-based approach. Level set-based method for multi-phase flow is tested with numerical and experimental data. It is found that level set-based method has better reconstruction performance when compared to pixel-based method
Mind-sets, low-level exposures, and research
International Nuclear Information System (INIS)
Sagan, L.A.
1993-01-01
Much of our environmental policy is based on the notion that carcinogenic agents are harmful at even minuscule doses. From where does this thinking come? What is the scientific evidence that supports such policy? Moreover, why is the public willing to buy into this? Or is it the other way around: Has the scientific community bought into a paradigm that has its origins in public imagery? Or, most likely, are there interactions between the two? It is essential that we find out whether or not there are risks associated with low-level exposures to radiation. The author can see three obvious areas where the future depends on better information: The increasing radiation exposures resulting from the use of medical diagnostic and therapeutic practices need to be properly evaluated for safety; Environmental policies, which direct enormous resources to the reduction of small radiation exposures, needs to be put on a firmer scientific basis; The future of nuclear energy, dependent as it is on public acceptance, may well rely upon a better understanding of low-dose effects. Nuclear energy could provide an important solution of global warming and other possible environmental hazards, but will probably not be implemented as long as fear of low-dose radiation persists. Although an established paradigm has great resilience, it cannot resist the onslaught of inconsistent scientific observations or of the social value system that supports it. Only new research will enable us to determine if a paradigm shift is in order here
Evaluation of a fever-management algorithm in a pediatric cancer center in a low-resource setting.
Mukkada, Sheena; Smith, Cristel Kate; Aguilar, Delta; Sykes, April; Tang, Li; Dolendo, Mae; Caniza, Miguela A
2018-02-01
In low- and middle-income countries (LMICs), inconsistent or delayed management of fever contributes to poor outcomes among pediatric patients with cancer. We hypothesized that standardizing practice with a clinical algorithm adapted to local resources would improve outcomes. Therefore, we developed a resource-specific algorithm for fever management in Davao City, Philippines. The primary objective of this study was to evaluate adherence to the algorithm. This was a prospective cohort study of algorithm adherence to assess the types of deviation, reasons for deviation, and pathogens isolated. All pediatric oncology patients who were admitted with fever (defined as an axillary temperature >37.7°C on one occasion or ≥37.4°C on two occasions 1 hr apart) or who developed fever within 48 hr of admission were included. Univariate and multiple linear regression analyses were used to determine the relation between clinical predictors and length of hospitalization. During the study, 93 patients had 141 qualifying febrile episodes. Even though the algorithm was designed locally, deviations occurred in 70 (50%) of 141 febrile episodes on day 0, reflecting implementation barriers at the patient, provider, and institutional levels. There were 259 deviations during the first 7 days of admission in 92 (65%) of 141 patient episodes. Failure to identify high-risk patients, missed antimicrobial doses, and pathogen isolation were associated with prolonged hospitalization. Monitoring algorithm adherence helps in assessing the quality of pediatric oncology care in LMICs and identifying opportunities for improvement. Measures that decrease high-frequency/high-impact algorithm deviations may shorten hospitalizations and improve healthcare use in LMICs. © 2017 Wiley Periodicals, Inc.
A hybrid interface tracking - level set technique for multiphase flow with soluble surfactant
Shin, Seungwon; Chergui, Jalel; Juric, Damir; Kahouadji, Lyes; Matar, Omar K.; Craster, Richard V.
2018-04-01
A formulation for soluble surfactant transport in multiphase flows recently presented by Muradoglu and Tryggvason (JCP 274 (2014) 737-757) [17] is adapted to the context of the Level Contour Reconstruction Method, LCRM, (Shin et al. IJNMF 60 (2009) 753-778, [8]) which is a hybrid method that combines the advantages of the Front-tracking and Level Set methods. Particularly close attention is paid to the formulation and numerical implementation of the surface gradients of surfactant concentration and surface tension. Various benchmark tests are performed to demonstrate the accuracy of different elements of the algorithm. To verify surfactant mass conservation, values for surfactant diffusion along the interface are compared with the exact solution for the problem of uniform expansion of a sphere. The numerical implementation of the discontinuous boundary condition for the source term in the bulk concentration is compared with the approximate solution. Surface tension forces are tested for Marangoni drop translation. Our numerical results for drop deformation in simple shear are compared with experiments and results from previous simulations. All benchmarking tests compare well with existing data thus providing confidence that the adapted LCRM formulation for surfactant advection and diffusion is accurate and effective in three-dimensional multiphase flows with a structured mesh. We also demonstrate that this approach applies easily to massively parallel simulations.
Directory of Open Access Journals (Sweden)
A. Sreenivasa Murthy
2014-11-01
Full Text Available With the spurt in the amount of data (Image, video, audio, speech, & text available on the net, there is a huge demand for memory & bandwidth savings. One has to achieve this, by maintaining the quality & fidelity of the data acceptable to the end user. Wavelet transform is an important and practical tool for data compression. Set partitioning in hierarchal trees (SPIHT is a widely used compression algorithm for wavelet transformed images. Among all wavelet transform and zero-tree quantization based image compression algorithms SPIHT has become the benchmark state-of-the-art algorithm because it is simple to implement & yields good results. In this paper we present a comparative study of various wavelet families for image compression with SPIHT algorithm. We have conducted experiments with Daubechies, Coiflet, Symlet, Bi-orthogonal, Reverse Bi-orthogonal and Demeyer wavelet types. The resulting image quality is measured objectively, using peak signal-to-noise ratio (PSNR, and subjectively, using perceived image quality (human visual perception, HVP for short. The resulting reduction in the image size is quantified by compression ratio (CR.
Daciuk, J; Champarnaud, JM; Maurel, D
2003-01-01
This paper compares various methods for constructing minimal, deterministic, acyclic, finite-state automata (recognizers) from sets of words. Incremental, semi-incremental, and non-incremental methods have been implemented and evaluated.
A Novel Rough Set Reduct Algorithm for Medical Domain Based on Bee Colony Optimization
Suguna, N.; Thanushkodi, K.
2010-01-01
Feature selection refers to the problem of selecting relevant features which produce the most predictive outcome. In particular, feature selection task is involved in datasets containing huge number of features. Rough set theory has been one of the most successful methods used for feature selection. However, this method is still not able to find optimal subsets. This paper proposes a new feature selection method based on Rough set theory hybrid with Bee Colony Optimization (BCO) in an attempt...
A fuzzy logic algorithm to assign confidence levels to heart and respiratory rate time series
International Nuclear Information System (INIS)
Liu, J; McKenna, T M; Gribok, A; Reifman, J; Beidleman, B A; Tharion, W J
2008-01-01
We have developed a fuzzy logic-based algorithm to qualify the reliability of heart rate (HR) and respiratory rate (RR) vital-sign time-series data by assigning a confidence level to the data points while they are measured as a continuous data stream. The algorithm's membership functions are derived from physiology-based performance limits and mass-assignment-based data-driven characteristics of the signals. The assigned confidence levels are based on the reliability of each HR and RR measurement as well as the relationship between them. The algorithm was tested on HR and RR data collected from subjects undertaking a range of physical activities, and it showed acceptable performance in detecting four types of faults that result in low-confidence data points (receiver operating characteristic areas under the curve ranged from 0.67 (SD 0.04) to 0.83 (SD 0.03), mean and standard deviation (SD) over all faults). The algorithm is sensitive to noise in the raw HR and RR data and will flag many data points as low confidence if the data are noisy; prior processing of the data to reduce noise allows identification of only the most substantial faults. Depending on how HR and RR data are processed, the algorithm can be applied as a tool to evaluate sensor performance or to qualify HR and RR time-series data in terms of their reliability before use in automated decision-assist systems
McGovern, S.; Kollet, S. J.; Buerger, C. M.; Schwede, R. L.; Podlaha, O. G.
2017-12-01
). Novel basin modelling concept for simulating deformation from mechanical compaction using level sets. Computational Geosciences, SI:ECMOR XV, 1-14.[2] Bangerth, et. al. (2011). Algorithms and data structures for massively parallel generic adaptive finite element codes. ACM Transactions on Mathematical Software (TOMS), 38(2):14.
A Level-2 trigger algorithm for the identification of muons in the ATLAS Muon Spectrometer
Di Mattia, A; Dos Anjos, A; Baines, J T M; Bee, C P; Biglietti, M; Bogaerts, J A C; Boisvert, V; Bosman, M; Caron, B; Casado, M P; Cataldi, G; Cavalli, D; Cervetto, M; Comune, G; Conde-Muíño, P; De Santo, A; Díaz-Gómez, M; Dosil, M; Ellis, Nick; Emeliyanov, D; Epp, B; Falciano, S; Farilla, A; George, S; Ghete, V M; González, S; Grothe, M; Kabana, S; Khomich, A; Kilvington, G; Konstantinidis, N P; Kootz, A; Lowe, A; Luminari, L; Maeno, T; Masik, J; Meessen, C; Mello, A G; Merino, G; Moore, R; Morettini, P; Negri, A; Nikitin, N V; Nisati, A; Padilla, C; Panikashvili, N; Parodi, F; Pasqualucci, E; Pérez-Réale, V; Pinfold, J L; Pinto, P; Qian, Z; Resconi, S; Rosati, S; Sánchez, C; Santamarina-Rios, C; Scannicchio, D A; Schiavi, C; Segura, E; De Seixas, J M; Sivoklokov, S Yu; Soluk, R A; Stefanidis, E; Sushkov, S S; Sutton, M; Tapprogge, Stefan; Thomas, E; Touchard, F; Venda-Pinto, B; Vercesi, V; Werner, P; Wheeler, S; Wickens, F J; Wiedenmann, W; Wielers, M; Zobernig, G; Computing In High Energy Physics
2005-01-01
The ATLAS Level-2 trigger provides a software-based event selection after the initial Level-1 hardware trigger. For the muon events, the selection is decomposed in a number of broad steps: first, the Muon Spectrometer data are processed to give physics quantities associated to the muon track (standalone feature extraction) then, other detector data are used to refine the extracted features. The “µFast” algorithm performs the standalone feature extraction, providing a first reduction of the muon event rate from Level-1. It confirms muon track candidates with a precise measurement of the muon momentum. The algorithm is designed to be both conceptually simple and fast so as to be readily implemented in the demanding online environment in which the Level-2 selection code will run. Never-the-less its physics performance approaches, in some cases, that of the offline reconstruction algorithms. This paper describes the implemented algorithm together with the software techniques employed to increase its timing p...
Level-set segmentation of pulmonary nodules in megavolt electronic portal images using a CT prior
International Nuclear Information System (INIS)
Schildkraut, J. S.; Prosser, N.; Savakis, A.; Gomez, J.; Nazareth, D.; Singh, A. K.; Malhotra, H. K.
2010-01-01
Purpose: Pulmonary nodules present unique problems during radiation treatment due to nodule position uncertainty that is caused by respiration. The radiation field has to be enlarged to account for nodule motion during treatment. The purpose of this work is to provide a method of locating a pulmonary nodule in a megavolt portal image that can be used to reduce the internal target volume (ITV) during radiation therapy. A reduction in the ITV would result in a decrease in radiation toxicity to healthy tissue. Methods: Eight patients with nonsmall cell lung cancer were used in this study. CT scans that include the pulmonary nodule were captured with a GE Healthcare LightSpeed RT 16 scanner. Megavolt portal images were acquired with a Varian Trilogy unit equipped with an AS1000 electronic portal imaging device. The nodule localization method uses grayscale morphological filtering and level-set segmentation with a prior. The treatment-time portion of the algorithm is implemented on a graphical processing unit. Results: The method was retrospectively tested on eight cases that include a total of 151 megavolt portal image frames. The method reduced the nodule position uncertainty by an average of 40% for seven out of the eight cases. The treatment phase portion of the method has a subsecond execution time that makes it suitable for near-real-time nodule localization. Conclusions: A method was developed to localize a pulmonary nodule in a megavolt portal image. The method uses the characteristics of the nodule in a prior CT scan to enhance the nodule in the portal image and to identify the nodule region by level-set segmentation. In a retrospective study, the method reduced the nodule position uncertainty by an average of 40% for seven out of the eight cases studied.
GPU accelerated edge-region based level set evolution constrained by 2D gray-scale histogram.
Balla-Arabé, Souleymane; Gao, Xinbo; Wang, Bin
2013-07-01
Due to its intrinsic nature which allows to easily handle complex shapes and topological changes, the level set method (LSM) has been widely used in image segmentation. Nevertheless, LSM is computationally expensive, which limits its applications in real-time systems. For this purpose, we propose a new level set algorithm, which uses simultaneously edge, region, and 2D histogram information in order to efficiently segment objects of interest in a given scene. The computational complexity of the proposed LSM is greatly reduced by using the highly parallelizable lattice Boltzmann method (LBM) with a body force to solve the level set equation (LSE). The body force is the link with image data and is defined from the proposed LSE. The proposed LSM is then implemented using an NVIDIA graphics processing units to fully take advantage of the LBM local nature. The new algorithm is effective, robust against noise, independent to the initial contour, fast, and highly parallelizable. The edge and region information enable to detect objects with and without edges, and the 2D histogram information enable the effectiveness of the method in a noisy environment. Experimental results on synthetic and real images demonstrate subjectively and objectively the performance of the proposed method.
Qian, F; Li, G; Ruan, H; Jing, H; Liu, L
1999-09-10
A novel, to our knowledge, two-step digit-set-restricted modified signed-digit (MSD) addition-subtraction algorithm is proposed. With the introduction of the reference digits, the operand words are mapped into an intermediate carry word with all digits restricted to the set {1, 0} and an intermediate sum word with all digits restricted to the set {0, 1}, which can be summed to form the final result without carry generation. The operation can be performed in parallel by use of binary logic. An optical system that utilizes an electron-trapping device is suggested for accomplishing the required binary logic operations. By programming of the illumination of data arrays, any complex logic operations of multiple variables can be realized without additional temporal latency of the intermediate results. This technique has a high space-bandwidth product and signal-to-noise ratio. The main structure can be stacked to construct a compact optoelectronic MSD adder-subtracter.
Xiang, Min; Qu, Qinqin; Chen, Cheng; Tian, Li; Zeng, Lingkang
2017-11-01
To improve the reliability of communication service in smart distribution grid (SDG), an access selection algorithm based on dynamic network status and different service types for heterogeneous wireless networks was proposed. The network performance index values were obtained in real time by multimode terminal and the variation trend of index values was analyzed by the growth matrix. The index weights were calculated by entropy-weight and then modified by rough set to get the final weights. Combining the grey relational analysis to sort the candidate networks, and the optimum communication network is selected. Simulation results show that the proposed algorithm can implement dynamically access selection in heterogeneous wireless networks of SDG effectively and reduce the network blocking probability.
A parallel algorithm for switch-level timing simulation on a hypercube multiprocessor
Rao, Hariprasad Nannapaneni
1989-01-01
The parallel approach to speeding up simulation is studied, specifically the simulation of digital LSI MOS circuitry on the Intel iPSC/2 hypercube. The simulation algorithm is based on RSIM, an event driven switch-level simulator that incorporates a linear transistor model for simulating digital MOS circuits. Parallel processing techniques based on the concepts of Virtual Time and rollback are utilized so that portions of the circuit may be simulated on separate processors, in parallel for as large an increase in speed as possible. A partitioning algorithm is also developed in order to subdivide the circuit for parallel processing.
Ghafouri, H. R.; Mosharaf-Dehkordi, M.; Afzalan, B.
2017-07-01
A simulation-optimization model is proposed for identifying the characteristics of local immiscible NAPL contaminant sources inside aquifers. This model employs the UTCHEM 9.0 software as its simulator for solving the governing equations associated with the multi-phase flow in porous media. As the optimization model, a novel two-level saturation based Imperialist Competitive Algorithm (ICA) is proposed to estimate the parameters of contaminant sources. The first level consists of three parallel independent ICAs and plays as a pre-conditioner for the second level which is a single modified ICA. The ICA in the second level is modified by dividing each country into a number of provinces (smaller parts). Similar to countries in the classical ICA, these provinces are optimized by the assimilation, competition, and revolution steps in the ICA. To increase the diversity of populations, a new approach named knock the base method is proposed. The performance and accuracy of the simulation-optimization model is assessed by solving a set of two and three-dimensional problems considering the effects of different parameters such as the grid size, rock heterogeneity and designated monitoring networks. The obtained numerical results indicate that using this simulation-optimization model provides accurate results at a less number of iterations when compared with the model employing the classical one-level ICA. A model is proposed to identify characteristics of immiscible NAPL contaminant sources. The contaminant is immiscible in water and multi-phase flow is simulated. The model is a multi-level saturation-based optimization algorithm based on ICA. Each answer string in second level is divided into a set of provinces. Each ICA is modified by incorporating a new knock the base model.
Kotrri, Gynter; Fusch, Gerhard; Kwan, Celia; Choi, Dasol; Choi, Arum; Al Kafi, Nisreen; Rochow, Niels; Fusch, Christoph
2016-02-26
Commercial infrared (IR) milk analyzers are being increasingly used in research settings for the macronutrient measurement of breast milk (BM) prior to its target fortification. These devices, however, may not provide reliable measurement if not properly calibrated. In the current study, we tested a correction algorithm for a Near-IR milk analyzer (Unity SpectraStar, Brookfield, CT, USA) for fat and protein measurements, and examined the effect of pasteurization on the IR matrix and the stability of fat, protein, and lactose. Measurement values generated through Near-IR analysis were compared against those obtained through chemical reference methods to test the correction algorithm for the Near-IR milk analyzer. Macronutrient levels were compared between unpasteurized and pasteurized milk samples to determine the effect of pasteurization on macronutrient stability. The correction algorithm generated for our device was found to be valid for unpasteurized and pasteurized BM. Pasteurization had no effect on the macronutrient levels and the IR matrix of BM. These results show that fat and protein content can be accurately measured and monitored for unpasteurized and pasteurized BM. Of additional importance is the implication that donated human milk, generally low in protein content, has the potential to be target fortified.
Directory of Open Access Journals (Sweden)
Lei Zhang
2016-01-01
Full Text Available Among non-small cell lung cancer (NSCLC, adenocarcinoma (AC, and squamous cell carcinoma (SCC are two major histology subtypes, accounting for roughly 40% and 30% of all lung cancer cases, respectively. Since AC and SCC differ in their cell of origin, location within the lung, and growth pattern, they are considered as distinct diseases. Gene expression signatures have been demonstrated to be an effective tool for distinguishing AC and SCC. Gene set analysis is regarded as irrelevant to the identification of gene expression signatures. Nevertheless, we found that one specific gene set analysis method, significance analysis of microarray-gene set reduction (SAMGSR, can be adopted directly to select relevant features and to construct gene expression signatures. In this study, we applied SAMGSR to a NSCLC gene expression dataset. When compared with several novel feature selection algorithms, for example, LASSO, SAMGSR has equivalent or better performance in terms of predictive ability and model parsimony. Therefore, SAMGSR is a feature selection algorithm, indeed. Additionally, we applied SAMGSR to AC and SCC subtypes separately to discriminate their respective stages, that is, stage II versus stage I. Few overlaps between these two resulting gene signatures illustrate that AC and SCC are technically distinct diseases. Therefore, stratified analyses on subtypes are recommended when diagnostic or prognostic signatures of these two NSCLC subtypes are constructed.
Directory of Open Access Journals (Sweden)
Ujwalla Gawande
2013-01-01
Full Text Available Recent times witnessed many advancements in the field of biometric and ultimodal biometric fields. This is typically observed in the area, of security, privacy, and forensics. Even for the best of unimodal biometric systems, it is often not possible to achieve a higher recognition rate. Multimodal biometric systems overcome various limitations of unimodal biometric systems, such as nonuniversality, lower false acceptance, and higher genuine acceptance rates. More reliable recognition performance is achievable as multiple pieces of evidence of the same identity are available. The work presented in this paper is focused on multimodal biometric system using fingerprint and iris. Distinct textual features of the iris and fingerprint are extracted using the Haar wavelet-based technique. A novel feature level fusion algorithm is developed to combine these unimodal features using the Mahalanobis distance technique. A support-vector-machine-based learning algorithm is used to train the system using the feature extracted. The performance of the proposed algorithms is validated and compared with other algorithms using the CASIA iris database and real fingerprint database. From the simulation results, it is evident that our algorithm has higher recognition rate and very less false rejection rate compared to existing approaches.
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.
O'Neill, P.; Podest, E.
2011-01-01
The planned Soil Moisture Active Passive (SMAP) mission is one of the first Earth observation satellites being developed by NASA in response to the National Research Council's Decadal Survey, Earth Science and Applications from Space: National Imperatives for the Next Decade and Beyond [1]. Scheduled to launch late in 2014, the proposed SMAP mission would provide high resolution and frequent revisit global mapping of soil moisture and freeze/thaw state, utilizing enhanced Radio Frequency Interference (RFI) mitigation approaches to collect new measurements of the hydrological condition of the Earth's surface. The SMAP instrument design incorporates an L-band radar (3 km) and an L band radiometer (40 km) sharing a single 6-meter rotating mesh antenna to provide measurements of soil moisture and landscape freeze/thaw state [2]. These observations would (1) improve our understanding of linkages between the Earth's water, energy, and carbon cycles, (2) benefit many application areas including numerical weather and climate prediction, flood and drought monitoring, agricultural productivity, human health, and national security, (3) help to address priority questions on climate change, and (4) potentially provide continuity with brightness temperature and soil moisture measurements from ESA's SMOS (Soil Moisture Ocean Salinity) and NASA's Aquarius missions. In the planned SMAP mission prelaunch time frame, baseline algorithms are being developed for generating (1) soil moisture products both from radiometer measurements on a 36 km grid and from combined radar/radiometer measurements on a 9 km grid, and (2) freeze/thaw products from radar measurements on a 3 km grid. These retrieval algorithms need a variety of global ancillary data, both static and dynamic, to run the retrieval models, constrain the retrievals, and provide flags for indicating retrieval quality. The choice of which ancillary dataset to use for a particular SMAP product would be based on a number of factors
Using MaxCompiler for High Level Synthesis of Trigger Algorithms
Summers, Sioni Paris; Sanders, P.
2017-01-01
Firmware for FPGA trigger applications at the CMS experiment is conventionally written using hardware description languages such as Verilog and VHDL. MaxCompiler is an alternative, Java based, tool for developing FPGA applications which uses a higher level of abstraction from the hardware than a hardware description language. An implementation of the jet and energy sum algorithms for the CMS Level-1 calorimeter trigger has been written using MaxCompiler to benchmark against the VHDL implementation in terms of accuracy, latency, resource usage, and code size. A Kalman Filter track fitting algorithm has been developed using MaxCompiler for a proposed CMS Level-1 track trigger for the High-Luminosity LHC upgrade. The design achieves a low resource usage, and has a latency of 187.5 ns per iteration.
Using MaxCompiler for the high level synthesis of trigger algorithms
International Nuclear Information System (INIS)
Summers, S.; Rose, A.; Sanders, P.
2017-01-01
Firmware for FPGA trigger applications at the CMS experiment is conventionally written using hardware description languages such as Verilog and VHDL. MaxCompiler is an alternative, Java based, tool for developing FPGA applications which uses a higher level of abstraction from the hardware than a hardware description language. An implementation of the jet and energy sum algorithms for the CMS Level-1 calorimeter trigger has been written using MaxCompiler to benchmark against the VHDL implementation in terms of accuracy, latency, resource usage, and code size. A Kalman Filter track fitting algorithm has been developed using MaxCompiler for a proposed CMS Level-1 track trigger for the High-Luminosity LHC upgrade. The design achieves a low resource usage, and has a latency of 187.5 ns per iteration.
Using MaxCompiler for the high level synthesis of trigger algorithms
Summers, S.; Rose, A.; Sanders, P.
2017-02-01
Firmware for FPGA trigger applications at the CMS experiment is conventionally written using hardware description languages such as Verilog and VHDL. MaxCompiler is an alternative, Java based, tool for developing FPGA applications which uses a higher level of abstraction from the hardware than a hardware description language. An implementation of the jet and energy sum algorithms for the CMS Level-1 calorimeter trigger has been written using MaxCompiler to benchmark against the VHDL implementation in terms of accuracy, latency, resource usage, and code size. A Kalman Filter track fitting algorithm has been developed using MaxCompiler for a proposed CMS Level-1 track trigger for the High-Luminosity LHC upgrade. The design achieves a low resource usage, and has a latency of 187.5 ns per iteration.
International Nuclear Information System (INIS)
Kim, Seung Geun; Seong, Poong Hyun
2017-01-01
Development of operation support systems and automation systems are closely related to machine learning field. However, since it is hard to achieve human-level delicacy and flexibility for complex tasks with conventional machine learning technologies, only operation support systems with simple purposes were developed and high-level automation related studies were not actively conducted. As one of the efforts for reducing human error in NPPs and technical advance toward automation, the ultimate goal of this research is to develop human-level decision making algorithm for NPPs during emergency situations. The concepts of SL, RL, policy network, value network, and MCTS, which were applied to decision making algorithm for other fields are introduced and combined with nuclear field specifications. Since the research is currently at the conceptual stage, more research is warranted.
Zhang, Zhengfang; Chen, Weifeng
2018-05-01
Maximization of the smallest eigenfrequency of the linearized elasticity system with area constraint is investigated. The elasticity system is extended into a large background domain, but the void is vacuum and not filled with ersatz material. The piecewise constant level set (PCLS) method is applied to present two regions, the original material region and the void region. A quadratic PCLS function is proposed to represent the characteristic function. Consequently, the functional derivative of the smallest eigenfrequency with respect to PCLS function takes nonzero value in the original material region and zero in the void region. A penalty gradient algorithm is proposed, which initializes the whole background domain with the original material and decreases the area of original material region till the area constraint is satisfied. 2D and 3D numerical examples are presented, illustrating the validity of the proposed algorithm.
Song, Lei; Gao, Jungang; Wang, Sheng; Hu, Huasi; Guo, Youmin
2017-01-01
Estimation of the pleural effusion's volume is an important clinical issue. The existing methods cannot assess it accurately when there is large volume of liquid in the pleural cavity and/or the patient has some other disease (e.g. pneumonia). In order to help solve this issue, the objective of this study is to develop and test a novel algorithm using B-spline and local clustering level set method jointly, namely BLL. The BLL algorithm was applied to a dataset involving 27 pleural effusions detected on chest CT examination of 18 adult patients with the presence of free pleural effusion. Study results showed that average volumes of pleural effusion computed using the BLL algorithm and assessed manually by the physicians were 586 ml±339 ml and 604±352 ml, respectively. For the same patient, the volume of the pleural effusion, segmented semi-automatically, was 101.8% ±4.6% of that was segmented manually. Dice similarity was found to be 0.917±0.031. The study demonstrated feasibility of applying the new BLL algorithm to accurately measure the volume of pleural effusion.
Directory of Open Access Journals (Sweden)
Jia-Cheng Yu
2018-02-01
Full Text Available A three-dimensional topography simulation of deep reactive ion etching (DRIE is developed based on the narrow band level set method for surface evolution and Monte Carlo method for flux distribution. The advanced level set method is implemented to simulate the time-related movements of etched surface. In the meanwhile, accelerated by ray tracing algorithm, the Monte Carlo method incorporates all dominant physical and chemical mechanisms such as ion-enhanced etching, ballistic transport, ion scattering, and sidewall passivation. The modified models of charged particles and neutral particles are epitomized to determine the contributions of etching rate. The effects such as scalloping effect and lag effect are investigated in simulations and experiments. Besides, the quantitative analyses are conducted to measure the simulation error. Finally, this simulator will be served as an accurate prediction tool for some MEMS fabrications.
International Nuclear Information System (INIS)
Ramos Muñoz, Edgar; Razeghi, Ghazal; Zhang, Li; Jabbari, Faryar
2016-01-01
The need to reduce greenhouse gas emissions and fossil fuel consumption has increased the popularity of plug-in electric vehicles. However, a large penetration of plug-in electric vehicles can pose challenges at the grid and local distribution levels. Various charging strategies have been proposed to address such challenges, often separately. In this paper, it is shown that, with uncoordinated charging, distribution transformers and the grid can operate under highly undesirable conditions. Next, several strategies that require modest communication efforts are proposed to mitigate the burden created by high concentrations of plug-in electric vehicles, at the grid and local levels. Existing transformer and battery electric vehicle characteristics are used along with the National Household Travel Survey to simulate various charging strategies. It is shown through the analysis of hot spot temperature and equivalent aging factor that the coordinated strategies proposed here reduce the chances of transformer failure with the addition of plug-in electric vehicle loads, even for an under-designed transformer while uncontrolled and uncoordinated plug-in electric vehicle charging results in increased risk of transformer failure. - Highlights: • Charging algorithm for battery electric vehicles, for high penetration levels. • Algorithm reduces transformer overloading, for grid level valley filling. • Computation and communication requirements are minimal. • The distributed algorithm is implemented without large scale iterations. • Hot spot temperature and loss of life for transformers are evaluated.
Besold, Tarek R.; Kühnberger, Kai-Uwe; Plaza, Enric
2017-10-01
Concept blending - a cognitive process which allows for the combination of certain elements (and their relations) from originally distinct conceptual spaces into a new unified space combining these previously separate elements, and enables reasoning and inference over the combination - is taken as a key element of creative thought and combinatorial creativity. In this article, we summarise our work towards the development of a computational-level and algorithmic-level account of concept blending, combining approaches from computational analogy-making and case-based reasoning (CBR). We present the theoretical background, as well as an algorithmic proposal integrating higher-order anti-unification matching and generalisation from analogy with amalgams from CBR. The feasibility of the approach is then exemplified in two case studies.
International Nuclear Information System (INIS)
Kang, Hyun Gook; Seong, Poong Hyun
1994-01-01
In this study a programmable smart transmitter is designed and applied to the nuclear engineering measurements. In order to apply the smart transmitter technology to nuclear engineering measurements, the water level detection function is developed and applied in this work. In the real time system, the application of level detection algorithm can make the operator of the nuclear power plant sense the water level more rapidly. Furthermore this work can simplify the data communication between the level-sensing thermocouples and the main signal processor because the level signal is determined at field. The water level detection function reduces the detection time to about 8.3 seconds by processing the signal which has the time constant 250 seconds and the heavy noise signal
Multi-Threaded Algorithms for GPGPU in the ATLAS High Level Trigger
Conde Muíño, P.; ATLAS Collaboration
2017-10-01
General purpose Graphics Processor Units (GPGPU) are being evaluated for possible future inclusion in an upgraded ATLAS High Level Trigger farm. We have developed a demonstrator including GPGPU implementations of Inner Detector and Muon tracking and Calorimeter clustering within the ATLAS software framework. ATLAS is a general purpose particle physics experiment located on the LHC collider at CERN. The ATLAS Trigger system consists of two levels, with Level-1 implemented in hardware and the High Level Trigger implemented in software running on a farm of commodity CPU. The High Level Trigger reduces the trigger rate from the 100 kHz Level-1 acceptance rate to 1.5 kHz for recording, requiring an average per-event processing time of ∼ 250 ms for this task. The selection in the high level trigger is based on reconstructing tracks in the Inner Detector and Muon Spectrometer and clusters of energy deposited in the Calorimeter. Performing this reconstruction within the available farm resources presents a significant challenge that will increase significantly with future LHC upgrades. During the LHC data taking period starting in 2021, luminosity will reach up to three times the original design value. Luminosity will increase further to 7.5 times the design value in 2026 following LHC and ATLAS upgrades. Corresponding improvements in the speed of the reconstruction code will be needed to provide the required trigger selection power within affordable computing resources. Key factors determining the potential benefit of including GPGPU as part of the HLT processor farm are: the relative speed of the CPU and GPGPU algorithm implementations; the relative execution times of the GPGPU algorithms and serial code remaining on the CPU; the number of GPGPU required, and the relative financial cost of the selected GPGPU. We give a brief overview of the algorithms implemented and present new measurements that compare the performance of various configurations exploiting GPGPU cards.
International Nuclear Information System (INIS)
Lin, Chang Sheng; Tseng, Tse Chuan
2014-01-01
Modal Identification from response data only is studied for structural systems under nonstationary ambient vibration. The topic of this paper is the estimation of modal parameters from nonstationary ambient vibration data by applying the random decrement algorithm with time-varying threshold level. In the conventional random decrement algorithm, the threshold level for evaluating random dec signatures is defined as the standard deviation value of response data of the reference channel. The distortion of random dec signatures may be, however, induced by the error involved in noise from the original response data in practice. To improve the accuracy of identification, a modification of the sampling procedure in random decrement algorithm is proposed for modal-parameter identification from the nonstationary ambient response data. The time-varying threshold level is presented for the acquisition of available sample time history to perform averaging analysis, and defined as the temporal root-mean-square function of structural response, which can appropriately describe a wide variety of nonstationary behaviors in reality, such as the time-varying amplitude (variance) of a nonstationary process in a seismic record. Numerical simulations confirm the validity and robustness of the proposed modal-identification method from nonstationary ambient response data under noisy conditions.
A LEVEL SET BASED SHAPE OPTIMIZATION METHOD FOR AN ELLIPTIC OBSTACLE PROBLEM
Burger, Martin; Matevosyan, Norayr; Wolfram, Marie-Therese
2011-01-01
analysis of the level set method in terms of viscosity solutions. To our knowledge this is the first complete analysis of a level set method for a nonlocal shape optimization problem. Finally, we discuss the implementation of the methods and illustrate its
Improving Limit Surface Search Algorithms in RAVEN Using Acceleration Schemes: Level II Milestone
Energy Technology Data Exchange (ETDEWEB)
Alfonsi, Andrea [Idaho National Laboratory (INL), Idaho Falls, ID (United States); Rabiti, Cristian [Idaho National Laboratory (INL), Idaho Falls, ID (United States); Mandelli, Diego [Idaho National Laboratory (INL), Idaho Falls, ID (United States); Cogliati, Joshua Joseph [Idaho National Laboratory (INL), Idaho Falls, ID (United States); Sen, Ramazan Sonat [Idaho National Laboratory (INL), Idaho Falls, ID (United States); Smith, Curtis Lee [Idaho National Laboratory (INL), Idaho Falls, ID (United States)
2015-07-01
The RAVEN code is becoming a comprehensive tool to perform Probabilistic Risk Assessment (PRA); Uncertainty Quantification (UQ) and Propagation; and Verification and Validation (V&V). The RAVEN code is being developed to support the Risk-Informed Safety Margin Characterization (RISMC) pathway by developing an advanced set of methodologies and algorithms for use in advanced risk analysis. The RISMC approach uses system simulator codes applied to stochastic analysis tools. The fundamental idea behind this coupling approach to perturb (by employing sampling strategies) timing and sequencing of events, internal parameters of the system codes (i.e., uncertain parameters of the physics model) and initial conditions to estimate values ranges and associated probabilities of figures of merit of interest for engineering and safety (e.g. core damage probability, etc.). This approach applied to complex systems such as nuclear power plants requires performing a series of computationally expensive simulation runs. The large computational burden is caused by the large set of (uncertain) parameters characterizing those systems. Consequently, exploring the uncertain/parametric domain, with a good level of confidence, is generally not affordable, considering the limited computational resources that are currently available. In addition, the recent tendency to develop newer tools, characterized by higher accuracy and larger computational resources (if compared with the presently used legacy codes, that have been developed decades ago), has made this issue even more compelling. In order to overcome to these limitations, the strategy for the exploration of the uncertain/parametric space needs to use at best the computational resources focusing the computational effort in those regions of the uncertain/parametric space that are “interesting” (e.g., risk-significant regions of the input space) with respect the targeted Figures Of Merit (FOM): for example, the failure of the system
Effect of a uniform magnetic field on dielectric two-phase bubbly flows using the level set method
International Nuclear Information System (INIS)
Ansari, M.R.; Hadidi, A.; Nimvari, M.E.
2012-01-01
In this study, the behavior of a single bubble in a dielectric viscous fluid under a uniform magnetic field has been simulated numerically using the Level Set method in two-phase bubbly flow. The two-phase bubbly flow was considered to be laminar and homogeneous. Deformation of the bubble was considered to be due to buoyancy and magnetic forces induced from the external applied magnetic field. A computer code was developed to solve the problem using the flow field, the interface of two phases, and the magnetic field. The Finite Volume method was applied using the SIMPLE algorithm to discretize the governing equations. Using this algorithm enables us to calculate the pressure parameter, which has been eliminated by previous researchers because of the complexity of the two-phase flow. The finite difference method was used to solve the magnetic field equation. The results outlined in the present study agree well with the existing experimental data and numerical results. These results show that the magnetic field affects and controls the shape, size, velocity, and location of the bubble. - Highlights: ►A bubble behavior was simulated numerically. ► A single bubble behavior was considered in a dielectric viscous fluid. ► A uniform magnetic field is used to study a bubble behavior. ► Deformation of the bubble was considered using the Level Set method. ► The magnetic field affects the shape, size, velocity, and location of the bubble.
ATLAS High-Level Trigger Performance for Calorimeter-Based Algorithms in LHC Run-I
Mann, A; The ATLAS collaboration
2013-01-01
The ATLAS detector operated during the three years of the Run-I of the Large Hadron Collider collecting information on a large number of proton-proton events. One the most important results obtained so far is the discovery of one Higgs boson. More precise measurements of this particle must be performed as well as there are other very important physics topics still to be explored. One of the key components of the ATLAS detector is its trigger system. It is composed of three levels: one (called Level 1 - L1) built on custom hardware and the two others based on software algorithms - called Level 2 (L2) and Event Filter (EF) – altogether referred to as the ATLAS High Level Trigger. The ATLAS trigger is responsible for reducing almost 20 million of collisions per second produced by the accelerator to less than 1000. The L2 operates only in the regions tagged by the first hardware level as containing possible interesting physics while the EF operates in the full detector, normally using offline-like algorithms to...
Directory of Open Access Journals (Sweden)
AYAS, S.
2018-02-01
Full Text Available Image thresholding is the most crucial step in microscopic image analysis to distinguish bacilli objects causing of tuberculosis disease. Therefore, several bi-level thresholding algorithms are widely used to increase the bacilli segmentation accuracy. However, bi-level microscopic image thresholding problem has not been solved using optimization algorithms. This paper introduces a novel approach for the segmentation problem using heuristic algorithms and presents visual and quantitative comparisons of heuristic and state-of-art thresholding algorithms. In this study, well-known heuristic algorithms such as Firefly Algorithm, Particle Swarm Optimization, Cuckoo Search, Flower Pollination are used to solve bi-level microscopic image thresholding problem, and the results are compared with the state-of-art thresholding algorithms such as K-Means, Fuzzy C-Means, Fast Marching. Kapur's entropy is chosen as the entropy measure to be maximized. Experiments are performed to make comparisons in terms of evaluation metrics and execution time. The quantitative results are calculated based on ground truth segmentation. According to the visual results, heuristic algorithms have better performance and the quantitative results are in accord with the visual results. Furthermore, experimental time comparisons show the superiority and effectiveness of the heuristic algorithms over traditional thresholding algorithms.
Li, Zhongwei; Xin, Yuezhen; Wang, Xun; Sun, Beibei; Xia, Shengyu; Li, Hui
2016-01-01
Phellinus is a kind of fungus and is known as one of the elemental components in drugs to avoid cancers. With the purpose of finding optimized culture conditions for Phellinus production in the laboratory, plenty of experiments focusing on single factor were operated and large scale of experimental data were generated. In this work, we use the data collected from experiments for regression analysis, and then a mathematical model of predicting Phellinus production is achieved. Subsequently, a gene-set based genetic algorithm is developed to optimize the values of parameters involved in culture conditions, including inoculum size, PH value, initial liquid volume, temperature, seed age, fermentation time, and rotation speed. These optimized values of the parameters have accordance with biological experimental results, which indicate that our method has a good predictability for culture conditions optimization. PMID:27610365
A level set approach for shock-induced α-γ phase transition of RDX
Josyula, Kartik; Rahul; De, Suvranu
2018-02-01
We present a thermodynamically consistent level sets approach based on regularization energy functional which can be directly incorporated into a Galerkin finite element framework to model interface motion. The regularization energy leads to a diffusive form of flux that is embedded within the level sets evolution equation which maintains the signed distance property of the level set function. The scheme is shown to compare well with the velocity extension method in capturing the interface position. The proposed level sets approach is employed to study the α-γphase transformation in RDX single crystal shocked along the (100) plane. Example problems in one and three dimensions are presented. We observe smooth evolution of the phase interface along the shock direction in both models. There is no diffusion of the interface during the zero level set evolution in the three dimensional model. The level sets approach is shown to capture the characteristics of the shock-induced α-γ phase transformation such as stress relaxation behind the phase interface and the finite time required for the phase transformation to complete. The regularization energy based level sets approach is efficient, robust, and easy to implement.
