Multi-scale graph-cut algorithm for efficient water-fat separation.

Science.gov (United States)

Berglund, Johan; Skorpil, Mikael

2017-09-01

To improve the accuracy and robustness to noise in water-fat separation by unifying the multiscale and graph cut based approaches to B 0 -correction. A previously proposed water-fat separation algorithm that corrects for B 0 field inhomogeneity in 3D by a single quadratic pseudo-Boolean optimization (QPBO) graph cut was incorporated into a multi-scale framework, where field map solutions are propagated from coarse to fine scales for voxels that are not resolved by the graph cut. The accuracy of the single-scale and multi-scale QPBO algorithms was evaluated against benchmark reference datasets. The robustness to noise was evaluated by adding noise to the input data prior to water-fat separation. Both algorithms achieved the highest accuracy when compared with seven previously published methods, while computation times were acceptable for implementation in clinical routine. The multi-scale algorithm was more robust to noise than the single-scale algorithm, while causing only a small increase (+10%) of the reconstruction time. The proposed 3D multi-scale QPBO algorithm offers accurate water-fat separation, robustness to noise, and fast reconstruction. The software implementation is freely available to the research community. Magn Reson Med 78:941-949, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

Algorithming the Algorithm

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...

New recursive-least-squares algorithms for nonlinear active control of sound and vibration using neural networks.

Science.gov (United States)

Bouchard, M

2001-01-01

In recent years, a few articles describing the use of neural networks for nonlinear active control of sound and vibration were published. Using a control structure with two multilayer feedforward neural networks (one as a nonlinear controller and one as a nonlinear plant model), steepest descent algorithms based on two distinct gradient approaches were introduced for the training of the controller network. The two gradient approaches were sometimes called the filtered-x approach and the adjoint approach. Some recursive-least-squares algorithms were also introduced, using the adjoint approach. In this paper, an heuristic procedure is introduced for the development of recursive-least-squares algorithms based on the filtered-x and the adjoint gradient approaches. This leads to the development of new recursive-least-squares algorithms for the training of the controller neural network in the two networks structure. These new algorithms produce a better convergence performance than previously published algorithms. Differences in the performance of algorithms using the filtered-x and the adjoint gradient approaches are discussed in the paper. The computational load of the algorithms discussed in the paper is evaluated for multichannel systems of nonlinear active control. Simulation results are presented to compare the convergence performance of the algorithms, showing the convergence gain provided by the new algorithms.

Optimization of wind farm turbines layout using an evolutive algorithm

International Nuclear Information System (INIS)

Gonzalez, Javier Serrano; Santos, Jesus Riquelme; Payan, Manuel Burgos; Gonzalez Rodriguez, Angel G.; Mora, Jose Castro

2010-01-01

The optimum wind farm configuration problem is discussed in this paper and an evolutive algorithm to optimize the wind farm layout is proposed. The algorithm's optimization process is based on a global wind farm cost model using the initial investment and the present value of the yearly net cash flow during the entire wind-farm life span. The proposed algorithm calculates the yearly income due to the sale of the net generated energy taking into account the individual wind turbine loss of production due to wake decay effects and it can deal with areas or terrains with non-uniform load-bearing capacity soil and different roughness length for every wind direction or restrictions such as forbidden areas or limitations in the number of wind turbines or the investment. The results are first favorably compared with those previously published and a second collection of test cases is used to proof the performance and suitability of the proposed evolutive algorithm to find the optimum wind farm configuration. (author)

Parallel algorithms for placement and routing in VLSI design. Ph.D. Thesis

Science.gov (United States)

Brouwer, Randall Jay

1991-01-01

The computational requirements for high quality synthesis, analysis, and verification of very large scale integration (VLSI) designs have rapidly increased with the fast growing complexity of these designs. Research in the past has focused on the development of heuristic algorithms, special purpose hardware accelerators, or parallel algorithms for the numerous design tasks to decrease the time required for solution. Two new parallel algorithms are proposed for two VLSI synthesis tasks, standard cell placement and global routing. The first algorithm, a parallel algorithm for global routing, uses hierarchical techniques to decompose the routing problem into independent routing subproblems that are solved in parallel. Results are then presented which compare the routing quality to the results of other published global routers and which evaluate the speedups attained. The second algorithm, a parallel algorithm for cell placement and global routing, hierarchically integrates a quadrisection placement algorithm, a bisection placement algorithm, and the previous global routing algorithm. Unique partitioning techniques are used to decompose the various stages of the algorithm into independent tasks which can be evaluated in parallel. Finally, results are presented which evaluate the various algorithm alternatives and compare the algorithm performance to other placement programs. Measurements are presented on the parallel speedups available.

Availability of nuclear decay data in electronic form, including beta spectra not previously published

International Nuclear Information System (INIS)

Eckerman, K.F.; Westfall, R.J.; Ryman, J.C.; Cristy, M.

1994-01-01

The unabridged data used in preparing ICRP Publication 38 (1983) and a monograph of the Medical Internal Radiation Dose (MIRD) Committee are now available in electronic form. The open-quotes ICRP38 collectionclose quotes contains data on the energies and intensities of radiations emitted by 825 radionuclides (those in ICRP Publication 38 plus 13 from the MIRD monograph), and the open-quotes MIRD collectionclose quotes contains data on 242 radionuclides. Each collection consists of a radiations data file and a beta spectra data file. The radiations data file contains the complete listing of the emitted radiations, their types, mean or unique energies, and absolute intensities for each radionuclide, the probability that a beta particle will be emitted with kinetic energies defined by a standard energy grid. Although summary information from the radiation data files has been published, neither the unabridged data nor the beta spectra have been published. These data files and a data extraction utility, which runs on a personal computer, are available from the Radiation Shielding Information Center at Oak Ridge National Laboratory. 13 refs., 1 fig., 6 tabs

Genetic Algorithm Applied to the Eigenvalue Equalization Filtered-x LMS Algorithm (EE-FXLMS

Directory of Open Access Journals (Sweden)

Stephan P. Lovstedt

2008-01-01

Full Text Available The FXLMS algorithm, used extensively in active noise control (ANC, exhibits frequency-dependent convergence behavior. This leads to degraded performance for time-varying tonal noise and noise with multiple stationary tones. Previous work by the authors proposed the eigenvalue equalization filtered-x least mean squares (EE-FXLMS algorithm. For that algorithm, magnitude coefficients of the secondary path transfer function are modified to decrease variation in the eigenvalues of the filtered-x autocorrelation matrix, while preserving the phase, giving faster convergence and increasing overall attenuation. This paper revisits the EE-FXLMS algorithm, using a genetic algorithm to find magnitude coefficients that give the least variation in eigenvalues. This method overcomes some of the problems with implementing the EE-FXLMS algorithm arising from finite resolution of sampled systems. Experimental control results using the original secondary path model, and a modified secondary path model for both the previous implementation of EE-FXLMS and the genetic algorithm implementation are compared.

Compilation of new and previously published geochemical and modal data for Mesoproterozoic igneous rocks of the St. Francois Mountains, southeast Missouri

Science.gov (United States)

du Bray, Edward A.; Day, Warren C.; Meighan, Corey J.

2018-04-16

The purpose of this report is to present recently acquired as well as previously published geochemical and modal petrographic data for igneous rocks in the St. Francois Mountains, southeast Missouri, as part of an ongoing effort to understand the regional geology and ore deposits of the Mesoproterozoic basement rocks of southeast Missouri, USA. The report includes geochemical data that is (1) newly acquired by the U.S. Geological Survey and (2) compiled from numerous sources published during the last fifty-five years. These data are required for ongoing petrogenetic investigations of these rocks. Voluminous Mesoproterozoic igneous rocks in the St. Francois Mountains of southeast Missouri constitute the basement buried beneath Paleozoic sedimentary rock that is over 600 meters thick in places. The Mesoproterozoic rocks of southeast Missouri represent a significant component of approximately 1.4 billion-year-old (Ga) igneous rocks that crop out extensively in North America along the southeast margin of Laurentia and subsequent researchers suggested that iron oxide-copper deposits in the St. Francois Mountains are genetically associated with ca. 1.4 Ga magmatism in this region. The geochemical and modal data sets described herein were compiled to support investigations concerning the tectonic setting and petrologic processes responsible for the associated magmatism.

List of new names and new combinations previously effectively, but not validly, published.

Science.gov (United States)

2008-09-01

The purpose of this announcement is to effect the valid publication of the following effectively published new names and new combinations under the procedure described in the Bacteriological Code (1990 Revision). Authors and other individuals wishing to have new names and/or combinations included in future lists should send three copies of the pertinent reprint or photocopies thereof, or an electronic copy of the published paper, to the IJSEM Editorial Office for confirmation that all of the other requirements for valid publication have been met. It is also a requirement of IJSEM and the ICSP that authors of new species, new subspecies and new combinations provide evidence that types are deposited in two recognized culture collections in two different countries (i.e. documents certifying deposition and availability of type strains). It should be noted that the date of valid publication of these new names and combinations is the date of publication of this list, not the date of the original publication of the names and combinations. The authors of the new names and combinations are as given below, and these authors' names will be included in the author index of the present issue and in the volume author index. Inclusion of a name on these lists validates the publication of the name and thereby makes it available in bacteriological nomenclature. The inclusion of a name on this list is not to be construed as taxonomic acceptance of the taxon to which the name is applied. Indeed, some of these names may, in time, be shown to be synonyms, or the organisms may be transferred to another genus, thus necessitating the creation of a new combination.

Low-dose computed tomography image restoration using previous normal-dose scan

International Nuclear Information System (INIS)

Ma, Jianhua; Huang, Jing; Feng, Qianjin; Zhang, Hua; Lu, Hongbing; Liang, Zhengrong; Chen, Wufan

2011-01-01

Purpose: In current computed tomography (CT) examinations, the associated x-ray radiation dose is of a significant concern to patients and operators. A simple and cost-effective means to perform the examinations is to lower the milliampere-seconds (mAs) or kVp parameter (or delivering less x-ray energy to the body) as low as reasonably achievable in data acquisition. However, lowering the mAs parameter will unavoidably increase data noise and the noise would propagate into the CT image if no adequate noise control is applied during image reconstruction. Since a normal-dose high diagnostic CT image scanned previously may be available in some clinical applications, such as CT perfusion imaging and CT angiography (CTA), this paper presents an innovative way to utilize the normal-dose scan as a priori information to induce signal restoration of the current low-dose CT image series. Methods: Unlike conventional local operations on neighboring image voxels, nonlocal means (NLM) algorithm utilizes the redundancy of information across the whole image. This paper adapts the NLM to utilize the redundancy of information in the previous normal-dose scan and further exploits ways to optimize the nonlocal weights for low-dose image restoration in the NLM framework. The resulting algorithm is called the previous normal-dose scan induced nonlocal means (ndiNLM). Because of the optimized nature of nonlocal weights calculation, the ndiNLM algorithm does not depend heavily on image registration between the current low-dose and the previous normal-dose CT scans. Furthermore, the smoothing parameter involved in the ndiNLM algorithm can be adaptively estimated based on the image noise relationship between the current low-dose and the previous normal-dose scanning protocols. Results: Qualitative and quantitative evaluations were carried out on a physical phantom as well as clinical abdominal and brain perfusion CT scans in terms of accuracy and resolution properties. The gain by the use

Genetic algorithms and fuzzy multiobjective optimization

CERN Document Server

Sakawa, Masatoshi

2002-01-01

Since the introduction of genetic algorithms in the 1970s, an enormous number of articles together with several significant monographs and books have been published on this methodology. As a result, genetic algorithms have made a major contribution to optimization, adaptation, and learning in a wide variety of unexpected fields. Over the years, many excellent books in genetic algorithm optimization have been published; however, they focus mainly on single-objective discrete or other hard optimization problems under certainty. There appears to be no book that is designed to present genetic algorithms for solving not only single-objective but also fuzzy and multiobjective optimization problems in a unified way. Genetic Algorithms And Fuzzy Multiobjective Optimization introduces the latest advances in the field of genetic algorithm optimization for 0-1 programming, integer programming, nonconvex programming, and job-shop scheduling problems under multiobjectiveness and fuzziness. In addition, the book treats a w...

Transition to electronic publishing

Science.gov (United States)

Bowning, Sam

Previous communications have described some of the many changes that will occur in the next few months as AGU makes the transition to fully electronic publishing. With the advent of the new AGU electronic publishing system, manuscripts will be submitted, edited, reviewed, and published in electronic formats. This piece discusses how the electronic journals will differ from the print journals. Electronic publishing will require some adjustments to the ways we currently think about journals from our perspective of standard print versions. Visiting the Web site of AGU's Geochemistry, Geophysics, Geosystems (G-Cubed) is a great way to get familiar with the look and feel of electronic publishing. However, protocols, especially for citations of articles, are still evolving. Some of the biggest changes for users of AGU publications may be the lack of page numbers, the use of a unique identifier (DOI),and changes in citation style.

Clinical algorithms to aid osteoarthritis guideline dissemination.

Science.gov (United States)

Meneses, S R F; Goode, A P; Nelson, A E; Lin, J; Jordan, J M; Allen, K D; Bennell, K L; Lohmander, L S; Fernandes, L; Hochberg, M C; Underwood, M; Conaghan, P G; Liu, S; McAlindon, T E; Golightly, Y M; Hunter, D J

2016-09-01

Numerous scientific organisations have developed evidence-based recommendations aiming to optimise the management of osteoarthritis (OA). Uptake, however, has been suboptimal. The purpose of this exercise was to harmonize the recent recommendations and develop a user-friendly treatment algorithm to facilitate translation of evidence into practice. We updated a previous systematic review on clinical practice guidelines (CPGs) for OA management. The guidelines were assessed using the Appraisal of Guidelines for Research and Evaluation for quality and the standards for developing trustworthy CPGs as established by the National Academy of Medicine (NAM). Four case scenarios and algorithms were developed by consensus of a multidisciplinary panel. Sixteen guidelines were included in the systematic review. Most recommendations were directed toward physicians and allied health professionals, and most had multi-disciplinary input. Analysis for trustworthiness suggests that many guidelines still present a lack of transparency. A treatment algorithm was developed for each case scenario advised by recommendations from guidelines and based on panel consensus. Strategies to facilitate the implementation of guidelines in clinical practice are necessary. The algorithms proposed are examples of how to apply recommendations in the clinical context, helping the clinician to visualise the patient flow and timing of different treatment modalities. Copyright © 2016 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved.

Arctic lead detection using a waveform mixture algorithm from CryoSat-2 data

Science.gov (United States)

Lee, Sanggyun; Kim, Hyun-cheol; Im, Jungho

2018-05-01

We propose a waveform mixture algorithm to detect leads from CryoSat-2 data, which is novel and different from the existing threshold-based lead detection methods. The waveform mixture algorithm adopts the concept of spectral mixture analysis, which is widely used in the field of hyperspectral image analysis. This lead detection method was evaluated with high-resolution (250 m) MODIS images and showed comparable and promising performance in detecting leads when compared to the previous methods. The robustness of the proposed approach also lies in the fact that it does not require the rescaling of parameters (i.e., stack standard deviation, stack skewness, stack kurtosis, pulse peakiness, and backscatter σ0), as it directly uses L1B waveform data, unlike the existing threshold-based methods. Monthly lead fraction maps were produced by the waveform mixture algorithm, which shows interannual variability of recent sea ice cover during 2011-2016, excluding the summer season (i.e., June to September). We also compared the lead fraction maps to other lead fraction maps generated from previously published data sets, resulting in similar spatiotemporal patterns.

A GPU-based finite-size pencil beam algorithm with 3D-density correction for radiotherapy dose calculation

International Nuclear Information System (INIS)

Gu Xuejun; Jia Xun; Jiang, Steve B; Jelen, Urszula; Li Jinsheng

2011-01-01

Targeting at the development of an accurate and efficient dose calculation engine for online adaptive radiotherapy, we have implemented a finite-size pencil beam (FSPB) algorithm with a 3D-density correction method on graphics processing unit (GPU). This new GPU-based dose engine is built on our previously published ultrafast FSPB computational framework (Gu et al 2009 Phys. Med. Biol. 54 6287-97). Dosimetric evaluations against Monte Carlo dose calculations are conducted on ten IMRT treatment plans (five head-and-neck cases and five lung cases). For all cases, there is improvement with the 3D-density correction over the conventional FSPB algorithm and for most cases the improvement is significant. Regarding the efficiency, because of the appropriate arrangement of memory access and the usage of GPU intrinsic functions, the dose calculation for an IMRT plan can be accomplished well within 1 s (except for one case) with this new GPU-based FSPB algorithm. Compared to the previous GPU-based FSPB algorithm without 3D-density correction, this new algorithm, though slightly sacrificing the computational efficiency (∼5-15% lower), has significantly improved the dose calculation accuracy, making it more suitable for online IMRT replanning.

Using the genome aggregation database, computational pathogenicity prediction tools, and patch clamp heterologous expression studies to demote previously published long QT syndrome type 1 mutations from pathogenic to benign.

Science.gov (United States)

Clemens, Daniel J; Lentino, Anne R; Kapplinger, Jamie D; Ye, Dan; Zhou, Wei; Tester, David J; Ackerman, Michael J

2018-04-01

Mutations in the KCNQ1-encoded Kv7.1 potassium channel cause long QT syndrome (LQTS) type 1 (LQT1). It has been suggested that ∼10%-20% of rare LQTS case-derived variants in the literature may have been published erroneously as LQT1-causative mutations and may be "false positives." The purpose of this study was to determine which previously published KCNQ1 case variants are likely false positives. A list of all published, case-derived KCNQ1 missense variants (MVs) was compiled. The occurrence of each MV within the Genome Aggregation Database (gnomAD) was assessed. Eight in silico tools were used to predict each variant's pathogenicity. Case-derived variants that were either (1) too frequently found in gnomAD or (2) absent in gnomAD but predicted to be pathogenic by ≤2 tools were considered potential false positives. Three of these variants were characterized functionally using whole-cell patch clamp technique. Overall, there were 244 KCNQ1 case-derived MVs. Of these, 29 (12%) were seen in ≥10 individuals in gnomAD and are demotable. However, 157 of 244 MVs (64%) were absent in gnomAD. Of these, 7 (4%) were predicted to be pathogenic by ≤2 tools, 3 of which we characterized functionally. There was no significant difference in current density between heterozygous KCNQ1-F127L, -P477L, or -L619M variant-containing channels compared to KCNQ1-WT. This study offers preliminary evidence for the demotion of 32 (13%) previously published LQT1 MVs. Of these, 29 were demoted because of their frequent sighting in gnomAD. Additionally, in silico analysis and in vitro functional studies have facilitated the demotion of 3 ultra-rare MVs (F127L, P477L, L619M). Copyright © 2017 Heart Rhythm Society. Published by Elsevier Inc. All rights reserved.

Efficient sequential and parallel algorithms for record linkage.

Science.gov (United States)

Mamun, Abdullah-Al; Mi, Tian; Aseltine, Robert; Rajasekaran, Sanguthevar

2014-01-01

Integrating data from multiple sources is a crucial and challenging problem. Even though there exist numerous algorithms for record linkage or deduplication, they suffer from either large time needs or restrictions on the number of datasets that they can integrate. In this paper we report efficient sequential and parallel algorithms for record linkage which handle any number of datasets and outperform previous algorithms. Our algorithms employ hierarchical clustering algorithms as the basis. A key idea that we use is radix sorting on certain attributes to eliminate identical records before any further processing. Another novel idea is to form a graph that links similar records and find the connected components. Our sequential and parallel algorithms have been tested on a real dataset of 1,083,878 records and synthetic datasets ranging in size from 50,000 to 9,000,000 records. Our sequential algorithm runs at least two times faster, for any dataset, than the previous best-known algorithm, the two-phase algorithm using faster computation of the edit distance (TPA (FCED)). The speedups obtained by our parallel algorithm are almost linear. For example, we get a speedup of 7.5 with 8 cores (residing in a single node), 14.1 with 16 cores (residing in two nodes), and 26.4 with 32 cores (residing in four nodes). We have compared the performance of our sequential algorithm with TPA (FCED) and found that our algorithm outperforms the previous one. The accuracy is the same as that of this previous best-known algorithm.

Greedy Algorithms for Nonnegativity-Constrained Simultaneous Sparse Recovery

Science.gov (United States)

Kim, Daeun; Haldar, Justin P.

2016-01-01

This work proposes a family of greedy algorithms to jointly reconstruct a set of vectors that are (i) nonnegative and (ii) simultaneously sparse with a shared support set. The proposed algorithms generalize previous approaches that were designed to impose these constraints individually. Similar to previous greedy algorithms for sparse recovery, the proposed algorithms iteratively identify promising support indices. In contrast to previous approaches, the support index selection procedure has been adapted to prioritize indices that are consistent with both the nonnegativity and shared support constraints. Empirical results demonstrate for the first time that the combined use of simultaneous sparsity and nonnegativity constraints can substantially improve recovery performance relative to existing greedy algorithms that impose less signal structure. PMID:26973368

Training nuclei detection algorithms with simple annotations

Directory of Open Access Journals (Sweden)

Henning Kost

2017-01-01

Full Text Available Background: Generating good training datasets is essential for machine learning-based nuclei detection methods. However, creating exhaustive nuclei contour annotations, to derive optimal training data from, is often infeasible. Methods: We compared different approaches for training nuclei detection methods solely based on nucleus center markers. Such markers contain less accurate information, especially with regard to nuclear boundaries, but can be produced much easier and in greater quantities. The approaches use different automated sample extraction methods to derive image positions and class labels from nucleus center markers. In addition, the approaches use different automated sample selection methods to improve the detection quality of the classification algorithm and reduce the run time of the training process. We evaluated the approaches based on a previously published generic nuclei detection algorithm and a set of Ki-67-stained breast cancer images. Results: A Voronoi tessellation-based sample extraction method produced the best performing training sets. However, subsampling of the extracted training samples was crucial. Even simple class balancing improved the detection quality considerably. The incorporation of active learning led to a further increase in detection quality. Conclusions: With appropriate sample extraction and selection methods, nuclei detection algorithms trained on the basis of simple center marker annotations can produce comparable quality to algorithms trained on conventionally created training sets.

A Global algorithm for linear radiosity

OpenAIRE

Sbert Cassasayas, Mateu; Pueyo Sánchez, Xavier

1993-01-01

A linear algorithm for radiosity is presented, linear both in time and storage. The new algorithm is based on previous work by the authors and on the well known algorithms for progressive radiosity and Monte Carlo particle transport.

Arctic lead detection using a waveform mixture algorithm from CryoSat-2 data

Directory of Open Access Journals (Sweden)

S. Lee

2018-05-01

Full Text Available We propose a waveform mixture algorithm to detect leads from CryoSat-2 data, which is novel and different from the existing threshold-based lead detection methods. The waveform mixture algorithm adopts the concept of spectral mixture analysis, which is widely used in the field of hyperspectral image analysis. This lead detection method was evaluated with high-resolution (250 m MODIS images and showed comparable and promising performance in detecting leads when compared to the previous methods. The robustness of the proposed approach also lies in the fact that it does not require the rescaling of parameters (i.e., stack standard deviation, stack skewness, stack kurtosis, pulse peakiness, and backscatter σ0, as it directly uses L1B waveform data, unlike the existing threshold-based methods. Monthly lead fraction maps were produced by the waveform mixture algorithm, which shows interannual variability of recent sea ice cover during 2011–2016, excluding the summer season (i.e., June to September. We also compared the lead fraction maps to other lead fraction maps generated from previously published data sets, resulting in similar spatiotemporal patterns.

Using Genetic Algorithm and MODFLOW to Characterize Aquifer System of Northwest Florida (Published Proceedings)

Science.gov (United States)

By integrating Genetic Algorithm and MODFLOW2005, an optimizing tool is developed to characterize the aquifer system of Region II, Northwest Florida. The history and the newest available observation data of the aquifer system is fitted automatically by using the numerical model c...

Filtered-X Affine Projection Algorithms for Active Noise Control Using Volterra Filters

Directory of Open Access Journals (Sweden)

Sicuranza Giovanni L

2004-01-01

Full Text Available We consider the use of adaptive Volterra filters, implemented in the form of multichannel filter banks, as nonlinear active noise controllers. In particular, we discuss the derivation of filtered-X affine projection algorithms for homogeneous quadratic filters. According to the multichannel approach, it is then easy to pass from these algorithms to those of a generic Volterra filter. It is shown in the paper that the AP technique offers better convergence and tracking capabilities than the classical LMS and NLMS algorithms usually applied in nonlinear active noise controllers, with a limited complexity increase. This paper extends in two ways the content of a previous contribution published in Proc. IEEE-EURASIP Workshop on Nonlinear Signal and Image Processing (NSIP '03, Grado, Italy, June 2003. First of all, a general adaptation algorithm valid for any order of affine projections is presented. Secondly, a more complete set of experiments is reported. In particular, the effects of using multichannel filter banks with a reduced number of channels are investigated and relevant results are shown.

Can We Train Machine Learning Methods to Outperform the High-dimensional Propensity Score Algorithm?

Science.gov (United States)

Karim, Mohammad Ehsanul; Pang, Menglan; Platt, Robert W

2018-03-01

The use of retrospective health care claims datasets is frequently criticized for the lack of complete information on potential confounders. Utilizing patient's health status-related information from claims datasets as surrogates or proxies for mismeasured and unobserved confounders, the high-dimensional propensity score algorithm enables us to reduce bias. Using a previously published cohort study of postmyocardial infarction statin use (1998-2012), we compare the performance of the algorithm with a number of popular machine learning approaches for confounder selection in high-dimensional covariate spaces: random forest, least absolute shrinkage and selection operator, and elastic net. Our results suggest that, when the data analysis is done with epidemiologic principles in mind, machine learning methods perform as well as the high-dimensional propensity score algorithm. Using a plasmode framework that mimicked the empirical data, we also showed that a hybrid of machine learning and high-dimensional propensity score algorithms generally perform slightly better than both in terms of mean squared error, when a bias-based analysis is used.

Ripple FPN reduced algorithm based on temporal high-pass filter and hardware implementation

Science.gov (United States)

Li, Yiyang; Li, Shuo; Zhang, Zhipeng; Jin, Weiqi; Wu, Lei; Jin, Minglei

2016-11-01

Cooled infrared detector arrays always suffer from undesired Ripple Fixed-Pattern Noise (FPN) when observe the scene of sky. The Ripple Fixed-Pattern Noise seriously affect the imaging quality of thermal imager, especially for small target detection and tracking. It is hard to eliminate the FPN by the Calibration based techniques and the current scene-based nonuniformity algorithms. In this paper, we present a modified space low-pass and temporal high-pass nonuniformity correction algorithm using adaptive time domain threshold (THP&GM). The threshold is designed to significantly reduce ghosting artifacts. We test the algorithm on real infrared in comparison to several previously published methods. This algorithm not only can effectively correct common FPN such as Stripe, but also has obviously advantage compared with the current methods in terms of detail protection and convergence speed, especially for Ripple FPN correction. Furthermore, we display our architecture with a prototype built on a Xilinx Virtex-5 XC5VLX50T field-programmable gate array (FPGA). The hardware implementation of the algorithm based on FPGA has two advantages: (1) low resources consumption, and (2) small hardware delay (less than 20 lines). The hardware has been successfully applied in actual system.

Testing the performance of empirical remote sensing algorithms in the Baltic Sea waters with modelled and in situ reflectance data

Directory of Open Access Journals (Sweden)

Martin Ligi

2017-01-01

Full Text Available Remote sensing studies published up to now show that the performance of empirical (band-ratio type algorithms in different parts of the Baltic Sea is highly variable. Best performing algorithms are different in the different regions of the Baltic Sea. Moreover, there is indication that the algorithms have to be seasonal as the optical properties of phytoplankton assemblages dominating in spring and summer are different. We modelled 15,600 reflectance spectra using HydroLight radiative transfer model to test 58 previously published empirical algorithms. 7200 of the spectra were modelled using specific inherent optical properties (SIOPs of the open parts of the Baltic Sea in summer and 8400 with SIOPs of spring season. Concentration range of chlorophyll-a, coloured dissolved organic matter (CDOM and suspended matter used in the model simulations were based on the actually measured values available in literature. For each optically active constituent we added one concentration below actually measured minimum and one concentration above the actually measured maximum value in order to test the performance of the algorithms in wider range. 77 in situ reflectance spectra from rocky (Sweden and sandy (Estonia, Latvia coastal areas were used to evaluate the performance of the algorithms also in coastal waters. Seasonal differences in the algorithm performance were confirmed but we found also algorithms that can be used in both spring and summer conditions. The algorithms that use bands available on OLCI, launched in February 2016, are highlighted as this sensor will be available for Baltic Sea monitoring for coming decades.

Optimal Fungal Space Searching Algorithms.

Science.gov (United States)

Asenova, Elitsa; Lin, Hsin-Yu; Fu, Eileen; Nicolau, Dan V; Nicolau, Dan V

2016-10-01

Previous experiments have shown that fungi use an efficient natural algorithm for searching the space available for their growth in micro-confined networks, e.g., mazes. This natural "master" algorithm, which comprises two "slave" sub-algorithms, i.e., collision-induced branching and directional memory, has been shown to be more efficient than alternatives, with one, or the other, or both sub-algorithms turned off. In contrast, the present contribution compares the performance of the fungal natural algorithm against several standard artificial homologues. It was found that the space-searching fungal algorithm consistently outperforms uninformed algorithms, such as Depth-First-Search (DFS). Furthermore, while the natural algorithm is inferior to informed ones, such as A*, this under-performance does not importantly increase with the increase of the size of the maze. These findings suggest that a systematic effort of harvesting the natural space searching algorithms used by microorganisms is warranted and possibly overdue. These natural algorithms, if efficient, can be reverse-engineered for graph and tree search strategies.

Successive combination jet algorithm for hadron collisions

International Nuclear Information System (INIS)

Ellis, S.D.; Soper, D.E.

1993-01-01

Jet finding algorithms, as they are used in e + e- and hadron collisions, are reviewed and compared. It is suggested that a successive combination style algorithm, similar to that used in e + e- physics, might be useful also in hadron collisions, where cone style algorithms have been used previously

A numeric comparison of variable selection algorithms for supervised learning

International Nuclear Information System (INIS)

Palombo, G.; Narsky, I.

2009-01-01

Datasets in modern High Energy Physics (HEP) experiments are often described by dozens or even hundreds of input variables. Reducing a full variable set to a subset that most completely represents information about data is therefore an important task in analysis of HEP data. We compare various variable selection algorithms for supervised learning using several datasets such as, for instance, imaging gamma-ray Cherenkov telescope (MAGIC) data found at the UCI repository. We use classifiers and variable selection methods implemented in the statistical package StatPatternRecognition (SPR), a free open-source C++ package developed in the HEP community ( (http://sourceforge.net/projects/statpatrec/)). For each dataset, we select a powerful classifier and estimate its learning accuracy on variable subsets obtained by various selection algorithms. When possible, we also estimate the CPU time needed for the variable subset selection. The results of this analysis are compared with those published previously for these datasets using other statistical packages such as R and Weka. We show that the most accurate, yet slowest, method is a wrapper algorithm known as generalized sequential forward selection ('Add N Remove R') implemented in SPR.

Group leaders optimization algorithm

Science.gov (United States)

Daskin, Anmer; Kais, Sabre

2011-03-01

We present a new global optimization algorithm in which the influence of the leaders in social groups is used as an inspiration for the evolutionary technique which is designed into a group architecture. To demonstrate the efficiency of the method, a standard suite of single and multi-dimensional optimization functions along with the energies and the geometric structures of Lennard-Jones clusters are given as well as the application of the algorithm on quantum circuit design problems. We show that as an improvement over previous methods, the algorithm scales as N 2.5 for the Lennard-Jones clusters of N-particles. In addition, an efficient circuit design is shown for a two-qubit Grover search algorithm which is a quantum algorithm providing quadratic speedup over the classical counterpart.

Variable depth recursion algorithm for leaf sequencing

International Nuclear Information System (INIS)

Siochi, R. Alfredo C.

2007-01-01

The processes of extraction and sweep are basic segmentation steps that are used in leaf sequencing algorithms. A modified version of a commercial leaf sequencer changed the way that the extracts are selected and expanded the search space, but the modification maintained the basic search paradigm of evaluating multiple solutions, each one consisting of up to 12 extracts and a sweep sequence. While it generated the best solutions compared to other published algorithms, it used more computation time. A new, faster algorithm selects one extract at a time but calls itself as an evaluation function a user-specified number of times, after which it uses the bidirectional sweeping window algorithm as the final evaluation function. To achieve a performance comparable to that of the modified commercial leaf sequencer, 2-3 calls were needed, and in all test cases, there were only slight improvements beyond two calls. For the 13 clinical test maps, computation speeds improved by a factor between 12 and 43, depending on the constraints, namely the ability to interdigitate and the avoidance of the tongue-and-groove under dose. The new algorithm was compared to the original and modified versions of the commercial leaf sequencer. It was also compared to other published algorithms for 1400, random, 15x15, test maps with 3-16 intensity levels. In every single case the new algorithm provided the best solution

Multispecies Coevolution Particle Swarm Optimization Based on Previous Search History

Directory of Open Access Journals (Sweden)

Danping Wang

2017-01-01

Full Text Available A hybrid coevolution particle swarm optimization algorithm with dynamic multispecies strategy based on K-means clustering and nonrevisit strategy based on Binary Space Partitioning fitness tree (called MCPSO-PSH is proposed. Previous search history memorized into the Binary Space Partitioning fitness tree can effectively restrain the individuals’ revisit phenomenon. The whole population is partitioned into several subspecies and cooperative coevolution is realized by an information communication mechanism between subspecies, which can enhance the global search ability of particles and avoid premature convergence to local optimum. To demonstrate the power of the method, comparisons between the proposed algorithm and state-of-the-art algorithms are grouped into two categories: 10 basic benchmark functions (10-dimensional and 30-dimensional, 10 CEC2005 benchmark functions (30-dimensional, and a real-world problem (multilevel image segmentation problems. Experimental results show that MCPSO-PSH displays a competitive performance compared to the other swarm-based or evolutionary algorithms in terms of solution accuracy and statistical tests.

Efficient Record Linkage Algorithms Using Complete Linkage Clustering.

Science.gov (United States)

Mamun, Abdullah-Al; Aseltine, Robert; Rajasekaran, Sanguthevar

2016-01-01

Data from different agencies share data of the same individuals. Linking these datasets to identify all the records belonging to the same individuals is a crucial and challenging problem, especially given the large volumes of data. A large number of available algorithms for record linkage are prone to either time inefficiency or low-accuracy in finding matches and non-matches among the records. In this paper we propose efficient as well as reliable sequential and parallel algorithms for the record linkage problem employing hierarchical clustering methods. We employ complete linkage hierarchical clustering algorithms to address this problem. In addition to hierarchical clustering, we also use two other techniques: elimination of duplicate records and blocking. Our algorithms use sorting as a sub-routine to identify identical copies of records. We have tested our algorithms on datasets with millions of synthetic records. Experimental results show that our algorithms achieve nearly 100% accuracy. Parallel implementations achieve almost linear speedups. Time complexities of these algorithms do not exceed those of previous best-known algorithms. Our proposed algorithms outperform previous best-known algorithms in terms of accuracy consuming reasonable run times.

Line-breaking algorithm enhancement in inverse typesetting paradigma

Directory of Open Access Journals (Sweden)

Jan Přichystal

2007-01-01

Full Text Available High quality text preparing using computer desktop publishing systems usually uses line-breaking algorithm which cannot make provision for line heights and typeset paragraph accurately when composition width, page break, line index or other object appears. This article deals with enhancing of line-breaking algorithm based on optimum-fit algorithm. This algorithm is enhanced with calculation of immediate typesetting width and thus solves problem of forced change. Line-breaking algorithm enhancement causes expansion potentialities of high-quality typesetting in cases that have not been yet covered with present typesetting systems.

To develop a universal gamut mapping algorithm

International Nuclear Information System (INIS)

Morovic, J.

1998-10-01

When a colour image from one colour reproduction medium (e.g. nature, a monitor) needs to be reproduced on another (e.g. on a monitor or in print) and these media have different colour ranges (gamuts), it is necessary to have a method for mapping between them. If such a gamut mapping algorithm can be used under a wide range of conditions, it can also be incorporated in an automated colour reproduction system and considered to be in some sense universal. In terms of preliminary work, a colour reproduction system was implemented, for which a new printer characterisation model (including grey-scale correction) was developed. Methods were also developed for calculating gamut boundary descriptors and for calculating gamut boundaries along given lines from them. The gamut mapping solution proposed in this thesis is a gamut compression algorithm developed with the aim of being accurate and universally applicable. It was arrived at by way of an evolutionary gamut mapping development strategy for the purposes of which five test images were reproduced between a CRT and printed media obtained using an inkjet printer. Initially, a number of previously published algorithms were chosen and psychophysically evaluated whereby an important characteristic of this evaluation was that it also considered the performance of algorithms for individual colour regions within the test images used. New algorithms were then developed on their basis, subsequently evaluated and this process was repeated once more. In this series of experiments the new GCUSP algorithm, which consists of a chroma-dependent lightness compression followed by a compression towards the lightness of the reproduction cusp on the lightness axis, gave the most accurate and stable performance overall. The results of these experiments were also useful for improving the understanding of some gamut mapping factors - in particular gamut difference. In addition to looking at accuracy, the pleasantness of reproductions obtained

Rapid fish stock depletion in previously unexploited seamounts: the ...

African Journals Online (AJOL)

Rapid fish stock depletion in previously unexploited seamounts: the case of Beryx splendens from the Sierra Leone Rise (Gulf of Guinea) ... A spectral analysis and red-noise spectra procedure (REDFIT) algorithm was used to identify the red-noise spectrum from the gaps in the observed time-series of catch per unit effort by ...

Assessing the effectiveness of Landsat 8 chlorophyll a retrieval algorithms for regional freshwater monitoring.

Science.gov (United States)

Boucher, Jonah; Weathers, Kathleen C; Norouzi, Hamid; Steele, Bethel

2018-06-01

Predicting algal blooms has become a priority for scientists, municipalities, businesses, and citizens. Remote sensing offers solutions to the spatial and temporal challenges facing existing lake research and monitoring programs that rely primarily on high-investment, in situ measurements. Techniques to remotely measure chlorophyll a (chl a) as a proxy for algal biomass have been limited to specific large water bodies in particular seasons and narrow chl a ranges. Thus, a first step toward prediction of algal blooms is generating regionally robust algorithms using in situ and remote sensing data. This study explores the relationship between in-lake measured chl a data from Maine and New Hampshire, USA lakes and remotely sensed chl a retrieval algorithm outputs. Landsat 8 images were obtained and then processed after required atmospheric and radiometric corrections. Six previously developed algorithms were tested on a regional scale on 11 scenes from 2013 to 2015 covering 192 lakes. The best performing algorithm across data from both states had a 0.16 correlation coefficient (R 2 ) and P ≤ 0.05 when Landsat 8 images within 5 d, and improved to R 2 of 0.25 when data from Maine only were used. The strength of the correlation varied with the specificity of the time window in relation to the in-situ sampling date, explaining up to 27% of the variation in the data across several scenes. Two previously published algorithms using Landsat 8's Bands 1-4 were best correlated with chl a, and for particular late-summer scenes, they accounted for up to 69% of the variation in in-situ measurements. A sensitivity analysis revealed that a longer time difference between in situ measurements and the satellite image increased uncertainty in the models, and an effect of the time of year on several indices was demonstrated. A regional model based on the best performing remote sensing algorithm was developed and was validated using independent in situ measurements and satellite

PCIU: Hardware Implementations of an Efficient Packet Classification Algorithm with an Incremental Update Capability

Directory of Open Access Journals (Sweden)

O. Ahmed

2011-01-01

Full Text Available Packet classification plays a crucial role for a number of network services such as policy-based routing, firewalls, and traffic billing, to name a few. However, classification can be a bottleneck in the above-mentioned applications if not implemented properly and efficiently. In this paper, we propose PCIU, a novel classification algorithm, which improves upon previously published work. PCIU provides lower preprocessing time, lower memory consumption, ease of incremental rule update, and reasonable classification time compared to state-of-the-art algorithms. The proposed algorithm was evaluated and compared to RFC and HiCut using several benchmarks. Results obtained indicate that PCIU outperforms these algorithms in terms of speed, memory usage, incremental update capability, and preprocessing time. The algorithm, furthermore, was improved and made more accessible for a variety of applications through implementation in hardware. Two such implementations are detailed and discussed in this paper. The results indicate that a hardware/software codesign approach results in a slower, but easier to optimize and improve within time constraints, PCIU solution. A hardware accelerator based on an ESL approach using Handel-C, on the other hand, resulted in a 31x speed-up over a pure software implementation running on a state of the art Xeon processor.

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

Science.gov (United States)

Mei, Gang; Xu, Nengxiong; Xu, Liangliang

2016-01-01

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

Kidnapping Detection and Recognition in Previous Unknown Environment

Directory of Open Access Journals (Sweden)

Yang Tian

2017-01-01

Full Text Available An unaware event referred to as kidnapping makes the estimation result of localization incorrect. In a previous unknown environment, incorrect localization result causes incorrect mapping result in Simultaneous Localization and Mapping (SLAM by kidnapping. In this situation, the explored area and unexplored area are divided to make the kidnapping recovery difficult. To provide sufficient information on kidnapping, a framework to judge whether kidnapping has occurred and to identify the type of kidnapping with filter-based SLAM is proposed. The framework is called double kidnapping detection and recognition (DKDR by performing two checks before and after the “update” process with different metrics in real time. To explain one of the principles of DKDR, we describe a property of filter-based SLAM that corrects the mapping result of the environment using the current observations after the “update” process. Two classical filter-based SLAM algorithms, Extend Kalman Filter (EKF SLAM and Particle Filter (PF SLAM, are modified to show that DKDR can be simply and widely applied in existing filter-based SLAM algorithms. Furthermore, a technique to determine the adapted thresholds of metrics in real time without previous data is presented. Both simulated and experimental results demonstrate the validity and accuracy of the proposed method.

A novel Random Walk algorithm with Compulsive Evolution for heat exchanger network synthesis

International Nuclear Information System (INIS)

Xiao, Yuan; Cui, Guomin

2017-01-01

Highlights: • A novel Random Walk Algorithm with Compulsive Evolution is proposed for HENS. • A simple and feasible evolution strategy is presented in RWCE algorithm. • The integer and continuous variables of HEN are optimized simultaneously in RWCE. • RWCE is demonstrated a relatively strong global search ability in HEN optimization. - Abstract: The heat exchanger network (HEN) synthesis can be characterized as highly combinatorial, nonlinear and nonconvex, contributing to unmanageable computational time and a challenge in identifying the global optimal network design. Stochastic methods are robust and show a powerful global optimizing ability. Based on the common characteristic of different stochastic methods, namely randomness, a novel Random Walk algorithm with Compulsive Evolution (RWCE) is proposed to achieve the best possible total annual cost of heat exchanger network with the relatively simple and feasible evolution strategy. A population of heat exchanger networks is first randomly initialized. Next, the heat load of heat exchanger for each individual is randomly expanded or contracted in order to optimize both the integer and continuous variables simultaneously and to obtain the lowest total annual cost. Besides, when individuals approach to local optima, there is a certain probability for them to compulsively accept the imperfect networks in order to keep the population diversity and ability of global optimization. The presented method is then applied to heat exchanger network synthesis cases from the literature to compare the best results published. RWCE consistently has a lower computed total annual cost compared to previously published results.

Clinical effectiveness of a Bayesian algorithm for the diagnosis and management of heparin-induced thrombocytopenia.

Science.gov (United States)

Raschke, R A; Gallo, T; Curry, S C; Whiting, T; Padilla-Jones, A; Warkentin, T E; Puri, A

2017-08-01

Essentials We previously published a diagnostic algorithm for heparin-induced thrombocytopenia (HIT). In this study, we validated the algorithm in an independent large healthcare system. The accuracy was 98%, sensitivity 82% and specificity 99%. The algorithm has potential to improve accuracy and efficiency in the diagnosis of HIT. Background Heparin-induced thrombocytopenia (HIT) is a life-threatening drug reaction caused by antiplatelet factor 4/heparin (anti-PF4/H) antibodies. Commercial tests to detect these antibodies have suboptimal operating characteristics. We previously developed a diagnostic algorithm for HIT that incorporated 'four Ts' (4Ts) scoring and a stratified interpretation of an anti-PF4/H enzyme-linked immunosorbent assay (ELISA) and yielded a discriminant accuracy of 0.97 (95% confidence interval [CI], 0.93-1.00). Objectives The purpose of this study was to validate the algorithm in an independent patient population and quantitate effects that algorithm adherence could have on clinical care. Methods A retrospective cohort comprised patients who had undergone anti-PF4/H ELISA and serotonin release assay (SRA) testing in our healthcare system from 2010 to 2014. We determined the algorithm recommendation for each patient, compared recommendations with the clinical care received, and enumerated consequences of discrepancies. Operating characteristics were calculated for algorithm recommendations using SRA as the reference standard. Results Analysis was performed on 181 patients, 10 of whom were ruled in for HIT. The algorithm accurately stratified 98% of patients (95% CI, 95-99%), ruling out HIT in 158, ruling in HIT in 10 and recommending an SRA in 13 patients. Algorithm adherence would have obviated 165 SRAs and prevented 30 courses of unnecessary antithrombotic therapy for HIT. Diagnostic sensitivity was 0.82 (95% CI, 0.48-0.98), specificity 0.99 (95% CI, 0.97-1.00), PPV 0.90 (95% CI, 0.56-0.99) and NPV 0.99 (95% CI, 0.96-1.00). Conclusions An

A note on the linear memory Baum-Welch algorithm

DEFF Research Database (Denmark)

Jensen, Jens Ledet

2009-01-01

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

Modified automatic R-peak detection algorithm for patients with epilepsy using a portable electrocardiogram recorder.

Science.gov (United States)

Jeppesen, J; Beniczky, S; Fuglsang Frederiksen, A; Sidenius, P; Johansen, P

2017-07-01

Earlier studies have shown that short term heart rate variability (HRV) analysis of ECG seems promising for detection of epileptic seizures. A precise and accurate automatic R-peak detection algorithm is a necessity in a real-time, continuous measurement of HRV, in a portable ECG device. We used the portable CE marked ePatch® heart monitor to record the ECG of 14 patients, who were enrolled in the videoEEG long term monitoring unit for clinical workup of epilepsy. Recordings of the first 7 patients were used as training set of data for the R-peak detection algorithm and the recordings of the last 7 patients (467.6 recording hours) were used to test the performance of the algorithm. We aimed to modify an existing QRS-detection algorithm to a more precise R-peak detection algorithm to avoid the possible jitter Qand S-peaks can create in the tachogram, which causes error in short-term HRVanalysis. The proposed R-peak detection algorithm showed a high sensitivity (Se = 99.979%) and positive predictive value (P+ = 99.976%), which was comparable with a previously published QRS-detection algorithm for the ePatch® ECG device, when testing the same dataset. The novel R-peak detection algorithm designed to avoid jitter has very high sensitivity and specificity and thus is a suitable tool for a robust, fast, real-time HRV-analysis in patients with epilepsy, creating the possibility for real-time seizure detection for these patients.

Optimization of memory use of fragment extension-based protein-ligand docking with an original fast minimum cost flow algorithm.

Science.gov (United States)

Yanagisawa, Keisuke; Komine, Shunta; Kubota, Rikuto; Ohue, Masahito; Akiyama, Yutaka

2018-03-16

The need to accelerate large-scale protein-ligand docking in virtual screening against a huge compound database led researchers to propose a strategy that entails memorizing the evaluation result of the partial structure of a compound and reusing it to evaluate other compounds. However, the previous method required frequent disk accesses, resulting in insufficient acceleration. Thus, more efficient memory usage can be expected to lead to further acceleration, and optimal memory usage could be achieved by solving the minimum cost flow problem. In this research, we propose a fast algorithm for the minimum cost flow problem utilizing the characteristics of the graph generated for this problem as constraints. The proposed algorithm, which optimized memory usage, was approximately seven times faster compared to existing minimum cost flow algorithms. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

DNABIT Compress - Genome compression algorithm.

Science.gov (United States)

Rajarajeswari, Pothuraju; Apparao, Allam

2011-01-22

Data compression is concerned with how information is organized in data. Efficient storage means removal of redundancy from the data being stored in the DNA molecule. Data compression algorithms remove redundancy and are used to understand biologically important molecules. We present a compression algorithm, "DNABIT Compress" for DNA sequences based on a novel algorithm of assigning binary bits for smaller segments of DNA bases to compress both repetitive and non repetitive DNA sequence. Our proposed algorithm achieves the best compression ratio for DNA sequences for larger genome. Significantly better compression results show that "DNABIT Compress" algorithm is the best among the remaining compression algorithms. While achieving the best compression ratios for DNA sequences (Genomes),our new DNABIT Compress algorithm significantly improves the running time of all previous DNA compression programs. Assigning binary bits (Unique BIT CODE) for (Exact Repeats, Reverse Repeats) fragments of DNA sequence is also a unique concept introduced in this algorithm for the first time in DNA compression. This proposed new algorithm could achieve the best compression ratio as much as 1.58 bits/bases where the existing best methods could not achieve a ratio less than 1.72 bits/bases.

A formal analysis of a dynamic distributed spanning tree algorithm

NARCIS (Netherlands)

Mooij, A.J.; Wesselink, J.W.

2003-01-01

Abstract. We analyze the spanning tree algorithm in the IEEE 1394.1 draft standard, which correctness has not previously been proved. This algorithm is a fully-dynamic distributed graph algorithm, which, in general, is hard to develop. The approach we use is to formally develop an algorithm that is

Algorithms for worst-case tolerance optimization

DEFF Research Database (Denmark)

Schjær-Jacobsen, Hans; Madsen, Kaj

1979-01-01

New algorithms are presented for the solution of optimum tolerance assignment problems. The problems considered are defined mathematically as a worst-case problem (WCP), a fixed tolerance problem (FTP), and a variable tolerance problem (VTP). The basic optimization problem without tolerances...... is denoted the zero tolerance problem (ZTP). For solution of the WCP we suggest application of interval arithmetic and also alternative methods. For solution of the FTP an algorithm is suggested which is conceptually similar to algorithms previously developed by the authors for the ZTP. Finally, the VTP...... is solved by a double-iterative algorithm in which the inner iteration is performed by the FTP- algorithm. The application of the algorithm is demonstrated by means of relatively simple numerical examples. Basic properties, such as convergence properties, are displayed based on the examples....

Publishing with XML structure, enter, publish

CERN Document Server

Prost, Bernard

2015-01-01

XML is now at the heart of book publishing techniques: it provides the industry with a robust, flexible format which is relatively easy to manipulate. Above all, it preserves the future: the XML text becomes a genuine tactical asset enabling publishers to respond quickly to market demands. When new publishing media appear, it will be possible to very quickly make your editorial content available at a lower cost. On the downside, XML can become a bottomless pit for publishers attracted by its possibilities. There is a strong temptation to switch to audiovisual production and to add video and a

An Algorithm for the Convolution of Legendre Series

KAUST Repository

Hale, Nicholas; Townsend, Alex

2014-01-01

An O(N2) algorithm for the convolution of compactly supported Legendre series is described. The algorithm is derived from the convolution theorem for Legendre polynomials and the recurrence relation satisfied by spherical Bessel functions. Combining with previous work yields an O(N 2) algorithm for the convolution of Chebyshev series. Numerical results are presented to demonstrate the improved efficiency over the existing algorithm. © 2014 Society for Industrial and Applied Mathematics.

A leaf sequencing algorithm to enlarge treatment field length in IMRT

International Nuclear Information System (INIS)

Xia Ping; Hwang, Andrew B.; Verhey, Lynn J.

