Heng-Yi Su
2016-11-01
Full Text Available This paper proposes an efficient approach for the computation of voltage stability margin (VSM in a large-scale power grid. The objective is to accurately and rapidly determine the load power margin which corresponds to voltage collapse phenomena. The proposed approach is based on the impedance match-based technique and the model-based technique. It combines the Thevenin equivalent (TE network method with cubic spline extrapolation technique and the continuation technique to achieve fast and accurate VSM computation for a bulk power grid. Moreover, the generator Q limits are taken into account for practical applications. Extensive case studies carried out on Institute of Electrical and Electronics Engineers (IEEE benchmark systems and the Taiwan Power Company (Taipower, Taipei, Taiwan system are used to demonstrate the effectiveness of the proposed approach.
Mehmani, Yashar; Oostrom, Mart; Balhoff, Matthew T.
2014-03-01
Several approaches have been developed in the literature for solving flow and transport at the pore scale. Some authors use a direct modeling approach where the fundamental flow and transport equations are solved on the actual pore-space geometry. Such direct modeling, while very accurate, comes at a great computational cost. Network models are computationally more efficient because the pore-space morphology is approximated. Typically, a mixed cell method (MCM) is employed for solving the flow and transport system which assumes pore-level perfect mixing. This assumption is invalid at moderate to high Peclet regimes. In this work, a novel Eulerian perspective on modeling flow and transport at the pore scale is developed. The new streamline splitting method (SSM) allows for circumventing the pore-level perfect-mixing assumption, while maintaining the computational efficiency of pore-network models. SSM was verified with direct simulations and validated against micromodel experiments; excellent matches were obtained across a wide range of pore-structure and fluid-flow parameters. The increase in the computational cost from MCM to SSM is shown to be minimal, while the accuracy of SSM is much higher than that of MCM and comparable to direct modeling approaches. Therefore, SSM can be regarded as an appropriate balance between incorporating detailed physics and controlling computational cost. The truly predictive capability of the model allows for the study of pore-level interactions of fluid flow and transport in different porous materials. In this paper, we apply SSM and MCM to study the effects of pore-level mixing on transverse dispersion in 3-D disordered granular media.
Accurate computation of Mathieu functions
Bibby, Malcolm M
2013-01-01
This lecture presents a modern approach for the computation of Mathieu functions. These functions find application in boundary value analysis such as electromagnetic scattering from elliptic cylinders and flat strips, as well as the analogous acoustic and optical problems, and many other applications in science and engineering. The authors review the traditional approach used for these functions, show its limitations, and provide an alternative ""tuned"" approach enabling improved accuracy and convergence. The performance of this approach is investigated for a wide range of parameters and mach
Chang, Chih-Hao; Liou, Meng-Sing
2007-07-01
In this paper, we propose a new approach to compute compressible multifluid equations. Firstly, a single-pressure compressible multifluid model based on the stratified flow model is proposed. The stratified flow model, which defines different fluids in separated regions, is shown to be amenable to the finite volume method. We can apply the conservation law to each subregion and obtain a set of balance equations . Secondly, the AUSM + scheme, which is originally designed for the compressible gas flow, is extended to solve compressible liquid flows. By introducing additional dissipation terms into the numerical flux, the new scheme, called AUSM +-up, can be applied to both liquid and gas flows. Thirdly, the contribution to the numerical flux due to interactions between different phases is taken into account and solved by the exact Riemann solver. We will show that the proposed approach yields an accurate and robust method for computing compressible multiphase flows involving discontinuities, such as shock waves and fluid interfaces. Several one-dimensional test problems are used to demonstrate the capability of our method, including the Ransom's water faucet problem and the air-water shock tube problem. Finally, several two dimensional problems will show the capability to capture enormous details and complicated wave patterns in flows having large disparities in the fluid density and velocities, such as interactions between water shock wave and air bubble, between air shock wave and water column(s), and underwater explosion. However, conservative form is lost in these balance equations when considering each individual phase; in fact, the interactions that exist simultaneously in both phases manifest themselves as nonconservative terms.
Schirle, M; Weinschenk, T; Stevanović, S
2001-11-01
The identification of T cell epitopes from immunologically relevant antigens remains a critical step in the development of vaccines and methods for monitoring of T cell responses. This review presents an overview of strategies that employ computer algorithms for the selection of candidate peptides from defined proteins and subsequent verification of their in vivo relevance by experimental approaches. Several computer algorithms are currently being used for epitope prediction of various major histocompatibility complex (MHC) class I and II molecules, based either on the analysis of natural MHC ligands or on the binding properties of synthetic peptides. Moreover, the analysis of proteasomal digests of peptides and whole proteins has led to the development of algorithms for the prediction of proteasomal cleavages. In order to verify the generation of the predicted peptides during antigen processing in vivo as well as their immunogenic potential, several experimental approaches have been pursued in the recent past. Mass spectrometry-based bioanalytical approaches have been used specifically to detect predicted peptides among isolated natural ligands. Other strategies employ various methods for the stimulation of primary T cell responses against the predicted peptides and subsequent testing of the recognition pattern towards target cells that express the antigen.