Xiao, Xun; Geyer, Veikko F; Bowne-Anderson, Hugo; Howard, Jonathon; Sbalzarini, Ivo F
2016-08-01
Biological filaments, such as actin filaments, microtubules, and cilia, are often imaged using different light-microscopy techniques. Reconstructing the filament curve from the acquired images constitutes the filament segmentation problem. Since filaments have lower dimensionality than the image itself, there is an inherent trade-off between tracing the filament with sub-pixel accuracy and avoiding noise artifacts. Here, we present a globally optimal filament segmentation method based on B-spline vector level-sets and a generalized linear model for the pixel intensity statistics. We show that the resulting optimization problem is convex and can hence be solved with global optimality. We introduce a simple and efficient algorithm to compute such optimal filament segmentations, and provide an open-source implementation as an ImageJ/Fiji plugin. We further derive an information-theoretic lower bound on the filament segmentation error, quantifying how well an algorithm could possibly do given the information in the image. We show that our algorithm asymptotically reaches this bound in the spline coefficients. We validate our method in comprehensive benchmarks, compare with other methods, and show applications from fluorescence, phase-contrast, and dark-field microscopy. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.
Out-of-Core Computations of High-Resolution Level Sets by Means of Code Transformation
DEFF Research Database (Denmark)
Christensen, Brian Bunch; Nielsen, Michael Bang; Museth, Ken
2012-01-01
We propose a storage efficient, fast and parallelizable out-of-core framework for streaming computations of high resolution level sets. The fundamental techniques are skewing and tiling transformations of streamed level set computations which allow for the combination of interface propagation, re...... computations are now CPU bound and consequently the overall performance is unaffected by disk latency and bandwidth limitations. We demonstrate this with several benchmark tests that show sustained out-of-core throughputs close to that of in-core level set simulations....
Approach to estimation of level of information security at enterprise based on genetic algorithm
V, Stepanov L.; V, Parinov A.; P, Korotkikh L.; S, Koltsov A.
2018-05-01
In the article, the way of formalization of different types of threats of information security and vulnerabilities of an information system of the enterprise and establishment is considered. In a type of complexity of ensuring information security of application of any new organized system, the concept and decisions in the sphere of information security are expedient. One of such approaches is the method of a genetic algorithm. For the enterprises of any fields of activity, the question of complex estimation of the level of security of information systems taking into account the quantitative and qualitative factors characterizing components of information security is relevant.
Cui, Wenchao; Wang, Yi; Lei, Tao; Fan, Yangyu; Feng, Yan
2013-01-01
This paper presents a variational level set method for simultaneous segmentation and bias field estimation of medical images with intensity inhomogeneity. In our model, the statistics of image intensities belonging to each different tissue in local regions are characterized by Gaussian distributions with different means and variances. According to maximum a posteriori probability (MAP) and Bayes' rule, we first derive a local objective function for image intensities in a neighborhood around each pixel. Then this local objective function is integrated with respect to the neighborhood center over the entire image domain to give a global criterion. In level set framework, this global criterion defines an energy in terms of the level set functions that represent a partition of the image domain and a bias field that accounts for the intensity inhomogeneity of the image. Therefore, image segmentation and bias field estimation are simultaneously achieved via a level set evolution process. Experimental results for synthetic and real images show desirable performances of our method.
A LEVEL SET BASED SHAPE OPTIMIZATION METHOD FOR AN ELLIPTIC OBSTACLE PROBLEM
Burger, Martin
2011-04-01
In this paper, we construct a level set method for an elliptic obstacle problem, which can be reformulated as a shape optimization problem. We provide a detailed shape sensitivity analysis for this reformulation and a stability result for the shape Hessian at the optimal shape. Using the shape sensitivities, we construct a geometric gradient flow, which can be realized in the context of level set methods. We prove the convergence of the gradient flow to an optimal shape and provide a complete analysis of the level set method in terms of viscosity solutions. To our knowledge this is the first complete analysis of a level set method for a nonlocal shape optimization problem. Finally, we discuss the implementation of the methods and illustrate its behavior through several computational experiments. © 2011 World Scientific Publishing Company.
An accurate conservative level set/ghost fluid method for simulating turbulent atomization
International Nuclear Information System (INIS)
Desjardins, Olivier; Moureau, Vincent; Pitsch, Heinz
2008-01-01
This paper presents a novel methodology for simulating incompressible two-phase flows by combining an improved version of the conservative level set technique introduced in [E. Olsson, G. Kreiss, A conservative level set method for two phase flow, J. Comput. Phys. 210 (2005) 225-246] with a ghost fluid approach. By employing a hyperbolic tangent level set function that is transported and re-initialized using fully conservative numerical schemes, mass conservation issues that are known to affect level set methods are greatly reduced. In order to improve the accuracy of the conservative level set method, high order numerical schemes are used. The overall robustness of the numerical approach is increased by computing the interface normals from a signed distance function reconstructed from the hyperbolic tangent level set by a fast marching method. The convergence of the curvature calculation is ensured by using a least squares reconstruction. The ghost fluid technique provides a way of handling the interfacial forces and large density jumps associated with two-phase flows with good accuracy, while avoiding artificial spreading of the interface. Since the proposed approach relies on partial differential equations, its implementation is straightforward in all coordinate systems, and it benefits from high parallel efficiency. The robustness and efficiency of the approach is further improved by using implicit schemes for the interface transport and re-initialization equations, as well as for the momentum solver. The performance of the method is assessed through both classical level set transport tests and simple two-phase flow examples including topology changes. It is then applied to simulate turbulent atomization of a liquid Diesel jet at Re=3000. The conservation errors associated with the accurate conservative level set technique are shown to remain small even for this complex case
A simple mass-conserved level set method for simulation of multiphase flows
Yuan, H.-Z.; Shu, C.; Wang, Y.; Shu, S.
2018-04-01
In this paper, a modified level set method is proposed for simulation of multiphase flows with large density ratio and high Reynolds number. The present method simply introduces a source or sink term into the level set equation to compensate the mass loss or offset the mass increase. The source or sink term is derived analytically by applying the mass conservation principle with the level set equation and the continuity equation of flow field. Since only a source term is introduced, the application of the present method is as simple as the original level set method, but it can guarantee the overall mass conservation. To validate the present method, the vortex flow problem is first considered. The simulation results are compared with those from the original level set method, which demonstrates that the modified level set method has the capability of accurately capturing the interface and keeping the mass conservation. Then, the proposed method is further validated by simulating the Laplace law, the merging of two bubbles, a bubble rising with high density ratio, and Rayleigh-Taylor instability with high Reynolds number. Numerical results show that the mass is a well-conserved by the present method.
Evaluating healthcare priority setting at the meso level: A thematic review of empirical literature
Waithaka, Dennis; Tsofa, Benjamin; Barasa, Edwine
2018-01-01
Background: Decentralization of health systems has made sub-national/regional healthcare systems the backbone of healthcare delivery. These regions are tasked with the difficult responsibility of determining healthcare priorities and resource allocation amidst scarce resources. We aimed to review empirical literature that evaluated priority setting practice at the meso (sub-national) level of health systems. Methods: We systematically searched PubMed, ScienceDirect and Google scholar databases and supplemented these with manual searching for relevant studies, based on the reference list of selected papers. We only included empirical studies that described and evaluated, or those that only evaluated priority setting practice at the meso-level. A total of 16 papers were identified from LMICs and HICs. We analyzed data from the selected papers by thematic review. Results: Few studies used systematic priority setting processes, and all but one were from HICs. Both formal and informal criteria are used in priority-setting, however, informal criteria appear to be more perverse in LMICs compared to HICs. The priority setting process at the meso-level is a top-down approach with minimal involvement of the community. Accountability for reasonableness was the most common evaluative framework as it was used in 12 of the 16 studies. Efficiency, reallocation of resources and options for service delivery redesign were the most common outcome measures used to evaluate priority setting. Limitations: Our study was limited by the fact that there are very few empirical studies that have evaluated priority setting at the meso-level and there is likelihood that we did not capture all the studies. Conclusions: Improving priority setting practices at the meso level is crucial to strengthening health systems. This can be achieved through incorporating and adapting systematic priority setting processes and frameworks to the context where used, and making considerations of both process
Directory of Open Access Journals (Sweden)
Hosseinali Salemi
2016-04-01
Full Text Available Facility location models are observed in many diverse areas such as communication networks, transportation, and distribution systems planning. They play significant role in supply chain and operations management and are one of the main well-known topics in strategic agenda of contemporary manufacturing and service companies accompanied by long-lasting effects. We define a new approach for solving stochastic single source capacitated facility location problem (SSSCFLP. Customers with stochastic demand are assigned to set of capacitated facilities that are selected to serve them. It is demonstrated that problem can be transformed to deterministic Single Source Capacitated Facility Location Problem (SSCFLP for Poisson demand distribution. A hybrid algorithm which combines Lagrangian heuristic with adjusted mixture of Ant colony and Genetic optimization is proposed to find lower and upper bounds for this problem. Computational results of various instances with distinct properties indicate that proposed solving approach is efficient.
Setting Healthcare Priorities at the Macro and Meso Levels: A Framework for Evaluation.
Barasa, Edwine W; Molyneux, Sassy; English, Mike; Cleary, Susan
2015-09-16
Priority setting in healthcare is a key determinant of health system performance. However, there is no widely accepted priority setting evaluation framework. We reviewed literature with the aim of developing and proposing a framework for the evaluation of macro and meso level healthcare priority setting practices. We systematically searched Econlit, PubMed, CINAHL, and EBSCOhost databases and supplemented this with searches in Google Scholar, relevant websites and reference lists of relevant papers. A total of 31 papers on evaluation of priority setting were identified. These were supplemented by broader theoretical literature related to evaluation of priority setting. A conceptual review of selected papers was undertaken. Based on a synthesis of the selected literature, we propose an evaluative framework that requires that priority setting practices at the macro and meso levels of the health system meet the following conditions: (1) Priority setting decisions should incorporate both efficiency and equity considerations as well as the following outcomes; (a) Stakeholder satisfaction, (b) Stakeholder understanding, (c) Shifted priorities (reallocation of resources), and (d) Implementation of decisions. (2) Priority setting processes should also meet the procedural conditions of (a) Stakeholder engagement, (b) Stakeholder empowerment, (c) Transparency, (d) Use of evidence, (e) Revisions, (f) Enforcement, and (g) Being grounded on community values. Available frameworks for the evaluation of priority setting are mostly grounded on procedural requirements, while few have included outcome requirements. There is, however, increasing recognition of the need to incorporate both consequential and procedural considerations in priority setting practices. In this review, we adapt an integrative approach to develop and propose a framework for the evaluation of priority setting practices at the macro and meso levels that draws from these complementary schools of thought. © 2015
Setting Healthcare Priorities at the Macro and Meso Levels: A Framework for Evaluation
Barasa, Edwine W.; Molyneux, Sassy; English, Mike; Cleary, Susan
2015-01-01
Background: Priority setting in healthcare is a key determinant of health system performance. However, there is no widely accepted priority setting evaluation framework. We reviewed literature with the aim of developing and proposing a framework for the evaluation of macro and meso level healthcare priority setting practices. Methods: We systematically searched Econlit, PubMed, CINAHL, and EBSCOhost databases and supplemented this with searches in Google Scholar, relevant websites and reference lists of relevant papers. A total of 31 papers on evaluation of priority setting were identified. These were supplemented by broader theoretical literature related to evaluation of priority setting. A conceptual review of selected papers was undertaken. Results: Based on a synthesis of the selected literature, we propose an evaluative framework that requires that priority setting practices at the macro and meso levels of the health system meet the following conditions: (1) Priority setting decisions should incorporate both efficiency and equity considerations as well as the following outcomes; (a) Stakeholder satisfaction, (b) Stakeholder understanding, (c) Shifted priorities (reallocation of resources), and (d) Implementation of decisions. (2) Priority setting processes should also meet the procedural conditions of (a) Stakeholder engagement, (b) Stakeholder empowerment, (c) Transparency, (d) Use of evidence, (e) Revisions, (f) Enforcement, and (g) Being grounded on community values. Conclusion: Available frameworks for the evaluation of priority setting are mostly grounded on procedural requirements, while few have included outcome requirements. There is, however, increasing recognition of the need to incorporate both consequential and procedural considerations in priority setting practices. In this review, we adapt an integrative approach to develop and propose a framework for the evaluation of priority setting practices at the macro and meso levels that draws from these
Setting Healthcare Priorities at the Macro and Meso Levels: A Framework for Evaluation
Directory of Open Access Journals (Sweden)
Edwine W. Barasa
2015-11-01
Full Text Available Background Priority setting in healthcare is a key determinant of health system performance. However, there is no widely accepted priority setting evaluation framework. We reviewed literature with the aim of developing and proposing a framework for the evaluation of macro and meso level healthcare priority setting practices. Methods We systematically searched Econlit, PubMed, CINAHL, and EBSCOhost databases and supplemented this with searches in Google Scholar, relevant websites and reference lists of relevant papers. A total of 31 papers on evaluation of priority setting were identified. These were supplemented by broader theoretical literature related to evaluation of priority setting. A conceptual review of selected papers was undertaken. Results Based on a synthesis of the selected literature, we propose an evaluative framework that requires that priority setting practices at the macro and meso levels of the health system meet the following conditions: (1 Priority setting decisions should incorporate both efficiency and equity considerations as well as the following outcomes; (a Stakeholder satisfaction, (b Stakeholder understanding, (c Shifted priorities (reallocation of resources, and (d Implementation of decisions. (2 Priority setting processes should also meet the procedural conditions of (a Stakeholder engagement, (b Stakeholder empowerment, (c Transparency, (d Use of evidence, (e Revisions, (f Enforcement, and (g Being grounded on community values. Conclusion Available frameworks for the evaluation of priority setting are mostly grounded on procedural requirements, while few have included outcome requirements. There is, however, increasing recognition of the need to incorporate both consequential and procedural considerations in priority setting practices. In this review, we adapt an integrative approach to develop and propose a framework for the evaluation of priority setting practices at the macro and meso levels that draws from
Shanks, Leslie; Siddiqui, M Ruby; Abebe, Almaz; Piriou, Erwan; Pearce, Neil; Ariti, Cono; Masiga, Johnson; Muluneh, Libsework; Wazome, Joseph; Ritmeijer, Koert; Klarkowski, Derryck
2015-05-14
Current WHO testing guidelines for resource limited settings diagnose HIV on the basis of screening tests without a confirmation test due to cost constraints. This leads to a potential risk of false positive HIV diagnosis. In this paper, we evaluate the dilution test, a novel method for confirmation testing, which is simple, rapid, and low cost. The principle of the dilution test is to alter the sensitivity of a rapid diagnostic test (RDT) by dilution of the sample, in order to screen out the cross reacting antibodies responsible for falsely positive RDT results. Participants were recruited from two testing centres in Ethiopia where a tiebreaker algorithm using 3 different RDTs in series is used to diagnose HIV. All samples positive on the initial screening RDT and every 10th negative sample underwent testing with the gold standard and dilution test. Dilution testing was performed using Determine™ rapid diagnostic test at 6 different dilutions. Results were compared to the gold standard of Western Blot; where Western Blot was indeterminate, PCR testing determined the final result. 2895 samples were recruited to the study. 247 were positive for a prevalence of 8.5 % (247/2895). A total of 495 samples underwent dilution testing. The RDT diagnostic algorithm misclassified 18 samples as positive. Dilution at the level of 1/160 was able to correctly identify all these 18 false positives, but at a cost of a single false negative result (sensitivity 99.6 %, 95 % CI 97.8-100; specificity 100 %, 95 % CI: 98.5-100). Concordance between the gold standard and the 1/160 dilution strength was 99.8 %. This study provides proof of concept for a new, low cost method of confirming HIV diagnosis in resource-limited settings. It has potential for use as a supplementary test in a confirmatory algorithm, whereby double positive RDT results undergo dilution testing, with positive results confirming HIV infection. Negative results require nucleic acid testing to rule out false
76 FR 9004 - Public Comment on Setting Achievement Levels in Writing
2011-02-16
... DEPARTMENT OF EDUCATION Public Comment on Setting Achievement Levels in Writing AGENCY: U.S... Achievement Levels in Writing. SUMMARY: The National Assessment Governing Board (Governing Board) is... for NAEP in writing. This notice provides opportunity for public comment and submitting...
Bos, Peter Martinus Jozef; Zeilmaker, Marco Jacob; Eijkeren, Jan Cornelis Henri van
2006-01-01
Acute exposure guideline levels (AEGLs) are derived to protect the human population from adverse health effects in case of single exposure due to an accidental release of chemicals into the atmosphere. AEGLs are set at three different levels of increasing toxicity for exposure durations ranging from
Hooker, Stanford B. (Editor); Firestone, Elaine R. (Editor); Acker, James G. (Editor); Campbell, Janet W.; Blaisdell, John M.; Darzi, Michael
1995-01-01
The level-3 data products from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) are statistical data sets derived from level-2 data. Each data set will be based on a fixed global grid of equal-area bins that are approximately 9 x 9 sq km. Statistics available for each bin include the sum and sum of squares of the natural logarithm of derived level-2 geophysical variables where sums are accumulated over a binning period. Operationally, products with binning periods of 1 day, 8 days, 1 month, and 1 year will be produced and archived. From these accumulated values and for each bin, estimates of the mean, standard deviation, median, and mode may be derived for each geophysical variable. This report contains two major parts: the first (Section 2) is intended as a users' guide for level-3 SeaWiFS data products. It contains an overview of level-0 to level-3 data processing, a discussion of important statistical considerations when using level-3 data, and details of how to use the level-3 data. The second part (Section 3) presents a comparative statistical study of several binning algorithms based on CZCS and moored fluorometer data. The operational binning algorithms were selected based on the results of this study.
Directory of Open Access Journals (Sweden)
Charles Noven Castillo
2017-01-01
Full Text Available Currently, there has been limited established specific set of criteria for personnel promotion to each level of the organization. This study is conducted in order to develop a personnel promotion strategy by identifying specific sets of criteria for each level of the organization. The complexity of identifying the criteria set along with the subjectivity of these criteria require the use of multi-criteria decision-making approach particularly the analytic hierarchy process (AHP. Results show different sets of criteria for each management level which are consistent with several frameworks in literature. These criteria sets would help avoid mismatch of employee skills and competencies and their job, and at the same time eliminate the issues in personnel promotion such as favouritism, glass ceiling, and gender and physical attractiveness preference. This work also shows that personality and traits, job satisfaction and experience and skills are more critical rather than social capital across different organizational levels. The contribution of this work is in identifying relevant criteria in developing a personnel promotion strategy across organizational levels.
Energy Technology Data Exchange (ETDEWEB)
Maldaner, Stephan; Caputo, Regina; Schaefer, Ulrich; Tapprogge, Stefan [Universitaet Mainz, Staudingerweg 7, 55128 Mainz (Germany)
2013-07-01
After the upgrade of the Large Hadron Collider in 2013/2014 proton-proton collisions will be provided at a center-of-mass energy of up to 14 TeV with an instantaneous luminosity of at least 1 . 10{sup 34} cm{sup -2}s{sup -1}. During this upgrade a new FPGA based electronics system (Topological Processor) will be included in the ATLAS trigger chain to keep up with the increased rate of events. To reduce rates while maintaining high signal efficiency of the trigger the processor will make its decisions based upon topological criteria like angular cuts and mass calculations. As a hardware based trigger, it will have to fit into the tight first level trigger latency budget of 2.5 μs and thus provides the challenge of making decisions within very short time. Beside the latency, the main constraints on the algorithms are the required amount of logic resources of the FPGA which will be implemented as firmware. Therefore to be able to use as much information as possible, each module will be equipped with 2 state-of-the-art Xilinx Virtex 7 FPGAs to process the incoming data. This talk will present some of the topological algorithms and discuss properties of their implementation in firmware.
International Nuclear Information System (INIS)
Hardisty, M.; Gordon, L.; Agarwal, P.; Skrinskas, T.; Whyne, C.
2007-01-01
Quantitative assessment of metastatic disease in bone is often considered immeasurable and, as such, patients with skeletal metastases are often excluded from clinical trials. In order to effectively quantify the impact of metastatic tumor involvement in the spine, accurate segmentation of the vertebra is required. Manual segmentation can be accurate but involves extensive and time-consuming user interaction. Potential solutions to automating segmentation of metastatically involved vertebrae are demons deformable image registration and level set methods. The purpose of this study was to develop a semiautomated method to accurately segment tumor-bearing vertebrae using the aforementioned techniques. By maintaining morphology of an atlas, the demons-level set composite algorithm was able to accurately differentiate between trans-cortical tumors and surrounding soft tissue of identical intensity. The algorithm successfully segmented both the vertebral body and trabecular centrum of tumor-involved and healthy vertebrae. This work validates our approach as equivalent in accuracy to an experienced user
TES Level 1 Algorithms: Interferogram Processing, Geolocation, Radiometric, and Spectral Calibration
Worden, Helen; Beer, Reinhard; Bowman, Kevin W.; Fisher, Brendan; Luo, Mingzhao; Rider, David; Sarkissian, Edwin; Tremblay, Denis; Zong, Jia
2006-01-01
The Tropospheric Emission Spectrometer (TES) on the Earth Observing System (EOS) Aura satellite measures the infrared radiance emitted by the Earth's surface and atmosphere using Fourier transform spectrometry. The measured interferograms are converted into geolocated, calibrated radiance spectra by the L1 (Level 1) processing, and are the inputs to L2 (Level 2) retrievals of atmospheric parameters, such as vertical profiles of trace gas abundance. We describe the algorithmic components of TES Level 1 processing, giving examples of the intermediate results and diagnostics that are necessary for creating TES L1 products. An assessment of noise-equivalent spectral radiance levels and current systematic errors is provided. As an initial validation of our spectral radiances, TES data are compared to the Atmospheric Infrared Sounder (AIRS) (on EOS Aqua), after accounting for spectral resolution differences by applying the AIRS spectral response function to the TES spectra. For the TES L1 nadir data products currently available, the agreement with AIRS is 1 K or better.
Priority setting at the micro-, meso- and macro-levels in Canada, Norway and Uganda.
Kapiriri, Lydia; Norheim, Ole Frithjof; Martin, Douglas K
2007-06-01
The objectives of this study were (1) to describe the process of healthcare priority setting in Ontario-Canada, Norway and Uganda at the three levels of decision-making; (2) to evaluate the description using the framework for fair priority setting, accountability for reasonableness; so as to identify lessons of good practices. We carried out case studies involving key informant interviews, with 184 health practitioners and health planners from the macro-level, meso-level and micro-level from Canada-Ontario, Norway and Uganda (selected by virtue of their varying experiences in priority setting). Interviews were audio-recorded, transcribed and analyzed using a modified thematic approach. The descriptions were evaluated against the four conditions of "accountability for reasonableness", relevance, publicity, revisions and enforcement. Areas of adherence to these conditions were identified as lessons of good practices; areas of non-adherence were identified as opportunities for improvement. (i) at the macro-level, in all three countries, cabinet makes most of the macro-level resource allocation decisions and they are influenced by politics, public pressure, and advocacy. Decisions within the ministries of health are based on objective formulae and evidence. International priorities influenced decisions in Uganda. Some priority-setting reasons are publicized through circulars, printed documents and the Internet in Canada and Norway. At the meso-level, hospital priority-setting decisions were made by the hospital managers and were based on national priorities, guidelines, and evidence. Hospital departments that handle emergencies, such as surgery, were prioritized. Some of the reasons are available on the hospital intranet or presented at meetings. Micro-level practitioners considered medical and social worth criteria. These reasons are not publicized. Many practitioners lacked knowledge of the macro- and meso-level priority-setting processes. (ii) Evaluation
Reconstruction of thin electromagnetic inclusions by a level-set method
International Nuclear Information System (INIS)
Park, Won-Kwang; Lesselier, Dominique
2009-01-01
In this contribution, we consider a technique of electromagnetic imaging (at a single, non-zero frequency) which uses the level-set evolution method for reconstructing a thin inclusion (possibly made of disconnected parts) with either dielectric or magnetic contrast with respect to the embedding homogeneous medium. Emphasis is on the proof of the concept, the scattering problem at hand being so far based on a two-dimensional scalar model. To do so, two level-set functions are employed; the first one describes location and shape, and the other one describes connectivity and length. Speeds of evolution of the level-set functions are calculated via the introduction of Fréchet derivatives of a least-square cost functional. Several numerical experiments on noiseless and noisy data as well illustrate how the proposed method behaves
Aerostructural Level Set Topology Optimization for a Common Research Model Wing
Dunning, Peter D.; Stanford, Bret K.; Kim, H. Alicia
2014-01-01
The purpose of this work is to use level set topology optimization to improve the design of a representative wing box structure for the NASA common research model. The objective is to minimize the total compliance of the structure under aerodynamic and body force loading, where the aerodynamic loading is coupled to the structural deformation. A taxi bump case was also considered, where only body force loads were applied. The trim condition that aerodynamic lift must balance the total weight of the aircraft is enforced by allowing the root angle of attack to change. The level set optimization method is implemented on an unstructured three-dimensional grid, so that the method can optimize a wing box with arbitrary geometry. Fast matching and upwind schemes are developed for an unstructured grid, which make the level set method robust and efficient. The adjoint method is used to obtain the coupled shape sensitivities required to perform aerostructural optimization of the wing box structure.
Multi person detection and tracking based on hierarchical level-set method
Khraief, Chadia; Benzarti, Faouzi; Amiri, Hamid
2018-04-01
In this paper, we propose an efficient unsupervised method for mutli-person tracking based on hierarchical level-set approach. The proposed method uses both edge and region information in order to effectively detect objects. The persons are tracked on each frame of the sequence by minimizing an energy functional that combines color, texture and shape information. These features are enrolled in covariance matrix as region descriptor. The present method is fully automated without the need to manually specify the initial contour of Level-set. It is based on combined person detection and background subtraction methods. The edge-based is employed to maintain a stable evolution, guide the segmentation towards apparent boundaries and inhibit regions fusion. The computational cost of level-set is reduced by using narrow band technique. Many experimental results are performed on challenging video sequences and show the effectiveness of the proposed method.
Level set methods for detonation shock dynamics using high-order finite elements
Energy Technology Data Exchange (ETDEWEB)
Dobrev, V. A. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Grogan, F. C. [Univ. of California, San Diego, CA (United States); Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Kolev, T. V. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Rieben, R [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Tomov, V. Z. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
2017-05-26
Level set methods are a popular approach to modeling evolving interfaces. We present a level set ad- vection solver in two and three dimensions using the discontinuous Galerkin method with high-order nite elements. During evolution, the level set function is reinitialized to a signed distance function to maintain ac- curacy. Our approach leads to stable front propagation and convergence on high-order, curved, unstructured meshes. The ability of the solver to implicitly track moving fronts lends itself to a number of applications; in particular, we highlight applications to high-explosive (HE) burn and detonation shock dynamics (DSD). We provide results for two- and three-dimensional benchmark problems as well as applications to DSD.
A parametric level-set approach for topology optimization of flow domains
DEFF Research Database (Denmark)
Pingen, Georg; Waidmann, Matthias; Evgrafov, Anton
2010-01-01
of the design variables in the traditional approaches is seen as a possible cause for the slow convergence. Non-smooth material distributions are suspected to trigger premature onset of instationary flows which cannot be treated by steady-state flow models. In the present work, we study whether the convergence...... and the versatility of topology optimization methods for fluidic systems can be improved by employing a parametric level-set description. In general, level-set methods allow controlling the smoothness of boundaries, yield a non-local influence of design variables, and decouple the material description from the flow...... field discretization. The parametric level-set method used in this study utilizes a material distribution approach to represent flow boundaries, resulting in a non-trivial mapping between design variables and local material properties. Using a hydrodynamic lattice Boltzmann method, we study...
Setting-level influences on implementation of the responsive classroom approach.
Wanless, Shannon B; Patton, Christine L; Rimm-Kaufman, Sara E; Deutsch, Nancy L
2013-02-01
We used mixed methods to examine the association between setting-level factors and observed implementation of a social and emotional learning intervention (Responsive Classroom® approach; RC). In study 1 (N = 33 3rd grade teachers after the first year of RC implementation), we identified relevant setting-level factors and uncovered the mechanisms through which they related to implementation. In study 2 (N = 50 4th grade teachers after the second year of RC implementation), we validated our most salient Study 1 finding across multiple informants. Findings suggested that teachers perceived setting-level factors, particularly principal buy-in to the intervention and individualized coaching, as influential to their degree of implementation. Further, we found that intervention coaches' perspectives of principal buy-in were more related to implementation than principals' or teachers' perspectives. Findings extend the application of setting theory to the field of implementation science and suggest that interventionists may want to consider particular accounts of school setting factors before determining the likelihood of schools achieving high levels of implementation.
Robust boundary detection of left ventricles on ultrasound images using ASM-level set method.
Zhang, Yaonan; Gao, Yuan; Li, Hong; Teng, Yueyang; Kang, Yan
2015-01-01
Level set method has been widely used in medical image analysis, but it has difficulties when being used in the segmentation of left ventricular (LV) boundaries on echocardiography images because the boundaries are not very distinguish, and the signal-to-noise ratio of echocardiography images is not very high. In this paper, we introduce the Active Shape Model (ASM) into the traditional level set method to enforce shape constraints. It improves the accuracy of boundary detection and makes the evolution more efficient. The experiments conducted on the real cardiac ultrasound image sequences show a positive and promising result.
Directory of Open Access Journals (Sweden)
Pugalendhi Ganesh Kumar
Full Text Available This study describes a novel approach to reducing the challenges of highly nonlinear multiclass gene expression values for cancer diagnosis. To build a fruitful system for cancer diagnosis, in this study, we introduced two levels of gene selection such as filtering and embedding for selection of potential genes and the most relevant genes associated with cancer, respectively. The filter procedure was implemented by developing a fuzzy rough set (FR-based method for redefining the criterion function of f-information (FI to identify the potential genes without discretizing the continuous gene expression values. The embedded procedure is implemented by means of a water swirl algorithm (WSA, which attempts to optimize the rule set and membership function required to classify samples using a fuzzy-rule-based multiclassification system (FRBMS. Two novel update equations are proposed in WSA, which have better exploration and exploitation abilities while designing a self-learning FRBMS. The efficiency of our new approach was evaluated on 13 multicategory and 9 binary datasets of cancer gene expression. Additionally, the performance of the proposed FRFI-WSA method in designing an FRBMS was compared with existing methods for gene selection and optimization such as genetic algorithm (GA, particle swarm optimization (PSO, and artificial bee colony algorithm (ABC on all the datasets. In the global cancer map with repeated measurements (GCM_RM dataset, the FRFI-WSA showed the smallest number of 16 most relevant genes associated with cancer using a minimal number of 26 compact rules with the highest classification accuracy (96.45%. In addition, the statistical validation used in this study revealed that the biological relevance of the most relevant genes associated with cancer and their linguistics detected by the proposed FRFI-WSA approach are better than those in the other methods. The simple interpretable rules with most relevant genes and effectively
Individual-and Setting-Level Correlates of Secondary Traumatic Stress in Rape Crisis Center Staff.
Dworkin, Emily R; Sorell, Nicole R; Allen, Nicole E
2016-02-01
Secondary traumatic stress (STS) is an issue of significant concern among providers who work with survivors of sexual assault. Although STS has been studied in relation to individual-level characteristics of a variety of types of trauma responders, less research has focused specifically on rape crisis centers as environments that might convey risk or protection from STS, and no research to knowledge has modeled setting-level variation in correlates of STS. The current study uses a sample of 164 staff members representing 40 rape crisis centers across a single Midwestern state to investigate the staff member-and agency-level correlates of STS. Results suggest that correlates exist at both levels of analysis. Younger age and greater severity of sexual assault history were statistically significant individual-level predictors of increased STS. Greater frequency of supervision was more strongly related to secondary stress for non-advocates than for advocates. At the setting level, lower levels of supervision and higher client loads agency-wide accounted for unique variance in staff members' STS. These findings suggest that characteristics of both providers and their settings are important to consider when understanding their STS. © The Author(s) 2014.
Directory of Open Access Journals (Sweden)
Raúl Esteban Jiménez-Mejía
2015-06-01
Full Text Available This paper presents an algorithm used to automatically mesh a 3D computational domain in order to solve electromagnetic interaction scenarios by means of the Finite-Difference Time-Domain -FDTD- Method. The proposed algorithm has been formulated in a general mathematical form, where convenient spacing functions can be defined for the problem space discretization, allowing the inclusion of small sized objects in the FDTD method and the calculation of detailed variations of the electromagnetic field at specified regions of the computation domain. The results obtained by using the FDTD method with the proposed algorithm have been contrasted not only with a typical uniform mesh algorithm, but also with experimental measurements for a two-wire crosstalk set-up, leading to excellent agreement between theoretical and experimental waveforms. A discussion about the advantages of the non-uniform mesh over the uniform one is also presented.
Siuly; Li, Yan; Paul Wen, Peng
2014-03-01
Motor imagery (MI) tasks classification provides an important basis for designing brain-computer interface (BCI) systems. If the MI tasks are reliably distinguished through identifying typical patterns in electroencephalography (EEG) data, a motor disabled people could communicate with a device by composing sequences of these mental states. In our earlier study, we developed a cross-correlation based logistic regression (CC-LR) algorithm for the classification of MI tasks for BCI applications, but its performance was not satisfactory. This study develops a modified version of the CC-LR algorithm exploring a suitable feature set that can improve the performance. The modified CC-LR algorithm uses the C3 electrode channel (in the international 10-20 system) as a reference channel for the cross-correlation (CC) technique and applies three diverse feature sets separately, as the input to the logistic regression (LR) classifier. The present algorithm investigates which feature set is the best to characterize the distribution of MI tasks based EEG data. This study also provides an insight into how to select a reference channel for the CC technique with EEG signals considering the anatomical structure of the human brain. The proposed algorithm is compared with eight of the most recently reported well-known methods including the BCI III Winner algorithm. The findings of this study indicate that the modified CC-LR algorithm has potential to improve the identification performance of MI tasks in BCI systems. The results demonstrate that the proposed technique provides a classification improvement over the existing methods tested. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.
Yu, Lin-Sheng; Ye, Guang-Hua; Fan, Yan-Yan; Li, Xing-Biao; Feng, Xiang-Ping; Han, Jun-Ge; Lin, Ke-Zhi; Deng, Miao-Wu; Li, Feng
2015-09-01
Despite advances in medical science, the causes of death can sometimes only be determined by pathologists after a complete autopsy. Few studies have investigated the importance of forensic autopsy in medically disputed cases among different levels of institutional settings. Our study aimed to analyze forensic autopsy in 120 cases of medical disputes among five levels of institutional settings between 2001 and 2012 in Wenzhou, China. The results showed an overall concordance rate of 55%. Of the 39% of clinically missed diagnosis, cardiovascular pathology comprises 55.32%, while respiratory pathology accounts for the remaining 44. 68%. Factors that increase the likelihood of missed diagnoses were private clinics, community settings, and county hospitals. These results support that autopsy remains an important tool in establishing causes of death in medically disputed case, which may directly determine or exclude the fault of medical care and therefore in helping in resolving these cases. © 2015 American Academy of Forensic Sciences.
Directory of Open Access Journals (Sweden)
Ü. Niinemets
2010-06-01
Full Text Available In models of plant volatile isoprenoid emissions, the instantaneous compound emission rate typically scales with the plant's emission potential under specified environmental conditions, also called as the emission factor, E_{S}. In the most widely employed plant isoprenoid emission models, the algorithms developed by Guenther and colleagues (1991, 1993, instantaneous variation of the steady-state emission rate is described as the product of E_{S} and light and temperature response functions. When these models are employed in the atmospheric chemistry modeling community, species-specific E_{S} values and parameter values defining the instantaneous response curves are often taken as initially defined. In the current review, we argue that E_{S} as a characteristic used in the models importantly depends on our understanding of which environmental factors affect isoprenoid emissions, and consequently need standardization during experimental E_{S} determinations. In particular, there is now increasing consensus that in addition to variations in light and temperature, alterations in atmospheric and/or within-leaf CO_{2} concentrations may need to be included in the emission models. Furthermore, we demonstrate that for less volatile isoprenoids, mono- and sesquiterpenes, the emissions are often jointly controlled by the compound synthesis and volatility. Because of these combined biochemical and physico-chemical drivers, specification of E_{S} as a constant value is incapable of describing instantaneous emissions within the sole assumptions of fluctuating light and temperature as used in the standard algorithms. The definition of E_{S} also varies depending on the degree of aggregation of E_{S} values in different parameterization schemes (leaf- vs. canopy- or region-scale, species vs. plant functional type levels and various
An investigation of children's levels of inquiry in an informal science setting
Clark-Thomas, Beth Anne
Elementary school students' understanding of both science content and processes are enhanced by the higher level thinking associated with inquiry-based science investigations. Informal science setting personnel, elementary school teachers, and curriculum specialists charged with designing inquiry-based investigations would be well served by an understanding of the varying influence of certain present factors upon the students' willingness and ability to delve into such higher level inquiries. This study examined young children's use of inquiry-based materials and factors which may influence the level of inquiry they engaged in during informal science activities. An informal science setting was selected as the context for the examination of student inquiry behaviors because of the rich inquiry-based environment present at the site and the benefits previously noted in the research regarding the impact of informal science settings upon the construction of knowledge in science. The study revealed several patterns of behavior among children when they are engaged in inquiry-based activities at informal science exhibits. These repeated behaviors varied in the children's apparent purposeful use of the materials at the exhibits. These levels of inquiry behavior were taxonomically defined as high/medium/low within this study utilizing a researcher-developed tool. Furthermore, in this study adult interventions, questions, or prompting were found to impact the level of inquiry engaged in by the children. This study revealed that higher levels of inquiry were preceded by task directed and physical feature prompts. Moreover, the levels of inquiry behaviors were haltered, even lowered, when preceded by a prompt that focused on a science content or concept question. Results of this study have implications for the enhancement of inquiry-based science activities in elementary schools as well as in informal science settings. These findings have significance for all science educators
Borrell, C.; Plasència, A.; Huisman, M.; Costa, G.; Kunst, A.; Andersen, O.; Bopp, M.; Borgan, J.-K.; Deboosere, P.; Glickman, M.; Gadeyne, S.; Minder, C.; Regidor, E.; Spadea, T.; Valkonen, T.; Mackenbach, J. P.
2005-01-01
OBJECTIVE: To study the differential distribution of transportation injury mortality by educational level in nine European settings, among people older than 30 years, during the 1990s. METHODS: Deaths of men and women older than 30 years from transportation injuries were studied. Rate differences
A thick level set interface model for simulating fatigue-drive delamination in composites
Latifi, M.; Van der Meer, F.P.; Sluys, L.J.
2015-01-01
This paper presents a new damage model for simulating fatigue-driven delamination in composite laminates. This model is developed based on the Thick Level Set approach (TLS) and provides a favorable link between damage mechanics and fracture mechanics through the non-local evaluation of the energy
Level of health care and services in a tertiary health setting in Nigeria
African Journals Online (AJOL)
Level of health care and services in a tertiary health setting in Nigeria. ... Background: There is a growing awareness and demand for quality health care across the world; hence the ... Doctors and nurses formed 64.3% of the study population.
Two Surface-Tension Formulations For The Level Set Interface-Tracking Method
International Nuclear Information System (INIS)
Shepel, S.V.; Smith, B.L.
2005-01-01
The paper describes a comparative study of two surface-tension models for the Level Set interface tracking method. In both models, the surface tension is represented as a body force, concentrated near the interface, but the technical implementation of the two options is different. The first is based on a traditional Level Set approach, in which the surface tension is distributed over a narrow band around the interface using a smoothed Delta function. In the second model, which is based on the integral form of the fluid-flow equations, the force is imposed only in those computational cells through which the interface passes. Both models have been incorporated into the Finite-Element/Finite-Volume Level Set method, previously implemented into the commercial Computational Fluid Dynamics (CFD) code CFX-4. A critical evaluation of the two models, undertaken in the context of four standard Level Set benchmark problems, shows that the first model, based on the smoothed Delta function approach, is the more general, and more robust, of the two. (author)
Fast Streaming 3D Level set Segmentation on the GPU for Smooth Multi-phase Segmentation
DEFF Research Database (Denmark)
Sharma, Ojaswa; Zhang, Qin; Anton, François
2011-01-01
Level set method based segmentation provides an efficient tool for topological and geometrical shape handling, but it is slow due to high computational burden. In this work, we provide a framework for streaming computations on large volumetric images on the GPU. A streaming computational model...
Multi-domain, higher order level set scheme for 3D image segmentation on the GPU
DEFF Research Database (Denmark)
Sharma, Ojaswa; Zhang, Qin; Anton, François
2010-01-01
to evaluate level set surfaces that are $C^2$ continuous, but are slow due to high computational burden. In this paper, we provide a higher order GPU based solver for fast and efficient segmentation of large volumetric images. We also extend the higher order method to multi-domain segmentation. Our streaming...