2002-01-01

With MLC-based IMRT, the maximum usable field size is often smaller than the maximum field size for conventional treatments. This is due to the constraints of the overtravel distances of MLC leaves and/or jaws. Using a new leaf sequencing algorithm, the usable IMRT field length (perpendicular to the MLC motion) can be mostly made equal to the full length of the MLC field without violating the upper jaw overtravel limit. For any given intensity pattern, a criterion was proposed to assess whether an intensity pattern can be delivered without violation of the jaw position constraints. If the criterion is met, the new algorithm will consider the jaw position constraints during the segmentation for the step and shoot delivery method. The strategy employed by the algorithm is to connect the intensity elements outside the jaw overtravel limits with those inside the jaw overtravel limits. Several methods were used to establish these connections during segmentation by modifying a previously published algorithm (areal algorithm), including changing the intensity level, alternating the leaf-sequencing direction, or limiting the segment field size. The algorithm was tested with 1000 random intensity patterns with dimensions of 21x27 cm2, 800 intensity patterns with higher intensity outside the jaw overtravel limit, and three different types of clinical treatment plans that were undeliverable using a segmentation method from a commercial treatment planning system. The new algorithm achieved a success rate of 100% with these test patterns. For the 1000 random patterns, the new algorithm yields a similar average number of segments of 36.9±2.9 in comparison to 36.6±1.3 when using the areal algorithm. For the 800 patterns with higher intensities outside the jaw overtravel limits, the new algorithm results in an increase of 25% in the average number of segments compared to the areal algorithm. However, the areal algorithm fails to create deliverable segments for 90% of these

On the performance of pre-microRNA detection algorithms

DEFF Research Database (Denmark)

Saçar Demirci, Müşerref Duygu; Baumbach, Jan; Allmer, Jens

2017-01-01

assess 13 ab initio pre-miRNA detection approaches using all relevant, published, and novel data sets while judging algorithm performance based on ten intrinsic performance measures. We present an extensible framework, izMiR, which allows for the unbiased comparison of existing algorithms, adding new...

Optimization of Antennas using a Hybrid Genetic-Algorithm Space-Mapping Algorithm

DEFF Research Database (Denmark)

Pantoja, M.F.; Bretones, A.R.; Meincke, Peter

2006-01-01

A hybrid global-local optimization technique for the design of antennas is presented. It consists of the subsequent application of a Genetic Algorithm (GA) that employs coarse models in the simulations and a space mapping (SM) that refines the solution found in the previous stage. The technique...

A Clustal Alignment Improver Using Evolutionary Algorithms

DEFF Research Database (Denmark)

Thomsen, Rene; Fogel, Gary B.; Krink, Thimo

2002-01-01

Multiple sequence alignment (MSA) is a crucial task in bioinformatics. In this paper we extended previous work with evolutionary algorithms (EA) by using MSA solutions obtained from the wellknown Clustal V algorithm as a candidate solution seed of the initial EA population. Our results clearly show...

Testing mapping algorithms of the cancer-specific EORTC QLQ-C30 onto EQ-5D in malignant mesothelioma.

Science.gov (United States)

Arnold, David T; Rowen, Donna; Versteegh, Matthijs M; Morley, Anna; Hooper, Clare E; Maskell, Nicholas A

2015-01-23

In order to estimate utilities for cancer studies where the EQ-5D was not used, the EORTC QLQ-C30 can be used to estimate EQ-5D using existing mapping algorithms. Several mapping algorithms exist for this transformation, however, algorithms tend to lose accuracy in patients in poor health states. The aim of this study was to test all existing mapping algorithms of QLQ-C30 onto EQ-5D, in a dataset of patients with malignant pleural mesothelioma, an invariably fatal malignancy where no previous mapping estimation has been published. Health related quality of life (HRQoL) data where both the EQ-5D and QLQ-C30 were used simultaneously was obtained from the UK-based prospective observational SWAMP (South West Area Mesothelioma and Pemetrexed) trial. In the original trial 73 patients with pleural mesothelioma were offered palliative chemotherapy and their HRQoL was assessed across five time points. This data was used to test the nine available mapping algorithms found in the literature, comparing predicted against observed EQ-5D values. The ability of algorithms to predict the mean, minimise error and detect clinically significant differences was assessed. The dataset had a total of 250 observations across 5 timepoints. The linear regression mapping algorithms tested generally performed poorly, over-estimating the predicted compared to observed EQ-5D values, especially when observed EQ-5D was below 0.5. The best performing algorithm used a response mapping method and predicted the mean EQ-5D with accuracy with an average root mean squared error of 0.17 (Standard Deviation; 0.22). This algorithm reliably discriminated between clinically distinct subgroups seen in the primary dataset. This study tested mapping algorithms in a population with poor health states, where they have been previously shown to perform poorly. Further research into EQ-5D estimation should be directed at response mapping methods given its superior performance in this study.

An algorithm for learning real-time automata

NARCIS (Netherlands)

Verwer, S.E.; De Weerdt, M.M.; Witteveen, C.

2007-01-01

We describe an algorithm for learning simple timed automata, known as real-time automata. The transitions of real-time automata can have a temporal constraint on the time of occurrence of the current symbol relative to the previous symbol. The learning algorithm is similar to the redblue fringe

A Faster Algorithm for Computing Straight Skeletons

KAUST Repository

Mencel, Liam A.

2014-01-01

computation in O(n (log n) log r) time. It improves on the previously best known algorithm for this reduction, which is randomised, and runs in expected O(n √(h+1) log² n) time for a polygon with h holes. Using known motorcycle graph algorithms, our result

Thomas Jefferson, Page Design, and Desktop Publishing.

Science.gov (United States)

Hartley, James

1991-01-01

Discussion of page design for desktop publishing focuses on the importance of functional issues as opposed to aesthetic issues, and criticizes a previous article that stressed aesthetic issues. Topics discussed include balance, consistency in text structure, and how differences in layout affect the clarity of "The Declaration of…

The geometry of entanglement and Grover's algorithm

International Nuclear Information System (INIS)

Iwai, Toshihiro; Hayashi, Naoki; Mizobe, Kimitake

2008-01-01

A measure of entanglement with respect to a bipartite partition of n-qubit has been defined and studied from the viewpoint of Riemannian geometry (Iwai 2007 J. Phys. A: Math. Theor. 40 12161). This paper has two aims. One is to study further the geometry of entanglement, and the other is to investigate Grover's search algorithms, both the original and the fixed-point ones, in reference with entanglement. As the distance between the maximally entangled states and the separable states is known already in the previous paper, this paper determines the set of maximally entangled states nearest to a typical separable state which is used as an initial state in Grover's search algorithms, and to find geodesic segments which realize the above-mentioned distance. As for Grover's algorithms, it is already known that while the initial and the target states are separable, the algorithms generate sequences of entangled states. This fact is confirmed also in the entanglement measure proposed in the previous paper, and then a split Grover algorithm is proposed which generates sequences of separable states only with respect to the bipartite partition

Evaluation of novel algorithm embedded in a wearable sEMG device for seizure detection

DEFF Research Database (Denmark)

Conradsen, Isa; Beniczky, Sandor; Wolf, Peter

2012-01-01

We implemented a modified version of a previously published algorithm for detection of generalized tonic-clonic seizures into a prototype wireless surface electromyography (sEMG) recording device. The method was modified to require minimum computational load, and two parameters were trained...... on prior sEMG data recorded with the device. Along with the normal sEMG recording, the device is able to set an alarm whenever the implemented algorithm detects a seizure. These alarms are annotated in the data file along with the signal. The device was tested at the Epilepsy Monitoring Unit (EMU......) at the Danish Epilepsy Center. Five patients were included in the study and two of them had generalized tonic-clonic seizures. All patients were monitored for 2–5 days. A double-blind study was made on the five patients. The overall result showed that the device detected four of seven seizures and had a false...

Marshall Rosenbluth and the Metropolis algorithm

International Nuclear Information System (INIS)

Gubernatis, J.E.

2005-01-01

The 1953 publication, 'Equation of State Calculations by Very Fast Computing Machines' by N. Metropolis, A. W. Rosenbluth and M. N. Rosenbluth, and M. Teller and E. Teller [J. Chem. Phys. 21, 1087 (1953)] marked the beginning of the use of the Monte Carlo method for solving problems in the physical sciences. The method described in this publication subsequently became known as the Metropolis algorithm, undoubtedly the most famous and most widely used Monte Carlo algorithm ever published. As none of the authors made subsequent use of the algorithm, they became unknown to the large simulation physics community that grew from this publication and their roles in its development became the subject of mystery and legend. At a conference marking the 50th anniversary of the 1953 publication, Marshall Rosenbluth gave his recollections of the algorithm's development. The present paper describes the algorithm, reconstructs the historical context in which it was developed, and summarizes Marshall's recollections

Machine Learning Algorithms Outperform Conventional Regression Models in Predicting Development of Hepatocellular Carcinoma

Science.gov (United States)

Singal, Amit G.; Mukherjee, Ashin; Elmunzer, B. Joseph; Higgins, Peter DR; Lok, Anna S.; Zhu, Ji; Marrero, Jorge A; Waljee, Akbar K

2015-01-01

Background Predictive models for hepatocellular carcinoma (HCC) have been limited by modest accuracy and lack of validation. Machine learning algorithms offer a novel methodology, which may improve HCC risk prognostication among patients with cirrhosis. Our study's aim was to develop and compare predictive models for HCC development among cirrhotic patients, using conventional regression analysis and machine learning algorithms. Methods We enrolled 442 patients with Child A or B cirrhosis at the University of Michigan between January 2004 and September 2006 (UM cohort) and prospectively followed them until HCC development, liver transplantation, death, or study termination. Regression analysis and machine learning algorithms were used to construct predictive models for HCC development, which were tested on an independent validation cohort from the Hepatitis C Antiviral Long-term Treatment against Cirrhosis (HALT-C) Trial. Both models were also compared to the previously published HALT-C model. Discrimination was assessed using receiver operating characteristic curve analysis and diagnostic accuracy was assessed with net reclassification improvement and integrated discrimination improvement statistics. Results After a median follow-up of 3.5 years, 41 patients developed HCC. The UM regression model had a c-statistic of 0.61 (95%CI 0.56-0.67), whereas the machine learning algorithm had a c-statistic of 0.64 (95%CI 0.60–0.69) in the validation cohort. The machine learning algorithm had significantly better diagnostic accuracy as assessed by net reclassification improvement (pmachine learning algorithm (p=0.047). Conclusion Machine learning algorithms improve the accuracy of risk stratifying patients with cirrhosis and can be used to accurately identify patients at high-risk for developing HCC. PMID:24169273

Shape: automatic conformation prediction of carbohydrates using a genetic algorithm

Directory of Open Access Journals (Sweden)

Rosen Jimmy

2009-09-01

Full Text Available Abstract Background Detailed experimental three dimensional structures of carbohydrates are often difficult to acquire. Molecular modelling and computational conformation prediction are therefore commonly used tools for three dimensional structure studies. Modelling procedures generally require significant training and computing resources, which is often impractical for most experimental chemists and biologists. Shape has been developed to improve the availability of modelling in this field. Results The Shape software package has been developed for simplicity of use and conformation prediction performance. A trivial user interface coupled to an efficient genetic algorithm conformation search makes it a powerful tool for automated modelling. Carbohydrates up to a few hundred atoms in size can be investigated on common computer hardware. It has been shown to perform well for the prediction of over four hundred bioactive oligosaccharides, as well as compare favourably with previously published studies on carbohydrate conformation prediction. Conclusion The Shape fully automated conformation prediction can be used by scientists who lack significant modelling training, and performs well on computing hardware such as laptops and desktops. It can also be deployed on computer clusters for increased capacity. The prediction accuracy under the default settings is good, as it agrees well with experimental data and previously published conformation prediction studies. This software is available both as open source and under commercial licenses.

Formal verification of algorithms for critical systems

Science.gov (United States)

Rushby, John M.; Von Henke, Friedrich

1993-01-01

We describe our experience with formal, machine-checked verification of algorithms for critical applications, concentrating on a Byzantine fault-tolerant algorithm for synchronizing the clocks in the replicated computers of a digital flight control system. First, we explain the problems encountered in unsynchronized systems and the necessity, and criticality, of fault-tolerant synchronization. We give an overview of one such algorithm, and of the arguments for its correctness. Next, we describe a verification of the algorithm that we performed using our EHDM system for formal specification and verification. We indicate the errors we found in the published analysis of the algorithm, and other benefits that we derived from the verification. Based on our experience, we derive some key requirements for a formal specification and verification system adequate to the task of verifying algorithms of the type considered. Finally, we summarize our conclusions regarding the benefits of formal verification in this domain, and the capabilities required of verification systems in order to realize those benefits.

Computational geometry algorithms and applications

CERN Document Server

de Berg, Mark; Overmars, Mark; Schwarzkopf, Otfried

1997-01-01

Computational geometry emerged from the field of algorithms design and anal­ ysis in the late 1970s. It has grown into a recognized discipline with its own journals, conferences, and a large community of active researchers. The suc­ cess of the field as a research discipline can on the one hand be explained from the beauty of the problems studied and the solutions obtained, and, on the other hand, by the many application domains--computer graphics, geographic in­ formation systems (GIS), robotics, and others-in which geometric algorithms play a fundamental role. For many geometric problems the early algorithmic solutions were either slow or difficult to understand and implement. In recent years a number of new algorithmic techniques have been developed that improved and simplified many of the previous approaches. In this textbook we have tried to make these modem algorithmic solutions accessible to a large audience. The book has been written as a textbook for a course in computational geometry, but it can ...

Four (Algorithms) in One (Bag): An Integrative Framework of Knowledge for Teaching the Standard Algorithms of the Basic Arithmetic Operations

Science.gov (United States)

Raveh, Ira; Koichu, Boris; Peled, Irit; Zaslavsky, Orit

2016-01-01

In this article we present an integrative framework of knowledge for teaching the standard algorithms of the four basic arithmetic operations. The framework is based on a mathematical analysis of the algorithms, a connectionist perspective on teaching mathematics and an analogy with previous frameworks of knowledge for teaching arithmetic…

A Faster Algorithm for Computing Motorcycle Graphs

KAUST Repository

Vigneron, Antoine E.; Yan, Lie

2014-01-01

We present a new algorithm for computing motorcycle graphs that runs in (Formula presented.) time for any (Formula presented.), improving on all previously known algorithms. The main application of this result is to computing the straight skeleton of a polygon. It allows us to compute the straight skeleton of a non-degenerate polygon with (Formula presented.) holes in (Formula presented.) expected time. If all input coordinates are (Formula presented.)-bit rational numbers, we can compute the straight skeleton of a (possibly degenerate) polygon with (Formula presented.) holes in (Formula presented.) expected time. In particular, it means that we can compute the straight skeleton of a simple polygon in (Formula presented.) expected time if all input coordinates are (Formula presented.)-bit rationals, while all previously known algorithms have worst-case running time (Formula presented.). © 2014 Springer Science+Business Media New York.

A Faster Algorithm for Computing Motorcycle Graphs

KAUST Repository

Vigneron, Antoine E.

2014-08-29

We present a new algorithm for computing motorcycle graphs that runs in (Formula presented.) time for any (Formula presented.), improving on all previously known algorithms. The main application of this result is to computing the straight skeleton of a polygon. It allows us to compute the straight skeleton of a non-degenerate polygon with (Formula presented.) holes in (Formula presented.) expected time. If all input coordinates are (Formula presented.)-bit rational numbers, we can compute the straight skeleton of a (possibly degenerate) polygon with (Formula presented.) holes in (Formula presented.) expected time. In particular, it means that we can compute the straight skeleton of a simple polygon in (Formula presented.) expected time if all input coordinates are (Formula presented.)-bit rationals, while all previously known algorithms have worst-case running time (Formula presented.). © 2014 Springer Science+Business Media New York.

DNABIT Compress – Genome compression algorithm

Science.gov (United States)

Rajarajeswari, Pothuraju; Apparao, Allam

2011-01-01

Data compression is concerned with how information is organized in data. Efficient storage means removal of redundancy from the data being stored in the DNA molecule. Data compression algorithms remove redundancy and are used to understand biologically important molecules. We present a compression algorithm, “DNABIT Compress” for DNA sequences based on a novel algorithm of assigning binary bits for smaller segments of DNA bases to compress both repetitive and non repetitive DNA sequence. Our proposed algorithm achieves the best compression ratio for DNA sequences for larger genome. Significantly better compression results show that “DNABIT Compress” algorithm is the best among the remaining compression algorithms. While achieving the best compression ratios for DNA sequences (Genomes),our new DNABIT Compress algorithm significantly improves the running time of all previous DNA compression programs. Assigning binary bits (Unique BIT CODE) for (Exact Repeats, Reverse Repeats) fragments of DNA sequence is also a unique concept introduced in this algorithm for the first time in DNA compression. This proposed new algorithm could achieve the best compression ratio as much as 1.58 bits/bases where the existing best methods could not achieve a ratio less than 1.72 bits/bases. PMID:21383923

A multi-parametric particle-pairing algorithm for particle tracking in single and multiphase flows

International Nuclear Information System (INIS)

Cardwell, Nicholas D; Vlachos, Pavlos P; Thole, Karen A

2011-01-01

Multiphase flows (MPFs) offer a rich area of fundamental study with many practical applications. Examples of such flows range from the ingestion of foreign particulates in gas turbines to transport of particles within the human body. Experimental investigation of MPFs, however, is challenging, and requires techniques that simultaneously resolve both the carrier and discrete phases present in the flowfield. This paper presents a new multi-parametric particle-pairing algorithm for particle tracking velocimetry (MP3-PTV) in MPFs. MP3-PTV improves upon previous particle tracking algorithms by employing a novel variable pair-matching algorithm which utilizes displacement preconditioning in combination with estimated particle size and intensity to more effectively and accurately match particle pairs between successive images. To improve the method's efficiency, a new particle identification and segmentation routine was also developed. Validation of the new method was initially performed on two artificial data sets: a traditional single-phase flow published by the Visualization Society of Japan (VSJ) and an in-house generated MPF data set having a bi-modal distribution of particles diameters. Metrics of the measurement yield, reliability and overall tracking efficiency were used for method comparison. On the VSJ data set, the newly presented segmentation routine delivered a twofold improvement in identifying particles when compared to other published methods. For the simulated MPF data set, measurement efficiency of the carrier phases improved from 9% to 41% for MP3-PTV as compared to a traditional hybrid PTV. When employed on experimental data of a gas–solid flow, the MP3-PTV effectively identified the two particle populations and reported a vector efficiency and velocity measurement error comparable to measurements for the single-phase flow images. Simultaneous measurement of the dispersed particle and the carrier flowfield velocities allowed for the calculation of

What comes first? Publishing business or publishing studies?

Directory of Open Access Journals (Sweden)

Josipa Selthofer

2015-07-01

Full Text Available The aim of this paper is to analyze and compare publishing studies, their programmes at the undergraduate and graduate levels and scholars involved in the teaching of publishing courses at the top universities around the world and in Croatia. Since traditional publishing business is rapidly changing, new skills and new jobs are involved in it. The main research question is: Can modern publishing studies produce a modern publisher? Or, is it the other way around? The hypothesis of the paper is that scholars involved in the teaching of publishing courses at the top universities around the world have a background in publishing business. So, can they prepare their students for the future and can their students gain competencies they need to compete in a confusing world of digital authors and electronic books? The research methods used were content analysis and comparison. Research sample included 36 university publishing programmes at the undergraduate and graduate level worldwide (24 MA, 12 BA. The research sample was limited mainly to the English-speaking countries. In most non-English-speaking countries, it was difficult to analyse the programme curriculum in the native language because the programme and course description did not exit. In the data gathering phase, a customized web application was used for content analysis. The application has three main sections: a list of websites to evaluate, a visual representation of the uploaded website and a list of characteristics grouped by categories for quantifying data. About twenty years ago, publishing was not considered a separate scientific branch in Croatia. Publishing studies are therefore a new phenomenon to both scholars and publishers in Croatia. To create a new, ideal publishing course, can we simply copy global trends or is it better to create something of our own?

Redundancy allocation of series-parallel systems using a variable neighborhood search algorithm

International Nuclear Information System (INIS)

Liang, Y.-C.; Chen, Y.-C.

2007-01-01

This paper presents a meta-heuristic algorithm, variable neighborhood search (VNS), to the redundancy allocation problem (RAP). The RAP, an NP-hard problem, has attracted the attention of much prior research, generally in a restricted form where each subsystem must consist of identical components. The newer meta-heuristic methods overcome this limitation and offer a practical way to solve large instances of the relaxed RAP where different components can be used in parallel. Authors' previously published work has shown promise for the variable neighborhood descent (VND) method, the simplest version among VNS variations, on RAP. The variable neighborhood search method itself has not been used in reliability design, yet it is a method that fits those combinatorial problems with potential neighborhood structures, as in the case of the RAP. Therefore, authors further extended their work to develop a VNS algorithm for the RAP and tested a set of well-known benchmark problems from the literature. Results on 33 test instances ranging from less to severely constrained conditions show that the variable neighborhood search method improves the performance of VND and provides a competitive solution quality at economically computational expense in comparison with the best-known heuristics including ant colony optimization, genetic algorithm, and tabu search

Redundancy allocation of series-parallel systems using a variable neighborhood search algorithm

Energy Technology Data Exchange (ETDEWEB)

Liang, Y.-C. [Department of Industrial Engineering and Management, Yuan Ze University, No 135 Yuan-Tung Road, Chung-Li, Taoyuan County, Taiwan 320 (China)]. E-mail: ycliang@saturn.yzu.edu.tw; Chen, Y.-C. [Department of Industrial Engineering and Management, Yuan Ze University, No 135 Yuan-Tung Road, Chung-Li, Taoyuan County, Taiwan 320 (China)]. E-mail: s927523@mail.yzu.edu.tw

2007-03-15

This paper presents a meta-heuristic algorithm, variable neighborhood search (VNS), to the redundancy allocation problem (RAP). The RAP, an NP-hard problem, has attracted the attention of much prior research, generally in a restricted form where each subsystem must consist of identical components. The newer meta-heuristic methods overcome this limitation and offer a practical way to solve large instances of the relaxed RAP where different components can be used in parallel. Authors' previously published work has shown promise for the variable neighborhood descent (VND) method, the simplest version among VNS variations, on RAP. The variable neighborhood search method itself has not been used in reliability design, yet it is a method that fits those combinatorial problems with potential neighborhood structures, as in the case of the RAP. Therefore, authors further extended their work to develop a VNS algorithm for the RAP and tested a set of well-known benchmark problems from the literature. Results on 33 test instances ranging from less to severely constrained conditions show that the variable neighborhood search method improves the performance of VND and provides a competitive solution quality at economically computational expense in comparison with the best-known heuristics including ant colony optimization, genetic algorithm, and tabu search.

Mixed media : feminist presses and publishing politics in twentieth-century Britain

OpenAIRE

Murray, S. E.

1999-01-01

The high cultural profile of contemporary feminist publishing in Britain has previously met with a curiously evasive response from those spheres of academic discourse in which it might be expected to figure: women's studies, while asserting the innate politicality of all communication, has tended to overlook the subject of publishing in favour of less materialist cultural modes; while publishing studies has conventionally overlooked the significance of gender as a differential ...

Quantum algorithm for linear regression

Science.gov (United States)

Wang, Guoming

2017-07-01

We present a quantum algorithm for fitting a linear regression model to a given data set using the least-squares approach. Differently from previous algorithms which yield a quantum state encoding the optimal parameters, our algorithm outputs these numbers in the classical form. So by running it once, one completely determines the fitted model and then can use it to make predictions on new data at little cost. Moreover, our algorithm works in the standard oracle model, and can handle data sets with nonsparse design matrices. It runs in time poly( log2(N ) ,d ,κ ,1 /ɛ ) , where N is the size of the data set, d is the number of adjustable parameters, κ is the condition number of the design matrix, and ɛ is the desired precision in the output. We also show that the polynomial dependence on d and κ is necessary. Thus, our algorithm cannot be significantly improved. Furthermore, we also give a quantum algorithm that estimates the quality of the least-squares fit (without computing its parameters explicitly). This algorithm runs faster than the one for finding this fit, and can be used to check whether the given data set qualifies for linear regression in the first place.

Test of TEDA, Tsunami Early Detection Algorithm

Science.gov (United States)

Bressan, Lidia; Tinti, Stefano

2010-05-01

Tsunami detection in real-time, both offshore and at the coastline, plays a key role in Tsunami Warning Systems since it provides so far the only reliable and timely proof of tsunami generation, and is used to confirm or cancel tsunami warnings previously issued on the basis of seismic data alone. Moreover, in case of submarine or coastal landslide generated tsunamis, which are not announced by clear seismic signals and are typically local, real-time detection at the coastline might be the fastest way to release a warning, even if the useful time for emergency operations might be limited. TEDA is an algorithm for real-time detection of tsunami signal on sea-level records, developed by the Tsunami Research Team of the University of Bologna. The development and testing of the algorithm has been accomplished within the framework of the Italian national project DPC-INGV S3 and the European project TRANSFER. The algorithm is to be implemented at station level, and it is based therefore only on sea-level data of a single station, either a coastal tide-gauge or an offshore buoy. TEDA's principle is to discriminate the first tsunami wave from the previous background signal, which implies the assumption that the tsunami waves introduce a difference in the previous sea-level signal. Therefore, in TEDA the instantaneous (most recent) and the previous background sea-level elevation gradients are characterized and compared by proper functions (IS and BS) that are updated at every new data acquisition. Detection is triggered when the instantaneous signal function passes a set threshold and at the same time it is significantly bigger compared to the previous background signal. The functions IS and BS depend on temporal parameters that allow the algorithm to be adapted different situations: in general, coastal tide-gauges have a typical background spectrum depending on the location where the instrument is installed, due to local topography and bathymetry, while offshore buoys are

An algorithmic decomposition of claw-free graphs leading to an O(n^3) algorithm for the weighted stable set problem

OpenAIRE

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 ...

Desktop Publishing.

Science.gov (United States)

Stanley, Milt

1986-01-01

Defines desktop publishing, describes microcomputer developments and software tools that make it possible, and discusses its use as an instructional tool to improve writing skills. Reasons why students' work should be published, examples of what to publish, and types of software and hardware to facilitate publishing are reviewed. (MBR)

Structural Revision of Some Recently Published Iridoid Glucosides

DEFF Research Database (Denmark)

Jensen, Søren Rosendal; Calis, Ihsan; Gotfredsen, Charlotte Held

2007-01-01

). Finally, two alleged iridoid galactosides from Buddleja crispa named buddlejosides A and B (12a and 12b) have been shown to be the corresponding glucosides; the former is identical to agnuside (13a) while the latter is 3,4-dihydroxybenzoylaucubin (13b), an iridoid glucoside not previously published...

An efficient parallel algorithm for matrix-vector multiplication

Energy Technology Data Exchange (ETDEWEB)

Hendrickson, B.; Leland, R.; Plimpton, S.

1993-03-01

The multiplication of a vector by a matrix is the kernel computation of many algorithms in scientific computation. A fast parallel algorithm for this calculation is therefore necessary if one is to make full use of the new generation of parallel supercomputers. This paper presents a high performance, parallel matrix-vector multiplication algorithm that is particularly well suited to hypercube multiprocessors. For an n x n matrix on p processors, the communication cost of this algorithm is O(n/[radical]p + log(p)), independent of the matrix sparsity pattern. The performance of the algorithm is demonstrated by employing it as the kernel in the well-known NAS conjugate gradient benchmark, where a run time of 6.09 seconds was observed. This is the best published performance on this benchmark achieved to date using a massively parallel supercomputer.

Accuracy and conservatism of vapour intrusion algorithms for contaminated land management

NARCIS (Netherlands)

Provoost, J.; Reijnders, L.; Bonders, J.

2013-01-01

This paper provides a view on the suitability of screening-level vapour intrusion (VI) algorithms for contaminated land management. It focuses on the accuracy and level of conservatism for a number of screening-level algorithms used for VI into buildings. The paper discusses the published evidence

Multicore and GPU algorithms for Nussinov RNA folding

Science.gov (United States)

2014-01-01

Background One segment of a RNA sequence might be paired with another segment of the same RNA sequence due to the force of hydrogen bonds. This two-dimensional structure is called the RNA sequence's secondary structure. Several algorithms have been proposed to predict an RNA sequence's secondary structure. These algorithms are referred to as RNA folding algorithms. Results We develop cache efficient, multicore, and GPU algorithms for RNA folding using Nussinov's algorithm. Conclusions Our cache efficient algorithm provides a speedup between 1.6 and 3.0 relative to a naive straightforward single core code. The multicore version of the cache efficient single core algorithm provides a speedup, relative to the naive single core algorithm, between 7.5 and 14.0 on a 6 core hyperthreaded CPU. Our GPU algorithm for the NVIDIA C2050 is up to 1582 times as fast as the naive single core algorithm and between 5.1 and 11.2 times as fast as the fastest previously known GPU algorithm for Nussinov RNA folding. PMID:25082539

Some multigrid algorithms for SIMD machines

Energy Technology Data Exchange (ETDEWEB)

Dendy, J.E. Jr. [Los Alamos National Lab., NM (United States)

1996-12-31

Previously a semicoarsening multigrid algorithm suitable for use on SIMD architectures was investigated. Through the use of new software tools, the performance of this algorithm has been considerably improved. The method has also been extended to three space dimensions. The method performs well for strongly anisotropic problems and for problems with coefficients jumping by orders of magnitude across internal interfaces. The parallel efficiency of this method is analyzed, and its actual performance on the CM-5 is compared with its performance on the CRAY-YMP. A standard coarsening multigrid algorithm is also considered, and we compare its performance on these two platforms as well.

Initialization-free generalized Deutsche-Jazz's algorithm

Energy Technology Data Exchange (ETDEWEB)

Chi, Dong Pyo [School of Mathematical Sciences, Seoul National University, Seoul (Korea, Republic of)]. E-mail: dpchi@math.snu.ac.kr; Kim, Jinsoo [School of Electrical Engineering and Computer Science, Seoul National University, Seoul (Korea)]. E-mail: jkim@ee.snu.ac.kr; Lee, Soojoon [School of Mathematical Sciences, Seoul National University, Seoul (Korea)]. E-mail: level@math.snu.ac.kr

2001-06-29

We generalize the Deutsch-Jozsa algorithm by exploiting summations of the roots of unity. The generalized algorithm distinguishes a wider class of functions promised to be either constant or many to one and onto an evenly spaced range. As previously, the generalized quantum algorithm solves this problem using a single functional evaluation. We also consider the problem of distinguishing constant and evenly balanced functions and present a quantum algorithm for this problem that does not require any initialization of an auxiliary register involved in the process of functional evaluation and after solving the problem recovers the initial state of an auxiliary register. (author)

A Performance Evaluation of Lightning-NO Algorithms in CMAQ

Science.gov (United States)

In the Community Multiscale Air Quality (CMAQv5.2) model, we have implemented two algorithms for lightning NO production; one algorithm is based on the hourly observed cloud-to-ground lightning strike data from National Lightning Detection Network (NLDN) to replace the previous m...

Validation of a clinical practice-based algorithm for the diagnosis of autosomal recessive cerebellar ataxias based on NGS identified cases.

Science.gov (United States)

Mallaret, Martial; Renaud, Mathilde; Redin, Claire; Drouot, Nathalie; Muller, Jean; Severac, Francois; Mandel, Jean Louis; Hamza, Wahiba; Benhassine, Traki; Ali-Pacha, Lamia; Tazir, Meriem; Durr, Alexandra; Monin, Marie-Lorraine; Mignot, Cyril; Charles, Perrine; Van Maldergem, Lionel; Chamard, Ludivine; Thauvin-Robinet, Christel; Laugel, Vincent; Burglen, Lydie; Calvas, Patrick; Fleury, Marie-Céline; Tranchant, Christine; Anheim, Mathieu; Koenig, Michel

2016-07-01

Establishing a molecular diagnosis of autosomal recessive cerebellar ataxias (ARCA) is challenging due to phenotype and genotype heterogeneity. We report the validation of a previously published clinical practice-based algorithm to diagnose ARCA. Two assessors performed a blind analysis to determine the most probable mutated gene based on comprehensive clinical and paraclinical data, without knowing the molecular diagnosis of 23 patients diagnosed by targeted capture of 57 ataxia genes and high-throughput sequencing coming from a 145 patients series. The correct gene was predicted in 61 and 78 % of the cases by the two assessors, respectively. There was a high inter-rater agreement [K = 0.85 (0.55-0.98) p < 0.001] confirming the algorithm's reproducibility. Phenotyping patients with proper clinical examination, imaging, biochemical investigations and nerve conduction studies remain crucial for the guidance of molecular analysis and to interpret next generation sequencing results. The proposed algorithm should be helpful for diagnosing ARCA in clinical practice.

A comparative analysis of biclustering algorithms for gene expression data

Science.gov (United States)

Eren, Kemal; Deveci, Mehmet; Küçüktunç, Onur; Çatalyürek, Ümit V.

2013-01-01

The need to analyze high-dimension biological data is driving the development of new data mining methods. Biclustering algorithms have been successfully applied to gene expression data to discover local patterns, in which a subset of genes exhibit similar expression levels over a subset of conditions. However, it is not clear which algorithms are best suited for this task. Many algorithms have been published in the past decade, most of which have been compared only to a small number of algorithms. Surveys and comparisons exist in the literature, but because of the large number and variety of biclustering algorithms, they are quickly outdated. In this article we partially address this problem of evaluating the strengths and weaknesses of existing biclustering methods. We used the BiBench package to compare 12 algorithms, many of which were recently published or have not been extensively studied. The algorithms were tested on a suite of synthetic data sets to measure their performance on data with varying conditions, such as different bicluster models, varying noise, varying numbers of biclusters and overlapping biclusters. The algorithms were also tested on eight large gene expression data sets obtained from the Gene Expression Omnibus. Gene Ontology enrichment analysis was performed on the resulting biclusters, and the best enrichment terms are reported. Our analyses show that the biclustering method and its parameters should be selected based on the desired model, whether that model allows overlapping biclusters, and its robustness to noise. In addition, we observe that the biclustering algorithms capable of finding more than one model are more successful at capturing biologically relevant clusters. PMID:22772837

XTALOPT version r11: An open-source evolutionary algorithm for crystal structure prediction

Science.gov (United States)

Avery, Patrick; Falls, Zackary; Zurek, Eva

2018-01-01

Version 11 of XTALOPT, an evolutionary algorithm for crystal structure prediction, has now been made available for download from the CPC library or the XTALOPT website, http://xtalopt.github.io. Whereas the previous versions of XTALOPT were published under the Gnu Public License (GPL), the current version is made available under the 3-Clause BSD License, which is an open source license that is recognized by the Open Source Initiative. Importantly, the new version can be executed via a command line interface (i.e., it does not require the use of a Graphical User Interface). Moreover, the new version is written as a stand-alone program, rather than an extension to AVOGADRO.

Music publishing

OpenAIRE

Simões, Alberto; Almeida, J. J.

2003-01-01

Current music publishing in the Internet is mainly concerned with sound publishing. We claim that music publishing is not only to make sound available but also to define relations between a set of music objects like music scores, guitar chords, lyrics and their meta-data. We want an easy way to publish music in the Internet, to make high quality paper booklets and even to create Audio CD's. In this document we present a workbench for music publishing based on open formats, using open-source t...

A relation between irreversibility and unlinkability for biometric template protection algorithms

OpenAIRE

井沼, 学

2014-01-01

For biometric recognition systems, privacy protection of enrolled users’ biometric information, which are called biometric templates, is a critical problem. Recently, various template protection algorithms have been proposed and many related previous works have discussed security notions to evaluate the protection performance of these protection algorithms. Irreversibility and unlinkability are important security notions discussed in many related previous works. In this paper, we prove that u...

Model-based Bayesian signal extraction algorithm for peripheral nerves

Science.gov (United States)

Eggers, Thomas E.; Dweiri, Yazan M.; McCallum, Grant A.; Durand, Dominique M.

2017-10-01

Objective. Multi-channel cuff electrodes have recently been investigated for extracting fascicular-level motor commands from mixed neural recordings. Such signals could provide volitional, intuitive control over a robotic prosthesis for amputee patients. Recent work has demonstrated success in extracting these signals in acute and chronic preparations using spatial filtering techniques. These extracted signals, however, had low signal-to-noise ratios and thus limited their utility to binary classification. In this work a new algorithm is proposed which combines previous source localization approaches to create a model based method which operates in real time. Approach. To validate this algorithm, a saline benchtop setup was created to allow the precise placement of artificial sources within a cuff and interference sources outside the cuff. The artificial source was taken from five seconds of chronic neural activity to replicate realistic recordings. The proposed algorithm, hybrid Bayesian signal extraction (HBSE), is then compared to previous algorithms, beamforming and a Bayesian spatial filtering method, on this test data. An example chronic neural recording is also analyzed with all three algorithms. Main results. The proposed algorithm improved the signal to noise and signal to interference ratio of extracted test signals two to three fold, as well as increased the correlation coefficient between the original and recovered signals by 10-20%. These improvements translated to the chronic recording example and increased the calculated bit rate between the recovered signals and the recorded motor activity. Significance. HBSE significantly outperforms previous algorithms in extracting realistic neural signals, even in the presence of external noise sources. These results demonstrate the feasibility of extracting dynamic motor signals from a multi-fascicled intact nerve trunk, which in turn could extract motor command signals from an amputee for the end goal of

Empirical ocean color algorithms and bio-optical properties of the western coastal waters of Svalbard, Arctic

Science.gov (United States)

Son, Young-Sun; Kim, Hyun-cheol

2018-05-01

Chlorophyll (Chl) concentration is one of the key indicators identifying changes in the Arctic marine ecosystem. However, current Chl algorithms are not accurate in the Arctic Ocean due to different bio-optical properties from those in the lower latitude oceans. In this study, we evaluated the current Chl algorithms and analyzed the cause of the error in the western coastal waters of Svalbard, which are known to be sensitive to climate change. The NASA standard algorithms showed to overestimate the Chl concentration in the region. This was due to the high non-algal particles (NAP) absorption and colored dissolved organic matter (CDOM) variability at the blue wavelength. In addition, at lower Chl concentrations (0.1-0.3 mg m-3), chlorophyll-specific absorption coefficients were ∼2.3 times higher than those of other Arctic oceans. This was another reason for the overestimation of Chl concentration. OC4 algorithm-based regionally tuned-Svalbard Chl (SC4) algorithm for retrieving more accurate Chl estimates reduced the mean absolute percentage difference (APD) error from 215% to 49%, the mean relative percentage difference (RPD) error from 212% to 16%, and the normalized root mean square (RMS) error from 211% to 68%. This region has abundant suspended matter due to the melting of tidal glaciers. We evaluated the performance of total suspended matter (TSM) algorithms. Previous published TSM algorithms generally overestimated the TSM concentration in this region. The Svalbard TSM-single band algorithm for low TSM range (ST-SB-L) decreased the APD and RPD errors by 52% and 14%, respectively, but the RMS error still remained high (105%).

Pioneers, publishers and the dissemination of archaeological knowledge: A study of publishing in British archaeology 1816-1851

Directory of Open Access Journals (Sweden)

Sarah Scott

2013-08-01

Full Text Available The first half of the nineteenth century was a formative period in the development of archaeology as a discipline and archaeological publishing played a key role in this. Libraries were an essential marker of social and intellectual status and there now exists a considerable body of scholarship on the most impressive publications of the day and on the factors influencing their presentation; for example, in relation to the publication of Mediterranean classical antiquities. The crucial role which publishers played in the selection and dissemination of scholarship has been addressed in recent studies of the history of the book, and there is a growing literature on the role of publishers in the dissemination of scientific knowledge, but there has to date been very limited evaluation of the role of publishers in the selection and dissemination of archaeological knowledge in Britain in this period. This study will investigate the extent to which the publication and dissemination of archaeological knowledge, and hence the discipline itself, was shaped by the intellectual and/or commercial concerns of publishers, with a view to providing a more nuanced understanding of the ways in which knowledge was filtered and the impact that this had. Key trends in archaeological publishing in the period 1816-51 will be identified, based on the London Catalogue of Books, and will show how and why this kind of study should be seen as an essential component of any research which considers the history of the discipline. Selected case studies will show the immense, and previously unacknowledged, importance of decisions made during the publication process on the development of archaeology in Britain, and directions for further study will be identified.

An improved algorithm for connectivity analysis of distribution networks

International Nuclear Information System (INIS)

Kansal, M.L.; Devi, Sunita

2007-01-01

In the present paper, an efficient algorithm for connectivity analysis of moderately sized distribution networks has been suggested. Algorithm is based on generation of all possible minimal system cutsets. The algorithm is efficient as it identifies only the necessary and sufficient conditions of system failure conditions in n-out-of-n type of distribution networks. The proposed algorithm is demonstrated with the help of saturated and unsaturated distribution networks. The computational efficiency of the algorithm is justified by comparing the computational efforts with the previously suggested appended spanning tree (AST) algorithm. The proposed technique has the added advantage as it can be utilized for generation of system inequalities which is useful in reliability estimation of capacitated networks

An Enhanced Genetic Algorithm for the Generalized Traveling Salesman Problem

Directory of Open Access Journals (Sweden)

H. Jafarzadeh

2017-12-01

Full Text Available The generalized traveling salesman problem (GTSP deals with finding the minimum-cost tour in a clustered set of cities. In this problem, the traveler is interested in finding the best path that goes through all clusters. As this problem is NP-hard, implementing a metaheuristic algorithm to solve the large scale problems is inevitable. The performance of these algorithms can be intensively promoted by other heuristic algorithms. In this study, a search method is developed that improves the quality of the solutions and competition time considerably in comparison with Genetic Algorithm. In the proposed algorithm, the genetic algorithms with the Nearest Neighbor Search (NNS are combined and a heuristic mutation operator is applied. According to the experimental results on a set of standard test problems with symmetric distances, the proposed algorithm finds the best solutions in most cases with the least computational time. The proposed algorithm is highly competitive with the published until now algorithms in both solution quality and running time.

Neurient: An Algorithm for Automatic Tracing of Confluent Neuronal Images to Determine Alignment

Science.gov (United States)

Mitchel, J.A.; Martin, I.S.

2013-01-01

A goal of neural tissue engineering is the development and evaluation of materials that guide neuronal growth and alignment. However, the methods available to quantitatively evaluate the response of neurons to guidance materials are limited and/or expensive, and may require manual tracing to be performed by the researcher. We have developed an open source, automated Matlab-based algorithm, building on previously published methods, to trace and quantify alignment of fluorescent images of neurons in culture. The algorithm is divided into three phases, including computation of a lookup table which contains directional information for each image, location of a set of seed points which may lie along neurite centerlines, and tracing neurites starting with each seed point and indexing into the lookup table. This method was used to obtain quantitative alignment data for complex images of densely cultured neurons. Complete automation of tracing allows for unsupervised processing of large numbers of images. Following image processing with our algorithm, available metrics to quantify neurite alignment include angular histograms, percent of neurite segments in a given direction, and mean neurite angle. The alignment information obtained from traced images can be used to compare the response of neurons to a range of conditions. This tracing algorithm is freely available to the scientific community under the name Neurient, and its implementation in Matlab allows a wide range of researchers to use a standardized, open source method to quantitatively evaluate the alignment of dense neuronal cultures. PMID:23384629

Geometric Algorithms for Private-Cache Chip Multiprocessors

DEFF Research Database (Denmark)

Ajwani, Deepak; Sitchinava, Nodari; Zeh, Norbert

2010-01-01

-D convex hulls. These results are obtained by analyzing adaptations of either the PEM merge sort algorithm or PRAM algorithms. For the second group of problems—orthogonal line segment intersection reporting, batched range reporting, and related problems—more effort is required. What distinguishes......We study techniques for obtaining efficient algorithms for geometric problems on private-cache chip multiprocessors. We show how to obtain optimal algorithms for interval stabbing counting, 1-D range counting, weighted 2-D dominance counting, and for computing 3-D maxima, 2-D lower envelopes, and 2...... these problems from the ones in the previous group is the variable output size, which requires I/O-efficient load balancing strategies based on the contribution of the individual input elements to the output size. To obtain nearly optimal algorithms for these problems, we introduce a parallel distribution...

Column Reduction of Polynomial Matrices; Some Remarks on the Algorithm of Wolovich

NARCIS (Netherlands)

Praagman, C.

1996-01-01

Recently an algorithm has been developed for column reduction of polynomial matrices. In a previous report the authors described a Fortran implementation of this algorithm. In this paper we compare the results of that implementation with an implementation of the algorithm originally developed by

Derivation of a regional active-optical reflectance sensor corn algorithm

Science.gov (United States)

Active-optical reflectance sensor (AORS) algorithms developed for in-season corn (Zea mays L.) N management have traditionally been derived using sub-regional scale information. However, studies have shown these previously developed AORS algorithms are not consistently accurate when used on a region...

An Electronic Publishing Model for Academic Publishers.

Science.gov (United States)

Gold, Jon D.

1994-01-01

Describes an electronic publishing model based on Standard Generalized Markup Language (SGML) and considers its use by an academic publisher. Highlights include how SGML is used to produce an electronic book, hypertext, methods of delivery, intellectual property rights, and future possibilities. Sample documents are included. (two references) (LRW)

An Active Sensor Algorithm for Corn Nitrogen Recommendations Based on a Chlorophyll Meter Algorithm

Science.gov (United States)

In previous work we found active canopy sensor reflectance assessments of corn (Zea mays L.) N status acquired at two growth stages (V11 and V15) have the greatest potential for directing in-season N applications, but emphasized an algorithm was needed to translate sensor readings into appropriate N...

Investigation of previously derived Hyades, Coma, and M67 reddenings

International Nuclear Information System (INIS)

Taylor, B.J.

1980-01-01

New Hyades polarimetry and field star photometry have been obtained to check the Hyades reddening, which was found to be nonzero in a previous paper. The new Hyades polarimetry implies essentially zero reddening; this is also true of polarimetry published by Behr (which was incorrectly interpreted in the previous paper). Four photometric techniques which are presumed to be insensitive to blanketing are used to compare the Hyades to nearby field stars; these four techniques also yield essentially zero reddening. When all of these results are combined with others which the author has previously published and a simultaneous solution for the Hyades, Coma, and M67 reddenings is made, the results are E (B-V) =3 +- 2 (sigma) mmag, -1 +- 3 (sigma) mmag, and 46 +- 6 (sigma) mmag, respectively. No support for a nonzero Hyades reddening is offered by the new results. When the newly obtained reddenings for the Hyades, Coma, and M67 are compared with results from techniques given by Crawford and by users of the David Dunlap Observatory photometric system, no differences between the new and other reddenings are found which are larger than about 2 sigma. The author had previously found that the M67 main-sequence stars have about the same blanketing as that of Coma and less blanketing than the Hyades; this conclusion is essentially unchanged by the revised reddenings

Two-Step Proximal Gradient Algorithm for Low-Rank Matrix Completion

Directory of Open Access Journals (Sweden)

Qiuyu Wang

2016-06-01

Full Text Available In this paper, we  propose a two-step proximal gradient algorithm to solve nuclear norm regularized least squares for the purpose of recovering low-rank data matrix from sampling of its entries. Each iteration generated by the proposed algorithm is a combination of the latest three points, namely, the previous point, the current iterate, and its proximal gradient point. This algorithm preserves the computational simplicity of classical proximal gradient algorithm where a singular value decomposition in proximal operator is involved. Global convergence is followed directly in the literature. Numerical results are reported to show the efficiency of the algorithm.

Charting taxonomic knowledge through ontologies and ranking algorithms

Science.gov (United States)

Huber, Robert; Klump, Jens

2009-04-01

Since the inception of geology as a modern science, paleontologists have described a large number of fossil species. This makes fossilized organisms an important tool in the study of stratigraphy and past environments. Since taxonomic classifications of organisms, and thereby their names, change frequently, the correct application of this tool requires taxonomic expertise in finding correct synonyms for a given species name. Much of this taxonomic information has already been published in journals and books where it is compiled in carefully prepared synonymy lists. Because this information is scattered throughout the paleontological literature, it is difficult to find and sometimes not accessible. Also, taxonomic information in the literature is often difficult to interpret for non-taxonomists looking for taxonomic synonymies as part of their research. The highly formalized structure makes Open Nomenclature synonymy lists ideally suited for computer aided identification of taxonomic synonyms. Because a synonymy list is a list of citations related to a taxon name, its bibliographic nature allows the application of bibliometric techniques to calculate the impact of synonymies and taxonomic concepts. TaxonRank is a ranking algorithm based on bibliometric analysis and Internet page ranking algorithms. TaxonRank uses published synonymy list data stored in TaxonConcept, a taxonomic information system. The basic ranking algorithm has been modified to include a measure of confidence on species identification based on the Open Nomenclature notation used in synonymy list, as well as other synonymy specific criteria. The results of our experiments show that the output of the proposed ranking algorithm gives a good estimate of the impact a published taxonomic concept has on the taxonomic opinions in the geological community. Also, our results show that treating taxonomic synonymies as part of on an ontology is a way to record and manage taxonomic knowledge, and thus contribute

Poet's Market, 1997: Where & How To Publish Your Poetry.

Science.gov (United States)

Martin, Christine, Ed.; Bentley, Chantelle, Ed.

This directory provides 1700 listings and evaluations of poetry publishers--300 more than in the previous edition--along with complete submission and contact information. Listings include both domestic and international markets, from mass circulation and literary magazines to small presses and university quarterlies, and contain complete profiles…

An administrative data validation study of the accuracy of algorithms for identifying rheumatoid arthritis: the influence of the reference standard on algorithm performance.

Science.gov (United States)

Widdifield, Jessica; Bombardier, Claire; Bernatsky, Sasha; Paterson, J Michael; Green, Diane; Young, Jacqueline; Ivers, Noah; Butt, Debra A; Jaakkimainen, R Liisa; Thorne, J Carter; Tu, Karen

2014-06-23

We have previously validated administrative data algorithms to identify patients with rheumatoid arthritis (RA) using rheumatology clinic records as the reference standard. Here we reassessed the accuracy of the algorithms using primary care records as the reference standard. We performed a retrospective chart abstraction study using a random sample of 7500 adult patients under the care of 83 family physicians contributing to the Electronic Medical Record Administrative data Linked Database (EMRALD) in Ontario, Canada. Using physician-reported diagnoses as the reference standard, we computed and compared the sensitivity, specificity, and predictive values for over 100 administrative data algorithms for RA case ascertainment. We identified 69 patients with RA for a lifetime RA prevalence of 0.9%. All algorithms had excellent specificity (>97%). However, sensitivity varied (75-90%) among physician billing algorithms. Despite the low prevalence of RA, most algorithms had adequate positive predictive value (PPV; 51-83%). The algorithm of "[1 hospitalization RA diagnosis code] or [3 physician RA diagnosis codes with ≥1 by a specialist over 2 years]" had a sensitivity of 78% (95% CI 69-88), specificity of 100% (95% CI 100-100), PPV of 78% (95% CI 69-88) and NPV of 100% (95% CI 100-100). Administrative data algorithms for detecting RA patients achieved a high degree of accuracy amongst the general population. However, results varied slightly from our previous report, which can be attributed to differences in the reference standards with respect to disease prevalence, spectrum of disease, and type of comparator group.

AlgoRun: a Docker-based packaging system for platform-agnostic implemented algorithms.