Zimmermann, Ralf
2014-01-01
) in an offline stage. The claimed trajectory is obtained locally by interpolating the given local subspaces considered as sample points in the Grassmann manifold. It is shown that the manifold interpolation technique is subject to certain restrictions. Moreover, it turns out that the application of computing...... under a sinusoidal pitching motion....
Wiktor, Julia; Jomard, Gérald; Torrent, Marc
2015-09-01
Many techniques have been developed in the past in order to compute positron lifetimes in materials from first principles. However, there is still a lack of a fast and accurate self-consistent scheme that could handle accurately the forces acting on the ions induced by the presence of the positron. We will show in this paper that we have reached this goal by developing the two-component density functional theory within the projector augmented-wave (PAW) method in the open-source code abinit. This tool offers the accuracy of the all-electron methods with the computational efficiency of the plane-wave ones. We can thus deal with supercells that contain few hundreds to thousands of atoms to study point defects as well as more extended defects clusters. Moreover, using the PAW basis set allows us to use techniques able to, for instance, treat strongly correlated systems or spin-orbit coupling, which are necessary to study heavy elements, such as the actinides or their compounds.
Accurate emulators for large-scale computer experiments
Haaland, Ben; 10.1214/11-AOS929
2012-01-01
Large-scale computer experiments are becoming increasingly important in science. A multi-step procedure is introduced to statisticians for modeling such experiments, which builds an accurate interpolator in multiple steps. In practice, the procedure shows substantial improvements in overall accuracy, but its theoretical properties are not well established. We introduce the terms nominal and numeric error and decompose the overall error of an interpolator into nominal and numeric portions. Bounds on the numeric and nominal error are developed to show theoretically that substantial gains in overall accuracy can be attained with the multi-step approach.
Accurate paleointensities - the multi-method approach
de Groot, Lennart
2016-04-01
The accuracy of models describing rapid changes in the geomagnetic field over the past millennia critically depends on the availability of reliable paleointensity estimates. Over the past decade methods to derive paleointensities from lavas (the only recorder of the geomagnetic field that is available all over the globe and through geologic times) have seen significant improvements and various alternative techniques were proposed. The 'classical' Thellier-style approach was optimized and selection criteria were defined in the 'Standard Paleointensity Definitions' (Paterson et al, 2014). The Multispecimen approach was validated and the importance of additional tests and criteria to assess Multispecimen results must be emphasized. Recently, a non-heating, relative paleointensity technique was proposed -the pseudo-Thellier protocol- which shows great potential in both accuracy and efficiency, but currently lacks a solid theoretical underpinning. Here I present work using all three of the aforementioned paleointensity methods on suites of young lavas taken from the volcanic islands of Hawaii, La Palma, Gran Canaria, Tenerife, and Terceira. Many of the sampled cooling units are <100 years old, the actual field strength at the time of cooling is therefore reasonably well known. Rather intuitively, flows that produce coherent results from two or more different paleointensity methods yield the most accurate estimates of the paleofield. Furthermore, the results for some flows pass the selection criteria for one method, but fail in other techniques. Scrutinizing and combing all acceptable results yielded reliable paleointensity estimates for 60-70% of all sampled cooling units - an exceptionally high success rate. This 'multi-method paleointensity approach' therefore has high potential to provide the much-needed paleointensities to improve geomagnetic field models for the Holocene.
Accurate atom-mapping computation for biochemical reactions.
Latendresse, Mario; Malerich, Jeremiah P; Travers, Mike; Karp, Peter D
2012-11-26
The complete atom mapping of a chemical reaction is a bijection of the reactant atoms to the product atoms that specifies the terminus of each reactant atom. Atom mapping of biochemical reactions is useful for many applications of systems biology, in particular for metabolic engineering where synthesizing new biochemical pathways has to take into account for the number of carbon atoms from a source compound that are conserved in the synthesis of a target compound. Rapid, accurate computation of the atom mapping(s) of a biochemical reaction remains elusive despite significant work on this topic. In particular, past researchers did not validate the accuracy of mapping algorithms. We introduce a new method for computing atom mappings called the minimum weighted edit-distance (MWED) metric. The metric is based on bond propensity to react and computes biochemically valid atom mappings for a large percentage of biochemical reactions. MWED models can be formulated efficiently as Mixed-Integer Linear Programs (MILPs). We have demonstrated this approach on 7501 reactions of the MetaCyc database for which 87% of the models could be solved in less than 10 s. For 2.1% of the reactions, we found multiple optimal atom mappings. We show that the error rate is 0.9% (22 reactions) by comparing these atom mappings to 2446 atom mappings of the manually curated Kyoto Encyclopedia of Genes and Genomes (KEGG) RPAIR database. To our knowledge, our computational atom-mapping approach is the most accurate and among the fastest published to date. The atom-mapping data will be available in the MetaCyc database later in 2012; the atom-mapping software will be available within the Pathway Tools software later in 2012.