An Optimized, Grid Independent, Narrow Band Data Structure for High Resolution Level Sets
DEFF Research Database (Denmark)
Nielsen, Michael Bang; Museth, Ken
2004-01-01
enforced by the convex boundaries of an underlying cartesian computational grid. Here we present a novel very memory efficient narrow band data structure, dubbed the Sparse Grid, that enables the representation of grid independent high resolution level sets. The key features our new data structure are...
Scope of physician procedures independently billed by mid-level providers in the office setting.
Coldiron, Brett; Ratnarathorn, Mondhipa
2014-11-01
Mid-level providers (nurse practitioners and physician assistants) were originally envisioned to provide primary care services in underserved areas. This study details the current scope of independent procedural billing to Medicare of difficult, invasive, and surgical procedures by medical mid-level providers. To understand the scope of independent billing to Medicare for procedures performed by mid-level providers in an outpatient office setting for a calendar year. Analyses of the 2012 Medicare Physician/Supplier Procedure Summary Master File, which reflects fee-for-service claims that were paid by Medicare, for Current Procedural Terminology procedures independently billed by mid-level providers. Outpatient office setting among health care providers. The scope of independent billing to Medicare for procedures performed by mid-level providers. In 2012, nurse practitioners and physician assistants billed independently for more than 4 million procedures at our cutoff of 5000 paid claims per procedure. Most (54.8%) of these procedures were performed in the specialty area of dermatology. The findings of this study are relevant to safety and quality of care. Recently, the shortage of primary care clinicians has prompted discussion of widening the scope of practice for mid-level providers. It would be prudent to temper widening the scope of practice of mid-level providers by recognizing that mid-level providers are not solely limited to primary care, and may involve procedures for which they may not have formal training.
Directory of Open Access Journals (Sweden)
Francisco Garcia
2017-01-01
Full Text Available Location privacy in wireless networks is nowadays a major concern. This is due to the fact that the mere fact of transmitting may allow a network to pinpoint a mobile node. We consider that a first step to protect a mobile node in this situation is to provide it with the means to quantify how accurately a network establishes its position. To achieve this end, we introduce the location-exposure algorithm (LEA, which runs on the mobile terminal only and whose operation consists of two steps. In the first step, LEA discovers the positions of nearby network nodes and uses this information to emulate how they estimate the position of the mobile node. In the second step, it quantifies the level of exposure by computing the distance between the position estimated in the first step and its true position. We refer to these steps as a location-exposure problem. We tested our proposal with simulations and testbed experiments. These results show the ability of LEA to reproduce the location of the mobile node, as seen by the network, and to quantify the level of exposure. This knowledge can help the mobile user decide which actions should be performed before transmitting.
Online monitoring of oil film using electrical capacitance tomography and level set method
International Nuclear Information System (INIS)
Xue, Q.; Ma, M.; Sun, B. Y.; Cui, Z. Q.; Wang, H. X.
2015-01-01
In the application of oil-air lubrication system, electrical capacitance tomography (ECT) provides a promising way for monitoring oil film in the pipelines by reconstructing cross sectional oil distributions in real time. While in the case of small diameter pipe and thin oil film, the thickness of the oil film is hard to be observed visually since the interface of oil and air is not obvious in the reconstructed images. And the existence of artifacts in the reconstructions has seriously influenced the effectiveness of image segmentation techniques such as level set method. Besides, level set method is also unavailable for online monitoring due to its low computation speed. To address these problems, a modified level set method is developed: a distance regularized level set evolution formulation is extended to image two-phase flow online using an ECT system, a narrowband image filter is defined to eliminate the influence of artifacts, and considering the continuity of the oil distribution variation, the detected oil-air interface of a former image can be used as the initial contour for the detection of the subsequent frame; thus, the propagation from the initial contour to the boundary can be greatly accelerated, making it possible for real time tracking. To testify the feasibility of the proposed method, an oil-air lubrication facility with 4 mm inner diameter pipe is measured in normal operation using an 8-electrode ECT system. Both simulation and experiment results indicate that the modified level set method is capable of visualizing the oil-air interface accurately online
Two parameter-tuned metaheuristic algorithms for the multi-level lot sizing and scheduling problem
Directory of Open Access Journals (Sweden)
S.M.T. Fatemi Ghomi
2012-10-01
Full Text Available This paper addresses the problem of lot sizing and scheduling problem for n-products and m-machines in flow shop environment where setups among machines are sequence-dependent and can be carried over. Many products must be produced under capacity constraints and allowing backorders. Since lot sizing and scheduling problems are well-known strongly NP-hard, much attention has been given to heuristics and metaheuristics methods. This paper presents two metaheuristics algorithms namely, Genetic Algorithm (GA and Imperialist Competitive Algorithm (ICA. Moreover, Taguchi robust design methodology is employed to calibrate the parameters of the algorithms for different size problems. In addition, the parameter-tuned algorithms are compared against a presented lower bound on randomly generated problems. At the end, comprehensive numerical examples are presented to demonstrate the effectiveness of the proposed algorithms. The results showed that the performance of both GA and ICA are very promising and ICA outperforms GA statistically.
INTEGRATED SFM TECHNIQUES USING DATA SET FROM GOOGLE EARTH 3D MODEL AND FROM STREET LEVEL
Directory of Open Access Journals (Sweden)
L. Inzerillo
2017-08-01
Full Text Available Structure from motion (SfM represents a widespread photogrammetric method that uses the photogrammetric rules to carry out a 3D model from a photo data set collection. Some complex ancient buildings, such as Cathedrals, or Theatres, or Castles, etc. need to implement the data set (realized from street level with the UAV one in order to have the 3D roof reconstruction. Nevertheless, the use of UAV is strong limited from the government rules. In these last years, Google Earth (GE has been enriched with the 3D models of the earth sites. For this reason, it seemed convenient to start to test the potentiality offered by GE in order to extract from it a data set that replace the UAV function, to close the aerial building data set, using screen images of high resolution 3D models. Users can take unlimited “aerial photos” of a scene while flying around in GE at any viewing angle and altitude. The challenge is to verify the metric reliability of the SfM model carried out with an integrated data set (the one from street level and the one from GE aimed at replace the UAV use in urban contest. This model is called integrated GE SfM model (i-GESfM. In this paper will be present a case study: the Cathedral of Palermo.
Directory of Open Access Journals (Sweden)
Cheng-Hong Yang
Full Text Available BACKGROUND: Complete mitochondrial (mt genome sequencing is becoming increasingly common for phylogenetic reconstruction and as a model for genome evolution. For long template sequencing, i.e., like the entire mtDNA, it is essential to design primers for Polymerase Chain Reaction (PCR amplicons which are partly overlapping each other. The presented chromosome walking strategy provides the overlapping design to solve the problem for unreliable sequencing data at the 5' end and provides the effective sequencing. However, current algorithms and tools are mostly focused on the primer design for a local region in the genomic sequence. Accordingly, it is still challenging to provide the primer sets for the entire mtDNA. METHODOLOGY/PRINCIPAL FINDINGS: The purpose of this study is to develop an integrated primer design algorithm for entire mt genome in general, and for the common primer sets for closely-related species in particular. We introduce ClustalW to generate the multiple sequence alignment needed to find the conserved sequences in closely-related species. These conserved sequences are suitable for designing the common primers for the entire mtDNA. Using a heuristic algorithm particle swarm optimization (PSO, all the designed primers were computationally validated to fit the common primer design constraints, such as the melting temperature, primer length and GC content, PCR product length, secondary structure, specificity, and terminal limitation. The overlap requirement for PCR amplicons in the entire mtDNA is satisfied by defining the overlapping region with the sliding window technology. Finally, primer sets were designed within the overlapping region. The primer sets for the entire mtDNA sequences were successfully demonstrated in the example of two closely-related fish species. The pseudo code for the primer design algorithm is provided. CONCLUSIONS/SIGNIFICANCE: In conclusion, it can be said that our proposed sliding window-based PSO
Broglia, Riccardo; Durante, Danilo
2017-11-01
This paper focuses on the analysis of a challenging free surface flow problem involving a surface vessel moving at high speeds, or planing. The investigation is performed using a general purpose high Reynolds free surface solver developed at CNR-INSEAN. The methodology is based on a second order finite volume discretization of the unsteady Reynolds-averaged Navier-Stokes equations (Di Mascio et al. in A second order Godunov—type scheme for naval hydrodynamics, Kluwer Academic/Plenum Publishers, Dordrecht, pp 253-261, 2001; Proceedings of 16th international offshore and polar engineering conference, San Francisco, CA, USA, 2006; J Mar Sci Technol 14:19-29, 2009); air/water interface dynamics is accurately modeled by a non standard level set approach (Di Mascio et al. in Comput Fluids 36(5):868-886, 2007a), known as the single-phase level set method. In this algorithm the governing equations are solved only in the water phase, whereas the numerical domain in the air phase is used for a suitable extension of the fluid dynamic variables. The level set function is used to track the free surface evolution; dynamic boundary conditions are enforced directly on the interface. This approach allows to accurately predict the evolution of the free surface even in the presence of violent breaking waves phenomena, maintaining the interface sharp, without any need to smear out the fluid properties across the two phases. This paper is aimed at the prediction of the complex free-surface flow field generated by a deep-V planing boat at medium and high Froude numbers (from 0.6 up to 1.2). In the present work, the planing hull is treated as a two-degree-of-freedom rigid object. Flow field is characterized by the presence of thin water sheets, several energetic breaking waves and plungings. The computational results include convergence of the trim angle, sinkage and resistance under grid refinement; high-quality experimental data are used for the purposes of validation, allowing to
Image-guided regularization level set evolution for MR image segmentation and bias field correction.
Wang, Lingfeng; Pan, Chunhong
2014-01-01
Magnetic resonance (MR) image segmentation is a crucial step in surgical and treatment planning. In this paper, we propose a level-set-based segmentation method for MR images with intensity inhomogeneous problem. To tackle the initialization sensitivity problem, we propose a new image-guided regularization to restrict the level set function. The maximum a posteriori inference is adopted to unify segmentation and bias field correction within a single framework. Under this framework, both the contour prior and the bias field prior are fully used. As a result, the image intensity inhomogeneity can be well solved. Extensive experiments are provided to evaluate the proposed method, showing significant improvements in both segmentation and bias field correction accuracies as compared with other state-of-the-art approaches. Copyright © 2014 Elsevier Inc. All rights reserved.
Level Set Projection Method for Incompressible Navier-Stokes on Arbitrary Boundaries
Williams-Rioux, Bertrand
2012-01-12
Second order level set projection method for incompressible Navier-Stokes equations is proposed to solve flow around arbitrary geometries. We used rectilinear grid with collocated cell centered velocity and pressure. An explicit Godunov procedure is used to address the nonlinear advection terms, and an implicit Crank-Nicholson method to update viscous effects. An approximate pressure projection is implemented at the end of the time stepping using multigrid as a conventional fast iterative method. The level set method developed by Osher and Sethian [17] is implemented to address real momentum and pressure boundary conditions by the advection of a distance function, as proposed by Aslam [3]. Numerical results for the Strouhal number and drag coefficients validated the model with good accuracy for flow over a cylinder in the parallel shedding regime (47 < Re < 180). Simulations for an array of cylinders and an oscillating cylinder were performed, with the latter demonstrating our methods ability to handle dynamic boundary conditions.
A Cartesian Adaptive Level Set Method for Two-Phase Flows
Ham, F.; Young, Y.-N.
2003-01-01
In the present contribution we develop a level set method based on local anisotropic Cartesian adaptation as described in Ham et al. (2002). Such an approach should allow for the smallest possible Cartesian grid capable of resolving a given flow. The remainder of the paper is organized as follows. In section 2 the level set formulation for free surface calculations is presented and its strengths and weaknesses relative to the other free surface methods reviewed. In section 3 the collocated numerical method is described. In section 4 the method is validated by solving the 2D and 3D drop oscilation problem. In section 5 we present some results from more complex cases including the 3D drop breakup in an impulsively accelerated free stream, and the 3D immiscible Rayleigh-Taylor instability. Conclusions are given in section 6.
Application of the level set method for multi-phase flow computation in fusion engineering
International Nuclear Information System (INIS)
Luo, X-Y.; Ni, M-J.; Ying, A.; Abdou, M.
2006-01-01
Numerical simulation of multi-phase flow is essential to evaluate the feasibility of a liquid protection scheme for the power plant chamber. The level set method is one of the best methods for computing and analyzing the motion of interface among the multi-phase flow. This paper presents a general formula for the second-order projection method combined with the level set method to simulate unsteady incompressible multi-phase flow with/out phase change flow encountered in fusion science and engineering. The third-order ENO scheme and second-order semi-implicit Crank-Nicholson scheme is used to update the convective and diffusion term. The numerical results show this method can handle the complex deformation of the interface and the effect of liquid-vapor phase change will be included in the future work
Embedded Real-Time Architecture for Level-Set-Based Active Contours
Directory of Open Access Journals (Sweden)
Dejnožková Eva
2005-01-01
Full Text Available Methods described by partial differential equations have gained a considerable interest because of undoubtful advantages such as an easy mathematical description of the underlying physics phenomena, subpixel precision, isotropy, or direct extension to higher dimensions. Though their implementation within the level set framework offers other interesting advantages, their vast industrial deployment on embedded systems is slowed down by their considerable computational effort. This paper exploits the high parallelization potential of the operators from the level set framework and proposes a scalable, asynchronous, multiprocessor platform suitable for system-on-chip solutions. We concentrate on obtaining real-time execution capabilities. The performance is evaluated on a continuous watershed and an object-tracking application based on a simple gradient-based attraction force driving the active countour. The proposed architecture can be realized on commercially available FPGAs. It is built around general-purpose processor cores, and can run code developed with usual tools.
Kir2.1 channels set two levels of resting membrane potential with inward rectification.
Chen, Kuihao; Zuo, Dongchuan; Liu, Zheng; Chen, Haijun
2018-04-01
Strong inward rectifier K + channels (Kir2.1) mediate background K + currents primarily responsible for maintenance of resting membrane potential. Multiple types of cells exhibit two levels of resting membrane potential. Kir2.1 and K2P1 currents counterbalance, partially accounting for the phenomenon of human cardiomyocytes in subphysiological extracellular K + concentrations or pathological hypokalemic conditions. The mechanism of how Kir2.1 channels contribute to the two levels of resting membrane potential in different types of cells is not well understood. Here we test the hypothesis that Kir2.1 channels set two levels of resting membrane potential with inward rectification. Under hypokalemic conditions, Kir2.1 currents counterbalance HCN2 or HCN4 cation currents in CHO cells that heterologously express both channels, generating N-shaped current-voltage relationships that cross the voltage axis three times and reconstituting two levels of resting membrane potential. Blockade of HCN channels eliminated the phenomenon in K2P1-deficient Kir2.1-expressing human cardiomyocytes derived from induced pluripotent stem cells or CHO cells expressing both Kir2.1 and HCN2 channels. Weakly inward rectifier Kir4.1 or inward rectification-deficient Kir2.1•E224G mutant channels do not set such two levels of resting membrane potential when co-expressed with HCN2 channels in CHO cells or when overexpressed in human cardiomyocytes derived from induced pluripotent stem cells. These findings demonstrate a common mechanism that Kir2.1 channels set two levels of resting membrane potential with inward rectification by balancing inward currents through different cation channels such as hyperpolarization-activated HCN channels or hypokalemia-induced K2P1 leak channels.
Reconstruction of incomplete cell paths through a 3D-2D level set segmentation
Hariri, Maia; Wan, Justin W. L.
2012-02-01
Segmentation of fluorescent cell images has been a popular technique for tracking live cells. One challenge of segmenting cells from fluorescence microscopy is that cells in fluorescent images frequently disappear. When the images are stacked together to form a 3D image volume, the disappearance of the cells leads to broken cell paths. In this paper, we present a segmentation method that can reconstruct incomplete cell paths. The key idea of this model is to perform 2D segmentation in a 3D framework. The 2D segmentation captures the cells that appear in the image slices while the 3D segmentation connects the broken cell paths. The formulation is similar to the Chan-Vese level set segmentation which detects edges by comparing the intensity value at each voxel with the mean intensity values inside and outside of the level set surface. Our model, however, performs the comparison on each 2D slice with the means calculated by the 2D projected contour. The resulting effect is to segment the cells on each image slice. Unlike segmentation on each image frame individually, these 2D contours together form the 3D level set function. By enforcing minimum mean curvature on the level set surface, our segmentation model is able to extend the cell contours right before (and after) the cell disappears (and reappears) into the gaps, eventually connecting the broken paths. We will present segmentation results of C2C12 cells in fluorescent images to illustrate the effectiveness of our model qualitatively and quantitatively by different numerical examples.
Laadhari , Aymen; Saramito , Pierre; Misbah , Chaouqi
2014-01-01
International audience; The numerical simulation of the deformation of vesicle membranes under simple shear external fluid flow is considered in this paper. A new saddle-point approach is proposed for the imposition of the fluid incompressibility and the membrane inextensibility constraints, through Lagrange multipliers defined in the fluid and on the membrane respectively. Using a level set formulation, the problem is approximated by mixed finite elements combined with an automatic adaptive ...
Energy Technology Data Exchange (ETDEWEB)
Zhou, Shenggao, E-mail: sgzhou@suda.edu.cn, E-mail: bli@math.ucsd.edu [Department of Mathematics and Mathematical Center for Interdiscipline Research, Soochow University, 1 Shizi Street, Jiangsu, Suzhou 215006 (China); Sun, Hui; Cheng, Li-Tien [Department of Mathematics, University of California, San Diego, La Jolla, California 92093-0112 (United States); Dzubiella, Joachim [Soft Matter and Functional Materials, Helmholtz-Zentrum Berlin, 14109 Berlin, Germany and Institut für Physik, Humboldt-Universität zu Berlin, 12489 Berlin (Germany); Li, Bo, E-mail: sgzhou@suda.edu.cn, E-mail: bli@math.ucsd.edu [Department of Mathematics and Quantitative Biology Graduate Program, University of California, San Diego, La Jolla, California 92093-0112 (United States); McCammon, J. Andrew [Department of Chemistry and Biochemistry, Department of Pharmacology, Howard Hughes Medical Institute, University of California, San Diego, La Jolla, California 92093-0365 (United States)
2016-08-07
Recent years have seen the initial success of a variational implicit-solvent model (VISM), implemented with a robust level-set method, in capturing efficiently different hydration states and providing quantitatively good estimation of solvation free energies of biomolecules. The level-set minimization of the VISM solvation free-energy functional of all possible solute-solvent interfaces or dielectric boundaries predicts an equilibrium biomolecular conformation that is often close to an initial guess. In this work, we develop a theory in the form of Langevin geometrical flow to incorporate solute-solvent interfacial fluctuations into the VISM. Such fluctuations are crucial to biomolecular conformational changes and binding process. We also develop a stochastic level-set method to numerically implement such a theory. We describe the interfacial fluctuation through the “normal velocity” that is the solute-solvent interfacial force, derive the corresponding stochastic level-set equation in the sense of Stratonovich so that the surface representation is independent of the choice of implicit function, and develop numerical techniques for solving such an equation and processing the numerical data. We apply our computational method to study the dewetting transition in the system of two hydrophobic plates and a hydrophobic cavity of a synthetic host molecule cucurbit[7]uril. Numerical simulations demonstrate that our approach can describe an underlying system jumping out of a local minimum of the free-energy functional and can capture dewetting transitions of hydrophobic systems. In the case of two hydrophobic plates, we find that the wavelength of interfacial fluctuations has a strong influence to the dewetting transition. In addition, we find that the estimated energy barrier of the dewetting transition scales quadratically with the inter-plate distance, agreeing well with existing studies of molecular dynamics simulations. Our work is a first step toward the
Level-set simulations of buoyancy-driven motion of single and multiple bubbles
International Nuclear Information System (INIS)
Balcázar, Néstor; Lehmkuhl, Oriol; Jofre, Lluís; Oliva, Assensi
2015-01-01
Highlights: • A conservative level-set method is validated and verified. • An extensive study of buoyancy-driven motion of single bubbles is performed. • The interactions of two spherical and ellipsoidal bubbles is studied. • The interaction of multiple bubbles is simulated in a vertical channel. - Abstract: This paper presents a numerical study of buoyancy-driven motion of single and multiple bubbles by means of the conservative level-set method. First, an extensive study of the hydrodynamics of single bubbles rising in a quiescent liquid is performed, including its shape, terminal velocity, drag coefficients and wake patterns. These results are validated against experimental and numerical data well established in the scientific literature. Then, a further study on the interaction of two spherical and ellipsoidal bubbles is performed for different orientation angles. Finally, the interaction of multiple bubbles is explored in a periodic vertical channel. The results show that the conservative level-set approach can be used for accurate modelling of bubble dynamics. Moreover, it is demonstrated that the present method is numerically stable for a wide range of Morton and Reynolds numbers.
Stabilized Conservative Level Set Method with Adaptive Wavelet-based Mesh Refinement
Shervani-Tabar, Navid; Vasilyev, Oleg V.
2016-11-01
This paper addresses one of the main challenges of the conservative level set method, namely the ill-conditioned behavior of the normal vector away from the interface. An alternative formulation for reconstruction of the interface is proposed. Unlike the commonly used methods which rely on the unit normal vector, Stabilized Conservative Level Set (SCLS) uses a modified renormalization vector with diminishing magnitude away from the interface. With the new formulation, in the vicinity of the interface the reinitialization procedure utilizes compressive flux and diffusive terms only in the normal direction to the interface, thus, preserving the conservative level set properties, while away from the interfaces the directional diffusion mechanism automatically switches to homogeneous diffusion. The proposed formulation is robust and general. It is especially well suited for use with adaptive mesh refinement (AMR) approaches due to need for a finer resolution in the vicinity of the interface in comparison with the rest of the domain. All of the results were obtained using the Adaptive Wavelet Collocation Method, a general AMR-type method, which utilizes wavelet decomposition to adapt on steep gradients in the solution while retaining a predetermined order of accuracy.
Ortiz-Osorno, Alberto Betto; Ehler, Linda A; Brooks, Judith
2015-01-01
Determining what constitutes an anticipatable incidental finding (IF) from clinical research and defining whether, and when, this IF should be returned to the participant have been topics of discussion in the field of human subject protections for the last 10 years. It has been debated that implementing a comprehensive IF-approach that addresses both the responsibility of researchers to return IFs and the expectation of participants to receive them can be logistically challenging. IFs have been debated at different levels, such as the ethical reasoning for considering their disclosure or the need for planning for them during the development of the research study. Some authors have discussed the methods for re-contacting participants for disclosing IFs, as well as the relevance of considering the clinical importance of the IFs. Similarly, other authors have debated about when IFs should be disclosed to participants. However, no author has addressed how the "actionability" of the IFs should be considered, evaluated, or characterized at the participant's research setting level. This paper defines the concept of "Actionability at the Participant's Research Setting Level" (APRSL) for anticipatable IFs from clinical research, discusses some related ethical concepts to justify the APRSL concept, proposes a strategy to incorporate APRSL into the planning and management of IFs, and suggests a strategy for integrating APRSL at each local research setting. © 2015 American Society of Law, Medicine & Ethics, Inc.
International Nuclear Information System (INIS)
2004-07-01
The objective of this publication is to highlight the importance of the early establishment of a comprehensive records system to manage primary level information (PLI) as an integrated set of information, not merely as a collection of information, throughout all the phases of radioactive waste management. Early establishment of a comprehensive records system to manage Primary Level Information as an integrated set of information throughout all phases of radioactive waste management is important. In addition to the information described in the waste inventory record keeping system (WIRKS), the PLI of a radioactive waste repository consists of the entire universe of information, data and records related to any aspect of the repository's life cycle. It is essential to establish PLI requirements based on integrated set of needs from Regulators and Waste Managers involved in the waste management chain and to update these requirements as needs change over time. Information flow for radioactive waste management should be back-end driven. Identification of an Authority that will oversee the management of PLI throughout all phases of the radioactive waste management life cycle would guarantee the information flow to future generations. The long term protection of information essential to future generations can only be assured by the timely establishment of a comprehensive and effective RMS capable of capturing, indexing and evaluating all PLI. The loss of intellectual control over the PLI will make it very difficult to subsequently identify the ILI and HLI information sets. At all times prior to the closure of a radioactive waste repository, there should be an identifiable entity with a legally enforceable financial and management responsibility for the continued operation of a PLI Records Management System. The information presented in this publication will assist Member States in ensuring that waste and repository records, relevant for retention after repository closure
Topological Hausdorff dimension and level sets of generic continuous functions on fractals
International Nuclear Information System (INIS)
Balka, Richárd; Buczolich, Zoltán; Elekes, Márton
2012-01-01
Highlights: ► We examine a new fractal dimension, the so called topological Hausdorff dimension. ► The generic continuous function has a level set of maximal Hausdorff dimension. ► This maximal dimension is the topological Hausdorff dimension minus one. ► Homogeneity implies that “most” level sets are of this dimension. ► We calculate the various dimensions of the graph of the generic function. - Abstract: In an earlier paper we introduced a new concept of dimension for metric spaces, the so called topological Hausdorff dimension. For a compact metric space K let dim H K and dim tH K denote its Hausdorff and topological Hausdorff dimension, respectively. We proved that this new dimension describes the Hausdorff dimension of the level sets of the generic continuous function on K, namely sup{ dim H f -1 (y):y∈R} =dim tH K-1 for the generic f ∈ C(K), provided that K is not totally disconnected, otherwise every non-empty level set is a singleton. We also proved that if K is not totally disconnected and sufficiently homogeneous then dim H f −1 (y) = dim tH K − 1 for the generic f ∈ C(K) and the generic y ∈ f(K). The most important goal of this paper is to make these theorems more precise. As for the first result, we prove that the supremum is actually attained on the left hand side of the first equation above, and also show that there may only be a unique level set of maximal Hausdorff dimension. As for the second result, we characterize those compact metric spaces for which for the generic f ∈ C(K) and the generic y ∈ f(K) we have dim H f −1 (y) = dim tH K − 1. We also generalize a result of B. Kirchheim by showing that if K is self-similar then for the generic f ∈ C(K) for every y∈intf(K) we have dim H f −1 (y) = dim tH K − 1. Finally, we prove that the graph of the generic f ∈ C(K) has the same Hausdorff and topological Hausdorff dimension as K.
A combined single-multiphase flow formulation of the premixing phase using the level set method
International Nuclear Information System (INIS)
Leskovar, M.; Marn, J.
1999-01-01
The premixing phase of a steam explosion covers the interaction of the melt jet or droplets with the water prior to any steam explosion occurring. To get a better insight of the hydrodynamic processes during the premixing phase beside hot premixing experiments, where the water evaporation is significant, also cold isothermal premixing experiments are performed. The specialty of isothermal premixing experiments is that three phases are involved: the water, the air and the spheres phase, but only the spheres phase mixes with the other two phases whereas the water and air phases do not mix and remain separated by a free surface. Our idea therefore was to treat the isothermal premixing process with a combined single-multiphase flow model. In this combined model the water and air phase are treated as a single phase with discontinuous phase properties at the water air interface, whereas the spheres are treated as usually with a multiphase flow model, where the spheres represent the dispersed phase and the common water-air phase represents the continuous phase. The common water-air phase was described with the front capturing method based on the level set formulation. In the level set formulation, the boundary of two-fluid interfaces is modeled as the zero set of a smooth signed normal distance function defined on the entire physical domain. The boundary is then updated by solving a nonlinear equation of the Hamilton-Jacobi type on the whole domain. With this single-multiphase flow model the Queos isothermal premixing Q08 has been simulated. A numerical analysis using different treatments of the water-air interface (level set, high-resolution and upwind) has been performed for the incompressible and compressible case and the results were compared to experimental measurements.(author)
Multi-Level Sensor Fusion Algorithm Approach for BMD Interceptor Applications
National Research Council Canada - National Science Library
Allen, Doug
1998-01-01
... through fabrication and testing of advanced sensor hardware concepts and advanced sensor fusion algorithms. Advanced sensor concepts include onboard LADAR in conjunction with a multi-color passive IR sensor...
Galuzzi, C.
2009-01-01
In this dissertation, we address the design of algorithms for the automatic identi?cation and selection of complex application-speci?c instructions used to speed up the execution of applications on recon?gurable architectures. The computationally intensive portions of an application are analyzed and
Rashno, Abdolreza; Koozekanani, Dara D; Drayna, Paul M; Nazari, Behzad; Sadri, Saeed; Rabbani, Hossein; Parhi, Keshab K
2018-05-01
This paper presents a fully automated algorithm to segment fluid-associated (fluid-filled) and cyst regions in optical coherence tomography (OCT) retina images of subjects with diabetic macular edema. The OCT image is segmented using a novel neutrosophic transformation and a graph-based shortest path method. In neutrosophic domain, an image is transformed into three sets: (true), (indeterminate) that represents noise, and (false). This paper makes four key contributions. First, a new method is introduced to compute the indeterminacy set , and a new -correction operation is introduced to compute the set in neutrosophic domain. Second, a graph shortest-path method is applied in neutrosophic domain to segment the inner limiting membrane and the retinal pigment epithelium as regions of interest (ROI) and outer plexiform layer and inner segment myeloid as middle layers using a novel definition of the edge weights . Third, a new cost function for cluster-based fluid/cyst segmentation in ROI is presented which also includes a novel approach in estimating the number of clusters in an automated manner. Fourth, the final fluid regions are achieved by ignoring very small regions and the regions between middle layers. The proposed method is evaluated using two publicly available datasets: Duke, Optima, and a third local dataset from the UMN clinic which is available online. The proposed algorithm outperforms the previously proposed Duke algorithm by 8% with respect to the dice coefficient and by 5% with respect to precision on the Duke dataset, while achieving about the same sensitivity. Also, the proposed algorithm outperforms a prior method for Optima dataset by 6%, 22%, and 23% with respect to the dice coefficient, sensitivity, and precision, respectively. Finally, the proposed algorithm also achieves sensitivity of 67.3%, 88.8%, and 76.7%, for the Duke, Optima, and the university of minnesota (UMN) datasets, respectively.
Improved inhalation technology for setting safe exposure levels for workplace chemicals
Stuart, Bruce O.
1993-01-01
Threshold Limit Values recommended as allowable air concentrations of a chemical in the workplace are often based upon a no-observable-effect-level (NOEL) determined by experimental inhalation studies using rodents. A 'safe level' for human exposure must then be estimated by the use of generalized safety factors in attempts to extrapolate from experimental rodents to man. The recent development of chemical-specific physiologically-based toxicokinetics makes use of measured physiological, biochemical, and metabolic parameters to construct a validated model that is able to 'scale-up' rodent response data to predict the behavior of the chemical in man. This procedure is made possible by recent advances in personal computer software and the emergence of appropriate biological data, and provides an analytical tool for much more reliable risk evaluation and airborne chemical exposure level setting for humans.
International Nuclear Information System (INIS)
Bolte, H.; Jahnke, T.; Schaefer, F.K.W.; Wenke, R.; Hoffmann, B.; Freitag-Wolf, S.; Dicken, V.; Kuhnigk, J.M.; Lohmann, J.; Voss, S.; Knoess, N.
2007-01-01
Objective: The aim of this study was to investigate the interobserver variability of CT based diameter and volumetric measurements of artificial pulmonary nodules. A special interest was the consideration of different measurement methods, observer experience and training levels. Materials and methods: For this purpose 46 artificial small solid nodules were examined in a dedicated ex-vivo chest phantom with multislice-spiral CT (20 mAs, 120 kV, collimation 16 mm x 0.75 mm, table feed 15 mm, reconstructed slice thickness 1 mm, reconstruction increment 0.7 mm, intermediate reconstruction kernel). Two observer groups of different radiologic experience (0 and more than 5 years of training, 3 observers each) analysed all lesions with digital callipers and 2 volumetry software packages (click-point depending and robust volumetry) in a semi-automatic and manually corrected mode. For data analysis the variation coefficient (VC) was calculated in per cent for each group and a Wilcoxon test was used for analytic statistics. Results: Click-point robust volumetry showed with a VC of <0.01% in both groups the smallest interobserver variability. Between experienced and un-experienced observers interobserver variability was significantly different for diameter measurements (p = 0.023) but not for semi-automatic and manual corrected volumetry. A significant training effect was revealed for diameter measurements (p = 0.003) and semi-automatic measurements of click-point depending volumetry (p = 0.007) in the un-experienced observer group. Conclusions: Compared to diameter measurements volumetry achieves a significantly smaller interobserver variance and advanced volumetry algorithms are independent of observer experience
Setting ozone critical levels for protecting horticultural Mediterranean crops: Case study of tomato
International Nuclear Information System (INIS)
González-Fernández, I.; Calvo, E.; Gerosa, G.; Bermejo, V.; Marzuoli, R.; Calatayud, V.; Alonso, R.
2014-01-01
Seven experiments carried out in Italy and Spain have been used to parameterising a stomatal conductance model and establishing exposure– and dose–response relationships for yield and quality of tomato with the main goal of setting O 3 critical levels (CLe). CLe with confidence intervals, between brackets, were set at an accumulated hourly O 3 exposure over 40 nl l −1 , AOT40 = 8.4 (1.2, 15.6) ppm h and a phytotoxic ozone dose above a threshold of 6 nmol m −2 s −1 , POD6 = 2.7 (0.8, 4.6) mmol m −2 for yield and AOT40 = 18.7 (8.5, 28.8) ppm h and POD6 = 4.1 (2.0, 6.2) mmol m −2 for quality, both indices performing equally well. CLe confidence intervals provide information on the quality of the dataset and should be included in future calculations of O 3 CLe for improving current methodologies. These CLe, derived for sensitive tomato cultivars, should not be applied for quantifying O 3 -induced losses at the risk of making important overestimations of the economical losses associated with O 3 pollution. -- Highlights: • Seven independent experiments from Italy and Spain were analysed. • O 3 critical levels are proposed for the protection of summer horticultural crops. • Exposure- and flux-based O 3 indices performed equally well. • Confidence intervals of the new O 3 critical levels are calculated. • A new method to estimate the degree risk of O 3 damage is proposed. -- Critical levels for tomato yield were set at AOT40 = 8.4 ppm h and POD6 = 2.7 mmol m −2 and confidence intervals should be used for improving O 3 risk assessment
Numerical Modelling of Three-Fluid Flow Using The Level-set Method
Li, Hongying; Lou, Jing; Shang, Zhi
2014-11-01
This work presents a numerical model for simulation of three-fluid flow involving two different moving interfaces. These interfaces are captured using the level-set method via two different level-set functions. A combined formulation with only one set of conservation equations for the whole physical domain, consisting of the three different immiscible fluids, is employed. Numerical solution is performed on a fixed mesh using the finite volume method. Surface tension effect is incorporated using the Continuum Surface Force model. Validation of the present model is made against available results for stratified flow and rising bubble in a container with a free surface. Applications of the present model are demonstrated by a variety of three-fluid flow systems including (1) three-fluid stratified flow, (2) two-fluid stratified flow carrying the third fluid in the form of drops and (3) simultaneous rising and settling of two drops in a stationary third fluid. The work is supported by a Thematic and Strategic Research from A*STAR, Singapore (Ref. #: 1021640075).
Cone, Pamela H; Giske, Tove
2017-10-01
To gain knowledge about nurses' comfort level in assessing spiritual matters and to learn what questions nurses use in practice related to spiritual assessment. Spirituality is important in holistic nursing care; however, nurses report feeling uncomfortable and ill-prepared to address this domain with patients. Education is reported to impact nurses' ability to engage in spiritual care. This cross-sectional exploratory survey reports on a mixed-method study examining how comfortable nurses are with spiritual assessment. In 2014, a 21-item survey with 10 demographic variables and three open-ended questions were distributed to Norwegian nurses working in diverse care settings with 172 nurse responses (72 % response rate). SPSS was used to analyse quantitative data; thematic analysis examined the open-ended questions. Norwegian nurses reported a high level of comfort with most questions even though spirituality is seen as private. Nurses with some preparation or experience in spiritual care were most comfortable assessing spirituality. Statistically significant correlations were found between the nurses' comfort level with spiritual assessment and their preparedness and sense of the importance of spiritual assessment. How well-prepared nurses felt was related to years of experience, degree of spirituality and religiosity, and importance of spiritual assessment. Many nurses are poorly prepared for spiritual assessment and care among patients in diverse care settings; educational preparation increases their comfort level with facilitating such care. Nurses who feel well prepared with spirituality feel more comfortable with the spiritual domain. By fostering a culture where patients' spirituality is discussed and reflected upon in everyday practice and in continued education, nurses' sense of preparedness, and thus their level of comfort, can increase. Clinical supervision and interprofessional collaboration with hospital chaplains and/or other spiritual leaders can
Song, Lei; Zhang, Bo
2017-07-01
Nowadays, the grid faces much more challenges caused by wind power and the accessing of electric vehicles (EVs). Based on the potentiality of coordinated dispatch, a model of wind-EVs coordinated dispatch was developed. Then, A bi-level particle swarm optimization algorithm for solving the model was proposed in this paper. The application of this algorithm to 10-unit test system carried out that coordinated dispatch can benefit the power system from the following aspects: (1) Reducing operating costs; (2) Improving the utilization of wind power; (3) Stabilizing the peak-valley difference.
DEFF Research Database (Denmark)
Otomori, Masaki; Yamada, Takayuki; Andkjær, Jacob Anders
2013-01-01
. A level set-based topology optimization method incorporating a fictitious interface energy is used to find optimized configurations of the ferrite material. The numerical results demonstrate that the optimization successfully found an appropriate ferrite configuration that functions as an electromagnetic......This paper presents a structural optimization method for the design of an electromagnetic cloak made of ferrite material. Ferrite materials exhibit a frequency-dependent degree of permeability, due to a magnetic resonance phenomenon that can be altered by changing the magnitude of an externally...
Joint level-set and spatio-temporal motion detection for cell segmentation.
Boukari, Fatima; Makrogiannis, Sokratis
2016-08-10
Cell segmentation is a critical step for quantification and monitoring of cell cycle progression, cell migration, and growth control to investigate cellular immune response, embryonic development, tumorigenesis, and drug effects on live cells in time-lapse microscopy images. In this study, we propose a joint spatio-temporal diffusion and region-based level-set optimization approach for moving cell segmentation. Moving regions are initially detected in each set of three consecutive sequence images by numerically solving a system of coupled spatio-temporal partial differential equations. In order to standardize intensities of each frame, we apply a histogram transformation approach to match the pixel intensities of each processed frame with an intensity distribution model learned from all frames of the sequence during the training stage. After the spatio-temporal diffusion stage is completed, we compute the edge map by nonparametric density estimation using Parzen kernels. This process is followed by watershed-based segmentation and moving cell detection. We use this result as an initial level-set function to evolve the cell boundaries, refine the delineation, and optimize the final segmentation result. We applied this method to several datasets of fluorescence microscopy images with varying levels of difficulty with respect to cell density, resolution, contrast, and signal-to-noise ratio. We compared the results with those produced by Chan and Vese segmentation, a temporally linked level-set technique, and nonlinear diffusion-based segmentation. We validated all segmentation techniques against reference masks provided by the international Cell Tracking Challenge consortium. The proposed approach delineated cells with an average Dice similarity coefficient of 89 % over a variety of simulated and real fluorescent image sequences. It yielded average improvements of 11 % in segmentation accuracy compared to both strictly spatial and temporally linked Chan
A multilevel, level-set method for optimizing eigenvalues in shape design problems
International Nuclear Information System (INIS)
Haber, E.
2004-01-01
In this paper, we consider optimal design problems that involve shape optimization. The goal is to determine the shape of a certain structure such that it is either as rigid or as soft as possible. To achieve this goal we combine two new ideas for an efficient solution of the problem. First, we replace the eigenvalue problem with an approximation by using inverse iteration. Second, we use a level set method but rather than propagating the front we use constrained optimization methods combined with multilevel continuation techniques. Combining these two ideas we obtain a robust and rapid method for the solution of the optimal design problem
Modeling Restrained Shrinkage Induced Cracking in Concrete Rings Using the Thick Level Set Approach
Directory of Open Access Journals (Sweden)
Rebecca Nakhoul
2018-03-01
Full Text Available Modeling restrained shrinkage-induced damage and cracking in concrete is addressed herein. The novel Thick Level Set (TLS damage growth and crack propagation model is used and adapted by introducing shrinkage contribution into the formulation. The TLS capacity to predict damage evolution, crack initiation and growth triggered by restrained shrinkage in absence of external loads is evaluated. A study dealing with shrinkage-induced cracking in elliptical concrete rings is presented herein. Key results such as the effect of rings oblateness on stress distribution and critical shrinkage strain needed to initiate damage are highlighted. In addition, crack positions are compared to those observed in experiments and are found satisfactory.