Science.gov (United States)

Hosny, Abdelrahman; Vera-Licona, Paola; Laubenbacher, Reinhard; Favre, Thibauld

2016-08-01

There is a growing need in bioinformatics for easy-to-use software implementations of algorithms that are usable across platforms. At the same time, reproducibility of computational results is critical and often a challenge due to source code changes over time and dependencies. The approach introduced in this paper addresses both of these needs with AlgoRun, a dedicated packaging system for implemented algorithms, using Docker technology. Implemented algorithms, packaged with AlgoRun, can be executed through a user-friendly interface directly from a web browser or via a standardized RESTful web API to allow easy integration into more complex workflows. The packaged algorithm includes the entire software execution environment, thereby eliminating the common problem of software dependencies and the irreproducibility of computations over time. AlgoRun-packaged algorithms can be published on http://algorun.org, a centralized searchable directory to find existing AlgoRun-packaged algorithms. AlgoRun is available at http://algorun.org and the source code under GPL license is available at https://github.com/algorun laubenbacher@uchc.edu Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Duality quantum algorithm efficiently simulates open quantum systems

Science.gov (United States)

Wei, Shi-Jie; Ruan, Dong; Long, Gui-Lu

2016-01-01

Because of inevitable coupling with the environment, nearly all practical quantum systems are open system, where the evolution is not necessarily unitary. In this paper, we propose a duality quantum algorithm for simulating Hamiltonian evolution of an open quantum system. In contrast to unitary evolution in a usual quantum computer, the evolution operator in a duality quantum computer is a linear combination of unitary operators. In this duality quantum algorithm, the time evolution of the open quantum system is realized by using Kraus operators which is naturally implemented in duality quantum computer. This duality quantum algorithm has two distinct advantages compared to existing quantum simulation algorithms with unitary evolution operations. Firstly, the query complexity of the algorithm is O(d3) in contrast to O(d4) in existing unitary simulation algorithm, where d is the dimension of the open quantum system. Secondly, By using a truncated Taylor series of the evolution operators, this duality quantum algorithm provides an exponential improvement in precision compared with previous unitary simulation algorithm. PMID:27464855

Improved algorithm for quantum separability and entanglement detection

International Nuclear Information System (INIS)

Ioannou, L.M.; Ekert, A.K.; Travaglione, B.C.; Cheung, D.

2004-01-01

Determining whether a quantum state is separable or entangled is a problem of fundamental importance in quantum information science. It has recently been shown that this problem is NP-hard, suggesting that an efficient, general solution does not exist. There is a highly inefficient 'basic algorithm' for solving the quantum separability problem which follows from the definition of a separable state. By exploiting specific properties of the set of separable states, we introduce a classical algorithm that solves the problem significantly faster than the 'basic algorithm', allowing a feasible separability test where none previously existed, e.g., in 3x3-dimensional systems. Our algorithm also provides a unique tool in the experimental detection of entanglement

A Systematic Approach to Modified BCJR MAP Algorithms for Convolutional Codes

Directory of Open Access Journals (Sweden)

Patenaude François

2006-01-01

Full Text Available Since Berrou, Glavieux and Thitimajshima published their landmark paper in 1993, different modified BCJR MAP algorithms have appeared in the literature. The existence of a relatively large number of similar but different modified BCJR MAP algorithms, derived using the Markov chain properties of convolutional codes, naturally leads to the following questions. What is the relationship among the different modified BCJR MAP algorithms? What are their relative performance, computational complexities, and memory requirements? In this paper, we answer these questions. We derive systematically four major modified BCJR MAP algorithms from the BCJR MAP algorithm using simple mathematical transformations. The connections between the original and the four modified BCJR MAP algorithms are established. A detailed analysis of the different modified BCJR MAP algorithms shows that they have identical computational complexities and memory requirements. Computer simulations demonstrate that the four modified BCJR MAP algorithms all have identical performance to the BCJR MAP algorithm.

Complexity optimization and high-throughput low-latency hardware implementation of a multi-electrode spike-sorting algorithm.

Science.gov (United States)

Dragas, Jelena; Jackel, David; Hierlemann, Andreas; Franke, Felix

2015-03-01

Reliable real-time low-latency spike sorting with large data throughput is essential for studies of neural network dynamics and for brain-machine interfaces (BMIs), in which the stimulation of neural networks is based on the networks' most recent activity. However, the majority of existing multi-electrode spike-sorting algorithms are unsuited for processing high quantities of simultaneously recorded data. Recording from large neuronal networks using large high-density electrode sets (thousands of electrodes) imposes high demands on the data-processing hardware regarding computational complexity and data transmission bandwidth; this, in turn, entails demanding requirements in terms of chip area, memory resources and processing latency. This paper presents computational complexity optimization techniques, which facilitate the use of spike-sorting algorithms in large multi-electrode-based recording systems. The techniques are then applied to a previously published algorithm, on its own, unsuited for large electrode set recordings. Further, a real-time low-latency high-performance VLSI hardware architecture of the modified algorithm is presented, featuring a folded structure capable of processing the activity of hundreds of neurons simultaneously. The hardware is reconfigurable “on-the-fly” and adaptable to the nonstationarities of neuronal recordings. By transmitting exclusively spike time stamps and/or spike waveforms, its real-time processing offers the possibility of data bandwidth and data storage reduction.

An Efficient Big Data Anonymization Algorithm Based on Chaos and Perturbation Techniques

Directory of Open Access Journals (Sweden)

Can Eyupoglu

2018-05-01

Full Text Available The topic of big data has attracted increasing interest in recent years. The emergence of big data leads to new difficulties in terms of protection models used for data privacy, which is of necessity for sharing and processing data. Protecting individuals’ sensitive information while maintaining the usability of the data set published is the most important challenge in privacy preserving. In this regard, data anonymization methods are utilized in order to protect data against identity disclosure and linking attacks. In this study, a novel data anonymization algorithm based on chaos and perturbation has been proposed for privacy and utility preserving in big data. The performance of the proposed algorithm is evaluated in terms of Kullback–Leibler divergence, probabilistic anonymity, classification accuracy, F-measure and execution time. The experimental results have shown that the proposed algorithm is efficient and performs better in terms of Kullback–Leibler divergence, classification accuracy and F-measure compared to most of the existing algorithms using the same data set. Resulting from applying chaos to perturb data, such successful algorithm is promising to be used in privacy preserving data mining and data publishing.

Structure-Based Algorithms for Microvessel Classification

KAUST Repository

Smith, Amy F.

2015-02-01

© 2014 The Authors. Microcirculation published by John Wiley & Sons Ltd. Objective: Recent developments in high-resolution imaging techniques have enabled digital reconstruction of three-dimensional sections of microvascular networks down to the capillary scale. To better interpret these large data sets, our goal is to distinguish branching trees of arterioles and venules from capillaries. Methods: Two novel algorithms are presented for classifying vessels in microvascular anatomical data sets without requiring flow information. The algorithms are compared with a classification based on observed flow directions (considered the gold standard), and with an existing resistance-based method that relies only on structural data. Results: The first algorithm, developed for networks with one arteriolar and one venular tree, performs well in identifying arterioles and venules and is robust to parameter changes, but incorrectly labels a significant number of capillaries as arterioles or venules. The second algorithm, developed for networks with multiple inlets and outlets, correctly identifies more arterioles and venules, but is more sensitive to parameter changes. Conclusions: The algorithms presented here can be used to classify microvessels in large microvascular data sets lacking flow information. This provides a basis for analyzing the distinct geometrical properties and modelling the functional behavior of arterioles, capillaries, and venules.

Generalized field-splitting algorithms for optimal IMRT delivery efficiency

Energy Technology Data Exchange (ETDEWEB)

Kamath, Srijit [Department of Radiation Oncology, University of Florida, Gainesville, FL (United States); Sahni, Sartaj [Department of Computer and Information Science and Engineering, University of Florida, Gainesville, FL (United States); Li, Jonathan [Department of Radiation Oncology, University of Florida, Gainesville, FL (United States); Ranka, Sanjay [Department of Computer and Information Science and Engineering, University of Florida, Gainesville, FL (United States); Palta, Jatinder [Department of Radiation Oncology, University of Florida, Gainesville, FL (United States)

2007-09-21

Intensity-modulated radiation therapy (IMRT) uses radiation beams of varying intensities to deliver varying doses of radiation to different areas of the tissue. The use of IMRT has allowed the delivery of higher doses of radiation to the tumor and lower doses to the surrounding healthy tissue. It is not uncommon for head and neck tumors, for example, to have large treatment widths that are not deliverable using a single field. In such cases, the intensity matrix generated by the optimizer needs to be split into two or three matrices, each of which may be delivered using a single field. Existing field-splitting algorithms used the pre-specified arbitrary split line or region where the intensity matrix is split along a column, i.e., all rows of the matrix are split along the same column (with or without the overlapping of split fields, i.e., feathering). If three fields result, then the two splits are along the same two columns for all rows. In this paper we study the problem of splitting a large field into two or three subfields with the field width as the only constraint, allowing for an arbitrary overlap of the split fields, so that the total MU efficiency of delivering the split fields is maximized. Proof of optimality is provided for the proposed algorithm. An average decrease of 18.8% is found in the total MUs when compared to the split generated by a commercial treatment planning system and that of 10% is found in the total MUs when compared to the split generated by our previously published algorithm. For more information on this article, see medicalphysicsweb.org.

Algorithms for the Computation of Debris Risk

Science.gov (United States)

Matney, Mark J.

2017-01-01

Determining the risks from space debris involve a number of statistical calculations. These calculations inevitably involve assumptions about geometry - including the physical geometry of orbits and the geometry of satellites. A number of tools have been developed in NASA’s Orbital Debris Program Office to handle these calculations; many of which have never been published before. These include algorithms that are used in NASA’s Orbital Debris Engineering Model ORDEM 3.0, as well as other tools useful for computing orbital collision rates and ground casualty risks. This paper presents an introduction to these algorithms and the assumptions upon which they are based.

Augmenting Data with Published Results in Bayesian Linear Regression

Science.gov (United States)

de Leeuw, Christiaan; Klugkist, Irene

2012-01-01

In most research, linear regression analyses are performed without taking into account published results (i.e., reported summary statistics) of similar previous studies. Although the prior density in Bayesian linear regression could accommodate such prior knowledge, formal models for doing so are absent from the literature. The goal of this…

Exact parallel maximum clique algorithm for general and protein graphs.

Science.gov (United States)

Depolli, Matjaž; Konc, Janez; Rozman, Kati; Trobec, Roman; Janežič, Dušanka

2013-09-23

A new exact parallel maximum clique algorithm MaxCliquePara, which finds the maximum clique (the fully connected subgraph) in undirected general and protein graphs, is presented. First, a new branch and bound algorithm for finding a maximum clique on a single computer core, which builds on ideas presented in two published state of the art sequential algorithms is implemented. The new sequential MaxCliqueSeq algorithm is faster than the reference algorithms on both DIMACS benchmark graphs as well as on protein-derived product graphs used for protein structural comparisons. Next, the MaxCliqueSeq algorithm is parallelized by splitting the branch-and-bound search tree to multiple cores, resulting in MaxCliquePara algorithm. The ability to exploit all cores efficiently makes the new parallel MaxCliquePara algorithm markedly superior to other tested algorithms. On a 12-core computer, the parallelization provides up to 2 orders of magnitude faster execution on the large DIMACS benchmark graphs and up to an order of magnitude faster execution on protein product graphs. The algorithms are freely accessible on http://commsys.ijs.si/~matjaz/maxclique.

Length-Bounded Hybrid CPU/GPU Pattern Matching Algorithm for Deep Packet Inspection

Directory of Open Access Journals (Sweden)

Yi-Shan Lin

2017-01-01

Full Text Available Since frequent communication between applications takes place in high speed networks, deep packet inspection (DPI plays an important role in the network application awareness. The signature-based network intrusion detection system (NIDS contains a DPI technique that examines the incoming packet payloads by employing a pattern matching algorithm that dominates the overall inspection performance. Existing studies focused on implementing efficient pattern matching algorithms by parallel programming on software platforms because of the advantages of lower cost and higher scalability. Either the central processing unit (CPU or the graphic processing unit (GPU were involved. Our studies focused on designing a pattern matching algorithm based on the cooperation between both CPU and GPU. In this paper, we present an enhanced design for our previous work, a length-bounded hybrid CPU/GPU pattern matching algorithm (LHPMA. In the preliminary experiment, the performance and comparison with the previous work are displayed, and the experimental results show that the LHPMA can achieve not only effective CPU/GPU cooperation but also higher throughput than the previous method.

A simple greedy algorithm for dynamic graph orientation

DEFF Research Database (Denmark)

Berglin, Edvin; Brodal, Gerth Stølting

2017-01-01

Graph orientations with low out-degree are one of several ways to efficiently store sparse graphs. If the graphs allow for insertion and deletion of edges, one may have to flip the orientation of some edges to prevent blowing up the maximum out-degree. We use arboricity as our sparsity measure....... With an immensely simple greedy algorithm, we get parametrized trade-off bounds between out-degree and worst case number of flips, which previously only existed for amortized number of flips. We match the previous best worst-case algorithm (in O(log n) flips) for general arboricity and beat it for either constant...... or super-logarithmic arboricity. We also match a previous best amortized result for at least logarithmic arboricity, and give the first results with worst-case O(1) and O(sqrt(log n)) flips nearly matching degree bounds to their respective amortized solutions....

Desiderata for computable representations of electronic health records-driven phenotype algorithms.

Science.gov (United States)

Mo, Huan; Thompson, William K; Rasmussen, Luke V; Pacheco, Jennifer A; Jiang, Guoqian; Kiefer, Richard; Zhu, Qian; Xu, Jie; Montague, Enid; Carrell, David S; Lingren, Todd; Mentch, Frank D; Ni, Yizhao; Wehbe, Firas H; Peissig, Peggy L; Tromp, Gerard; Larson, Eric B; Chute, Christopher G; Pathak, Jyotishman; Denny, Joshua C; Speltz, Peter; Kho, Abel N; Jarvik, Gail P; Bejan, Cosmin A; Williams, Marc S; Borthwick, Kenneth; Kitchner, Terrie E; Roden, Dan M; Harris, Paul A

2015-11-01

Electronic health records (EHRs) are increasingly used for clinical and translational research through the creation of phenotype algorithms. Currently, phenotype algorithms are most commonly represented as noncomputable descriptive documents and knowledge artifacts that detail the protocols for querying diagnoses, symptoms, procedures, medications, and/or text-driven medical concepts, and are primarily meant for human comprehension. We present desiderata for developing a computable phenotype representation model (PheRM). A team of clinicians and informaticians reviewed common features for multisite phenotype algorithms published in PheKB.org and existing phenotype representation platforms. We also evaluated well-known diagnostic criteria and clinical decision-making guidelines to encompass a broader category of algorithms. We propose 10 desired characteristics for a flexible, computable PheRM: (1) structure clinical data into queryable forms; (2) recommend use of a common data model, but also support customization for the variability and availability of EHR data among sites; (3) support both human-readable and computable representations of phenotype algorithms; (4) implement set operations and relational algebra for modeling phenotype algorithms; (5) represent phenotype criteria with structured rules; (6) support defining temporal relations between events; (7) use standardized terminologies and ontologies, and facilitate reuse of value sets; (8) define representations for text searching and natural language processing; (9) provide interfaces for external software algorithms; and (10) maintain backward compatibility. A computable PheRM is needed for true phenotype portability and reliability across different EHR products and healthcare systems. These desiderata are a guide to inform the establishment and evolution of EHR phenotype algorithm authoring platforms and languages. © The Author 2015. Published by Oxford University Press on behalf of the American Medical

Quantifying the costs and benefits of privacy-preserving health data publishing.

Science.gov (United States)

Khokhar, Rashid Hussain; Chen, Rui; Fung, Benjamin C M; Lui, Siu Man

2014-08-01

Cost-benefit analysis is a prerequisite for making good business decisions. In the business environment, companies intend to make profit from maximizing information utility of published data while having an obligation to protect individual privacy. In this paper, we quantify the trade-off between privacy and data utility in health data publishing in terms of monetary value. We propose an analytical cost model that can help health information custodians (HICs) make better decisions about sharing person-specific health data with other parties. We examine relevant cost factors associated with the value of anonymized data and the possible damage cost due to potential privacy breaches. Our model guides an HIC to find the optimal value of publishing health data and could be utilized for both perturbative and non-perturbative anonymization techniques. We show that our approach can identify the optimal value for different privacy models, including K-anonymity, LKC-privacy, and ∊-differential privacy, under various anonymization algorithms and privacy parameters through extensive experiments on real-life data. Copyright © 2014 Elsevier Inc. All rights reserved.

Developing an Enhanced Lightning Jump Algorithm for Operational Use

Science.gov (United States)

Schultz, Christopher J.; Petersen, Walter A.; Carey, Lawrence D.

2009-01-01

Overall Goals: 1. Build on the lightning jump framework set through previous studies. 2. Understand what typically occurs in nonsevere convection with respect to increases in lightning. 3. Ultimately develop a lightning jump algorithm for use on the Geostationary Lightning Mapper (GLM). 4 Lightning jump algorithm configurations were developed (2(sigma), 3(sigma), Threshold 10 and Threshold 8). 5 algorithms were tested on a population of 47 nonsevere and 38 severe thunderstorms. Results indicate that the 2(sigma) algorithm performed best over the entire thunderstorm sample set with a POD of 87%, a far of 35%, a CSI of 59% and a HSS of 75%.

jClustering, an open framework for the development of 4D clustering algorithms.

Directory of Open Access Journals (Sweden)

José María Mateos-Pérez

Full Text Available We present jClustering, an open framework for the design of clustering algorithms in dynamic medical imaging. We developed this tool because of the difficulty involved in manually segmenting dynamic PET images and the lack of availability of source code for published segmentation algorithms. Providing an easily extensible open tool encourages publication of source code to facilitate the process of comparing algorithms and provide interested third parties with the opportunity to review code. The internal structure of the framework allows an external developer to implement new algorithms easily and quickly, focusing only on the particulars of the method being implemented and not on image data handling and preprocessing. This tool has been coded in Java and is presented as an ImageJ plugin in order to take advantage of all the functionalities offered by this imaging analysis platform. Both binary packages and source code have been published, the latter under a free software license (GNU General Public License to allow modification if necessary.

Comparison of switching control algorithms effective in restricting the switching in the neighborhood of the origin

International Nuclear Information System (INIS)

Joung, JinWook; Chung, Lan; Smyth, Andrew W

2010-01-01

The active interaction control (AIC) system consisting of a primary structure, an auxiliary structure and an interaction element was proposed to protect the primary structure against earthquakes and winds. The objective of the AIC system in reducing the responses of the primary structure is fulfilled by activating or deactivating the switching between the engagement and the disengagement of the primary and auxiliary structures through the interaction element. The status of the interaction element is controlled by switching control algorithms. The previously developed switching control algorithms require an excessive amount of switching, which is inefficient. In this paper, the excessive amount of switching is restricted by imposing an appropriately designed switching boundary region, where switching is prohibited, on pre-designed engagement–disengagement conditions. Two different approaches are used in designing the newly proposed AID-off and AID-off 2 algorithms. The AID-off 2 algorithm is designed to affect deactivated switching regions explicitly, unlike the AID-off algorithm, which follows the same procedure of designing the engagement–disengagement conditions of the previously developed algorithms, by using the current status of the AIC system. Both algorithms are shown to be effective in reducing the amount of switching times triggered from the previously developed AID algorithm under an appropriately selected control sampling period for different earthquakes, but the AID-off 2 algorithm outperforms the AID-off algorithm in reducing the number of switching times

TITRATION: A Randomized Study to Assess 2 Treatment Algorithms with New Insulin Glargine 300 units/mL.

Science.gov (United States)

Yale, Jean-François; Berard, Lori; Groleau, Mélanie; Javadi, Pasha; Stewart, John; Harris, Stewart B

2017-10-01

It was uncertain whether an algorithm that involves increasing insulin dosages by 1 unit/day may cause more hypoglycemia with the longer-acting insulin glargine 300 units/mL (GLA-300). The objective of this study was to compare safety and efficacy of 2 titration algorithms, INSIGHT and EDITION, for GLA-300 in people with uncontrolled type 2 diabetes mellitus, mainly in a primary care setting. This was a 12-week, open-label, randomized, multicentre pilot study. Participants were randomly assigned to 1 of 2 algorithms: they either increased their dosage by 1 unit/day (INSIGHT, n=108) or the dose was adjusted by the investigator at least once weekly, but no more often than every 3 days (EDITION, n=104). The target fasting self-monitored blood glucose was in the range of 4.4 to 5.6 mmol/L. The percentages of participants reaching the primary endpoint of fasting self-monitored blood glucose ≤5.6 mmol/L without nocturnal hypoglycemia were 19.4% (INSIGHT) and 18.3% (EDITION). At week 12, 26.9% (INSIGHT) and 28.8% (EDITION) of participants achieved a glycated hemoglobin value of ≤7%. No differences in the incidence of hypoglycemia of any category were noted between algorithms. Participants in both arms of the study were much more satisfied with their new treatment as assessed by the Diabetes Treatment Satisfaction Questionnaire. Most health-care professionals (86%) preferred the INSIGHT over the EDITION algorithm. The frequency of adverse events was similar between algorithms. A patient-driven titration algorithm of 1 unit/day with GLA-300 is effective and comparable to the previously tested EDITION algorithm and is preferred by health-care professionals. Copyright © 2017 Diabetes Canada. Published by Elsevier Inc. All rights reserved.

THE QUALITY CRITERIA AND SELF-PUBLISHING IN SCIENTIFIC PUBLISHING

Directory of Open Access Journals (Sweden)

Almudena Mangas-Vega

2015-11-01

Full Text Available Self-publishing is a growing phenomenon in recent years. It is a process that goes beyond a simple change of leader in the publication, since it involves also a change of role of agents that were consolidated over time. A self-published work does not have to mean lack of quality, so it is important to define parameters and indicators that help its evaluation and identify who has the responsibility of those criteria. The article shows these aspects from the possibilities for cross-platform publishing and concludes with an analysis of the aspects that can be considered in assessing the quality of self-publishing.

Parallel Algorithms for the Exascale Era

Energy Technology Data Exchange (ETDEWEB)

Robey, Robert W. [Los Alamos National Laboratory

2016-10-19

New parallel algorithms are needed to reach the Exascale level of parallelism with millions of cores. We look at some of the research developed by students in projects at LANL. The research blends ideas from the early days of computing while weaving in the fresh approach brought by students new to the field of high performance computing. We look at reproducibility of global sums and why it is important to parallel computing. Next we look at how the concept of hashing has led to the development of more scalable algorithms suitable for next-generation parallel computers. Nearly all of this work has been done by undergraduates and published in leading scientific journals.

SU-G-JeP1-12: Head-To-Head Performance Characterization of Two Multileaf Collimator Tracking Algorithms for Radiotherapy

International Nuclear Information System (INIS)

Caillet, V; Colvill, E; O’Brien, R; Keall, P; Poulsen, P; Moore, D; Booth, J; Sawant, A

2016-01-01

Purpose: Multi-leaf collimator (MLC) tracking is being clinically pioneered to continuously compensate for thoracic and abdominal motion during radiotherapy. The purpose of this work is to characterize the performance of two MLC tracking algorithms for cancer radiotherapy, based on a direct optimization and a piecewise leaf fitting approach respectively. Methods: To test the algorithms, both physical and in silico experiments were performed. Previously published high and low modulation VMAT plans for lung and prostate cancer cases were used along with eight patient-measured organ-specific trajectories. For both MLC tracking algorithm, the plans were run with their corresponding patient trajectories. The physical experiments were performed on a Trilogy Varian linac and a programmable phantom (HexaMotion platform). For each MLC tracking algorithm, plan and patient trajectory, the tracking accuracy was quantified as the difference in aperture area between ideal and fitted MLC. To compare algorithms, the average cumulative tracking error area for each experiment was calculated. The two-sample Kolmogorov-Smirnov (KS) test was used to evaluate the cumulative tracking errors between algorithms. Results: Comparison of tracking errors for the physical and in silico experiments showed minor differences between the two algorithms. The KS D-statistics for the physical experiments were below 0.05 denoting no significant differences between the two distributions pattern and the average error area (direct optimization/piecewise leaf-fitting) were comparable (66.64 cm2/65.65 cm2). For the in silico experiments, the KS D-statistics were below 0.05 and the average errors area were also equivalent (49.38 cm2/48.98 cm2). Conclusion: The comparison between the two leaf fittings algorithms demonstrated no significant differences in tracking errors, neither in a clinically realistic environment nor in silico. The similarities in the two independent algorithms give confidence in the use

SU-G-JeP1-12: Head-To-Head Performance Characterization of Two Multileaf Collimator Tracking Algorithms for Radiotherapy

Energy Technology Data Exchange (ETDEWEB)

Caillet, V; Colvill, E [School of Medecine, The University of Sydney, Sydney, NSW (Australia); Royal North Shore Hospital, St Leonards, Sydney (Australia); O’Brien, R; Keall, P [School of Medecine, The University of Sydney, Sydney, NSW (Australia); Poulsen, P [Aarhus University Hospital, Aarhus (Denmark); Moore, D [UT Southwestern Medical Center, Dallas, TX (United States); University of Maryland School of Medicine, Baltimore, MD (United States); Booth, J [Royal North Shore Hospital, St Leonards, Sydney (Australia); Sawant, A [University of Maryland School of Medicine, Baltimore, MD (United States)

2016-06-15

Purpose: Multi-leaf collimator (MLC) tracking is being clinically pioneered to continuously compensate for thoracic and abdominal motion during radiotherapy. The purpose of this work is to characterize the performance of two MLC tracking algorithms for cancer radiotherapy, based on a direct optimization and a piecewise leaf fitting approach respectively. Methods: To test the algorithms, both physical and in silico experiments were performed. Previously published high and low modulation VMAT plans for lung and prostate cancer cases were used along with eight patient-measured organ-specific trajectories. For both MLC tracking algorithm, the plans were run with their corresponding patient trajectories. The physical experiments were performed on a Trilogy Varian linac and a programmable phantom (HexaMotion platform). For each MLC tracking algorithm, plan and patient trajectory, the tracking accuracy was quantified as the difference in aperture area between ideal and fitted MLC. To compare algorithms, the average cumulative tracking error area for each experiment was calculated. The two-sample Kolmogorov-Smirnov (KS) test was used to evaluate the cumulative tracking errors between algorithms. Results: Comparison of tracking errors for the physical and in silico experiments showed minor differences between the two algorithms. The KS D-statistics for the physical experiments were below 0.05 denoting no significant differences between the two distributions pattern and the average error area (direct optimization/piecewise leaf-fitting) were comparable (66.64 cm2/65.65 cm2). For the in silico experiments, the KS D-statistics were below 0.05 and the average errors area were also equivalent (49.38 cm2/48.98 cm2). Conclusion: The comparison between the two leaf fittings algorithms demonstrated no significant differences in tracking errors, neither in a clinically realistic environment nor in silico. The similarities in the two independent algorithms give confidence in the use

Embracing Electronic Publishing.

Science.gov (United States)

Wills, Gordon

1996-01-01

Electronic publishing is the grandest revolution in the capture and dissemination of academic and professional knowledge since Caxton developed the printing press. This article examines electronic publishing, describes different electronic publishing scenarios (authors' cooperative, consolidator/retailer/agent oligopsony, publisher oligopoly), and…

Efficient conjugate gradient algorithms for computation of the manipulator forward dynamics

Science.gov (United States)

Fijany, Amir; Scheid, Robert E.

1989-01-01

The applicability of conjugate gradient algorithms for computation of the manipulator forward dynamics is investigated. The redundancies in the previously proposed conjugate gradient algorithm are analyzed. A new version is developed which, by avoiding these redundancies, achieves a significantly greater efficiency. A preconditioned conjugate gradient algorithm is also presented. A diagonal matrix whose elements are the diagonal elements of the inertia matrix is proposed as the preconditioner. In order to increase the computational efficiency, an algorithm is developed which exploits the synergism between the computation of the diagonal elements of the inertia matrix and that required by the conjugate gradient algorithm.

Enabling Large-Scale IoT-Based Services through Elastic Publish/Subscribe.

Science.gov (United States)

Vavassori, Sergio; Soriano, Javier; Fernández, Rafael

2017-09-19

In this paper, we report an algorithm that is designed to leverage the cloud as infrastructure to support Internet of Things (IoT) by elastically scaling in/out so that IoT-based service users never stop receiving sensors' data. This algorithm is able to provide an uninterrupted service to end users even during the scaling operation since its internal state repartitioning is transparent for publishers or subscribers; its scaling operation is time-bounded and depends only on the dimension of the state partitions to be transmitted to the different nodes. We describe its implementation in E-SilboPS, an elastic content-based publish/subscribe (CBPS) system specifically designed to support context-aware sensing and communication in IoT-based services. E-SilboPS is a key internal asset of the FIWARE IoT services enablement platform, which offers an architecture of components specifically designed to capture data from, or act upon, IoT devices as easily as reading/changing the value of attributes linked to context entities. In addition, we discuss the quantitative measurements used to evaluate the scale-out process, as well as the results of this evaluation. This new feature rounds out the context-aware content-based features of E-SilboPS by providing, for example, the necessary middleware for constructing dashboards and monitoring panels that are capable of dynamically changing queries and continuously handling data in IoT-based services.

Automated training for algorithms that learn from genomic data.

Science.gov (United States)

Cilingir, Gokcen; Broschat, Shira L

2015-01-01

Supervised machine learning algorithms are used by life scientists for a variety of objectives. Expert-curated public gene and protein databases are major resources for gathering data to train these algorithms. While these data resources are continuously updated, generally, these updates are not incorporated into published machine learning algorithms which thereby can become outdated soon after their introduction. In this paper, we propose a new model of operation for supervised machine learning algorithms that learn from genomic data. By defining these algorithms in a pipeline in which the training data gathering procedure and the learning process are automated, one can create a system that generates a classifier or predictor using information available from public resources. The proposed model is explained using three case studies on SignalP, MemLoci, and ApicoAP in which existing machine learning models are utilized in pipelines. Given that the vast majority of the procedures described for gathering training data can easily be automated, it is possible to transform valuable machine learning algorithms into self-evolving learners that benefit from the ever-changing data available for gene products and to develop new machine learning algorithms that are similarly capable.

Analysis of thirteen predatory publishers: a trap for eager-to-publish researchers.

Science.gov (United States)

Bolshete, Pravin

2018-01-01

To demonstrate a strategy employed by predatory publishers to trap eager-to-publish authors or researchers into submitting their work. This was a case study of 13 potential, possible, or probable predatory scholarly open-access publishers with similar characteristics. Eleven publishers were included from Beall's list and two additional publishers were identified from a Google web search. Each publisher's site was visited and its content analyzed. Publishers publishing biomedical journals were further explored and additional data was collected regarding their volumes, details of publications and editorial-board members. Overall, the look and feel of all 13 publishers was similar including names of publishers, website addresses, homepage content, homepage images, list of journals and subject areas, as if they were copied and pasted. There were discrepancies in article-processing charges within the publishers. None of the publishers identified names in their contact details and primarily included only email addresses. Author instructions were similar across all 13 publishers. Most publishers listed journals of varied subject areas including biomedical journals (12 publishers) covering different geographic locations. Most biomedical journals published none or very few articles. The highest number of articles published by any single biomedical journal was 28. Several editorial-board members were listed across more than one journals, with one member listed 81 times in different 69 journals (i.e. twice in 12 journals). There was a strong reason to believe that predatory publishers may have several publication houses with different names under a single roof to trap authors from different geographic locations.

A New Plant Intelligent Behaviour Optimisation Algorithm for Solving Vehicle Routing Problem

OpenAIRE

Chagwiza, Godfrey

2018-01-01

A new plant intelligent behaviour optimisation algorithm is developed. The algorithm is motivated by intelligent behaviour of plants and is implemented to solve benchmark vehicle routing problems of all sizes, and results were compared to those in literature. The results show that the new algorithm outperforms most of algorithms it was compared to for very large and large vehicle routing problem instances. This is attributed to the ability of the plant to use previously stored memory to respo...

Expediting Combinatorial Data Set Analysis by Combining Human and Algorithmic Analysis.

Science.gov (United States)

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.

DELISHUS: an efficient and exact algorithm for genome-wide detection of deletion polymorphism in autism

Science.gov (United States)

Aguiar, Derek; Halldórsson, Bjarni V.; Morrow, Eric M.; Istrail, Sorin

2012-01-01

Motivation: The understanding of the genetic determinants of complex disease is undergoing a paradigm shift. Genetic heterogeneity of rare mutations with deleterious effects is more commonly being viewed as a major component of disease. Autism is an excellent example where research is active in identifying matches between the phenotypic and genomic heterogeneities. A considerable portion of autism appears to be correlated with copy number variation, which is not directly probed by single nucleotide polymorphism (SNP) array or sequencing technologies. Identifying the genetic heterogeneity of small deletions remains a major unresolved computational problem partly due to the inability of algorithms to detect them. Results: In this article, we present an algorithmic framework, which we term DELISHUS, that implements three exact algorithms for inferring regions of hemizygosity containing genomic deletions of all sizes and frequencies in SNP genotype data. We implement an efficient backtracking algorithm—that processes a 1 billion entry genome-wide association study SNP matrix in a few minutes—to compute all inherited deletions in a dataset. We further extend our model to give an efficient algorithm for detecting de novo deletions. Finally, given a set of called deletions, we also give a polynomial time algorithm for computing the critical regions of recurrent deletions. DELISHUS achieves significantly lower false-positive rates and higher power than previously published algorithms partly because it considers all individuals in the sample simultaneously. DELISHUS may be applied to SNP array or sequencing data to identify the deletion spectrum for family-based association studies. Availability: DELISHUS is available at http://www.brown.edu/Research/Istrail_Lab/. Contact: Eric_Morrow@brown.edu and Sorin_Istrail@brown.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:22689755

A Numerical Instability in an ADI Algorithm for Gyrokinetics

International Nuclear Information System (INIS)

Belli, E.A.; Hammett, G.W.

2004-01-01

We explore the implementation of an Alternating Direction Implicit (ADI) algorithm for a gyrokinetic plasma problem and its resulting numerical stability properties. This algorithm, which uses a standard ADI scheme to divide the field solve from the particle distribution function advance, has previously been found to work well for certain plasma kinetic problems involving one spatial and two velocity dimensions, including collisions and an electric field. However, for the gyrokinetic problem we find a severe stability restriction on the time step. Furthermore, we find that this numerical instability limitation also affects some other algorithms, such as a partially implicit Adams-Bashforth algorithm, where the parallel motion operator v parallel ∂/∂z is treated implicitly and the field terms are treated with an Adams-Bashforth explicit scheme. Fully explicit algorithms applied to all terms can be better at long wavelengths than these ADI or partially implicit algorithms

Hybrid Modeling KMeans – Genetic Algorithms in the Health Care Data

Directory of Open Access Journals (Sweden)

Tessy Badriyah

2013-06-01

Full Text Available K-Means is one of the major algorithms widely used in clustering due to its good computational performance. However, K-Means is very sensitive to the initially selected points which randomly selected, and therefore it does not always generate optimum solutions. Genetic algorithm approach can be applied to solve this problem. In this research we examine the potential of applying hybrid GA- KMeans with focus on the area of health care data. We proposed a new technique using hybrid method combining KMeans Clustering and Genetic Algorithms, called the “Hybrid K-Means Genetic Algorithms” (HKGA. HKGA combines the power of Genetic Algorithms and the efficiency of K-Means Clustering. We compare our results with other conventional algorithms and also with other published research as well. Our results demonstrate that the HKGA achieves very good results and in some cases superior to other methods. Keywords: Machine Learning, K-Means, Genetic Algorithms, Hybrid KMeans Genetic Algorithm (HGKA.

Quantum algorithms for the ordered search problem via semidefinite programming

International Nuclear Information System (INIS)

Childs, Andrew M.; Landahl, Andrew J.; Parrilo, Pablo A.

2007-01-01

One of the most basic computational problems is the task of finding a desired item in an ordered list of N items. While the best classical algorithm for this problem uses log 2 N queries to the list, a quantum computer can solve the problem using a constant factor fewer queries. However, the precise value of this constant is unknown. By characterizing a class of quantum query algorithms for the ordered search problem in terms of a semidefinite program, we find quantum algorithms for small instances of the ordered search problem. Extending these algorithms to arbitrarily large instances using recursion, we show that there is an exact quantum ordered search algorithm using 4 log 605 N≅0.433 log 2 N queries, which improves upon the previously best known exact algorithm

Reproducibility discrepancies following reanalysis of raw data for a previously published study on diisononyl phthalate (DINP in rats

Directory of Open Access Journals (Sweden)

Min Chen

2017-08-01

Full Text Available A 2011 publication by Boberg et al. entitled “Reproductive and behavioral effects of diisononyl phthalate (DINP in perinatally exposed rats” [1] reported statistically significant changes in sperm parameters, testicular histopathology, anogenital distance and retained nipples in developing males. Using the statistical methods as reported by Boberg et al. (2011 [1], we reanalyzed the publically available raw data ([dataset] US EPA (United States Environmental Protection Agency, 2016 [2]. The output of our reanalysis and the discordances with the data as published in Boberg et al. (2011 [1] are highlighted herein. Further discussion of the basis for the replication discordances and the insufficiency of the Boberg et al. (2011 [1] response to address them can be found in a companion letter of correspondence (doi: 10.1016/j.reprotox.2017.03.013.; (Morfeld et al., 2011 [3].

A Faster Algorithm for Computing Straight Skeletons

KAUST Repository

Cheng, Siu-Wing

2014-09-01

We present a new algorithm for computing the straight skeleton of a polygon. For a polygon with n vertices, among which r are reflex vertices, we give a deterministic algorithm that reduces the straight skeleton computation to a motorcycle graph computation in O(n (logn)logr) time. It improves on the previously best known algorithm for this reduction, which is randomized, and runs in expected O(n√h+1log2n) time for a polygon with h holes. Using known motorcycle graph algorithms, our result yields improved time bounds for computing straight skeletons. In particular, we can compute the straight skeleton of a non-degenerate polygon in O(n (logn) logr + r 4/3 + ε ) time for any ε > 0. On degenerate input, our time bound increases to O(n (logn) logr + r 17/11 + ε ).

A Faster Algorithm for Computing Straight Skeletons

KAUST Repository

Mencel, Liam A.

2014-05-06

We present a new algorithm for computing the straight skeleton of a polygon. For a polygon with n vertices, among which r are reflex vertices, we give a deterministic algorithm that reduces the straight skeleton computation to a motorcycle graph computation in O(n (log n) log r) time. It improves on the previously best known algorithm for this reduction, which is randomised, and runs in expected O(n √(h+1) log² n) time for a polygon with h holes. Using known motorcycle graph algorithms, our result yields improved time bounds for computing straight skeletons. In particular, we can compute the straight skeleton of a non-degenerate polygon in O(n (log n) log r + r^(4/3 + ε)) time for any ε > 0. On degenerate input, our time bound increases to O(n (log n) log r + r^(17/11 + ε))

A Faster Algorithm for Computing Straight Skeletons

KAUST Repository

Cheng, Siu-Wing; Mencel, Liam A.; Vigneron, Antoine E.

2014-01-01

We present a new algorithm for computing the straight skeleton of a polygon. For a polygon with n vertices, among which r are reflex vertices, we give a deterministic algorithm that reduces the straight skeleton computation to a motorcycle graph computation in O(n (logn)logr) time. It improves on the previously best known algorithm for this reduction, which is randomized, and runs in expected O(n√h+1log2n) time for a polygon with h holes. Using known motorcycle graph algorithms, our result yields improved time bounds for computing straight skeletons. In particular, we can compute the straight skeleton of a non-degenerate polygon in O(n (logn) logr + r 4/3 + ε ) time for any ε > 0. On degenerate input, our time bound increases to O(n (logn) logr + r 17/11 + ε ).

Algorithms for the Computation of Debris Risks

Science.gov (United States)

Matney, Mark

2017-01-01

Determining the risks from space debris involve a number of statistical calculations. These calculations inevitably involve assumptions about geometry - including the physical geometry of orbits and the geometry of non-spherical satellites. A number of tools have been developed in NASA's Orbital Debris Program Office to handle these calculations; many of which have never been published before. These include algorithms that are used in NASA's Orbital Debris Engineering Model ORDEM 3.0, as well as other tools useful for computing orbital collision rates and ground casualty risks. This paper will present an introduction to these algorithms and the assumptions upon which they are based.

PCTFPeval: a web tool for benchmarking newly developed algorithms for predicting cooperative transcription factor pairs in yeast.

Science.gov (United States)

Lai, Fu-Jou; Chang, Hong-Tsun; Wu, Wei-Sheng

2015-01-01

Computational identification of cooperative transcription factor (TF) pairs helps understand the combinatorial regulation of gene expression in eukaryotic cells. Many advanced algorithms have been proposed to predict cooperative TF pairs in yeast. However, it is still difficult to conduct a comprehensive and objective performance comparison of different algorithms because of lacking sufficient performance indices and adequate overall performance scores. To solve this problem, in our previous study (published in BMC Systems Biology 2014), we adopted/proposed eight performance indices and designed two overall performance scores to compare the performance of 14 existing algorithms for predicting cooperative TF pairs in yeast. Most importantly, our performance comparison framework can be applied to comprehensively and objectively evaluate the performance of a newly developed algorithm. However, to use our framework, researchers have to put a lot of effort to construct it first. To save researchers time and effort, here we develop a web tool to implement our performance comparison framework, featuring fast data processing, a comprehensive performance comparison and an easy-to-use web interface. The developed tool is called PCTFPeval (Predicted Cooperative TF Pair evaluator), written in PHP and Python programming languages. The friendly web interface allows users to input a list of predicted cooperative TF pairs from their algorithm and select (i) the compared algorithms among the 15 existing algorithms, (ii) the performance indices among the eight existing indices, and (iii) the overall performance scores from two possible choices. The comprehensive performance comparison results are then generated in tens of seconds and shown as both bar charts and tables. The original comparison results of each compared algorithm and each selected performance index can be downloaded as text files for further analyses. Allowing users to select eight existing performance indices and 15

Quantum signature scheme based on a quantum search algorithm

International Nuclear Information System (INIS)

Yoon, Chun Seok; Kang, Min Sung; Lim, Jong In; Yang, Hyung Jin

2015-01-01

We present a quantum signature scheme based on a two-qubit quantum search algorithm. For secure transmission of signatures, we use a quantum search algorithm that has not been used in previous quantum signature schemes. A two-step protocol secures the quantum channel, and a trusted center guarantees non-repudiation that is similar to other quantum signature schemes. We discuss the security of our protocol. (paper)

Implementation of software-based sensor linearization algorithms on low-cost microcontrollers.

Science.gov (United States)

Erdem, Hamit

2010-10-01

Nonlinear sensors and microcontrollers are used in many embedded system designs. As the input-output characteristic of most sensors is nonlinear in nature, obtaining data from a nonlinear sensor by using an integer microcontroller has always been a design challenge. This paper discusses the implementation of six software-based sensor linearization algorithms for low-cost microcontrollers. The comparative study of the linearization algorithms is performed by using a nonlinear optical distance-measuring sensor. The performance of the algorithms is examined with respect to memory space usage, linearization accuracy and algorithm execution time. The implementation and comparison results can be used for selection of a linearization algorithm based on the sensor transfer function, expected linearization accuracy and microcontroller capacity. Copyright © 2010 ISA. Published by Elsevier Ltd. All rights reserved.

Assessment of available integration algorithms for initial value ordinary differential equations

International Nuclear Information System (INIS)

Carver, M.B.; Stewart, D.G.

1979-11-01

There exists an extremely large number of algorithms designed for the ordinary differential equation initial value problem. The integration is normally done by a finite sum at time intervals which are chosen dynamically to satisfy an imposed error tolerance. This report describes the basic logistics of the integration process, identifies common areas of difficulty, and establishes a comprehensive test profile for integration algorithms. A number of algorithms are described, and selected published subroutines are evaluated using the test profile. It concludes that an effective library for general use need have only two such routines. The two selected are versions of the well-known Gear and Runge-Kutta-Fehlberg algorithms. Full documentation and listings are included. (auth)

Assistance algorithm of nursing for amiodarone intravenous infusion

Directory of Open Access Journals (Sweden)

Francimar Tinoco de Oliveira

2014-12-01

Full Text Available This study aimed at identifying scientific publication on phlebitis caused by amiodarone and proposes a nursing care algorithm for interventions in intravenous amiodarone administration grounded in the Infusion Nursing Society and the Center for Disease Control and Prevention. It is a descriptive study mediated by integrative review in MedLine, LILACS, IBECS, BDENF, Cochrane Library and Scielo bases, published from 2006 to 2013. The sample consisted of nine articles. The evidence pointed the incidence of phlebitis due to the infusion of amiodarone and the need to control this event. The algorithm proposed shows the materials to be used and the procedure of drug administration in order to minimize injury. Besides subsidizing the development of future studies, this algorithm also promotes the incorporation of the best recommendation for the interventionist clinical practice.

BLINCK?A diagnostic algorithm for skin cancer diagnosis combining clinical features with dermatoscopy findings

OpenAIRE

Bourne, Peter; Rosendahl, Cliff; Keir, Jeff; Cameron, Alan

2012-01-01

Background: Deciding whether a skin lesion requires biopsy to exclude skin cancer is often challenging for primary care clinicians in Australia. There are several published algorithms designed to assist with the diagnosis of skin cancer but apart from the clinical ABCD rule, these algorithms only evaluate the dermatoscopic features of a lesion. Objectives: The BLINCK algorithm explores the effect of combining clinical history and examination with fundamental dermatoscopic assessment in primar...

Autumn Algorithm-Computation of Hybridization Networks for Realistic Phylogenetic Trees.

Science.gov (United States)

Huson, Daniel H; Linz, Simone

2018-01-01

A minimum hybridization network is a rooted phylogenetic network that displays two given rooted phylogenetic trees using a minimum number of reticulations. Previous mathematical work on their calculation has usually assumed the input trees to be bifurcating, correctly rooted, or that they both contain the same taxa. These assumptions do not hold in biological studies and "realistic" trees have multifurcations, are difficult to root, and rarely contain the same taxa. We present a new algorithm for computing minimum hybridization networks for a given pair of "realistic" rooted phylogenetic trees. We also describe how the algorithm might be used to improve the rooting of the input trees. We introduce the concept of "autumn trees", a nice framework for the formulation of algorithms based on the mathematics of "maximum acyclic agreement forests". While the main computational problem is hard, the run-time depends mainly on how different the given input trees are. In biological studies, where the trees are reasonably similar, our parallel implementation performs well in practice. The algorithm is available in our open source program Dendroscope 3, providing a platform for biologists to explore rooted phylogenetic networks. We demonstrate the utility of the algorithm using several previously studied data sets.

Plagiarism in scientific publishing.

Science.gov (United States)

Masic, Izet

2012-12-01

Scientific publishing is the ultimate product of scientist work. Number of publications and their quoting are measures of scientist success while unpublished researches are invisible to the scientific community, and as such nonexistent. Researchers in their work rely on their predecessors, while the extent of use of one scientist work, as a source for the work of other authors is the verification of its contributions to the growth of human knowledge. If the author has published an article in a scientific journal it cannot publish the article in any other journal h with a few minor adjustments or without quoting parts of the first article, which are used in another article. Copyright infringement occurs when the author of a new article with or without the mentioning the author used substantial portions of previously published articles, including tables and figures. Scientific institutions and universities should,in accordance with the principles of Good Scientific Practice (GSP) and Good Laboratory Practices (GLP) have a center for monitoring,security, promotion and development of quality research. Establish rules and compliance to rules of good scientific practice are the obligations of each research institutions,universities and every individual-researchers,regardless of which area of science is investigated. In this way, internal quality control ensures that a research institution such as a university, assume responsibility for creating an environment that promotes standards of excellence, intellectual honesty and legality. Although the truth should be the aim of scientific research, it is not guiding fact for all scientists. The best way to reach the truth in its study and to avoid the methodological and ethical mistakes is to consistently apply scientific methods and ethical standards in research. Although variously defined plagiarism is basically intended to deceive the reader's own scientific contribution. There is no general regulation of control of

CiSE: a circular spring embedder layout algorithm.

Science.gov (United States)

Dogrusoz, Ugur; Belviranli, Mehmet E; Dilek, Alptug

2013-06-01

We present a new algorithm for automatic layout of clustered graphs using a circular style. The algorithm tries to determine optimal location and orientation of individual clusters intrinsically within a modified spring embedder. Heuristics such as reversal of the order of nodes in a cluster and swap of neighboring node pairs in the same cluster are employed intermittently to further relax the spring embedder system, resulting in reduced inter-cluster edge crossings. Unlike other algorithms generating circular drawings, our algorithm does not require the quotient graph to be acyclic, nor does it sacrifice the edge crossing number of individual clusters to improve respective positioning of the clusters. Moreover, it reduces the total area required by a cluster by using the space inside the associated circle. Experimental results show that the execution time and quality of the produced drawings with respect to commonly accepted layout criteria are quite satisfactory, surpassing previous algorithms. The algorithm has also been successfully implemented and made publicly available as part of a compound and clustered graph editing and layout tool named CHISIO.

Selective epidemic vaccination under the performant routing algorithms

Science.gov (United States)

Bamaarouf, O.; Alweimine, A. Ould Baba; Rachadi, A.; EZ-Zahraouy, H.

2018-04-01

Despite the extensive research on traffic dynamics and epidemic spreading, the effect of the routing algorithms strategies on the traffic-driven epidemic spreading has not received an adequate attention. It is well known that more performant routing algorithm strategies are used to overcome the congestion problem. However, our main result shows unexpectedly that these algorithms favor the virus spreading more than the case where the shortest path based algorithm is used. In this work, we studied the virus spreading in a complex network using the efficient path and the global dynamic routing algorithms as compared to shortest path strategy. Some previous studies have tried to modify the routing rules to limit the virus spreading, but at the expense of reducing the traffic transport efficiency. This work proposed a solution to overcome this drawback by using a selective vaccination procedure instead of a random vaccination used often in the literature. We found that the selective vaccination succeeded in eradicating the virus better than a pure random intervention for the performant routing algorithm strategies.

Faster Algorithms for Computing Longest Common Increasing Subsequences

DEFF Research Database (Denmark)

Kutz, Martin; Brodal, Gerth Stølting; Kaligosi, Kanela

2011-01-01

of the alphabet, and Sort is the time to sort each input sequence. For k⩾3 length-n sequences we present an algorithm which improves the previous best bound by more than a factor k for many inputs. In both cases, our algorithms are conceptually quite simple but rely on existing sophisticated data structures......We present algorithms for finding a longest common increasing subsequence of two or more input sequences. For two sequences of lengths n and m, where m⩾n, we present an algorithm with an output-dependent expected running time of and O(m) space, where ℓ is the length of an LCIS, σ is the size....... Finally, we introduce the problem of longest common weakly-increasing (or non-decreasing) subsequences (LCWIS), for which we present an -time algorithm for the 3-letter alphabet case. For the extensively studied longest common subsequence problem, comparable speedups have not been achieved for small...

Predictive effects of previous episodes on the risk of recurrence in depressive and bipolar disorders

DEFF Research Database (Denmark)

Kessing, Lars Vedel; Andersen, Per Kragh

2005-01-01

Findings from several studies have suggested that the risk of recurrence increases with the number of previous episodes in depressive and bipolar disorders. However, a comprehensive and critical review of the literature published during the past century shows that in several previous studies...

Mobility-Assisted on-Demand Routing Algorithm for MANETs in the Presence of Location Errors

Directory of Open Access Journals (Sweden)

Trung Kien Vu

2014-01-01

Full Text Available We propose a mobility-assisted on-demand routing algorithm for mobile ad hoc networks in the presence of location errors. Location awareness enables mobile nodes to predict their mobility and enhances routing performance by estimating link duration and selecting reliable routes. However, measured locations intrinsically include errors in measurement. Such errors degrade mobility prediction and have been ignored in previous work. To mitigate the impact of location errors on routing, we propose an on-demand routing algorithm taking into account location errors. To that end, we adopt the Kalman filter to estimate accurate locations and consider route confidence in discovering routes. Via simulations, we compare our algorithm and previous algorithms in various environments. Our proposed mobility prediction is robust to the location errors.

Genetic algorithms coupled with quantum mechanics for refinement of force fields for RNA simulation: a case study of glycosidic torsions in the canonical ribonucleosides.

Science.gov (United States)

Kato, Rodrigo B; Silva, Frederico T; Pappa, Gisele L; Belchior, Jadson C

2015-01-28

We report the use of genetic algorithms (GA) as a method to refine force field parameters in order to determine RNA energy. Quantum-mechanical (QM) calculations are carried out for the isolated canonical ribonucleosides (adenosine, guanosine, cytidine and uridine) that are taken as reference data. In this particular study, the dihedral and electrostatic energies are reparametrized in order to test the proposed approach, i.e., GA coupled with QM calculations. Overall, RMSE comparison with recent published results for ribonucleosides energies shows an improvement, on average, of 50%. Finally, the new reparametrized potential energy function is used to determine the spatial structure of RNA (PDB code ) that was not taken into account in the parametrization process. This structure was improved about 82% comparable with previously published results.