Novel multimodality segmentation using level sets and Jensen-Renyi divergence
Markel, Daniel; Zaidi, Habib; El Naqa, Issam
2013-01-01
Purpose: Positron emission tomography (PET) is playing an increasing role in radiotherapy treatment planning. However, despite progress, robust algorithms for PET and multimodal image segmentation are still lacking, especially if the algorithm were extended to image-guided and adaptive radiotherapy
International Nuclear Information System (INIS)
Loef, Johan; Lind, Bengt K.; Brahme, Anders
1998-01-01
A new general beam optimization algorithm for inverse treatment planning is presented. It utilizes a new formulation of the probability to achieve complication-free tumour control. The new formulation explicitly describes the dependence of the treatment outcome on the incident fluence distribution, the patient geometry, the radiobiological properties of the patient and the fractionation schedule. In order to account for both measured and non-measured positioning uncertainties, the algorithm is based on a combination of dynamic and stochastic optimization techniques. Because of the difficulty in measuring all aspects of the intra- and interfractional variations in the patient geometry, such as internal organ displacements and deformations, these uncertainties are primarily accounted for in the treatment planning process by intensity modulation using stochastic optimization. The information about the deviations from the nominal fluence profiles and the nominal position of the patient relative to the beam that is obtained by portal imaging during treatment delivery, is used in a feedback loop to automatically adjust the profiles and the location of the patient for all subsequent treatments. Based on the treatment delivered in previous fractions, the algorithm furnishes optimal corrections for the remaining dose delivery both with regard to the fluence profile and its position relative to the patient. By dynamically refining the beam configuration from fraction to fraction, the algorithm generates an optimal sequence of treatments that very effectively reduces the influence of systematic and random set-up uncertainties to minimize and almost eliminate their overall effect on the treatment. Computer simulations have shown that the present algorithm leads to a significant increase in the probability of uncomplicated tumour control compared with the simple classical approach of adding fixed set-up margins to the internal target volume. (author)
Le, T Hoang Ngan; Luu, Khoa; Savvides, Marios
2013-08-01
Robust facial hair detection and segmentation is a highly valued soft biometric attribute for carrying out forensic facial analysis. In this paper, we propose a novel and fully automatic system, called SparCLeS, for beard/moustache detection and segmentation in challenging facial images. SparCLeS uses the multiscale self-quotient (MSQ) algorithm to preprocess facial images and deal with illumination variation. Histogram of oriented gradients (HOG) features are extracted from the preprocessed images and a dynamic sparse classifier is built using these features to classify a facial region as either containing skin or facial hair. A level set based approach, which makes use of the advantages of both global and local information, is then used to segment the regions of a face containing facial hair. Experimental results demonstrate the effectiveness of our proposed system in detecting and segmenting facial hair regions in images drawn from three databases, i.e., the NIST Multiple Biometric Grand Challenge (MBGC) still face database, the NIST Color Facial Recognition Technology FERET database, and the Labeled Faces in the Wild (LFW) database.
Novosel, Jelena; Wang, Ziyuan; de Jong, Henk; Vermeer, Koenraad A.; van Vliet, Lucas J.
2016-03-01
Optical coherence tomography (OCT) is used to produce high-resolution three-dimensional images of the retina, which permit the investigation of retinal irregularities. In dry age-related macular degeneration (AMD), a chronic eye disease that causes central vision loss, disruptions such as drusen and changes in retinal layer thicknesses occur which could be used as biomarkers for disease monitoring and diagnosis. Due to the topology disrupting pathology, existing segmentation methods often fail. Here, we present a solution for the segmentation of retinal layers in dry AMD subjects by extending our previously presented loosely coupled level sets framework which operates on attenuation coefficients. In eyes affected by AMD, Bruch's membrane becomes visible only below the drusen and our segmentation framework is adapted to delineate such a partially discernible interface. Furthermore, the initialization stage, which tentatively segments five interfaces, is modified to accommodate the appearance of drusen. This stage is based on Dijkstra's algorithm and combines prior knowledge on the shape of the interface, gradient and attenuation coefficient in the newly proposed cost function. This prior knowledge is incorporated by varying the weights for horizontal, diagonal and vertical edges. Finally, quantitative evaluation of the accuracy shows a good agreement between manual and automated segmentation.
Tang, Jian; Jiang, Xiaoliang
2017-01-01
Image segmentation has always been a considerable challenge in image analysis and understanding due to the intensity inhomogeneity, which is also commonly known as bias field. In this paper, we present a novel region-based approach based on local entropy for segmenting images and estimating the bias field simultaneously. Firstly, a local Gaussian distribution fitting (LGDF) energy function is defined as a weighted energy integral, where the weight is local entropy derived from a grey level distribution of local image. The means of this objective function have a multiplicative factor that estimates the bias field in the transformed domain. Then, the bias field prior is fully used. Therefore, our model can estimate the bias field more accurately. Finally, minimization of this energy function with a level set regularization term, image segmentation, and bias field estimation can be achieved. Experiments on images of various modalities demonstrated the superior performance of the proposed method when compared with other state-of-the-art approaches.
Implications of sea-level rise in a modern carbonate ramp setting
Lokier, Stephen W.; Court, Wesley M.; Onuma, Takumi; Paul, Andreas
2018-03-01
This study addresses a gap in our understanding of the effects of sea-level rise on the sedimentary systems and morphological development of recent and ancient carbonate ramp settings. Many ancient carbonate sequences are interpreted as having been deposited in carbonate ramp settings. These settings are poorly-represented in the Recent. The study documents the present-day transgressive flooding of the Abu Dhabi coastline at the southern shoreline of the Arabian/Persian Gulf, a carbonate ramp depositional system that is widely employed as a Recent analogue for numerous ancient carbonate systems. Fourteen years of field-based observations are integrated with historical and recent high-resolution satellite imagery in order to document and assess the onset of flooding. Predicted rates of transgression (i.e. landward movement of the shoreline) of 2.5 m yr- 1 (± 0.2 m yr- 1) based on global sea-level rise alone were far exceeded by the flooding rate calculated from the back-stepping of coastal features (10-29 m yr- 1). This discrepancy results from the dynamic nature of the flooding with increased water depth exposing the coastline to increased erosion and, thereby, enhancing back-stepping. A non-accretionary transgressive shoreline trajectory results from relatively rapid sea-level rise coupled with a low-angle ramp geometry and a paucity of sediments. The flooding is represented by the landward migration of facies belts, a range of erosive features and the onset of bioturbation. Employing Intergovernmental Panel on Climate Change (Church et al., 2013) predictions for 21st century sea-level rise, and allowing for the post-flooding lag time that is typical for the start-up of carbonate factories, it is calculated that the coastline will continue to retrograde for the foreseeable future. Total passive flooding (without considering feedback in the modification of the shoreline) by the year 2100 is calculated to likely be between 340 and 571 m with a flooding rate of 3
Robust space-time extraction of ventricular surface evolution using multiphase level sets
Drapaca, Corina S.; Cardenas, Valerie; Studholme, Colin
2004-05-01
This paper focuses on the problem of accurately extracting the CSF-tissue boundary, particularly around the ventricular surface, from serial structural MRI of the brain acquired in imaging studies of aging and dementia. This is a challenging problem because of the common occurrence of peri-ventricular lesions which locally alter the appearance of white matter. We examine a level set approach which evolves a four dimensional description of the ventricular surface over time. This has the advantage of allowing constraints on the contour in the temporal dimension, improving the consistency of the extracted object over time. We follow the approach proposed by Chan and Vese which is based on the Mumford and Shah model and implemented using the Osher and Sethian level set method. We have extended this to the 4 dimensional case to propagate a 4D contour toward the tissue boundaries through the evolution of a 5D implicit function. For convergence we use region-based information provided by the image rather than the gradient of the image. This is adapted to allow intensity contrast changes between time frames in the MRI sequence. Results on time sequences of 3D brain MR images are presented and discussed.
An improved level set method for brain MR images segmentation and bias correction.
Chen, Yunjie; Zhang, Jianwei; Macione, Jim
2009-10-01
Intensity inhomogeneities cause considerable difficulty in the quantitative analysis of magnetic resonance (MR) images. Thus, bias field estimation is a necessary step before quantitative analysis of MR data can be undertaken. This paper presents a variational level set approach to bias correction and segmentation for images with intensity inhomogeneities. Our method is based on an observation that intensities in a relatively small local region are separable, despite of the inseparability of the intensities in the whole image caused by the overall intensity inhomogeneity. We first define a localized K-means-type clustering objective function for image intensities in a neighborhood around each point. The cluster centers in this objective function have a multiplicative factor that estimates the bias within the neighborhood. The objective function is then integrated over the entire domain to define the data term into the level set framework. Our method is able to capture bias of quite general profiles. Moreover, it is robust to initialization, and thereby allows fully automated applications. The proposed method has been used for images of various modalities with promising results.
Topology optimization in acoustics and elasto-acoustics via a level-set method
Desai, J.; Faure, A.; Michailidis, G.; Parry, G.; Estevez, R.
2018-04-01
Optimizing the shape and topology (S&T) of structures to improve their acoustic performance is quite challenging. The exact position of the structural boundary is usually of critical importance, which dictates the use of geometric methods for topology optimization instead of standard density approaches. The goal of the present work is to investigate different possibilities for handling topology optimization problems in acoustics and elasto-acoustics via a level-set method. From a theoretical point of view, we detail two equivalent ways to perform the derivation of surface-dependent terms and propose a smoothing technique for treating problems of boundary conditions optimization. In the numerical part, we examine the importance of the surface-dependent term in the shape derivative, neglected in previous studies found in the literature, on the optimal designs. Moreover, we test different mesh adaptation choices, as well as technical details related to the implicit surface definition in the level-set approach. We present results in two and three-space dimensions.
A mass conserving level set method for detailed numerical simulation of liquid atomization
Energy Technology Data Exchange (ETDEWEB)
Luo, Kun; Shao, Changxiao [State Key Laboratory of Clean Energy Utilization, Zhejiang University, Hangzhou 310027 (China); Yang, Yue [State Key Laboratory of Turbulence and Complex Systems, Peking University, Beijing 100871 (China); Fan, Jianren, E-mail: fanjr@zju.edu.cn [State Key Laboratory of Clean Energy Utilization, Zhejiang University, Hangzhou 310027 (China)
2015-10-01
An improved mass conserving level set method for detailed numerical simulations of liquid atomization is developed to address the issue of mass loss in the existing level set method. This method introduces a mass remedy procedure based on the local curvature at the interface, and in principle, can ensure the absolute mass conservation of the liquid phase in the computational domain. Three benchmark cases, including Zalesak's disk, a drop deforming in a vortex field, and the binary drop head-on collision, are simulated to validate the present method, and the excellent agreement with exact solutions or experimental results is achieved. It is shown that the present method is able to capture the complex interface with second-order accuracy and negligible additional computational cost. The present method is then applied to study more complex flows, such as a drop impacting on a liquid film and the swirling liquid sheet atomization, which again, demonstrates the advantages of mass conservation and the capability to represent the interface accurately.
On the Relationship between Variational Level Set-Based and SOM-Based Active Contours
Abdelsamea, Mohammed M.; Gnecco, Giorgio; Gaber, Mohamed Medhat; Elyan, Eyad
2015-01-01
Most Active Contour Models (ACMs) deal with the image segmentation problem as a functional optimization problem, as they work on dividing an image into several regions by optimizing a suitable functional. Among ACMs, variational level set methods have been used to build an active contour with the aim of modeling arbitrarily complex shapes. Moreover, they can handle also topological changes of the contours. Self-Organizing Maps (SOMs) have attracted the attention of many computer vision scientists, particularly in modeling an active contour based on the idea of utilizing the prototypes (weights) of a SOM to control the evolution of the contour. SOM-based models have been proposed in general with the aim of exploiting the specific ability of SOMs to learn the edge-map information via their topology preservation property and overcoming some drawbacks of other ACMs, such as trapping into local minima of the image energy functional to be minimized in such models. In this survey, we illustrate the main concepts of variational level set-based ACMs, SOM-based ACMs, and their relationship and review in a comprehensive fashion the development of their state-of-the-art models from a machine learning perspective, with a focus on their strengths and weaknesses. PMID:25960736
High-Level Topology-Oblivious Optimization of MPI Broadcast Algorithms on Extreme-Scale Platforms
Hasanov, Khalid; Quintin, Jean-Noë l; Lastovetsky, Alexey
2014-01-01
by taking into account either their topology or platform parameters. In this work we propose a very simple and at the same time general approach to optimize legacy MPI broadcast algorithms, which are widely used in MPICH and OpenMPI. Theoretical analysis
2015-04-01
HPD model. In an article on measuring HPD attenuation, Berger (1986) points out that Real Ear Attenuation at Threshold (REAT) tests are...men. Audiology . 1991;30:345–356. Fedele P, Binseel M, Kalb J, Price GR. Using the auditory hazard assessment algorithm for humans (AHAAH) with
Munshi, Saif U; Oyewale, Tajudeen O; Begum, Shahnaz; Uddin, Ziya; Tabassum, Shahina
2016-03-01
Serum-based rapid HIV testing algorithm in Bangladesh constitutes operational challenge to scaleup HIV testing and counselling (HTC) in the country. This study explored the operational feasibility of using whole blood as alternative to serum for rapid HIV testing in Bangladesh. Whole blood specimens were collected from two study groups. The groups included HIV-positive patients (n = 200) and HIV-negative individuals (n = 200) presenting at the reference laboratory in Dhaka, Bangladesh. The specimens were subjected to rapid HIV tests using the national algorithm with A1 = Alere Determine (United States), A2 = Uni-Gold (Ireland), and A3 = First Response (India). The sensitivity and specificity of the test results, and the operational cost were compared with current serum-based testing. The sensitivities [95% of confidence interval (CI)] for A1, A2, and A3 tests using whole blood were 100% (CI: 99.1-100%), 100% (CI: 99.1-100%), and 97% (CI: 96.4-98.2%), respectively, and specificities of all test kits were 100% (CI: 99.1-100%). Significant (P < 0.05) reduction in the cost of establishing HTC centre and consumables by 94 and 61%, respectively, were observed. The cost of administration and external quality assurance reduced by 39 and 43%, respectively. Overall, there was a 36% cost reduction in total operational cost of rapid HIV testing with blood when compared with serum. Considering the similar sensitivity and specificity of the two specimens, and significant cost reduction, rapid HIV testing with whole blood is feasible. A review of the national HIV rapid testing algorithm with whole blood will contribute toward improving HTC coverage in Bangladesh.
Directory of Open Access Journals (Sweden)
Akanksha Mishra
2017-05-01
Full Text Available In a deregulated electricity market it may at times become difficult to dispatch all the required power that is scheduled to flow due to congestion in transmission lines. An Interline Power Flow Controller (IPFC can be used to reduce the system loss and power flow in the heavily loaded line, improve stability and loadability of the system. This paper proposes a Disparity Line Utilization Factor for the optimal placement and Gravitational Search algorithm based optimal tuning of IPFC to control the congestion in transmission lines. DLUF ranks the transmission lines in terms of relative line congestion. The IPFC is accordingly placed in the most congested and the least congested line connected to the same bus. Optimal sizing of IPFC is carried using Gravitational Search algorithm. A multi-objective function has been chosen for tuning the parameters of the IPFC. The proposed method is implemented on an IEEE-30 bus test system. Graphical representations have been included in the paper showing reduction in LUF of the transmission lines after the placement of an IPFC. A reduction in active power and reactive power loss of the system by about 6% is observed after an optimally tuned IPFC has been included in the power system. The effectiveness of the proposed tuning method has also been shown in the paper through the reduction in the values of the objective functions.
Reservoir characterisation by a binary level set method and adaptive multiscale estimation
Energy Technology Data Exchange (ETDEWEB)
Nielsen, Lars Kristian
2006-01-15
The main focus of this work is on estimation of the absolute permeability as a solution of an inverse problem. We have both considered a single-phase and a two-phase flow model. Two novel approaches have been introduced and tested numerical for solving the inverse problems. The first approach is a multi scale zonation technique which is treated in Paper A. The purpose of the work in this paper is to find a coarse scale solution based on production data from wells. In the suggested approach, the robustness of an already developed method, the adaptive multi scale estimation (AME), has been improved by utilising information from several candidate solutions generated by a stochastic optimizer. The new approach also suggests a way of combining a stochastic and a gradient search method, which in general is a problematic issue. The second approach is a piecewise constant level set approach and is applied in Paper B, C, D and E. Paper B considers the stationary single-phase problem, while Paper C, D and E use a two-phase flow model. In the two-phase flow problem we have utilised information from both production data in wells and spatially distributed data gathered from seismic surveys. Due to the higher content of information provided by the spatially distributed data, we search solutions on a slightly finer scale than one typically does with only production data included. The applied level set method is suitable for reconstruction of fields with a supposed known facies-type of solution. That is, the solution should be close to piecewise constant. This information is utilised through a strong restriction of the number of constant levels in the estimate. On the other hand, the flexibility in the geometries of the zones is much larger for this method than in a typical zonation approach, for example the multi scale approach applied in Paper A. In all these papers, the numerical studies are done on synthetic data sets. An advantage of synthetic data studies is that the true
CT Findings of Disease with Elevated Serum D-Dimer Levels in an Emergency Room Setting
Energy Technology Data Exchange (ETDEWEB)
Choi, Ji Youn; Kwon, Woo Cheol; Kim, Young Ju [Dept. of Radiology, Wonju Christian Hospital, Yensei University Wonju College of Medicine, Wonju (Korea, Republic of)
2012-01-15
Pulmonary embolism and deep vein thrombosis are the leading causes of elevated serum D-dimer levels in the emergency room. Although D-dimer is a useful screening test because of its high sensitivity and negative predictive value, it has a low specificity. In addition, D-dimer can be elevated in various diseases. Therefore, information on the various diseases with elevated D-dimer levels and their radiologic findings may allow for accurate diagnosis and proper management. Herein, we report the CT findings of various diseases with elevated D-dimer levels in an emergency room setting, including an intravascular contrast filling defect with associated findings in a venous thromboembolism, fracture with soft tissue swelling and hematoma formation in a trauma patient, enlargement with contrast enhancement in the infected organ of a patient, coronary artery stenosis with a perfusion defect of the myocardium in a patient with acute myocardial infarction, high density of acute thrombus in a cerebral vessel with a low density of affected brain parenchyma in an acute cerebral infarction, intimal flap with two separated lumens in a case of aortic dissection, organ involvement of malignancy in a cancer patient, and atrophy of a liver with a dilated portal vein and associated findings.
Kitamura, Tetsuhiro; Otsuki, Michio; Tamada, Daisuke; Tabuchi, Yukiko; Mukai, Kosuke; Morita, Shinya; Kasayama, Soji; Shimomura, Iichiro; Koga, Masafumi
2013-09-23
Glycated albumin (GA) is an indicator of glycemic control, which has some specific characters in comparison with HbA1c. Since glucocorticoids (GC) promote protein catabolism including serum albumin, GC excess state would influence GA levels. We therefore investigated GA levels in patients with Cushing's syndrome. We studied 16 patients with Cushing's syndrome (8 patients had diabetes mellitus and the remaining 8 patients were non-diabetic). Thirty-two patients with type 2 diabetes mellitus and 32 non-diabetic subjects matched for age, sex and BMI were used as controls. In the patients with Cushing's syndrome, GA was significantly correlated with HbA1c, but the regression line shifted downwards as compared with the controls. The GA/HbA1c ratio in the patients with Cushing's syndrome was also significantly lower than the controls. HbA1c in the non-diabetic patients with Cushing's syndrome was not different from the non-diabetic controls, whereas GA was significantly lower. In 7 patients with Cushing's syndrome who performed self-monitoring of blood glucose, the measured HbA1c was matched with HbA1c estimated from mean blood glucose, whereas the measured GA was significantly lower than the estimated GA. We clarified that GA is set lower in relation to plasma glucose levels in patients with Cushing's syndrome. Copyright © 2013 Elsevier B.V. All rights reserved.
CT Findings of Disease with Elevated Serum D-Dimer Levels in an Emergency Room Setting
International Nuclear Information System (INIS)
Choi, Ji Youn; Kwon, Woo Cheol; Kim, Young Ju
2012-01-01
Pulmonary embolism and deep vein thrombosis are the leading causes of elevated serum D-dimer levels in the emergency room. Although D-dimer is a useful screening test because of its high sensitivity and negative predictive value, it has a low specificity. In addition, D-dimer can be elevated in various diseases. Therefore, information on the various diseases with elevated D-dimer levels and their radiologic findings may allow for accurate diagnosis and proper management. Herein, we report the CT findings of various diseases with elevated D-dimer levels in an emergency room setting, including an intravascular contrast filling defect with associated findings in a venous thromboembolism, fracture with soft tissue swelling and hematoma formation in a trauma patient, enlargement with contrast enhancement in the infected organ of a patient, coronary artery stenosis with a perfusion defect of the myocardium in a patient with acute myocardial infarction, high density of acute thrombus in a cerebral vessel with a low density of affected brain parenchyma in an acute cerebral infarction, intimal flap with two separated lumens in a case of aortic dissection, organ involvement of malignancy in a cancer patient, and atrophy of a liver with a dilated portal vein and associated findings.
Tri-Level Optimization Algorithms for Solving Defender-Attacker-Defender Network Models
2016-06-01
not improved over three iterations of relaxation. In the heuristic , the current upper bound represents the best found feasible solution that does not...nested loops in the 167 algorithm which represent the outer and inner decompositions of the DAD CSP problem instance. Since our heuristic ...path problem. We merge the attacker model with Lagrangian relaxation of the operator model into a single formulation that can obtain fast heuristic
Directory of Open Access Journals (Sweden)
Ahmet Mete Vural
2016-09-01
Full Text Available This paper presents the design details of a two-level space vector pulse width modulation algorithm in PSCAD that is able to generate pulses for three-phase two-level DC/AC converters with two different switching patterns. The presented FORTRAN code is generic and can be easily modified to meet many other kinds of space vector modulation strategies. The code is also editable for hardware programming. The new component is tested and verified by comparing its output as six gating signals with those of a similar component in MATLAB library. Moreover the component is used to generate digital signals for closed-loop control of STATCOM for reactive power compensation in PSCAD. This add-on can be an effective tool to give students better understanding of the space vector modulation algorithm for different control tasks in power electronics area, and can motivate them for learning.
Numerical simulation of overflow at vertical weirs using a hybrid level set/VOF method
Lv, Xin; Zou, Qingping; Reeve, Dominic
2011-10-01
This paper presents the applications of a newly developed free surface flow model to the practical, while challenging overflow problems for weirs. Since the model takes advantage of the strengths of both the level set and volume of fluid methods and solves the Navier-Stokes equations on an unstructured mesh, it is capable of resolving the time evolution of very complex vortical motions, air entrainment and pressure variations due to violent deformations following overflow of the weir crest. In the present study, two different types of vertical weir, namely broad-crested and sharp-crested, are considered for validation purposes. The calculated overflow parameters such as pressure head distributions, velocity distributions, and water surface profiles are compared against experimental data as well as numerical results available in literature. A very good quantitative agreement has been obtained. The numerical model, thus, offers a good alternative to traditional experimental methods in the study of weir problems.
Level set method for optimal shape design of MRAM core. Micromagnetic approach
International Nuclear Information System (INIS)
Melicher, Valdemar; Cimrak, Ivan; Keer, Roger van
2008-01-01
We aim at optimizing the shape of the magnetic core in MRAM memories. The evolution of the magnetization during the writing process is described by the Landau-Lifshitz equation (LLE). The actual shape of the core in one cell is characterized by the coefficient γ. Cost functional f=f(γ) expresses the quality of the writing process having in mind the competition between the full-select and the half-select element. We derive an explicit form of the derivative F=∂f/∂γ which allows for the use of gradient-type methods for the actual computation of the optimized shape (e.g., steepest descend method). The level set method (LSM) is employed for the representation of the piecewise constant coefficient γ
Geurts, Bernard J.; Vreman, Bert; Kuerten, Hans; Luo, Kai H.
2001-01-01
The mixing efficiency in a turbulent mixing layer is quantified by monitoring the surface-area of level-sets of scalar fields. The Laplace transform is applied to numerically calculate integrals over arbitrary level-sets. The analysis includes both direct and large-eddy simulation and is used to
International Nuclear Information System (INIS)
Shi Jiazheng; Sahiner, Berkman; Chan Heangping; Ge Jun; Hadjiiski, Lubomir; Helvie, Mark A.; Nees, Alexis; Wu Yita; Wei Jun; Zhou Chuan; Zhang Yiheng; Cui Jing
2008-01-01
Computer-aided diagnosis (CAD) for characterization of mammographic masses as malignant or benign has the potential to assist radiologists in reducing the biopsy rate without increasing false negatives. The purpose of this study was to develop an automated method for mammographic mass segmentation and explore new image based features in combination with patient information in order to improve the performance of mass characterization. The authors' previous CAD system, which used the active contour segmentation, and morphological, textural, and spiculation features, has achieved promising results in mass characterization. The new CAD system is based on the level set method and includes two new types of image features related to the presence of microcalcifications with the mass and abruptness of the mass margin, and patient age. A linear discriminant analysis (LDA) classifier with stepwise feature selection was used to merge the extracted features into a classification score. The classification accuracy was evaluated using the area under the receiver operating characteristic curve. The authors' primary data set consisted of 427 biopsy-proven masses (200 malignant and 227 benign) in 909 regions of interest (ROIs) (451 malignant and 458 benign) from multiple mammographic views. Leave-one-case-out resampling was used for training and testing. The new CAD system based on the level set segmentation and the new mammographic feature space achieved a view-based A z value of 0.83±0.01. The improvement compared to the previous CAD system was statistically significant (p=0.02). When patient age was included in the new CAD system, view-based and case-based A z values were 0.85±0.01 and 0.87±0.02, respectively. The study also demonstrated the consistency of the newly developed CAD system by evaluating the statistics of the weights of the LDA classifiers in leave-one-case-out classification. Finally, an independent test on the publicly available digital database for screening
Directory of Open Access Journals (Sweden)
Jean-François Mahfouf
2012-06-01
Full Text Available The performance of a new data assimilation algorithm called back and forth nudging (BFN is evaluated using a high-resolution numerical mesoscale model and simulated wind observations in the boundary layer. This new algorithm, of interest for the assimilation of high-frequency observations provided by ground-based active remote-sensing instruments, is straightforward to implement in a realistic atmospheric model. The convergence towards a steady-state profile can be achieved after five iterations of the BFN algorithm, and the algorithm provides an improved solution with respect to direct nudging. It is shown that the contribution of the nudging term does not dominate over other model physical and dynamical tendencies. Moreover, by running backward integrations with an adiabatic version of the model, the nudging coefficients do not need to be increased in order to stabilise the numerical equations. The ability of BFN to produce model changes upstream from the observations, in a similar way to 4-D-Var assimilation systems, is demonstrated. The capacity of the model to adjust to rapid changes in wind direction with the BFN is a first encouraging step, for example, to improve the detection and prediction of low-level wind shear phenomena through high-resolution mesoscale modelling over airports.
Cooperative Fuzzy Games Approach to Setting Target Levels of ECs in Quality Function Deployment
Directory of Open Access Journals (Sweden)
Zhihui Yang
2014-01-01
Full Text Available Quality function deployment (QFD can provide a means of translating customer requirements (CRs into engineering characteristics (ECs for each stage of product development and production. The main objective of QFD-based product planning is to determine the target levels of ECs for a new product or service. QFD is a breakthrough tool which can effectively reduce the gap between CRs and a new product/service. Even though there are conflicts among some ECs, the objective of developing new product is to maximize the overall customer satisfaction. Therefore, there may be room for cooperation among ECs. A cooperative game framework combined with fuzzy set theory is developed to determine the target levels of the ECs in QFD. The key to develop the model is the formulation of the bargaining function. In the proposed methodology, the players are viewed as the membership functions of ECs to formulate the bargaining function. The solution for the proposed model is Pareto-optimal. An illustrated example is cited to demonstrate the application and performance of the proposed approach.
Natural setting of Japanese islands and geologic disposal of high-level waste
International Nuclear Information System (INIS)
Koide, Hitoshi
1991-01-01
The Japanese islands are a combination of arcuate islands along boundaries between four major plates: Eurasia, North America, Pacific and Philippine Sea plates. The interaction among the four plates formed complex geological structures which are basically patchworks of small blocks of land and sea-floor sediments piled up by the subduction of oceanic plates along the margin of the Eurasia continent. Although frequent earthquakes and volcanic eruptions clearly indicate active crustal deformation, the distribution of active faults and volcanoes is localized regionally in the Japanese islands. Crustal displacement faster than 1 mm/year takes place only in restricted regions near plate boundaries or close to major active faults. Volcanic activity is absent in the region between the volcanic front and the subduction zone. The site selection is especially important in Japan. The scenarios for the long-term performance assessment of high-level waste disposal are discussed with special reference to the geological setting of Japan. The long-term prediction of tectonic disturbance, evaluation of faults and fractures in rocks and estimation of long-term water-rock interaction are key issues in the performance assessment of the high-level waste disposal in the Japanese islands. (author)
Cooperative fuzzy games approach to setting target levels of ECs in quality function deployment.
Yang, Zhihui; Chen, Yizeng; Yin, Yunqiang
2014-01-01
Quality function deployment (QFD) can provide a means of translating customer requirements (CRs) into engineering characteristics (ECs) for each stage of product development and production. The main objective of QFD-based product planning is to determine the target levels of ECs for a new product or service. QFD is a breakthrough tool which can effectively reduce the gap between CRs and a new product/service. Even though there are conflicts among some ECs, the objective of developing new product is to maximize the overall customer satisfaction. Therefore, there may be room for cooperation among ECs. A cooperative game framework combined with fuzzy set theory is developed to determine the target levels of the ECs in QFD. The key to develop the model is the formulation of the bargaining function. In the proposed methodology, the players are viewed as the membership functions of ECs to formulate the bargaining function. The solution for the proposed model is Pareto-optimal. An illustrated example is cited to demonstrate the application and performance of the proposed approach.
An Efficient Data Fingerprint Query Algorithm Based on Two-Leveled Bloom Filter
Bin Zhou; Rongbo Zhu; Ying Zhang; Linhui Cheng
2013-01-01
The function of the comparing fingerprints algorithm was to judge whether a new partitioned data chunk was in a storage system a decade ago. At present, in the most de-duplication backup system the fingerprints of the big data chunks are huge and cannot be stored in the memory completely. The performance of the system is unavoidably retarded by data chunks accessing the storage system at the querying stage. Accordingly, a new query mechanism namely Two-stage Bloom Filter (TBF) mechanism...
High-Level Topology-Oblivious Optimization of MPI Broadcast Algorithms on Extreme-Scale Platforms
Hasanov, Khalid
2014-01-01
There has been a significant research in collective communication operations, in particular in MPI broadcast, on distributed memory platforms. Most of the research works are done to optimize the collective operations for particular architectures by taking into account either their topology or platform parameters. In this work we propose a very simple and at the same time general approach to optimize legacy MPI broadcast algorithms, which are widely used in MPICH and OpenMPI. Theoretical analysis and experimental results on IBM BlueGene/P and a cluster of Grid’5000 platform are presented.
Paschall, Mallie J; Saltz, Robert F
2007-11-01
We examined how alcohol risk is distributed based on college students' drinking before, during and after they go to certain settings. Students attending 14 California public universities (N=10,152) completed a web-based or mailed survey in the fall 2003 semester, which included questions about how many drinks they consumed before, during and after the last time they went to six settings/events: fraternity or sorority party, residence hall party, campus event (e.g. football game), off-campus party, bar/restaurant and outdoor setting (referent). Multi-level analyses were conducted in hierarchical linear modeling (HLM) to examine relationships between type of setting and level of alcohol use before, during and after going to the setting, and possible age and gender differences in these relationships. Drinking episodes (N=24,207) were level 1 units, students were level 2 units and colleges were level 3 units. The highest drinking levels were observed during all settings/events except campus events, with the highest number of drinks being consumed at off-campus parties, followed by residence hall and fraternity/sorority parties. The number of drinks consumed before a fraternity/sorority party was higher than other settings/events. Age group and gender differences in relationships between type of setting/event and 'before,''during' and 'after' drinking levels also were observed. For example, going to a bar/restaurant (relative to an outdoor setting) was positively associated with 'during' drinks among students of legal drinking age while no relationship was observed for underage students. Findings of this study indicate differences in the extent to which college settings are associated with student drinking levels before, during and after related events, and may have implications for intervention strategies targeting different types of settings.
Generalized cost-effectiveness analysis for national-level priority-setting in the health sector
Directory of Open Access Journals (Sweden)
Edejer Tessa
2003-12-01
Full Text Available Abstract Cost-effectiveness analysis (CEA is potentially an important aid to public health decision-making but, with some notable exceptions, its use and impact at the level of individual countries is limited. A number of potential reasons may account for this, among them technical shortcomings associated with the generation of current economic evidence, political expediency, social preferences and systemic barriers to implementation. As a form of sectoral CEA, Generalized CEA sets out to overcome a number of these barriers to the appropriate use of cost-effectiveness information at the regional and country level. Its application via WHO-CHOICE provides a new economic evidence base, as well as underlying methodological developments, concerning the cost-effectiveness of a range of health interventions for leading causes of, and risk factors for, disease. The estimated sub-regional costs and effects of different interventions provided by WHO-CHOICE can readily be tailored to the specific context of individual countries, for example by adjustment to the quantity and unit prices of intervention inputs (costs or the coverage, efficacy and adherence rates of interventions (effectiveness. The potential usefulness of this information for health policy and planning is in assessing if current intervention strategies represent an efficient use of scarce resources, and which of the potential additional interventions that are not yet implemented, or not implemented fully, should be given priority on the grounds of cost-effectiveness. Health policy-makers and programme managers can use results from WHO-CHOICE as a valuable input into the planning and prioritization of services at national level, as well as a starting point for additional analyses of the trade-off between the efficiency of interventions in producing health and their impact on other key outcomes such as reducing inequalities and improving the health of the poor.
Optimization of algorithms of Level 1 Trigger in Overlap region in CMS detector
Pijanowski, Karol Andrzej
2017-01-01
CMS has recently upgraded the L1 muon trigger. The Overlap Muon Track Finder (OMTF) is using data from three types of muon detectors in barrel-endcap transition region to ﬁnd muon tracks and estimate their transverse momentum. The goal is to decrease rate of events produced by OMTF and maintain high eﬃciency in detection of muons with high transverse momentum. In order to achieve this the change in OMTF algorithm has been proposed. Until now algorithm was based on a similar principle as the "naive Bayesian classiﬁer" and it was not taking into account the correlation between the detector hits, but only probability of matching them to a given transverse momentum hypothesis. The addition of the correlation has decreased the rate of events around the threshold, but it has also aﬀected eﬃciency above the threshold. In addition it has not aﬀected the rate produced by low transverse momentum muons, which gives the highest contribution to overall rate.
Hu, Peijun; Wu, Fa; Peng, Jialin; Bao, Yuanyuan; Chen, Feng; Kong, Dexing
2017-03-01
Multi-organ segmentation from CT images is an essential step for computer-aided diagnosis and surgery planning. However, manual delineation of the organs by radiologists is tedious, time-consuming and poorly reproducible. Therefore, we propose a fully automatic method for the segmentation of multiple organs from three-dimensional abdominal CT images. The proposed method employs deep fully convolutional neural networks (CNNs) for organ detection and segmentation, which is further refined by a time-implicit multi-phase evolution method. Firstly, a 3D CNN is trained to automatically localize and delineate the organs of interest with a probability prediction map. The learned probability map provides both subject-specific spatial priors and initialization for subsequent fine segmentation. Then, for the refinement of the multi-organ segmentation, image intensity models, probability priors as well as a disjoint region constraint are incorporated into an unified energy functional. Finally, a novel time-implicit multi-phase level-set algorithm is utilized to efficiently optimize the proposed energy functional model. Our method has been evaluated on 140 abdominal CT scans for the segmentation of four organs (liver, spleen and both kidneys). With respect to the ground truth, average Dice overlap ratios for the liver, spleen and both kidneys are 96.0, 94.2 and 95.4%, respectively, and average symmetric surface distance is less than 1.3 mm for all the segmented organs. The computation time for a CT volume is 125 s in average. The achieved accuracy compares well to state-of-the-art methods with much higher efficiency. A fully automatic method for multi-organ segmentation from abdominal CT images was developed and evaluated. The results demonstrated its potential in clinical usage with high effectiveness, robustness and efficiency.
Energy Technology Data Exchange (ETDEWEB)
Zhang, L; Pi, Y; Chen, Z; Xu, X [University of Science and Technology of China, Hefei, Anhui (China); Wang, Z [University of Science and Technology of China, Hefei, Anhui (China); The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui (China); Shi, C [Saint Vincent Medical Center, Bridgeport, CT (United States); Long, T; Luo, W; Wang, F [The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui (China)
2016-06-15
Purpose: To evaluate the ROI contours and accumulated dose difference using different deformable image registration (DIR) algorithms for head and neck (H&N) adaptive radiotherapy. Methods: Eight H&N cancer patients were randomly selected from the affiliated hospital. During the treatment, patients were rescanned every week with ROIs well delineated by radiation oncologist on each weekly CT. New weekly treatment plans were also re-designed with consistent dose prescription on the rescanned CT and executed for one week on Siemens CT-on-rails accelerator. At the end, we got six weekly CT scans from CT1 to CT6 including six weekly treatment plans for each patient. The primary CT1 was set as the reference CT for DIR proceeding with the left five weekly CTs using ANACONDA and MORFEUS algorithms separately in RayStation and the external skin ROI was set to be the controlling ROI both. The entire calculated weekly dose were deformed and accumulated on corresponding reference CT1 according to the deformation vector field (DVFs) generated by the two different DIR algorithms respectively. Thus we got both the ANACONDA-based and MORFEUS-based accumulated total dose on CT1 for each patient. At the same time, we mapped the ROIs on CT1 to generate the corresponding ROIs on CT6 using ANACONDA and MORFEUS DIR algorithms. DICE coefficients between the DIR deformed and radiation oncologist delineated ROIs on CT6 were calculated. Results: For DIR accumulated dose, PTV D95 and Left-Eyeball Dmax show significant differences with 67.13 cGy and 109.29 cGy respectively (Table1). For DIR mapped ROIs, PTV, Spinal cord and Left-Optic nerve show difference with −0.025, −0.127 and −0.124 (Table2). Conclusion: Even two excellent DIR algorithms can give divergent results for ROI deformation and dose accumulation. As more and more TPS get DIR module integrated, there is an urgent need to realize the potential risk using DIR in clinical.
Home advantage in high-level volleyball varies according to set number.
Marcelino, Rui; Mesquita, Isabel; Palao Andrés, José Manuel; Sampaio, Jaime
2009-01-01
The aim of the present study was to identify the probability of winning each Volleyball set according to game location (home, away). Archival data was obtained from 275 sets in the 2005 Men's Senior World League and 65,949 actions were analysed. Set result (win, loss), game location (home, away), set number (first, second, third, fourth and fifth) and performance indicators (serve, reception, set, attack, dig and block) were the variables considered in this study. In a first moment, performance indicators were used in a logistic model of set result, by binary logistic regression analysis. After finding the adjusted logistic model, the log-odds of winning the set were analysed according to game location and set number. The results showed that winning a set is significantly related to performance indicators (Chisquare(18)=660.97, padvantage at the beginning of the game (first set) and in the two last sets of the game (fourth and fifth sets), probably due to facilities familiarity and crowd effects. Different game actions explain these advantages and showed that to win the first set is more important to take risk, through a better performance in the attack and block, and to win the final set is important to manage the risk through a better performance on the reception. These results may suggest intra-game variation in home advantage and can be most useful to better prepare and direct the competition. Key pointsHome teams always have more probability of winning the game than away teams.Home teams have higher performance in reception, set and attack in the total of the sets.The advantage of home teams is more pronounced at the beginning of the game (first set) and in two last sets of the game (fourth and fifth sets) suggesting intra-game variation in home advantage.Analysis by sets showed that home teams have a better performance in the attack and block in the first set and in the reception in the third and fifth sets.