A rank-based algorithm of differential expression analysis for small cell line data with statistical control.

Science.gov (United States)

Li, Xiangyu; Cai, Hao; Wang, Xianlong; Ao, Lu; Guo, You; He, Jun; Gu, Yunyan; Qi, Lishuang; Guan, Qingzhou; Lin, Xu; Guo, Zheng

2017-10-13

To detect differentially expressed genes (DEGs) in small-scale cell line experiments, usually with only two or three technical replicates for each state, the commonly used statistical methods such as significance analysis of microarrays (SAM), limma and RankProd (RP) lack statistical power, while the fold change method lacks any statistical control. In this study, we demonstrated that the within-sample relative expression orderings (REOs) of gene pairs were highly stable among technical replicates of a cell line but often widely disrupted after certain treatments such like gene knockdown, gene transfection and drug treatment. Based on this finding, we customized the RankComp algorithm, previously designed for individualized differential expression analysis through REO comparison, to identify DEGs with certain statistical control for small-scale cell line data. In both simulated and real data, the new algorithm, named CellComp, exhibited high precision with much higher sensitivity than the original RankComp, SAM, limma and RP methods. Therefore, CellComp provides an efficient tool for analyzing small-scale cell line data. © The Author 2017. Published by Oxford University Press.

Zero-block mode decision algorithm for H.264/AVC.

Science.gov (United States)

Lee, Yu-Ming; Lin, Yinyi

2009-03-01

In the previous paper , we proposed a zero-block intermode decision algorithm for H.264 video coding based upon the number of zero-blocks of 4 x 4 DCT coefficients between the current macroblock and the co-located macroblock. The proposed algorithm can achieve significant improvement in computation, but the computation performance is limited for high bit-rate coding. To improve computation efficiency, in this paper, we suggest an enhanced zero-block decision algorithm, which uses an early zero-block detection method to compute the number of zero-blocks instead of direct DCT and quantization (DCT/Q) calculation and incorporates two adequate decision methods into semi-stationary and nonstationary regions of a video sequence. In addition, the zero-block decision algorithm is also applied to the intramode prediction in the P frame. The enhanced zero-block decision algorithm brings out a reduction of average 27% of total encoding time compared to the zero-block decision algorithm.

Optimization and experimental realization of the quantum permutation algorithm

Science.gov (United States)

Yalçınkaya, I.; Gedik, Z.

2017-12-01

The quantum permutation algorithm provides computational speed-up over classical algorithms for determining the parity of a given cyclic permutation. For its n -qubit implementations, the number of required quantum gates scales quadratically with n due to the quantum Fourier transforms included. We show here for the n -qubit case that the algorithm can be simplified so that it requires only O (n ) quantum gates, which theoretically reduces the complexity of the implementation. To test our results experimentally, we utilize IBM's 5-qubit quantum processor to realize the algorithm by using the original and simplified recipes for the 2-qubit case. It turns out that the latter results in a significantly higher success probability which allows us to verify the algorithm more precisely than the previous experimental realizations. We also verify the algorithm for the first time for the 3-qubit case with a considerable success probability by taking the advantage of our simplified scheme.

A new hybrid metaheuristic algorithm for wind farm micrositing

International Nuclear Information System (INIS)

Massan, S.U.R.; Wagan, A.I.; Shaikh, M.M.

2017-01-01

This work focuses on proposing a new algorithm, referred as HMA (Hybrid Metaheuristic Algorithm) for the solution of the WTO (Wind Turbine Optimization) problem. It is well documented that turbines located behind one another face a power loss due to the obstruction of the wind due to wake loss. It is required to reduce this wake loss by the effective placement of turbines using a new HMA. This HMA is derived from the two basic algorithms i.e. DEA (Differential Evolution Algorithm) and the FA (Firefly Algorithm). The function of optimization is undertaken on the N.O. Jensen model. The blending of DEA and FA into HMA are discussed and the new algorithm HMA is implemented maximize power and minimize the cost in a WTO problem. The results by HMA have been compared with GA (Genetic Algorithm) used in some previous studies. The successfully calculated total power produced and cost per unit turbine for a wind farm by using HMA and its comparison with past approaches using single algorithms have shown that there is a significant advantage of using the HMA as compared to the use of single algorithms. The first time implementation of a new algorithm by blending two single algorithms is a significant step towards learning the behavior of algorithms and their added advantages by using them together. (author)

A New Hybrid Metaheuristic Algorithm for Wind Farm Micrositing

Directory of Open Access Journals (Sweden)

SHAFIQ-UR-REHMAN MASSAN

2017-07-01

Full Text Available This work focuses on proposing a new algorithm, referred as HMA (Hybrid Metaheuristic Algorithm for the solution of the WTO (Wind Turbine Optimization problem. It is well documented that turbines located behind one another face a power loss due to the obstruction of the wind due to wake loss. It is required to reduce this wake loss by the effective placement of turbines using a new HMA. This HMA is derived from the two basic algorithms i.e. DEA (Differential Evolution Algorithm and the FA (Firefly Algorithm. The function of optimization is undertaken on the N.O. Jensen model. The blending of DEA and FA into HMA are discussed and the new algorithm HMA is implemented maximize power and minimize the cost in a WTO problem. The results by HMA have been compared with GA (Genetic Algorithm used in some previous studies. The successfully calculated total power produced and cost per unit turbine for a wind farm by using HMA and its comparison with past approaches using single algorithms have shown that there is a significant advantage of using the HMA as compared to the use of single algorithms. The first time implementation of a new algorithm by blending two single algorithms is a significant step towards learning the behavior of algorithms and their added advantages by using them together.

Designing synthetic networks in silico: a generalised evolutionary algorithm approach.

Science.gov (United States)

Smith, Robert W; van Sluijs, Bob; Fleck, Christian

2017-12-02

Evolution has led to the development of biological networks that are shaped by environmental signals. Elucidating, understanding and then reconstructing important network motifs is one of the principal aims of Systems & Synthetic Biology. Consequently, previous research has focused on finding optimal network structures and reaction rates that respond to pulses or produce stable oscillations. In this work we present a generalised in silico evolutionary algorithm that simultaneously finds network structures and reaction rates (genotypes) that can satisfy multiple defined objectives (phenotypes). The key step to our approach is to translate a schema/binary-based description of biological networks into systems of ordinary differential equations (ODEs). The ODEs can then be solved numerically to provide dynamic information about an evolved networks functionality. Initially we benchmark algorithm performance by finding optimal networks that can recapitulate concentration time-series data and perform parameter optimisation on oscillatory dynamics of the Repressilator. We go on to show the utility of our algorithm by finding new designs for robust synthetic oscillators, and by performing multi-objective optimisation to find a set of oscillators and feed-forward loops that are optimal at balancing different system properties. In sum, our results not only confirm and build on previous observations but we also provide new designs of synthetic oscillators for experimental construction. In this work we have presented and tested an evolutionary algorithm that can design a biological network to produce desired output. Given that previous designs of synthetic networks have been limited to subregions of network- and parameter-space, the use of our evolutionary optimisation algorithm will enable Synthetic Biologists to construct new systems with the potential to display a wider range of complex responses.

DNA Microarray Data Analysis: A Novel Biclustering Algorithm Approach

Directory of Open Access Journals (Sweden)

Tewfik Ahmed H

2006-01-01

Full Text Available Biclustering algorithms refer to a distinct class of clustering algorithms that perform simultaneous row-column clustering. Biclustering problems arise in DNA microarray data analysis, collaborative filtering, market research, information retrieval, text mining, electoral trends, exchange analysis, and so forth. When dealing with DNA microarray experimental data for example, the goal of biclustering algorithms is to find submatrices, that is, subgroups of genes and subgroups of conditions, where the genes exhibit highly correlated activities for every condition. In this study, we develop novel biclustering algorithms using basic linear algebra and arithmetic tools. The proposed biclustering algorithms can be used to search for all biclusters with constant values, biclusters with constant values on rows, biclusters with constant values on columns, and biclusters with coherent values from a set of data in a timely manner and without solving any optimization problem. We also show how one of the proposed biclustering algorithms can be adapted to identify biclusters with coherent evolution. The algorithms developed in this study discover all valid biclusters of each type, while almost all previous biclustering approaches will miss some.

A flexible fuzzy regression algorithm for forecasting oil consumption estimation

International Nuclear Information System (INIS)

Azadeh, A.; Khakestani, M.; Saberi, M.

2009-01-01

Oil consumption plays a vital role in socio-economic development of most countries. This study presents a flexible fuzzy regression algorithm for forecasting oil consumption based on standard economic indicators. The standard indicators are annual population, cost of crude oil import, gross domestic production (GDP) and annual oil production in the last period. The proposed algorithm uses analysis of variance (ANOVA) to select either fuzzy regression or conventional regression for future demand estimation. The significance of the proposed algorithm is three fold. First, it is flexible and identifies the best model based on the results of ANOVA and minimum absolute percentage error (MAPE), whereas previous studies consider the best fitted fuzzy regression model based on MAPE or other relative error results. Second, the proposed model may identify conventional regression as the best model for future oil consumption forecasting because of its dynamic structure, whereas previous studies assume that fuzzy regression always provide the best solutions and estimation. Third, it utilizes the most standard independent variables for the regression models. To show the applicability and superiority of the proposed flexible fuzzy regression algorithm the data for oil consumption in Canada, United States, Japan and Australia from 1990 to 2005 are used. The results show that the flexible algorithm provides accurate solution for oil consumption estimation problem. The algorithm may be used by policy makers to accurately foresee the behavior of oil consumption in various regions.

SafePub: A Truthful Data Anonymization Algorithm With Strong Privacy Guarantees

Directory of Open Access Journals (Sweden)

Bild Raffael

2018-01-01

Full Text Available Methods for privacy-preserving data publishing and analysis trade off privacy risks for individuals against the quality of output data. In this article, we present a data publishing algorithm that satisfies the differential privacy model. The transformations performed are truthful, which means that the algorithm does not perturb input data or generate synthetic output data. Instead, records are randomly drawn from the input dataset and the uniqueness of their features is reduced. This also offers an intuitive notion of privacy protection. Moreover, the approach is generic, as it can be parameterized with different objective functions to optimize its output towards different applications. We show this by integrating six well-known data quality models. We present an extensive analytical and experimental evaluation and a comparison with prior work. The results show that our algorithm is the first practical implementation of the described approach and that it can be used with reasonable privacy parameters resulting in high degrees of protection. Moreover, when parameterizing the generic method with an objective function quantifying the suitability of data for building statistical classifiers, we measured prediction accuracies that compare very well with results obtained using state-of-the-art differentially private classification algorithms.

A Modularity Degree Based Heuristic Community Detection Algorithm

Directory of Open Access Journals (Sweden)

Dongming Chen

2014-01-01

Full Text Available A community in a complex network can be seen as a subgroup of nodes that are densely connected. Discovery of community structures is a basic problem of research and can be used in various areas, such as biology, computer science, and sociology. Existing community detection methods usually try to expand or collapse the nodes partitions in order to optimize a given quality function. These optimization function based methods share the same drawback of inefficiency. Here we propose a heuristic algorithm (MDBH algorithm based on network structure which employs modularity degree as a measure function. Experiments on both synthetic benchmarks and real-world networks show that our algorithm gives competitive accuracy with previous modularity optimization methods, even though it has less computational complexity. Furthermore, due to the use of modularity degree, our algorithm naturally improves the resolution limit in community detection.

Publisher Correction: Measuring progress from nationally determined contributions to mid-century strategies

Science.gov (United States)

Iyer, Gokul; Ledna, Catherine; Clarke, Leon; Edmonds, James; McJeon, Haewon; Kyle, Page; Williams, James H.

2018-03-01

In the version of this Article previously published, technical problems led to the wrong summary appearing on the homepage, and an incorrect Supplementary Information file being uploaded. Both errors have now been corrected.

ERGC: an efficient referential genome compression algorithm.

Science.gov (United States)

Saha, Subrata; Rajasekaran, Sanguthevar

2015-11-01

Genome sequencing has become faster and more affordable. Consequently, the number of available complete genomic sequences is increasing rapidly. As a result, the cost to store, process, analyze and transmit the data is becoming a bottleneck for research and future medical applications. So, the need for devising efficient data compression and data reduction techniques for biological sequencing data is growing by the day. Although there exists a number of standard data compression algorithms, they are not efficient in compressing biological data. These generic algorithms do not exploit some inherent properties of the sequencing data while compressing. To exploit statistical and information-theoretic properties of genomic sequences, we need specialized compression algorithms. Five different next-generation sequencing data compression problems have been identified and studied in the literature. We propose a novel algorithm for one of these problems known as reference-based genome compression. We have done extensive experiments using five real sequencing datasets. The results on real genomes show that our proposed algorithm is indeed competitive and performs better than the best known algorithms for this problem. It achieves compression ratios that are better than those of the currently best performing algorithms. The time to compress and decompress the whole genome is also very promising. The implementations are freely available for non-commercial purposes. They can be downloaded from http://engr.uconn.edu/∼rajasek/ERGC.zip. rajasek@engr.uconn.edu. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

A Study on the Communication Mechanism for Publishing and Producing News on Mobile Devices

Directory of Open Access Journals (Sweden)

Ruhan Zhao

2016-07-01

Full Text Available This study explores the communication mechanism for publishing and producing news through analyzing mediums such as Microblog, WeChat and, in particular, the mobile app, TouTiao. The results of this study show that the status and practice of professional journalism and gatekeepers are being phased out of news production. Adversely, algorithms and technology are taking their place at the center of the circle of news production.

Algebraic dynamics algorithm: Numerical comparison with Runge-Kutta algorithm and symplectic geometric algorithm

Institute of Scientific and Technical Information of China (English)

WANG ShunJin; ZHANG Hua

2007-01-01

Based on the exact analytical solution of ordinary differential equations,a truncation of the Taylor series of the exact solution to the Nth order leads to the Nth order algebraic dynamics algorithm.A detailed numerical comparison is presented with Runge-Kutta algorithm and symplectic geometric algorithm for 12 test models.The results show that the algebraic dynamics algorithm can better preserve both geometrical and dynamical fidelity of a dynamical system at a controllable precision,and it can solve the problem of algorithm-induced dissipation for the Runge-Kutta algorithm and the problem of algorithm-induced phase shift for the symplectic geometric algorithm.

Algebraic dynamics algorithm:Numerical comparison with Runge-Kutta algorithm and symplectic geometric algorithm

Institute of Scientific and Technical Information of China (English)

2007-01-01

Based on the exact analytical solution of ordinary differential equations, a truncation of the Taylor series of the exact solution to the Nth order leads to the Nth order algebraic dynamics algorithm. A detailed numerical comparison is presented with Runge-Kutta algorithm and symplectic geometric algorithm for 12 test models. The results show that the algebraic dynamics algorithm can better preserve both geometrical and dynamical fidelity of a dynamical system at a controllable precision, and it can solve the problem of algorithm-induced dissipation for the Runge-Kutta algorithm and the problem of algorithm-induced phase shift for the symplectic geometric algorithm.

Algorithm comparison for schedule optimization in MR fingerprinting.

Science.gov (United States)

Cohen, Ouri; Rosen, Matthew S

2017-09-01

In MR Fingerprinting, the flip angles and repetition times are chosen according to a pseudorandom schedule. In previous work, we have shown that maximizing the discrimination between different tissue types by optimizing the acquisition schedule allows reductions in the number of measurements required. The ideal optimization algorithm for this application remains unknown, however. In this work we examine several different optimization algorithms to determine the one best suited for optimizing MR Fingerprinting acquisition schedules. Copyright © 2017 Elsevier Inc. All rights reserved.

Implementation of Real-Time Feedback Flow Control Algorithms on a Canonical Testbed

Science.gov (United States)

Tian, Ye; Song, Qi; Cattafesta, Louis

2005-01-01

This report summarizes the activities on "Implementation of Real-Time Feedback Flow Control Algorithms on a Canonical Testbed." The work summarized consists primarily of two parts. The first part summarizes our previous work and the extensions to adaptive ID and control algorithms. The second part concentrates on the validation of adaptive algorithms by applying them to a vibration beam test bed. Extensions to flow control problems are discussed.

Algorithmic correspondence and completeness in modal logic. V. Recursive extensions of SQEMA

DEFF Research Database (Denmark)

Conradie, Willem; Goranko, Valentin; Vakarelov, Dimiter

2010-01-01

The previously introduced algorithm SQEMA computes first-order frame equivalents for modal formulae and also proves their canonicity. Here we extend SQEMA with an additional rule based on a recursive version of Ackermann's lemma, which enables the algorithm to compute local frame equivalents...... on the class of ‘recursive formulae’. We also show that a certain version of this algorithm guarantees the canonicity of the formulae on which it succeeds....

False gold: Safely navigating open access publishing to avoid predatory publishers and journals.

Science.gov (United States)

McCann, Terence V; Polacsek, Meg

2018-04-01

The aim of this study was to review and discuss predatory open access publishing in the context of nursing and midwifery and develop a set of guidelines that serve as a framework to help clinicians, educators and researchers avoid predatory publishers. Open access publishing is increasingly common across all academic disciplines. However, this publishing model is vulnerable to exploitation by predatory publishers, posing a threat to nursing and midwifery scholarship and practice. Guidelines are needed to help researchers recognize predatory journals and publishers and understand the negative consequences of publishing in them. Discussion paper. A literature search of BioMed Central, CINAHL, MEDLINE with Full Text and PubMed for terms related to predatory publishing, published in the period 2007-2017. Lack of awareness of the risks and pressure to publish in international journals, may result in nursing and midwifery researchers publishing their work in dubious open access journals. Caution should be taken prior to writing and submitting a paper, to avoid predatory publishers. The advantage of open access publishing is that it provides readers with access to peer-reviewed research as soon as it is published online. However, predatory publishers use deceptive methods to exploit open access publishing for their own profit. Clear guidelines are needed to help researchers navigate safely open access publishing. A deeper understanding of the risks of predatory publishing is needed. Clear guidelines should be followed by nursing and midwifery researchers seeking to publish their work in open access journals. © 2017 John Wiley & Sons Ltd.

Swarm, genetic and evolutionary programming algorithms applied to multiuser detection

Directory of Open Access Journals (Sweden)

Paul Jean Etienne Jeszensky

2005-02-01

Full Text Available In this paper, the particles swarm optimization technique, recently published in the literature, and applied to Direct Sequence/Code Division Multiple Access systems (DS/CDMA with multiuser detection (MuD is analyzed, evaluated and compared. The Swarm algorithm efficiency when applied to the DS-CDMA multiuser detection (Swarm-MuD is compared through the tradeoff performance versus computational complexity, being the complexity expressed in terms of the number of necessary operations in order to reach the performance obtained through the optimum detector or the Maximum Likelihood detector (ML. The comparison is accomplished among the genetic algorithm, evolutionary programming with cloning and Swarm algorithm under the same simulation basis. Additionally, it is proposed an heuristics-MuD complexity analysis through the number of computational operations. Finally, an analysis is carried out for the input parameters of the Swarm algorithm in the attempt to find the optimum parameters (or almost-optimum for the algorithm applied to the MuD problem.

Connectivity algorithm with depth first search (DFS) on simple graphs

Science.gov (United States)

Riansanti, O.; Ihsan, M.; Suhaimi, D.

2018-01-01

This paper discusses an algorithm to detect connectivity of a simple graph using Depth First Search (DFS). The DFS implementation in this paper differs than other research, that is, on counting the number of visited vertices. The algorithm obtains s from the number of vertices and visits source vertex, following by its adjacent vertices until the last vertex adjacent to the previous source vertex. Any simple graph is connected if s equals 0 and disconnected if s is greater than 0. The complexity of the algorithm is O(n2).

NASAwide electronic publishing system: Electronic printing and duplicating, stage-2 evaluation report (GSFC)

Science.gov (United States)

Tuey, Richard C.; Lane, Robert; Hart, Susan V.

1995-01-01

The NASA Scientific and Technical Information Office was assigned the responsibility to continue with the expansion of the NASAwide networked electronic duplicating effort by including the Goddard Space Flight Center (GSFC) as an additional node to the existing configuration of networked electronic duplicating systems within NASA. The subject of this report is the evaluation of a networked electronic duplicating system which meets the duplicating requirements and expands electronic publishing capabilities without increasing current operating costs. This report continues the evaluation reported in 'NASA Electronic Publishing System - Electronic Printing and Duplicating Evaluation Report' (NASA TM-106242) and 'NASA Electronic Publishing System - Stage 1 Evaluation Report' (NASA TM-106510). This report differs from the previous reports through the inclusion of an external networked desktop editing, archival, and publishing functionality which did not exist with the previous networked electronic duplicating system. Additionally, a two-phase approach to the evaluation was undertaken; the first was a paper study justifying a 90-day, on-site evaluation, and the second phase was to validate, during the 90-day evaluation, the cost benefits and productivity increases that could be achieved in an operational mode. A benchmark of the functionality of the networked electronic publishing system and external networked desktop editing, archival, and publishing system was performed under a simulated daily production environment. This report can be used to guide others in determining the most cost effective duplicating/publishing alternative through the use of cost/benefit analysis and return on investment techniques. A treatise on the use of these techniques can be found by referring to 'NASA Electronic Publishing System -Cost/Benefit Methodology' (NASA TM-106662).

Genetic algorithm optimization of atomic clusters

International Nuclear Information System (INIS)

Morris, J.R.; Deaven, D.M.; Ho, K.M.; Wang, C.Z.; Pan, B.C.; Wacker, J.G.; Turner, D.E.; Iowa State Univ., Ames, IA

1996-01-01

The authors have been using genetic algorithms to study the structures of atomic clusters and related problems. This is a problem where local minima are easy to locate, but barriers between the many minima are large, and the number of minima prohibit a systematic search. They use a novel mating algorithm that preserves some of the geometrical relationship between atoms, in order to ensure that the resultant structures are likely to inherit the best features of the parent clusters. Using this approach, they have been able to find lower energy structures than had been previously obtained. Most recently, they have been able to turn around the building block idea, using optimized structures from the GA to learn about systematic structural trends. They believe that an effective GA can help provide such heuristic information, and (conversely) that such information can be introduced back into the algorithm to assist in the search process

The Algorithm for Algorithms: An Evolutionary Algorithm Based on Automatic Designing of Genetic Operators

Directory of Open Access Journals (Sweden)

Dazhi Jiang

2015-01-01

Full Text Available At present there is a wide range of evolutionary algorithms available to researchers and practitioners. Despite the great diversity of these algorithms, virtually all of the algorithms share one feature: they have been manually designed. A fundamental question is “are there any algorithms that can design evolutionary algorithms automatically?” A more complete definition of the question is “can computer construct an algorithm which will generate algorithms according to the requirement of a problem?” In this paper, a novel evolutionary algorithm based on automatic designing of genetic operators is presented to address these questions. The resulting algorithm not only explores solutions in the problem space like most traditional evolutionary algorithms do, but also automatically generates genetic operators in the operator space. In order to verify the performance of the proposed algorithm, comprehensive experiments on 23 well-known benchmark optimization problems are conducted. The results show that the proposed algorithm can outperform standard differential evolution algorithm in terms of convergence speed and solution accuracy which shows that the algorithm designed automatically by computers can compete with the algorithms designed by human beings.

Algorithm and Hardware Design of a Fast Intra Frame Mode Decision Module for H.264/AVC Encoders

Directory of Open Access Journals (Sweden)

Daniel Palomino

2012-01-01

Full Text Available In the rate-distortion optimization (RDO, the process of choosing the best prediction mode is performed through exhaustive executions of the whole encoding process, increasing significantly the encoder computational complexity. Considering H.264/AVC intra frame prediction, there are several modes to encode a macroblock (MB. This work proposes an algorithm and the hardware design for a fast intra frame mode decision module for H.264/AVC encoders. The application of the proposed algorithm reduces in more than 10 times the number of encoding iterations for choosing the best intramode when compared with RDO-based decision. The architecture was synthesized to FPGA and achieved an operation frequency of 98 MHz processing more than 300 HD1080p frames per second. With this approach, we achieved one order-of-magnitude performance improvement compared with RDO-based approaches, which is very important not only from the performance but also from the energy consumption perspective for battery-operated devices. In order to compare the architecture with previously published works, we also synthesized it to standard cells. Compared with the best previous results reported, the implemented architecture achieves a complexity reduction of five times, a processing capability increase of 14 times, and a reduction in the number of clock cycles per MB of 11 times.

Simulating prescribed particle densities in the grand canonical ensemble using iterative algorithms.

Science.gov (United States)

Malasics, Attila; Gillespie, Dirk; Boda, Dezso

2008-03-28

We present two efficient iterative Monte Carlo algorithms in the grand canonical ensemble with which the chemical potentials corresponding to prescribed (targeted) partial densities can be determined. The first algorithm works by always using the targeted densities in the kT log(rho(i)) (ideal gas) terms and updating the excess chemical potentials from the previous iteration. The second algorithm extrapolates the chemical potentials in the next iteration from the results of the previous iteration using a first order series expansion of the densities. The coefficients of the series, the derivatives of the densities with respect to the chemical potentials, are obtained from the simulations by fluctuation formulas. The convergence of this procedure is shown for the examples of a homogeneous Lennard-Jones mixture and a NaCl-CaCl(2) electrolyte mixture in the primitive model. The methods are quite robust under the conditions investigated. The first algorithm is less sensitive to initial conditions.

Combined Dust Detection Algorithm by Using MODIS Infrared Channels over East Asia

Science.gov (United States)

Park, Sang Seo; Kim, Jhoon; Lee, Jaehwa; Lee, Sukjo; Kim, Jeong Soo; Chang, Lim Seok; Ou, Steve

2014-01-01

A new dust detection algorithm is developed by combining the results of multiple dust detectionmethods using IR channels onboard the MODerate resolution Imaging Spectroradiometer (MODIS). Brightness Temperature Difference (BTD) between two wavelength channels has been used widely in previous dust detection methods. However, BTDmethods have limitations in identifying the offset values of the BTDto discriminate clear-sky areas. The current algorithm overcomes the disadvantages of previous dust detection methods by considering the Brightness Temperature Ratio (BTR) values of the dual wavelength channels with 30-day composite, the optical properties of the dust particles, the variability of surface properties, and the cloud contamination. Therefore, the current algorithm shows improvements in detecting the dust loaded region over land during daytime. Finally, the confidence index of the current dust algorithm is shown in 10 × 10 pixels of the MODIS observations. From January to June, 2006, the results of the current algorithm are within 64 to 81% of those found using the fine mode fraction (FMF) and aerosol index (AI) from the MODIS and Ozone Monitoring Instrument (OMI). The agreement between the results of the current algorithm and the OMI AI over the non-polluted land also ranges from 60 to 67% to avoid errors due to the anthropogenic aerosol. In addition, the developed algorithm shows statistically significant results at four AErosol RObotic NETwork (AERONET) sites in East Asia.

3rd International Conference on Harmony Search Algorithm

CERN Document Server

2017-01-01

This book presents state-of-the-art technical contributions based around one of the most successful evolutionary optimization algorithms published to date: Harmony Search. Contributions span from novel technical derivations of this algorithm to applications in the broad fields of civil engineering, energy, transportation & mobility and health, among many others and focus not only on its cross-domain applicability, but also on its core evolutionary operators, including elements inspired from other meta-heuristics. The global scientific community is witnessing an upsurge in groundbreaking, new advances in all areas of computational intelligence, with a particular flurry of research focusing on evolutionary computation and bio-inspired optimization. Observed processes in nature and sociology have provided the basis for innovative algorithmic developments aimed at leveraging the inherent capability to adapt characterized by various animals, including ants, fireflies, wolves and humans. However, it is the beha...

Developments in Publishing: The Potential of Digital Publishing

OpenAIRE

X. Tian

2007-01-01

This research aims to identify issues associated with the impact of digital technology on the publishing industry with a specific focus on aspects of the sustainability of existing business models in Australia. Based on the case studies, interviews and Australian-wide online surveys, the research presents a review of the traditional business models in book publishing for investigating their effectiveness in a digital environment. It speculates on how and what should be considered for construc...

Theoretical and numerical study of an optimum design algorithm

International Nuclear Information System (INIS)

Destuynder, Philippe.

1976-08-01

This work can be separated into two main parts. First, the behavior of the solution of an elliptic variational equation is analyzed when the domain is submitted to a small perturbation. The case of inequations is also considered. Secondly the previous results are used for deriving an optimum design algorithm. This algorithm was suggested by the center-method proposed by Huard. Numerical results show the superiority of the method on other different optimization techniques [fr

Real-time recursive hyperspectral sample and band processing algorithm architecture and implementation

CERN Document Server

Chang, Chein-I

2017-01-01

This book explores recursive architectures in designing progressive hyperspectral imaging algorithms. In particular, it makes progressive imaging algorithms recursive by introducing the concept of Kalman filtering in algorithm design so that hyperspectral imagery can be processed not only progressively sample by sample or band by band but also recursively via recursive equations. This book can be considered a companion book of author’s books, Real-Time Progressive Hyperspectral Image Processing, published by Springer in 2016. Explores recursive structures in algorithm architecture Implements algorithmic recursive architecture in conjunction with progressive sample and band processing Derives Recursive Hyperspectral Sample Processing (RHSP) techniques according to Band-Interleaved Sample/Pixel (BIS/BIP) acquisition format Develops Recursive Hyperspectral Band Processing (RHBP) techniques according to Band SeQuential (BSQ) acquisition format for hyperspectral data.

PLAGIARISM IN SCIENTIFIC PUBLISHING

Science.gov (United States)

Masic, Izet

2012-01-01

Scientific publishing is the ultimate product of scientist work. Number of publications and their quoting are measures of scientist success while unpublished researches are invisible to the scientific community, and as such nonexistent. Researchers in their work rely on their predecessors, while the extent of use of one scientist work, as a source for the work of other authors is the verification of its contributions to the growth of human knowledge. If the author has published an article in a scientific journal it cannot publish the article in any other journal h with a few minor adjustments or without quoting parts of the first article, which are used in another article. Copyright infringement occurs when the author of a new article with or without the mentioning the author used substantial portions of previously published articles, including tables and figures. Scientific institutions and universities should,in accordance with the principles of Good Scientific Practice (GSP) and Good Laboratory Practices (GLP) have a center for monitoring,security, promotion and development of quality research. Establish rules and compliance to rules of good scientific practice are the obligations of each research institutions,universities and every individual-researchers,regardless of which area of science is investigated. In this way, internal quality control ensures that a research institution such as a university, assume responsibility for creating an environment that promotes standards of excellence, intellectual honesty and legality. Although the truth should be the aim of scientific research, it is not guiding fact for all scientists. The best way to reach the truth in its study and to avoid the methodological and ethical mistakes is to consistently apply scientific methods and ethical standards in research. Although variously defined plagiarism is basically intended to deceive the reader’s own scientific contribution. There is no general regulation of control of

Novel prediction- and subblock-based algorithm for fractal image compression

International Nuclear Information System (INIS)

Chung, K.-L.; Hsu, C.-H.

2006-01-01

Fractal encoding is the most consuming part in fractal image compression. In this paper, a novel two-phase prediction- and subblock-based fractal encoding algorithm is presented. Initially the original gray image is partitioned into a set of variable-size blocks according to the S-tree- and interpolation-based decomposition principle. In the first phase, each current block of variable-size range block tries to find the best matched domain block based on the proposed prediction-based search strategy which utilizes the relevant neighboring variable-size domain blocks. The first phase leads to a significant computation-saving effect. If the domain block found within the predicted search space is unacceptable, in the second phase, a subblock strategy is employed to partition the current variable-size range block into smaller blocks to improve the image quality. Experimental results show that our proposed prediction- and subblock-based fractal encoding algorithm outperforms the conventional full search algorithm and the recently published spatial-correlation-based algorithm by Truong et al. in terms of encoding time and image quality. In addition, the performance comparison among our proposed algorithm and the other two algorithms, the no search-based algorithm and the quadtree-based algorithm, are also investigated

Feasibility study of the iterative x-ray phase retrieval algorithm

International Nuclear Information System (INIS)

Meng Fanbo; Liu Hong; Wu Xizeng

2009-01-01

An iterative phase retrieval algorithm was previously investigated for in-line x-ray phase imaging. Through detailed theoretical analysis and computer simulations, we now discuss the limitations, robustness, and efficiency of the algorithm. The iterative algorithm was proved robust against imaging noise but sensitive to the variations of several system parameters. It is also efficient in terms of calculation time. It was shown that the algorithm can be applied to phase retrieval based on one phase-contrast image and one attenuation image, or two phase-contrast images; in both cases, the two images can be obtained either by one detector in two exposures, or by two detectors in only one exposure as in the dual-detector scheme

Probabilistic analysis algorithm for UA slope software program.

Science.gov (United States)

2013-12-01

A reliability-based computational algorithm for using a single row and equally spaced drilled shafts to : stabilize an unstable slope has been developed in this research. The Monte-Carlo simulation (MCS) : technique was used in the previously develop...

FPSoC-Based Architecture for a Fast Motion Estimation Algorithm in H.264/AVC

Directory of Open Access Journals (Sweden)

Obianuju Ndili

2009-01-01

Full Text Available There is an increasing need for high quality video on low power, portable devices. Possible target applications range from entertainment and personal communications to security and health care. While H.264/AVC answers the need for high quality video at lower bit rates, it is significantly more complex than previous coding standards and thus results in greater power consumption in practical implementations. In particular, motion estimation (ME, in H.264/AVC consumes the largest power in an H.264/AVC encoder. It is therefore critical to speed-up integer ME in H.264/AVC via fast motion estimation (FME algorithms and hardware acceleration. In this paper, we present our hardware oriented modifications to a hybrid FME algorithm, our architecture based on the modified algorithm, and our implementation and prototype on a PowerPC-based Field Programmable System on Chip (FPSoC. Our results show that the modified hybrid FME algorithm on average, outperforms previous state-of-the-art FME algorithms, while its losses when compared with FSME, in terms of PSNR performance and computation time, are insignificant. We show that although our implementation platform is FPGA-based, our implementation results compare favourably with previous architectures implemented on ASICs. Finally we also show an improvement over some existing architectures implemented on FPGAs.

A Study on New Pochonka Published in A.D. 1792

Science.gov (United States)

Ahn, Sang-Hyeon

2009-12-01

New Pochonka published in the eighteenth century of the Choson dynasty was composed of star-charts based on the new observations made by Jesuits in China and songs corrected a little bit from previous version of Pochonka. The asterisms in the previous Pochonka are listed in the same order to that in the Song dynasty's literature; while the asterisms in the new Pochonka are listed in accordance with Pu-tien-ko published in China after the Ming dynasty. The Chinese-style twelve-equatorial-section system is adopted in the new Pochonka, while in its song is adopted the zodiac system, which can be seen in the star-charts of previous version of Pochonka. The asterisms belonging to three or four neighboring lunar-mansions are drawn in one chart. Each chart covers asterisms not belonging to a certain range of right ascension, but to a certain lunar mansion. We estimate the forming era of the new Pochonka from the following facts; that the Ling-Tai-I-Hsiang-Chih was used to make charts and footnotes whose archetype can be found in the Chinese literature around A.D. 1700, that these Chinese books were imported into Choson in A.D. 1709, that the naming taboo to the emperor Khang-Hsi was used, that the order of Shen-Hsiu (參宿) was transposed with Tshui-Hsiu (자宿), and that the new Pochonka was substituted for the old version when the rules of Royal Astronomical Bureau was reformed in A.D. 1791. In conclusion, the parent sources of the charts and footnotes of the new Pochonka might be imported from the Ching dynasty around 1709 A.D. to form the new Pochonka between A.D. 1709 and A.D. 1791, and finally to be published in A.D. 1792. We discuss the possible future works to make a firm conclusion.

Parallel algorithms for continuum dynamics

International Nuclear Information System (INIS)

Hicks, D.L.; Liebrock, L.M.

1987-01-01

Simply porting existing parallel programs to a new parallel processor may not achieve the full speedup possible; to achieve the maximum efficiency may require redesigning the parallel algorithms for the specific architecture. The authors discuss here parallel algorithms that were developed first for the HEP processor and then ported to the CRAY X-MP/4, the ELXSI/10, and the Intel iPSC/32. Focus is mainly on the most recent parallel processing results produced, i.e., those on the Intel Hypercube. The applications are simulations of continuum dynamics in which the momentum and stress gradients are important. Examples of these are inertial confinement fusion experiments, severe breaks in the coolant system of a reactor, weapons physics, shock-wave physics. Speedup efficiencies on the Intel iPSC Hypercube are very sensitive to the ratio of communication to computation. Great care must be taken in designing algorithms for this machine to avoid global communication. This is much more critical on the iPSC than it was on the three previous parallel processors

PeptX: Using Genetic Algorithms to optimize peptides for MHC binding

Directory of Open Access Journals (Sweden)

Ribarics Reiner

2011-06-01

Full Text Available Abstract Background The binding between the major histocompatibility complex and the presented peptide is an indispensable prerequisite for the adaptive immune response. There is a plethora of different in silico techniques for the prediction of the peptide binding affinity to major histocompatibility complexes. Most studies screen a set of peptides for promising candidates to predict possible T cell epitopes. In this study we ask the question vice versa: Which peptides do have highest binding affinities to a given major histocompatibility complex according to certain in silico scoring functions? Results Since a full screening of all possible peptides is not feasible in reasonable runtime, we introduce a heuristic approach. We developed a framework for Genetic Algorithms to optimize peptides for the binding to major histocompatibility complexes. In an extensive benchmark we tested various operator combinations. We found that (1 selection operators have a strong influence on the convergence of the population while recombination operators have minor influence and (2 that five different binding prediction methods lead to five different sets of "optimal" peptides for the same major histocompatibility complex. The consensus peptides were experimentally verified as high affinity binders. Conclusion We provide a generalized framework to calculate sets of high affinity binders based on different previously published scoring functions in reasonable runtime. Furthermore we give insight into the different behaviours of operators and scoring functions of the Genetic Algorithm.

Reactor controller design using genetic algorithm with simulated annealing

International Nuclear Information System (INIS)

Willjuice Iruthyarajan, M.

2012-01-01

Many reactor control design work, specifically the problem of synthesis and optimization of reactor networks involving the classical reaction schemes was studied, considering a superstructure formed by a CSTR and a PFR and their possible arrangements. A genetic algorithm was proposed, together with a systematic procedure. Two case studies were solved with the proposed systematic. Both of them present similar results than the published in the literature. The first case studied was the Trambouze reaction scheme. Although selectivity values are smaller then the values published in the referred papers, the reactors system combined volume is always minor them the other ones. The second case studied was the Van de Vusse reaction scheme. In this case, the obtained value for the total volume is always minor then the considered papers. One can conclude that when compared with the other works presented in the literature results are compatible and very interesting. The developed algorithms can be used as a good alternative for reactor networks design and optimization problem

A distributed scheduling algorithm for heterogeneous real-time systems

Science.gov (United States)

Zeineldine, Osman; El-Toweissy, Mohamed; Mukkamala, Ravi

1991-01-01

Much of the previous work on load balancing and scheduling in distributed environments was concerned with homogeneous systems and homogeneous loads. Several of the results indicated that random policies are as effective as other more complex load allocation policies. The effects of heterogeneity on scheduling algorithms for hard real time systems is examined. A distributed scheduler specifically to handle heterogeneities in both nodes and node traffic is proposed. The performance of the algorithm is measured in terms of the percentage of jobs discarded. While a random task allocation is very sensitive to heterogeneities, the algorithm is shown to be robust to such non-uniformities in system components and load.

Development and Evaluation of Algorithms for Breath Alcohol Screening.

Science.gov (United States)

Ljungblad, Jonas; Hök, Bertil; Ekström, Mikael

2016-04-01

Breath alcohol screening is important for traffic safety, access control and other areas of health promotion. A family of sensor devices useful for these purposes is being developed and evaluated. This paper is focusing on algorithms for the determination of breath alcohol concentration in diluted breath samples using carbon dioxide to compensate for the dilution. The examined algorithms make use of signal averaging, weighting and personalization to reduce estimation errors. Evaluation has been performed by using data from a previously conducted human study. It is concluded that these features in combination will significantly reduce the random error compared to the signal averaging algorithm taken alone.

Open-Access Publishing

Directory of Open Access Journals (Sweden)

Nedjeljko Frančula

2013-06-01

Full Text Available Nature, one of the most prominent scientific journals dedicated one of its issues to recent changes in scientific publishing (Vol. 495, Issue 7442, 27 March 2013. Its editors stressed that words technology and revolution are closely related when it comes to scientific publishing. In addition, the transformation of research publishing is not as much a revolution than an attrition war in which all sides are buried. The most important change they refer to is the open-access model in which an author or an institution pays in advance for publishing a paper in a journal, and the paper is then available to users on the Internet free of charge.According to preliminary results of a survey conducted among 23 000 scientists by the publisher of Nature, 45% of them believes all papers should be published in open access, but at the same time 22% of them would not allow the use of papers for commercial purposes. Attitudes toward open access vary according to scientific disciplines, leading the editors to conclude the revolution still does not suit everyone.

Is It that Difficult to Find a Good Preference Order for the Incremental Algorithm?

Science.gov (United States)

Krahmer, Emiel; Koolen, Ruud; Theune, Mariet

2012-01-01

In a recent article published in this journal (van Deemter, Gatt, van der Sluis, & Power, 2012), the authors criticize the Incremental Algorithm (a well-known algorithm for the generation of referring expressions due to Dale & Reiter, 1995, also in this journal) because of its strong reliance on a pre-determined, domain-dependent Preference Order.…

A Cultural Algorithm for Optimal Design of Truss Structures

Directory of Open Access Journals (Sweden)

Shahin Jalili

Full Text Available Abstract A cultural algorithm was utilized in this study to solve optimal design of truss structures problem achieving minimum weight objective under stress and deflection constraints. The algorithm is inspired by principles of human social evolution. It simulates the social interaction between the peoples and their beliefs in a belief space. Cultural Algorithm (CA utilizes the belief space and population space which affects each other based on acceptance and influence functions. The belief space of CA consists of different knowledge components. In this paper, only situational and normative knowledge components are used within the belief space. The performance of the method is demonstrated through four benchmark design examples. Comparison of the obtained results with those of some previous studies demonstrates the efficiency of this algorithm.

Publisher Correction

DEFF Research Database (Denmark)

Turcot, Valérie; Lu, Yingchang; Highland, Heather M

2018-01-01

In the published version of this paper, the name of author Emanuele Di Angelantonio was misspelled. This error has now been corrected in the HTML and PDF versions of the article.......In the published version of this paper, the name of author Emanuele Di Angelantonio was misspelled. This error has now been corrected in the HTML and PDF versions of the article....

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....

Scalable Nearest Neighbor Algorithms for High Dimensional Data.

Science.gov (United States)

Muja, Marius; Lowe, David G

2014-11-01

For many computer vision and machine learning problems, large training sets are key for good performance. However, the most computationally expensive part of many computer vision and machine learning algorithms consists of finding nearest neighbor matches to high dimensional vectors that represent the training data. We propose new algorithms for approximate nearest neighbor matching and evaluate and compare them with previous algorithms. For matching high dimensional features, we find two algorithms to be the most efficient: the randomized k-d forest and a new algorithm proposed in this paper, the priority search k-means tree. We also propose a new algorithm for matching binary features by searching multiple hierarchical clustering trees and show it outperforms methods typically used in the literature. We show that the optimal nearest neighbor algorithm and its parameters depend on the data set characteristics and describe an automated configuration procedure for finding the best algorithm to search a particular data set. In order to scale to very large data sets that would otherwise not fit in the memory of a single machine, we propose a distributed nearest neighbor matching framework that can be used with any of the algorithms described in the paper. All this research has been released as an open source library called fast library for approximate nearest neighbors (FLANN), which has been incorporated into OpenCV and is now one of the most popular libraries for nearest neighbor matching.

Dynamic gradient descent learning algorithms for enhanced empirical modeling of power plants

International Nuclear Information System (INIS)

Parlos, A.G.; Atiya, Amir; Chong, K.T.

1991-01-01

A newly developed dynamic gradient descent-based learning algorithm is used to train a recurrent multilayer perceptron network for use in empirical modeling of power plants. The two main advantages of the proposed learning algorithm are its ability to consider past error gradient information for future use and the two forward passes associated with its implementation, instead of one forward and one backward pass of the backpropagation algorithm. The latter advantage results in computational time saving because both passes can be performed simultaneously. The dynamic learning algorithm is used to train a hybrid feedforward/feedback neural network, a recurrent multilayer perceptron, which was previously found to exhibit good interpolation and extrapolation capabilities in modeling nonlinear dynamic systems. One of the drawbacks, however, of the previously reported work has been the long training times associated with accurate empirical models. The enhanced learning capabilities provided by the dynamic gradient descent-based learning algorithm are demonstrated by a case study of a steam power plant. The number of iterations required for accurate empirical modeling has been reduced from tens of thousands to hundreds, thus significantly expediting the learning process

Special Issue on Time Scale Algorithms

Science.gov (United States)

2008-01-01

unclassified Standard Form 298 (Rev. 8-98) Prescribed by ANSI Std Z39-18 IOP PUBLISHING METROLOGIA Metrologia 45 (2008) doi:10.1088/0026-1394/45/6/E01...special issue of Metrologia presents selected papers from the Fifth International Time Scale Algorithm Symposium (VITSAS), including some of the...scientists, and hosted by the Real Instituto y Observatorio de la Armada (ROA) in San Fernando, Spain, whose staff further enhanced their nation’s high

A novel discrete PSO algorithm for solving job shop scheduling problem to minimize makespan

Science.gov (United States)

Rameshkumar, K.; Rajendran, C.

2018-02-01

In this work, a discrete version of PSO algorithm is proposed to minimize the makespan of a job-shop. A novel schedule builder has been utilized to generate active schedules. The discrete PSO is tested using well known benchmark problems available in the literature. The solution produced by the proposed algorithms is compared with best known solution published in the literature and also compared with hybrid particle swarm algorithm and variable neighborhood search PSO algorithm. The solution construction methodology adopted in this study is found to be effective in producing good quality solutions for the various benchmark job-shop scheduling problems.

Blind Source Separation Based on Covariance Ratio and Artificial Bee Colony Algorithm

Directory of Open Access Journals (Sweden)

Lei Chen

2014-01-01

Full Text Available The computation amount in blind source separation based on bioinspired intelligence optimization is high. In order to solve this problem, we propose an effective blind source separation algorithm based on the artificial bee colony algorithm. In the proposed algorithm, the covariance ratio of the signals is utilized as the objective function and the artificial bee colony algorithm is used to solve it. The source signal component which is separated out, is then wiped off from mixtures using the deflation method. All the source signals can be recovered successfully by repeating the separation process. Simulation experiments demonstrate that significant improvement of the computation amount and the quality of signal separation is achieved by the proposed algorithm when compared to previous algorithms.

STREAMFINDER I: A New Algorithm for detecting Stellar Streams

Science.gov (United States)

Malhan, Khyati; Ibata, Rodrigo A.

2018-04-01

We have designed a powerful new algorithm to detect stellar streams in an automated and systematic way. The algorithm, which we call the STREAMFINDER, is well suited for finding dynamically cold and thin stream structures that may lie along any simple or complex orbits in Galactic stellar surveys containing any combination of positional and kinematic information. In the present contribution we introduce the algorithm, lay out the ideas behind it, explain the methodology adopted to detect streams and detail its workings by running it on a suite of simulations of mock Galactic survey data of similar quality to that expected from the ESA/Gaia mission. We show that our algorithm is able to detect even ultra-faint stream features lying well below previous detection limits. Tests show that our algorithm will be able to detect distant halo stream structures >10° long containing as few as ˜15 members (ΣG ˜ 33.6 mag arcsec-2) in the Gaia dataset.

Proportionate Minimum Error Entropy Algorithm for Sparse System Identification

Directory of Open Access Journals (Sweden)

Zongze Wu

2015-08-01

Full Text Available Sparse system identification has received a great deal of attention due to its broad applicability. The proportionate normalized least mean square (PNLMS algorithm, as a popular tool, achieves excellent performance for sparse system identification. In previous studies, most of the cost functions used in proportionate-type sparse adaptive algorithms are based on the mean square error (MSE criterion, which is optimal only when the measurement noise is Gaussian. However, this condition does not hold in most real-world environments. In this work, we use the minimum error entropy (MEE criterion, an alternative to the conventional MSE criterion, to develop the proportionate minimum error entropy (PMEE algorithm for sparse system identification, which may achieve much better performance than the MSE based methods especially in heavy-tailed non-Gaussian situations. Moreover, we analyze the convergence of the proposed algorithm and derive a sufficient condition that ensures the mean square convergence. Simulation results confirm the excellent performance of the new algorithm.

A Location-Aware Vertical Handoff Algorithm for Hybrid Networks

KAUST Repository

Mehbodniya, Abolfazl

2010-07-01

One of the main objectives of wireless networking is to provide mobile users with a robust connection to different networks so that they can move freely between heterogeneous networks while running their computing applications with no interruption. Horizontal handoff, or generally speaking handoff, is a process which maintains a mobile user\\'s active connection as it moves within a wireless network, whereas vertical handoff (VHO) refers to handover between different types of networks or different network layers. Optimizing VHO process is an important issue, required to reduce network signalling and mobile device power consumption as well as to improve network quality of service (QoS) and grade of service (GoS). In this paper, a VHO algorithm in multitier (overlay) networks is proposed. This algorithm uses pattern recognition to estimate user\\'s position, and decides on the handoff based on this information. For the pattern recognition algorithm structure, the probabilistic neural network (PNN) which has considerable simplicity and efficiency over existing pattern classifiers is used. Further optimization is proposed to improve the performance of the PNN algorithm. Performance analysis and comparisons with the existing VHO algorithm are provided and demonstrate a significant improvement with the proposed algorithm. Furthermore, incorporating the proposed algorithm, a structure is proposed for VHO from the medium access control (MAC) layer point of view. © 2010 ACADEMY PUBLISHER.

Publishing and Revising Content

Science.gov (United States)

Editors and Webmasters can publish content without going through a workflow. Publishing times and dates can be set, and multiple pages can be published in bulk. Making an edit to published content created a revision.

Combined Simulated Annealing Algorithm for the Discrete Facility Location Problem

Directory of Open Access Journals (Sweden)

Jin Qin

2012-01-01

Full Text Available The combined simulated annealing (CSA algorithm was developed for the discrete facility location problem (DFLP in the paper. The method is a two-layer algorithm, in which the external subalgorithm optimizes the decision of the facility location decision while the internal subalgorithm optimizes the decision of the allocation of customer's demand under the determined location decision. The performance of the CSA is tested by 30 instances with different sizes. The computational results show that CSA works much better than the previous algorithm on DFLP and offers a new reasonable alternative solution method to it.

A second chance for authors of hijacked journals to publish in legitimate journals.

Science.gov (United States)

Jalalian, Mehrdad

2015-01-01

This article proposes the republication of articles that have previously been published in counterfeit websites of hijacked journals. The paper also discusses the technical and ethical aspects of republishing such articles.

Column generation algorithms for virtual network embedding in flexi-grid optical networks.

Science.gov (United States)

Lin, Rongping; Luo, Shan; Zhou, Jingwei; Wang, Sheng; Chen, Bin; Zhang, Xiaoning; Cai, Anliang; Zhong, Wen-De; Zukerman, Moshe

2018-04-16

Network virtualization provides means for efficient management of network resources by embedding multiple virtual networks (VNs) to share efficiently the same substrate network. Such virtual network embedding (VNE) gives rise to a challenging problem of how to optimize resource allocation to VNs and to guarantee their performance requirements. In this paper, we provide VNE algorithms for efficient management of flexi-grid optical networks. We provide an exact algorithm aiming to minimize the total embedding cost in terms of spectrum cost and computation cost for a single VN request. Then, to achieve scalability, we also develop a heuristic algorithm for the same problem. We apply these two algorithms for a dynamic traffic scenario where many VN requests arrive one-by-one. We first demonstrate by simulations for the case of a six-node network that the heuristic algorithm obtains very close blocking probabilities to exact algorithm (about 0.2% higher). Then, for a network of realistic size (namely, USnet) we demonstrate that the blocking probability of our new heuristic algorithm is about one magnitude lower than a simpler heuristic algorithm, which was a component of an earlier published algorithm.