On the modeling of bubble evolution and transport using coupled level-set/CFD method
International Nuclear Information System (INIS)
Bartlomiej Wierzbicki; Steven P Antal; Michael Z Podowski
2005-01-01
Full text of publication follows: The ability to predict the shape of the gas/liquid/solid interfaces is important for various multiphase flow and heat transfer applications. Specific issues of interest to nuclear reactor thermal-hydraulics, include the evolution of the shape of bubbles attached to solid surfaces during nucleation, bubble surface interactions in complex geometries, etc. Additional problems, making the overall task even more complicated, are associated with the effect of material properties that may be significantly altered by the addition of minute amounts of impurities, such as surfactants or nano-particles. The present paper is concerned with the development of an innovative approach to model time-dependent shape of gas/liquid interfaces in the presence of solid walls. The proposed approach combines a modified level-set method with an advanced CFD code, NPHASE. The coupled numerical solver can be used to simulate the evolution of gas/liquid interfaces in two-phase flows for a variety of geometries and flow conditions, from individual bubbles to free surfaces (stratified flows). The issues discussed in the full paper will include: a description of the novel aspects of the proposed level-set concept based method, an overview of the NPHASE code modeling framework and a description of the coupling method between these two elements of the overall model. A particular attention will be give to the consistency and completeness of model formulation for the interfacial phenomena near the liquid/gas/solid triple line, and to the impact of the proposed numerical approach on the accuracy and consistency of predictions. The accuracy will be measured in terms of both the calculated shape of the interfaces and the gas and liquid velocity fields around the interfaces and in the entire computational domain. The results of model testing and validation will also be shown in the full paper. The situations analyzed will include: bubbles of different sizes and varying
Directory of Open Access Journals (Sweden)
Vincentius Raki Mahindhara
2017-01-01
Full Text Available Penggunaan relay arus lebih (over current relay pada industri memerlukan pengaturan beberapa parameter seperti arus pickup (Ip, time dial setting (TDS, serta waktu operasi (top. Dalam standard acuan dicantumkan batasan-batasan dan formulasi dalam menentukan parameter tersebut. Salah satu permasalahan adalah penentuan TDS pada relay inverse (Kode ANSI 51. Umumnya penentuan nilai TDS dilakukan dengan metode trial and error, hal ini dirasa kurang efektif sehingga diusulkan suatu metode baru dalam menentukan TDS pada sistem kelistrikan eksisting PT. Pupuk Kalimantan Timur. Digunakan algoritma adaptive firefly yang dimodifikasi dalam menyelesaikan permasalahan dengan mempertimbangkan kurva starting motor dan perbedaan tipe kurva antar relay
International Nuclear Information System (INIS)
Gao Min; Zhong Xia; Huang Shutao
2008-01-01
A multi-source database for high-level radioactive waste geological disposal, aims to promote the information process of the geological of HLW. In the periods of the multi-dimensional and multi-source and the integration of information and applications, it also relates to computer software and hardware, the paper preliminary analysises the data resources Beishan area, Gansu Province. The paper introduces a theory based on GIS technology and methods and open source code GDAL application, at the same time, it discusses the technical methods how to finish the application of the Quadtree algorithm in the area of information resources management system, fully sharing, rapid retrieval and so on. A more detailed description of the characteristics of existing data resources, space-related data retrieval algorithm theory, programming design and implementation of ideas are showed in the paper. (authors)
DEFF Research Database (Denmark)
Sharma, Ojaswa; Anton, François; Zhang, Qin
2009-01-01
-manding in terms of computation and memory space, we employ a CUDA based fast GPU segmentation and provide accuracy measures compared with an equivalent CPU implementation. Our resulting surfaces are C2-smooth resulting from tri-cubic spline interpolation algorithm. We also provide error bounds...
Taljaard, Monica; Tuna, Meltem; Bennett, Carol; Perez, Richard; Rosella, Laura; Tu, Jack V; Sanmartin, Claudia; Hennessy, Deirdre; Tanuseputro, Peter; Lebenbaum, Michael; Manuel, Douglas G
2014-10-23
Recent publications have called for substantial improvements in the design, conduct, analysis and reporting of prediction models. Publication of study protocols, with prespecification of key aspects of the analysis plan, can help to improve transparency, increase quality and protect against increased type I error. Valid population-based risk algorithms are essential for population health planning and policy decision-making. The purpose of this study is to develop, evaluate and apply cardiovascular disease (CVD) risk algorithms for the population setting. The Ontario sample of the Canadian Community Health Survey (2001, 2003, 2005; 77,251 respondents) will be used to assess risk factors focusing on health behaviours (physical activity, diet, smoking and alcohol use). Incident CVD outcomes will be assessed through linkage to administrative healthcare databases (619,886 person-years of follow-up until 31 December 2011). Sociodemographic factors (age, sex, immigrant status, education) and mediating factors such as presence of diabetes and hypertension will be included as predictors. Algorithms will be developed using competing risks survival analysis. The analysis plan adheres to published recommendations for the development of valid prediction models to limit the risk of overfitting and improve the quality of predictions. Key considerations are fully prespecifying the predictor variables; appropriate handling of missing data; use of flexible functions for continuous predictors; and avoiding data-driven variable selection procedures. The 2007 and 2009 surveys (approximately 50,000 respondents) will be used for validation. Calibration will be assessed overall and in predefined subgroups of importance to clinicians and policymakers. This study has been approved by the Ottawa Health Science Network Research Ethics Board. The findings will be disseminated through professional and scientific conferences, and in peer-reviewed journals. The algorithm will be accessible
International Nuclear Information System (INIS)
Vitta, Lavanya; Raghavan, Ashok; Sprigg, Alan; Morrell, Rachel
2009-01-01
Little is known about the radiation burden from fluoroscopy-guided insertions of nasojejunal tubes (NJTs) in children. There are no recommended or published standards of diagnostic reference levels (DRLs) available. To establish reference dose area product (DAP) levels for the fluoroscopy-guided insertion of nasojejunal tubes as a basis for setting DRLs for children. In addition, we wanted to assess our local practice and determine the success and complication rates associated with this procedure. Children who had NJT insertion procedures were identified retrospectively from the fluoroscopy database. The age of the child at the time of the procedure, DAP, screening time, outcome of the procedure, and any complications were recorded for each procedure. As the radiation dose depends on the size of the child, the children were assigned to three different age groups. The sample size, mean, median and third-quartile DAPs were calculated for each group. The third-quartile values were used to establish the DRLs. Of 186 procedures performed, 172 were successful on the first attempt. These were performed in a total of 43 children with 60% having multiple insertions over time. The third-quartile DAPs were as follows for each age group: 0-12 months, 2.6 cGy cm 2 ; 1-7 years, 2.45 cGy cm 2 ; >8 years, 14.6 cGy cm 2 . High DAP readings were obtained in the 0-12 months (n = 4) and >8 years (n = 2) age groups. No immediate complications were recorded. Fluoroscopy-guided insertion of NJTs is a highly successful procedure in a selected population of children and is associated with a low complication rate. The radiation dose per procedure is relatively low. (orig.)
Evaluation of two-phase flow solvers using Level Set and Volume of Fluid methods
Bilger, C.; Aboukhedr, M.; Vogiatzaki, K.; Cant, R. S.
2017-09-01
Two principal methods have been used to simulate the evolution of two-phase immiscible flows of liquid and gas separated by an interface. These are the Level-Set (LS) method and the Volume of Fluid (VoF) method. Both methods attempt to represent the very sharp interface between the phases and to deal with the large jumps in physical properties associated with it. Both methods have their own strengths and weaknesses. For example, the VoF method is known to be prone to excessive numerical diffusion, while the basic LS method has some difficulty in conserving mass. Major progress has been made in remedying these deficiencies, and both methods have now reached a high level of physical accuracy. Nevertheless, there remains an issue, in that each of these methods has been developed by different research groups, using different codes and most importantly the implementations have been fine tuned to tackle different applications. Thus, it remains unclear what are the remaining advantages and drawbacks of each method relative to the other, and what might be the optimal way to unify them. In this paper, we address this gap by performing a direct comparison of two current state-of-the-art variations of these methods (LS: RCLSFoam and VoF: interPore) and implemented in the same code (OpenFoam). We subject both methods to a pair of benchmark test cases while using the same numerical meshes to examine a) the accuracy of curvature representation, b) the effect of tuning parameters, c) the ability to minimise spurious velocities and d) the ability to tackle fluids with very different densities. For each method, one of the test cases is chosen to be fairly benign while the other test case is expected to present a greater challenge. The results indicate that both methods can be made to work well on both test cases, while displaying different sensitivity to the relevant parameters.
Panciera, Rocco; Walker, Jeffrey P.; Kalma, Jetse; Kim, Edward
2011-01-01
The Soil Moisture and Ocean Salinity (SMOS)mission, launched in November 2009, provides global maps of soil moisture and ocean salinity by measuring the L-band (1.4 GHz) emission of the Earth's surface with a spatial resolution of 40-50 km.Uncertainty in the retrieval of soilmoisture over large heterogeneous areas such as SMOS pixels is expected, due to the non-linearity of the relationship between soil moisture and the microwave emission. The current baseline soilmoisture retrieval algorithm adopted by SMOS and implemented in the SMOS Level 2 (SMOS L2) processor partially accounts for the sub-pixel heterogeneity of the land surface, by modelling the individual contributions of different pixel fractions to the overall pixel emission. This retrieval approach is tested in this study using airborne L-band data over an area the size of a SMOS pixel characterised by a mix Eucalypt forest and moderate vegetation types (grassland and crops),with the objective of assessing its ability to correct for the soil moisture retrieval error induced by the land surface heterogeneity. A preliminary analysis using a traditional uniform pixel retrieval approach shows that the sub-pixel heterogeneity of land cover type causes significant errors in soil moisture retrieval (7.7%v/v RMSE, 2%v/v bias) in pixels characterised by a significant amount of forest (40-60%). Although the retrieval approach adopted by SMOS partially reduces this error, it is affected by errors beyond the SMOS target accuracy, presenting in particular a strong dry bias when a fraction of the pixel is occupied by forest (4.1%v/v RMSE,-3.1%v/v bias). An extension to the SMOS approach is proposed that accounts for the heterogeneity of vegetation optical depth within the SMOS pixel. The proposed approach is shown to significantly reduce the error in retrieved soil moisture (2.8%v/v RMSE, -0.3%v/v bias) in pixels characterised by a critical amount of forest (40-60%), at the limited cost of only a crude estimate of the
Bunnoon, Pituk; Chalermyanont, Kusumal; Limsakul, Chusak
2010-02-01
This paper proposed the discrete transform and neural network algorithms to obtain the monthly peak load demand in mid term load forecasting. The mother wavelet daubechies2 (db2) is employed to decomposed, high pass filter and low pass filter signals from the original signal before using feed forward back propagation neural network to determine the forecasting results. The historical data records in 1997-2007 of Electricity Generating Authority of Thailand (EGAT) is used as reference. In this study, historical information of peak load demand(MW), mean temperature(Tmean), consumer price index (CPI), and industrial index (economic:IDI) are used as feature inputs of the network. The experimental results show that the Mean Absolute Percentage Error (MAPE) is approximately 4.32%. This forecasting results can be used for fuel planning and unit commitment of the power system in the future.
[Cardiac Synchronization Function Estimation Based on ASM Level Set Segmentation Method].
Zhang, Yaonan; Gao, Yuan; Tang, Liang; He, Ying; Zhang, Huie
At present, there is no accurate and quantitative methods for the determination of cardiac mechanical synchronism, and quantitative determination of the synchronization function of the four cardiac cavities with medical images has a great clinical value. This paper uses the whole heart ultrasound image sequence, and segments the left & right atriums and left & right ventricles of each frame. After the segmentation, the number of pixels in each cavity and in each frame is recorded, and the areas of the four cavities of the image sequence are therefore obtained. The area change curves of the four cavities are further extracted, and the synchronous information of the four cavities is obtained. Because of the low SNR of Ultrasound images, the boundary lines of cardiac cavities are vague, so the extraction of cardiac contours is still a challenging problem. Therefore, the ASM model information is added to the traditional level set method to force the curve evolution process. According to the experimental results, the improved method improves the accuracy of the segmentation. Furthermore, based on the ventricular segmentation, the right and left ventricular systolic functions are evaluated, mainly according to the area changes. The synchronization of the four cavities of the heart is estimated based on the area changes and the volume changes.
Automatic Fontanel Extraction from Newborns' CT Images Using Variational Level Set
Kazemi, Kamran; Ghadimi, Sona; Lyaghat, Alireza; Tarighati, Alla; Golshaeyan, Narjes; Abrishami-Moghaddam, Hamid; Grebe, Reinhard; Gondary-Jouet, Catherine; Wallois, Fabrice
A realistic head model is needed for source localization methods used for the study of epilepsy in neonates applying Electroencephalographic (EEG) measurements from the scalp. The earliest models consider the head as a series of concentric spheres, each layer corresponding to a different tissue whose conductivity is assumed to be homogeneous. The results of the source reconstruction depend highly on the electric conductivities of the tissues forming the head.The most used model is constituted of three layers (scalp, skull, and intracranial). Most of the major bones of the neonates’ skull are ossified at birth but can slightly move relative to each other. This is due to the sutures, fibrous membranes that at this stage of development connect the already ossified flat bones of the neurocranium. These weak parts of the neurocranium are called fontanels. Thus it is important to enter the exact geometry of fontaneles and flat bone in a source reconstruction because they show pronounced in conductivity. Computer Tomography (CT) imaging provides an excellent tool for non-invasive investigation of the skull which expresses itself in high contrast to all other tissues while the fontanels only can be identified as absence of bone, gaps in the skull formed by flat bone. Therefore, the aim of this paper is to extract the fontanels from CT images applying a variational level set method. We applied the proposed method to CT-images of five different subjects. The automatically extracted fontanels show good agreement with the manually extracted ones.
Two-phase electro-hydrodynamic flow modeling by a conservative level set model.
Lin, Yuan
2013-03-01
The principles of electro-hydrodynamic (EHD) flow have been known for more than a century and have been adopted for various industrial applications, for example, fluid mixing and demixing. Analytical solutions of such EHD flow only exist in a limited number of scenarios, for example, predicting a small deformation of a single droplet in a uniform electric field. Numerical modeling of such phenomena can provide significant insights about EHDs multiphase flows. During the last decade, many numerical results have been reported to provide novel and useful tools of studying the multiphase EHD flow. Based on a conservative level set method, the proposed model is able to simulate large deformations of a droplet by a steady electric field, which is beyond the region of theoretic prediction. The model is validated for both leaky dielectrics and perfect dielectrics, and is found to be in excellent agreement with existing analytical solutions and numerical studies in the literature. Furthermore, simulations of the deformation of a water droplet in decyl alcohol in a steady electric field match better with published experimental data than the theoretical prediction for large deformations. Therefore the proposed model can serve as a practical and accurate tool for simulating two-phase EHD flow. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Modeling of Two-Phase Flow in Rough-Walled Fracture Using Level Set Method
Directory of Open Access Journals (Sweden)
Yunfeng Dai
2017-01-01
Full Text Available To describe accurately the flow characteristic of fracture scale displacements of immiscible fluids, an incompressible two-phase (crude oil and water flow model incorporating interfacial forces and nonzero contact angles is developed. The roughness of the two-dimensional synthetic rough-walled fractures is controlled with different fractal dimension parameters. Described by the Navier–Stokes equations, the moving interface between crude oil and water is tracked using level set method. The method accounts for differences in densities and viscosities of crude oil and water and includes the effect of interfacial force. The wettability of the rough fracture wall is taken into account by defining the contact angle and slip length. The curve of the invasion pressure-water volume fraction is generated by modeling two-phase flow during a sudden drainage. The volume fraction of water restricted in the rough-walled fracture is calculated by integrating the water volume and dividing by the total cavity volume of the fracture while the two-phase flow is quasistatic. The effect of invasion pressure of crude oil, roughness of fracture wall, and wettability of the wall on two-phase flow in rough-walled fracture is evaluated.
Tokunaga and Horton self-similarity for level set trees of Markov chains
International Nuclear Information System (INIS)
Zaliapin, Ilia; Kovchegov, Yevgeniy
2012-01-01
Highlights: ► Self-similar properties of the level set trees for Markov chains are studied. ► Tokunaga and Horton self-similarity are established for symmetric Markov chains and regular Brownian motion. ► Strong, distributional self-similarity is established for symmetric Markov chains with exponential jumps. ► It is conjectured that fractional Brownian motions are Tokunaga self-similar. - Abstract: The Horton and Tokunaga branching laws provide a convenient framework for studying self-similarity in random trees. The Horton self-similarity is a weaker property that addresses the principal branching in a tree; it is a counterpart of the power-law size distribution for elements of a branching system. The stronger Tokunaga self-similarity addresses so-called side branching. The Horton and Tokunaga self-similarity have been empirically established in numerous observed and modeled systems, and proven for two paradigmatic models: the critical Galton–Watson branching process with finite progeny and the finite-tree representation of a regular Brownian excursion. This study establishes the Tokunaga and Horton self-similarity for a tree representation of a finite symmetric homogeneous Markov chain. We also extend the concept of Horton and Tokunaga self-similarity to infinite trees and establish self-similarity for an infinite-tree representation of a regular Brownian motion. We conjecture that fractional Brownian motions are also Tokunaga and Horton self-similar, with self-similarity parameters depending on the Hurst exponent.
Energy Technology Data Exchange (ETDEWEB)
Hammond, Glenn Edward; Song, Xuehang; Ye, Ming; Dai, Zhenxue; Zachara, John; Chen, Xingyuan
2017-03-01
A new approach is developed to delineate the spatial distribution of discrete facies (geological units that have unique distributions of hydraulic, physical, and/or chemical properties) conditioned not only on direct data (measurements directly related to facies properties, e.g., grain size distribution obtained from borehole samples) but also on indirect data (observations indirectly related to facies distribution, e.g., hydraulic head and tracer concentration). Our method integrates for the first time ensemble data assimilation with traditional transition probability-based geostatistics. The concept of level set is introduced to build shape parameterization that allows transformation between discrete facies indicators and continuous random variables. The spatial structure of different facies is simulated by indicator models using conditioning points selected adaptively during the iterative process of data assimilation. To evaluate the new method, a two-dimensional semi-synthetic example is designed to estimate the spatial distribution and permeability of two distinct facies from transient head data induced by pumping tests. The example demonstrates that our new method adequately captures the spatial pattern of facies distribution by imposing spatial continuity through conditioning points. The new method also reproduces the overall response in hydraulic head field with better accuracy compared to data assimilation with no constraints on spatial continuity on facies.
International Nuclear Information System (INIS)
Levitin, Gregory; Dai Yuanshun; Xie Min; Leng Poh, Kim
2003-01-01
In this paper we consider vulnerable systems which can have different states corresponding to different combinations of available elements composing the system. Each state can be characterized by a performance rate, which is the quantitative measure of a system's ability to perform its task. Both the impact of external factors (stress) and internal causes (failures) affect system survivability, which is determined as probability of meeting a given demand. In order to increase the survivability of the system, a multi-level protection is applied to its subsystems. This means that a subsystem and its inner level of protection are in their turn protected by the protection of an outer level. This double-protected subsystem has its outer protection and so forth. In such systems, the protected subsystems can be destroyed only if all of the levels of their protection are destroyed. Each level of protection can be destroyed only if all of the outer levels of protection are destroyed. We formulate the problem of finding the structure of series-parallel multi-state system (including choice of system elements, choice of structure of multi-level protection and choice of protection methods) in order to achieve a desired level of system survivability by the minimal cost. An algorithm based on the universal generating function method is used for determination of the system survivability. A multi-processor version of genetic algorithm is used as optimization tool in order to solve the structure optimization problem. An application example is presented to illustrate the procedure presented in this paper
Directory of Open Access Journals (Sweden)
Amara Umar
2015-06-01
Full Text Available Performance enhancement of Underwater Wireless Sensor Networks (UWSNs in terms of throughput maximization, energy conservation and Bit Error Rate (BER minimization is a potential research area. However, limited available bandwidth, high propagation delay, highly dynamic network topology, and high error probability leads to performance degradation in these networks. In this regard, many cooperative communication protocols have been developed that either investigate the physical layer or the Medium Access Control (MAC layer, however, the network layer is still unexplored. More specifically, cooperative routing has not yet been jointly considered with sink mobility. Therefore, this paper aims to enhance the network reliability and efficiency via dominating set based cooperative routing and sink mobility. The proposed work is validated via simulations which show relatively improved performance of our proposed work in terms the selected performance metrics.
Moraros, John; Islam, Adiba; Yu, Stan; Banow, Ryan; Schindelka, Barbara
2015-02-28
opportunities based on problem-solving activities and offer timely feedback/guidance to students. Yet in our study, this teaching style had its fair share of challenges, which were largely dependent on the use and management of technology. Despite these challenges, the Flipped Classroom proved to be a novel and effective teaching approach at the graduate level setting.
Level-3 Cholesky Factorization Routines Improve Performance of Many Cholesky Algorithms
DEFF Research Database (Denmark)
Gustavson, Fred G.; Wasniewski, Jerzy; Dongarra, Jack J.
2013-01-01
Four routines called DPOTF3i, i = a,b,c,d, are presented. DPOTF3i are a novel type of level-3 BLAS for use by BPF (Blocked Packed Format) Cholesky factorization and LAPACK routine DPOTRF. Performance of routines DPOTF3i are still increasing when the performance of Level-2 routine DPOTF2 of LAPACK...
de Groene, L.; Harmsen, R. E.; Binnekade, J. M.; Spronk, P. E.; Schultz, M. J.
2010-01-01
Background. Hyperglycemia and glycemic variabilities are associated with adverse outcomes in critically ill patients. Blood glucose control with insulin mandates an adequate and precise assessment of blood glucose levels. Blood glucose levels, however, can change ex vivo after sampling. The aim of
van de Meent D; Aldenberg T; Canton JH; van Gestel CAM; Slooff W
1990-01-01
The report provides scientific support for setting environmental quality objectives for water, sediment and soil. Quality criteria are not set in this report. Only options for decisions are given. The report is restricted to the derivation of the 'maximally acceptable risk' levels (MAR)
Schramm, Georg; Holler, Martin; Rezaei, Ahmadreza; Vunckx, Kathleen; Knoll, Florian; Bredies, Kristian; Boada, Fernando; Nuyts, Johan
2018-02-01
In this article, we evaluate Parallel Level Sets (PLS) and Bowsher's method as segmentation-free anatomical priors for regularized brain positron emission tomography (PET) reconstruction. We derive the proximity operators for two PLS priors and use the EM-TV algorithm in combination with the first order primal-dual algorithm by Chambolle and Pock to solve the non-smooth optimization problem for PET reconstruction with PLS regularization. In addition, we compare the performance of two PLS versions against the symmetric and asymmetric Bowsher priors with quadratic and relative difference penalty function. For this aim, we first evaluate reconstructions of 30 noise realizations of simulated PET data derived from a real hybrid positron emission tomography/magnetic resonance imaging (PET/MR) acquisition in terms of regional bias and noise. Second, we evaluate reconstructions of a real brain PET/MR data set acquired on a GE Signa time-of-flight PET/MR in a similar way. The reconstructions of simulated and real 3D PET/MR data show that all priors were superior to post-smoothed maximum likelihood expectation maximization with ordered subsets (OSEM) in terms of bias-noise characteristics in different regions of interest where the PET uptake follows anatomical boundaries. Our implementation of the asymmetric Bowsher prior showed slightly superior performance compared with the two versions of PLS and the symmetric Bowsher prior. At very high regularization weights, all investigated anatomical priors suffer from the transfer of non-shared gradients.
Toward accurate tooth segmentation from computed tomography images using a hybrid level set model
Energy Technology Data Exchange (ETDEWEB)
Gan, Yangzhou; Zhao, Qunfei [Department of Automation, Shanghai Jiao Tong University, and Key Laboratory of System Control and Information Processing, Ministry of Education of China, Shanghai 200240 (China); Xia, Zeyang, E-mail: zy.xia@siat.ac.cn, E-mail: jing.xiong@siat.ac.cn; Hu, Ying [Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, and The Chinese University of Hong Kong, Shenzhen 518055 (China); Xiong, Jing, E-mail: zy.xia@siat.ac.cn, E-mail: jing.xiong@siat.ac.cn [Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 510855 (China); Zhang, Jianwei [TAMS, Department of Informatics, University of Hamburg, Hamburg 22527 (Germany)
2015-01-15
Purpose: A three-dimensional (3D) model of the teeth provides important information for orthodontic diagnosis and treatment planning. Tooth segmentation is an essential step in generating the 3D digital model from computed tomography (CT) images. The aim of this study is to develop an accurate and efficient tooth segmentation method from CT images. Methods: The 3D dental CT volumetric images are segmented slice by slice in a two-dimensional (2D) transverse plane. The 2D segmentation is composed of a manual initialization step and an automatic slice by slice segmentation step. In the manual initialization step, the user manually picks a starting slice and selects a seed point for each tooth in this slice. In the automatic slice segmentation step, a developed hybrid level set model is applied to segment tooth contours from each slice. Tooth contour propagation strategy is employed to initialize the level set function automatically. Cone beam CT (CBCT) images of two subjects were used to tune the parameters. Images of 16 additional subjects were used to validate the performance of the method. Volume overlap metrics and surface distance metrics were adopted to assess the segmentation accuracy quantitatively. The volume overlap metrics were volume difference (VD, mm{sup 3}) and Dice similarity coefficient (DSC, %). The surface distance metrics were average symmetric surface distance (ASSD, mm), RMS (root mean square) symmetric surface distance (RMSSSD, mm), and maximum symmetric surface distance (MSSD, mm). Computation time was recorded to assess the efficiency. The performance of the proposed method has been compared with two state-of-the-art methods. Results: For the tested CBCT images, the VD, DSC, ASSD, RMSSSD, and MSSD for the incisor were 38.16 ± 12.94 mm{sup 3}, 88.82 ± 2.14%, 0.29 ± 0.03 mm, 0.32 ± 0.08 mm, and 1.25 ± 0.58 mm, respectively; the VD, DSC, ASSD, RMSSSD, and MSSD for the canine were 49.12 ± 9.33 mm{sup 3}, 91.57 ± 0.82%, 0.27 ± 0.02 mm, 0
Toward accurate tooth segmentation from computed tomography images using a hybrid level set model
International Nuclear Information System (INIS)
Gan, Yangzhou; Zhao, Qunfei; Xia, Zeyang; Hu, Ying; Xiong, Jing; Zhang, Jianwei
2015-01-01
Purpose: A three-dimensional (3D) model of the teeth provides important information for orthodontic diagnosis and treatment planning. Tooth segmentation is an essential step in generating the 3D digital model from computed tomography (CT) images. The aim of this study is to develop an accurate and efficient tooth segmentation method from CT images. Methods: The 3D dental CT volumetric images are segmented slice by slice in a two-dimensional (2D) transverse plane. The 2D segmentation is composed of a manual initialization step and an automatic slice by slice segmentation step. In the manual initialization step, the user manually picks a starting slice and selects a seed point for each tooth in this slice. In the automatic slice segmentation step, a developed hybrid level set model is applied to segment tooth contours from each slice. Tooth contour propagation strategy is employed to initialize the level set function automatically. Cone beam CT (CBCT) images of two subjects were used to tune the parameters. Images of 16 additional subjects were used to validate the performance of the method. Volume overlap metrics and surface distance metrics were adopted to assess the segmentation accuracy quantitatively. The volume overlap metrics were volume difference (VD, mm 3 ) and Dice similarity coefficient (DSC, %). The surface distance metrics were average symmetric surface distance (ASSD, mm), RMS (root mean square) symmetric surface distance (RMSSSD, mm), and maximum symmetric surface distance (MSSD, mm). Computation time was recorded to assess the efficiency. The performance of the proposed method has been compared with two state-of-the-art methods. Results: For the tested CBCT images, the VD, DSC, ASSD, RMSSSD, and MSSD for the incisor were 38.16 ± 12.94 mm 3 , 88.82 ± 2.14%, 0.29 ± 0.03 mm, 0.32 ± 0.08 mm, and 1.25 ± 0.58 mm, respectively; the VD, DSC, ASSD, RMSSSD, and MSSD for the canine were 49.12 ± 9.33 mm 3 , 91.57 ± 0.82%, 0.27 ± 0.02 mm, 0.28 ± 0.03 mm
Multi-threaded algorithms for GPGPU in the ATLAS High Level Trigger
AUTHOR|(INSPIRE)INSPIRE-00212700; The ATLAS collaboration
2017-01-01
General purpose Graphics Processor Units (GPGPU) are being evaluated for possible future inclusion in an upgraded ATLAS High Level Trigger farm. We have developed a demonstrator including GPGPU implementations of Inner Detector and Muon tracking and Calorimeter clustering within the ATLAS software framework. ATLAS is a general purpose particle physics experiment located on the LHC collider at CERN. The ATLAS Trigger system consists of two levels, with Level-1 implemented in hardware and the High Level Trigger implemented in software running on a farm of commodity CPU. The High Level Trigger reduces the trigger rate from the 100 kHz Level-1 acceptance rate to 1.5 kHz for recording, requiring an average per-event processing time of ∼ 250 ms for this task. The selection in the high level trigger is based on reconstructing tracks in the Inner Detector and Muon Spectrometer and clusters of energy deposited in the Calorimeter. Performing this reconstruction within the available farm resources presents a significa...
Sensitivity Analysis of features in tolerancing based on constraint function level sets
International Nuclear Information System (INIS)
Ziegler, Philipp; Wartzack, Sandro
2015-01-01
Usually, the geometry of the manufactured product inherently varies from the nominal geometry. This may negatively affect the product functions and properties (such as quality and reliability), as well as the assemblability of the single components. In order to avoid this, the geometric variation of these component surfaces and associated geometry elements (like hole axes) are restricted by tolerances. Since tighter tolerances lead to significant higher manufacturing costs, tolerances should be specified carefully. Therefore, the impact of deviating component surfaces on functions, properties and assemblability of the product has to be analyzed. As physical experiments are expensive, methods of statistical tolerance analysis tools are widely used in engineering design. Current tolerance simulation tools lack of an appropriate indicator for the impact of deviating component surfaces. In the adoption of Sensitivity Analysis methods, there are several challenges, which arise from the specific framework in tolerancing. This paper presents an approach to adopt Sensitivity Analysis methods on current tolerance simulations with an interface module, which bases on level sets of constraint functions for parameters of the simulation model. The paper is an extension and generalization of Ziegler and Wartzack [1]. Mathematical properties of the constraint functions (convexity, homogeneity), which are important for the computational costs of the Sensitivity Analysis, are shown. The practical use of the method is illustrated in a case study of a plain bearing. - Highlights: • Alternative definition of Deviation Domains. • Proof of mathematical properties of the Deviation Domains. • Definition of the interface between Deviation Domains and Sensitivity Analysis. • Sensitivity analysis of a gearbox to show the methods practical use
Directory of Open Access Journals (Sweden)
Won-Kwang Park
2013-01-01
Full Text Available An inverse problem for reconstructing arbitrary-shaped thin penetrable electromagnetic inclusions concealed in a homogeneous material is considered in this paper. For this purpose, the level-set evolution method is adopted. The topological derivative concept is incorporated in order to evaluate the evolution speed of the level-set functions. The results of the corresponding numerical simulations with and without noise are presented in this paper.
Revil, A.
2015-12-01
Geological expertise and petrophysical relationships can be brought together to provide prior information while inverting multiple geophysical datasets. The merging of such information can result in more realistic solution in the distribution of the model parameters, reducing ipse facto the non-uniqueness of the inverse problem. We consider two level of heterogeneities: facies, described by facies boundaries and heteroegenities inside each facies determined by a correlogram. In this presentation, we pose the geophysical inverse problem in terms of Gaussian random fields with mean functions controlled by petrophysical relationships and covariance functions controlled by a prior geological cross-section, including the definition of spatial boundaries for the geological facies. The petrophysical relationship problem is formulated as a regression problem upon each facies. The inversion of the geophysical data is performed in a Bayesian framework. We demonstrate the usefulness of this strategy using a first synthetic case for which we perform a joint inversion of gravity and galvanometric resistivity data with the stations located at the ground surface. The joint inversion is used to recover the density and resistivity distributions of the subsurface. In a second step, we consider the possibility that the facies boundaries are deformable and their shapes are inverted as well. We use the level set approach to perform such deformation preserving prior topological properties of the facies throughout the inversion. With the help of prior facies petrophysical relationships and topological characteristic of each facies, we make posterior inference about multiple geophysical tomograms based on their corresponding geophysical data misfits. The method is applied to a second synthetic case showing that we can recover the heterogeneities inside the facies, the mean values for the petrophysical properties, and, to some extent, the facies boundaries using the 2D joint inversion of
Energy Technology Data Exchange (ETDEWEB)
Umarova, Zhanat; Botayeva, Saule; Yegenova, Aliya; Usenova, Aisaule [South Kazakhstan State University, 5, Tauke Khan Avenue, 160012 Shymkent (Kazakhstan)
2015-05-15
In the given article, the main thermodynamic aspects of the issue of modeling diffusion transfer in molecular sieves have been formulated. Dissipation function is used as a basic notion. The differential equation, connecting volume flow with the change of the concentration of catchable component has been derived. As a result, the expression for changing the concentration of the catchable component and the coefficient of membrane detecting has been received. As well, the system approach to describing the process of gases separation in ultra porous membranes has been realized and micro and meso-levels of mathematical modeling have been distinguished. The non-ideality of the shared system is primarily taken into consideration at the micro-level and the departure from the diffusion law of Fick has been taken into account. The calculation method of selectivity considering fractal structure of membranes has been developed at the meso level. The calculation algorithm and its software implementation have been suggested.
International Nuclear Information System (INIS)
Umarova, Zhanat; Botayeva, Saule; Yegenova, Aliya; Usenova, Aisaule
2015-01-01
In the given article, the main thermodynamic aspects of the issue of modeling diffusion transfer in molecular sieves have been formulated. Dissipation function is used as a basic notion. The differential equation, connecting volume flow with the change of the concentration of catchable component has been derived. As a result, the expression for changing the concentration of the catchable component and the coefficient of membrane detecting has been received. As well, the system approach to describing the process of gases separation in ultra porous membranes has been realized and micro and meso-levels of mathematical modeling have been distinguished. The non-ideality of the shared system is primarily taken into consideration at the micro-level and the departure from the diffusion law of Fick has been taken into account. The calculation method of selectivity considering fractal structure of membranes has been developed at the meso level. The calculation algorithm and its software implementation have been suggested
DEFF Research Database (Denmark)
Maluka, Stephen; Kamuzora, Peter; Sebastián, Miguel San
2010-01-01
In 2006, researchers and decision-makers launched a five-year project - Response to Accountable Priority Setting for Trust in Health Systems (REACT) - to improve planning and priority-setting through implementing the Accountability for Reasonableness framework in Mbarali District, Tanzania...
Directory of Open Access Journals (Sweden)
Olmos Pablo R
2010-07-01
Full Text Available Abstract Background It is known that tight control of glucose in the Intensive Care Unit reduces morbidity and mortality not only in diabetic patients but also in those non-diabetics who become transiently hyperglycemic. Taking advantage of a recently marketed subcutaneous glucose sensor we designed an Automatic Insulin Infusion System (AIIS for inpatient treatment, and tested its stability under simulated clinical conditions. Methods The system included: reference glucose, glucose sensor, insulin and glucose infusion controllers and emergency infusion logic. We carried out computer simulations using Matlab/Simulink®, in both common and worst-case conditions. Results The system was capable of controlling glucose levels without entering in a phase of catastrophic instability, even under severe simulated challenges. Care was taken to include in all simulations the 5-10 minute delay of the subcutaneous glucose signal when compared to the real-time serum glucose signal, a well-known characteristic of all subcutaneous glucose sensors. Conclusions When tested in-Silico, a commercially available subcutaneous glucose sensor allowed the stable functioning of a proportional-derivative Automatic Insulin Infusion System, which was able to maintain glucose within acceptable limits when using a well-established glucose response model simulating a patient. Testing of the system in vivo using animal models is now warranted.
Végh, Ladislav
2016-01-01
The first data structure that first-year undergraduate students learn during the programming and algorithms courses is the one-dimensional array. For novice programmers, it might be hard to understand different algorithms on arrays (e.g. searching, mirroring, sorting algorithms), because the algorithms dynamically change the values of elements. In…
Siddeq, M. M.; Rodrigues, M. A.
2015-09-01
Image compression techniques are widely used on 2D image 2D video 3D images and 3D video. There are many types of compression techniques and among the most popular are JPEG and JPEG2000. In this research, we introduce a new compression method based on applying a two level discrete cosine transform (DCT) and a two level discrete wavelet transform (DWT) in connection with novel compression steps for high-resolution images. The proposed image compression algorithm consists of four steps. (1) Transform an image by a two level DWT followed by a DCT to produce two matrices: DC- and AC-Matrix, or low and high frequency matrix, respectively, (2) apply a second level DCT on the DC-Matrix to generate two arrays, namely nonzero-array and zero-array, (3) apply the Minimize-Matrix-Size algorithm to the AC-Matrix and to the other high-frequencies generated by the second level DWT, (4) apply arithmetic coding to the output of previous steps. A novel decompression algorithm, Fast-Match-Search algorithm (FMS), is used to reconstruct all high-frequency matrices. The FMS-algorithm computes all compressed data probabilities by using a table of data, and then using a binary search algorithm for finding decompressed data inside the table. Thereafter, all decoded DC-values with the decoded AC-coefficients are combined in one matrix followed by inverse two levels DCT with two levels DWT. The technique is tested by compression and reconstruction of 3D surface patches. Additionally, this technique is compared with JPEG and JPEG2000 algorithm through 2D and 3D root-mean-square-error following reconstruction. The results demonstrate that the proposed compression method has better visual properties than JPEG and JPEG2000 and is able to more accurately reconstruct surface patches in 3D.
Directory of Open Access Journals (Sweden)
L. Bressan
2011-05-01
Full Text Available The goal of this paper is to present an original real-time algorithm devised for detection of tsunami or tsunami-like waves we call TEDA (Tsunami Early Detection Algorithm, and to introduce a methodology to evaluate its performance. TEDA works on the sea level records of a single station and implements two distinct modules running concurrently: one to assess the presence of tsunami waves ("tsunami detection" and the other to identify high-amplitude long waves ("secure detection". Both detection methods are based on continuously updated time functions depending on a number of parameters that can be varied according to the application. In order to select the most adequate parameter setting for a given station, a methodology to evaluate TEDA performance has been devised, that is based on a number of indicators and that is simple to use. In this paper an example of TEDA application is given by using data from a tide gauge located at the Adak Island in Alaska, USA, that resulted in being quite suitable since it recorded several tsunamis in the last years using the sampling rate of 1 min.
Quan, Haiyang; Wu, Fan; Hou, Xi
2015-10-01
New method for reconstructing rotationally asymmetric surface deviation with pixel-level spatial resolution is proposed. It is based on basic iterative scheme and accelerates the Gauss-Seidel method by introducing an acceleration parameter. This modified Successive Over-relaxation (SOR) is effective for solving the rotationally asymmetric components with pixel-level spatial resolution, without the usage of a fitting procedure. Compared to the Jacobi and Gauss-Seidel method, the modified SOR method with an optimal relaxation factor converges much faster and saves more computational costs and memory space without reducing accuracy. It has been proved by real experimental results.
MO-AB-BRA-01: A Global Level Set Based Formulation for Volumetric Modulated Arc Therapy
Energy Technology Data Exchange (ETDEWEB)
Nguyen, D; Lyu, Q; Ruan, D; O’Connor, D; Low, D; Sheng, K [Department of Radiation Oncology, University of California Los Angeles, Los Angeles, CA (United States)
2016-06-15
Purpose: The current clinical Volumetric Modulated Arc Therapy (VMAT) optimization is formulated as a non-convex problem and various greedy heuristics have been employed for an empirical solution, jeopardizing plan consistency and quality. We introduce a novel global direct aperture optimization method for VMAT to overcome these limitations. Methods: The global VMAT (gVMAT) planning was formulated as an optimization problem with an L2-norm fidelity term and an anisotropic total variation term. A level set function was used to describe the aperture shapes and adjacent aperture shapes were penalized to control MLC motion range. An alternating optimization strategy was implemented to solve the fluence intensity and aperture shapes simultaneously. Single arc gVMAT plans, utilizing 180 beams with 2° angular resolution, were generated for a glioblastoma multiforme (GBM), lung (LNG), and 2 head and neck cases—one with 3 PTVs (H&N3PTV) and one with 4 PTVs (H&N4PTV). The plans were compared against the clinical VMAT (cVMAT) plans utilizing two overlapping coplanar arcs. Results: The optimization of the gVMAT plans had converged within 600 iterations. gVMAT reduced the average max and mean OAR dose by 6.59% and 7.45% of the prescription dose. Reductions in max dose and mean dose were as high as 14.5 Gy in the LNG case and 15.3 Gy in the H&N3PTV case. PTV coverages (D95, D98, D99) were within 0.25% of the prescription dose. By globally considering all beams, the gVMAT optimizer allowed some beams to deliver higher intensities, yielding a dose distribution that resembles a static beam IMRT plan with beam orientation optimization. Conclusions: The novel VMAT approach allows for the search of an optimal plan in the global solution space and generates deliverable apertures directly. The single arc VMAT approach fully utilizes the digital linacs’ capability in dose rate and gantry rotation speed modulation. Varian Medical Systems, NIH grant R01CA188300, NIH grant R43CA183390.