Improvement of Parallel Algorithm for MATRA Code

International Nuclear Information System (INIS)

Kim, Seong-Jin; Seo, Kyong-Won; Kwon, Hyouk; Hwang, Dae-Hyun

2014-01-01

The feasibility study to parallelize the MATRA code was conducted in KAERI early this year. As a result, a parallel algorithm for the MATRA code has been developed to decrease a considerably required computing time to solve a bigsize problem such as a whole core pin-by-pin problem of a general PWR reactor and to improve an overall performance of the multi-physics coupling calculations. It was shown that the performance of the MATRA code was greatly improved by implementing the parallel algorithm using MPI communication. For problems of a 1/8 core and whole core for SMART reactor, a speedup was evaluated as about 10 when the numbers of used processor were 25. However, it was also shown that the performance deteriorated as the axial node number increased. In this paper, the procedure of a communication between processors is optimized to improve the previous parallel algorithm.. To improve the performance deterioration of the parallelized MATRA code, the communication algorithm between processors was newly presented. It was shown that the speedup was improved and stable regardless of the axial node number

A New Adaptive Hungarian Mating Scheme in Genetic Algorithms

Directory of Open Access Journals (Sweden)

Chanju Jung

2016-01-01

Full Text Available In genetic algorithms, selection or mating scheme is one of the important operations. In this paper, we suggest an adaptive mating scheme using previously suggested Hungarian mating schemes. Hungarian mating schemes consist of maximizing the sum of mating distances, minimizing the sum, and random matching. We propose an algorithm to elect one of these Hungarian mating schemes. Every mated pair of solutions has to vote for the next generation mating scheme. The distance between parents and the distance between parent and offspring are considered when they vote. Well-known combinatorial optimization problems, the traveling salesperson problem, and the graph bisection problem are used for the test bed of our method. Our adaptive strategy showed better results than not only pure and previous hybrid schemes but also existing distance-based mating schemes.

The gradient boosting algorithm and random boosting for genome-assisted evaluation in large data sets.

Science.gov (United States)

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

A fast algorithm for 3D azimuthally anisotropic velocity scan

KAUST Repository

Hu, Jingwei; Fomel, Sergey; Ying, Lexing

2014-01-01

© 2014 European Association of Geoscientists & Engineers. The conventional velocity scan can be computationally expensive for large-scale seismic data sets, particularly when the presence of anisotropy requires multiparameter scanning. We introduce a fast algorithm for 3D azimuthally anisotropic velocity scan by generalizing the previously proposed 2D butterfly algorithm for hyperbolic Radon transforms. To compute semblance in a two-parameter residual moveout domain, the numerical complexity of our algorithm is roughly O(N3logN) as opposed to O(N5) of the straightforward velocity scan, with N being the representative of the number of points in a particular dimension of either data space or parameter space. Synthetic and field data examples demonstrate the superior efficiency of the proposed algorithm.

An Improved Recovery Algorithm for Decayed AES Key Schedule Images

Science.gov (United States)

Tsow, Alex

A practical algorithm that recovers AES key schedules from decayed memory images is presented. Halderman et al. [1] established this recovery capability, dubbed the cold-boot attack, as a serious vulnerability for several widespread software-based encryption packages. Our algorithm recovers AES-128 key schedules tens of millions of times faster than the original proof-of-concept release. In practice, it enables reliable recovery of key schedules at 70% decay, well over twice the decay capacity of previous methods. The algorithm is generalized to AES-256 and is empirically shown to recover 256-bit key schedules that have suffered 65% decay. When solutions are unique, the algorithm efficiently validates this property and outputs the solution for memory images decayed up to 60%.

A fast algorithm for 3D azimuthally anisotropic velocity scan

KAUST Repository

Hu, Jingwei

2014-11-11

© 2014 European Association of Geoscientists & Engineers. The conventional velocity scan can be computationally expensive for large-scale seismic data sets, particularly when the presence of anisotropy requires multiparameter scanning. We introduce a fast algorithm for 3D azimuthally anisotropic velocity scan by generalizing the previously proposed 2D butterfly algorithm for hyperbolic Radon transforms. To compute semblance in a two-parameter residual moveout domain, the numerical complexity of our algorithm is roughly O(N3logN) as opposed to O(N5) of the straightforward velocity scan, with N being the representative of the number of points in a particular dimension of either data space or parameter space. Synthetic and field data examples demonstrate the superior efficiency of the proposed algorithm.

HMC algorithm with multiple time scale integration and mass preconditioning

Science.gov (United States)

Urbach, C.; Jansen, K.; Shindler, A.; Wenger, U.

2006-01-01

We present a variant of the HMC algorithm with mass preconditioning (Hasenbusch acceleration) and multiple time scale integration. We have tested this variant for standard Wilson fermions at β=5.6 and at pion masses ranging from 380 to 680 MeV. We show that in this situation its performance is comparable to the recently proposed HMC variant with domain decomposition as preconditioner. We give an update of the "Berlin Wall" figure, comparing the performance of our variant of the HMC algorithm to other published performance data. Advantages of the HMC algorithm with mass preconditioning and multiple time scale integration are that it is straightforward to implement and can be used in combination with a wide variety of lattice Dirac operators.

Computational complexity of algorithms for sequence comparison, short-read assembly and genome alignment.

Science.gov (United States)

Baichoo, Shakuntala; Ouzounis, Christos A

A multitude of algorithms for sequence comparison, short-read assembly and whole-genome alignment have been developed in the general context of molecular biology, to support technology development for high-throughput sequencing, numerous applications in genome biology and fundamental research on comparative genomics. The computational complexity of these algorithms has been previously reported in original research papers, yet this often neglected property has not been reviewed previously in a systematic manner and for a wider audience. We provide a review of space and time complexity of key sequence analysis algorithms and highlight their properties in a comprehensive manner, in order to identify potential opportunities for further research in algorithm or data structure optimization. The complexity aspect is poised to become pivotal as we will be facing challenges related to the continuous increase of genomic data on unprecedented scales and complexity in the foreseeable future, when robust biological simulation at the cell level and above becomes a reality. Copyright © 2017 Elsevier B.V. All rights reserved.

Prediction of insemination outcomes in Holstein dairy cattle using alternative machine learning algorithms.

Science.gov (United States)

Shahinfar, Saleh; Page, David; Guenther, Jerry; Cabrera, Victor; Fricke, Paul; Weigel, Kent

2014-02-01

When making the decision about whether or not to breed a given cow, knowledge about the expected outcome would have an economic impact on profitability of the breeding program and net income of the farm. The outcome of each breeding can be affected by many management and physiological features that vary between farms and interact with each other. Hence, the ability of machine learning algorithms to accommodate complex relationships in the data and missing values for explanatory variables makes these algorithms well suited for investigation of reproduction performance in dairy cattle. The objective of this study was to develop a user-friendly and intuitive on-farm tool to help farmers make reproduction management decisions. Several different machine learning algorithms were applied to predict the insemination outcomes of individual cows based on phenotypic and genotypic data. Data from 26 dairy farms in the Alta Genetics (Watertown, WI) Advantage Progeny Testing Program were used, representing a 10-yr period from 2000 to 2010. Health, reproduction, and production data were extracted from on-farm dairy management software, and estimated breeding values were downloaded from the US Department of Agriculture Agricultural Research Service Animal Improvement Programs Laboratory (Beltsville, MD) database. The edited data set consisted of 129,245 breeding records from primiparous Holstein cows and 195,128 breeding records from multiparous Holstein cows. Each data point in the final data set included 23 and 25 explanatory variables and 1 binary outcome for of 0.756 ± 0.005 and 0.736 ± 0.005 for primiparous and multiparous cows, respectively. The naïve Bayes algorithm, Bayesian network, and decision tree algorithms showed somewhat poorer classification performance. An information-based variable selection procedure identified herd average conception rate, incidence of ketosis, number of previous (failed) inseminations, days in milk at breeding, and mastitis as the most

Publishing bioethics and bioethics--reflections on academic publishing by a journal editor.

Science.gov (United States)

Schüklenk, Udo

2011-02-01

This article by one of the Editors of Bioethics, published in the 25th anniversary issue of the journal, describes some of the revolutionary changes academic publishing has undergone during the last decades. Many humanities journals went from typically small print-runs, counting by the hundreds, to on-line availability in thousands of university libraries worldwide. Article up-take by our subscribers can be measured efficiently. The implications of this and other changes to academic publishing are discussed. Important ethical challenges need to be addressed in areas such as the enforcement of plagiarism-related policies, the so-called 'impact factor' and its impact on academic integrity, and the question of whether on-line only publishing can currently guarantee the integrity of academic publishing histories. © 2010 Blackwell Publishing Ltd.

A comparison between physicians and computer algorithms for form CMS-2728 data reporting.

Science.gov (United States)

Malas, Mohammed Said; Wish, Jay; Moorthi, Ranjani; Grannis, Shaun; Dexter, Paul; Duke, Jon; Moe, Sharon

2017-01-01

CMS-2728 form (Medical Evidence Report) assesses 23 comorbidities chosen to reflect poor outcomes and increased mortality risk. Previous studies questioned the validity of physician reporting on forms CMS-2728. We hypothesize that reporting of comorbidities by computer algorithms identifies more comorbidities than physician completion, and, therefore, is more reflective of underlying disease burden. We collected data from CMS-2728 forms for all 296 patients who had incident ESRD diagnosis and received chronic dialysis from 2005 through 2014 at Indiana University outpatient dialysis centers. We analyzed patients' data from electronic medical records systems that collated information from multiple health care sources. Previously utilized algorithms or natural language processing was used to extract data on 10 comorbidities for a period of up to 10 years prior to ESRD incidence. These algorithms incorporate billing codes, prescriptions, and other relevant elements. We compared the presence or unchecked status of these comorbidities on the forms to the presence or absence according to the algorithms. Computer algorithms had higher reporting of comorbidities compared to forms completion by physicians. This remained true when decreasing data span to one year and using only a single health center source. The algorithms determination was well accepted by a physician panel. Importantly, algorithms use significantly increased the expected deaths and lowered the standardized mortality ratios. Using computer algorithms showed superior identification of comorbidities for form CMS-2728 and altered standardized mortality ratios. Adapting similar algorithms in available EMR systems may offer more thorough evaluation of comorbidities and improve quality reporting. © 2016 International Society for Hemodialysis.

What Desktop Publishing Can Teach Professional Writing Students about Publishing.

Science.gov (United States)

Dobberstein, Michael

1992-01-01

Points out that desktop publishing is a metatechnology that allows professional writing students access to the production phase of publishing, giving students hands-on practice in preparing text for printing and in learning how that preparation affects the visual meaning of documents. (SR)

A comparison of MCNP4C electron transport with ITS 3.0 and experiment at incident energies between 100 keV and 20 MeV: influence of voxel size, substeps and energy indexing algorithm

International Nuclear Information System (INIS)

Schaart, Dennis R.; Jansen, Jan Th.M.; Zoetelief, Johannes; Leege, Piet F.A. de

2002-01-01

The condensed-history electron transport algorithms in the Monte Carlo code MCNP4C are derived from ITS 3.0, which is a well-validated code for coupled electron-photon simulations. This, combined with its user-friendliness and versatility, makes MCNP4C a promising code for medical physics applications. Such applications, however, require a high degree of accuracy. In this work, MCNP4C electron depth-dose distributions in water are compared with published ITS 3.0 results. The influences of voxel size, substeps and choice of electron energy indexing algorithm are investigated at incident energies between 100 keV and 20 MeV. Furthermore, previously published dose measurements for seven beta emitters are simulated. Since MCNP4C does not allow tally segmentation with the *F8 energy deposition tally, even a homogeneous phantom must be subdivided in cells to calculate the distribution of dose. The repeated interruption of the electron tracks at the cell boundaries significantly affects the electron transport. An electron track length estimator of absorbed dose is described which allows tally segmentation. In combination with the ITS electron energy indexing algorithm, this estimator appears to reproduce ITS 3.0 and experimental results well. If, however, cell boundaries are used instead of segments, or if the MCNP indexing algorithm is applied, the agreement is considerably worse. (author)

UV Reconstruction Algorithm And Diurnal Cycle Variability

Science.gov (United States)

Curylo, Aleksander; Litynska, Zenobia; Krzyscin, Janusz; Bogdanska, Barbara

2009-03-01

UV reconstruction is a method of estimation of surface UV with the use of available actinometrical and aerological measurements. UV reconstruction is necessary for the study of long-term UV change. A typical series of UV measurements is not longer than 15 years, which is too short for trend estimation. The essential problem in the reconstruction algorithm is the good parameterization of clouds. In our previous algorithm we used an empirical relation between Cloud Modification Factor (CMF) in global radiation and CMF in UV. The CMF is defined as the ratio between measured and modelled irradiances. Clear sky irradiance was calculated with a solar radiative transfer model. In the proposed algorithm, the time variability of global radiation during the diurnal cycle is used as an additional source of information. For elaborating an improved reconstruction algorithm relevant data from Legionowo [52.4 N, 21.0 E, 96 m a.s.l], Poland were collected with the following instruments: NILU-UV multi channel radiometer, Kipp&Zonen pyranometer, radiosonde profiles of ozone, humidity and temperature. The proposed algorithm has been used for reconstruction of UV at four Polish sites: Mikolajki, Kolobrzeg, Warszawa-Bielany and Zakopane since the early 1960s. Krzyscin's reconstruction of total ozone has been used in the calculations.

Consensus algorithm in smart grid and communication networks

Science.gov (United States)

Alfagee, Husain Abdulaziz

On a daily basis, consensus theory attracts more and more researches from different areas of interest, to apply its techniques to solve technical problems in a way that is faster, more reliable, and even more precise than ever before. A power system network is one of those fields that consensus theory employs extensively. The use of the consensus algorithm to solve the Economic Dispatch and Load Restoration Problems is a good example. Instead of a conventional central controller, some researchers have explored an algorithm to solve the above mentioned problems, in a distribution manner, using the consensus algorithm, which is based on calculation methods, i.e., non estimation methods, for updating the information consensus matrix. Starting from this point of solving these types of problems mentioned, specifically, in a distribution fashion, using the consensus algorithm, we have implemented a new advanced consensus algorithm. It is based on the adaptive estimation techniques, such as the Gradient Algorithm and the Recursive Least Square Algorithm, to solve the same problems. This advanced work was tested on different case studies that had formerly been explored, as seen in references 5, 7, and 18. Three and five generators, or agents, with different topologies, correspond to the Economic Dispatch Problem and the IEEE 16-Bus power system corresponds to the Load Restoration Problem. In all the cases we have studied, the results met our expectations with extreme accuracy, and completely matched the results of the previous researchers. There is little question that this research proves the capability and dependability of using the consensus algorithm, based on the estimation methods as the Gradient Algorithm and the Recursive Least Square Algorithm to solve such power problems.

Recursive parameter estimation for Hammerstein-Wiener systems using modified EKF algorithm.

Science.gov (United States)

Yu, Feng; Mao, Zhizhong; Yuan, Ping; He, Dakuo; Jia, Mingxing

2017-09-01

This paper focuses on the recursive parameter estimation for the single input single output Hammerstein-Wiener system model, and the study is then extended to a rarely mentioned multiple input single output Hammerstein-Wiener system. Inspired by the extended Kalman filter algorithm, two basic recursive algorithms are derived from the first and the second order Taylor approximation. Based on the form of the first order approximation algorithm, a modified algorithm with larger parameter convergence domain is proposed to cope with the problem of small parameter convergence domain of the first order one and the application limit of the second order one. The validity of the modification on the expansion of convergence domain is shown from the convergence analysis and is demonstrated with two simulation cases. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Algorithm for Video Summarization of Bronchoscopy Procedures

Directory of Open Access Journals (Sweden)

Leszczuk Mikołaj I

2011-12-01

Full Text Available Abstract Background The duration of bronchoscopy examinations varies considerably depending on the diagnostic and therapeutic procedures used. It can last more than 20 minutes if a complex diagnostic work-up is included. With wide access to videobronchoscopy, the whole procedure can be recorded as a video sequence. Common practice relies on an active attitude of the bronchoscopist who initiates the recording process and usually chooses to archive only selected views and sequences. However, it may be important to record the full bronchoscopy procedure as documentation when liability issues are at stake. Furthermore, an automatic recording of the whole procedure enables the bronchoscopist to focus solely on the performed procedures. Video recordings registered during bronchoscopies include a considerable number of frames of poor quality due to blurry or unfocused images. It seems that such frames are unavoidable due to the relatively tight endobronchial space, rapid movements of the respiratory tract due to breathing or coughing, and secretions which occur commonly in the bronchi, especially in patients suffering from pulmonary disorders. Methods The use of recorded bronchoscopy video sequences for diagnostic, reference and educational purposes could be considerably extended with efficient, flexible summarization algorithms. Thus, the authors developed a prototype system to create shortcuts (called summaries or abstracts of bronchoscopy video recordings. Such a system, based on models described in previously published papers, employs image analysis methods to exclude frames or sequences of limited diagnostic or education value. Results The algorithm for the selection or exclusion of specific frames or shots from video sequences recorded during bronchoscopy procedures is based on several criteria, including automatic detection of "non-informative", frames showing the branching of the airways and frames including pathological lesions. Conclusions

A Radix-10 Digit-Recurrence Division Unit: Algorithm and Architecture

DEFF Research Database (Denmark)

Lang, Tomas; Nannarelli, Alberto

2007-01-01

In this work, we present a radix-10 division unit that is based on the digit-recurrence algorithm. The previous decimal division designs do not include recent developments in the theory and practice of this type of algorithm, which were developed for radix-2^k dividers. In addition to the adaptat...... dynamic range of significant) and it has a shorter latency than a radix-10 unit based on the Newton-Raphson approximation....

Efficient Serial and Parallel Algorithms for Selection of Unique Oligos in EST Databases.

Science.gov (United States)

Mata-Montero, Manrique; Shalaby, Nabil; Sheppard, Bradley

2013-01-01

Obtaining unique oligos from an EST database is a problem of great importance in bioinformatics, particularly in the discovery of new genes and the mapping of the human genome. Many algorithms have been developed to find unique oligos, many of which are much less time consuming than the traditional brute force approach. An algorithm was presented by Zheng et al. (2004) which finds the solution of the unique oligos search problem efficiently. We implement this algorithm as well as several new algorithms based on some theorems included in this paper. We demonstrate how, with these new algorithms, we can obtain unique oligos much faster than with previous ones. We parallelize these new algorithms to further improve the time of finding unique oligos. All algorithms are run on ESTs obtained from a Barley EST database.

[Trends of electronic publishing in medicine and life sciences].

Science.gov (United States)

Strelski-Waisman, Neta; Waisman, Dan

2005-09-01

Scientific publication in the electronic media is gaining popularity in academic libraries, research institutions and commercial organizations. The electronic journal may shorten the processes of writing and publication, decrease publication and distribution costs, and enable access from any location in the world. Electronic publications have unique advantages: it is possible to search them, to create hyperlinks to references and footnotes, as well as to information on the web and to include graphics and photographs at a very low cost. Audio, video and tri-dimensional images may also be included. Electronic publishing may also speed up review and publication processes and enable the writer to receive immediate feedback through the web. However, in spite of the advantages, there are certain points that must be considered: accessibility to previously published material is not guaranteed as databases are not always stable and coverage may change without notice. In addition, the price that commercial publishers charge for their services may be very high or be subject to the purchase of a packaged deal that may include unwanted databases. Many issues of copyright and the use of published material are not yet finalized. In this review we discuss the advantages and disadvantages of the electronic scientific publication, the feasibility of keeping appropriate quality and peer-review process, the stability and accessibility of databases managed by the publishers and the acceptance of the electronic format by scientists and clinicians.

Novel density-based and hierarchical density-based clustering algorithms for uncertain data.

Science.gov (United States)

Zhang, Xianchao; Liu, Han; Zhang, Xiaotong

2017-09-01

Uncertain data has posed a great challenge to traditional clustering algorithms. Recently, several algorithms have been proposed for clustering uncertain data, and among them density-based techniques seem promising for handling data uncertainty. However, some issues like losing uncertain information, high time complexity and nonadaptive threshold have not been addressed well in the previous density-based algorithm FDBSCAN and hierarchical density-based algorithm FOPTICS. In this paper, we firstly propose a novel density-based algorithm PDBSCAN, which improves the previous FDBSCAN from the following aspects: (1) it employs a more accurate method to compute the probability that the distance between two uncertain objects is less than or equal to a boundary value, instead of the sampling-based method in FDBSCAN; (2) it introduces new definitions of probability neighborhood, support degree, core object probability, direct reachability probability, thus reducing the complexity and solving the issue of nonadaptive threshold (for core object judgement) in FDBSCAN. Then, we modify the algorithm PDBSCAN to an improved version (PDBSCANi), by using a better cluster assignment strategy to ensure that every object will be assigned to the most appropriate cluster, thus solving the issue of nonadaptive threshold (for direct density reachability judgement) in FDBSCAN. Furthermore, as PDBSCAN and PDBSCANi have difficulties for clustering uncertain data with non-uniform cluster density, we propose a novel hierarchical density-based algorithm POPTICS by extending the definitions of PDBSCAN, adding new definitions of fuzzy core distance and fuzzy reachability distance, and employing a new clustering framework. POPTICS can reveal the cluster structures of the datasets with different local densities in different regions better than PDBSCAN and PDBSCANi, and it addresses the issues in FOPTICS. Experimental results demonstrate the superiority of our proposed algorithms over the existing

A sparse matrix based full-configuration interaction algorithm

International Nuclear Information System (INIS)

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

2008-01-01

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

Reinvention of publishers' revenue model: expectations of advertisers towards publishers' products

OpenAIRE

Koller, Hans; Dennstedt, Bianca

2017-01-01

Publishers have to reconsider their revenue model. Facing a massive decline in the circulation of newspapers and magazines over the past years, publishers have lost not only readers but also many advertisers. Thus, publishers are faced with both changed customer expectations as well as difficulty in generating profit. Users are increasingly less willing to pay for digital products and their expectations of digital content have changed: They would like to contribute their own content as well a...

Modified automatic term selection v2: A faster algorithm to calculate inelastic scattering cross-sections

Energy Technology Data Exchange (ETDEWEB)

Rusz, Ján, E-mail: jan.rusz@fysik.uu.se

2017-06-15

Highlights: • New algorithm for calculating double differential scattering cross-section. • Shown good convergence properties. • Outperforms older MATS algorithm, particularly in zone axis calculations. - Abstract: We present a new algorithm for calculating inelastic scattering cross-section for fast electrons. Compared to the previous Modified Automatic Term Selection (MATS) algorithm (Rusz et al. [18]), it has far better convergence properties in zone axis calculations and it allows to identify contributions of individual atoms. One can think of it as a blend of MATS algorithm and a method described by Weickenmeier and Kohl [10].

Algorithms

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.

Evaluation of Static JavaScript Call Graph Algorithms

NARCIS (Netherlands)

J.-J. Dijkstra (Jorryt-Jan)

2014-01-01

htmlabstractThis thesis consists of a replication study in which two algorithms to compute JavaScript call graphs have been implemented and evaluated. Existing IDE support for JavaScript is hampered due to the dynamic nature of the language. Previous studies partially solve call graph computation

Automatic boiling water reactor control rod pattern design using particle swarm optimization algorithm and local search

Energy Technology Data Exchange (ETDEWEB)

Wang, Cheng-Der, E-mail: jdwang@iner.gov.tw [Nuclear Engineering Division, Institute of Nuclear Energy Research, No. 1000, Wenhua Rd., Jiaan Village, Longtan Township, Taoyuan County 32546, Taiwan, ROC (China); Lin, Chaung [National Tsing Hua University, Department of Engineering and System Science, 101, Section 2, Kuang Fu Road, Hsinchu 30013, Taiwan (China)

2013-02-15

Highlights: ► The PSO algorithm was adopted to automatically design a BWR CRP. ► The local search procedure was added to improve the result of PSO algorithm. ► The results show that the obtained CRP is the same good as that in the previous work. -- Abstract: This study developed a method for the automatic design of a boiling water reactor (BWR) control rod pattern (CRP) using the particle swarm optimization (PSO) algorithm. The PSO algorithm is more random compared to the rank-based ant system (RAS) that was used to solve the same BWR CRP design problem in the previous work. In addition, the local search procedure was used to make improvements after PSO, by adding the single control rod (CR) effect. The design goal was to obtain the CRP so that the thermal limits and shutdown margin would satisfy the design requirement and the cycle length, which is implicitly controlled by the axial power distribution, would be acceptable. The results showed that the same acceptable CRP found in the previous work could be obtained.

NRGC: a novel referential genome compression algorithm.

Science.gov (United States)

Saha, Subrata; Rajasekaran, Sanguthevar

2016-11-15

Next-generation sequencing techniques produce millions to billions of short reads. The procedure is not only very cost effective but also can be done in laboratory environment. The state-of-the-art sequence assemblers then construct the whole genomic sequence from these reads. Current cutting edge computing technology makes it possible to build genomic sequences from the billions of reads within a minimal cost and time. As a consequence, we see an explosion of biological sequences in recent times. In turn, the cost of storing the sequences in physical memory or transmitting them over the internet is becoming a major bottleneck for research and future medical applications. Data compression techniques are one of the most important remedies in this context. We are in need of suitable data compression algorithms that can exploit the inherent structure of biological sequences. Although standard data compression algorithms are prevalent, they are not suitable to compress biological sequencing data effectively. In this article, we propose a novel referential genome compression algorithm (NRGC) to effectively and efficiently compress the genomic sequences. We have done rigorous experiments to evaluate NRGC by taking a set of real human genomes. The simulation results show that our algorithm is indeed an effective genome compression algorithm that performs better than the best-known algorithms in most of the cases. Compression and decompression times are also very impressive. The implementations are freely available for non-commercial purposes. They can be downloaded from: http://www.engr.uconn.edu/~rajasek/NRGC.zip CONTACT: rajasek@engr.uconn.edu. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Evolving Stochastic Learning Algorithm based on Tsallis entropic index

Science.gov (United States)

Anastasiadis, A. D.; Magoulas, G. D.

2006-03-01

In this paper, inspired from our previous algorithm, which was based on the theory of Tsallis statistical mechanics, we develop a new evolving stochastic learning algorithm for neural networks. The new algorithm combines deterministic and stochastic search steps by employing a different adaptive stepsize for each network weight, and applies a form of noise that is characterized by the nonextensive entropic index q, regulated by a weight decay term. The behavior of the learning algorithm can be made more stochastic or deterministic depending on the trade off between the temperature T and the q values. This is achieved by introducing a formula that defines a time-dependent relationship between these two important learning parameters. Our experimental study verifies that there are indeed improvements in the convergence speed of this new evolving stochastic learning algorithm, which makes learning faster than using the original Hybrid Learning Scheme (HLS). In addition, experiments are conducted to explore the influence of the entropic index q and temperature T on the convergence speed and stability of the proposed method.

CAT-PUMA: CME Arrival Time Prediction Using Machine learning Algorithms

Science.gov (United States)

Liu, Jiajia; Ye, Yudong; Shen, Chenglong; Wang, Yuming; Erdélyi, Robert

2018-04-01

CAT-PUMA (CME Arrival Time Prediction Using Machine learning Algorithms) quickly and accurately predicts the arrival of Coronal Mass Ejections (CMEs) of CME arrival time. The software was trained via detailed analysis of CME features and solar wind parameters using 182 previously observed geo-effective partial-/full-halo CMEs and uses algorithms of the Support Vector Machine (SVM) to make its predictions, which can be made within minutes of providing the necessary input parameters of a CME.

Double evolutsional artificial bee colony algorithm for multiple traveling salesman problem

Directory of Open Access Journals (Sweden)

Xue Ming Hao

2016-01-01

Full Text Available The double evolutional artificial bee colony algorithm (DEABC is proposed for solving the single depot multiple traveling salesman problem (MTSP. The proposed DEABC algorithm, which takes advantage of the strength of the upgraded operators, is characterized by its guidance in exploitation search and diversity in exploration search. The double evolutional process for exploitation search is composed of two phases of half stochastic optimal search, and the diversity generating operator for exploration search is used for solutions which cannot be improved after limited times. The computational results demonstrated the superiority of our algorithm over previous state-of-the-art methods.

New Facets and a Branch-and-Cut Algorithm for the Weighted Clique Problem

DEFF Research Database (Denmark)

Sørensen, Michael Malmros

2001-01-01

of facet defining inequalities in a branch-and-cut algorithm for the problem. We give a description of this algorithm, including some separation procedures, and present the computational results for different sets of test problems. The computation times that are obtained indicate that this algorithm...... four new classes of facet defining inequalities for the associated b-clique polytope. One of these inequality classes constitutes a generalization of the well known tree inequalities; the other classes are associated with multistars. We utilize these inequality classes together with other classes...... is more efficient than previously described algorithms for the problem....

Publisher Correction

DEFF Research Database (Denmark)

Bonàs-Guarch, Sílvia; Guindo-Martínez, Marta; Miguel-Escalada, Irene

2018-01-01

In the originally published version of this Article, the affiliation details for Santi González, Jian'an Luan and Claudia Langenberg were inadvertently omitted. Santi González should have been affiliated with 'Barcelona Supercomputing Center (BSC), Joint BSC-CRG-IRB Research Program in Computatio......In the originally published version of this Article, the affiliation details for Santi González, Jian'an Luan and Claudia Langenberg were inadvertently omitted. Santi González should have been affiliated with 'Barcelona Supercomputing Center (BSC), Joint BSC-CRG-IRB Research Program...

Research and Applications of Shop Scheduling Based on Genetic Algorithms

Directory of Open Access Journals (Sweden)

Hang ZHAO

Full Text Available ABSTRACT Shop Scheduling is an important factor affecting the efficiency of production, efficient scheduling method and a research and application for optimization technology play an important role for manufacturing enterprises to improve production efficiency, reduce production costs and many other aspects. Existing studies have shown that improved genetic algorithm has solved the limitations that existed in the genetic algorithm, the objective function is able to meet customers' needs for shop scheduling, and the future research should focus on the combination of genetic algorithm with other optimized algorithms. In this paper, in order to overcome the shortcomings of early convergence of genetic algorithm and resolve local minimization problem in search process,aiming at mixed flow shop scheduling problem, an improved cyclic search genetic algorithm is put forward, and chromosome coding method and corresponding operation are given.The operation has the nature of inheriting the optimal individual ofthe previous generation and is able to avoid the emergence of local minimum, and cyclic and crossover operation and mutation operation can enhance the diversity of the population and then quickly get the optimal individual, and the effectiveness of the algorithm is validated. Experimental results show that the improved algorithm can well avoid the emergency of local minimum and is rapid in convergence.

STAR Algorithm Integration Team - Facilitating operational algorithm development

Science.gov (United States)

Mikles, V. J.

2015-12-01

The NOAA/NESDIS Center for Satellite Research and Applications (STAR) provides technical support of the Joint Polar Satellite System (JPSS) algorithm development and integration tasks. Utilizing data from the S-NPP satellite, JPSS generates over thirty Environmental Data Records (EDRs) and Intermediate Products (IPs) spanning atmospheric, ocean, cryosphere, and land weather disciplines. The Algorithm Integration Team (AIT) brings technical expertise and support to product algorithms, specifically in testing and validating science algorithms in a pre-operational environment. The AIT verifies that new and updated algorithms function in the development environment, enforces established software development standards, and ensures that delivered packages are functional and complete. AIT facilitates the development of new JPSS-1 algorithms by implementing a review approach based on the Enterprise Product Lifecycle (EPL) process. Building on relationships established during the S-NPP algorithm development process and coordinating directly with science algorithm developers, the AIT has implemented structured reviews with self-contained document suites. The process has supported algorithm improvements for products such as ozone, active fire, vegetation index, and temperature and moisture profiles.

Adaptive sampling algorithm for detection of superpoints

Institute of Scientific and Technical Information of China (English)

CHENG Guang; GONG Jian; DING Wei; WU Hua; QIANG ShiQiang

2008-01-01

The superpoints are the sources (or the destinations) that connect with a great deal of destinations (or sources) during a measurement time interval, so detecting the superpoints in real time is very important to network security and management. Previous algorithms are not able to control the usage of the memory and to deliver the desired accuracy, so it is hard to detect the superpoints on a high speed link in real time. In this paper, we propose an adaptive sampling algorithm to detect the superpoints in real time, which uses a flow sample and hold module to reduce the detection of the non-superpoints and to improve the measurement accuracy of the superpoints. We also design a data stream structure to maintain the flow records, which compensates for the flow Hash collisions statistically. An adaptive process based on different sampling probabilities is used to maintain the recorded IP ad dresses in the limited memory. This algorithm is compared with the other algo rithms by analyzing the real network trace data. Experiment results and mathematic analysis show that this algorithm has the advantages of both the limited memory requirement and high measurement accuracy.

Getting Your Textbook Published.

Science.gov (United States)

Irwin, Armond J.

1982-01-01

Points to remember in getting a textbook published are examined: book idea, publisher's sales representatives, letter of inquiry, qualifications for authorship, author information form, idea proposal, reviews, marketing and sales, publishing agreement, author royalties, and copyright assignment. (CT)

Angular-contact ball-bearing internal load estimation algorithm using runtime adaptive relaxation

Science.gov (United States)

Medina, H.; Mutu, R.

2017-07-01

An algorithm to estimate internal loads for single-row angular contact ball bearings due to externally applied thrust loads and high-operating speeds is presented. A new runtime adaptive relaxation procedure and blending function is proposed which ensures algorithm stability whilst also reducing the number of iterations needed to reach convergence, leading to an average reduction in computation time in excess of approximately 80%. The model is validated based on a 218 angular contact bearing and shows excellent agreement compared to published results.

A Faster Algorithm to Recognize Even-Hole-Free Graphs

OpenAIRE

Chang, Hsien-Chih; Lu, Hsueh-I

2013-01-01

We study the problem of determining whether an $n$-node graph $G$ has an even hole, i.e., an induced simple cycle consisting of an even number of nodes. Conforti, Cornu\\'ejols, Kapoor, and Vu\\v{s}kovi\\'c gave the first polynomial-time algorithm for the problem, which runs in $O(n^{40})$ time. Later, Chudnovsky, Kawarabayashi, and Seymour reduced the running time to $O(n^{31})$. The best previously known algorithm for the problem, due to da Silva and Vu\\v{s}kovi\\'c, runs in $O(n^{19})$ time. I...

mRMR-ABC: A Hybrid Gene Selection Algorithm for Cancer Classification Using Microarray Gene Expression Profiling

Directory of Open Access Journals (Sweden)

Hala Alshamlan

2015-01-01

Full Text Available An artificial bee colony (ABC is a relatively recent swarm intelligence optimization approach. In this paper, we propose the first attempt at applying ABC algorithm in analyzing a microarray gene expression profile. In addition, we propose an innovative feature selection algorithm, minimum redundancy maximum relevance (mRMR, and combine it with an ABC algorithm, mRMR-ABC, to select informative genes from microarray profile. The new approach is based on a support vector machine (SVM algorithm to measure the classification accuracy for selected genes. We evaluate the performance of the proposed mRMR-ABC algorithm by conducting extensive experiments on six binary and multiclass gene expression microarray datasets. Furthermore, we compare our proposed mRMR-ABC algorithm with previously known techniques. We reimplemented two of these techniques for the sake of a fair comparison using the same parameters. These two techniques are mRMR when combined with a genetic algorithm (mRMR-GA and mRMR when combined with a particle swarm optimization algorithm (mRMR-PSO. The experimental results prove that the proposed mRMR-ABC algorithm achieves accurate classification performance using small number of predictive genes when tested using both datasets and compared to previously suggested methods. This shows that mRMR-ABC is a promising approach for solving gene selection and cancer classification problems.

mRMR-ABC: A Hybrid Gene Selection Algorithm for Cancer Classification Using Microarray Gene Expression Profiling.

Science.gov (United States)

Alshamlan, Hala; Badr, Ghada; Alohali, Yousef

2015-01-01

An artificial bee colony (ABC) is a relatively recent swarm intelligence optimization approach. In this paper, we propose the first attempt at applying ABC algorithm in analyzing a microarray gene expression profile. In addition, we propose an innovative feature selection algorithm, minimum redundancy maximum relevance (mRMR), and combine it with an ABC algorithm, mRMR-ABC, to select informative genes from microarray profile. The new approach is based on a support vector machine (SVM) algorithm to measure the classification accuracy for selected genes. We evaluate the performance of the proposed mRMR-ABC algorithm by conducting extensive experiments on six binary and multiclass gene expression microarray datasets. Furthermore, we compare our proposed mRMR-ABC algorithm with previously known techniques. We reimplemented two of these techniques for the sake of a fair comparison using the same parameters. These two techniques are mRMR when combined with a genetic algorithm (mRMR-GA) and mRMR when combined with a particle swarm optimization algorithm (mRMR-PSO). The experimental results prove that the proposed mRMR-ABC algorithm achieves accurate classification performance using small number of predictive genes when tested using both datasets and compared to previously suggested methods. This shows that mRMR-ABC is a promising approach for solving gene selection and cancer classification problems.

Publisher Correction to

NARCIS (Netherlands)

Barrio, Isabel C.; Lindén, Elin; Beest, Te Mariska; Olofsson, Johan; Rocha, Adrian; Soininen, Eeva M.; Alatalo, Juha M.; Andersson, Tommi; Asmus, Ashley; Boike, Julia; Bråthen, Kari Anne; Bryant, John P.; Buchwal, Agata; Bueno, C.G.; Christie, Katherine S.; Egelkraut, Dagmar; Ehrich, Dorothee; Fishback, Lee Ann; Forbes, Bruce C.; Gartzia, Maite; Grogan, Paul; Hallinger, Martin; Heijmans, Monique M.P.D.; Hik, David S.; Hofgaard, Annika; Holmgren, Milena; Høye, Toke T.; Huebner, Diane C.; Jónsdóttir, Ingibjörg Svala; Kaarlejärvi, Elina; Kumpula, Timo; Lange, Cynthia Y.M.J.G.; Lange, Jelena; Lévesque, Esther; Limpens, Juul; Macias-Fauria, Marc; Myers-Smith, Isla; Nieukerken, van Erik J.; Normand, Signe; Post, Eric S.; Schmidt, Niels Martin; Sitters, Judith; Skoracka, Anna; Sokolov, Alexander; Sokolova, Natalya; Speed, James D.M.; Street, Lorna E.; Sundqvist, Maja K.; Suominen, Otso; Tananaev, Nikita; Tremblay, Jean Pierre; Urbanowicz, Christine; Uvarov, Sergey A.; Watts, David; Wilmking, Martin; Wookey, Philip A.; Zimmermann, Heike H.; Zverev, Vitali; Kozlov, Mikhail V.

2018-01-01

The above mentioned article was originally scheduled for publication in the special issue on Ecology of Tundra Arthropods with guest editors Toke T. Høye . Lauren E. Culler. Erroneously, the article was published in Polar Biology, Volume 40, Issue 11, November, 2017. The publisher sincerely

The effect of 18F-FDG-PET image reconstruction algorithms on the expression of characteristic metabolic brain network in Parkinson's disease.

Science.gov (United States)

Tomše, Petra; Jensterle, Luka; Rep, Sebastijan; Grmek, Marko; Zaletel, Katja; Eidelberg, David; Dhawan, Vijay; Ma, Yilong; Trošt, Maja

2017-09-01

To evaluate the reproducibility of the expression of Parkinson's Disease Related Pattern (PDRP) across multiple sets of 18F-FDG-PET brain images reconstructed with different reconstruction algorithms. 18F-FDG-PET brain imaging was performed in two independent cohorts of Parkinson's disease (PD) patients and normal controls (NC). Slovenian cohort (20 PD patients, 20 NC) was scanned with Siemens Biograph mCT camera and reconstructed using FBP, FBP+TOF, OSEM, OSEM+TOF, OSEM+PSF and OSEM+PSF+TOF. American Cohort (20 PD patients, 7 NC) was scanned with GE Advance camera and reconstructed using 3DRP, FORE-FBP and FORE-Iterative. Expressions of two previously-validated PDRP patterns (PDRP-Slovenia and PDRP-USA) were calculated. We compared the ability of PDRP to discriminate PD patients from NC, differences and correlation between the corresponding subject scores and ROC analysis results across the different reconstruction algorithms. The expression of PDRP-Slovenia and PDRP-USA networks was significantly elevated in PD patients compared to NC (palgorithms. PDRP expression strongly correlated between all studied algorithms and the reference algorithm (r⩾0.993, palgorithms varied within 0.73 and 0.08 of the reference value for PDRP-Slovenia and PDRP-USA, respectively. ROC analysis confirmed high similarity in sensitivity, specificity and AUC among all studied reconstruction algorithms. These results show that the expression of PDRP is reproducible across a variety of reconstruction algorithms of 18F-FDG-PET brain images. PDRP is capable of providing a robust metabolic biomarker of PD for multicenter 18F-FDG-PET images acquired in the context of differential diagnosis or clinical trials. Copyright © 2017 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Vectorised Spreading Activation algorithm for centrality measurement

Directory of Open Access Journals (Sweden)

Alexander Troussov

2011-01-01

Full Text Available Spreading Activation is a family of graph-based algorithms widely used in areas such as information retrieval, epidemic models, and recommender systems. In this paper we introduce a novel Spreading Activation (SA method that we call Vectorised Spreading Activation (VSA. VSA algorithms, like “traditional” SA algorithms, iteratively propagate the activation from the initially activated set of nodes to the other nodes in a network through outward links. The level of the node’s activation could be used as a centrality measurement in accordance with dynamic model-based view of centrality that focuses on the outcomes for nodes in a network where something is flowing from node to node across the edges. Representing the activation by vectors allows the use of the information about various dimensionalities of the flow and the dynamic of the flow. In this capacity, VSA algorithms can model multitude of complex multidimensional network flows. We present the results of numerical simulations on small synthetic social networks and multi­dimensional network models of folksonomies which show that the results of VSA propagation are more sensitive to the positions of the initial seed and to the community structure of the network than the results produced by traditional SA algorithms. We tentatively conclude that the VSA methods could be instrumental to develop scalable and computationally efficient algorithms which could achieve synergy between computation of centrality indexes with detection of community structures in networks. Based on our preliminary results and on improvements made over previous studies, we foresee advances and applications in the current state of the art of this family of algorithms and their applications to centrality measurement.

A survey on the reference citation in the case reports published in The Journal of the Korean Radiological Society

International Nuclear Information System (INIS)

Lee, Hong Jae; Lee, Han Jin; Park, Seog Hee; Kim, Choon Yul; Bahk, Yong Whee; Shinn, Kyung Sub

1993-01-01

We analyzed 105 case reports published in The Journal of the Korean Radiological Society between 1975 and 1985. The objectives of this studies were to find out (1) whether those case reports were truly original or not as far as domestic publications were concerned and (2) whether their citations of domestic literatures were correct. In two papers, we found previous reports published already in the domestic journal in spite of the authors' claim as their 'first case reports'. In 105 case reports, only 94 references were cited while 151 omitted. It is concluded that a case report must include a statement to authentically clarify whether similar report had been previously published through meticulous review of published literatures. We also recommend to computerize the index of domestic literatures

An improved multi-domain convolution tracking algorithm

Science.gov (United States)

Sun, Xin; Wang, Haiying; Zeng, Yingsen

2018-04-01

Along with the wide application of the Deep Learning in the field of Computer vision, Deep learning has become a mainstream direction in the field of object tracking. The tracking algorithm in this paper is based on the improved multidomain convolution neural network, and the VOT video set is pre-trained on the network by multi-domain training strategy. In the process of online tracking, the network evaluates candidate targets sampled from vicinity of the prediction target in the previous with Gaussian distribution, and the candidate target with the highest score is recognized as the prediction target of this frame. The Bounding Box Regression model is introduced to make the prediction target closer to the ground-truths target box of the test set. Grouping-update strategy is involved to extract and select useful update samples in each frame, which can effectively prevent over fitting. And adapt to changes in both target and environment. To improve the speed of the algorithm while maintaining the performance, the number of candidate target succeed in adjusting dynamically with the help of Self-adaption parameter Strategy. Finally, the algorithm is tested by OTB set, compared with other high-performance tracking algorithms, and the plot of success rate and the accuracy are drawn. which illustrates outstanding performance of the tracking algorithm in this paper.

Perturbation of convex risk minimization and its application in differential private learning algorithms

Directory of Open Access Journals (Sweden)

Weilin Nie

2017-01-01

Full Text Available Abstract Convex risk minimization is a commonly used setting in learning theory. In this paper, we firstly give a perturbation analysis for such algorithms, and then we apply this result to differential private learning algorithms. Our analysis needs the objective functions to be strongly convex. This leads to an extension of our previous analysis to the non-differentiable loss functions, when constructing differential private algorithms. Finally, an error analysis is then provided to show the selection for the parameters.

Angle Statistics Reconstruction: a robust reconstruction algorithm for Muon Scattering Tomography

Science.gov (United States)

Stapleton, M.; Burns, J.; Quillin, S.; Steer, C.

2014-11-01

Muon Scattering Tomography (MST) is a technique for using the scattering of cosmic ray muons to probe the contents of enclosed volumes. As a muon passes through material it undergoes multiple Coulomb scattering, where the amount of scattering is dependent on the density and atomic number of the material as well as the path length. Hence, MST has been proposed as a means of imaging dense materials, for instance to detect special nuclear material in cargo containers. Algorithms are required to generate an accurate reconstruction of the material density inside the volume from the muon scattering information and some have already been proposed, most notably the Point of Closest Approach (PoCA) and Maximum Likelihood/Expectation Maximisation (MLEM) algorithms. However, whilst PoCA-based algorithms are easy to implement, they perform rather poorly in practice. Conversely, MLEM is a complicated algorithm to implement and computationally intensive and there is currently no published, fast and easily-implementable algorithm that performs well in practice. In this paper, we first provide a detailed analysis of the source of inaccuracy in PoCA-based algorithms. We then motivate an alternative method, based on ideas first laid out by Morris et al, presenting and fully specifying an algorithm that performs well against simulations of realistic scenarios. We argue this new algorithm should be adopted by developers of Muon Scattering Tomography as an alternative to PoCA.

FPGA Implementation of an Efficient Algorithm for the Calculation of Charged Particle Trajectories in Cosmic Ray Detectors

Science.gov (United States)

Villar, Xabier; Piso, Daniel; Bruguera, Javier D.

2014-02-01

This paper presents an FPGA implementation of an algorithm, previously published, for the the reconstruction of cosmic rays' trajectories and the determination of the time of arrival and velocity of the particles. The accuracy and precision issues of the algorithm have been analyzed to propose a suitable implementation. Thus, a 32-bit fixed-point format has been used for the representation of the data values. Moreover, the dependencies among the different operations have been taken into account to obtain a highly parallel and efficient hardware implementation. The final hardware architecture requires 18 cycles to process every particle, and has been exhaustively simulated to validate all the design decisions. The architecture has been mapped over different commercial FPGAs, with a frequency of operation ranging from 300 MHz to 1.3 GHz, depending on the FPGA being used. Consequently, the number of particle trajectories processed per second is between 16 million and 72 million. The high number of particle trajectories calculated per second shows that the proposed FPGA implementation might be used also in high rate environments such as those found in particle and nuclear physics experiments.

Selfish Gene Algorithm Vs Genetic Algorithm: A Review

Science.gov (United States)

Ariff, Norharyati Md; Khalid, Noor Elaiza Abdul; Hashim, Rathiah; Noor, Noorhayati Mohamed

2016-11-01

Evolutionary algorithm is one of the algorithms inspired by the nature. Within little more than a decade hundreds of papers have reported successful applications of EAs. In this paper, the Selfish Gene Algorithms (SFGA), as one of the latest evolutionary algorithms (EAs) inspired from the Selfish Gene Theory which is an interpretation of Darwinian Theory ideas from the biologist Richards Dawkins on 1989. In this paper, following a brief introduction to the Selfish Gene Algorithm (SFGA), the chronology of its evolution is presented. It is the purpose of this paper is to present an overview of the concepts of Selfish Gene Algorithm (SFGA) as well as its opportunities and challenges. Accordingly, the history, step involves in the algorithm are discussed and its different applications together with an analysis of these applications are evaluated.

Algorithms

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 ...

Analysis algorithm for digital data used in nuclear spectroscopy

CERN Document Server

AUTHOR|(CDS)2085950; Sin, Mihaela

Data obtained from digital acquisition systems used in nuclear spectroscopy experiments must be converted by a dedicated algorithm in or- der to extract the physical quantities of interest. I will report here the de- velopment of an algorithm capable to read digital data, discriminate between random and true signals and convert the results into a format readable by a special data analysis program package used to interpret nuclear spectra and to create coincident matrices. The algorithm can be used in any nuclear spectroscopy experimental setup provided that digital acquisition modules are involved. In particular it was used to treat data obtained from the IS441 experiment at ISOLDE where the beta decay of 80Zn was investigated as part of ultra-fast timing studies of neutron rich Zn nuclei. The results obtained for the half-lives of 80Zn and 80Ga were in very good agreement with previous measurements. This fact proved unquestionably that the conversion algorithm works. Another remarkable result was the improve...

Quantum Image Encryption Algorithm Based on Image Correlation Decomposition

Science.gov (United States)

Hua, Tianxiang; Chen, Jiamin; Pei, Dongju; Zhang, Wenquan; Zhou, Nanrun

2015-02-01

A novel quantum gray-level image encryption and decryption algorithm based on image correlation decomposition is proposed. The correlation among image pixels is established by utilizing the superposition and measurement principle of quantum states. And a whole quantum image is divided into a series of sub-images. These sub-images are stored into a complete binary tree array constructed previously and then randomly performed by one of the operations of quantum random-phase gate, quantum revolving gate and Hadamard transform. The encrypted image can be obtained by superimposing the resulting sub-images with the superposition principle of quantum states. For the encryption algorithm, the keys are the parameters of random phase gate, rotation angle, binary sequence and orthonormal basis states. The security and the computational complexity of the proposed algorithm are analyzed. The proposed encryption algorithm can resist brute force attack due to its very large key space and has lower computational complexity than its classical counterparts.

A Hybrid Backtracking Search Optimization Algorithm with Differential Evolution

Directory of Open Access Journals (Sweden)

Lijin Wang

2015-01-01

Full Text Available The backtracking search optimization algorithm (BSA is a new nature-inspired method which possesses a memory to take advantage of experiences gained from previous generation to guide the population to the global optimum. BSA is capable of solving multimodal problems, but it slowly converges and poorly exploits solution. The differential evolution (DE algorithm is a robust evolutionary algorithm and has a fast convergence speed in the case of exploitive mutation strategies that utilize the information of the best solution found so far. In this paper, we propose a hybrid backtracking search optimization algorithm with differential evolution, called HBD. In HBD, DE with exploitive strategy is used to accelerate the convergence by optimizing one worse individual according to its probability at each iteration process. A suit of 28 benchmark functions are employed to verify the performance of HBD, and the results show the improvement in effectiveness and efficiency of hybridization of BSA and DE.

Computationally Efficient DOA Tracking Algorithm in Monostatic MIMO Radar with Automatic Association

Directory of Open Access Journals (Sweden)

Huaxin Yu

2014-01-01

Full Text Available We consider the problem of tracking the direction of arrivals (DOA of multiple moving targets in monostatic multiple-input multiple-output (MIMO radar. A low-complexity DOA tracking algorithm in monostatic MIMO radar is proposed. The proposed algorithm obtains DOA estimation via the difference between previous and current covariance matrix of the reduced-dimension transformation signal, and it reduces the computational complexity and realizes automatic association in DOA tracking. Error analysis and Cramér-Rao lower bound (CRLB of DOA tracking are derived in the paper. The proposed algorithm not only can be regarded as an extension of array-signal-processing DOA tracking algorithm in (Zhang et al. (2008, but also is an improved version of the DOA tracking algorithm in (Zhang et al. (2008. Furthermore, the proposed algorithm has better DOA tracking performance than the DOA tracking algorithm in (Zhang et al. (2008. The simulation results demonstrate effectiveness of the proposed algorithm. Our work provides the technical support for the practical application of MIMO radar.