A finite element/level set model of polyurethane foam expansion and polymerization
Energy Technology Data Exchange (ETDEWEB)
Rao, Rekha R. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Long, Kevin Nicholas [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Roberts, Christine Cardinal [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Celina, Mathias C. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Brunini, Victor [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Soehnel, Melissa Marie [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Noble, David R. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Tinsley, James [Honeywell Federal Manufacturing & Technologies, Kansas City, MO (United States); Mondy, Lisa [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
2017-12-01
Polyurethane foams are used widely for encapsulation and structural purposes because they are inexpensive, straightforward to process, amenable to a wide range of density variations (1 lb/ft3 - 50 lb/ft3), and able to fill complex molds quickly and effectively. Computational model of the filling and curing process are needed to reduce defects such as voids, out-of-specification density, density gradients, foam decomposition from high temperatures due to exotherms, and incomplete filling. This paper details the development of a computational fluid dynamics model of a moderate density PMDI structural foam, PMDI-10. PMDI is an isocyanate-based polyurethane foam, which is chemically blown with water. The polyol reacts with isocyanate to produces the polymer. PMDI- 10 is catalyzed giving it a short pot life: it foams and polymerizes to a solid within 5 minutes during normal processing. To achieve a higher density, the foam is over-packed to twice or more of its free rise density of 10 lb/ft3. The goal for modeling is to represent the expansion, filling of molds, and the polymerization of the foam. This will be used to reduce defects, optimize the mold design, troubleshoot the processed, and predict the final foam properties. A homogenized continuum model foaming and curing was developed based on reaction kinetics, documented in a recent paper; it uses a simplified mathematical formalism that decouples these two reactions. The chemo-rheology of PMDI is measured experimentally and fit to a generalized- Newtonian viscosity model that is dependent on the extent of cure, gas fraction, and temperature. The conservation equations, including the equations of motion, an energy balance, and three rate equations are solved via a stabilized finite element method. The equations are combined with a level set method to determine the location of the foam-gas interface as it evolves to fill the mold. Understanding the thermal history and loads on the foam due to exothermicity and oven
Uniqueness, intractability and exact algorithms: reflections on level-k phylogenetic networks
L.J.J. van Iersel (Leo); S.M. Kelk (Steven); M. Mnich
2009-01-01
htmlabstractPhylogenetic networks provide a way to describe and visualize evolutionary histories that have undergone so-called reticulate evolutionary events such as recombination, hybridization or horizontal gene transfer. The level k of a network determines how non-treelike the evolution can be,
Directory of Open Access Journals (Sweden)
Stephen Maluka
2011-11-01
Full Text Available Health care systems are faced with the challenge of resource scarcity and have insufficient resources to respond to all health problems and target groups simultaneously. Hence, priority setting is an inevitable aspect of every health system. However, priority setting is complex and difficult because the process is frequently influenced by political, institutional and managerial factors that are not considered by conventional priority-setting tools. In a five-year EU-supported project, which started in 2006, ways of strengthening fairness and accountability in priority setting in district health management were studied. This review is based on a PhD thesis that aimed to analyse health care organisation and management systems, and explore the potential and challenges of implementing Accountability for Reasonableness (A4R approach to priority setting in Tanzania. A qualitative case study in Mbarali district formed the basis of exploring the sociopolitical and institutional contexts within which health care decision making takes place. The study also explores how the A4R intervention was shaped, enabled and constrained by the contexts. Key informant interviews were conducted. Relevant documents were also gathered and group priority-setting processes in the district were observed. The study revealed that, despite the obvious national rhetoric on decentralisation, actual practice in the district involved little community participation. The assumption that devolution to local government promotes transparency, accountability and community participation, is far from reality. The study also found that while the A4R approach was perceived to be helpful in strengthening transparency, accountability and stakeholder engagement, integrating the innovation into the district health system was challenging. This study underscores the idea that greater involvement and accountability among local actors may increase the legitimacy and fairness of priority-setting
The Digital Algorithm Processors for the ATLAS Level-1 Calorimeter Trigger
Silverstein, S
2010-01-01
The ATLAS Level-1 Calorimeter Trigger identifies high-ET jets, electrons/photons and hadrons and measures total and missing transverse energy in proton-proton collisions at the Large Hadron Collider. Two subsystems – the Jet/Energy-sum Processor (JEP) and the Cluster Processor(CP) – process data from every crossing, and report feature multiplicities and energy sums to the ATLAS Central Trigger Processor, which produces a Level-1 Accept decision. Locations and types of identified features are read out to the Level-2 Trigger as regions-of-interest, and quality-monitoring information is read out to the ATLAS data acquisition system. The JEP and CP subsystems share a great deal of common infrastructure, including a custom backplane, several common hardware modules, and readout hardware. Some of the common modules use FPGAs with selectable firmware configurations based on the location in the system. This approach saved substantial development effort and provided a uniform model for software development. We pre...
The Digital Algorithm Processors for the ATLAS Level-1 Calorimeter Trigger
Silverstein, S; The ATLAS collaboration
2009-01-01
The ATLAS Level-1 Calorimeter Trigger identifies high-ET jets, electrons/photons and hadrons and measures total and missing transverse energy in proton-proton collisions at the Large Hadron Collider. Two subsystems – the Jet/Energy-sum Processor (JEP) and the Cluster Processor(CP) – process data from every crossing, and report feature multiplicities and energy sums to the ATLAS Central Trigger Processor, which produces a Level-1 Accept decision. Locations and types of identified features are read out to the Level-2 Trigger as regions-of-interest, and quality-monitoring information is read out to the ATLAS data acquisition system. The JEP and CP subsystems share a great deal of common infrastructure, including a custom backplane, several common hardware modules, and readout hardware. Some of the common modules use FPGAs with selectable firmware configurations based on the location in the system. This approach saved substantial development effort and provided a uniform model for software development. We pre...
Developing a b-tagging algorithm using soft muons at level-3 for the DO detector at Fermilab
Energy Technology Data Exchange (ETDEWEB)
Das, Mayukh [Louisiana Tech. U.
2005-01-01
The current data-taking phase of the DØ detector at Fermilab, called Run II, is designed to aid the search for the Higgs Boson. The neutral Higgs is postulated to have a mass of 117 GeV. One of the channels promising the presence of this hypothetical particle is through the decay of b-quark into a muon. The process of identifying a b-quark in a jet using muon as a reference is b-tagging with a muon tag. At the current data taking and analysis rate, it will take long to reach the process of identifying valid events. The triggering mechanism of the experiment, consisting of 3 levels of combined hardware, firmware and software writes fi physics events at the rate of 50 Hz to data disks, with Level-3 alone accounting for the reduction from 1 kHz to 50 Hz. This large rejection is achieved through algorithms implemented in the search for key physics processes. The work presented in this dissertation is the development of a fast b-tagging algorithm using central-matched muons, called L3FBTagMU. Additional tools such as the impact parameter tracks and calorimeter jets have been used to tag B jets. The dR or the differential increment in cone radius is the most significant variable introduced. Plots within thresholds of dR for both Z → bb Monte Carlo and monitor stream data show similar efficiency trends when checked against other parameters. The differential efficiencies saturate at dR within 0.5 to 0.7 range. Differential bins of 0.1 intervals project an overall efficiency of tagging a b-jet in any event is 17.25 in data. This is in good agreement with the theory. The algorithm is currently running online and offline through the DØ database repository. This work is primarily used by the b-id, B-Physics and Higgs Physics groups for their physics analysis wherein the above b-tagging efficiency serves as a crucial tool. The prospect for optimizing the physics potential using this algorithm is very promising for current and future analyses.
A two-level strategy to realize life-cycle production optimization in an operational setting
Essen, van G.M.; Hof, Van den P.M.J.; Jansen, J.D.
2012-01-01
We present a two-level strategy to improve robustness against uncertainty and model errors in life-cycle flooding optimization. At the upper level, a physics-based large-scale reservoir model is used to determine optimal life-cycle injection and production profiles. At the lower level these profiles
A two-level strategy to realize life-cycle production optimization in an operational setting
Essen, van G.M.; Hof, Van den P.M.J.; Jansen, J.D.
2013-01-01
We present a two-level strategy to improve robustness against uncertainty and model errors in life-cycle flooding optimization. At the upper level, a physics-based large-scale reservoir model is used to determine optimal life-cycle injection and production profiles. At the lower level these profiles
Energy Technology Data Exchange (ETDEWEB)
Almeida, Luciana O.; Goto, Renata N. [Department of Clinical Analyses, Toxicology and Food Sciences, School of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo, Ribeirão Preto, SP (Brazil); Neto, Marinaldo P.C. [Department of Physics and Chemistry, School of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo, Ribeirão Preto, SP (Brazil); Sousa, Lucas O. [Department of Clinical Analyses, Toxicology and Food Sciences, School of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo, Ribeirão Preto, SP (Brazil); Curti, Carlos [Department of Physics and Chemistry, School of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo, Ribeirão Preto, SP (Brazil); Leopoldino, Andréia M., E-mail: andreiaml@usp.br [Department of Clinical Analyses, Toxicology and Food Sciences, School of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo, Ribeirão Preto, SP (Brazil)
2015-03-06
We hypothesized that SET, a protein accumulated in some cancer types and Alzheimer disease, is involved in cell death through mitochondrial mechanisms. We addressed the mRNA and protein levels of the mitochondrial uncoupling proteins UCP1, UCP2 and UCP3 (S and L isoforms) by quantitative real-time PCR and immunofluorescence as well as other mitochondrial involvements, in HEK293 cells overexpressing the SET protein (HEK293/SET), either in the presence or absence of oxidative stress induced by the pro-oxidant t-butyl hydroperoxide (t-BHP). SET overexpression in HEK293 cells decreased UCP1 and increased UCP2 and UCP3 (S/L) mRNA and protein levels, whilst also preventing lipid peroxidation and decreasing the content of cellular ATP. SET overexpression also (i) decreased the area of mitochondria and increased the number of organelles and lysosomes, (ii) increased mitochondrial fission, as demonstrated by increased FIS1 mRNA and FIS-1 protein levels, an apparent accumulation of DRP-1 protein, and an increase in the VDAC protein level, and (iii) reduced autophagic flux, as demonstrated by a decrease in LC3B lipidation (LC3B-II) in the presence of chloroquine. Therefore, SET overexpression in HEK293 cells promotes mitochondrial fission and reduces autophagic flux in apparent association with up-regulation of UCP2 and UCP3; this implies a potential involvement in cellular processes that are deregulated such as in Alzheimer's disease and cancer. - Highlights: • SET, UCPs and autophagy prevention are correlated. • SET action has mitochondrial involvement. • UCP2/3 may reduce ROS and prevent autophagy. • SET protects cell from ROS via UCP2/3.
Raouafi, Sana; Achiche, Sofiane; Begon, Mickael; Sarcher, Aurélie; Raison, Maxime
2018-01-01
Treatment for cerebral palsy depends upon the severity of the child's condition and requires knowledge about upper limb disability. The aim of this study was to develop a systematic quantitative classification method of the upper limb disability levels for children with spastic unilateral cerebral palsy based on upper limb movements and muscle activation. Thirteen children with spastic unilateral cerebral palsy and six typically developing children participated in this study. Patients were matched on age and manual ability classification system levels I to III. Twenty-three kinematic and electromyographic variables were collected from two tasks. Discriminative analysis and K-means clustering algorithm were applied using 23 kinematic and EMG variables of each participant. Among the 23 kinematic and electromyographic variables, only two variables containing the most relevant information for the prediction of the four levels of severity of spastic unilateral cerebral palsy, which are fixed by manual ability classification system, were identified by discriminant analysis: (1) the Falconer index (CAI E ) which represents the ratio of biceps to triceps brachii activity during extension and (2) the maximal angle extension (θ Extension,max ). A good correlation (Kendall Rank correlation coefficient = -0.53, p = 0.01) was found between levels fixed by manual ability classification system and the obtained classes. These findings suggest that the cost and effort needed to assess and characterize the disability level of a child can be further reduced.
International Nuclear Information System (INIS)
Kuwazuru, Junpei; Magome, Taiki; Arimura, Hidetaka; Yamashita, Yasuo; Oki, Masafumi; Toyofuku, Fukai; Kakeda, Shingo; Yamamoto, Daisuke
2010-01-01
Yamamoto et al. developed the system for computer-aided detection of multiple sclerosis (MS) candidate regions. In a level set method in their proposed method, they employed the constant threshold value for the edge indicator function related to a speed function of the level set method. However, it would be appropriate to adjust the threshold value to each MS candidate region, because the edge magnitudes in MS candidates differ from each other. Our purpose of this study was to develop a computerized detection of MS candidate regions in MR images based on a level set method using an artificial neural network (ANN). To adjust the threshold value for the edge indicator function in the level set method to each true positive (TP) and false positive (FP) region, we constructed the ANN. The ANN could provide the suitable threshold value for each candidate region in the proposed level set method so that TP regions can be segmented and FP regions can be removed. Our proposed method detected MS regions at a sensitivity of 82.1% with 0.204 FPs per slice and similarity index of MS candidate regions was 0.717 on average. (author)
Hansen, Mary A.; Lyon, Steven R.; Heh, Peter; Zigmond, Naomi
2013-01-01
Large-scale assessment programs, including alternate assessments based on alternate achievement standards (AA-AAS), must provide evidence of technical quality and validity. This study provides information about the technical quality of one AA-AAS by evaluating the standard setting for the science component. The assessment was designed to have…
International Nuclear Information System (INIS)
Cieri, D.
2016-01-01
At the HL-LHC, proton bunches collide every 25 ns, producing an average of 140 pp interactions per bunch crossing. To operate in such an environment, the CMS experiment will need a Level-1 (L1) hardware trigger, able to identify interesting events within a latency of 12.5 μs. This novel L1 trigger will make use of data coming from the silicon tracker to constrain the trigger rate . Goal of this new track trigger will be to build L1 tracks from the tracker information. The architecture that will be implemented in future to process tracker data is still under discussion. One possibility is to adopt a system entirely based on FPGA electronic. The proposed track finding algorithm is based on the Hough transform method. The algorithm has been tested using simulated pp collision data and it is currently being demonstrated in hardware, using the “MP7”, which is a μTCA board with a powerful FPGA capable of handling data rates approaching 1 Tb/s. Two different implementations of the Hough transform technique are currently under investigation: one utilizes a systolic array to represent the Hough space, while the other exploits a pipelined approach. (paper)
AUTHOR|(CDS)2090481
2016-01-01
At the HL-LHC, proton bunches collide every 25\\,ns, producing an average of 140 pp interactions per bunch crossing. To operate in such an environment, the CMS experiment will need a Level-1 (L1) hardware trigger, able to identify interesting events within a latency of 12.5\\,$\\mu$s. This novel L1 trigger will make use of data coming from the silicon tracker to constrain the trigger rate. Goal of this new \\textit{track trigger} will be to build L1 tracks from the tracker information. The architecture that will be implemented in future to process tracker data is still under discussion. One possibility is to adopt a system entirely based on FPGA electronic. The proposed track finding algorithm is based on the Hough transform method. The algorithm has been tested using simulated pp collision data and it is currently being demonstrated in hardware, using the ``MP7'', which is a $\\mu$TCA board with a powerful FPGA capable of handling data rates approaching 1 Tb/s. Two different implementations of the Hough tran...
Kim, Ji-Su; Park, Jung-Hyeon; Lee, Dong-Ho
2017-10-01
This study addresses a variant of job-shop scheduling in which jobs are grouped into job families, but they are processed individually. The problem can be found in various industrial systems, especially in reprocessing shops of remanufacturing systems. If the reprocessing shop is a job-shop type and has the component-matching requirements, it can be regarded as a job shop with job families since the components of a product constitute a job family. In particular, sequence-dependent set-ups in which set-up time depends on the job just completed and the next job to be processed are also considered. The objective is to minimize the total family flow time, i.e. the maximum among the completion times of the jobs within a job family. A mixed-integer programming model is developed and two iterated greedy algorithms with different local search methods are proposed. Computational experiments were conducted on modified benchmark instances and the results are reported.
International Nuclear Information System (INIS)
Slopsema, R. L.; Flampouri, S.; Yeung, D.; Li, Z.; Lin, L.; McDonough, J. E.; Palta, J.
2014-01-01
Purpose: The purpose of this investigation is to determine if a single set of beam data, described by a minimal set of equations and fitting variables, can be used to commission different installations of a proton double-scattering system in a commercial pencil-beam dose calculation algorithm. Methods: The beam model parameters required to commission the pencil-beam dose calculation algorithm (virtual and effective SAD, effective source size, and pristine-peak energy spread) are determined for a commercial double-scattering system. These parameters are measured in a first room and parameterized as function of proton energy and nozzle settings by fitting four analytical equations to the measured data. The combination of these equations and fitting values constitutes the golden beam data (GBD). To determine the variation in dose delivery between installations, the same dosimetric properties are measured in two additional rooms at the same facility, as well as in a single room at another facility. The difference between the room-specific measurements and the GBD is evaluated against tolerances that guarantee the 3D dose distribution in each of the rooms matches the GBD-based dose distribution within clinically reasonable limits. The pencil-beam treatment-planning algorithm is commissioned with the GBD. The three-dimensional dose distribution in water is evaluated in the four treatment rooms and compared to the treatment-planning calculated dose distribution. Results: The virtual and effective SAD measurements fall between 226 and 257 cm. The effective source size varies between 2.4 and 6.2 cm for the large-field options, and 1.0 and 2.0 cm for the small-field options. The pristine-peak energy spread decreases from 1.05% at the lowest range to 0.6% at the highest. The virtual SAD as well as the effective source size can be accurately described by a linear relationship as function of the inverse of the residual energy. An additional linear correction term as function of
Energy Technology Data Exchange (ETDEWEB)
Slopsema, R. L., E-mail: rslopsema@floridaproton.org; Flampouri, S.; Yeung, D.; Li, Z. [University of Florida Proton Therapy Institute, 2015 North Jefferson Street, Jacksonville, Florida 32205 (United States); Lin, L.; McDonough, J. E. [Department of Radiation Oncology, University of Pennsylvania, 3400 Civic Boulevard, 2326W TRC, PCAM, Philadelphia, Pennsylvania 19104 (United States); Palta, J. [VCU Massey Cancer Center, Virginia Commonwealth University, 401 College Street, Richmond, Virginia 23298 (United States)
2014-09-15
Purpose: The purpose of this investigation is to determine if a single set of beam data, described by a minimal set of equations and fitting variables, can be used to commission different installations of a proton double-scattering system in a commercial pencil-beam dose calculation algorithm. Methods: The beam model parameters required to commission the pencil-beam dose calculation algorithm (virtual and effective SAD, effective source size, and pristine-peak energy spread) are determined for a commercial double-scattering system. These parameters are measured in a first room and parameterized as function of proton energy and nozzle settings by fitting four analytical equations to the measured data. The combination of these equations and fitting values constitutes the golden beam data (GBD). To determine the variation in dose delivery between installations, the same dosimetric properties are measured in two additional rooms at the same facility, as well as in a single room at another facility. The difference between the room-specific measurements and the GBD is evaluated against tolerances that guarantee the 3D dose distribution in each of the rooms matches the GBD-based dose distribution within clinically reasonable limits. The pencil-beam treatment-planning algorithm is commissioned with the GBD. The three-dimensional dose distribution in water is evaluated in the four treatment rooms and compared to the treatment-planning calculated dose distribution. Results: The virtual and effective SAD measurements fall between 226 and 257 cm. The effective source size varies between 2.4 and 6.2 cm for the large-field options, and 1.0 and 2.0 cm for the small-field options. The pristine-peak energy spread decreases from 1.05% at the lowest range to 0.6% at the highest. The virtual SAD as well as the effective source size can be accurately described by a linear relationship as function of the inverse of the residual energy. An additional linear correction term as function of
Stoetzer, Ulrich; Bergman, Peter; Aborg, Carl; Johansson, Gun; Ahlberg, Gunnel; Parmsund, Marianne; Svartengren, Magnus
2014-01-01
The aim of this qualitative study was to identify manageable organizational factors that could explain why some companies have low levels of sickness absence. There may be factors at company level that can be managed to influence levels of sickness absence, and promote health and a prosperous organization. 38 representative Swedish companies. The study included a total of 204 semi-structured interviews at 38 representative Swedish companies. Qualitative thematic analysis was applied to the interviews, primarily with managers, to indicate the organizational factors that characterize companies with low levels of sickness absence. The factors that were found to characterize companies with low levels of sickness absence concerned strategies and procedures for managing leadership, employee development, communication, employee participation and involvement, corporate values and visions, and employee health. The results may be useful in finding strategies and procedures to reduce levels of sickness absence and promote health. There is research at individual level on the reasons for sickness absence. This study tries to elevate the issue to an organizational level. The findings suggest that explicit strategies for managing certain organizational factors can reduce sickness absence and help companies to develop more health-promoting strategies.
Directory of Open Access Journals (Sweden)
Georgii N. Lebedev
2017-01-01
Full Text Available The improvement in the effectiveness of airfield operation largely depends on the problem solving quality on the interaction boundaries of different technological sections. One of such hotspots is the use of the same runway by inbound and outbound aircraft. At certain intensity of outbound and inbound air traffic flow the conflict of aircraft interests appears, where it may be quite difficult to sort out priorities even for experienced controllers, in consequence of which mistakes in decision-making unavoidably appear.In this work the task of response correction of landing and takeoff time of the aircraft using the same RW, in condition of the conflict of interests “arrival – departure” at the increased operating intensity is formulated. The choice of optimal solution is made taking into account mutual interests without the complete sorting and the evaluation of all solutions.Accordingly, the genetic algorithm, which offers a simple and effective approach to optimal control problem solution by providing flight safety at an acceptably high level, is proposed. The estimation of additional aviation fuel consumption is used as optimal choice evaluation criterion.The advantages of the genetic algorithm application at decision-making in comparison with today’s “team” solution of the conflict “departure – arrival” in the airfield area are shown.
A cascadic monotonic time-discretized algorithm for finite-level quantum control computation
Ditz, P.; Borzi`, A.
2008-03-01
A computer package (CNMS) is presented aimed at the solution of finite-level quantum optimal control problems. This package is based on a recently developed computational strategy known as monotonic schemes. Quantum optimal control problems arise in particular in quantum optics where the optimization of a control representing laser pulses is required. The purpose of the external control field is to channel the system's wavefunction between given states in its most efficient way. Physically motivated constraints, such as limited laser resources, are accommodated through appropriately chosen cost functionals. Program summaryProgram title: CNMS Catalogue identifier: ADEB_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADEB_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 770 No. of bytes in distributed program, including test data, etc.: 7098 Distribution format: tar.gz Programming language: MATLAB 6 Computer: AMD Athlon 64 × 2 Dual, 2:21 GHz, 1:5 GB RAM Operating system: Microsoft Windows XP Word size: 32 Classification: 4.9 Nature of problem: Quantum control Solution method: Iterative Running time: 60-600 sec
Cai, Wenli; Yoshida, Hiroyuki; Harris, Gordon J.
2007-03-01
Measurement of the volume of focal liver tumors, called liver tumor volumetry, is indispensable for assessing the growth of tumors and for monitoring the response of tumors to oncology treatments. Traditional edge models, such as the maximum gradient and zero-crossing methods, often fail to detect the accurate boundary of a fuzzy object such as a liver tumor. As a result, the computerized volumetry based on these edge models tends to differ from manual segmentation results performed by physicians. In this study, we developed a novel computerized volumetry method for fuzzy objects, called dynamic-thresholding level set (DT level set). An optimal threshold value computed from a histogram tends to shift, relative to the theoretical threshold value obtained from a normal distribution model, toward a smaller region in the histogram. We thus designed a mobile shell structure, called a propagating shell, which is a thick region encompassing the level set front. The optimal threshold calculated from the histogram of the shell drives the level set front toward the boundary of a liver tumor. When the volume ratio between the object and the background in the shell approaches one, the optimal threshold value best fits the theoretical threshold value and the shell stops propagating. Application of the DT level set to 26 hepatic CT cases with 63 biopsy-confirmed hepatocellular carcinomas (HCCs) and metastases showed that the computer measured volumes were highly correlated with those of tumors measured manually by physicians. Our preliminary results showed that DT level set was effective and accurate in estimating the volumes of liver tumors detected in hepatic CT images.
Soltanipour, Asieh; Sadri, Saeed; Rabbani, Hossein; Akhlaghi, Mohammad Reza
2015-01-01
This paper presents a new procedure for automatic extraction of the blood vessels and optic disk (OD) in fundus fluorescein angiogram (FFA). In order to extract blood vessel centerlines, the algorithm of vessel extraction starts with the analysis of directional images resulting from sub-bands of fast discrete curvelet transform (FDCT) in the similar directions and different scales. For this purpose, each directional image is processed by using information of the first order derivative and eigenvalues obtained from the Hessian matrix. The final vessel segmentation is obtained using a simple region growing algorithm iteratively, which merges centerline images with the contents of images resulting from modified top-hat transform followed by bit plane slicing. After extracting blood vessels from FFA image, candidates regions for OD are enhanced by removing blood vessels from the FFA image, using multi-structure elements morphology, and modification of FDCT coefficients. Then, canny edge detector and Hough transform are applied to the reconstructed image to extract the boundary of candidate regions. At the next step, the information of the main arc of the retinal vessels surrounding the OD region is used to extract the actual location of the OD. Finally, the OD boundary is detected by applying distance regularized level set evolution. The proposed method was tested on the FFA images from angiography unit of Isfahan Feiz Hospital, containing 70 FFA images from different diabetic retinopathy stages. The experimental results show the accuracy more than 93% for vessel segmentation and more than 87% for OD boundary extraction.
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Abdu Kisekka Musubire
2017-12-01
Full Text Available BackgroundNon-traumatic myelopathy is common in Africa and there are geographic differences in etiology. Clinical management is challenging due to the broad differential diagnosis and the lack of diagnostics. The objective of this systematic review is to determine the most common etiologies of non-traumatic myelopathy in sub-Saharan Africa to inform a regionally appropriate diagnostic algorithm.MethodsWe conducted a systemic review searching Medline and Embase databases using the following search terms: “Non traumatic spinal cord injury” or “myelopathy” with limitations to epidemiology or etiologies and Sub-Saharan Africa. We described the frequencies of the different etiologies and proposed a diagnostic algorithm based on the most common diagnoses.ResultsWe identified 19 studies all performed at tertiary institutions; 15 were retrospective and 13 were published in the era of the HIV epidemic. Compressive bone lesions accounted for more than 48% of the cases; a majority were Pott’s disease and metastatic disease. No diagnosis was identified in up to 30% of cases in most studies; in particular, definitive diagnoses of non-compressive lesions were rare and a majority were clinical diagnoses of transverse myelitis and HIV myelopathy. Age and HIV were major determinants of etiology.ConclusionCompressive myelopathies represent a majority of non-traumatic myelopathies in sub-Saharan Africa, and most were due to Pott’s disease. Non-compressive myelopathies have not been well defined and need further research in Africa. We recommend a standardized approach to management of non-traumatic myelopathy focused on identifying treatable conditions with tests widely available in low-resource settings.
International Nuclear Information System (INIS)
De Cezaro, A; Leitão, A; Tai, X-C
2013-01-01
We investigate level-set-type methods for solving ill-posed problems with discontinuous (piecewise constant) coefficients. The goal is to identify the level sets as well as the level values of an unknown parameter function on a model described by a nonlinear ill-posed operator equation. The PCLS approach is used here to parametrize the solution of a given operator equation in terms of a L 2 level-set function, i.e. the level-set function itself is assumed to be a piecewise constant function. Two distinct methods are proposed for computing stable solutions of the resulting ill-posed problem: the first is based on Tikhonov regularization, while the second is based on the augmented Lagrangian approach with total variation penalization. Classical regularization results (Engl H W et al 1996 Mathematics and its Applications (Dordrecht: Kluwer)) are derived for the Tikhonov method. On the other hand, for the augmented Lagrangian method, we succeed in proving the existence of (generalized) Lagrangian multipliers in the sense of (Rockafellar R T and Wets R J-B 1998 Grundlehren der Mathematischen Wissenschaften (Berlin: Springer)). Numerical experiments are performed for a 2D inverse potential problem (Hettlich F and Rundell W 1996 Inverse Problems 12 251–66), demonstrating the capabilities of both methods for solving this ill-posed problem in a stable way (complicated inclusions are recovered without any a priori geometrical information on the unknown parameter). (paper)
Area-level risk factors for adverse birth outcomes: trends in urban and rural settings
Kent, Shia T; McClure, Leslie A; Zaitchik, Ben F; Gohlke, Julia M
2013-01-01
Background Significant and persistent racial and income disparities in birth outcomes exist in the US. The analyses in this manuscript examine whether adverse birth outcome time trends and associations between area-level variables and adverse birth outcomes differ by urban?rural status. Methods Alabama births records were merged with ZIP code-level census measures of race, poverty, and rurality. B-splines were used to determine long-term preterm birth (PTB) and low birth weight (LBW) trends b...
Directory of Open Access Journals (Sweden)
Z. Qorbali
2013-12-01
.Conclusion: as a result of establishing the presented method, identical levels in conventional risk graph table are replaced with different sublevels that not only increases the accuracy in determining the SIL, but also elucidates the effective factor in improving the safety level and consequently saves time and cost significantly. The proposed technique has been employed to develop the SIL of Tehran Refinery ISOMAX Center. IRG and FIRG results have been compared to clarify the efficacy and importance of the proposed method
On the Level Set of a Function with Degenerate Minimum Point
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Yasuhiko Kamiyama
2015-01-01
Full Text Available For n≥2, let M be an n-dimensional smooth closed manifold and f:M→R a smooth function. We set minf(M=m and assume that m is attained by unique point p∈M such that p is a nondegenerate critical point. Then the Morse lemma tells us that if a is slightly bigger than m, f-1(a is diffeomorphic to Sn-1. In this paper, we relax the condition on p from being nondegenerate to being an isolated critical point and obtain the same consequence. Some application to the topology of polygon spaces is also included.
CUDA based Level Set Method for 3D Reconstruction of Fishes from Large Acoustic Data
DEFF Research Database (Denmark)
Sharma, Ojaswa; Anton, François
2009-01-01
Acoustic images present views of underwater dynamics, even in high depths. With multi-beam echo sounders (SONARs), it is possible to capture series of 2D high resolution acoustic images. 3D reconstruction of the water column and subsequent estimation of fish abundance and fish species identificat...... of suppressing threshold and show its convergence as the evolution proceeds. We also present a GPU based streaming computation of the method using NVIDIA's CUDA framework to handle large volume data-sets. Our implementation is optimised for memory usage to handle large volumes....
Energy Technology Data Exchange (ETDEWEB)
Fiorucci, I.; Muscari, G. [Istituto Nazionale di Geofisica e Vulcanologia, Rome (Italy); De Zafra, R.L. [State Univ. of New York, Stony Brook, NY (United States). Dept. of Physics and Astronomy
2011-07-01
The Ground-Based Millimeter-wave Spectrometer (GBMS) was designed and built at the State University of New York at Stony Brook in the early 1990s and since then has carried out many measurement campaigns of stratospheric O{sub 3}, HNO{sub 3}, CO and N{sub 2}O at polar and mid-latitudes. Its HNO{sub 3} data set shed light on HNO{sub 3} annual cycles over the Antarctic continent and contributed to the validation of both generations of the satellite-based JPL Microwave Limb Sounder (MLS). Following the increasing need for long-term data sets of stratospheric constituents, we resolved to establish a long-term GMBS observation site at the Arctic station of Thule (76.5 N, 68.8 W), Greenland, beginning in January 2009, in order to track the long- and short-term interactions between the changing climate and the seasonal processes tied to the ozone depletion phenomenon. Furthermore, we updated the retrieval algorithm adapting the Optimal Estimation (OE) method to GBMS spectral data in order to conform to the standard of the Network for the Detection of Atmospheric Composition Change (NDACC) microwave group, and to provide our retrievals with a set of averaging kernels that allow more straightforward comparisons with other data sets. The new OE algorithm was applied to GBMS HNO{sub 3} data sets from 1993 South Pole observations to date, in order to produce HNO{sub 3} version 2 (v2) profiles. A sample of results obtained at Antarctic latitudes in fall and winter and at mid-latitudes is shown here. In most conditions, v2 inversions show a sensitivity (i.e., sum of column elements of the averaging kernel matrix) of 100{+-}20% from 20 to 45 km altitude, with somewhat worse (better) sensitivity in the Antarctic winter lower (upper) stratosphere. The 1{sigma} uncertainty on HNO{sub 3} v2 mixing ratio vertical profiles depends on altitude and is estimated at {proportional_to}15% or 0.3 ppbv, whichever is larger. Comparisons of v2 with former (v1) GBMS HNO{sub 3} vertical profiles
Wave energy level and geographic setting correlate with Florida beach water quality.
Feng, Zhixuan; Reniers, Ad; Haus, Brian K; Solo-Gabriele, Helena M; Kelly, Elizabeth A
2016-03-15
Many recreational beaches suffer from elevated levels of microorganisms, resulting in beach advisories and closures due to lack of compliance with Environmental Protection Agency guidelines. We conducted the first statewide beach water quality assessment by analyzing decadal records of fecal indicator bacteria (enterococci and fecal coliform) levels at 262 Florida beaches. The objectives were to depict synoptic patterns of beach water quality exceedance along the entire Florida shoreline and to evaluate their relationships with wave condition and geographic location. Percent exceedances based on enterococci and fecal coliform were negatively correlated with both long-term mean wave energy and beach slope. Also, Gulf of Mexico beaches exceeded the thresholds significantly more than Atlantic Ocean ones, perhaps partially due to the lower wave energy. A possible linkage between wave energy level and water quality is beach sand, a pervasive nonpoint source that tends to harbor more bacteria in the low-wave-energy environment. Copyright © 2016 Elsevier Ltd. All rights reserved.
Area-level risk factors for adverse birth outcomes: trends in urban and rural settings.
Kent, Shia T; McClure, Leslie A; Zaitchik, Ben F; Gohlke, Julia M
2013-06-10
Significant and persistent racial and income disparities in birth outcomes exist in the US. The analyses in this manuscript examine whether adverse birth outcome time trends and associations between area-level variables and adverse birth outcomes differ by urban-rural status. Alabama births records were merged with ZIP code-level census measures of race, poverty, and rurality. B-splines were used to determine long-term preterm birth (PTB) and low birth weight (LBW) trends by rurality. Logistic regression models were used to examine differences in the relationships between ZIP code-level percent poverty or percent African-American with either PTB or LBW. Interactions with rurality were examined. Population dense areas had higher adverse birth outcome rates compared to other regions. For LBW, the disparity between population dense and other regions increased during the 1991-2005 time period, and the magnitude of the disparity was maintained through 2010. Overall PTB and LBW rates have decreased since 2006, except within isolated rural regions. The addition of individual-level socioeconomic or race risk factors greatly attenuated these geographical disparities, but isolated rural regions maintained increased odds of adverse birth outcomes. ZIP code-level percent poverty and percent African American both had significant relationships with adverse birth outcomes. Poverty associations remained significant in the most population-dense regions when models were adjusted for individual-level risk factors. Population dense urban areas have heightened rates of adverse birth outcomes. High-poverty African American areas have higher odds of adverse birth outcomes in urban versus rural regions. These results suggest there are urban-specific social or environmental factors increasing risk for adverse birth outcomes in underserved communities. On the other hand, trends in PTBs and LBWs suggest interventions that have decreased adverse birth outcomes elsewhere may not be reaching
County-Level Poverty Is Equally Associated with Unmet Health Care Needs in Rural and Urban Settings
Peterson, Lars E.; Litaker, David G.
2010-01-01
Context: Regional poverty is associated with reduced access to health care. Whether this relationship is equally strong in both rural and urban settings or is affected by the contextual and individual-level characteristics that distinguish these areas, is unclear. Purpose: Compare the association between regional poverty with self-reported unmet…
Edwards, Todd M.; Patterson, Jo Ellen
2012-01-01
The Day Reconstruction Method (DRM) was used to assess the daily events and emotions of one program's master's-level family therapy trainees in off-campus practicum settings. This study examines the DRM reports of 35 family therapy trainees in the second year of their master's program in marriage and family therapy. Four themes emerged from the…
Gerrit Willem Ziggers; Kristina Manser; Bas Hillebrand; Paul Driessen; Josée Bloemer
2014-01-01
Complex innovations involve multi-organizational ecologies consisting of a myriad of different actors. This study investigates how innovation activities can be interpreted in the context of multi-organizational ecologies. Taking a project-level perspective, this study proposes a typology of four
Supporting Diverse Young Adolescents: Cooperative Grouping in Inclusive Middle-Level Settings
Miller, Nicole C.; McKissick, Bethany R.; Ivy, Jessica T.; Moser, Kelly
2017-01-01
The middle level classroom presents unique challenges to educators who strive to provide opportunities that acknowledge learner diversity in terms of social, cognitive, physical, and emotional development. This is confounded even further within inclusive middle-school classrooms where the responsibility to differentiate instruction is even more…
Directory of Open Access Journals (Sweden)
Chuanfa Chen
2015-03-01
Full Text Available Remote-sensing-derived elevation data sets often suffer from noise and outliers due to various reasons, such as the physical limitations of sensors, multiple reflectance, occlusions and low contrast of texture. Outliers generally have a seriously negative effect on DEM construction. Some interpolation methods like ordinary kriging (OK are capable of smoothing noise inherent in sample points, but are sensitive to outliers. In this paper, a robust algorithm of multiquadric method (MQ based on an Improved Huber loss function (MQ-IH has been developed to decrease the impact of outliers on DEM construction. Theoretically, the improved Huber loss function is null for outliers, quadratic for small errors, and linear for others. Simulated data sets drawn from a mathematical surface with different error distributions were employed to analyze the robustness of MQ-IH. Results indicate that MQ-IH obtains a good balance between efficiency and robustness. Namely, the performance of MQ-IH is comparative to those of the classical MQ and MQ based on the Classical Huber loss function (MQ-CH when sample points follow a normal distribution, and the former outperforms the latter two when sample points are subject to outliers. For example, for the Cauchy error distribution with the location parameter of 0 and scale parameter of 1, the root mean square errors (RMSEs of MQ-CH and the classical MQ are 0.3916 and 1.4591, respectively, whereas that of MQ-IH is 0.3698. The performance of MQ-IH is further evaluated by qualitative and quantitative analysis through a real-world example of DEM construction with the stereo-images-derived elevation points. Results demonstrate that compared with the classical interpolation methods, including natural neighbor (NN, OK and ANUDEM (a program that calculates regular grid digital elevation models (DEMs with sensible shape and drainage structure from arbitrarily large topographic data sets, and two versions of MQ, including the
Funama, Yoshinori; Utsunomiya, Daisuke; Taguchi, Katsuyuki; Oda, Seitaro; Shimonobo, Toshiaki; Yamashita, Yasuyuki
2014-05-01
To investigate whether electrocardiogram (ECG)-gated single- and dual-heartbeat computed tomography coronary angiography (CTCA) with automatic exposure control (AEC) yields images with uniform image noise at reduced radiation doses. Using an anthropomorphic chest CT phantom we performed prospectively ECG-gated single- and dual-heartbeat CTCA on a second-generation 320-multidetector CT volume scanner. The exposure phase window was set at 75%, 70-80%, 40-80%, and 0-100% and the heart rate at 60 or 80 or corr80 bpm; images were reconstructed with filtered back projection (FBP) or iterative reconstruction (IR, adaptive iterative dose reduction 3D). We applied AEC and set the image noise level to 20 or 25 HU. For each technique we determined the image noise and the radiation dose to the phantom center. With half-scan reconstruction at 60 bpm, a 70-80% phase window- and a 20-HU standard deviation (SD) setting, the imagenoise level and -variation along the z axis manifested similar curves with FBP and IR. With half-scan reconstruction, the radiation dose to the phantom center with 70-80% phase window was 18.89 and 12.34 mGy for FBP and 4.61 and 3.10 mGy for IR at an SD setting SD of 20 and 25 HU, respectively. At 80 bpm with two-segment reconstruction the dose was approximately twice that of 60 bpm at both SD settings. However, increasing radiation dose at corr80 bpm was suppressed to 1.39 times compared to 60 bpm. AEC at ECG-gated single- and dual-heartbeat CTCA controls the image noise at different radiation dose. Copyright © 2013 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.
Moraros, John; Islam, Adiba; Yu, Stan; Banow, Ryan; Schindelka, Barbara
2015-01-01
Background Flipped Classroom is a model that?s quickly gaining recognition as a novel teaching approach among health science curricula. The purpose of this study was four-fold and aimed to compare Flipped Classroom effectiveness ratings with: 1) student socio-demographic characteristics, 2) student final grades, 3) student overall course satisfaction, and 4) course pre-Flipped Classroom effectiveness ratings. Methods The participants in the study consisted of 67 Masters-level graduate student...
Hou, Tingjun; Xu, Xiaojie
2002-12-01
In this study, the relationships between the brain-blood concentration ratio of 96 structurally diverse compounds with a large number of structurally derived descriptors were investigated. The linear models were based on molecular descriptors that can be calculated for any compound simply from a knowledge of its molecular structure. The linear correlation coefficients of the models were optimized by genetic algorithms (GAs), and the descriptors used in the linear models were automatically selected from 27 structurally derived descriptors. The GA optimizations resulted in a group of linear models with three or four molecular descriptors with good statistical significance. The change of descriptor use as the evolution proceeds demonstrates that the octane/water partition coefficient and the partial negative solvent-accessible surface area multiplied by the negative charge are crucial to brain-blood barrier permeability. Moreover, we found that the predictions using multiple QSPR models from GA optimization gave quite good results in spite of the diversity of structures, which was better than the predictions using the best single model. The predictions for the two external sets with 37 diverse compounds using multiple QSPR models indicate that the best linear models with four descriptors are sufficiently effective for predictive use. Considering the ease of computation of the descriptors, the linear models may be used as general utilities to screen the blood-brain barrier partitioning of drugs in a high-throughput fashion.
A quantum causal discovery algorithm
Giarmatzi, Christina; Costa, Fabio
2018-03-01
Finding a causal model for a set of classical variables is now a well-established task—but what about the quantum equivalent? Even the notion of a quantum causal model is controversial. Here, we present a causal discovery algorithm for quantum systems. The input to the algorithm is a process matrix describing correlations between quantum events. Its output consists of different levels of information about the underlying causal model. Our algorithm determines whether the process is causally ordered by grouping the events into causally ordered non-signaling sets. It detects if all relevant common causes are included in the process, which we label Markovian, or alternatively if some causal relations are mediated through some external memory. For a Markovian process, it outputs a causal model, namely the causal relations and the corresponding mechanisms, represented as quantum states and channels. Our algorithm opens the route to more general quantum causal discovery methods.
Directory of Open Access Journals (Sweden)
Henry Mbah
Full Text Available The surge of donor funds to fight HIV&AIDS epidemic inadvertently resulted in the setup of laboratories as parallel structures to rapidly respond to the identified need. However these parallel structures are a threat to the existing fragile laboratory systems. Laboratory service integration is critical to remedy this situation. This paper describes an approach to quantitatively measure and track integration of HIV-related laboratory services into the mainstream laboratory services and highlight some key intervention steps taken, to enhance service integration.A quantitative before-and-after study conducted in 122 Family Health International (FHI360 supported health facilities across Nigeria. A minimum service package was identified including management structure; trainings; equipment utilization and maintenance; information, commodity and quality management for laboratory integration. A check list was used to assess facilities at baseline and 3 months follow-up. Level of integration was assessed on an ordinal scale (0 = no integration, 1 = partial integration, 2 = full integration for each service package. A composite score grading expressed as a percentage of total obtainable score of 14 was defined and used to classify facilities (≤ 80% FULL, 25% to 79% PARTIAL and <25% NO integration. Weaknesses were noted and addressed.We analyzed 9 (7.4% primary, 104 (85.2% secondary and 9 (7.4% tertiary level facilities. There were statistically significant differences in integration levels between baseline and 3 months follow-up period (p<0.01. Baseline median total integration score was 4 (IQR 3 to 5 compared to 7 (IQR 4 to 9 at 3 months follow-up (p = 0.000. Partial and fully integrated laboratory systems were 64 (52.5% and 0 (0.0% at baseline, compared to 100 (82.0% and 3 (2.4% respectively at 3 months follow-up (p = 0.000.This project showcases our novel approach to measure the status of each laboratory on the integration continuum.
Job satisfaction in nurses working in tertiary level health care settings of Islamabad, Pakistan.
Bahalkani, Habib Akhtar; Kumar, Ramesh; Lakho, Abdul Rehman; Mahar, Benazir; Mazhar, Syeda Batool; Majeed, Abdul
2011-01-01
Job satisfaction greatly determines the productivity and efficiency of human resource for health. It literally means: 'the extent to which Health Professionals like or dislike their jobs'. Job satisfaction is said to be linked with employee's work environment, job responsibilities, and powers; and time pressure among various health professionals. As such it affects employee's organizational commitment and consequently the quality of health services. Objective of this study was to determine the level of job satisfaction and factors influencing it among nurses in a public sector hospital of Islamabad. A cross sectional study with self-administered structured questionnaire was conducted in the federal capital of Pakistan, Islamabad. Sample included 56 qualified nurses working in a tertiary care hospital. Overall 86% respondents were dissatisfied with about 26% highly dissatisfied with their job. The work environments, poor fringe benefits, dignity, responsibility given at workplace and time pressure were reason for dissatisfaction. Poor work environment, low salaries, lack of training opportunities, proper supervision, time pressure and financial rewards reported by the respondents. Our findings state a low level of overall satisfaction among workers in a public sector tertiary care health organization in Islamabad. Most of this dissatisfaction is caused by poor salaries, not given the due respect, poor work environment, unbalanced responsibilities with little overall control, time pressure, patient care and lack of opportunities for professional development.
County-level poverty is equally associated with unmet health care needs in rural and urban settings.
Peterson, Lars E; Litaker, David G
2010-01-01
Regional poverty is associated with reduced access to health care. Whether this relationship is equally strong in both rural and urban settings or is affected by the contextual and individual-level characteristics that distinguish these areas, is unclear. Compare the association between regional poverty with self-reported unmet need, a marker of health care access, by rural/urban setting. Multilevel, cross-sectional analysis of a state-representative sample of 39,953 adults stratified by rural/urban status, linked at the county level to data describing contextual characteristics. Weighted random intercept models examined the independent association of regional poverty with unmet needs, controlling for a range of contextual and individual-level characteristics. The unadjusted association between regional poverty levels and unmet needs was similar in both rural (OR = 1.06 [95% CI, 1.04-1.08]) and urban (OR = 1.03 [1.02-1.05]) settings. Adjusting for other contextual characteristics increased the size of the association in both rural (OR = 1.11 [1.04-1.19]) and urban (OR = 1.11 [1.05-1.18]) settings. Further adjustment for individual characteristics had little additional effect in rural (OR = 1.10 [1.00-1.20]) or urban (OR = 1.11 [1.01-1.22]) settings. To better meet the health care needs of all Americans, health care systems in areas with high regional poverty should acknowledge the relationship between poverty and unmet health care needs. Investments, or other interventions, that reduce regional poverty may be useful strategies for improving health through better access to health care. © 2010 National Rural Health Association.
Jiryaee, Nasrin; Siadat, Zahra Dana; Zamani, Ahmadreza; Taleban, Roya
2015-10-01
Designing an intervention to increase physical activity is important to be based on the health care settings resources and be acceptable by the subject group. This study was designed to assess and compare the effect of the goal setting strategy with a group education method on increasing the physical activity of mothers of children aged 1 to 5. Mothers who had at least one child of 1-5 years were randomized into two groups. The effect of 1) goal-setting strategy and 2) group education method on increasing physical activity was assessed and compared 1 month and 3 months after the intervention. Also, the weight, height, body mass index (BMI), waist and hip circumference, and well-being were compared between the two groups before and after the intervention. Physical activity level increased significantly after the intervention in the goal-setting group and it was significantly different between the two groups after intervention (P goal-setting group after the intervention. In the group education method, only the well-being score improved significantly (P goal-setting strategy to boost physical activity, improving the state of well-being and decreasing BMI, waist, and hip circumference.
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Nasrin Jiryaee
2015-01-01
Full Text Available Background: Designing an intervention to increase physical activity is important to be based on the health care settings resources and be acceptable by the subject group. This study was designed to assess and compare the effect of the goal setting strategy with a group education method on increasing the physical activity of mothers of children aged 1 to 5. Materials and Methods: Mothers who had at least one child of 1-5 years were randomized into two groups. The effect of 1 goal-setting strategy and 2 group education method on increasing physical activity was assessed and compared 1 month and 3 months after the intervention. Also, the weight, height, body mass index (BMI, waist and hip circumference, and well-being were compared between the two groups before and after the intervention. Results: Physical activity level increased significantly after the intervention in the goal-setting group and it was significantly different between the two groups after intervention (P < 0.05. BMI, waist circumference, hip circumference, and well-being score were significantly different in the goal-setting group after the intervention. In the group education method, only the well-being score improved significantly (P < 0.05. Conclusion: Our study presented the effects of using the goal-setting strategy to boost physical activity, improving the state of well-being and decreasing BMI, waist, and hip circumference.
A possible methodological approach to setting up control level of radiation factors
International Nuclear Information System (INIS)
Devyatajkin, E.V.; Abramov, Yu.V.
1986-01-01
The mathematical formalization of the concept of control levels (CL) which enables one to obtain CL numerical values of controllable parameters required for rapid control purposes is described. The initial data for the assessment of environmental radioactivity are the controllable parameter values that is practical characteristic of controllable radiation factor showing technically measurable or calculation value. The controllable parameters can be divided into two classes depending on the degree of radiation effect on a man: possessing additivity properties (dosimetric class) and non-possessing (radiation class, which comprises the results of control of medium alteration dynamics, equipment operation safety, completeness of protection measures performance). The CL calculation formulas with account for requirements of radiation safety standards (RSS-76) are presented
High Levels of Post-Abortion Complication in a Setting Where Abortion Service Is Not Legalized
Melese, Tadele; Habte, Dereje; Tsima, Billy M.; Mogobe, Keitshokile Dintle; Chabaesele, Kesegofetse; Rankgoane, Goabaone; Keakabetse, Tshiamo R.; Masweu, Mabole; Mokotedi, Mosidi; Motana, Mpho; Moreri-Ntshabele, Badani
2017-01-01
Background Maternal mortality due to abortion complications stands among the three leading causes of maternal death in Botswana where there is a restrictive abortion law. This study aimed at assessing the patterns and determinants of post-abortion complications. Methods A retrospective institution based cross-sectional study was conducted at four hospitals from January to August 2014. Data were extracted from patients’ records with regards to their socio-demographic variables, abortion complications and length of hospital stay. Descriptive statistics and bivariate analysis were employed. Result A total of 619 patients’ records were reviewed with a mean (SD) age of 27.12 (5.97) years. The majority of abortions (95.5%) were reported to be spontaneous and 3.9% of the abortions were induced by the patient. Two thirds of the patients were admitted as their first visit to the hospitals and one third were referrals from other health facilities. Two thirds of the patients were admitted as a result of incomplete abortion followed by inevitable abortion (16.8%). Offensive vaginal discharge (17.9%), tender uterus (11.3%), septic shock (3.9%) and pelvic peritonitis (2.4%) were among the physical findings recorded on admission. Clinically detectable anaemia evidenced by pallor was found to be the leading major complication in 193 (31.2%) of the cases followed by hypovolemic and septic shock 65 (10.5%). There were a total of 9 abortion related deaths with a case fatality rate of 1.5%. Self-induced abortion and delayed uterine evacuation of more than six hours were found to have significant association with post-abortion complications (p-values of 0.018 and 0.035 respectively). Conclusion Abortion related complications and deaths are high in our setting where abortion is illegal. Mechanisms need to be devised in the health facilities to evacuate the uterus in good time whenever it is indicated and to be equipped to handle the fatal complications. There is an indication for
High Levels of Post-Abortion Complication in a Setting Where Abortion Service Is Not Legalized.
Directory of Open Access Journals (Sweden)
Tadele Melese
Full Text Available Maternal mortality due to abortion complications stands among the three leading causes of maternal death in Botswana where there is a restrictive abortion law. This study aimed at assessing the patterns and determinants of post-abortion complications.A retrospective institution based cross-sectional study was conducted at four hospitals from January to August 2014. Data were extracted from patients' records with regards to their socio-demographic variables, abortion complications and length of hospital stay. Descriptive statistics and bivariate analysis were employed.A total of 619 patients' records were reviewed with a mean (SD age of 27.12 (5.97 years. The majority of abortions (95.5% were reported to be spontaneous and 3.9% of the abortions were induced by the patient. Two thirds of the patients were admitted as their first visit to the hospitals and one third were referrals from other health facilities. Two thirds of the patients were admitted as a result of incomplete abortion followed by inevitable abortion (16.8%. Offensive vaginal discharge (17.9%, tender uterus (11.3%, septic shock (3.9% and pelvic peritonitis (2.4% were among the physical findings recorded on admission. Clinically detectable anaemia evidenced by pallor was found to be the leading major complication in 193 (31.2% of the cases followed by hypovolemic and septic shock 65 (10.5%. There were a total of 9 abortion related deaths with a case fatality rate of 1.5%. Self-induced abortion and delayed uterine evacuation of more than six hours were found to have significant association with post-abortion complications (p-values of 0.018 and 0.035 respectively.Abortion related complications and deaths are high in our setting where abortion is illegal. Mechanisms need to be devised in the health facilities to evacuate the uterus in good time whenever it is indicated and to be equipped to handle the fatal complications. There is an indication for clinical audit on post-abortion care
International Nuclear Information System (INIS)
Yumoto, Yasuhiro; Hanafusa, Tadashi; Nagamatsu, Tomohiro; Okada, Shigeru
1997-01-01
An incineration system was constructed which were composed of a combustion furnace (AP-150R), a cyclone dust collector, radioisotope trapping and measurement apparatus and a radioisotope storage room built in the first basement of the Radioisotope Center. Low level radioactive samples (LLRS) used for the combustion experiment were composed of combustible material or semi-combustible material containing 500 kBq of 99m TcO 4 or 23.25 kBq of 131 INa. The distribution of radioisotopes both in the inside and outside of combustion furnace were estimated. We measured radioactivity of a smoke duct gas in terminal exit of the exhaust port. In case of combustion of LLRS containing 99m TcO 4 or 131 INa, concentration of radioisotopes at the exhaust port showed less than legal concentration limit of these radioisotopes. In cases of combustion of LLRS containing 99m TcO 4 or 131 INa, decontamination factors of the incineration system were 120 and 1.1, respectively. (author)
Mbah, Henry; Negedu-Momoh, Olubunmi Ruth; Adedokun, Oluwasanmi; Ikani, Patrick Anibbe; Balogun, Oluseyi; Sanwo, Olusola; Ochei, Kingsley; Ekanem, Maurice; Torpey, Kwasi
2014-01-01
The surge of donor funds to fight HIV&AIDS epidemic inadvertently resulted in the setup of laboratories as parallel structures to rapidly respond to the identified need. However these parallel structures are a threat to the existing fragile laboratory systems. Laboratory service integration is critical to remedy this situation. This paper describes an approach to quantitatively measure and track integration of HIV-related laboratory services into the mainstream laboratory services and highlight some key intervention steps taken, to enhance service integration. A quantitative before-and-after study conducted in 122 Family Health International (FHI360) supported health facilities across Nigeria. A minimum service package was identified including management structure; trainings; equipment utilization and maintenance; information, commodity and quality management for laboratory integration. A check list was used to assess facilities at baseline and 3 months follow-up. Level of integration was assessed on an ordinal scale (0 = no integration, 1 = partial integration, 2 = full integration) for each service package. A composite score grading expressed as a percentage of total obtainable score of 14 was defined and used to classify facilities (≤ 80% FULL, 25% to 79% PARTIAL and laboratory systems were 64 (52.5%) and 0 (0.0%) at baseline, compared to 100 (82.0%) and 3 (2.4%) respectively at 3 months follow-up (p = 0.000). This project showcases our novel approach to measure the status of each laboratory on the integration continuum.
DEFF Research Database (Denmark)
Otomori, Masaki; Yamada, Takayuki; Izui, Kazuhiro
2012-01-01
This paper presents a level set-based topology optimization method for the design of negative permeability dielectric metamaterials. Metamaterials are artificial materials that display extraordinary physical properties that are unavailable with natural materials. The aim of the formulated...... optimization problem is to find optimized layouts of a dielectric material that achieve negative permeability. The presence of grayscale areas in the optimized configurations critically affects the performance of metamaterials, positively as well as negatively, but configurations that contain grayscale areas...... are highly impractical from an engineering and manufacturing point of view. Therefore, a topology optimization method that can obtain clear optimized configurations is desirable. Here, a level set-based topology optimization method incorporating a fictitious interface energy is applied to a negative...
Quasi-min-max Fuzzy MPC of UTSG Water Level Based on Off-Line Invariant Set
Liu, Xiangjie; Jiang, Di; Lee, Kwang Y.
2015-10-01
In a nuclear power plant, the water level of the U-tube steam generator (UTSG) must be maintained within a safe range. Traditional control methods encounter difficulties due to the complexity, strong nonlinearity and “swell and shrink” effects, especially at low power levels. A properly designed robust model predictive control can well solve this problem. In this paper, a quasi-min-max fuzzy model predictive controller is developed for controlling the constrained UTSG system. While the online computational burden could be quite large for the real-time control, a bank of ellipsoid invariant sets together with the corresponding feedback control laws are obtained by off-line solving linear matrix inequalities (LMIs). Based on the UTSG states, the online optimization is simplified as a constrained optimization problem with a bisection search for the corresponding ellipsoid invariant set. Simulation results are given to show the effectiveness of the proposed controller.
Balouchestani, Mohammadreza; Krishnan, Sridhar
2014-01-01
Long-term recording of Electrocardiogram (ECG) signals plays an important role in health care systems for diagnostic and treatment purposes of heart diseases. Clustering and classification of collecting data are essential parts for detecting concealed information of P-QRS-T waves in the long-term ECG recording. Currently used algorithms do have their share of drawbacks: 1) clustering and classification cannot be done in real time; 2) they suffer from huge energy consumption and load of sampling. These drawbacks motivated us in developing novel optimized clustering algorithm which could easily scan large ECG datasets for establishing low power long-term ECG recording. In this paper, we present an advanced K-means clustering algorithm based on Compressed Sensing (CS) theory as a random sampling procedure. Then, two dimensionality reduction methods: Principal Component Analysis (PCA) and Linear Correlation Coefficient (LCC) followed by sorting the data using the K-Nearest Neighbours (K-NN) and Probabilistic Neural Network (PNN) classifiers are applied to the proposed algorithm. We show our algorithm based on PCA features in combination with K-NN classifier shows better performance than other methods. The proposed algorithm outperforms existing algorithms by increasing 11% classification accuracy. In addition, the proposed algorithm illustrates classification accuracy for K-NN and PNN classifiers, and a Receiver Operating Characteristics (ROC) area of 99.98%, 99.83%, and 99.75% respectively.
CryoSat Level1b SAR/SARin BaselineC: Product Format and Algorithm Improvements
Scagliola, Michele; Fornari, Marco; Di Giacinto, Andrea; Bouffard, Jerome; Féménias, Pierre; Parrinello, Tommaso
2015-04-01
CryoSat was launched on the 8th April 2010 and is the first European ice mission dedicated to the monitoring of precise changes in the thickness of polar ice sheets and floating sea ice. Cryosat carries an innovative radar altimeter called the Synthetic Aperture Interferometric Altimeter (SIRAL), that transmits pulses at a high pulse repetition frequency thus making the received echoes phase coherent and suitable for azimuth processing. This allows to reach a significantly improved along track resolution with respect to traditional pulse-width limited altimeters. CryoSat is the first altimetry mission operating in SAR mode and continuous improvements in the Level1 Instrument Processing Facility (IPF1) are being identified, tested and validated in order to improve the quality of the Level1b products. The current IPF, Baseline B, was released in operation in February 2012. A reprocessing campaign followed, in order to reprocess the data since July 2010. After more than 2 years of development, the release in operations of Baseline C is expected in the first half of 2015. BaselineC Level1b products will be distributed in an updated format, including for example the attitude information (roll, pitch and yaw) and, for SAR/SARIN, the waveform length doubled with respect to Baseline B. Moreveor, various algorithm improvements have been identified: • a datation bias of about -0.5195 ms will be corrected (SAR/SARIn) • a range bias of about 0.6730 m will be corrected (SAR/SARIn) • a roll bias of 0.1062 deg and a pitch bias of 0.0520 deg • Surface sample stack weighting to filter out the single look echoes acquired at highest look angle, that results in a sharpening of the 20Hz waveforms With the operational release of BaselineC, the second CryoSat reprocessing campaign will be initiated, taking benefit of the upgrade implemented in the IPF1 processing chain but also at IPF2 level. The reprocessing campaign will cover the full Cryosat mission starting on 16th July 2010
Numerical simulation of interface movement in gas-liquid two-phase flows with Level Set method
International Nuclear Information System (INIS)
Li Huixiong; Chinese Academy of Sciences, Beijing; Deng Sheng; Chen Tingkuan; Zhao Jianfu; Wang Fei
2005-01-01
Numerical simulation of gas-liquid two-phase flow and heat transfer has been an attractive work for a quite long time, but still remains as a knotty difficulty due to the inherent complexities of the gas-liquid two-phase flow resulted from the existence of moving interfaces with topology changes. This paper reports the effort and the latest advances that have been made by the authors, with special emphasis on the methods for computing solutions to the advection equation of the Level set function, which is utilized to capture the moving interfaces in gas-liquid two-phase flows. Three different schemes, i.e. the simple finite difference scheme, the Superbee-TVD scheme and the 5-order WENO scheme in combination with the Runge-Kutta method are respectively applied to solve the advection equation of the Level Set. A numerical procedure based on the well-verified SIMPLER method is employed to numerically calculate the momentum equations of the two-phase flow. The above-mentioned three schemes are employed to simulate the movement of four typical interfaces under 5 typical flowing conditions. Analysis of the numerical results shows that the 5-order WENO scheme and the Superbee-TVD scheme are much better than the simple finite difference scheme, and the 5-order WENO scheme is the best to compute solutions to the advection equation of the Level Set. The 5-order WENO scheme will be employed as the main scheme to get solutions to the advection equations of the Level Set when gas-liquid two-phase flows are numerically studied in the future. (authors)
Directory of Open Access Journals (Sweden)
Brownson Ross C
2010-05-01
Full Text Available Abstract Background To achieve widespread cancer control, a better understanding is needed of the factors that contribute to successful implementation of effective skin cancer prevention interventions. This study assessed the relative contributions of individual- and setting-level characteristics to implementation of a widely disseminated skin cancer prevention program. Methods A multilevel analysis was conducted using data from the Pool Cool Diffusion Trial from 2004 and replicated with data from 2005. Implementation of Pool Cool by lifeguards was measured using a composite score (implementation variable, range 0 to 10 that assessed whether the lifeguard performed different components of the intervention. Predictors included lifeguard background characteristics, lifeguard sun protection-related attitudes and behaviors, pool characteristics, and enhanced (i.e., more technical assistance, tailored materials, and incentives are provided versus basic treatment group. Results The mean value of the implementation variable was 4 in both years (2004 and 2005; SD = 2 in 2004 and SD = 3 in 2005 indicating a moderate implementation for most lifeguards. Several individual-level (lifeguard characteristics and setting-level (pool characteristics and treatment group factors were found to be significantly associated with implementation of Pool Cool by lifeguards. All three lifeguard-level domains (lifeguard background characteristics, lifeguard sun protection-related attitudes and behaviors and six pool-level predictors (number of weekly pool visitors, intervention intensity, geographic latitude, pool location, sun safety and/or skin cancer prevention programs, and sun safety programs and policies were included in the final model. The most important predictors of implementation were the number of weekly pool visitors (inverse association and enhanced treatment group (positive association. That is, pools with fewer weekly visitors and pools in the enhanced
Kergadallan, Xavier; Bernardara, Pietro; Benoit, Michel; Andreewsky, Marc; Weiss, Jérôme
2013-04-01
Estimating the probability of occurrence of extreme sea levels is a central issue for the protection of the coast. Return periods of sea level with wave set-up contribution are estimated here in one site : Cherbourg in France in the English Channel. The methodology follows two steps : the first one is computation of joint probability of simultaneous wave height and still sea level, the second one is interpretation of that joint probabilities to assess a sea level for a given return period. Two different approaches were evaluated to compute joint probability of simultaneous wave height and still sea level : the first one is multivariate extreme values distributions of logistic type in which all components of the variables become large simultaneously, the second one is conditional approach for multivariate extreme values in which only one component of the variables have to be large. Two different methods were applied to estimate sea level with wave set-up contribution for a given return period : Monte-Carlo simulation in which estimation is more accurate but needs higher calculation time and classical ocean engineering design contours of type inverse-FORM in which the method is simpler and allows more complex estimation of wave setup part (wave propagation to the coast for example). We compare results from the two different approaches with the two different methods. To be able to use both Monte-Carlo simulation and design contours methods, wave setup is estimated with an simple empirical formula. We show advantages of the conditional approach compared to the multivariate extreme values approach when extreme sea-level occurs when either surge or wave height is large. We discuss the validity of the ocean engineering design contours method which is an alternative when computation of sea levels is too complex to use Monte-Carlo simulation method.
Directory of Open Access Journals (Sweden)
Prixia Nieto
2006-11-01
Full Text Available Two predictive models were developed within a geographic information system using Genetic Algorithm Rule-Set Prediction (GARP and the growing degree day (GDD-water budget (WB concept to predict the distribution and potential risk of visceral leishmaniasis (VL in the State of Bahia, Brazil. The objective was to define the environmental suitability of the disease as well as to obtain a deeper understanding of the eco-epidemiology of VL by associating environmental and climatic variables with disease prevalence. Both the GARP model and the GDDWB model, using different analysis approaches and with the same human prevalence database, predicted similar distribution and abundance patterns for the Lutzomyia longipalpis-Leishmania chagasi system in Bahia. High and moderate prevalence sites for VL were significantly related to areas of high and moderate risk prediction by: (i the area predicted by the GARP model, depending on the number of pixels that overlapped among eleven annual model years, and (ii the number of potential generations per year that could be completed by the Lu. longipalpis-L. chagasi system by GDD-WB analysis. When applied to the ecological zones of Bahia, both the GARP and the GDD-WB prediction models suggest that the highest VL risk is in the interior region of the state, characterized by a semi-arid and hot climate known as Caatinga, while the risk in the Bahia interior forest and the Cerrado ecological regions is lower. The Bahia coastal forest was predicted to be a low-risk area due to the unsuitable conditions for the vector and VL transmission.
Adaptive discrete-ordinates algorithms and strategies
International Nuclear Information System (INIS)
Stone, J.C.; Adams, M.L.
2005-01-01
We present our latest algorithms and strategies for adaptively refined discrete-ordinates quadrature sets. In our basic strategy, which we apply here in two-dimensional Cartesian geometry, the spatial domain is divided into regions. Each region has its own quadrature set, which is adapted to the region's angular flux. Our algorithms add a 'test' direction to the quadrature set if the angular flux calculated at that direction differs by more than a user-specified tolerance from the angular flux interpolated from other directions. Different algorithms have different prescriptions for the method of interpolation and/or choice of test directions and/or prescriptions for quadrature weights. We discuss three different algorithms of different interpolation orders. We demonstrate through numerical results that each algorithm is capable of generating solutions with negligible angular discretization error. This includes elimination of ray effects. We demonstrate that all of our algorithms achieve a given level of error with far fewer unknowns than does a standard quadrature set applied to an entire problem. To address a potential issue with other algorithms, we present one algorithm that retains exact integration of high-order spherical-harmonics functions, no matter how much local refinement takes place. To address another potential issue, we demonstrate that all of our methods conserve partial currents across interfaces where quadrature sets change. We conclude that our approach is extremely promising for solving the long-standing problem of angular discretization error in multidimensional transport problems. (authors)
Directory of Open Access Journals (Sweden)
Brown, Andrew
2014-08-01
Full Text Available This paper presents a prototype Stereolithography (STL file format slicing and tool-path generation algorithm, which serves as a data front-end for a Rapid Prototyping (RP entry- level three-dimensional (3-D printer. Used mainly in Additive Manufacturing (AM, 3-D printers are devices that apply plastic, ceramic, and metal, layer by layer, in all three dimensions on a flat surface (X, Y, and Z axis. 3-D printers, unfortunately, cannot print an object without a special algorithm that is required to create the Computer Numerical Control (CNC instructions for printing. An STL algorithm therefore forms a critical component for Layered Manufacturing (LM, also referred to as RP. The purpose of this study was to develop an algorithm that is capable of processing and slicing an STL file or multiple files, resulting in a tool-path, and finally compiling a CNC file for an entry-level 3- D printer. The prototype algorithm was implemented for an entry-level 3-D printer that utilises the Fused Deposition Modelling (FDM process or Solid Freeform Fabrication (SFF process; an AM technology. Following an experimental method, the full data flow path for the prototype algorithm was developed, starting with STL data files, and then processing the STL data file into a G-code file format by slicing the model and creating a tool-path. This layering method is used by most 3-D printers to turn a 2-D object into a 3-D object. The STL algorithm developed in this study presents innovative opportunities for LM, since it allows engineers and architects to transform their ideas easily into a solid model in a fast, simple, and cheap way. This is accomplished by allowing STL models to be sliced rapidly, effectively, and without error, and finally to be processed and prepared into a G-code print file.
International Nuclear Information System (INIS)
Saba, Luca; Sannia, Stefano; Ledda, Giuseppe; Gao, Hao; Acharya, U.R.; Suri, Jasjit S.
2012-01-01
The purpose of this study was to evaluate the potentialities of a semi-automated technique in the detection and measurement of the carotid artery plaque. Twenty-two consecutive patients (18 males, 4 females; mean age 62 years) examined with MDCTA from January 2011 to March 2011 were included in this retrospective study. Carotid arteries are examined with a 16-multi-detector-row CT system, and for each patient, the most diseased carotid was selected. In the first phase, the carotid plaque was identified and one experienced radiologist manually traced the inner and outer boundaries by using polyline and radial distance method (PDM and RDM, respectively). In the second phase, the carotid inner and outer boundaries were traced with an automated algorithm: level-set-method (LSM). Data were compared by using Pearson rho correlation, Bland-Altman, and regression. A total of 715 slices were analyzed. The mean thickness of the plaque using the reference PDM was 1.86 mm whereas using the LSM-PDM was 1.96 mm; using the reference RDM was 2.06 mm whereas using the LSM-RDM was 2.03 mm. The correlation values between the references, the LSM, the PDM and the RDM were 0.8428, 0.9921, 0.745 and 0.6425. Bland-Altman demonstrated a very good agreement in particular with the RDM method. Results of our study indicate that LSM method can automatically measure the thickness of the plaque and that the best results are obtained with the RDM. Our results suggest that advanced computer-based algorithms can identify and trace the plaque boundaries like an experienced human reader. (orig.)
Energy Technology Data Exchange (ETDEWEB)
Saba, Luca; Sannia, Stefano; Ledda, Giuseppe [University of Cagliari - Azienda Ospedaliero Universitaria di Cagliari, Department of Radiology, Monserrato, Cagliari (Italy); Gao, Hao [University of Strathclyde, Signal Processing Centre for Excellence in Signal and Image Processing, Department of Electronic and Electrical Engineering, Glasgow (United Kingdom); Acharya, U.R. [Ngee Ann Polytechnic University, Department of Electronics and Computer Engineering, Clementi (Singapore); Suri, Jasjit S. [Biomedical Technologies Inc., Denver, CO (United States); Idaho State University (Aff.), Pocatello, ID (United States)
2012-11-15
The purpose of this study was to evaluate the potentialities of a semi-automated technique in the detection and measurement of the carotid artery plaque. Twenty-two consecutive patients (18 males, 4 females; mean age 62 years) examined with MDCTA from January 2011 to March 2011 were included in this retrospective study. Carotid arteries are examined with a 16-multi-detector-row CT system, and for each patient, the most diseased carotid was selected. In the first phase, the carotid plaque was identified and one experienced radiologist manually traced the inner and outer boundaries by using polyline and radial distance method (PDM and RDM, respectively). In the second phase, the carotid inner and outer boundaries were traced with an automated algorithm: level-set-method (LSM). Data were compared by using Pearson rho correlation, Bland-Altman, and regression. A total of 715 slices were analyzed. The mean thickness of the plaque using the reference PDM was 1.86 mm whereas using the LSM-PDM was 1.96 mm; using the reference RDM was 2.06 mm whereas using the LSM-RDM was 2.03 mm. The correlation values between the references, the LSM, the PDM and the RDM were 0.8428, 0.9921, 0.745 and 0.6425. Bland-Altman demonstrated a very good agreement in particular with the RDM method. Results of our study indicate that LSM method can automatically measure the thickness of the plaque and that the best results are obtained with the RDM. Our results suggest that advanced computer-based algorithms can identify and trace the plaque boundaries like an experienced human reader. (orig.)
Mohammad, Fatimah; Ansari, Rashid; Shahidi, Mahnaz
2013-03-01
The visibility and continuity of the inner segment outer segment (ISOS) junction layer of the photoreceptors on spectral domain optical coherence tomography images is known to be related to visual acuity in patients with age-related macular degeneration (AMD). Automatic detection and segmentation of lesions and pathologies in retinal images is crucial for the screening, diagnosis, and follow-up of patients with retinal diseases. One of the challenges of using the classical level-set algorithms for segmentation involves the placement of the initial contour. Manually defining the contour or randomly placing it in the image may lead to segmentation of erroneous structures. It is important to be able to automatically define the contour by using information provided by image features. We explored a level-set method which is based on the classical Chan-Vese model and which utilizes image feature information for automatic contour placement for the segmentation of pathologies in fluorescein angiograms and en face retinal images of the ISOS layer. This was accomplished by exploiting a priori knowledge of the shape and intensity distribution allowing the use of projection profiles to detect the presence of pathologies that are characterized by intensity differences with surrounding areas in retinal images. We first tested our method by applying it to fluorescein angiograms. We then applied our method to en face retinal images of patients with AMD. The experimental results included demonstrate that the proposed method provided a quick and improved outcome as compared to the classical Chan-Vese method in which the initial contour is randomly placed, thus indicating the potential to provide a more accurate and detailed view of changes in pathologies due to disease progression and treatment.
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Quintin Ernst Muhl
2013-12-01
Full Text Available Moringa oleifera is becoming increasingly popular as an industrial crop due to its multitude of useful attributes as water purifier, nutritional supplement and biofuel feedstock. Given its tolerance to sub-optimal growing conditions, most of the current and anticipated cultivation areas are in medium to low rainfall areas. This study aimed to assess the effect of various irrigation levels on floral initiation, flowering and fruit set. Three treatments namely, a 900 mm (900IT, 600 mm (600IT and 300 mm (300IT per annum irrigation treatment were administered through drip irrigation, simulating three total annual rainfall amounts. Individual inflorescences from each treatment were tagged during floral initiation and monitored throughout until fruit set. Flower bud initiation was highest at the 300IT and lowest at the 900IT for two consecutive growing seasons. Fruit set on the other hand, decreased with the decrease in irrigation treatment. Floral abortion, reduced pollen viability as well as moisture stress in the style were contributing factors to the reduction in fruiting/yield observed at the 300IT. Moderate water stress prior to floral initiation could stimulate flower initiation, however, this should be followed by sufficient irrigation to ensure good pollination, fruit set and yield.
Maluka, Stephen; Kamuzora, Peter; San Sebastián, Miguel; Byskov, Jens; Ndawi, Benedict; Hurtig, Anna-Karin
2010-12-01
In 2006, researchers and decision-makers launched a five-year project - Response to Accountable Priority Setting for Trust in Health Systems (REACT) - to improve planning and priority-setting through implementing the Accountability for Reasonableness framework in Mbarali District, Tanzania. The objective of this paper is to explore the acceptability of Accountability for Reasonableness from the perspectives of the Council Health Management Team, local government officials, health workforce and members of user boards and committees. Individual interviews were carried out with different categories of actors and stakeholders in the district. The interview guide consisted of a series of questions, asking respondents to describe their perceptions regarding each condition of the Accountability for Reasonableness framework in terms of priority setting. Interviews were analysed using thematic framework analysis. Documentary data were used to support, verify and highlight the key issues that emerged. Almost all stakeholders viewed Accountability for Reasonableness as an important and feasible approach for improving priority-setting and health service delivery in their context. However, a few aspects of Accountability for Reasonableness were seen as too difficult to implement given the socio-political conditions and traditions in Tanzania. Respondents mentioned: budget ceilings and guidelines, low level of public awareness, unreliable and untimely funding, as well as the limited capacity of the district to generate local resources as the major contextual factors that hampered the full implementation of the framework in their context. This study was one of the first assessments of the applicability of Accountability for Reasonableness in health care priority-setting in Tanzania. The analysis, overall, suggests that the Accountability for Reasonableness framework could be an important tool for improving priority-setting processes in the contexts of resource-poor settings
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Polychronopoulou D.
2016-01-01
Full Text Available Fragmentation of α lamellae and subsequent spheroidization of α laths in α/β titanium alloys occurring during and after deformation are well known phenomena. We will illustrate the development of a new finite element methodology to model them. This new methodology is based on a level set framework to model the deformation and the ad hoc simultaneous and/or subsequent interfaces kinetics. We will focus, at yet, on the modeling of the surface diffusion at the α/β phase interfaces and the motion by mean curvature at the α/α grain interfaces.
International Nuclear Information System (INIS)
Wagh, A.S.; Singh, D.
1994-01-01
Argonne National Laboratory, with support from the Office of Technology in the US Department of Energy (DOE), has developed a new process employing novel, chemically bonded ceramic materials to stabilize secondary waste streams. Such waste streams result from the thermal processes used to stabilize low-level, mixed wastes. The process will help the electric power industry treat its combustion and low-level mixed wastes. The ceramic materials are strong, dense, leach-resistant, and inexpensive to fabricate. The room-temperature-setting process allows stabilization of volatile components containing lead, mercury, cadmium, chromium, and nickel. The process also provides effective stabilization of fossil fuel combustion products. It is most suitable for treating fly and bottom ashes
Automated volume analysis of head and neck lesions on CT scans using 3D level set segmentation
International Nuclear Information System (INIS)
Street, Ethan; Hadjiiski, Lubomir; Sahiner, Berkman; Gujar, Sachin; Ibrahim, Mohannad; Mukherji, Suresh K.; Chan, Heang-Ping
2007-01-01
The authors have developed a semiautomatic system for segmentation of a diverse set of lesions in head and neck CT scans. The system takes as input an approximate bounding box, and uses a multistage level set to perform the final segmentation. A data set consisting of 69 lesions marked on 33 scans from 23 patients was used to evaluate the performance of the system. The contours from automatic segmentation were compared to both 2D and 3D gold standard contours manually drawn by three experienced radiologists. Three performance metric measures were used for the comparison. In addition, a radiologist provided quality ratings on a 1 to 10 scale for all of the automatic segmentations. For this pilot study, the authors observed that the differences between the automatic and gold standard contours were larger than the interobserver differences. However, the system performed comparably to the radiologists, achieving an average area intersection ratio of 85.4% compared to an average of 91.2% between two radiologists. The average absolute area error was 21.1% compared to 10.8%, and the average 2D distance was 1.38 mm compared to 0.84 mm between the radiologists. In addition, the quality rating data showed that, despite the very lax assumptions made on the lesion characteristics in designing the system, the automatic contours approximated many of the lesions very well
Topping, Christopher John; Luttik, Robert
2017-10-01
Specific protection goals (SPGs) comprise an explicit expression of the environmental components that need protection and the maximum impacts that can be tolerated. SPGs are set by risk managers and are typically based on protecting populations or functions. However, the measurable endpoints available to risk managers, at least for vertebrates, are typically laboratory tests. We demonstrate, using the example of eggshell thinning in skylarks, how simulation can be used to place laboratory endpoints in context of population-level effects as an aid to setting the SPGs. We develop explanatory scenarios investigating the impact of different assumptions of eggshell thinning on skylark population size, density and distribution in 10 Danish landscapes, chosen to represent the range of typical Danish agricultural conditions. Landscape and timing of application of the pesticide were found to be the most critical factors to consider in the impact assessment. Consequently, a regulatory scenario of monoculture spring barley with an early spray treatment eliciting the eggshell thinning effect was applied using concentrations eliciting effects of zero to 100% in steps of 5%. Setting the SPGs requires balancing scientific, social and political realities. However, the provision of clear and detailed options such as those from comprehensive simulation results can inform the decision process by improving transparency and by putting the more abstract testing data into the context of real-world impacts. Copyright © 2017 Elsevier Inc. All rights reserved.
Chu, C.; Sun-Mack, S.; Chen, Y.; Heckert, E.; Doelling, D. R.
2017-12-01
In Langley NASA, Clouds and the Earth's Radiant Energy System (CERES) and Moderate Resolution Imaging Spectroradiometer (MODIS) are merged with Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) on the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) and CloudSat Cloud Profiling Radar (CPR). The CERES merged product (C3M) matches up to three CALIPSO footprints with each MODIS pixel along its ground track. It then assigns the nearest CloudSat footprint to each of those MODIS pixels. The cloud properties from MODIS, retrieved using the CERES algorithms, are included in C3M with the matched CALIPSO and CloudSat products along with radiances from 18 MODIS channels. The dataset is used to validate the CERES retrieved MODIS cloud properties and the computed TOA and surface flux difference using MODIS or CALIOP/CloudSAT retrieved clouds. This information is then used to tune the computed fluxes to match the CERES observed TOA flux. A visualization tool will be invaluable to determine the cause of these large cloud and flux differences in order to improve the methodology. This effort is part of larger effort to allow users to order the CERES C3M product sub-setted by time and parameter as well as the previously mentioned visualization capabilities. This presentation will show a new graphical 3D-interface, 3D-CERESVis, that allows users to view both passive remote sensing satellites (MODIS and CERES) and active satellites (CALIPSO and CloudSat), such that the detailed vertical structures of cloud properties from CALIPSO and CloudSat are displayed side by side with horizontally retrieved cloud properties from MODIS and CERES. Similarly, the CERES computed profile fluxes whether using MODIS or CALIPSO and CloudSat clouds can also be compared. 3D-CERESVis is a browser-based visualization tool that makes uses of techniques such as multiple synchronized cursors, COLLADA format data and Cesium.