Pressure algorithm for elliptic flow calculations with the PDF method

Science.gov (United States)

Anand, M. S.; Pope, S. B.; Mongia, H. C.

1991-01-01

An algorithm to determine the mean pressure field for elliptic flow calculations with the probability density function (PDF) method is developed and applied. The PDF method is a most promising approach for the computation of turbulent reacting flows. Previous computations of elliptic flows with the method were in conjunction with conventional finite volume based calculations that provided the mean pressure field. The algorithm developed and described here permits the mean pressure field to be determined within the PDF calculations. The PDF method incorporating the pressure algorithm is applied to the flow past a backward-facing step. The results are in good agreement with data for the reattachment length, mean velocities, and turbulence quantities including triple correlations.

Algorithmic mathematics

CERN Document Server

Hougardy, Stefan

2016-01-01

Algorithms play an increasingly important role in nearly all fields of mathematics. This book allows readers to develop basic mathematical abilities, in particular those concerning the design and analysis of algorithms as well as their implementation. It presents not only fundamental algorithms like the sieve of Eratosthenes, the Euclidean algorithm, sorting algorithms, algorithms on graphs, and Gaussian elimination, but also discusses elementary data structures, basic graph theory, and numerical questions. In addition, it provides an introduction to programming and demonstrates in detail how to implement algorithms in C++. This textbook is suitable for students who are new to the subject and covers a basic mathematical lecture course, complementing traditional courses on analysis and linear algebra. Both authors have given this "Algorithmic Mathematics" course at the University of Bonn several times in recent years.

Desktop Publishing Made Simple.

Science.gov (United States)

Wentling, Rose Mary

1989-01-01

The author discusses the types of computer hardware and software necessary to set up a desktop publishing system, both for use in educational administration and for instructional purposes. Classroom applications of desktop publishing are presented. The author also provides guidelines for preparing to teach desktop publishing. (CH)

Desktop Publishing: A Brave New World and Publishing from the Desktop.

Science.gov (United States)

Lormand, Robert; Rowe, Jane J.

1988-01-01

The first of two articles presents basic selection criteria for desktop publishing software packages, including discussion of expectations, required equipment, training costs, publication size, desired software features, additional equipment needed, and quality control. The second provides a brief description of desktop publishing using the Apple…

Accuracy of algorithms to predict accessory pathway location in children with Wolff-Parkinson-White syndrome.

Science.gov (United States)

Wren, Christopher; Vogel, Melanie; Lord, Stephen; Abrams, Dominic; Bourke, John; Rees, Philip; Rosenthal, Eric

2012-02-01

The aim of this study was to examine the accuracy in predicting pathway location in children with Wolff-Parkinson-White syndrome for each of seven published algorithms. ECGs from 100 consecutive children with Wolff-Parkinson-White syndrome undergoing electrophysiological study were analysed by six investigators using seven published algorithms, six of which had been developed in adult patients. Accuracy and concordance of predictions were adjusted for the number of pathway locations. Accessory pathways were left-sided in 49, septal in 20 and right-sided in 31 children. Overall accuracy of prediction was 30-49% for the exact location and 61-68% including adjacent locations. Concordance between investigators varied between 41% and 86%. No algorithm was better at predicting septal pathways (accuracy 5-35%, improving to 40-78% including adjacent locations), but one was significantly worse. Predictive accuracy was 24-53% for the exact location of right-sided pathways (50-71% including adjacent locations) and 32-55% for the exact location of left-sided pathways (58-73% including adjacent locations). All algorithms were less accurate in our hands than in other authors' own assessment. None performed well in identifying midseptal or right anteroseptal accessory pathway locations.

Small sum privacy and large sum utility in data publishing.

Science.gov (United States)

Fu, Ada Wai-Chee; Wang, Ke; Wong, Raymond Chi-Wing; Wang, Jia; Jiang, Minhao

2014-08-01

While the study of privacy preserving data publishing has drawn a lot of interest, some recent work has shown that existing mechanisms do not limit all inferences about individuals. This paper is a positive note in response to this finding. We point out that not all inference attacks should be countered, in contrast to all existing works known to us, and based on this we propose a model called SPLU. This model protects sensitive information, by which we refer to answers for aggregate queries with small sums, while queries with large sums are answered with higher accuracy. Using SPLU, we introduce a sanitization algorithm to protect data while maintaining high data utility for queries with large sums. Empirical results show that our method behaves as desired. Copyright © 2014 Elsevier Inc. All rights reserved.

E-publishing and multimodalities

OpenAIRE

Yngve Nordkvelle

2008-01-01

In the literature of e-publishing there has been a consistent call from the advent of e-publishing on, until now, to explore new ways of expressing ideas through the new media. It has been claimed that the Internet opens an alley of possibilities and opportunites for publishing that will change the ways of publishing once and for all. In the area of publication of e-journals, however, the call for changes has received very modest responds.The thing is, it appears, that the conventional paper ...

Essential algorithms a practical approach to computer algorithms

CERN Document Server

Stephens, Rod

2013-01-01

A friendly and accessible introduction to the most useful algorithms Computer algorithms are the basic recipes for programming. Professional programmers need to know how to use algorithms to solve difficult programming problems. Written in simple, intuitive English, this book describes how and when to use the most practical classic algorithms, and even how to create new algorithms to meet future needs. The book also includes a collection of questions that can help readers prepare for a programming job interview. Reveals methods for manipulating common data structures s

Designing algorithm visualization on mobile platform: The proposed guidelines

Science.gov (United States)

Supli, A. A.; Shiratuddin, N.

2017-09-01

This paper entails an ongoing study about the design guidelines of algorithm visualization (AV) on mobile platform, helping students learning data structures and algorithm (DSA) subject effectively. Our previous review indicated that design guidelines of AV on mobile platform are still few. Mostly, previous guidelines of AV are developed for AV on desktop and website platform. In fact, mobile learning has been proved to enhance engagement in learning circumstances, and thus effect student's performance. In addition, the researchers highly recommend including UI design and Interactivity in designing effective AV system. However, the discussions of these two aspects in previous AV design guidelines are not comprehensive. The UI design in this paper describes the arrangement of AV features in mobile environment, whereas interactivity is about the active learning strategy features based on learning experiences (how to engage learners). Thus, this study main objective is to propose design guidelines of AV on mobile platform (AVOMP) that entails comprehensively UI design and interactivity aspects. These guidelines are developed through content analysis and comparative analysis from various related studies. These guidelines are useful for AV designers to help them constructing AVOMP for various topics on DSA.

A Taylor weak-statement algorithm for hyperbolic conservation laws

Science.gov (United States)

Baker, A. J.; Kim, J. W.

1987-01-01

Finite element analysis, applied to computational fluid dynamics (CFD) problem classes, presents a formal procedure for establishing the ingredients of a discrete approximation numerical solution algorithm. A classical Galerkin weak-statement formulation, formed on a Taylor series extension of the conservation law system, is developed herein that embeds a set of parameters eligible for constraint according to specification of suitable norms. The derived family of Taylor weak statements is shown to contain, as special cases, over one dozen independently derived CFD algorithms published over the past several decades for the high speed flow problem class. A theoretical analysis is completed that facilitates direct qualitative comparisons. Numerical results for definitive linear and nonlinear test problems permit direct quantitative performance comparisons.

Academic Nightmares: Predatory Publishing

Science.gov (United States)

Van Nuland, Sonya E.; Rogers, Kem A.

2017-01-01

Academic researchers who seek to publish their work are confronted daily with a barrage of e-mails from aggressive marketing campaigns that solicit them to publish their research with a specialized, often newly launched, journal. Known as predatory journals, they often promise high editorial and publishing standards, yet their exploitive business…

[Parathyroid cancer in a patient with previous history of hypernephroma: a clinical case].

Science.gov (United States)

Martín Navarro, J; Mendoza, E; Mateos, P; Cereceda, A; Coca, S

2007-01-01

We report the clinical case of a 55 year-old male patient, with a previous history of nephrectomy by hypernephroma sixteen years ago, first presenting hypercalcemia and rising of intact parathyroid hormone (iPTH) levels. A localization study revealed an intrathyroid nodule with cystic appearance. After undergoing a hemi-thyroidectomy, the patient is diagnosed with parathyroid carcinoma. This article analyzes previously published cases presenting parathyroidal pathologies associated with hypernephroma. A broader differential diagnosis--including the screening of parathyroidal pathologies should be considered in patients with hypercalcemia and hypernephroma.

Comparative analysis of instance selection algorithms for instance-based classifiers in the context of medical decision support

International Nuclear Information System (INIS)

Mazurowski, Maciej A; Tourassi, Georgia D; Malof, Jordan M

2011-01-01

When constructing a pattern classifier, it is important to make best use of the instances (a.k.a. cases, examples, patterns or prototypes) available for its development. In this paper we present an extensive comparative analysis of algorithms that, given a pool of previously acquired instances, attempt to select those that will be the most effective to construct an instance-based classifier in terms of classification performance, time efficiency and storage requirements. We evaluate seven previously proposed instance selection algorithms and compare their performance to simple random selection of instances. We perform the evaluation using k-nearest neighbor classifier and three classification problems: one with simulated Gaussian data and two based on clinical databases for breast cancer detection and diagnosis, respectively. Finally, we evaluate the impact of the number of instances available for selection on the performance of the selection algorithms and conduct initial analysis of the selected instances. The experiments show that for all investigated classification problems, it was possible to reduce the size of the original development dataset to less than 3% of its initial size while maintaining or improving the classification performance. Random mutation hill climbing emerges as the superior selection algorithm. Furthermore, we show that some previously proposed algorithms perform worse than random selection. Regarding the impact of the number of instances available for the classifier development on the performance of the selection algorithms, we confirm that the selection algorithms are generally more effective as the pool of available instances increases. In conclusion, instance selection is generally beneficial for instance-based classifiers as it can improve their performance, reduce their storage requirements and improve their response time. However, choosing the right selection algorithm is crucial.

Algorithmic cryptanalysis

CERN Document Server

Joux, Antoine

2009-01-01

Illustrating the power of algorithms, Algorithmic Cryptanalysis describes algorithmic methods with cryptographically relevant examples. Focusing on both private- and public-key cryptographic algorithms, it presents each algorithm either as a textual description, in pseudo-code, or in a C code program.Divided into three parts, the book begins with a short introduction to cryptography and a background chapter on elementary number theory and algebra. It then moves on to algorithms, with each chapter in this section dedicated to a single topic and often illustrated with simple cryptographic applic

An item-oriented recommendation algorithm on cold-start problem

Science.gov (United States)

Qiu, Tian; Chen, Guang; Zhang, Zi-Ke; Zhou, Tao

2011-09-01

Based on a hybrid algorithm incorporating the heat conduction and probability spreading processes (Proc. Natl. Acad. Sci. U.S.A., 107 (2010) 4511), in this letter, we propose an improved method by introducing an item-oriented function, focusing on solving the dilemma of the recommendation accuracy between the cold and popular items. Differently from previous works, the present algorithm does not require any additional information (e.g., tags). Further experimental results obtained in three real datasets, RYM, Netflix and MovieLens, show that, compared with the original hybrid method, the proposed algorithm significantly enhances the recommendation accuracy of the cold items, while it keeps the recommendation accuracy of the overall and the popular items. This work might shed some light on both understanding and designing effective methods for long-tailed online applications of recommender systems.

Digital signal processing algorithms for nuclear particle spectroscopy

International Nuclear Information System (INIS)

Zejnalova, O.; Zejnalov, Sh.; Hambsch, F.J.; Oberstedt, S.

2007-01-01

Digital signal processing algorithms for nuclear particle spectroscopy are described along with a digital pile-up elimination method applicable to equidistantly sampled detector signals pre-processed by a charge-sensitive preamplifier. The signal processing algorithms are provided as recursive one- or multi-step procedures which can be easily programmed using modern computer programming languages. The influence of the number of bits of the sampling analogue-to-digital converter on the final signal-to-noise ratio of the spectrometer is considered. Algorithms for a digital shaping-filter amplifier, for a digital pile-up elimination scheme and for ballistic deficit correction were investigated using a high purity germanium detector. The pile-up elimination method was originally developed for fission fragment spectroscopy using a Frisch-grid back-to-back double ionization chamber and was mainly intended for pile-up elimination in case of high alpha-radioactivity of the fissile target. The developed pile-up elimination method affects only the electronic noise generated by the preamplifier. Therefore the influence of the pile-up elimination scheme on the final resolution of the spectrometer is investigated in terms of the distance between pile-up pulses. The efficiency of the developed algorithms is compared with other signal processing schemes published in literature

Preresidency publication record and its association with publishing during paediatric residency.

Science.gov (United States)

Gupta, Ronish; Norris, Mark Lorne; Writer, Hilary

2016-05-01

To determine whether an association exists between the publication of journal articles before and during paediatrics residency. A retrospective search of PubMed was conducted for publications by all 567 Canadian paediatricians certified between 2009 and 2012, inclusive. Paediatricians were separated into groups based on the number of articles published preresidency (0 or ≥1) and during residency (0 or ≥1). The methodology was validated using a group of local paediatricians who were contacted to verify whether their publications were identified accurately. A total of 160 of 567 (28%) certified paediatricians had preresidency publications; of these, 93 (58%) subsequently published during their residency period. Among the remaining 407 (72%) paediatricians without preresidency publications, 129 (32%) published during residency. The association between publication before and during paediatric residency was statistically significant (OR 2.98 [95% CI 2.04 to 4.36]; Ppublication status with 87% and 90% accuracy, respectively. Individuals with previous publications were more likely to publish as residents; however, 42% of individuals with pre-residency publications did not publish as residents. Residency selection committees may find these data helpful in assessing the publication potential of their applicants. In addition, this information may assist in building more targeted and individualized research curricula within residency programs.

Validation of deformable image registration algorithms on CT images of ex vivo porcine bladders with fiducial markers

Energy Technology Data Exchange (ETDEWEB)

Wognum, S., E-mail: s.wognum@gmail.com; Heethuis, S. E.; Bel, A. [Department of Radiation Oncology, Academic Medical Center, Meibergdreef 9, 1105 AZ Amsterdam (Netherlands); Rosario, T. [Department of Radiation Oncology, VU University Medical Center, De Boelelaan 1117, 1081 HZ Amsterdam (Netherlands); Hoogeman, M. S. [Department of Radiation Oncology, Erasmus MC Cancer Institute, Erasmus Medical Center, Groene Hilledijk 301, 3075 EA Rotterdam (Netherlands)

2014-07-15

Purpose: The spatial accuracy of deformable image registration (DIR) is important in the implementation of image guided adaptive radiotherapy techniques for cancer in the pelvic region. Validation of algorithms is best performed on phantoms with fiducial markers undergoing controlled large deformations. Excised porcine bladders, exhibiting similar filling and voiding behavior as human bladders, provide such an environment. The aim of this study was to determine the spatial accuracy of different DIR algorithms on CT images ofex vivo porcine bladders with radiopaque fiducial markers applied to the outer surface, for a range of bladder volumes, using various accuracy metrics. Methods: Five excised porcine bladders with a grid of 30–40 radiopaque fiducial markers attached to the outer wall were suspended inside a water-filled phantom. The bladder was filled with a controlled amount of water with added contrast medium for a range of filling volumes (100–400 ml in steps of 50 ml) using a luer lock syringe, and CT scans were acquired at each filling volume. DIR was performed for each data set, with the 100 ml bladder as the reference image. Six intensity-based algorithms (optical flow or demons-based) implemented in theMATLAB platform DIRART, a b-spline algorithm implemented in the commercial software package VelocityAI, and a structure-based algorithm (Symmetric Thin Plate Spline Robust Point Matching) were validated, using adequate parameter settings according to values previously published. The resulting deformation vector field from each registration was applied to the contoured bladder structures and to the marker coordinates for spatial error calculation. The quality of the algorithms was assessed by comparing the different error metrics across the different algorithms, and by comparing the effect of deformation magnitude (bladder volume difference) per algorithm, using the Independent Samples Kruskal-Wallis test. Results: The authors found good structure

Validation of deformable image registration algorithms on CT images of ex vivo porcine bladders with fiducial markers.

Science.gov (United States)

Wognum, S; Heethuis, S E; Rosario, T; Hoogeman, M S; Bel, A

2014-07-01

The spatial accuracy of deformable image registration (DIR) is important in the implementation of image guided adaptive radiotherapy techniques for cancer in the pelvic region. Validation of algorithms is best performed on phantoms with fiducial markers undergoing controlled large deformations. Excised porcine bladders, exhibiting similar filling and voiding behavior as human bladders, provide such an environment. The aim of this study was to determine the spatial accuracy of different DIR algorithms on CT images of ex vivo porcine bladders with radiopaque fiducial markers applied to the outer surface, for a range of bladder volumes, using various accuracy metrics. Five excised porcine bladders with a grid of 30-40 radiopaque fiducial markers attached to the outer wall were suspended inside a water-filled phantom. The bladder was filled with a controlled amount of water with added contrast medium for a range of filling volumes (100-400 ml in steps of 50 ml) using a luer lock syringe, and CT scans were acquired at each filling volume. DIR was performed for each data set, with the 100 ml bladder as the reference image. Six intensity-based algorithms (optical flow or demons-based) implemented in theMATLAB platform DIRART, a b-spline algorithm implemented in the commercial software package VelocityAI, and a structure-based algorithm (Symmetric Thin Plate Spline Robust Point Matching) were validated, using adequate parameter settings according to values previously published. The resulting deformation vector field from each registration was applied to the contoured bladder structures and to the marker coordinates for spatial error calculation. The quality of the algorithms was assessed by comparing the different error metrics across the different algorithms, and by comparing the effect of deformation magnitude (bladder volume difference) per algorithm, using the Independent Samples Kruskal-Wallis test. The authors found good structure accuracy without dependency on

Validation of deformable image registration algorithms on CT images of ex vivo porcine bladders with fiducial markers

International Nuclear Information System (INIS)

Wognum, S.; Heethuis, S. E.; Bel, A.; Rosario, T.; Hoogeman, M. S.

2014-01-01

Purpose: The spatial accuracy of deformable image registration (DIR) is important in the implementation of image guided adaptive radiotherapy techniques for cancer in the pelvic region. Validation of algorithms is best performed on phantoms with fiducial markers undergoing controlled large deformations. Excised porcine bladders, exhibiting similar filling and voiding behavior as human bladders, provide such an environment. The aim of this study was to determine the spatial accuracy of different DIR algorithms on CT images ofex vivo porcine bladders with radiopaque fiducial markers applied to the outer surface, for a range of bladder volumes, using various accuracy metrics. Methods: Five excised porcine bladders with a grid of 30–40 radiopaque fiducial markers attached to the outer wall were suspended inside a water-filled phantom. The bladder was filled with a controlled amount of water with added contrast medium for a range of filling volumes (100–400 ml in steps of 50 ml) using a luer lock syringe, and CT scans were acquired at each filling volume. DIR was performed for each data set, with the 100 ml bladder as the reference image. Six intensity-based algorithms (optical flow or demons-based) implemented in theMATLAB platform DIRART, a b-spline algorithm implemented in the commercial software package VelocityAI, and a structure-based algorithm (Symmetric Thin Plate Spline Robust Point Matching) were validated, using adequate parameter settings according to values previously published. The resulting deformation vector field from each registration was applied to the contoured bladder structures and to the marker coordinates for spatial error calculation. The quality of the algorithms was assessed by comparing the different error metrics across the different algorithms, and by comparing the effect of deformation magnitude (bladder volume difference) per algorithm, using the Independent Samples Kruskal-Wallis test. Results: The authors found good structure

Measuring Disorientation Based on the Needleman-Wunsch Algorithm

Science.gov (United States)

Güyer, Tolga; Atasoy, Bilal; Somyürek, Sibel

2015-01-01

This study offers a new method to measure navigation disorientation in web based systems which is powerful learning medium for distance and open education. The Needleman-Wunsch algorithm is used to measure disorientation in a more precise manner. The process combines theoretical and applied knowledge from two previously distinct research areas,…

Warfarin Dosing Algorithms Underpredict Dose Requirements in Patients Requiring ≥7 mg Daily: A Systematic Review and Meta-analysis.

Science.gov (United States)

Saffian, S M; Duffull, S B; Wright, Dfb

2017-08-01

There is preliminary evidence to suggest that some published warfarin dosing algorithms produce biased maintenance dose predictions in patients who require higher than average doses. We conducted a meta-analysis of warfarin dosing algorithms to determine if there exists a systematic under- or overprediction of dose requirements for patients requiring ≥7 mg/day across published algorithms. Medline and Embase databases were searched up to September 2015. We quantified the proportion of over- and underpredicted doses in patients whose observed maintenance dose was ≥7 mg/day. The meta-analysis included 47 evaluations of 22 different warfarin dosing algorithms from 16 studies. The meta-analysis included data from 1,492 patients who required warfarin doses of ≥7 mg/day. All 22 algorithms were found to underpredict warfarin dosing requirements in patients who required ≥7 mg/day by an average of 2.3 mg/day with a pooled estimate of underpredicted doses of 92.3% (95% confidence interval 90.3-94.1, I 2 = 24%). © 2017 American Society for Clinical Pharmacology and Therapeutics.

Publishing: The Creative Business.

Science.gov (United States)

Bohne, Harald; Van Ierssel, Harry

This book offers guidelines to emerging and would-be publishers, whether they plan to enter publishing as a career, a sideline, or a diversion. It stresses the business aspects of publishing and emphasizes the major housekeeping functions encountered in the business, except methods of sales and distribution. Contents include "The Mechanics of…

Gene selection heuristic algorithm for nutrigenomics studies.

Science.gov (United States)

Valour, D; Hue, I; Grimard, B; Valour, B

2013-07-15

Large datasets from -omics studies need to be deeply investigated. The aim of this paper is to provide a new method (LEM method) for the search of transcriptome and metabolome connections. The heuristic algorithm here described extends the classical canonical correlation analysis (CCA) to a high number of variables (without regularization) and combines well-conditioning and fast-computing in "R." Reduced CCA models are summarized in PageRank matrices, the product of which gives a stochastic matrix that resumes the self-avoiding walk covered by the algorithm. Then, a homogeneous Markov process applied to this stochastic matrix converges the probabilities of interconnection between genes, providing a selection of disjointed subsets of genes. This is an alternative to regularized generalized CCA for the determination of blocks within the structure matrix. Each gene subset is thus linked to the whole metabolic or clinical dataset that represents the biological phenotype of interest. Moreover, this selection process reaches the aim of biologists who often need small sets of genes for further validation or extended phenotyping. The algorithm is shown to work efficiently on three published datasets, resulting in meaningfully broadened gene networks.

Persistent seropositivity for yellow fever in a previously vaccinated autologous hematopoietic stem cell transplantation recipient.

Science.gov (United States)

Hayakawa, Kayoko; Takasaki, Tomohiko; Tsunemine, Hiroko; Kanagawa, Shuzo; Kutsuna, Satoshi; Takeshita, Nozomi; Mawatari, Momoko; Fujiya, Yoshihiro; Yamamoto, Kei; Ohmagari, Norio; Kato, Yasuyuki

2015-08-01

The duration of a protective level of yellow fever antibodies after autologous hematopoietic stem cell transplantation in a previously vaccinated person is unclear. The case of a patient who had previously been vaccinated for yellow fever and who remained seropositive for 22 months after autologous peripheral blood stem cell transplantation for malignant lymphoma is described herein. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Creep force modelling for rail traction vehicles based on the Fastsim algorithm

Science.gov (United States)

Spiryagin, Maksym; Polach, Oldrich; Cole, Colin

2013-11-01

The evaluation of creep forces is a complex task and their calculation is a time-consuming process for multibody simulation (MBS). A methodology of creep forces modelling at large traction creepages has been proposed by Polach [Creep forces in simulations of traction vehicles running on adhesion limit. Wear. 2005;258:992-1000; Influence of locomotive tractive effort on the forces between wheel and rail. Veh Syst Dyn. 2001(Suppl);35:7-22] adapting his previously published algorithm [Polach O. A fast wheel-rail forces calculation computer code. Veh Syst Dyn. 1999(Suppl);33:728-739]. The most common method for creep force modelling used by software packages for MBS of running dynamics is the Fastsim algorithm by Kalker [A fast algorithm for the simplified theory of rolling contact. Veh Syst Dyn. 1982;11:1-13]. However, the Fastsim code has some limitations which do not allow modelling the creep force - creep characteristic in agreement with measurements for locomotives and other high-power traction vehicles, mainly for large traction creep at low-adhesion conditions. This paper describes a newly developed methodology based on a variable contact flexibility increasing with the ratio of the slip area to the area of adhesion. This variable contact flexibility is introduced in a modification of Kalker's code Fastsim by replacing the constant Kalker's reduction factor, widely used in MBS, by a variable reduction factor together with a slip-velocity-dependent friction coefficient decreasing with increasing global creepage. The proposed methodology is presented in this work and compared with measurements for different locomotives. The modification allows use of the well recognised Fastsim code for simulation of creep forces at large creepages in agreement with measurements without modifying the proven modelling methodology at small creepages.

Denni Algorithm An Enhanced Of SMS (Scan, Move and Sort) Algorithm

Science.gov (United States)

Aprilsyah Lubis, Denni; Salim Sitompul, Opim; Marwan; Tulus; Andri Budiman, M.

2017-12-01

Sorting has been a profound area for the algorithmic researchers, and many resources are invested to suggest a more working sorting algorithm. For this purpose many existing sorting algorithms were observed in terms of the efficiency of the algorithmic complexity. Efficient sorting is important to optimize the use of other algorithms that require sorted lists to work correctly. Sorting has been considered as a fundamental problem in the study of algorithms that due to many reasons namely, the necessary to sort information is inherent in many applications, algorithms often use sorting as a key subroutine, in algorithm design there are many essential techniques represented in the body of sorting algorithms, and many engineering issues come to the fore when implementing sorting algorithms., Many algorithms are very well known for sorting the unordered lists, and one of the well-known algorithms that make the process of sorting to be more economical and efficient is SMS (Scan, Move and Sort) algorithm, an enhancement of Quicksort invented Rami Mansi in 2010. This paper presents a new sorting algorithm called Denni-algorithm. The Denni algorithm is considered as an enhancement on the SMS algorithm in average, and worst cases. The Denni algorithm is compared with the SMS algorithm and the results were promising.

A Parallel Particle Swarm Optimization Algorithm Accelerated by Asynchronous Evaluations

Science.gov (United States)

Venter, Gerhard; Sobieszczanski-Sobieski, Jaroslaw

2005-01-01

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

The algorithms for calculating synthetic seismograms from a dipole source using the derivatives of Green's function

Science.gov (United States)

Pavlov, V. M.

2017-07-01

The problem of calculating complete synthetic seismograms from a point dipole with an arbitrary seismic moment tensor in a plane parallel medium composed of homogeneous elastic isotropic layers is considered. It is established that the solutions of the system of ordinary differential equations for the motion-stress vector have a reciprocity property, which allows obtaining a compact formula for the derivative of the motion vector with respect to the source depth. The reciprocity theorem for Green's functions with respect to the interchange of the source and receiver is obtained for a medium with cylindrical boundary. The differentiation of Green's functions with respect to the coordinates of the source leads to the same calculation formulas as the algorithm developed in the previous work (Pavlov, 2013). A new algorithm appears when the derivatives with respect to the horizontal coordinates of the source is replaced by the derivatives with respect to the horizontal coordinates of the receiver (with the minus sign). This algorithm is more transparent, compact, and economic than the previous one. It requires calculating the wavenumbers associated with Bessel function's roots of order 0 and order 1, whereas the previous algorithm additionally requires the second order roots.

A comparison of an algorithm for automated sequential beam orientation selection (Cycle) with simulated annealing

International Nuclear Information System (INIS)

Woudstra, Evert; Heijmen, Ben J M; Storchi, Pascal R M

2008-01-01

Some time ago we developed and published a new deterministic algorithm (called Cycle) for automatic selection of beam orientations in radiotherapy. This algorithm is a plan generation process aiming at the prescribed PTV dose within hard dose and dose-volume constraints. The algorithm allows a large number of input orientations to be used and selects only the most efficient orientations, surviving the selection process. Efficiency is determined by a score function and is more or less equal to the extent of uninhibited access to the PTV for a specific beam during the selection process. In this paper we compare the capabilities of fast-simulated annealing (FSA) and Cycle for cases where local optima are supposed to be present. Five pancreas and five oesophagus cases previously treated in our institute were selected for this comparison. Plans were generated for FSA and Cycle, using the same hard dose and dose-volume constraints, and the largest possible achieved PTV doses as obtained from these algorithms were compared. The largest achieved PTV dose values were generally very similar for the two algorithms. In some cases FSA resulted in a slightly higher PTV dose than Cycle, at the cost of switching on substantially more beam orientations than Cycle. In other cases, when Cycle generated the solution with the highest PTV dose using only a limited number of non-zero weight beams, FSA seemed to have some difficulty in switching off the unfavourable directions. Cycle was faster than FSA, especially for large-dimensional feasible spaces. In conclusion, for the cases studied in this paper, we have found that despite the inherent drawback of sequential search as used by Cycle (where Cycle could probably get trapped in a local optimum), Cycle is nevertheless able to find comparable or sometimes slightly better treatment plans in comparison with FSA (which in theory finds the global optimum) especially in large-dimensional beam weight spaces

A Linearized Relaxing Algorithm for the Specific Nonlinear Optimization Problem

Directory of Open Access Journals (Sweden)

Mio Horai

2016-01-01

Full Text Available We propose a new method for the specific nonlinear and nonconvex global optimization problem by using a linear relaxation technique. To simplify the specific nonlinear and nonconvex optimization problem, we transform the problem to the lower linear relaxation form, and we solve the linear relaxation optimization problem by the Branch and Bound Algorithm. Under some reasonable assumptions, the global convergence of the algorithm is certified for the problem. Numerical results show that this method is more efficient than the previous methods.

A backtracking algorithm for the stream AND-parallel execution of logic programs

Energy Technology Data Exchange (ETDEWEB)

Somogyi, Z.; Ramamohanarao, K.; Vaghani, J. (Univ. of Melbourne, Parkville (Australia))

1988-06-01

The authors present the first backtracking algorithm for stream AND-parallel logic programs. It relies on compile-time knowledge of the data flow graph of each clause to let it figure out efficiently which goals to kill or restart when a goal fails. This crucial information, which they derive from mode declarations, was not available at compile-time in any previous stream AND-parallel system. They show that modes can increase the precision of the backtracking algorithm, though their algorithm allows this precision to be traded off against overhead on a procedure-by-procedure and call-by-call basis. The modes also allow their algorithm to handle efficiently programs that manipulate partially instantiated data structures and an important class of programs with circular dependency graphs. On code that does not need backtracking, the efficiency of their algorithm approaches that of the committed-choice languages; on code that does need backtracking its overhead is comparable to that of the independent AND-parallel backtracking algorithms.

Python algorithms mastering basic algorithms in the Python language

CERN Document Server

Hetland, Magnus Lie

2014-01-01

Python Algorithms, Second Edition explains the Python approach to algorithm analysis and design. Written by Magnus Lie Hetland, author of Beginning Python, this book is sharply focused on classical algorithms, but it also gives a solid understanding of fundamental algorithmic problem-solving techniques. The book deals with some of the most important and challenging areas of programming and computer science in a highly readable manner. It covers both algorithmic theory and programming practice, demonstrating how theory is reflected in real Python programs. Well-known algorithms and data struc

Why should we publish Linked Data?

Science.gov (United States)

Blower, Jon; Riechert, Maik; Koubarakis, Manolis; Pace, Nino

2016-04-01

We use the Web every day to access information from all kinds of different sources. But the complexity and diversity of scientific data mean that discovering accessing and interpreting data remains a large challenge to researchers, decision-makers and other users. Different sources of useful information on data, algorithms, instruments and publications are scattered around the Web. How can we link all these things together to help users to better understand and exploit earth science data? How can we combine scientific data with other relevant data sources, when standards for describing and sharing data vary so widely between communities? "Linked Data" is a term that describes a set of standards and "best practices" for sharing data on the Web (http://www.w3.org/standards/semanticweb/data). These principles can be summarised as follows: 1. Create unique and persistent identifiers for the important "things" in a community (e.g. datasets, publications, algorithms, instruments). 2. Allow users to "look up" these identifiers on the web to find out more information about them. 3. Make this information machine-readable in a community-neutral format (such as RDF, Resource Description Framework). 4. Within this information, embed links to other things and concepts and say how these are related. 5. Optionally, provide web service interfaces to allow the user to perform sophisticated queries over this information (using a language such as SPARQL). The promise of Linked Data is that, through these techniques, data will be more discoverable, more comprehensible and more usable by different communities, not just the community that produced the data. As a result, many data providers (particularly public-sector institutions) are now publishing data in this way. However, this area is still in its infancy in terms of real-world applications. Data users need guidance and tools to help them use Linked Data. Data providers need reassurance that the investments they are making in

A Robust Formant Extraction Algorithm Combining Spectral Peak Picking and Root Polishing

Directory of Open Access Journals (Sweden)

Seo Kwang-deok

2006-01-01

Full Text Available We propose a robust formant extraction algorithm that combines the spectral peak picking, formants location examining for peak merger checking, and the root extraction methods. The spectral peak picking method is employed to locate the formant candidates, and the root extraction is used for solving the peak merger problem. The location and the distance between the extracted formants are also utilized to efficiently find out suspected peak mergers. The proposed algorithm does not require much computation, and is shown to be superior to previous formant extraction algorithms through extensive tests using TIMIT speech database.

Use of Genetic Algorithms for Contrast and Entropy Optimization in ISAR Autofocusing

Directory of Open Access Journals (Sweden)

Martorella Marco

2006-01-01

Full Text Available Image contrast maximization and entropy minimization are two commonly used techniques for ISAR image autofocusing. When the signal phase history due to the target radial motion has to be approximated with high order polynomial models, classic optimization techniques fail when attempting to either maximize the image contrast or minimize the image entropy. In this paper a solution of this problem is proposed by using genetic algorithms. The performances of the new algorithms that make use of genetic algorithms overcome the problem with previous implementations based on deterministic approaches. Tests on real data of airplanes and ships confirm the insight.

An Algorithm for Timely Transmission of Solicitation Messages in RPL for Energy-Efficient Node Mobility.

Science.gov (United States)

Park, Jihong; Kim, Ki-Hyung; Kim, Kangseok

2017-04-19

The IPv6 Routing Protocol for Low Power and Lossy Networks (RPL) was proposed for various applications of IPv6 low power wireless networks. While RPL supports various routing metrics and is designed to be suitable for wireless sensor network environments, it does not consider the mobility of nodes. Therefore, there is a need for a method that is energy efficient and that provides stable and reliable data transmission by considering the mobility of nodes in RPL networks. This paper proposes an algorithm to support node mobility in RPL in an energy-efficient manner and describes its operating principle based on different scenarios. The proposed algorithm supports the mobility of nodes by dynamically adjusting the transmission interval of the messages that request the route based on the speed and direction of the motion of mobile nodes, as well as the costs between neighboring nodes. The performance of the proposed algorithm and previous algorithms for supporting node mobility were examined experimentally. From the experiment, it was observed that the proposed algorithm requires fewer messages per unit time for selecting a new parent node following the movement of a mobile node. Since fewer messages are used to select a parent node, the energy consumption is also less than that of previous algorithms.

A simulation study comparing aberration detection algorithms for syndromic surveillance

Directory of Open Access Journals (Sweden)

Painter Ian

2007-03-01

Full Text Available Abstract Background The usefulness of syndromic surveillance for early outbreak detection depends in part on effective statistical aberration detection. However, few published studies have compared different detection algorithms on identical data. In the largest simulation study conducted to date, we compared the performance of six aberration detection algorithms on simulated outbreaks superimposed on authentic syndromic surveillance data. Methods We compared three control-chart-based statistics, two exponential weighted moving averages, and a generalized linear model. We simulated 310 unique outbreak signals, and added these to actual daily counts of four syndromes monitored by Public Health – Seattle and King County's syndromic surveillance system. We compared the sensitivity of the six algorithms at detecting these simulated outbreaks at a fixed alert rate of 0.01. Results Stratified by baseline or by outbreak distribution, duration, or size, the generalized linear model was more sensitive than the other algorithms and detected 54% (95% CI = 52%–56% of the simulated epidemics when run at an alert rate of 0.01. However, all of the algorithms had poor sensitivity, particularly for outbreaks that did not begin with a surge of cases. Conclusion When tested on county-level data aggregated across age groups, these algorithms often did not perform well in detecting signals other than large, rapid increases in case counts relative to baseline levels.

Clinical algorithms to aid osteoarthritis guideline dissemination

DEFF Research Database (Denmark)

Meneses, S. R. F.; Goode, A. P.; Nelson, A. E

2016-01-01

Background: Numerous scientific organisations have developed evidence-based recommendations aiming to optimise the management of osteoarthritis (OA). Uptake, however, has been suboptimal. The purpose of this exercise was to harmonize the recent recommendations and develop a user-friendly treatment...... algorithm to facilitate translation of evidence into practice. Methods: We updated a previous systematic review on clinical practice guidelines (CPGs) for OA management. The guidelines were assessed using the Appraisal of Guidelines for Research and Evaluation for quality and the standards for developing...... to facilitate the implementation of guidelines in clinical practice are necessary. The algorithms proposed are examples of how to apply recommendations in the clinical context, helping the clinician to visualise the patient flow and timing of different treatment modalities. (C) 2016 Osteoarthritis Research...

Parameter optimization of differential evolution algorithm for automatic playlist generation problem

Science.gov (United States)

Alamag, Kaye Melina Natividad B.; Addawe, Joel M.

2017-11-01

With the digitalization of music, the number of collection of music increased largely and there is a need to create lists of music that filter the collection according to user preferences, thus giving rise to the Automatic Playlist Generation Problem (APGP). Previous attempts to solve this problem include the use of search and optimization algorithms. If a music database is very large, the algorithm to be used must be able to search the lists thoroughly taking into account the quality of the playlist given a set of user constraints. In this paper we perform an evolutionary meta-heuristic optimization algorithm, Differential Evolution (DE) using different combination of parameter values and select the best performing set when used to solve four standard test functions. Performance of the proposed algorithm is then compared with normal Genetic Algorithm (GA) and a hybrid GA with Tabu Search. Numerical simulations are carried out to show better results from Differential Evolution approach with the optimized parameter values.

A Data Forward Stepwise Fitting Algorithm Based on Orthogonal Function System

Directory of Open Access Journals (Sweden)

Li Han-Ju

2017-01-01

Full Text Available Data fitting is the main method of functional data analysis, and it is widely used in the fields of economy, social science, engineering technology and so on. Least square method is the main method of data fitting, but the least square method is not convergent, no memory property, big fitting error and it is easy to over fitting. Based on the orthogonal trigonometric function system, this paper presents a data forward stepwise fitting algorithm. This algorithm takes forward stepwise fitting strategy, each time using the nearest base function to fit the residual error generated by the previous base function fitting, which makes the residual mean square error minimum. In this paper, we theoretically prove the convergence, the memory property and the fitting error diminishing character for the algorithm. Experimental results show that the proposed algorithm is effective, and the fitting performance is better than that of the least square method and the forward stepwise fitting algorithm based on the non-orthogonal function system.

Radionuclide identification algorithm for organic scintillator-based radiation portal monitor

Energy Technology Data Exchange (ETDEWEB)

Paff, Marc Gerrit, E-mail: mpaff@umich.edu; Di Fulvio, Angela; Clarke, Shaun D.; Pozzi, Sara A.

2017-03-21

We have developed an algorithm for on-the-fly radionuclide identification for radiation portal monitors using organic scintillation detectors. The algorithm was demonstrated on experimental data acquired with our pedestrian portal monitor on moving special nuclear material and industrial sources at a purpose-built radiation portal monitor testing facility. The experimental data also included common medical isotopes. The algorithm takes the power spectral density of the cumulative distribution function of the measured pulse height distributions and matches these to reference spectra using a spectral angle mapper. F-score analysis showed that the new algorithm exhibited significant performance improvements over previously implemented radionuclide identification algorithms for organic scintillators. Reliable on-the-fly radionuclide identification would help portal monitor operators more effectively screen out the hundreds of thousands of nuisance alarms they encounter annually due to recent nuclear-medicine patients and cargo containing naturally occurring radioactive material. Portal monitor operators could instead focus on the rare but potentially high impact incidents of nuclear and radiological material smuggling detection for which portal monitors are intended.

Radionuclide identification algorithm for organic scintillator-based radiation portal monitor

Science.gov (United States)

Paff, Marc Gerrit; Di Fulvio, Angela; Clarke, Shaun D.; Pozzi, Sara A.

2017-03-01

We have developed an algorithm for on-the-fly radionuclide identification for radiation portal monitors using organic scintillation detectors. The algorithm was demonstrated on experimental data acquired with our pedestrian portal monitor on moving special nuclear material and industrial sources at a purpose-built radiation portal monitor testing facility. The experimental data also included common medical isotopes. The algorithm takes the power spectral density of the cumulative distribution function of the measured pulse height distributions and matches these to reference spectra using a spectral angle mapper. F-score analysis showed that the new algorithm exhibited significant performance improvements over previously implemented radionuclide identification algorithms for organic scintillators. Reliable on-the-fly radionuclide identification would help portal monitor operators more effectively screen out the hundreds of thousands of nuisance alarms they encounter annually due to recent nuclear-medicine patients and cargo containing naturally occurring radioactive material. Portal monitor operators could instead focus on the rare but potentially high impact incidents of nuclear and radiological material smuggling detection for which portal monitors are intended.

Atrial Fibrillation Screening in Nonmetropolitan Areas Using a Telehealth Surveillance System With an Embedded Cloud-Computing Algorithm: Prospective Pilot Study.

Science.gov (United States)

Chen, Ying-Hsien; Hung, Chi-Sheng; Huang, Ching-Chang; Hung, Yu-Chien; Hwang, Juey-Jen; Ho, Yi-Lwun

2017-09-26

Atrial fibrillation (AF) is a common form of arrhythmia that is associated with increased risk of stroke and mortality. Detecting AF before the first complication occurs is a recognized priority. No previous studies have examined the feasibility of undertaking AF screening using a telehealth surveillance system with an embedded cloud-computing algorithm; we address this issue in this study. The objective of this study was to evaluate the feasibility of AF screening in nonmetropolitan areas using a telehealth surveillance system with an embedded cloud-computing algorithm. We conducted a prospective AF screening study in a nonmetropolitan area using a single-lead electrocardiogram (ECG) recorder. All ECG measurements were reviewed on the telehealth surveillance system and interpreted by the cloud-computing algorithm and a cardiologist. The process of AF screening was evaluated with a satisfaction questionnaire. Between March 11, 2016 and August 31, 2016, 967 ECGs were recorded from 922 residents in nonmetropolitan areas. A total of 22 (2.4%, 22/922) residents with AF were identified by the physician's ECG interpretation, and only 0.2% (2/967) of ECGs contained significant artifacts. The novel cloud-computing algorithm for AF detection had a sensitivity of 95.5% (95% CI 77.2%-99.9%) and specificity of 97.7% (95% CI 96.5%-98.5%). The overall satisfaction score for the process of AF screening was 92.1%. AF screening in nonmetropolitan areas using a telehealth surveillance system with an embedded cloud-computing algorithm is feasible. ©Ying-Hsien Chen, Chi-Sheng Hung, Ching-Chang Huang, Yu-Chien Hung, Juey-Jen Hwang, Yi-Lwun Ho. Originally published in JMIR Mhealth and Uhealth (http://mhealth.jmir.org), 26.09.2017.

Optimisation in radiotherapy II: Programmed and inversion optimisation algorithms

International Nuclear Information System (INIS)

Ebert, M.

1997-01-01

This is the second article in a three part examination of optimisation in radiotherapy. The previous article established the bases of optimisation in radiotherapy, and the formulation of the optimisation problem. This paper outlines several algorithms that have been used in radiotherapy, for searching for the best irradiation strategy within the full set of possible strategies. Two principle classes of algorithm are considered - those associated with mathematical programming which employ specific search techniques, linear programming type searches or artificial intelligence - and those which seek to perform a numerical inversion of the optimisation problem, finishing with deterministic iterative inversion. (author)

Noise propagation in iterative reconstruction algorithms with line searches

International Nuclear Information System (INIS)

Qi, Jinyi

2003-01-01

In this paper we analyze the propagation of noise in iterative image reconstruction algorithms. We derive theoretical expressions for the general form of preconditioned gradient algorithms with line searches. The results are applicable to a wide range of iterative reconstruction problems, such as emission tomography, transmission tomography, and image restoration. A unique contribution of this paper comparing to our previous work [1] is that the line search is explicitly modeled and we do not use the approximation that the gradient of the objective function is zero. As a result, the error in the estimate of noise at early iterations is significantly reduced

A highly efficient multi-core algorithm for clustering extremely large datasets

Directory of Open Access Journals (Sweden)

Kraus Johann M

2010-04-01

Full Text Available Abstract Background In recent years, the demand for computational power in computational biology has increased due to rapidly growing data sets from microarray and other high-throughput technologies. This demand is likely to increase. Standard algorithms for analyzing data, such as cluster algorithms, need to be parallelized for fast processing. Unfortunately, most approaches for parallelizing algorithms largely rely on network communication protocols connecting and requiring multiple computers. One answer to this problem is to utilize the intrinsic capabilities in current multi-core hardware to distribute the tasks among the different cores of one computer. Results We introduce a multi-core parallelization of the k-means and k-modes cluster algorithms based on the design principles of transactional memory for clustering gene expression microarray type data and categorial SNP data. Our new shared memory parallel algorithms show to be highly efficient. We demonstrate their computational power and show their utility in cluster stability and sensitivity analysis employing repeated runs with slightly changed parameters. Computation speed of our Java based algorithm was increased by a factor of 10 for large data sets while preserving computational accuracy compared to single-core implementations and a recently published network based parallelization. Conclusions Most desktop computers and even notebooks provide at least dual-core processors. Our multi-core algorithms show that using modern algorithmic concepts, parallelization makes it possible to perform even such laborious tasks as cluster sensitivity and cluster number estimation on the laboratory computer.

A homotopy algorithm for digital optimal projection control GASD-HADOC

Science.gov (United States)

Collins, Emmanuel G., Jr.; Richter, Stephen; Davis, Lawrence D.

1993-01-01

The linear-quadratic-gaussian (LQG) compensator was developed to facilitate the design of control laws for multi-input, multi-output (MIMO) systems. The compensator is computed by solving two algebraic equations for which standard closed-loop solutions exist. Unfortunately, the minimal dimension of an LQG compensator is almost always equal to the dimension of the plant and can thus often violate practical implementation constraints on controller order. This deficiency is especially highlighted when considering control-design for high-order systems such as flexible space structures. This deficiency motivated the development of techniques that enable the design of optimal controllers whose dimension is less than that of the design plant. A homotopy approach based on the optimal projection equations that characterize the necessary conditions for optimal reduced-order control. Homotopy algorithms have global convergence properties and hence do not require that the initializing reduced-order controller be close to the optimal reduced-order controller to guarantee convergence. However, the homotopy algorithm previously developed for solving the optimal projection equations has sublinear convergence properties and the convergence slows at higher authority levels and may fail. A new homotopy algorithm for synthesizing optimal reduced-order controllers for discrete-time systems is described. Unlike the previous homotopy approach, the new algorithm is a gradient-based, parameter optimization formulation and was implemented in MATLAB. The results reported may offer the foundation for a reliable approach to optimal, reduced-order controller design.

Noninteractive Verifiable Outsourcing Algorithm for Bilinear Pairing with Improved Checkability

Directory of Open Access Journals (Sweden)

Yanli Ren

2017-01-01

Full Text Available It is well known that the computation of bilinear pairing is the most expensive operation in pairing-based cryptography. In this paper, we propose a noninteractive verifiable outsourcing algorithm of bilinear pairing based on two servers in the one-malicious model. The outsourcer need not execute any expensive operation, such as scalar multiplication and modular exponentiation. Moreover, the outsourcer could detect any failure with a probability close to 1 if one of the servers misbehaves. Therefore, the proposed algorithm improves checkability and decreases communication cost compared with the previous ones. Finally, we utilize the proposed algorithm as a subroutine to achieve an anonymous identity-based encryption (AIBE scheme with outsourced decryption and an identity-based signature (IBS scheme with outsourced verification.

Hybrid Cryptosystem Using Tiny Encryption Algorithm and LUC Algorithm

Science.gov (United States)

Rachmawati, Dian; Sharif, Amer; Jaysilen; Andri Budiman, Mohammad

2018-01-01

Security becomes a very important issue in data transmission and there are so many methods to make files more secure. One of that method is cryptography. Cryptography is a method to secure file by writing the hidden code to cover the original file. Therefore, if the people do not involve in cryptography, they cannot decrypt the hidden code to read the original file. There are many methods are used in cryptography, one of that method is hybrid cryptosystem. A hybrid cryptosystem is a method that uses a symmetric algorithm to secure the file and use an asymmetric algorithm to secure the symmetric algorithm key. In this research, TEA algorithm is used as symmetric algorithm and LUC algorithm is used as an asymmetric algorithm. The system is tested by encrypting and decrypting the file by using TEA algorithm and using LUC algorithm to encrypt and decrypt the TEA key. The result of this research is by using TEA Algorithm to encrypt the file, the cipher text form is the character from ASCII (American Standard for Information Interchange) table in the form of hexadecimal numbers and the cipher text size increase by sixteen bytes as the plaintext length is increased by eight characters.

Efficient sequential and parallel algorithms for planted motif search.

Science.gov (United States)

Nicolae, Marius; Rajasekaran, Sanguthevar

2014-01-31

Motif searching is an important step in the detection of rare events occurring in a set of DNA or protein sequences. One formulation of the problem is known as (l,d)-motif search or Planted Motif Search (PMS). In PMS we are given two integers l and d and n biological sequences. We want to find all sequences of length l that appear in each of the input sequences with at most d mismatches. The PMS problem is NP-complete. PMS algorithms are typically evaluated on certain instances considered challenging. Despite ample research in the area, a considerable performance gap exists because many state of the art algorithms have large runtimes even for moderately challenging instances. This paper presents a fast exact parallel PMS algorithm called PMS8. PMS8 is the first algorithm to solve the challenging (l,d) instances (25,10) and (26,11). PMS8 is also efficient on instances with larger l and d such as (50,21). We include a comparison of PMS8 with several state of the art algorithms on multiple problem instances. This paper also presents necessary and sufficient conditions for 3 l-mers to have a common d-neighbor. The program is freely available at http://engr.uconn.edu/~man09004/PMS8/. We present PMS8, an efficient exact algorithm for Planted Motif Search. PMS8 introduces novel ideas for generating common neighborhoods. We have also implemented a parallel version for this algorithm. PMS8 can solve instances not solved by any previous algorithms.

Publishing studies: what else?

Directory of Open Access Journals (Sweden)

Bertrand Legendre

2015-07-01

Full Text Available This paper intends to reposition “publishing studies” in the long process that goes from the beginning of book history to the current research on cultural industries. It raises questions about interdisciplinarity and the possibility of considering publishing independently of other sectors of the media and cultural offerings. Publishing is now included in a large range of industries and, at the same time, analyses tend to become more and more segmented according to production sectors and scientific fields. In addition to the problems created, from the professional point of view, by this double movement, this one requires a questioning of the concept of “publishing studies”.