Planar graphs theory and algorithms
Nishizeki, T
1988-01-01
Collected in this volume are most of the important theorems and algorithms currently known for planar graphs, together with constructive proofs for the theorems. Many of the algorithms are written in Pidgin PASCAL, and are the best-known ones; the complexities are linear or 0(nlogn). The first two chapters provide the foundations of graph theoretic notions and algorithmic techniques. The remaining chapters discuss the topics of planarity testing, embedding, drawing, vertex- or edge-coloring, maximum independence set, subgraph listing, planar separator theorem, Hamiltonian cycles, and single- or multicommodity flows. Suitable for a course on algorithms, graph theory, or planar graphs, the volume will also be useful for computer scientists and graph theorists at the research level. An extensive reference section is included.
GSHR, a Web-Based Platform Provides Gene Set-Level Analyses of Hormone Responses in Arabidopsis
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Xiaojuan Ran
2018-01-01
Full Text Available Phytohormones regulate diverse aspects of plant growth and environmental responses. Recent high-throughput technologies have promoted a more comprehensive profiling of genes regulated by different hormones. However, these omics data generally result in large gene lists that make it challenging to interpret the data and extract insights into biological significance. With the rapid accumulation of theses large-scale experiments, especially the transcriptomic data available in public databases, a means of using this information to explore the transcriptional networks is needed. Different platforms have different architectures and designs, and even similar studies using the same platform may obtain data with large variances because of the highly dynamic and flexible effects of plant hormones; this makes it difficult to make comparisons across different studies and platforms. Here, we present a web server providing gene set-level analyses of Arabidopsis thaliana hormone responses. GSHR collected 333 RNA-seq and 1,205 microarray datasets from the Gene Expression Omnibus, characterizing transcriptomic changes in Arabidopsis in response to phytohormones including abscisic acid, auxin, brassinosteroids, cytokinins, ethylene, gibberellins, jasmonic acid, salicylic acid, and strigolactones. These data were further processed and organized into 1,368 gene sets regulated by different hormones or hormone-related factors. By comparing input gene lists to these gene sets, GSHR helped to identify gene sets from the input gene list regulated by different phytohormones or related factors. Together, GSHR links prior information regarding transcriptomic changes induced by hormones and related factors to newly generated data and facilities cross-study and cross-platform comparisons; this helps facilitate the mining of biologically significant information from large-scale datasets. The GSHR is freely available at http://bioinfo.sibs.ac.cn/GSHR/.
International Nuclear Information System (INIS)
Gonzalez, V.; Dolores, VV. de los; Pastor, V.; Martinez, J.; Gimeno, J.; Guardino, C.; Crispin, V.
2011-01-01
Algorithm has been used at our institution iGRiMLO scheduled for individual verification of treatment plans for intensity modulated radiotherapy (IMRT) step and shoot through portal dosimetry pretreatment of non-transmission, triggering the plan directly to a portal imaging device (EPID) of an amorphous silicon flat panel.
Lamu, Admassu N; Chen, Gang; Gamst-Klaussen, Thor; Olsen, Jan Abel
2018-03-22
To develop mapping algorithms that transform Diabetes-39 (D-39) scores onto EQ-5D-5L utility values for each of eight recently published country-specific EQ-5D-5L value sets, and to compare mapping functions across the EQ-5D-5L value sets. Data include 924 individuals with self-reported diabetes from six countries. The D-39 dimensions, age and gender were used as potential predictors for EQ-5D-5L utilities, which were scored using value sets from eight countries (England, Netherland, Spain, Canada, Uruguay, China, Japan and Korea). Ordinary least squares, generalised linear model, beta binomial regression, fractional regression, MM estimation and censored least absolute deviation were used to estimate the mapping algorithms. The optimal algorithm for each country-specific value set was primarily selected based on normalised root mean square error (NRMSE), normalised mean absolute error (NMAE) and adjusted-r 2 . Cross-validation with fivefold approach was conducted to test the generalizability of each model. The fractional regression model with loglog as a link function consistently performed best in all country-specific value sets. For instance, the NRMSE (0.1282) and NMAE (0.0914) were the lowest, while adjusted-r 2 was the highest (52.5%) when the English value set was considered. Among D-39 dimensions, the energy and mobility was the only one that was consistently significant for all models. The D-39 can be mapped onto the EQ-5D-5L utilities with good predictive accuracy. The fractional regression model, which is appropriate for handling bounded outcomes, outperformed other candidate methods in all country-specific value sets. However, the regression coefficients differed reflecting preference heterogeneity across countries.
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Uzma Tahir
2018-04-01
Full Text Available Powered ankle-foot prostheses assist users through plantarflexion during stance and dorsiflexion during swing. Provision of motor power permits faster preferred walking speeds than passive devices, but use of active motor power raises the issue of control. While several commercially available algorithms provide torque control for many intended activities and variations of terrain, control approaches typically exhibit no inherent adaptation. In contrast, muscles adapt instantaneously to changes in load without sensory feedback due to the intrinsic property that their stiffness changes with length and velocity. We previously developed a “winding filament” hypothesis (WFH for muscle contraction that accounts for intrinsic muscle properties by incorporating the giant titin protein. The goals of this study were to develop a WFH-based control algorithm for a powered prosthesis and to test its robustness during level walking and stair ascent in a case study of two subjects with 4–5 years of experience using a powered prosthesis. In the WFH algorithm, ankle moments produced by virtual muscles are calculated based on muscle length and activation. Net ankle moment determines the current applied to the motor. Using this algorithm implemented in a BiOM T2 prosthesis, we tested subjects during level walking and stair ascent. During level walking at variable speeds, the WFH algorithm produced plantarflexion angles (range = −8 to −19° and ankle moments (range = 1 to 1.5 Nm/kg similar to those produced by the BiOM T2 stock controller and to people with no amputation. During stair ascent, the WFH algorithm produced plantarflexion angles (range −15 to −19° that were similar to persons with no amputation and were ~5 times larger on average at 80 steps/min than those produced by the stock controller. This case study provides proof-of-concept that, by emulating muscle properties, the WFH algorithm provides robust, adaptive control of level walking at
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Kimmel April D
2012-09-01
Full Text Available Abstract Background In resource-limited settings, HIV budgets are flattening or decreasing. A policy of discontinuing antiretroviral therapy (ART after HIV treatment failure was modeled to highlight trade-offs among competing policy goals of optimizing individual and population health outcomes. Methods In settings with two available ART regimens, we assessed two strategies: (1 continue ART after second-line failure (Status Quo and (2 discontinue ART after second-line failure (Alternative. A computer model simulated outcomes for a single cohort of newly detected, HIV-infected individuals. Projections were fed into a population-level model allowing multiple cohorts to compete for ART with constraints on treatment capacity. In the Alternative strategy, discontinuation of second-line ART occurred upon detection of antiretroviral failure, specified by WHO guidelines. Those discontinuing failed ART experienced an increased risk of AIDS-related mortality compared to those continuing ART. Results At the population level, the Alternative strategy increased the mean number initiating ART annually by 1,100 individuals (+18.7% to 6,980 compared to the Status Quo. More individuals initiating ART under the Alternative strategy increased total life-years by 15,000 (+2.8% to 555,000, compared to the Status Quo. Although more individuals received treatment under the Alternative strategy, life expectancy for those treated decreased by 0.7 years (−8.0% to 8.1 years compared to the Status Quo. In a cohort of treated patients only, 600 more individuals (+27.1% died by 5 years under the Alternative strategy compared to the Status Quo. Results were sensitive to the timing of detection of ART failure, number of ART regimens, and treatment capacity. Although we believe the results robust in the short-term, this analysis reflects settings where HIV case detection occurs late in the disease course and treatment capacity and the incidence of newly detected patients are
Altazi, Baderaldeen A; Zhang, Geoffrey G; Fernandez, Daniel C; Montejo, Michael E; Hunt, Dylan; Werner, Joan; Biagioli, Matthew C; Moros, Eduardo G
2017-11-01
Site-specific investigations of the role of radiomics in cancer diagnosis and therapy are emerging. We evaluated the reproducibility of radiomic features extracted from 18 Flourine-fluorodeoxyglucose ( 18 F-FDG) PET images for three parameters: manual versus computer-aided segmentation methods, gray-level discretization, and PET image reconstruction algorithms. Our cohort consisted of pretreatment PET/CT scans from 88 cervical cancer patients. Two board-certified radiation oncologists manually segmented the metabolic tumor volume (MTV 1 and MTV 2 ) for each patient. For comparison, we used a graphical-based method to generate semiautomated segmented volumes (GBSV). To address any perturbations in radiomic feature values, we down-sampled the tumor volumes into three gray-levels: 32, 64, and 128 from the original gray-level of 256. Finally, we analyzed the effect on radiomic features on PET images of eight patients due to four PET 3D-reconstruction algorithms: maximum likelihood-ordered subset expectation maximization (OSEM) iterative reconstruction (IR) method, fourier rebinning-ML-OSEM (FOREIR), FORE-filtered back projection (FOREFBP), and 3D-Reprojection (3DRP) analytical method. We extracted 79 features from all segmentation method, gray-levels of down-sampled volumes, and PET reconstruction algorithms. The features were extracted using gray-level co-occurrence matrices (GLCM), gray-level size zone matrices (GLSZM), gray-level run-length matrices (GLRLM), neighborhood gray-tone difference matrices (NGTDM), shape-based features (SF), and intensity histogram features (IHF). We computed the Dice coefficient between each MTV and GBSV to measure segmentation accuracy. Coefficient values close to one indicate high agreement, and values close to zero indicate low agreement. We evaluated the effect on radiomic features by calculating the mean percentage differences (d¯) between feature values measured from each pair of parameter elements (i.e. segmentation methods: MTV
International Nuclear Information System (INIS)
Kuttig, Jan; Steiding, Christian; Hupfer, Martin; Karolczak, Marek; Kolditz, Daniel
2015-01-01
In this study we compared various defect pixel correction methods for reducing artifact appearance within projection images used for computed tomography (CT) reconstructions.Defect pixel correction algorithms were examined with respect to their artifact behaviour within planar projection images as well as in volumetric CT reconstructions. We investigated four algorithms: nearest neighbour, linear and adaptive linear interpolation, and a frequency-selective spectral-domain approach.To characterise the quality of each algorithm in planar image data, we inserted line defects of varying widths and orientations into images. The structure preservation of each algorithm was analysed by corrupting and correcting the image of a slit phantom pattern and by evaluating its line spread function (LSF). The noise preservation was assessed by interpolating corrupted flat images and estimating the noise power spectrum (NPS) of the interpolated region.For the volumetric investigations, we examined the structure and noise preservation within a structured aluminium foam, a mid-contrast cone-beam phantom and a homogeneous Polyurethane (PUR) cylinder.The frequency-selective algorithm showed the best structure and noise preservation for planar data of the correction methods tested. For volumetric data it still showed the best noise preservation, whereas the structure preservation was outperformed by the linear interpolation.The frequency-selective spectral-domain approach in the correction of line defects is recommended for planar image data, but its abilities within high-contrast volumes are restricted. In that case, the application of a simple linear interpolation might be the better choice to correct line defects within projection images used for CT. (paper)
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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.
Constructing a graph of connections in clustering algorithm of complex objects
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Татьяна Шатовская
2015-05-01
Full Text Available The article describes the results of modifying the algorithm Chameleon. Hierarchical multi-level algorithm consists of several phases: the construction of the count, coarsening, the separation and recovery. Each phase can be used various approaches and algorithms. The main aim of the work is to study the quality of the clustering of different sets of data using a set of algorithms combinations at different stages of the algorithm and improve the stage of construction by the optimization algorithm of k choice in the graph construction of k of nearest neighbors
2017-01-01
Background Machine learning techniques may be an effective and efficient way to classify open-text reports on doctor’s activity for the purposes of quality assurance, safety, and continuing professional development. Objective The objective of the study was to evaluate the accuracy of machine learning algorithms trained to classify open-text reports of doctor performance and to assess the potential for classifications to identify significant differences in doctors’ professional performance in the United Kingdom. Methods We used 1636 open-text comments (34,283 words) relating to the performance of 548 doctors collected from a survey of clinicians’ colleagues using the General Medical Council Colleague Questionnaire (GMC-CQ). We coded 77.75% (1272/1636) of the comments into 5 global themes (innovation, interpersonal skills, popularity, professionalism, and respect) using a qualitative framework. We trained 8 machine learning algorithms to classify comments and assessed their performance using several training samples. We evaluated doctor performance using the GMC-CQ and compared scores between doctors with different classifications using t tests. Results Individual algorithm performance was high (range F score=.68 to .83). Interrater agreement between the algorithms and the human coder was highest for codes relating to “popular” (recall=.97), “innovator” (recall=.98), and “respected” (recall=.87) codes and was lower for the “interpersonal” (recall=.80) and “professional” (recall=.82) codes. A 10-fold cross-validation demonstrated similar performance in each analysis. When combined together into an ensemble of multiple algorithms, mean human-computer interrater agreement was .88. Comments that were classified as “respected,” “professional,” and “interpersonal” related to higher doctor scores on the GMC-CQ compared with comments that were not classified (P.05). Conclusions Machine learning algorithms can classify open-text feedback
Gibbons, Chris; Richards, Suzanne; Valderas, Jose Maria; Campbell, John
2017-03-15
Machine learning techniques may be an effective and efficient way to classify open-text reports on doctor's activity for the purposes of quality assurance, safety, and continuing professional development. The objective of the study was to evaluate the accuracy of machine learning algorithms trained to classify open-text reports of doctor performance and to assess the potential for classifications to identify significant differences in doctors' professional performance in the United Kingdom. We used 1636 open-text comments (34,283 words) relating to the performance of 548 doctors collected from a survey of clinicians' colleagues using the General Medical Council Colleague Questionnaire (GMC-CQ). We coded 77.75% (1272/1636) of the comments into 5 global themes (innovation, interpersonal skills, popularity, professionalism, and respect) using a qualitative framework. We trained 8 machine learning algorithms to classify comments and assessed their performance using several training samples. We evaluated doctor performance using the GMC-CQ and compared scores between doctors with different classifications using t tests. Individual algorithm performance was high (range F score=.68 to .83). Interrater agreement between the algorithms and the human coder was highest for codes relating to "popular" (recall=.97), "innovator" (recall=.98), and "respected" (recall=.87) codes and was lower for the "interpersonal" (recall=.80) and "professional" (recall=.82) codes. A 10-fold cross-validation demonstrated similar performance in each analysis. When combined together into an ensemble of multiple algorithms, mean human-computer interrater agreement was .88. Comments that were classified as "respected," "professional," and "interpersonal" related to higher doctor scores on the GMC-CQ compared with comments that were not classified (P.05). Machine learning algorithms can classify open-text feedback of doctor performance into multiple themes derived by human raters with high
Xiao, Li-Hong; Chen, Pei-Ran; Gou, Zhong-Ping; Li, Yong-Zhong; Li, Mei; Xiang, Liang-Cheng; Feng, Ping
2017-01-01
The aim of this study is to evaluate the ability of the random forest algorithm that combines data on transrectal ultrasound findings, age, and serum levels of prostate-specific antigen to predict prostate carcinoma. Clinico-demographic data were analyzed for 941 patients with prostate diseases treated at our hospital, including age, serum prostate-specific antigen levels, transrectal ultrasound findings, and pathology diagnosis based on ultrasound-guided needle biopsy of the prostate. These data were compared between patients with and without prostate cancer using the Chi-square test, and then entered into the random forest model to predict diagnosis. Patients with and without prostate cancer differed significantly in age and serum prostate-specific antigen levels (P prostate-specific antigen and ultrasound predicted prostate cancer with an accuracy of 83.10%, sensitivity of 65.64%, and specificity of 93.83%. Positive predictive value was 86.72%, and negative predictive value was 81.64%. By integrating age, prostate-specific antigen levels and transrectal ultrasound findings, the random forest algorithm shows better diagnostic performance for prostate cancer than either diagnostic indicator on its own. This algorithm may help improve diagnosis of the disease by identifying patients at high risk for biopsy.
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Li-Hong Xiao
2017-01-01
Full Text Available The aim of this study is to evaluate the ability of the random forest algorithm that combines data on transrectal ultrasound findings, age, and serum levels of prostate-specific antigen to predict prostate carcinoma. Clinico-demographic data were analyzed for 941 patients with prostate diseases treated at our hospital, including age, serum prostate-specific antigen levels, transrectal ultrasound findings, and pathology diagnosis based on ultrasound-guided needle biopsy of the prostate. These data were compared between patients with and without prostate cancer using the Chi-square test, and then entered into the random forest model to predict diagnosis. Patients with and without prostate cancer differed significantly in age and serum prostate-specific antigen levels (P < 0.001, as well as in all transrectal ultrasound characteristics (P < 0.05 except uneven echo (P = 0.609. The random forest model based on age, prostate-specific antigen and ultrasound predicted prostate cancer with an accuracy of 83.10%, sensitivity of 65.64%, and specificity of 93.83%. Positive predictive value was 86.72%, and negative predictive value was 81.64%. By integrating age, prostate-specific antigen levels and transrectal ultrasound findings, the random forest algorithm shows better diagnostic performance for prostate cancer than either diagnostic indicator on its own. This algorithm may help improve diagnosis of the disease by identifying patients at high risk for biopsy.
Bergeest, Jan-Philip; Rohr, Karl
2012-10-01
In high-throughput applications, accurate and efficient segmentation of cells in fluorescence microscopy images is of central importance for the quantification of protein expression and the understanding of cell function. We propose an approach for segmenting cell nuclei which is based on active contours using level sets and convex energy functionals. Compared to previous work, our approach determines the global solution. Thus, the approach does not suffer from local minima and the segmentation result does not depend on the initialization. We consider three different well-known energy functionals for active contour-based segmentation and introduce convex formulations of these functionals. We also suggest a numeric approach for efficiently computing the solution. The performance of our approach has been evaluated using fluorescence microscopy images from different experiments comprising different cell types. We have also performed a quantitative comparison with previous segmentation approaches. Copyright © 2012 Elsevier B.V. All rights reserved.
Directory of Open Access Journals (Sweden)
Mehrdad Shahmohammadi Beni
2017-06-01
Full Text Available Cold plasmas were proposed for treatment of leukemia. In the present work, conceptual designs of mixing chambers that increased the contact between the two fluids (plasma and blood through addition of obstacles within rectangular-block-shaped chambers were proposed and the dynamic mixing between the plasma and blood were studied using the level set method coupled with heat transfer. Enhancement of mixing between blood and plasma in the presence of obstacles was demonstrated. Continuous tracking of fluid mixing with determination of temperature distributions was enabled by the present model, which would be a useful tool for future development of cold plasma devices for treatment of blood-related diseases such as leukemia.
Energy Technology Data Exchange (ETDEWEB)
Kim, Yeong Ju; Lee, Jin Soo [Dept. of Radiology, Inje University Haeundae Paik Hospital, Busan (Korea, Republic of); Kang, Se Sik; Kim, Chang Soo [Dept. of Radiological Science, College of Health Sciences, Catholic University of Pusan, Busan (Korea, Republic of)
2017-06-15
This study evaluated the applicability of computer-aided diagnosis by retrospective analysis of GLCM algorithm based on cytopathological diagnosis of normal and malignant nodules in thyroid ultrasound images. In the experiment, the recognition rate and ROC curve of thyroid malignant nodule were analyzed using 6 parameters of GLCM algorithm. Experimental results showed 97% energy, 93% contrast, 92% correlation, 92% homogeneity, 100% entropy and 100% variance. Statistical analysis showed that the area under the curve of each parameter was more than 0.947 (p = 0 .001) in t he ROC curve, which was s ignificant in the recognition of thyroid malignant nodules. In the GLCM, the cut-off value of each parameter can be used to predict the disease through analysis of quantitative computer-aided diagnosis.
Yadav, Vijesh; Gupta, Vijay Kumar; Meena, Ganga Sahay
2018-05-01
Studied the effect of culture (2, 2.5 and 3%), ultrafiltered (UF) retentate addition (0, 11, 18%), total milk solids (13, 13.50, 14%) and heat treatments (80 and 85 °C/30 min) on the change in pH and titratable acidity (TA), sensory scores and rheological parameters of yoghurt. With 3% culture levels, the required TA (0.90% LA) was achieved in minimum 6 h incubation. With an increase in UF retentate addition, there was observed a highly significant decrease in overall acceptability, body and texture and colour and appearance scores, but there was highly significant increase in rheological parameters of yoghurt samples. Yoghurt made from even 13.75% total solids containing nil UF retentate was observed to be sufficiently firm by the sensory panel. Most of the sensory attributes of yoghurt made with 13.50% total solids were significantly better than yoghurt prepared with either 13 or 14% total solids. Standardised milk heated to 85 °C/30 min resulted in significantly better overall acceptability in yoghurt. Overall acceptability of optimised yoghurt was significantly better than a branded market sample. UF retentate addition adversely affected yoghurt quality, whereas optimization of culture levels, totals milk solids and others process parameters noticeably improved the quality of plain set yoghurt with a shelf life of 15 days at 4 °C.
DEFF Research Database (Denmark)
Markham, Annette
This paper takes an actor network theory approach to explore some of the ways that algorithms co-construct identity and relational meaning in contemporary use of social media. Based on intensive interviews with participants as well as activity logging and data tracking, the author presents a richly...... layered set of accounts to help build our understanding of how individuals relate to their devices, search systems, and social network sites. This work extends critical analyses of the power of algorithms in implicating the social self by offering narrative accounts from multiple perspectives. It also...... contributes an innovative method for blending actor network theory with symbolic interaction to grapple with the complexity of everyday sensemaking practices within networked global information flows....
Set-up and first operation of a plasma oven for treatment of low level radioactive wastes
Directory of Open Access Journals (Sweden)
Nachtrodt Frederik
2014-01-01
Full Text Available An experimental device for plasma treatment of low and intermediate level radioactive waste was built and tested in several design variations. The laboratory device is designed with the intention to study the general effects and difficulties in a plasma incineration set-up for the further future development of a larger scale pilot plant. The key part of the device consists of a novel microwave plasma torch driven by 200 W electric power, and operating at atmospheric pressure. It is a specific design characteristic of the torch that a high peak temperature can be reached with a low power input compared to other plasma torches. Experiments have been carried out to analyze the effect of the plasma on materials typical for operational low-level wastes. In some preliminary cold tests the behavior of stable volatile species e. g., caesium was investigated by TXRF measurements of material collected from the oven walls and the filtered off-gas. The results help in improving and scaling up the existing design and in understanding the effects for a pilot plant, especially for the off-gas collection and treatment.
Szwedowski, T D; Fialkov, J; Pakdel, A; Whyne, C M
2013-01-01
Accurate representation of skeletal structures is essential for quantifying structural integrity, for developing accurate models, for improving patient-specific implant design and in image-guided surgery applications. The complex morphology of thin cortical structures of the craniofacial skeleton (CFS) represents a significant challenge with respect to accurate bony segmentation. This technical study presents optimized processing steps to segment the three-dimensional (3D) geometry of thin cortical bone structures from CT images. In this procedure, anoisotropic filtering and a connected components scheme were utilized to isolate and enhance the internal boundaries between craniofacial cortical and trabecular bone. Subsequently, the shell-like nature of cortical bone was exploited using boundary-tracking level-set methods with optimized parameters determined from large-scale sensitivity analysis. The process was applied to clinical CT images acquired from two cadaveric CFSs. The accuracy of the automated segmentations was determined based on their volumetric concurrencies with visually optimized manual segmentations, without statistical appraisal. The full CFSs demonstrated volumetric concurrencies of 0.904 and 0.719; accuracy increased to concurrencies of 0.936 and 0.846 when considering only the maxillary region. The highly automated approach presented here is able to segment the cortical shell and trabecular boundaries of the CFS in clinical CT images. The results indicate that initial scan resolution and cortical-trabecular bone contrast may impact performance. Future application of these steps to larger data sets will enable the determination of the method's sensitivity to differences in image quality and CFS morphology.
DEFF Research Database (Denmark)
Gustavson, Fred G.; Reid, John K.; Wasniewski, Jerzy
2007-01-01
We present subroutines for the Cholesky factorization of a positive-definite symmetric matrix and for solving corresponding sets of linear equations. They exploit cache memory by using the block hybrid format proposed by the authors in a companion article. The matrix is packed into n(n + 1)/2 real...... variables, and the speed is usually better than that of the LAPACK algorithm that uses full storage (n2 variables). Included are subroutines for rearranging a matrix whose upper or lower-triangular part is packed by columns to this format and for the inverse rearrangement. Also included is a kernel...
Kumar, Keshav
2018-03-29
Excitation-emission matrix fluorescence (EEMF) and total synchronous fluorescence spectroscopy (TSFS) are the 2 fluorescence techniques that are commonly used for the analysis of multifluorophoric mixtures. These 2 fluorescence techniques are conceptually different and provide certain advantages over each other. The manual analysis of such highly correlated large volume of EEMF and TSFS towards developing a calibration model is difficult. Partial least square (PLS) analysis can analyze the large volume of EEMF and TSFS data sets by finding important factors that maximize the correlation between the spectral and concentration information for each fluorophore. However, often the application of PLS analysis on entire data sets does not provide a robust calibration model and requires application of suitable pre-processing step. The present work evaluates the application of genetic algorithm (GA) analysis prior to PLS analysis on EEMF and TSFS data sets towards improving the precision and accuracy of the calibration model. The GA algorithm essentially combines the advantages provided by stochastic methods with those provided by deterministic approaches and can find the set of EEMF and TSFS variables that perfectly correlate well with the concentration of each of the fluorophores present in the multifluorophoric mixtures. The utility of the GA assisted PLS analysis is successfully validated using (i) EEMF data sets acquired for dilute aqueous mixture of four biomolecules and (ii) TSFS data sets acquired for dilute aqueous mixtures of four carcinogenic polycyclic aromatic hydrocarbons (PAHs) mixtures. In the present work, it is shown that by using the GA it is possible to significantly improve the accuracy and precision of the PLS calibration model developed for both EEMF and TSFS data set. Hence, GA must be considered as a useful pre-processing technique while developing an EEMF and TSFS calibration model.
André, Florian; Fortner, Philipp; Vembar, Mani; Mueller, Dirk; Stiller, Wolfram; Buss, Sebastian J; Kauczor, Hans-Ulrich; Katus, Hugo A; Korosoglou, Grigorios
The aim of this study was to assess the potential for radiation dose reduction using knowledge-based iterative model reconstruction (K-IMR) algorithms in combination with ultra-low dose body mass index (BMI)-adapted protocols in coronary CT angiography (coronary CTA). Forty patients undergoing clinically indicated coronary CTA were randomly assigned to two groups with BMI-adapted (I: quality was significantly better in the ULD group using K-IMR CR 1 compared to FBP, iD 2 and iD 5 in the LD group, resulting in fewer non-diagnostic coronary segments (2.4% vs. 11.6%, 9.2% and 6.1%; p quality compared to LD protocols with FBP or hybrid iterative algorithms. Therefore, K-IMR allows for coronary CTA examinations with high diagnostic value and very low radiation exposure in clinical routine. Copyright © 2017 Society of Cardiovascular Computed Tomography. Published by Elsevier Inc. All rights reserved.
Ferrari, Ulisse
2016-08-01
Maximum entropy models provide the least constrained probability distributions that reproduce statistical properties of experimental datasets. In this work we characterize the learning dynamics that maximizes the log-likelihood in the case of large but finite datasets. We first show how the steepest descent dynamics is not optimal as it is slowed down by the inhomogeneous curvature of the model parameters' space. We then provide a way for rectifying this space which relies only on dataset properties and does not require large computational efforts. We conclude by solving the long-time limit of the parameters' dynamics including the randomness generated by the systematic use of Gibbs sampling. In this stochastic framework, rather than converging to a fixed point, the dynamics reaches a stationary distribution, which for the rectified dynamics reproduces the posterior distribution of the parameters. We sum up all these insights in a "rectified" data-driven algorithm that is fast and by sampling from the parameters' posterior avoids both under- and overfitting along all the directions of the parameters' space. Through the learning of pairwise Ising models from the recording of a large population of retina neurons, we show how our algorithm outperforms the steepest descent method.
International Nuclear Information System (INIS)
Liu Juzhen; Yang Wenying; Cai Tietie
2001-01-01
Objective: To study the relationship between UET and SET variation and early changes of diabetic nephropathy. Methods: UET and SET were measured in 24 patients with diabetes, 19 with early stage diabetic nephropathy, 21 with advanced diabetic nephropathy and 30 normal as contrast. Results: Apparent uprise of UET and SET was observed in all patients when compared to normal contrasts (P 2 -macroglobulin was revealed (P<0.05). Conclusion: UET and SET levels uprose as long as diabetic nephropathy deteriorated. As a result, UET and SET may act as sensitive indices in diagnosing early stage diabetic nephropathy
Shahriyari, Leili
2017-11-03
One of the main challenges in machine learning (ML) is choosing an appropriate normalization method. Here, we examine the effect of various normalization methods on analyzing FPKM upper quartile (FPKM-UQ) RNA sequencing data sets. We collect the HTSeq-FPKM-UQ files of patients with colon adenocarcinoma from TCGA-COAD project. We compare three most common normalization methods: scaling, standardizing using z-score and vector normalization by visualizing the normalized data set and evaluating the performance of 12 supervised learning algorithms on the normalized data set. Additionally, for each of these normalization methods, we use two different normalization strategies: normalizing samples (files) or normalizing features (genes). Regardless of normalization methods, a support vector machine (SVM) model with the radial basis function kernel had the maximum accuracy (78%) in predicting the vital status of the patients. However, the fitting time of SVM depended on the normalization methods, and it reached its minimum fitting time when files were normalized to the unit length. Furthermore, among all 12 learning algorithms and 6 different normalization techniques, the Bernoulli naive Bayes model after standardizing files had the best performance in terms of maximizing the accuracy as well as minimizing the fitting time. We also investigated the effect of dimensionality reduction methods on the performance of the supervised ML algorithms. Reducing the dimension of the data set did not increase the maximum accuracy of 78%. However, it leaded to discovery of the 7SK RNA gene expression as a predictor of survival in patients with colon adenocarcinoma with accuracy of 78%. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com
Rabideau, Gregg R.; Chien, Steve A.
2010-01-01
AVA v2 software selects goals for execution from a set of goals that oversubscribe shared resources. The term goal refers to a science or engineering request to execute a possibly complex command sequence, such as image targets or ground-station downlinks. Developed as an extension to the Virtual Machine Language (VML) execution system, the software enables onboard and remote goal triggering through the use of an embedded, dynamic goal set that can oversubscribe resources. From the set of conflicting goals, a subset must be chosen that maximizes a given quality metric, which in this case is strict priority selection. A goal can never be pre-empted by a lower priority goal, and high-level goals can be added, removed, or updated at any time, and the "best" goals will be selected for execution. The software addresses the issue of re-planning that must be performed in a short time frame by the embedded system where computational resources are constrained. In particular, the algorithm addresses problems with well-defined goal requests without temporal flexibility that oversubscribes available resources. By using a fast, incremental algorithm, goal selection can be postponed in a "just-in-time" fashion allowing requests to be changed or added at the last minute. Thereby enabling shorter response times and greater autonomy for the system under control.
Maximal Conflict Set Enumeration Algorithm Based on Locality of Petri Nets%基于Pe tri网局部性的极大冲突集枚举算法
Institute of Scientific and Technical Information of China (English)
潘理; 郑红; 刘显明; 杨勃
2016-01-01
冲突是Petri网研究的重要主题。目前Petri网冲突研究主要集中于冲突建模和冲突消解策略，而对冲突问题本身的计算复杂性却很少关注。提出Petri网的冲突集问题，并证明冲突集问题是NP（Non-deterministic Polyno-mial）完全的。提出极大冲突集动态枚举算法，该算法基于当前标识的所有极大冲突集，利用Petri网实施局部性，仅计算下一标识中受局部性影响的极大冲突集，从而避免重新枚举所有极大冲突集。该算法时间复杂度为O（m2 n），m是当前标识的极大冲突集数目，n是变迁数。最后证明自由选择网、非对称选择网的极大冲突集枚举算法复杂度可降至O（n2）。极大冲突集枚举算法研究将为Petri网冲突问题的算法求解提供理论参考。%Conflict is an essential concept in Petri net theory.The existing research focuses on the modelling and resolu-tion strategies of conflict problems,but less on the computational complexity of the problems theirselves.In this paper,we pro-pose the conflict set problem for Petri nets,and prove that the conflict set problem is NP-complete.Furthermore,we present a dynamic algorithm for the maximal conflict set enumeration.Our algorithm only computes those conflict sets that are affected by local firing,which avoids enumerating all maximal conflict sets at each marking.The algorithm needs time O(m2n)where m is the number of maximal conflict sets at the current marking and n is the number of transitions.Finally,we show that the maximal conflict set enumeration problem can be solved in O(n2)for free-choice nets and asymmetric choice nets.The results on complexity of thel conflict set problem provide a theoretical reference for solving conflict problems of Petri nets.
Taheri, Shaghayegh; Fevens, Thomas; Bui, Tien D.
2017-02-01
Computerized assessments for diagnosis or malignancy grading of cyto-histopathological specimens have drawn increased attention in the field of digital pathology. Automatic segmentation of cell nuclei is a fundamental step in such automated systems. Despite considerable research, nuclei segmentation is still a challenging task due noise, nonuniform illumination, and most importantly, in 2D projection images, overlapping and touching nuclei. In most published approaches, nuclei refinement is a post-processing step after segmentation, which usually refers to the task of detaching the aggregated nuclei or merging the over-segmented nuclei. In this work, we present a novel segmentation technique which effectively addresses the problem of individually segmenting touching or overlapping cell nuclei during the segmentation process. The proposed framework is a region-based segmentation method, which consists of three major modules: i) the image is passed through a color deconvolution step to extract the desired stains; ii) then the generalized fast radial symmetry transform is applied to the image followed by non-maxima suppression to specify the initial seed points for nuclei, and their corresponding GFRS ellipses which are interpreted as the initial nuclei borders for segmentation; iii) finally, these nuclei border initial curves are evolved through the use of a statistical level-set approach along with topology preserving criteria for segmentation and separation of nuclei at the same time. The proposed method is evaluated using Hematoxylin and Eosin, and fluorescent stained images, performing qualitative and quantitative analysis, showing that the method outperforms thresholding and watershed segmentation approaches.
Starkweather, S.; Crain, R.; Derry, K. R.
2017-12-01
Knowledge is empowering in all settings, but plays an elevated role in empowering under-represented groups in field research. Field research, particularly polar field research, has deep roots in masculinized and colonial traditions, which can lead to high barriers for women and minorities (e.g. Carey et al., 2016). While recruitment of underrepresented groups into polar field research has improved through the efforts of organizations like the Association of Polar Early Career Scientists (APECS), the experiences and successes of these participants is often contingent on the availability of specialized training opportunities or the quality of explicitly documented information about how to survive Arctic conditions or how to establish successful measurement protocols in harsh environments. In Arctic field research, knowledge is often not explicitly documented or conveyed, but learned through "experience" or informally through ad hoc advice. The advancement of field training programs and knowledge management systems suggest two means for unleashing more explicit forms of knowledge about field work. Examples will be presented along with a case for how they level the playing field and improve the experience of field work for all participants.
Energy Technology Data Exchange (ETDEWEB)
Sufyan, Muhammad; Ngo, Long Cu; Choi, Hyoung Gwon [Seoul National University, Seoul (Korea, Republic of)
2016-04-15
Unstructured grids were used to compare the performance of a direct reinitialization scheme with those of two reinitialization approaches based on the solution of a hyperbolic Partial differential equation (PDE). The problems of moving interface were solved in the context of a finite element method. A least-square weighted residual method was used to discretize the advection equation of the level set method. The benchmark problems of rotating Zalesak's disk, time-reversed single vortex, and two-dimensional sloshing were examined. Numerical results showed that the direct reinitialization scheme performed better than the PDE-based reinitialization approaches in terms of mass conservation, dissipation and dispersion error, and computational time. In the case of sloshing, numerical results were found to be in good agreement with existing experimental data. The direct reinitialization approach consumed considerably less CPU time than the PDE-based simulations for 20 time periods of sloshing. This approach was stable, accurate, and efficient for all the problems considered in this study.
Fischer, Vinicius Jobim; Morris, Jodi; Martines, José
2014-06-01
An estimated 150 million children have a disability. Early identification of developmental disabilities is a high priority for the World Health Organization to allow action to reduce impairments through Gap Action Program on mental health. The study identified the feasibility of using the developmental screening and monitoring tools for children aged 0-3 year(s) by non-specialist primary healthcare providers in low-resource settings. A systematic review of the literature was conducted to identify the tools, assess their psychometric properties, and feasibility of use in low- and middle-income countries (LMICs). Key indicators to examine feasibility in LMICs were derived from a consultation with 23 international experts. We identified 426 studies from which 14 tools used in LMICs were extracted for further examination. Three tools reported adequate psychometric properties and met most of the feasibility criteria. Three tools appear promising for use in identifying and monitoring young children with disabilities at primary healthcare level in LMICs. Further research and development are needed to optimize these tools.
DEFF Research Database (Denmark)
Mahnke, Martina; Uprichard, Emma
2014-01-01
Imagine sailing across the ocean. The sun is shining, vastness all around you. And suddenly [BOOM] you’ve hit an invisible wall. Welcome to the Truman Show! Ever since Eli Pariser published his thoughts on a potential filter bubble, this movie scenario seems to have become reality, just with slight...... changes: it’s not the ocean, it’s the internet we’re talking about, and it’s not a TV show producer, but algorithms that constitute a sort of invisible wall. Building on this assumption, most research is trying to ‘tame the algorithmic tiger’. While this is a valuable and often inspiring approach, we...
Directory of Open Access Journals (Sweden)
G.Chaitanya
2013-12-01
Full Text Available The present work aims at maximizing the overall heat transfer rate of an automobile radiator using Genetic Algorithm approach. The design specifications and empirical data pertaining to a rally car radiator obtained from literature are considered in the present work. The mathematical function describing the objective for the problem is formulated using the radiator core design equations and heat transfer relations governing the radiator. The overall heat transfer rate obtained from the present optimization technique is found to be 9.48 percent higher compared to the empirical value present in the literature. Also, the enhancement in the overall heat transfer rate is achieved with a marginal reduction in the radiator dimensions indicating better spacing ratio compared to the existing design.
Abedini, M. J.; Nasseri, M.; Burn, D. H.
2012-04-01
In any geostatistical study, an important consideration is the choice of an appropriate, repeatable, and objective search strategy that controls the nearby samples to be included in the location-specific estimation procedure. Almost all geostatistical software available in the market puts the onus on the user to supply search strategy parameters in a heuristic manner. These parameters are solely controlled by geographical coordinates that are defined for the entire area under study, and the user has no guidance as to how to choose these parameters. The main thesis of the current study is that the selection of search strategy parameters has to be driven by data—both the spatial coordinates and the sample values—and cannot be chosen beforehand. For this purpose, a genetic-algorithm-based ordinary kriging with moving neighborhood technique is proposed. The search capability of a genetic algorithm is exploited to search the feature space for appropriate, either local or global, search strategy parameters. Radius of circle/sphere and/or radii of standard or rotated ellipse/ellipsoid are considered as the decision variables to be optimized by GA. The superiority of GA-based ordinary kriging is demonstrated through application to the Wolfcamp Aquifer piezometric head data. Assessment of numerical results showed that definition of search strategy parameters based on both geographical coordinates and sample values improves cross-validation statistics when compared with that based on geographical coordinates alone. In the case of a variable search neighborhood for each estimation point, optimization of local search strategy parameters for an elliptical support domain—the orientation of which is dictated by anisotropic axes—via GA was able to capture the dynamics of piezometric head in west Texas/New Mexico in an efficient way.
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
Conde Mui\\~no, Patricia; The ATLAS collaboration
2016-01-01
General purpose Graphics Processor Units (GPGPU) are being evaluated for possible future inclusion in an upgraded ATLAS High Level Trigger farm. We have developed a demonstrator including GPGPU implementations of Inner Detector and Muon tracking and Calorimeter clustering within the ATLAS software framework. ATLAS is a general purpose particle physics experiment located on the LHC collider at CERN. The ATLAS Trigger system consists of two levels, with level 1 implemented in hardware and the High Level Trigger implemented in software running on a farm of commodity CPU. The High Level Trigger reduces the trigger rate from the 100 kHz level 1 acceptance rate to 1 kHz for recording, requiring an average per-event processing time of ~250 ms for this task. The selection in the high level trigger is based on reconstructing tracks in the Inner Detector and Muon Spectrometer and clusters of energy deposited in the Calorime