A new column-generation-based algorithm for VMAT treatment plan optimization

International Nuclear Information System (INIS)

Peng Fei; Epelman, Marina A; Romeijn, H Edwin; Jia Xun; Gu Xuejun; Jiang, Steve B

2012-01-01

We study the treatment plan optimization problem for volumetric modulated arc therapy (VMAT). We propose a new column-generation-based algorithm that takes into account bounds on the gantry speed and dose rate, as well as an upper bound on the rate of change of the gantry speed, in addition to MLC constraints. The algorithm iteratively adds one aperture at each control point along the treatment arc. In each iteration, a restricted problem optimizing intensities at previously selected apertures is solved, and its solution is used to formulate a pricing problem, which selects an aperture at another control point that is compatible with previously selected apertures and leads to the largest rate of improvement in the objective function value of the restricted problem. Once a complete set of apertures is obtained, their intensities are optimized and the gantry speeds and dose rates are adjusted to minimize treatment time while satisfying all machine restrictions. Comparisons of treatment plans obtained by our algorithm to idealized IMRT plans of 177 beams on five clinical prostate cancer cases demonstrate high quality with respect to clinical dose–volume criteria. For all cases, our algorithm yields treatment plans that can be delivered in around 2 min. Implementation on a graphic processing unit enables us to finish the optimization of a VMAT plan in 25–55 s. (paper)

A new automated assign and analysing method for high-resolution rotationally resolved spectra using genetic algorithms

NARCIS (Netherlands)

Meerts, W.L.; Schmitt, M.

2006-01-01

This paper describes a numerical technique that has recently been developed to automatically assign and fit high-resolution spectra. The method makes use of genetic algorithms (GA). The current algorithm is compared with previously used analysing methods. The general features of the GA and its

A new fast algorithm for solving the minimum spanning tree problem based on DNA molecules computation.

Science.gov (United States)

Wang, Zhaocai; Huang, Dongmei; Meng, Huajun; Tang, Chengpei

2013-10-01

The minimum spanning tree (MST) problem is to find minimum edge connected subsets containing all the vertex of a given undirected graph. It is a vitally important NP-complete problem in graph theory and applied mathematics, having numerous real life applications. Moreover in previous studies, DNA molecular operations usually were used to solve NP-complete head-to-tail path search problems, rarely for NP-hard problems with multi-lateral path solutions result, such as the minimum spanning tree problem. In this paper, we present a new fast DNA algorithm for solving the MST problem using DNA molecular operations. For an undirected graph with n vertex and m edges, we reasonably design flexible length DNA strands representing the vertex and edges, take appropriate steps and get the solutions of the MST problem in proper length range and O(3m+n) time complexity. We extend the application of DNA molecular operations and simultaneity simplify the complexity of the computation. Results of computer simulative experiments show that the proposed method updates some of the best known values with very short time and that the proposed method provides a better performance with solution accuracy over existing algorithms. Copyright © 2013 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

An Automated Algorithm for Identifying and Tracking Transverse Waves in Solar Images

Science.gov (United States)

Weberg, Micah J.; Morton, Richard J.; McLaughlin, James A.

2018-01-01

Recent instrumentation has demonstrated that the solar atmosphere supports omnipresent transverse waves, which could play a key role in energizing the solar corona. Large-scale studies are required in order to build up an understanding of the general properties of these transverse waves. To help facilitate this, we present an automated algorithm for identifying and tracking features in solar images and extracting the wave properties of any observed transverse oscillations. We test and calibrate our algorithm using a set of synthetic data, which includes noise and rotational effects. The results indicate an accuracy of 1%–2% for displacement amplitudes and 4%–10% for wave periods and velocity amplitudes. We also apply the algorithm to data from the Atmospheric Imaging Assembly on board the Solar Dynamics Observatory and find good agreement with previous studies. Of note, we find that 35%–41% of the observed plumes exhibit multiple wave signatures, which indicates either the superposition of waves or multiple independent wave packets observed at different times within a single structure. The automated methods described in this paper represent a significant improvement on the speed and quality of direct measurements of transverse waves within the solar atmosphere. This algorithm unlocks a wide range of statistical studies that were previously impractical.

I/O-Efficient Algorithms for Problems on Grid-Based Terrains

DEFF Research Database (Denmark)

Arge, Lars Allan; Toma, Laura; Vitter, Jeffrey Scott

2001-01-01

The potential and use of Geographic Information Systems is rapidly increasing due to the increasing availability of massive amounts of geospatial data from projects like NASA's Mission to Planet Earth. However, the use of these massive datasets also exposes scalability problems with existing GIS...... hydrologic attributes of a terrain. We present the results of an extensive set of experiments on real-life terrain datasets of different sizes and characteristics. Our experiments show that while our new algorithm scales nicely with dataset size, the previously known algorithm "breaks down" once the size...

Sound algorithms

OpenAIRE

De Götzen , Amalia; Mion , Luca; Tache , Olivier

2007-01-01

International audience; We call sound algorithms the categories of algorithms that deal with digital sound signal. Sound algorithms appeared in the very infancy of computer. Sound algorithms present strong specificities that are the consequence of two dual considerations: the properties of the digital sound signal itself and its uses, and the properties of auditory perception.

GraDit: graph-based data repair algorithm for multiple data edits rule violations

Science.gov (United States)

Ode Zuhayeni Madjida, Wa; Gusti Bagus Baskara Nugraha, I.

2018-03-01

Constraint-based data cleaning captures data violation to a set of rule called data quality rules. The rules consist of integrity constraint and data edits. Structurally, they are similar, where the rule contain left hand side and right hand side. Previous research proposed a data repair algorithm for integrity constraint violation. The algorithm uses undirected hypergraph as rule violation representation. Nevertheless, this algorithm can not be applied for data edits because of different rule characteristics. This study proposed GraDit, a repair algorithm for data edits rule. First, we use bipartite-directed hypergraph as model representation of overall defined rules. These representation is used for getting interaction between violation rules and clean rules. On the other hand, we proposed undirected graph as violation representation. Our experimental study showed that algorithm with undirected graph as violation representation model gave better data quality than algorithm with undirected hypergraph as representation model.

Parallel CFD Algorithms for Aerodynamical Flow Solvers on Unstructured Meshes. Parts 1 and 2

Science.gov (United States)

Barth, Timothy J.; Kwak, Dochan (Technical Monitor)

1995-01-01

The Advisory Group for Aerospace Research and Development (AGARD) has requested my participation in the lecture series entitled Parallel Computing in Computational Fluid Dynamics to be held at the von Karman Institute in Brussels, Belgium on May 15-19, 1995. In addition, a request has been made from the US Coordinator for AGARD at the Pentagon for NASA Ames to hold a repetition of the lecture series on October 16-20, 1995. I have been asked to be a local coordinator for the Ames event. All AGARD lecture series events have attendance limited to NATO allied countries. A brief of the lecture series is provided in the attached enclosure. Specifically, I have been asked to give two lectures of approximately 75 minutes each on the subject of parallel solution techniques for the fluid flow equations on unstructured meshes. The title of my lectures is "Parallel CFD Algorithms for Aerodynamical Flow Solvers on Unstructured Meshes" (Parts I-II). The contents of these lectures will be largely review in nature and will draw upon previously published work in this area. Topics of my lectures will include: (1) Mesh partitioning algorithms. Recursive techniques based on coordinate bisection, Cuthill-McKee level structures, and spectral bisection. (2) Newton's method for large scale CFD problems. Size and complexity estimates for Newton's method, modifications for insuring global convergence. (3) Techniques for constructing the Jacobian matrix. Analytic and numerical techniques for Jacobian matrix-vector products, constructing the transposed matrix, extensions to optimization and homotopy theories. (4) Iterative solution algorithms. Practical experience with GIVIRES and BICG-STAB matrix solvers. (5) Parallel matrix preconditioning. Incomplete Lower-Upper (ILU) factorization, domain-decomposed ILU, approximate Schur complement strategies.

Numerical algorithms for intragranular diffusional fission gas release incorporated in the Transuranus code

International Nuclear Information System (INIS)

Lassmann, K.

2002-01-01

Complicated physical processes govern diffusional fission gas release in nuclear fuels. In addition to the physical problem there exists a numerical problem, as some solutions of the underlying diffusion equation contain numerical errors that by far exceed the physical details. In this paper the two algorithms incorporated in the TRANSURANUS code, the URGAS and the new FORMAS algorithm are compared. The previously reported deficiency of the most elegant and mathematically sound FORMAS algorithm at low release could be overcome. Both algorithms are simple, fast, without numerical problems, insensitive to time step lengths and well balanced over the entire range of fission gas release. They can be made available on request as FORTRAN subroutines. (author)

Large-scale sequential quadratic programming algorithms

Energy Technology Data Exchange (ETDEWEB)

Eldersveld, S.K.

1992-09-01

The problem addressed is the general nonlinear programming problem: finding a local minimizer for a nonlinear function subject to a mixture of nonlinear equality and inequality constraints. The methods studied are in the class of sequential quadratic programming (SQP) algorithms, which have previously proved successful for problems of moderate size. Our goal is to devise an SQP algorithm that is applicable to large-scale optimization problems, using sparse data structures and storing less curvature information but maintaining the property of superlinear convergence. The main features are: 1. The use of a quasi-Newton approximation to the reduced Hessian of the Lagrangian function. Only an estimate of the reduced Hessian matrix is required by our algorithm. The impact of not having available the full Hessian approximation is studied and alternative estimates are constructed. 2. The use of a transformation matrix Q. This allows the QP gradient to be computed easily when only the reduced Hessian approximation is maintained. 3. The use of a reduced-gradient form of the basis for the null space of the working set. This choice of basis is more practical than an orthogonal null-space basis for large-scale problems. The continuity condition for this choice is proven. 4. The use of incomplete solutions of quadratic programming subproblems. Certain iterates generated by an active-set method for the QP subproblem are used in place of the QP minimizer to define the search direction for the nonlinear problem. An implementation of the new algorithm has been obtained by modifying the code MINOS. Results and comparisons with MINOS and NPSOL are given for the new algorithm on a set of 92 test problems.

RCQ-GA: RDF Chain Query Optimization Using Genetic Algorithms

Science.gov (United States)

Hogenboom, Alexander; Milea, Viorel; Frasincar, Flavius; Kaymak, Uzay

The application of Semantic Web technologies in an Electronic Commerce environment implies a need for good support tools. Fast query engines are needed for efficient querying of large amounts of data, usually represented using RDF. We focus on optimizing a special class of SPARQL queries, the so-called RDF chain queries. For this purpose, we devise a genetic algorithm called RCQ-GA that determines the order in which joins need to be performed for an efficient evaluation of RDF chain queries. The approach is benchmarked against a two-phase optimization algorithm, previously proposed in literature. The more complex a query is, the more RCQ-GA outperforms the benchmark in solution quality, execution time needed, and consistency of solution quality. When the algorithms are constrained by a time limit, the overall performance of RCQ-GA compared to the benchmark further improves.

Differential Evolution Algorithm with Self-Adaptive Population Resizing Mechanism

Directory of Open Access Journals (Sweden)

Xu Wang

2013-01-01

Full Text Available A differential evolution (DE algorithm with self-adaptive population resizing mechanism, SapsDE, is proposed to enhance the performance of DE by dynamically choosing one of two mutation strategies and tuning control parameters in a self-adaptive manner. More specifically, more appropriate mutation strategies along with its parameter settings can be determined adaptively according to the previous status at different stages of the evolution process. To verify the performance of SapsDE, 17 benchmark functions with a wide range of dimensions, and diverse complexities are used. Nonparametric statistical procedures were performed for multiple comparisons between the proposed algorithm and five well-known DE variants from the literature. Simulation results show that SapsDE is effective and efficient. It also exhibits much more superiorresultsthan the other five algorithms employed in the comparison in most of the cases.

Publishers and repositories

CERN Multimedia

CERN. Geneva

2007-01-01

The impact of self-archiving on journals and publishers is an important topic for all those involved in scholarly communication. There is some evidence that the physics arXiv has had no impact on physics journals, while 'economic common sense' suggests that some impact is inevitable. I shall review recent studies of librarian attitudes towards repositories and journals, and place this in the context of IOP Publishing's experiences with arXiv. I shall offer some possible reasons for the mis-match between these perspectives and then discuss how IOP has linked with arXiv and experimented with OA publishing. As well as launching OA journals we have co-operated with Cornell and the arXiv on Eprintweb.org, a platform that offers new features to repository users. View Andrew Wray's biography

A new cut-based algorithm for the multi-state flow network reliability problem

International Nuclear Information System (INIS)

Yeh, Wei-Chang; Bae, Changseok; Huang, Chia-Ling

2015-01-01

Many real-world systems can be modeled as multi-state network systems in which reliability can be derived in terms of the lower bound points of level d, called d-minimal cuts (d-MCs). This study proposes a new method to find and verify obtained d-MCs with simple and useful found properties for the multi-state flow network reliability problem. The proposed algorithm runs in O(mσp) time, which represents a significant improvement over the previous O(mp 2 σ) time bound based on max-flow/min-cut, where p, σ and m denote the number of MCs, d-MC candidates and edges, respectively. The proposed algorithm also conquers the weakness of some existing methods, which failed to remove duplicate d-MCs in special cases. A step-by-step example is given to demonstrate how the proposed algorithm locates and verifies all d-MC candidates. As evidence of the utility of the proposed approach, we present extensive computational results on 20 benchmark networks in another example. The computational results compare favorably with a previously developed algorithm in the literature. - Highlights: • A new method is proposed to find all d-MCs for the multi-state flow networks. • The proposed method can prevent the generation of d-MC duplicates. • The proposed method is simpler and more efficient than the best-known algorithms

Previously unknown species of Aspergillus.

Science.gov (United States)

Gautier, M; Normand, A-C; Ranque, S

2016-08-01

The use of multi-locus DNA sequence analysis has led to the description of previously unknown 'cryptic' Aspergillus species, whereas classical morphology-based identification of Aspergillus remains limited to the section or species-complex level. The current literature highlights two main features concerning these 'cryptic' Aspergillus species. First, the prevalence of such species in clinical samples is relatively high compared with emergent filamentous fungal taxa such as Mucorales, Scedosporium or Fusarium. Second, it is clearly important to identify these species in the clinical laboratory because of the high frequency of antifungal drug-resistant isolates of such Aspergillus species. Matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS) has recently been shown to enable the identification of filamentous fungi with an accuracy similar to that of DNA sequence-based methods. As MALDI-TOF MS is well suited to the routine clinical laboratory workflow, it facilitates the identification of these 'cryptic' Aspergillus species at the routine mycology bench. The rapid establishment of enhanced filamentous fungi identification facilities will lead to a better understanding of the epidemiology and clinical importance of these emerging Aspergillus species. Based on routine MALDI-TOF MS-based identification results, we provide original insights into the key interpretation issues of a positive Aspergillus culture from a clinical sample. Which ubiquitous species that are frequently isolated from air samples are rarely involved in human invasive disease? Can both the species and the type of biological sample indicate Aspergillus carriage, colonization or infection in a patient? Highly accurate routine filamentous fungi identification is central to enhance the understanding of these previously unknown Aspergillus species, with a vital impact on further improved patient care. Copyright © 2016 European Society of Clinical Microbiology and

Does previous use affect litter box appeal in multi-cat households?

Science.gov (United States)

Ellis, J J; McGowan, R T S; Martin, F

2017-08-01

It is commonly assumed that cats actively avoid eliminated materials (especially in multi-cat homes), suggesting regular litter box cleaning as the best defense against out-of-box elimination. The relationship between previous use and litter box appeal to familiar subsequent users is currently unknown. The purpose of this study was to investigate the relationship between previous litter box use and the identity of the previous user, type of elimination, odor, and presence of physical/visual obstructions in a multi-cat household scenario. Cats preferred a clean litter box to a dirty one, but the identity of the previous user had no impact on preferences. While the presence of odor from urine and/or feces did not impact litter box preferences, the presence of odorless faux-urine and/or feces did - with the presence of faux-feces being preferred over faux-urine. Results suggest neither malodor nor chemical communication play a role in litter box preferences, and instead emphasize the importance of regular removal of physical/visual obstructions as the key factor in promoting proper litter box use. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Automatic generation control of multi-area power systems with diverse energy sources using Teaching Learning Based Optimization algorithm

Directory of Open Access Journals (Sweden)

Rabindra Kumar Sahu

2016-03-01

Full Text Available This paper presents the design and analysis of Proportional-Integral-Double Derivative (PIDD controller for Automatic Generation Control (AGC of multi-area power systems with diverse energy sources using Teaching Learning Based Optimization (TLBO algorithm. At first, a two-area reheat thermal power system with appropriate Generation Rate Constraint (GRC is considered. The design problem is formulated as an optimization problem and TLBO is employed to optimize the parameters of the PIDD controller. The superiority of the proposed TLBO based PIDD controller has been demonstrated by comparing the results with recently published optimization technique such as hybrid Firefly Algorithm and Pattern Search (hFA-PS, Firefly Algorithm (FA, Bacteria Foraging Optimization Algorithm (BFOA, Genetic Algorithm (GA and conventional Ziegler Nichols (ZN for the same interconnected power system. Also, the proposed approach has been extended to two-area power system with diverse sources of generation like thermal, hydro, wind and diesel units. The system model includes boiler dynamics, GRC and Governor Dead Band (GDB non-linearity. It is observed from simulation results that the performance of the proposed approach provides better dynamic responses by comparing the results with recently published in the literature. Further, the study is extended to a three unequal-area thermal power system with different controllers in each area and the results are compared with published FA optimized PID controller for the same system under study. Finally, sensitivity analysis is performed by varying the system parameters and operating load conditions in the range of ±25% from their nominal values to test the robustness.

Performance of genetic algorithms in search for water splitting perovskites

DEFF Research Database (Denmark)

Jain, A.; Castelli, Ivano Eligio; Hautier, G.

2013-01-01

We examine the performance of genetic algorithms (GAs) in uncovering solar water light splitters over a space of almost 19,000 perovskite materials. The entire search space was previously calculated using density functional theory to determine solutions that fulfill constraints on stability, band...

A Robust Parallel Algorithm for Combinatorial Compressed Sensing

Science.gov (United States)

Mendoza-Smith, Rodrigo; Tanner, Jared W.; Wechsung, Florian

2018-04-01

In previous work two of the authors have shown that a vector $x \\in \\mathbb{R}^n$ with at most $k Parallel-$\\ell_0$ decoding algorithm, where $\\mathrm{nnz}(A)$ denotes the number of nonzero entries in $A \\in \\mathbb{R}^{m \\times n}$. In this paper we present the Robust-$\\ell_0$ decoding algorithm, which robustifies Parallel-$\\ell_0$ when the sketch $Ax$ is corrupted by additive noise. This robustness is achieved by approximating the asymptotic posterior distribution of values in the sketch given its corrupted measurements. We provide analytic expressions that approximate these posteriors under the assumptions that the nonzero entries in the signal and the noise are drawn from continuous distributions. Numerical experiments presented show that Robust-$\\ell_0$ is superior to existing greedy and combinatorial compressed sensing algorithms in the presence of small to moderate signal-to-noise ratios in the setting of Gaussian signals and Gaussian additive noise.

GTI: a novel algorithm for identifying outlier gene expression profiles from integrated microarray datasets.

Directory of Open Access Journals (Sweden)

John Patrick Mpindi

Full Text Available BACKGROUND: Meta-analysis of gene expression microarray datasets presents significant challenges for statistical analysis. We developed and validated a new bioinformatic method for the identification of genes upregulated in subsets of samples of a given tumour type ('outlier genes', a hallmark of potential oncogenes. METHODOLOGY: A new statistical method (the gene tissue index, GTI was developed by modifying and adapting algorithms originally developed for statistical problems in economics. We compared the potential of the GTI to detect outlier genes in meta-datasets with four previously defined statistical methods, COPA, the OS statistic, the t-test and ORT, using simulated data. We demonstrated that the GTI performed equally well to existing methods in a single study simulation. Next, we evaluated the performance of the GTI in the analysis of combined Affymetrix gene expression data from several published studies covering 392 normal samples of tissue from the central nervous system, 74 astrocytomas, and 353 glioblastomas. According to the results, the GTI was better able than most of the previous methods to identify known oncogenic outlier genes. In addition, the GTI identified 29 novel outlier genes in glioblastomas, including TYMS and CDKN2A. The over-expression of these genes was validated in vivo by immunohistochemical staining data from clinical glioblastoma samples. Immunohistochemical data were available for 65% (19 of 29 of these genes, and 17 of these 19 genes (90% showed a typical outlier staining pattern. Furthermore, raltitrexed, a specific inhibitor of TYMS used in the therapy of tumour types other than glioblastoma, also effectively blocked cell proliferation in glioblastoma cell lines, thus highlighting this outlier gene candidate as a potential therapeutic target. CONCLUSIONS/SIGNIFICANCE: Taken together, these results support the GTI as a novel approach to identify potential oncogene outliers and drug targets. The algorithm is

An Adaptive Tradeoff Algorithm for Multi-issue SLA Negotiation

Science.gov (United States)

Son, Seokho; Sim, Kwang Mong

Since participants in a Cloud may be independent bodies, mechanisms are necessary for resolving different preferences in leasing Cloud services. Whereas there are currently mechanisms that support service-level agreement negotiation, there is little or no negotiation support for concurrent price and timeslot for Cloud service reservations. For the concurrent price and timeslot negotiation, a tradeoff algorithm to generate and evaluate a proposal which consists of price and timeslot proposal is necessary. The contribution of this work is thus to design an adaptive tradeoff algorithm for multi-issue negotiation mechanism. The tradeoff algorithm referred to as "adaptive burst mode" is especially designed to increase negotiation speed and total utility and to reduce computational load by adaptively generating concurrent set of proposals. The empirical results obtained from simulations carried out using a testbed suggest that due to the concurrent price and timeslot negotiation mechanism with adaptive tradeoff algorithm: 1) both agents achieve the best performance in terms of negotiation speed and utility; 2) the number of evaluations of each proposal is comparatively lower than previous scheme (burst-N).

Performance evaluation of the EM algorithm applied to radiographic images

International Nuclear Information System (INIS)

Brailean, J.C.; Giger, M.L.; Chen, C.T.; Sullivan, B.J.

1990-01-01

In this paper the authors evaluate the expectation maximization (EM) algorithm, both qualitatively and quantitatively, as a technique for enhancing radiographic images. Previous studies have qualitatively shown the usefulness of the EM algorithm but have failed to quantify and compare its performance with those of other image processing techniques. Recent studies by Loo et al, Ishida et al, and Giger et al, have explained improvements in image quality quantitatively in terms of a signal-to-noise ratio (SNR) derived from signal detection theory. In this study, we take a similar approach in quantifying the effect of the EM algorithm on detection of simulated low-contrast square objects superimposed on radiographic mottle. The SNRs of the original and processed images are calculated taking into account both the human visual system response and the screen-film transfer function as well as a noise component internal to the eye-brain system. The EM algorithm was also implemented on digital screen-film images of test patterns and clinical mammograms

Final Technical Report: Sparse Grid Scenario Generation and Interior Algorithms for Stochastic Optimization in a Parallel Computing Environment

Energy Technology Data Exchange (ETDEWEB)

Mehrotra, Sanjay [Northwestern Univ., Evanston, IL (United States)

2016-09-07

The support from this grant resulted in seven published papers and a technical report. Two papers are published in SIAM J. on Optimization [87, 88]; two papers are published in IEEE Transactions on Power Systems [77, 78]; one paper is published in Smart Grid [79]; one paper is published in Computational Optimization and Applications [44] and one in INFORMS J. on Computing [67]). The works in [44, 67, 87, 88] were funded primarily by this DOE grant. The applied papers in [77, 78, 79] were also supported through a subcontract from the Argonne National Lab. We start by presenting our main research results on the scenario generation problem in Sections 1–2. We present our algorithmic results on interior point methods for convex optimization problems in Section 3. We describe a new ‘central’ cutting surface algorithm developed for solving large scale convex programming problems (as is the case with our proposed research) with semi-infinite number of constraints in Section 4. In Sections 5–6 we present our work on two application problems of interest to DOE.

Algorithms for contrast enhancement of electronic portal images

International Nuclear Information System (INIS)

Díez, S.; Sánchez, S.

2015-01-01

An implementation of two new automatized image processing algorithms for contrast enhancement of portal images is presented as suitable tools which facilitate the setup verification and visualization of patients during radiotherapy treatments. In the first algorithm, called Automatic Segmentation and Histogram Stretching (ASHS), the portal image is automatically segmented in two sub-images delimited by the conformed treatment beam: one image consisting of the imaged patient obtained directly from the radiation treatment field, and the second one is composed of the imaged patient outside it. By segmenting the original image, a histogram stretching can be independently performed and improved in both regions. The second algorithm involves a two-step process. In the first step, a Normalization to Local Mean (NLM), an inverse restoration filter is applied by dividing pixel by pixel a portal image by its blurred version. In the second step, named Lineally Combined Local Histogram Equalization (LCLHE), the contrast of the original image is strongly improved by a Local Contrast Enhancement (LCE) algorithm, revealing the anatomical structures of patients. The output image is lineally combined with a portal image of the patient. Finally the output images of the previous algorithms (NLM and LCLHE) are lineally combined, once again, in order to obtain a contrast enhanced image. These two algorithms have been tested on several portal images with great results. - Highlights: • Two Algorithms are implemented to improve the contrast of Electronic Portal Images. • The multi-leaf and conformed beam are automatically segmented into Portal Images. • Hidden anatomical and bony structures in portal images are revealed. • The task related to the patient setup verification is facilitated by the contrast enhancement then achieved.

Common integration sites of published datasets identified using a graph-based framework

Directory of Open Access Journals (Sweden)

Alessandro Vasciaveo

2016-01-01

Full Text Available With next-generation sequencing, the genomic data available for the characterization of integration sites (IS has dramatically increased. At present, in a single experiment, several thousand viral integration genome targets can be investigated to define genomic hot spots. In a previous article, we renovated a formal CIS analysis based on a rigid fixed window demarcation into a more stretchy definition grounded on graphs. Here, we present a selection of supporting data related to the graph-based framework (GBF from our previous article, in which a collection of common integration sites (CIS was identified on six published datasets. In this work, we will focus on two datasets, ISRTCGD and ISHIV, which have been previously discussed. Moreover, we show in more detail the workflow design that originates the datasets.

Books average previous decade of economic misery.

Science.gov (United States)

Bentley, R Alexander; Acerbi, Alberto; Ormerod, Paul; Lampos, Vasileios

2014-01-01

For the 20(th) century since the Depression, we find a strong correlation between a 'literary misery index' derived from English language books and a moving average of the previous decade of the annual U.S. economic misery index, which is the sum of inflation and unemployment rates. We find a peak in the goodness of fit at 11 years for the moving average. The fit between the two misery indices holds when using different techniques to measure the literary misery index, and this fit is significantly better than other possible correlations with different emotion indices. To check the robustness of the results, we also analysed books written in German language and obtained very similar correlations with the German economic misery index. The results suggest that millions of books published every year average the authors' shared economic experiences over the past decade.

Human activity recognition based on feature selection in smart home using back-propagation algorithm.

Science.gov (United States)

Fang, Hongqing; He, Lei; Si, Hao; Liu, Peng; Xie, Xiaolei

2014-09-01

In this paper, Back-propagation(BP) algorithm has been used to train the feed forward neural network for human activity recognition in smart home environments, and inter-class distance method for feature selection of observed motion sensor events is discussed and tested. And then, the human activity recognition performances of neural network using BP algorithm have been evaluated and compared with other probabilistic algorithms: Naïve Bayes(NB) classifier and Hidden Markov Model(HMM). The results show that different feature datasets yield different activity recognition accuracy. The selection of unsuitable feature datasets increases the computational complexity and degrades the activity recognition accuracy. Furthermore, neural network using BP algorithm has relatively better human activity recognition performances than NB classifier and HMM. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

SU-E-T-516: Dosimetric Validation of AcurosXB Algorithm in Comparison with AAA & CCC Algorithms for VMAT Technique.

Science.gov (United States)

Kathirvel, M; Subramanian, V Sai; Arun, G; Thirumalaiswamy, S; Ramalingam, K; Kumar, S Ashok; Jagadeesh, K

2012-06-01

To dosimetrically validate AcurosXB algorithm for Volumetric Modulated Arc Therapy (VMAT) in comparison with standard clinical Anisotropic Analytic Algorithm(AAA) and Collapsed Cone Convolution(CCC) dose calculation algorithms. AcurosXB dose calculation algorithm is available with Varian Eclipse treatment planning system (V10). It uses grid-based Boltzmann equation solver to predict dose precisely in lesser time. This study was made to realize algorithms ability to predict dose accurately as its delivery for which five clinical cases each of Brain, Head&Neck, Thoracic, Pelvic and SBRT were taken. Verification plans were created on multicube phantom with iMatrixx-2D detector array and then dose prediction was done with AcurosXB, AAA & CCC (COMPASS System) algorithm and the same were delivered onto CLINAC-iX treatment machine. Delivered dose was captured in iMatrixx plane for all 25 plans. Measured dose was taken as reference to quantify the agreement between AcurosXB calculation algorithm against previously validated AAA and CCC algorithm. Gamma evaluation was performed with clinical criteria distance-to-agreement 3&2mm and dose difference 3&2% in omnipro-I'MRT software. Plans were evaluated in terms of correlation coefficient, quantitative area gamma and average gamma. Study shows good agreement between mean correlation 0.9979±0.0012, 0.9984±0.0009 & 0.9979±0.0011 for AAA, CCC & Acuros respectively. Mean area gamma for criteria 3mm/3% was found to be 98.80±1.04, 98.14±2.31, 98.08±2.01 and 2mm/2% was found to be 93.94±3.83, 87.17±10.54 & 92.36±5.46 for AAA, CCC & Acuros respectively. Mean average gamma for 3mm/3% was 0.26±0.07, 0.42±0.08, 0.28±0.09 and 2mm/2% was found to be 0.39±0.10, 0.64±0.11, 0.42±0.13 for AAA, CCC & Acuros respectively. This study demonstrated that the AcurosXB algorithm had a good agreement with the AAA & CCC in terms of dose prediction. In conclusion AcurosXB algorithm provides a valid, accurate and speedy alternative to AAA

Genetic algorithms

Science.gov (United States)

Wang, Lui; Bayer, Steven E.

1991-01-01

Genetic algorithms are mathematical, highly parallel, adaptive search procedures (i.e., problem solving methods) based loosely on the processes of natural genetics and Darwinian survival of the fittest. Basic genetic algorithms concepts are introduced, genetic algorithm applications are introduced, and results are presented from a project to develop a software tool that will enable the widespread use of genetic algorithm technology.

Analysis of Network Clustering Algorithms and Cluster Quality Metrics at Scale.

Science.gov (United States)

Emmons, Scott; Kobourov, Stephen; Gallant, Mike; Börner, Katy

2016-01-01

Notions of community quality underlie the clustering of networks. While studies surrounding network clustering are increasingly common, a precise understanding of the realtionship between different cluster quality metrics is unknown. In this paper, we examine the relationship between stand-alone cluster quality metrics and information recovery metrics through a rigorous analysis of four widely-used network clustering algorithms-Louvain, Infomap, label propagation, and smart local moving. We consider the stand-alone quality metrics of modularity, conductance, and coverage, and we consider the information recovery metrics of adjusted Rand score, normalized mutual information, and a variant of normalized mutual information used in previous work. Our study includes both synthetic graphs and empirical data sets of sizes varying from 1,000 to 1,000,000 nodes. We find significant differences among the results of the different cluster quality metrics. For example, clustering algorithms can return a value of 0.4 out of 1 on modularity but score 0 out of 1 on information recovery. We find conductance, though imperfect, to be the stand-alone quality metric that best indicates performance on the information recovery metrics. Additionally, our study shows that the variant of normalized mutual information used in previous work cannot be assumed to differ only slightly from traditional normalized mutual information. Smart local moving is the overall best performing algorithm in our study, but discrepancies between cluster evaluation metrics prevent us from declaring it an absolutely superior algorithm. Interestingly, Louvain performed better than Infomap in nearly all the tests in our study, contradicting the results of previous work in which Infomap was superior to Louvain. We find that although label propagation performs poorly when clusters are less clearly defined, it scales efficiently and accurately to large graphs with well-defined clusters.

Genetic Bee Colony (GBC) algorithm: A new gene selection method for microarray cancer classification.

Science.gov (United States)

Alshamlan, Hala M; Badr, Ghada H; Alohali, Yousef A

2015-06-01

Naturally inspired evolutionary algorithms prove effectiveness when used for solving feature selection and classification problems. Artificial Bee Colony (ABC) is a relatively new swarm intelligence method. In this paper, we propose a new hybrid gene selection method, namely Genetic Bee Colony (GBC) algorithm. The proposed algorithm combines the used of a Genetic Algorithm (GA) along with Artificial Bee Colony (ABC) algorithm. The goal is to integrate the advantages of both algorithms. The proposed algorithm is applied to a microarray gene expression profile in order to select the most predictive and informative genes for cancer classification. In order to test the accuracy performance of the proposed algorithm, extensive experiments were conducted. Three binary microarray datasets are use, which include: colon, leukemia, and lung. In addition, another three multi-class microarray datasets are used, which are: SRBCT, lymphoma, and leukemia. Results of the GBC algorithm are compared with our recently proposed technique: mRMR when combined with the Artificial Bee Colony algorithm (mRMR-ABC). We also compared the combination of mRMR with GA (mRMR-GA) and Particle Swarm Optimization (mRMR-PSO) algorithms. In addition, we compared the GBC algorithm with other related algorithms that have been recently published in the literature, using all benchmark datasets. The GBC algorithm shows superior performance as it achieved the highest classification accuracy along with the lowest average number of selected genes. This proves that the GBC algorithm is a promising approach for solving the gene selection problem in both binary and multi-class cancer classification. Copyright © 2015 Elsevier Ltd. All rights reserved.

The BiPublishers ranking: Main results and methodological problems when constructing rankings of academic publishers

Directory of Open Access Journals (Sweden)

Torres-Salinas, Daniel

2015-12-01

Full Text Available We present the results of the Bibliometric Indicators for Publishers project (also known as BiPublishers. This project represents the first attempt to systematically develop bibliometric publisher rankings. The data for this project was derived from the Book Citation Index and the study time period was 2009-2013. We have developed 42 rankings: 4 by fields and 38 by disciplines. We display six indicators for publishers divided into three types: output, impact and publisher’s profile. The aim is to capture different characteristics of the research performance of publishers. 254 publishers were processed and classified according to publisher type: commercial publishers and university presses. We present the main publishers by field and then discuss the principal challenges presented when developing this type of tool. The BiPublishers ranking is an on-going project which aims to develop and explore new data sources and indicators to better capture and define the research impact of publishers.Presentamos los resultados del proyecto Bibliometric Indicators for Publishers (BiPublishers. Es el primer proyecto que desarrolla de manera sistemática rankings bibliométricos de editoriales. La fuente de datos empleada es el Book Citation Index y el periodo de análisis 2009-2013. Se presentan 42 rankings: 4 por áreas y 38 por disciplinas. Mostramos seis indicadores por editorial divididos según su tipología: producción, impacto y características editoriales. Se procesaron 254 editoriales y se clasificaron según el tipo: comerciales y universitarias. Se presentan las principales editoriales por áreas. Después, se discuten los principales retos a superar en el desarrollo de este tipo de herramientas. El ranking Bipublishers es un proyecto en desarrollo que persigue analizar y explorar nuevas fuentes de datos e indicadores para captar y definir el impacto de las editoriales académicas.

Design of 2-D Recursive Filters Using Self-adaptive Mutation Differential Evolution Algorithm

Directory of Open Access Journals (Sweden)

Lianghong Wu

2011-08-01

Full Text Available This paper investigates a novel approach to the design of two-dimensional recursive digital filters using differential evolution (DE algorithm. The design task is reformulated as a constrained minimization problem and is solved by an Self-adaptive Mutation DE algorithm (SAMDE, which adopts an adaptive mutation operator that combines with the advantages of the DE/rand/1/bin strategy and the DE/best/2/bin strategy. As a result, its convergence performance is improved greatly. Numerical experiment results confirm the conclusion. The proposedSAMDE approach is effectively applied to test a numerical example and is compared with previous design methods. The computational experiments show that the SAMDE approach can obtain better results than previous design methods.

Algorithm aversion: people erroneously avoid algorithms after seeing them err.

Science.gov (United States)

Dietvorst, Berkeley J; Simmons, Joseph P; Massey, Cade

2015-02-01

Research shows that evidence-based algorithms more accurately predict the future than do human forecasters. Yet when forecasters are deciding whether to use a human forecaster or a statistical algorithm, they often choose the human forecaster. This phenomenon, which we call algorithm aversion, is costly, and it is important to understand its causes. We show that people are especially averse to algorithmic forecasters after seeing them perform, even when they see them outperform a human forecaster. This is because people more quickly lose confidence in algorithmic than human forecasters after seeing them make the same mistake. In 5 studies, participants either saw an algorithm make forecasts, a human make forecasts, both, or neither. They then decided whether to tie their incentives to the future predictions of the algorithm or the human. Participants who saw the algorithm perform were less confident in it, and less likely to choose it over an inferior human forecaster. This was true even among those who saw the algorithm outperform the human.

Increasing Prediction the Original Final Year Project of Student Using Genetic Algorithm

Science.gov (United States)

Saragih, Rijois Iboy Erwin; Turnip, Mardi; Sitanggang, Delima; Aritonang, Mendarissan; Harianja, Eva

2018-04-01

Final year project is very important forgraduation study of a student. Unfortunately, many students are not seriouslydidtheir final projects. Many of studentsask for someone to do it for them. In this paper, an application of genetic algorithms to predict the original final year project of a studentis proposed. In the simulation, the data of the final project for the last 5 years is collected. The genetic algorithm has several operators namely population, selection, crossover, and mutation. The result suggest that genetic algorithm can do better prediction than other comparable model. Experimental results of predicting showed that 70% was more accurate than the previous researched.

Data Sharing & Publishing at Nature Publishing Group

Science.gov (United States)

VanDecar, J. C.; Hrynaszkiewicz, I.; Hufton, A. L.

2015-12-01

In recent years, the research community has come to recognize that upon-request data sharing has important limitations1,2. The Nature-titled journals feel that researchers have a duty to share data without undue qualifications, in a manner that allows others to replicate and build upon their published findings. Historically, the Nature journals have been strong supporters of data deposition in communities with existing data mandates, and have required data sharing upon request in all other cases. To help address some of the limitations of upon-request data sharing, the Nature titles have strengthened their existing data policies and forged a new partnership with Scientific Data, to promote wider data sharing in discoverable, citeable and reusable forms, and to ensure that scientists get appropriate credit for sharing3. Scientific Data is a new peer-reviewed journal for descriptions of research datasets, which works with a wide of range of public data repositories4. Articles at Scientific Data may either expand on research publications at other journals or may be used to publish new datasets. The Nature Publishing Group has also signed the Joint Declaration of Data Citation Principles5, and Scientific Data is our first journal to include formal data citations. We are currently in the process of adding data citation support to our various journals. 1 Wicherts, J. M., Borsboom, D., Kats, J. & Molenaar, D. The poor availability of psychological research data for reanalysis. Am. Psychol. 61, 726-728, doi:10.1037/0003-066x.61.7.726 (2006). 2 Vines, T. H. et al. Mandated data archiving greatly improves access to research data. FASEB J. 27, 1304-1308, doi:10.1096/fj.12-218164 (2013). 3 Data-access practices strengthened. Nature 515, 312, doi:10.1038/515312a (2014). 4 More bang for your byte. Sci. Data 1, 140010, doi:10.1038/sdata.2014.10 (2014). 5 Data Citation Synthesis Group: Joint Declaration of Data Citation Principles. (FORCE11, San Diego, CA, 2014).

NUCLEAR SEGMENTATION IN MICROSCOPE CELL IMAGES: A HAND-SEGMENTED DATASET AND COMPARISON OF ALGORITHMS

OpenAIRE

Coelho, Luís Pedro; Shariff, Aabid; Murphy, Robert F.

2009-01-01

Image segmentation is an essential step in many image analysis pipelines and many algorithms have been proposed to solve this problem. However, they are often evaluated subjectively or based on a small number of examples. To fill this gap, we hand-segmented a set of 97 fluorescence microscopy images (a total of 4009 cells) and objectively evaluated some previously proposed segmentation algorithms.

The Texas Medication Algorithm Project (TMAP) schizophrenia algorithms.

Science.gov (United States)

Miller, A L; Chiles, J A; Chiles, J K; Crismon, M L; Rush, A J; Shon, S P

1999-10-01

In the Texas Medication Algorithm Project (TMAP), detailed guidelines for medication management of schizophrenia and related disorders, bipolar disorders, and major depressive disorders have been developed and implemented. This article describes the algorithms developed for medication treatment of schizophrenia and related disorders. The guidelines recommend a sequence of medications and discuss dosing, duration, and switch-over tactics. They also specify response criteria at each stage of the algorithm for both positive and negative symptoms. The rationale and evidence for each aspect of the algorithms are presented.

A New Augmentation Based Algorithm for Extracting Maximal Chordal Subgraphs.

Science.gov (United States)

Bhowmick, Sanjukta; Chen, Tzu-Yi; Halappanavar, Mahantesh

2015-02-01

A graph is chordal if every cycle of length greater than three contains an edge between non-adjacent vertices. Chordal graphs are of interest both theoretically, since they admit polynomial time solutions to a range of NP-hard graph problems, and practically, since they arise in many applications including sparse linear algebra, computer vision, and computational biology. A maximal chordal subgraph is a chordal subgraph that is not a proper subgraph of any other chordal subgraph. Existing algorithms for computing maximal chordal subgraphs depend on dynamically ordering the vertices, which is an inherently sequential process and therefore limits the algorithms' parallelizability. In this paper we explore techniques to develop a scalable parallel algorithm for extracting a maximal chordal subgraph. We demonstrate that an earlier attempt at developing a parallel algorithm may induce a non-optimal vertex ordering and is therefore not guaranteed to terminate with a maximal chordal subgraph. We then give a new algorithm that first computes and then repeatedly augments a spanning chordal subgraph. After proving that the algorithm terminates with a maximal chordal subgraph, we then demonstrate that this algorithm is more amenable to parallelization and that the parallel version also terminates with a maximal chordal subgraph. That said, the complexity of the new algorithm is higher than that of the previous parallel algorithm, although the earlier algorithm computes a chordal subgraph which is not guaranteed to be maximal. We experimented with our augmentation-based algorithm on both synthetic and real-world graphs. We provide scalability results and also explore the effect of different choices for the initial spanning chordal subgraph on both the running time and on the number of edges in the maximal chordal subgraph.

2010 International consensus algorithm for the diagnosis, therapy and management of hereditary angioedema

DEFF Research Database (Denmark)

Bowen, Tom; Cicardi, Marco; Farkas, Henriette

2010-01-01

ABSTRACT: BACKGROUND: We published the Canadian 2003 International Consensus Algorithm for the Diagnosis, Therapy, and Management of Hereditary Angioedema (HAE; C1 inhibitor [C1-INH] deficiency) and updated this as Hereditary angioedema: a current state-of-the-art review: Canadian Hungarian 2007 ...

Introduction: a brief overview of iterative algorithms in X-ray computed tomography.

Science.gov (United States)

Soleimani, M; Pengpen, T

2015-06-13

This paper presents a brief overview of some basic iterative algorithms, and more sophisticated methods are presented in the research papers in this issue. A range of algebraic iterative algorithms are covered here including ART, SART and OS-SART. A major limitation of the traditional iterative methods is their computational time. The Krylov subspace based methods such as the conjugate gradients (CG) algorithm and its variants can be used to solve linear systems of equations arising from large-scale CT with possible implementation using modern high-performance computing tools. The overall aim of this theme issue is to stimulate international efforts to develop the next generation of X-ray computed tomography (CT) image reconstruction software. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

[New calculation algorithms in brachytherapy for iridium 192 treatments].

Science.gov (United States)

Robert, C; Dumas, I; Martinetti, F; Chargari, C; Haie-Meder, C; Lefkopoulos, D

2018-05-18

Since 1995, the brachytherapy dosimetry protocols follow the methodology recommended by the Task Group 43. This methodology, which has the advantage of being fast, is based on several approximations that are not always valid in clinical conditions. Model-based dose calculation algorithms have recently emerged in treatment planning stations and are considered as a major evolution by allowing for consideration of the patient's finite dimensions, tissue heterogeneities and the presence of high atomic number materials in applicators. In 2012, a report from the American Association of Physicists in Medicine Radiation Therapy Task Group 186 reviews these models and makes recommendations for their clinical implementation. This review focuses on the use of model-based dose calculation algorithms in the context of iridium 192 treatments. After a description of these algorithms and their clinical implementation, a summary of the main questions raised by these new methods is performed. Considerations regarding the choice of the medium used for the dose specification and the recommended methodology for assigning materials characteristics are especially described. In the last part, recent concrete examples from the literature illustrate the capabilities of these new algorithms on clinical cases. Copyright © 2018 Société française de radiothérapie oncologique (SFRO). Published by Elsevier SAS. All rights reserved.

Reliability and safety of a new upper cervical spine injury treatment algorithm

Directory of Open Access Journals (Sweden)

Andrei Fernandes Joaquim

Full Text Available ABSTRACT In the present study, we evaluated the reliability and safety of a new upper cervical spine injury treatment algorithm to help in the selection of the best treatment modality for these injuries. Methods Thirty cases, previously treated according to the new algorithm, were presented to four spine surgeons who were questioned about their personal suggestion for treatment, and the treatment suggested according to the application of the algorithm. After four weeks, the same questions were asked again to evaluate reliability (intra- and inter-observer using the Kappa index. Results The reliability of the treatment suggested by applying the algorithm was superior to the reliability of the surgeons’ personal suggestion for treatment. When applying the upper cervical spine injury treatment algorithm, an agreement with the treatment actually performed was obtained in more than 89% of the cases. Conclusion The system is safe and reliable for treating traumatic upper cervical spine injuries. The algorithm can be used to help surgeons in the decision between conservative versus surgical treatment of these injuries.

The new American Heart Association algorithm: is it progress?

African Journals Online (AJOL)

has removed surgical grading from the risk stratification. They have now integrated “surgical risk” into the recommended preoperative risk stratification model.2. Previously, low-risk surgery was essentially “a ticket to surgery”,2 but in the new algorithm, emphasis is placed on the predicted risk of major adverse cardiac events ...

An optimal iterative algorithm to solve Cauchy problem for Laplace equation

KAUST Repository

Majeed, Muhammad Usman

2015-05-25

An optimal mean square error minimizer algorithm is developed to solve severely ill-posed Cauchy problem for Laplace equation on an annulus domain. The mathematical problem is presented as a first order state space-like system and an optimal iterative algorithm is developed that minimizes the mean square error in states. Finite difference discretization schemes are used to discretize first order system. After numerical discretization algorithm equations are derived taking inspiration from Kalman filter however using one of the space variables as a time-like variable. Given Dirichlet and Neumann boundary conditions are used on the Cauchy data boundary and fictitious points are introduced on the unknown solution boundary. The algorithm is run for a number of iterations using the solution of previous iteration as a guess for the next one. The method developed happens to be highly robust to noise in Cauchy data and numerically efficient results are illustrated.

Demosaicking algorithm for the Kodak-RGBW color filter array

Science.gov (United States)

Rafinazari, M.; Dubois, E.

2015-01-01

Digital cameras capture images through different Color Filter Arrays and then reconstruct the full color image. Each CFA pixel only captures one primary color component; the other primary components will be estimated using information from neighboring pixels. During the demosaicking algorithm, the two unknown color components will be estimated at each pixel location. Most of the demosaicking algorithms use the RGB Bayer CFA pattern with Red, Green and Blue filters. The least-Squares Luma-Chroma demultiplexing method is a state of the art demosaicking method for the Bayer CFA. In this paper we develop a new demosaicking algorithm using the Kodak-RGBW CFA. This particular CFA reduces noise and improves the quality of the reconstructed images by adding white pixels. We have applied non-adaptive and adaptive demosaicking method using the Kodak-RGBW CFA on the standard Kodak image dataset and the results have been compared with previous work.

Towards Automatic Controller Design using Multi-Objective Evolutionary Algorithms

DEFF Research Database (Denmark)

Pedersen, Gerulf

of evolutionary computation, a choice was made to use multi-objective algorithms for the purpose of aiding in automatic controller design. More specifically, the choice was made to use the Non-dominated Sorting Genetic Algorithm II (NSGAII), which is one of the most potent algorithms currently in use...... for automatic controller design. However, because the field of evolutionary computation is relatively unknown in the field of control engineering, this thesis also includes a comprehensive introduction to the basic field of evolutionary computation as well as a description of how the field has previously been......In order to design the controllers of tomorrow, a need has risen for tools that can aid in the design of these. A desire to use evolutionary computation as a tool to achieve that goal is what gave inspiration for the work contained in this thesis. After having studied the foundations...

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

Directory of Open Access Journals (Sweden)

Yazheng Dang

2013-01-01

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

Fast algorithms for transport models. Final report, June 1, 1993--May 31, 1994

International Nuclear Information System (INIS)

Manteuffel, T.

1994-12-01

The focus of this project is the study of multigrid and multilevel algorithms for the numerical solution of Boltzmann models of the transport of neutral and charged particles. In previous work a fast multigrid algorithm was developed for the numerical solution of the Boltzmann model of neutral particle transport in slab geometry assuming isotropic scattering. The new algorithm is extremely fast in the thick diffusion limit; the multigrid v-cycle convergence factor approaches zero as the mean-free-path between collisions approaches zero, independent of the mesh. Also, a fast multilevel method was developed for the numerical solution of the Boltzmann model of charged particle transport in the thick Fokker-Plank limit for slab geometry. Parallel implementations were developed for both algorithms

Implementation of a parallel algorithm for spherical SN calculations on the IBM 3090

International Nuclear Information System (INIS)

Haghighat, A.; Lawrence, R.D.

1989-01-01

Parallel S N algorithms based on domain decomposition in angle are straightforward to develop in Cartesian geometry because the computation of the angular fluxes for a specific discrete ordinate can be performed independently of all other angles. This is not the case for curvilinear geometries, where the angular redistribution component of the discretized streaming operator results in coupling between angular fluxes along adjacent discrete ordinates. Previously, the authors developed a parallel algorithm for S N calculations in spherical geometry and examined its iterative convergence for criticality and detector problems with differing scattering/absorption ratios. In this paper, the authors describe the implementation of the algorithm on an IBM 3090 Model 400 (four processors) and present computational results illustrating the efficiency of the algorithm relative to serial execution

An introduction to quantum computing algorithms

CERN Document Server

Pittenger, Arthur O

2000-01-01

In 1994 Peter Shor [65] published a factoring algorithm for a quantum computer that finds the prime factors of a composite integer N more efficiently than is possible with the known algorithms for a classical com­ puter. Since the difficulty of the factoring problem is crucial for the se­ curity of a public key encryption system, interest (and funding) in quan­ tum computing and quantum computation suddenly blossomed. Quan­ tum computing had arrived. The study of the role of quantum mechanics in the theory of computa­ tion seems to have begun in the early 1980s with the publications of Paul Benioff [6]' [7] who considered a quantum mechanical model of computers and the computation process. A related question was discussed shortly thereafter by Richard Feynman [35] who began from a different perspec­ tive by asking what kind of computer should be used to simulate physics. His analysis led him to the belief that with a suitable class of "quantum machines" one could imitate any quantum system.

The Academic Publishing Industry

DEFF Research Database (Denmark)

Nell, Phillip Christopher; Wenzel, Tim Ole; Schmidt, Florian

2014-01-01

The case starts with introducing the outstanding profitability of academic journal publishers such as Elsevier and then dives into describing the research process from an idea to conducting research and to publishing the results in academic journals. Subsequently, demand and supply for scientific...... journals and papers are discussed including drivers and involved parties. Furthermore, the case describes competition between suppliers, customers, and publishers. In sum, the case study features a rich description of the industry’s many unusual attributes which allows for discussing the benefits...

Parallel algorithms for mapping pipelined and parallel computations

Science.gov (United States)

Nicol, David M.

1988-01-01

Many computational problems in image processing, signal processing, and scientific computing are naturally structured for either pipelined or parallel computation. When mapping such problems onto a parallel architecture it is often necessary to aggregate an obvious problem decomposition. Even in this context the general mapping problem is known to be computationally intractable, but recent advances have been made in identifying classes of problems and architectures for which optimal solutions can be found in polynomial time. Among these, the mapping of pipelined or parallel computations onto linear array, shared memory, and host-satellite systems figures prominently. This paper extends that work first by showing how to improve existing serial mapping algorithms. These improvements have significantly lower time and space complexities: in one case a published O(nm sup 3) time algorithm for mapping m modules onto n processors is reduced to an O(nm log m) time complexity, and its space requirements reduced from O(nm sup 2) to O(m). Run time complexity is further reduced with parallel mapping algorithms based on these improvements, which run on the architecture for which they create the mappings.

Design of intelligent locks based on the triple KeeLoq algorithm

Directory of Open Access Journals (Sweden)

Huibin Chen

2016-04-01

Full Text Available KeeLoq algorithm with high security was usually used in wireless codec. Its security lack is indicated in this article according to the detailed rationale and the introduction of previous attack researches. Taking examples from Triple Data Encryption Standard algorithm, the triple KeeLoq codec algorithm was first proposed. Experimental results showed that the algorithm would not reduce powerful rolling effect and in consideration of limited computing power of embedded microcontroller three 64-bit keys were suitable to increase the crack difficulties and further improved its security. The method was applied to intelligent door access system for experimental verification. 16F690 extended Bluetooth or WiFi interface was employed to design the lock system on door. Key application was constructed on Android platform. The wireless communication between the lock on door and Android key application employed triple KeeLoq algorithm to ensure the higher security. Due to flexibility and multiformity (an Android key application with various keys of software-based keys, the solution owned overwhelmed advantages of low cost, high security, humanity, and green environmental protection.

Copyright of Electronic Publishing.

Science.gov (United States)

Dong, Elaine; Wang, Bob

2002-01-01

Analyzes the importance of copyright, considers the main causes of copyright infringement in electronic publishing, discusses fair use of a copyrighted work, and suggests methods to safeguard copyrighted electronic publishing, including legislation, contracts, and technology. (Author/LRW)

Pseudo-deterministic Algorithms

OpenAIRE

Goldwasser , Shafi

2012-01-01

International audience; In this talk we describe a new type of probabilistic algorithm which we call Bellagio Algorithms: a randomized algorithm which is guaranteed to run in expected polynomial time, and to produce a correct and unique solution with high probability. These algorithms are pseudo-deterministic: they can not be distinguished from deterministic algorithms in polynomial time by a probabilistic polynomial time observer with black box access to the algorithm. We show a necessary an...

The Algorithmic Imaginary

DEFF Research Database (Denmark)

Bucher, Taina

2017-01-01

the notion of the algorithmic imaginary. It is argued that the algorithmic imaginary – ways of thinking about what algorithms are, what they should be and how they function – is not just productive of different moods and sensations but plays a generative role in moulding the Facebook algorithm itself...... of algorithms affect people's use of these platforms, if at all? To help answer these questions, this article examines people's personal stories about the Facebook algorithm through tweets and interviews with 25 ordinary users. To understand the spaces where people and algorithms meet, this article develops...

An adaptive left–right eigenvector evolution algorithm for vibration isolation control

International Nuclear Information System (INIS)

Wu, T Y

2009-01-01

The purpose of this research is to investigate the feasibility of utilizing an adaptive left and right eigenvector evolution (ALREE) algorithm for active vibration isolation. As depicted in the previous paper presented by Wu and Wang (2008 Smart Mater. Struct. 17 015048), the structural vibration behavior depends on both the disturbance rejection capability and mode shape distributions, which correspond to the left and right eigenvector distributions of the system, respectively. In this paper, a novel adaptive evolution algorithm is developed for finding the optimal combination of left–right eigenvectors of the vibration isolator, which is an improvement over the simultaneous left–right eigenvector assignment (SLREA) method proposed by Wu and Wang (2008 Smart Mater. Struct. 17 015048). The isolation performance index used in the proposed algorithm is defined by combining the orthogonality index of left eigenvectors and the modal energy ratio index of right eigenvectors. Through the proposed ALREE algorithm, both the left and right eigenvectors evolve such that the isolation performance index decreases, and therefore one can find the optimal combination of left–right eigenvectors of the closed-loop system for vibration isolation purposes. The optimal combination of left–right eigenvectors is then synthesized to determine the feedback gain matrix of the closed-loop system. The result of the active isolation control shows that the proposed method can be utilized to improve the vibration isolation performance compared with the previous approaches

Precise algorithm to generate random sequential adsorption of hard polygons at saturation

Science.gov (United States)

Zhang, G.

2018-04-01

Random sequential adsorption (RSA) is a time-dependent packing process, in which particles of certain shapes are randomly and sequentially placed into an empty space without overlap. In the infinite-time limit, the density approaches a "saturation" limit. Although this limit has attracted particular research interest, the majority of past studies could only probe this limit by extrapolation. We have previously found an algorithm to reach this limit using finite computational time for spherical particles and could thus determine the saturation density of spheres with high accuracy. In this paper, we generalize this algorithm to generate saturated RSA packings of two-dimensional polygons. We also calculate the saturation density for regular polygons of three to ten sides and obtain results that are consistent with previous, extrapolation-based studies.

Road detection in SAR images using a tensor voting algorithm

Science.gov (United States)

Shen, Dajiang; Hu, Chun; Yang, Bing; Tian, Jinwen; Liu, Jian

2007-11-01

In this paper, the problem of the detection of road networks in Synthetic Aperture Radar (SAR) images is addressed. Most of the previous methods extract the road by detecting lines and network reconstruction. Traditional algorithms such as MRFs, GA, Level Set, used in the progress of reconstruction are iterative. The tensor voting methodology we proposed is non-iterative, and non-sensitive to initialization. Furthermore, the only free parameter is the size of the neighborhood, related to the scale. The algorithm we present is verified to be effective when it's applied to the road extraction using the real Radarsat Image.

Improved implementation algorithms of the two-dimensional nonseparable linear canonical transform.

Science.gov (United States)

Ding, Jian-Jiun; Pei, Soo-Chang; Liu, Chun-Lin

2012-08-01

The two-dimensional nonseparable linear canonical transform (2D NSLCT), which is a generalization of the fractional Fourier transform and the linear canonical transform, is useful for analyzing optical systems. However, since the 2D NSLCT has 16 parameters and is very complicated, it is a great challenge to implement it in an efficient way. In this paper, we improved the previous work and propose an efficient way to implement the 2D NSLCT. The proposed algorithm can minimize the numerical error arising from interpolation operations and requires fewer chirp multiplications. The simulation results show that, compared with the existing algorithm, the proposed algorithms can implement the 2D NSLCT more accurately and the required computation time is also less.

Elearning and digital publishing

CERN Document Server

Ching, Hsianghoo Steve; Mc Naught, Carmel

2006-01-01

""ELearning and Digital Publishing"" will occupy a unique niche in the literature accessed by library and publishing specialists, and by university teachers and planners. It examines the interfaces between the work done by four groups of university staff who have been in the past quite separate from, or only marginally related to, each other - library staff, university teachers, university policy makers, and staff who work in university publishing presses. All four groups are directly and intimately connected with the main functions of universities - the creation, management and dissemination

Books Average Previous Decade of Economic Misery

Science.gov (United States)

Bentley, R. Alexander; Acerbi, Alberto; Ormerod, Paul; Lampos, Vasileios

2014-01-01

For the 20th century since the Depression, we find a strong correlation between a ‘literary misery index’ derived from English language books and a moving average of the previous decade of the annual U.S. economic misery index, which is the sum of inflation and unemployment rates. We find a peak in the goodness of fit at 11 years for the moving average. The fit between the two misery indices holds when using different techniques to measure the literary misery index, and this fit is significantly better than other possible correlations with different emotion indices. To check the robustness of the results, we also analysed books written in German language and obtained very similar correlations with the German economic misery index. The results suggest that millions of books published every year average the authors' shared economic experiences over the past decade. PMID:24416159

Algorithms for detecting and analysing autocatalytic sets.

Science.gov (United States)

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

How libraries use publisher metadata

Directory of Open Access Journals (Sweden)

Steve Shadle

2013-11-01

Full Text Available With the proliferation of electronic publishing, libraries are increasingly relying on publisher-supplied metadata to meet user needs for discovery in library systems. However, many publisher/content provider staff creating metadata are unaware of the end-user environment and how libraries use their metadata. This article provides an overview of the three primary discovery systems that are used by academic libraries, with examples illustrating how publisher-supplied metadata directly feeds into these systems and is used to support end-user discovery and access. Commonly seen metadata problems are discussed, with recommendations suggested. Based on a series of presentations given in Autumn 2012 to the staff of a large publisher, this article uses the University of Washington Libraries systems and services as illustrative examples. Judging by the feedback received from these presentations, publishers (specifically staff not familiar with the big picture of metadata standards work would benefit from a better understanding of the systems and services libraries provide using the data that is created and managed by publishers.

Electronic Publishing.

Science.gov (United States)

Lancaster, F. W.

1989-01-01

Describes various stages involved in the applications of electronic media to the publishing industry. Highlights include computer typesetting, or photocomposition; machine-readable databases; the distribution of publications in electronic form; computer conferencing and electronic mail; collaborative authorship; hypertext; hypermedia publications;…

International Marketing Developing Publishing Business

Directory of Open Access Journals (Sweden)

Eugenijus Chlivickas

2015-05-01

Full Text Available Lithuanian integration in the financial Eurozone and Lithuanian publishing business development in the European Union and outside it, becomes an important problem requiring a solution. Promoting the dissemination of printed books and literacy in Lithuania and beyond, to properly introduce the achievements of Lithuania in foreign countries, it is important to ensure Lithuanian letter, educational and scientific book publishing development. The article examines the characteristics of the international marketing publishing, the world and Lithuanian state publishing houses on the basis of foreign and Lithuanian scientists theoretical insights about the instruments of international marketing opportunities, developing proposals for publishing business integration of new economic conditions.

Automated System for Teaching Computational Complexity of Algorithms Course

Directory of Open Access Journals (Sweden)

Vadim S. Roublev

2017-01-01

Full Text Available This article describes problems of designing automated teaching system for “Computational complexity of algorithms” course. This system should provide students with means to familiarize themselves with complex mathematical apparatus and improve their mathematical thinking in the respective area. The article introduces the technique of algorithms symbol scroll table that allows estimating lower and upper bounds of computational complexity. Further, we introduce a set of theorems that facilitate the analysis in cases when the integer rounding of algorithm parameters is involved and when analyzing the complexity of a sum. At the end, the article introduces a normal system of symbol transformations that allows one both to perform any symbol transformations and simplifies the automated validation of such transformations. The article is published in the authors’ wording.

Joint optimization of algorithmic suites for EEG analysis.

Science.gov (United States)

Santana, Eder; Brockmeier, Austin J; Principe, Jose C

2014-01-01

Electroencephalogram (EEG) data analysis algorithms consist of multiple processing steps each with a number of free parameters. A joint optimization methodology can be used as a wrapper to fine-tune these parameters for the patient or application. This approach is inspired by deep learning neural network models, but differs because the processing layers for EEG are heterogeneous with different approaches used for processing space and time. Nonetheless, we treat the processing stages as a neural network and apply backpropagation to jointly optimize the parameters. This approach outperforms previous results on the BCI Competition II - dataset IV; additionally, it outperforms the common spatial patterns (CSP) algorithm on the BCI Competition III dataset IV. In addition, the optimized parameters in the architecture are still interpretable.

A comparison of two open source LiDAR surface classification algorithms

Science.gov (United States)

Wade T. Tinkham; Hongyu Huang; Alistair M.S. Smith; Rupesh Shrestha; Michael J. Falkowski; Andrew T. Hudak; Timothy E. Link; Nancy F. Glenn; Danny G. Marks

2011-01-01

With the progression of LiDAR (Light Detection and Ranging) towards a mainstream resource management tool, it has become necessary to understand how best to process and analyze the data. While most ground surface identification algorithms remain proprietary and have high purchase costs; a few are openly available, free to use, and are supported by published results....

Adoption of the Hash algorithm in a conceptual model for the civil registry of Ecuador

Science.gov (United States)

Toapanta, Moisés; Mafla, Enrique; Orizaga, Antonio

2018-04-01

The Hash security algorithm was analyzed in order to mitigate information security in a distributed architecture. The objective of this research is to develop a prototype for the Adoption of the algorithm Hash in a conceptual model for the Civil Registry of Ecuador. The deductive method was used in order to analyze the published articles that have a direct relation with the research project "Algorithms and Security Protocols for the Civil Registry of Ecuador" and articles related to the Hash security algorithm. It resulted from this research: That the SHA-1 security algorithm is appropriate for use in Ecuador's civil registry; we adopted the SHA-1 algorithm used in the flowchart technique and finally we obtained the adoption of the hash algorithm in a conceptual model. It is concluded that from the comparison of the DM5 and SHA-1 algorithm, it is suggested that in the case of an implementation, the SHA-1 algorithm is taken due to the amount of information and data available from the Civil Registry of Ecuador; It is determined that the SHA-1 algorithm that was defined using the flowchart technique can be modified according to the requirements of each institution; the model for adopting the hash algorithm in a conceptual model is a prototype that can be modified according to all the actors that make up each organization.

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

Directory of Open Access Journals (Sweden)

ZHU Xiaoxiao

2018-02-01

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

An Adaptive Filtering Algorithm Based on Genetic Algorithm-Backpropagation Network

Directory of Open Access Journals (Sweden)

Kai Hu

2013-01-01

Full Text Available A new image filtering algorithm is proposed. GA-BPN algorithm uses genetic algorithm (GA to decide weights in a back propagation neural network (BPN. It has better global optimal characteristics than traditional optimal algorithm. In this paper, we used GA-BPN to do image noise filter researching work. Firstly, this paper uses training samples to train GA-BPN as the noise detector. Then, we utilize the well-trained GA-BPN to recognize noise pixels in target image. And at last, an adaptive weighted average algorithm is used to recover noise pixels recognized by GA-BPN. Experiment data shows that this algorithm has better performance than other filters.

Which clustering algorithm is better for predicting protein complexes?

Directory of Open Access Journals (Sweden)

Moschopoulos Charalampos N

2011-12-01

Full Text Available Abstract Background Protein-Protein interactions (PPI play a key role in determining the outcome of most cellular processes. The correct identification and characterization of protein interactions and the networks, which they comprise, is critical for understanding the molecular mechanisms within the cell. Large-scale techniques such as pull down assays and tandem affinity purification are used in order to detect protein interactions in an organism. Today, relatively new high-throughput methods like yeast two hybrid, mass spectrometry, microarrays, and phage display are also used to reveal protein interaction networks. Results In this paper we evaluated four different clustering algorithms using six different interaction datasets. We parameterized the MCL, Spectral, RNSC and Affinity Propagation algorithms and applied them to six PPI datasets produced experimentally by Yeast 2 Hybrid (Y2H and Tandem Affinity Purification (TAP methods. The predicted clusters, so called protein complexes, were then compared and benchmarked with already known complexes stored in published databases. Conclusions While results may differ upon parameterization, the MCL and RNSC algorithms seem to be more promising and more accurate at predicting PPI complexes. Moreover, they predict more complexes than other reviewed algorithms in absolute numbers. On the other hand the spectral clustering algorithm achieves the highest valid prediction rate in our experiments. However, it is nearly always outperformed by both RNSC and MCL in terms of the geometrical accuracy while it generates the fewest valid clusters than any other reviewed algorithm. This article demonstrates various metrics to evaluate the accuracy of such predictions as they are presented in the text below. Supplementary material can be found at: http://www.bioacademy.gr/bioinformatics/projects/ppireview.htm

BitPAl: a bit-parallel, general integer-scoring sequence alignment algorithm.

Science.gov (United States)

Loving, Joshua; Hernandez, Yozen; Benson, Gary

2014-11-15

Mapping of high-throughput sequencing data and other bulk sequence comparison applications have motivated a search for high-efficiency sequence alignment algorithms. The bit-parallel approach represents individual cells in an alignment scoring matrix as bits in computer words and emulates the calculation of scores by a series of logic operations composed of AND, OR, XOR, complement, shift and addition. Bit-parallelism has been successfully applied to the longest common subsequence (LCS) and edit-distance problems, producing fast algorithms in practice. We have developed BitPAl, a bit-parallel algorithm for general, integer-scoring global alignment. Integer-scoring schemes assign integer weights for match, mismatch and insertion/deletion. The BitPAl method uses structural properties in the relationship between adjacent scores in the scoring matrix to construct classes of efficient algorithms, each designed for a particular set of weights. In timed tests, we show that BitPAl runs 7-25 times faster than a standard iterative algorithm. Source code is freely available for download at http://lobstah.bu.edu/BitPAl/BitPAl.html. BitPAl is implemented in C and runs on all major operating systems. jloving@bu.edu or yhernand@bu.edu or gbenson@bu.edu Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press.

New algorithms for identifying the flavour of [Formula: see text] mesons using pions and protons.

Science.gov (United States)

Aaij, R; Adeva, B; Adinolfi, M; Ajaltouni, Z; Akar, S; Albrecht, J; Alessio, F; Alexander, M; Ali, S; Alkhazov, G; Alvarez Cartelle, P; Alves, A A; Amato, S; Amerio, S; Amhis, Y; An, L; Anderlini, L; Andreassi, G; Andreotti, M; Andrews, J E; Appleby, R B; Archilli, F; d'Argent, P; Arnau Romeu, J; Artamonov, A; Artuso, M; Aslanides, E; Auriemma, G; Baalouch, M; Babuschkin, I; Bachmann, S; Back, J J; Badalov, A; Baesso, C; Baker, S; Baldini, W; Barlow, R J; Barschel, C; Barsuk, S; Barter, W; Baszczyk, M; Batozskaya, V; Batsukh, B; Battista, V; Bay, A; Beaucourt, L; Beddow, J; Bedeschi, F; Bediaga, I; Bel, L J; Bellee, V; Belloli, N; Belous, K; Belyaev, I; Ben-Haim, E; Bencivenni, G; Benson, S; Benton, J; Berezhnoy, A; Bernet, R; Bertolin, A; Betti, F; Bettler, M-O; van Beuzekom, M; Bezshyiko, Ia; Bifani, S; Billoir, P; Bird, T; Birnkraut, A; Bitadze, A; Bizzeti, A; Blake, T; Blanc, F; Blouw, J; Blusk, S; Bocci, V; Boettcher, T; Bondar, A; Bondar, N; Bonivento, W; Bordyuzhin, I; Borgheresi, A; Borghi, S; Borisyak, M; Borsato, M; Bossu, F; Boubdir, M; Bowcock, T J V; Bowen, E; Bozzi, C; Braun, S; Britsch, M; Britton, T; Brodzicka, J; Buchanan, E; Burr, C; Bursche, A; Buytaert, J; Cadeddu, S; Calabrese, R; Calvi, M; Calvo Gomez, M; Camboni, A; Campana, P; Campora Perez, D; Campora Perez, D H; Capriotti, L; Carbone, A; Carboni, G; Cardinale, R; Cardini, A; Carniti, P; Carson, L; Carvalho Akiba, K; Casse, G; Cassina, L; Castillo Garcia, L; Cattaneo, M; Cauet, Ch; Cavallero, G; Cenci, R; Charles, M; Charpentier, Ph; Chatzikonstantinidis, G; Chefdeville, M; Chen, S; Cheung, S F; Chobanova, V; Chrzaszcz, M; Cid Vidal, X; Ciezarek, G; Clarke, P E L; Clemencic, M; Cliff, H V; Closier, J; Coco, V; Cogan, J; Cogneras, E; Cogoni, V; Cojocariu, L; Collins, P; Comerma-Montells, A; Contu, A; Cook, A; Coombs, G; Coquereau, S; Corti, G; Corvo, M; Costa Sobral, C M; Couturier, B; Cowan, G A; Craik, D C; Crocombe, A; Cruz Torres, M; Cunliffe, S; Currie, R; D'Ambrosio, C; Da Cunha Marinho, F; Dall'Occo, E; Dalseno, J; David, P N Y; Davis, A; De Aguiar Francisco, O; De Bruyn, K; De Capua, S; De Cian, M; De Miranda, J M; De Paula, L; De Serio, M; De Simone, P; Dean, C T; Decamp, D; Deckenhoff, M; Del Buono, L; Demmer, M; Dendek, A; Derkach, D; Deschamps, O; Dettori, F; Dey, B; Di Canto, A; Dijkstra, H; Dordei, F; Dorigo, M; Dosil Suárez, A; Dovbnya, A; Dreimanis, K; Dufour, L; Dujany, G; Dungs, K; Durante, P; Dzhelyadin, R; Dziurda, A; Dzyuba, A; Déléage, N; Easo, S; Ebert, M; Egede, U; Egorychev, V; Eidelman, S; Eisenhardt, S; Eitschberger, U; Ekelhof, R; Eklund, L; Elsasser, Ch; Ely, S; Esen, S; Evans, H M; Evans, T; Falabella, A; Farley, N; Farry, S; Fay, R; Fazzini, D; Ferguson, D; Fernandez Prieto, A; Ferrari, F; Ferreira Rodrigues, F; Ferro-Luzzi, M; Filippov, S; Fini, R A; Fiore, M; Fiorini, M; Firlej, M; Fitzpatrick, C; Fiutowski, T; Fleuret, F; Fohl, K; Fontana, M; Fontanelli, F; Forshaw, D C; Forty, R; Franco Lima, V; Frank, M; Frei, C; Fu, J; Furfaro, E; Färber, C; Gallas Torreira, A; Galli, D; Gallorini, S; Gambetta, S; Gandelman, M; Gandini, P; Gao, Y; Garcia Martin, L M; García Pardiñas, J; Garra Tico, J; Garrido, L; Garsed, P J; Gascon, D; Gaspar, C; Gavardi, L; Gazzoni, G; Gerick, D; Gersabeck, E; Gersabeck, M; Gershon, T; Ghez, Ph; Gianì, S; Gibson, V; Girard, O G; Giubega, L; Gizdov, K; Gligorov, V V; Golubkov, D; Golutvin, A; Gomes, A; Gorelov, I V; Gotti, C; Grabalosa Gándara, M; Graciani Diaz, R; Granado Cardoso, L A; Graugés, E; Graverini, E; Graziani, G; Grecu, A; Griffith, P; Grillo, L; Gruberg Cazon, B R; Grünberg, O; Gushchin, E; Guz, Yu; Gys, T; Göbel, C; Hadavizadeh, T; Hadjivasiliou, C; Haefeli, G; Haen, C; Haines, S C; Hall, S; Hamilton, B; Han, X; Hansmann-Menzemer, S; Harnew, N; Harnew, S T; Harrison, J; Hatch, M; He, J; Head, T; Heister, A; Hennessy, K; Henrard, P; Henry, L; Hernando Morata, J A; van Herwijnen, E; Heß, M; Hicheur, A; Hill, D; Hombach, C; Hopchev, P H; Hulsbergen, W; Humair, T; Hushchyn, M; Hussain, N; Hutchcroft, D; Idzik, M; Ilten, P; Jacobsson, R; Jaeger, A; Jalocha, J; Jans, E; Jawahery, A; Jiang, F; John, M; Johnson, D; Jones, C R; Joram, C; Jost, B; Jurik, N; Kandybei, S; Kanso, W; Karacson, M; Kariuki, J M; Karodia, S; Kecke, M; Kelsey, M; Kenyon, I R; Kenzie, M; Ketel, T; Khairullin, E; Khanji, B; Khurewathanakul, C; Kirn, T; Klaver, S; Klimaszewski, K; Koliiev, S; Kolpin, M; Komarov, I; Koopman, R F; Koppenburg, P; Kosmyntseva, A; Kozeiha, M; Kravchuk, L; Kreplin, K; Kreps, M; Krokovny, P; Kruse, F; Krzemien, W; Kucewicz, W; Kucharczyk, M; Kudryavtsev, V; Kuonen, A K; Kurek, K; Kvaratskheliya, T; Lacarrere, D; Lafferty, G; Lai, A; Lambert, D; Lanfranchi, G; Langenbruch, C; Latham, T; Lazzeroni, C; Le Gac, R; van Leerdam, J; Lees, J-P; Leflat, A; Lefrançois, J; Lefèvre, R; Lemaitre, F; Lemos Cid, E; Leroy, O; Lesiak, T; Leverington, B; Li, Y; Likhomanenko, T; Lindner, R; Linn, C; Lionetto, F; Liu, B; Liu, X; Loh, D; Longstaff, I; Lopes, J H; Lucchesi, D; Lucio Martinez, M; Luo, H; Lupato, A; Luppi, E; Lupton, O; Lusiani, A; Lyu, X; Machefert, F; Maciuc, F; Maev, O; Maguire, K; Malde, S; Malinin, A; Maltsev, T; Manca, G; Mancinelli, G; Manning, P; Maratas, J; Marchand, J F; Marconi, U; Marin Benito, C; Marino, P; Marks, J; Martellotti, G; Martin, M; Martinelli, M; Martinez Santos, D; Martinez Vidal, F; Martins Tostes, D; Massacrier, L M; Massafferri, A; Matev, R; Mathad, A; Mathe, Z; Matteuzzi, C; Mauri, A; Maurin, B; Mazurov, A; McCann, M; McCarthy, J; McNab, A; McNulty, R; Meadows, B; Meier, F; Meissner, M; Melnychuk, D; Merk, M; Merli, A; Michielin, E; Milanes, D A; Minard, M-N; Mitzel, D S; Mogini, A; Molina Rodriguez, J; Monroy, I A; Monteil, S; Morandin, M; Morawski, P; Mordà, A; Morello, M J; Moron, J; Morris, A B; Mountain, R; Muheim, F; Mulder, M; Mussini, M; Müller, D; Müller, J; Müller, K; Müller, V; Naik, P; Nakada, T; Nandakumar, R; Nandi, A; Nasteva, I; Needham, M; Neri, N; Neubert, S; Neufeld, N; Neuner, M; Nguyen, A D; Nguyen, T D; Nguyen-Mau, C; Nieswand, S; Niet, R; Nikitin, N; Nikodem, T; Novoselov, A; O'Hanlon, D P; Oblakowska-Mucha, A; Obraztsov, V; Ogilvy, S; Oldeman, R; Onderwater, C J G; Otalora Goicochea, J M; Otto, A; Owen, P; Oyanguren, A; Pais, P R; Palano, A; Palombo, F; Palutan, M; Panman, J; Papanestis, A; Pappagallo, M; Pappalardo, L L; Parker, W; Parkes, C; Passaleva, G; Pastore, A; Patel, G D; Patel, M; Patrignani, C; Pearce, A; Pellegrino, A; Penso, G; Pepe Altarelli, M; Perazzini, S; Perret, P; Pescatore, L; Petridis, K; Petrolini, A; Petrov, A; Petruzzo, M; Picatoste Olloqui, E; Pietrzyk, B; Pikies, M; Pinci, D; Pistone, A; Piucci, A; Playfer, S; Plo Casasus, M; Poikela, T; Polci, F; Poluektov, A; Polyakov, I; Polycarpo, E; Pomery, G J; Popov, A; Popov, D; Popovici, B; Poslavskii, S; Potterat, C; Price, E; Price, J D; Prisciandaro, J; Pritchard, A; Prouve, C; Pugatch, V; Puig Navarro, A; Punzi, G; Qian, W; Quagliani, R; Rachwal, B; Rademacker, J H; Rama, M; Ramos Pernas, M; Rangel, M S; Raniuk, I; Ratnikov, F; Raven, G; Redi, F; Reichert, S; Dos Reis, A C; Remon Alepuz, C; Renaudin, V; Ricciardi, S; Richards, S; Rihl, M; Rinnert, K; Rives Molina, V; Robbe, P; Rodrigues, A B; Rodrigues, E; Rodriguez Lopez, J A; Rodriguez Perez, P; Rogozhnikov, A; Roiser, S; Rollings, A; Romanovskiy, V; Romero Vidal, A; Ronayne, J W; Rotondo, M; Rudolph, M S; Ruf, T; Ruiz Valls, P; Saborido Silva, J J; Sadykhov, E; Sagidova, N; Saitta, B; Salustino Guimaraes, V; Sanchez Mayordomo, C; Sanmartin Sedes, B; Santacesaria, R; Santamarina Rios, C; Santimaria, M; Santovetti, E; Sarti, A; Satriano, C; Satta, A; Saunders, D M; Savrina, D; Schael, S; Schellenberg, M; Schiller, M; Schindler, H; Schlupp, M; Schmelling, M; Schmelzer, T; Schmidt, B; Schneider, O; Schopper, A; Schubert, K; Schubiger, M; Schune, M-H; Schwemmer, R; Sciascia, B; Sciubba, A; Semennikov, A; Sergi, A; Serra, N; Serrano, J; Sestini, L; Seyfert, P; Shapkin, M; Shapoval, I; Shcheglov, Y; Shears, T; Shekhtman, L; Shevchenko, V; Shires, A; Siddi, B G; Silva Coutinho, R; Silva de Oliveira, L; Simi, G; Simone, S; Sirendi, M; Skidmore, N; Skwarnicki, T; Smith, E; Smith, I T; Smith, J; Smith, M; Snoek, H; Sokoloff, M D; Soler, F J P; Souza De Paula, B; Spaan, B; Spradlin, P; Sridharan, S; Stagni, F; Stahl, M; Stahl, S; Stefko, P; Stefkova, S; Steinkamp, O; Stemmle, S; Stenyakin, O; Stevenson, S; Stoica, S; Stone, S; Storaci, B; Stracka, S; Straticiuc, M; Straumann, U; Sun, L; Sutcliffe, W; Swientek, K; Syropoulos, V; Szczekowski, M; Szumlak, T; T'Jampens, S; Tayduganov, A; Tekampe, T; Teklishyn, M; Tellarini, G; Teubert, F; Thomas, E; van Tilburg, J; Tilley, M J; Tisserand, V; Tobin, M; Tolk, S; Tomassetti, L; Tonelli, D; Topp-Joergensen, S; Toriello, F; Tournefier, E; Tourneur, S; Trabelsi, K; Traill, M; Tran, M T; Tresch, M; Trisovic, A; Tsaregorodtsev, A; Tsopelas, P; Tully, A; Tuning, N; Ukleja, A; Ustyuzhanin, A; Uwer, U; Vacca, C; Vagnoni, V; Valassi, A; Valat, S; Valenti, G; Vallier, A; Vazquez Gomez, R; Vazquez Regueiro, P; Vecchi, S; van Veghel, M; Velthuis, J J; Veltri, M; Veneziano, G; Venkateswaran, A; Vernet, M; Vesterinen, M; Viaud, B; Vieira, D; Vieites Diaz, M; Vilasis-Cardona, X; Volkov, V; Vollhardt, A; Voneki, B; Vorobyev, A; Vorobyev, V; Voß, C; de Vries, J A; Vázquez Sierra, C; Waldi, R; Wallace, C; Wallace, R; Walsh, J; Wang, J; Ward, D R; Wark, H M; Watson, N K; Websdale, D; Weiden, A; Whitehead, M; Wicht, J; Wilkinson, G; Wilkinson, M; Williams, M; Williams, M P; Williams, M; Williams, T; Wilson, F F; Wimberley, J; Wishahi, J; Wislicki, W; Witek, M; Wormser, G; Wotton, S A; Wraight, K; Wyllie, K; Xie, Y; Xu, Z; Yang, Z; Yin, H; Yu, J; Yuan, X; Yushchenko, O; Zarebski, K A; Zavertyaev, M; Zhang, L; Zhang, Y; Zhelezov, A; Zheng, Y; Zhokhov, A; Zhu, X; Zhukov, V; Zucchelli, S

2017-01-01

Two new algorithms for use in the analysis of [Formula: see text] collision are developed to identify the flavour of [Formula: see text] mesons at production using pions and protons from the hadronization process. The algorithms are optimized and calibrated on data, using [Formula: see text] decays from [Formula: see text] collision data collected by LHCb at centre-of-mass energies of 7 and 8 TeV . The tagging power of the new pion algorithm is 60% greater than the previously available one; the algorithm using protons to identify the flavour of a [Formula: see text] meson is the first of its kind.

Evaluation of an automated single-channel sleep staging algorithm

Directory of Open Access Journals (Sweden)

Wang Y

2015-09-01

Full Text Available Ying Wang,1 Kenneth A Loparo,1,2 Monica R Kelly,3 Richard F Kaplan1 1General Sleep Corporation, Euclid, OH, 2Department of Electrical Engineering and Computer Science, Case Western Reserve University, Cleveland, OH, 3Department of Psychology, University of Arizona, Tucson, AZ, USA Background: We previously published the performance evaluation of an automated electroencephalography (EEG-based single-channel sleep–wake detection algorithm called Z-ALG used by the Zmachine® sleep monitoring system. The objective of this paper is to evaluate the performance of a new algorithm called Z-PLUS, which further differentiates sleep as detected by Z-ALG into Light Sleep, Deep Sleep, and Rapid Eye Movement (REM Sleep, against laboratory polysomnography (PSG using a consensus of expert visual scorers. Methods: Single night, in-lab PSG recordings from 99 subjects (52F/47M, 18–60 years, median age 32.7 years, including both normal sleepers and those reporting a variety of sleep complaints consistent with chronic insomnia, sleep apnea, and restless leg syndrome, as well as those taking selective serotonin reuptake inhibitor/serotonin–norepinephrine reuptake inhibitor antidepressant medications, previously evaluated using Z-ALG were re-examined using Z-PLUS. EEG data collected from electrodes placed at the differential-mastoids (A1–A2 were processed by Z-ALG to determine wake and sleep, then those epochs detected as sleep were further processed by Z-PLUS to differentiate into Light Sleep, Deep Sleep, and REM. EEG data were visually scored by multiple certified polysomnographic technologists according to the Rechtschaffen and Kales criterion, and then combined using a majority-voting rule to create a PSG Consensus score file for each of the 99 subjects. Z-PLUS output was compared to the PSG Consensus score files for both epoch-by-epoch (eg, sensitivity, specificity, and kappa and sleep stage-related statistics (eg, Latency to Deep Sleep, Latency to REM

Expeditious 3D poisson vlasov algorithm applied to ion extraction from a plasma

International Nuclear Information System (INIS)

Whealton, J.H.; McGaffey, R.W.; Meszaros, P.S.

1983-01-01

A new 3D Poisson Vlasov algorithm is under development which differs from a previous algorithm, referenced in this paper, in two respects: the mesh lines are cartesian, and the Poisson equation is solved iteratively. The resulting algorithm has been used to examine the same boundary value problem as considered in the earlier algorithm except that the number of nodes is 2 times greater. The same physical results were obtained except the computational time was reduced by a factor of 60 and the memory requirement was reduced by a factor of 10. This algorithm at present restricts Neumann boundary conditions to orthogonal planes lying along mesh lines. No such restriction applies to Dirichlet boundaries. An emittance diagram is shown below where those points lying on the y = 0 line start on the axis of symmetry and those near the y = 1 line start near the slot end

Electrons, Electronic Publishing, and Electronic Display.

Science.gov (United States)

Brownrigg, Edwin B.; Lynch, Clifford A.

1985-01-01

Provides a perspective on electronic publishing by distinguishing between "Newtonian" publishing and "quantum-mechanical" publishing. Highlights include media and publishing, works delivered through electronic media, electronic publishing and the printed word, management of intellectual property, and recent copyright-law issues…

Improved quantum backtracking algorithms using effective resistance estimates

Science.gov (United States)

Jarret, Michael; Wan, Kianna

2018-02-01

We investigate quantum backtracking algorithms of the type introduced by Montanaro (Montanaro, arXiv:1509.02374). These algorithms explore trees of unknown structure and in certain settings exponentially outperform their classical counterparts. Some of the previous work focused on obtaining a quantum advantage for trees in which a unique marked vertex is promised to exist. We remove this restriction by recharacterizing the problem in terms of the effective resistance of the search space. In this paper, we present a generalization of one of Montanaro's algorithms to trees containing k marked vertices, where k is not necessarily known a priori. Our approach involves using amplitude estimation to determine a near-optimal weighting of a diffusion operator, which can then be applied to prepare a superposition state with support only on marked vertices and ancestors thereof. By repeatedly sampling this state and updating the input vertex, a marked vertex is reached in a logarithmic number of steps. The algorithm thereby achieves the conjectured bound of O ˜(√{T Rmax }) for finding a single marked vertex and O ˜(k √{T Rmax }) for finding all k marked vertices, where T is an upper bound on the tree size and Rmax is the maximum effective resistance encountered by the algorithm. This constitutes a speedup over Montanaro's original procedure in both the case of finding one and the case of finding multiple marked vertices in an arbitrary tree.

Nature-inspired optimization algorithms

CERN Document Server

Yang, Xin-She

2014-01-01

Nature-Inspired Optimization Algorithms provides a systematic introduction to all major nature-inspired algorithms for optimization. The book's unified approach, balancing algorithm introduction, theoretical background and practical implementation, complements extensive literature with well-chosen case studies to illustrate how these algorithms work. Topics include particle swarm optimization, ant and bee algorithms, simulated annealing, cuckoo search, firefly algorithm, bat algorithm, flower algorithm, harmony search, algorithm analysis, constraint handling, hybrid methods, parameter tuning

PUBLISHER'S ANNOUNCEMENT: Refereeing standards

Science.gov (United States)

Bender, C.; Scriven, N.

2004-08-01

On 1 January 2004 I will be assuming the position of Editor-in-Chief of Journal of Physics A: Mathematical and General (J. Phys. A). I am flattered at the confidence expressed in my ability to carry out this challenging job and I will try hard to justify this confidence. The previous Editor-in-Chief, Ed Corrigan, has worked tirelessly for the last five years and has done an excellent job for the journal. Everyone at the journal is profoundly grateful for his leadership and for his achievements. Before accepting the position of Editor-in-Chief, I visited the office of J. Phys. A to examine the organization and to assess its strengths and weaknesses. This office is located at the Institute of Physics Publishing (IOPP) headquarters in Bristol. J. Phys. A has been expanding rapidly and now publishes at the rate of nearly 1000 articles (or about 14,000 pages) per year. The entire operation of the journal is conducted in a very small space---about 15 square metres! Working in this space are six highly intelligent, talented, hard working, and dedicated people: Neil Scriven, Publisher; Mike Williams, Publishing Editor; Rose Gray and Sarah Nadin, Publishing Administrators; Laura Smith and Steve Richards, Production Editors. In this small space every day about eight submitted manuscripts are downloaded from the computer or received in the post. These papers are then processed and catalogued, referees are selected, and the papers are sent out for evaluation. In this small space the referees' reports are received, publication decisions are made, and accepted articles are then published quickly by IOPP. The whole operation is amazingly efficient. Indeed, one of the great strengths of J. Phys. A is the speed at which papers are processed. The average time between the receipt of a manuscript and an editorial decision is under sixty days. (Many distinguished journals take three to five times this amount of time.) This speed of publication is an extremely strong enticement for

Toxoplasma gondii and schizophrenia: a review of published RCTs.

Science.gov (United States)

Chorlton, Sam D

2017-07-01

Over the last 60 years, accumulating evidence has suggested that acute, chronic, and maternal Toxoplasma gondii infections predispose to schizophrenia. More recent evidence suggests that chronically infected patients with schizophrenia present with more severe disease. After acute infection, parasites form walled cysts in the brain, leading to lifelong chronic infection and drug resistance to commonly used antiparasitics. Chronic infection is the most studied and closely linked with development and severity of schizophrenia. There are currently four published randomized controlled trials evaluating antiparasitic drugs, specifically azithromycin, trimethoprim, artemisinin, and artemether, in patients with schizophrenia. No trials have demonstrated a change in psychopathology with adjunctive treatment. Published trials have either selected drugs without evidence against chronic infection or used them at doses too low to reduce brain cyst burden. Furthermore, trials have failed to achieve sufficient power or account for confounders such as previous antipsychotic treatment, sex, age, or rhesus status on antiparasitic effect. There are currently no ongoing trials of anti-Toxoplasma therapy in schizophrenia despite ample evidence to justify further testing.

Convex hull ranking algorithm for multi-objective evolutionary algorithms

NARCIS (Netherlands)

Davoodi Monfrared, M.; Mohades, A.; Rezaei, J.

2012-01-01

Due to many applications of multi-objective evolutionary algorithms in real world optimization problems, several studies have been done to improve these algorithms in recent years. Since most multi-objective evolutionary algorithms are based on the non-dominated principle, and their complexity

An improved algorithm for MFR fragment assembly

International Nuclear Information System (INIS)

Kontaxis, Georg

2012-01-01

A method for generating protein backbone models from backbone only NMR data is presented, which is based on molecular fragment replacement (MFR). In a first step, the PDB database is mined for homologous peptide fragments using experimental backbone-only data i.e. backbone chemical shifts (CS) and residual dipolar couplings (RDC). Second, this fragment library is refined against the experimental restraints. Finally, the fragments are assembled into a protein backbone fold using a rigid body docking algorithm using the RDCs as restraints. For improved performance, backbone nuclear Overhauser effects (NOEs) may be included at that stage. Compared to previous implementations of MFR-derived structure determination protocols this model-building algorithm offers improved stability and reliability. Furthermore, relative to CS-ROSETTA based methods, it provides faster performance and straightforward implementation with the option to easily include further types of restraints and additional energy terms.

A spectral algorithm for the seriation problem

Energy Technology Data Exchange (ETDEWEB)

Atkins, J.E. [Michigan Univ., Ann Arbor, MI (United States). Dept. of Mathematics; Boman, E.G. [Stanford Univ., CA (United States). Dept. of Computer Science; Hendrickson, B. [Sandia National Labs., Albuquerque, NM (United States)

1994-11-01

Given a set of objects and a correlation function f reflecting the desire for two items to be near each other, find all sequences {pi} of the items so that correlation preferences are preserved; that is if {pi}(i) < {pi}(j) < {pi}(k) then f(i,j) {ge} f(i,k) and f(j,k) {ge} f(i,k). This seriation problem has numerous applications, for instance, solving it yields a solution to the consecutive ones problem. We present a spectral algorithm for this problem that has a number of interesting features. Whereas most previous applications of spectral techniques provided bounds or heuristics, our result is an algorithm for a nontrivial combinatorial problem. Our analysis introduces powerful tools from matrix theory to the theoretical computer science community. Also, spectral methods are being applied as heuristics for a variety of sequencing problems and our result helps explain and justify these applications. Although the worst case running time for our approach is not competitive with that of existing methods for well posed problem instances, unlike combinatorial approaches our algorithm remains a credible heuristic for the important cases where there are errors in the data.

Total algorithms

NARCIS (Netherlands)

Tel, G.

We define the notion of total algorithms for networks of processes. A total algorithm enforces that a "decision" is taken by a subset of the processes, and that participation of all processes is required to reach this decision. Total algorithms are an important building block in the design of

An Efficient Meta Heuristic Algorithm to Solve Economic Load Dispatch Problems

Directory of Open Access Journals (Sweden)

R Subramanian

2013-12-01

Full Text Available The Economic Load Dispatch (ELD problems in power generation systems are to reduce the fuel cost by reducing the total cost for the generation of electric power. This paper presents an efficient Modified Firefly Algorithm (MFA, for solving ELD Problem. The main objective of the problems is to minimize the total fuel cost of the generating units having quadratic cost functions subjected to limits on generator true power output and transmission losses. The MFA is a stochastic, Meta heuristic approach based on the idealized behaviour of the flashing characteristics of fireflies. This paper presents an application of MFA to ELD for six generator test case system. MFA is applied to ELD problem and compared its solution quality and computation efficiency to Genetic algorithm (GA, Differential Evolution (DE, Particle swarm optimization (PSO, Artificial Bee Colony optimization (ABC, Biogeography-Based Optimization (BBO, Bacterial Foraging optimization (BFO, Firefly Algorithm (FA techniques. The simulation result shows that the proposed algorithm outperforms previous optimization methods.

HPC-NMF: A High-Performance Parallel Algorithm for Nonnegative Matrix Factorization

Energy Technology Data Exchange (ETDEWEB)

2016-08-22

NMF is a useful tool for many applications in different domains such as topic modeling in text mining, background separation in video analysis, and community detection in social networks. Despite its popularity in the data mining community, there is a lack of efficient distributed algorithms to solve the problem for big data sets. We propose a high-performance distributed-memory parallel algorithm that computes the factorization by iteratively solving alternating non-negative least squares (NLS) subproblems for $\\WW$ and $\\HH$. It maintains the data and factor matrices in memory (distributed across processors), uses MPI for interprocessor communication, and, in the dense case, provably minimizes communication costs (under mild assumptions). As opposed to previous implementation, our algorithm is also flexible: It performs well for both dense and sparse matrices, and allows the user to choose any one of the multiple algorithms for solving the updates to low rank factors $\\WW$ and $\\HH$ within the alternating iterations.

Dear Publisher.

Science.gov (United States)

Chelton, Mary K.

1992-01-01

Addresses issues that concern the relationship between publishers and librarians, including differences between libraries and bookstores; necessary information for advertisements; out-of-stock designations and their effect on budgets; the role of distributors and vendors; direct mail for book promotions; unsolicited review copies; communications…

Publisher Correction

DEFF Research Database (Denmark)

Stokholm, Jakob; Blaser, Martin J.; Thorsen, Jonathan

2018-01-01

The originally published version of this Article contained an incorrect version of Figure 3 that was introduced following peer review and inadvertently not corrected during the production process. Both versions contain the same set of abundance data, but the incorrect version has the children...

In-depth analysis of protein inference algorithms using multiple search engines and well-defined metrics.

Science.gov (United States)

Audain, Enrique; Uszkoreit, Julian; Sachsenberg, Timo; Pfeuffer, Julianus; Liang, Xiao; Hermjakob, Henning; Sanchez, Aniel; Eisenacher, Martin; Reinert, Knut; Tabb, David L; Kohlbacher, Oliver; Perez-Riverol, Yasset

2017-01-06

inference is a crucial step in proteomics data analysis, a comprehensive evaluation of the many different inference methods has never been performed. Previously Journal of proteomics has published multiple studies about other benchmark of bioinformatics algorithms (PMID: 26585461; PMID: 22728601) in proteomics studies making clear the importance of those studies for the proteomics community and the journal audience. This manuscript presents a new bioinformatics solution based on the KNIME/OpenMS platform that aims at providing a fair comparison of protein inference algorithms (https://github.com/KNIME-OMICS). Six different algorithms - ProteinProphet, MSBayesPro, ProteinLP, Fido and PIA- were evaluated using the highly customizable workflow on four public datasets with varying complexities. Five popular database search engines Mascot, X!Tandem, MS-GF+ and combinations thereof were evaluated for every protein inference tool. In total >186 proteins lists were analyzed and carefully compare using three metrics for quality assessments of the protein inference results: 1) the numbers of reported proteins, 2) peptides per protein, and the 3) number of uniquely reported proteins per inference method, to address the quality of each inference method. We also examined how many proteins were reported by choosing each combination of search engines, protein inference algorithms and parameters on each dataset. The results show that using 1) PIA or Fido seems to be a good choice when studying the results of the analyzed workflow, regarding not only the reported proteins and the high-quality identifications, but also the required runtime. 2) Merging the identifications of multiple search engines gives almost always more confident results and increases the number of peptides per protein group. 3) The usage of databases containing not only the canonical, but also known isoforms of proteins has a small impact on the number of reported proteins. The detection of specific isoforms could

Evaluation of downwelling diffuse attenuation coefficient algorithms in the Red Sea

KAUST Repository

Tiwari, Surya Prakash

2016-05-07

Despite the importance of the optical properties such as the downwelling diffuse attenuation coefficient for characterizing the upper water column, until recently no in situ optical measurements were published for the Red Sea. Kirby et al. used observations from the Coastal Zone Color Scanner to characterize the spatial and temporal variability of the diffuse attenuation coefficient (Kd(490)) in the Red Sea. To better understand optical variability and its utility in the Red Sea, it is imperative to comprehend the diffuse attenuation coefficient and its relationship with in situ properties. Two apparent optical properties, spectral remote sensing reflectance (Rrs) and the downwelling diffuse attenuation coefficient (Kd), are calculated from vertical profile measurements of downwelling irradiance (Ed) and upwelling radiance (Lu). Kd characterizes light penetration into water column that is important for understanding both the physical and biogeochemical environment, including water quality and the health of ocean environment. Our study tests the performance of the existing Kd(490) algorithms in the Red Sea and compares them against direct in situ measurements within various subdivisions of the Red Sea. Most standard algorithms either overestimated or underestimated with the measured in situ values of Kd. Consequently, these algorithms provided poor retrieval of Kd(490) for the Red Sea. Random errors were high for all algorithms and the correlation coefficients (r2) with in situ measurements were quite low. Hence, these algorithms may not be suitable for the Red Sea. Overall, statistical analyses of the various algorithms indicated that the existing algorithms are inadequate for the Red Sea. The present study suggests that reparameterizing existing algorithms or developing new regional algorithms is required to improve retrieval of Kd(490) for the Red Sea. © (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is

EPIC: Electronic Publishing is Cheaper.

Science.gov (United States)

Regier, Willis G.

Advocates of inexpensive publishing confront a widespread complaint that there is already an overproduction of scholarship that electronic publishing will make worse. The costs of electronic publishing correlate to a clutch of choices: speeds of access, breadth and depth of content, visibility, flexibility, durability, dependability, definition of…

NDPA: A generalized efficient parallel in-place N-Dimensional Permutation Algorithm

Directory of Open Access Journals (Sweden)

Muhammad Elsayed Ali

2015-09-01

Full Text Available N-dimensional transpose/permutation is a very important operation in many large-scale data intensive and scientific applications. These applications include but not limited to oil industry i.e. seismic data processing, nuclear medicine, media production, digital signal processing and business intelligence. This paper proposes an efficient in-place N-dimensional permutation algorithm. The algorithm is based on a novel 3D transpose algorithm that was published recently. The proposed algorithm has been tested on 3D, 4D, 5D, 6D and 7D data sets as a proof of concept. This is the first contribution which is breaking the dimensions’ limitation of the base algorithm. The suggested algorithm exploits the idea of mixing both logical and physical permutations together. In the logical permutation, the address map is transposed for each data unit access. In the physical permutation, actual data elements are swapped. Both permutation levels exploit the fast on-chip memory bandwidth by transferring large amount of data and allowing for fine-grain SIMD (Single Instruction, Multiple Data operations. Thus, the performance is improved as evident from the experimental results section. The algorithm is implemented on NVidia GeForce GTS 250 GPU (Graphics Processing Unit containing 128 cores. The rapid increase in GPUs performance coupled with the recent and continuous improvements in its programmability proved that GPUs are the right choice for computationally demanding tasks. The use of GPUs is the second contribution which reflects how strongly they fit for high performance tasks. The third contribution is improving the proposed algorithm performance to its peak as discussed in the results section.

Desktop Publishing for Counselors.

Science.gov (United States)

Lucking, Robert; Mitchum, Nancy

1990-01-01

Discusses the fundamentals of desktop publishing for counselors, including hardware and software systems and peripherals. Notes by using desktop publishing, counselors can produce their own high-quality documents without the expense of commercial printers. Concludes computers present a way of streamlining the communications of a counseling…

About this Publishing System

African Journals Online (AJOL)

This journal uses Open Journal Systems 2.4.3.0, which is open source journal management and publishing software developed, supported, and freely distributed by the Public Knowledge Project under the GNU General Public License. OJS Editorial and Publishing Process. ISSN: 1596-6798. AJOL African Journals Online.

About this Publishing System

African Journals Online (AJOL)

This journal uses Open Journal Systems 2.4.3.0, which is open source journal management and publishing software developed, supported, and freely distributed by the Public Knowledge Project under the GNU General Public License. OJS Editorial and Publishing Process. ISSN: 1115-2613. AJOL African Journals Online.

About this Publishing System

African Journals Online (AJOL)

This journal uses Open Journal Systems 2.4.3.0, which is open source journal management and publishing software developed, supported, and freely distributed by the Public Knowledge Project under the GNU General Public License. OJS Editorial and Publishing Process. ISSN: 0856-7212. AJOL African Journals Online.

About this Publishing System