Harbusch, Karin; Itsova, Gergana; Koch, Ulrich; Kuhner, Christine
2009-01-01
We built a natural language processing (NLP) system implementing a "virtual writing conference" for elementary-school children, with German as the target language. Currently, state-of-the-art computer support for writing tasks is restricted to multiple-choice questions or quizzes because automatic parsing of the often ambiguous and fragmentary…
Harbusch, Karin; Itsova, Gergana; Koch, Ulrich; Kuhner, Christine
2009-01-01
We built a natural language processing (NLP) system implementing a "virtual writing conference" for elementary-school children, with German as the target language. Currently, state-of-the-art computer support for writing tasks is restricted to multiple-choice questions or quizzes because automatic parsing of the often ambiguous and fragmentary…
Kirk, David Blair
This thesis develops an engineering practice and design methodology to enable us to use CMOS analog VLSI chips to perform more accurate and precise computation. These techniques form the basis of an approach that permits us to build computer graphics and neural network applications using analog VLSI. The nature of the design methodology focuses on defining goals for circuit behavior to be met as part of the design process. To increase the accuracy of analog computation, we develop techniques for creating compensated circuit building blocks, where compensation implies the cancellation of device variations, offsets, and nonlinearities. These compensated building blocks can be used as components in larger and more complex circuits, which can then also be compensated. To this end, we develop techniques for automatically determining appropriate parameters for circuits, using constrained optimization. We also fabricate circuits that implement multi-dimensional gradient estimation for a gradient descent optimization technique. The parameter-setting and optimization tools allow us to automatically choose values for compensating our circuit building blocks, based on our goals for the circuit performance. We can also use the techniques to optimize parameters for larger systems, applying the goal-based techniques hierarchically. We also describe a set of thought experiments involving circuit techniques for increasing the precision of analog computation. Our engineering design methodology is a step toward easier use of analog VLSI to solve problems in computer graphics and neural networks. We provide data measured from compensated multipliers built using these design techniques. To demonstrate the feasibility of using analog VLSI for more quantitative computation, we develop small applications using the goal-based design approach and compensated components. Finally, we conclude by discussing the expected significance of this work for the wider use of analog VLSI for
Measurement of Fracture Geometry for Accurate Computation of Hydraulic Conductivity
Chae, B.; Ichikawa, Y.; Kim, Y.
2003-12-01
Fluid flow in rock mass is controlled by geometry of fractures which is mainly characterized by roughness, aperture and orientation. Fracture roughness and aperture was observed by a new confocal laser scanning microscope (CLSM; Olympus OLS1100). The wavelength of laser is 488nm, and the laser scanning is managed by a light polarization method using two galvano-meter scanner mirrors. The system improves resolution in the light axis (namely z) direction because of the confocal optics. The sampling is managed in a spacing 2.5 μ m along x and y directions. The highest measurement resolution of z direction is 0.05 μ m, which is the more accurate than other methods. For the roughness measurements, core specimens of coarse and fine grained granites were provided. Measurements were performed along three scan lines on each fracture surface. The measured data were represented as 2-D and 3-D digital images showing detailed features of roughness. Spectral analyses by the fast Fourier transform (FFT) were performed to characterize on the roughness data quantitatively and to identify influential frequency of roughness. The FFT results showed that components of low frequencies were dominant in the fracture roughness. This study also verifies that spectral analysis is a good approach to understand complicate characteristics of fracture roughness. For the aperture measurements, digital images of the aperture were acquired under applying five stages of uniaxial normal stresses. This method can characterize the response of aperture directly using the same specimen. Results of measurements show that reduction values of aperture are different at each part due to rough geometry of fracture walls. Laboratory permeability tests were also conducted to evaluate changes of hydraulic conductivities related to aperture variation due to different stress levels. The results showed non-uniform reduction of hydraulic conductivity under increase of the normal stress and different values of
Fast and accurate method for computing ATC with voltage stability
Eidiani, M; Vahedi, E
2002-01-01
Order 889 mandated each control area to computer ATC (Available Transfer Capability) and post them on a communication system called the Open Access Same-time Information System (OASIS). Approaches of computing ATC can be divided into the following groups: Static and Dynamic methods. This paper presents a fast method for ATC calculations with voltage stability termination criteria. We use estimation of the determinant of Jacobian matrix for assessment of voltage stability. This method is compared with these methods: different between energy in SEP (Stable Equilibrium Point) and UEP (Unstable Equilibrium Point), ts index of Dr.Chiang and continuation power flow. The idea are demonstrated on 2, 3, 7 (CIGRE), 10, 30 (IEEE) and 145 bus (Iowa State University).
Automated Development of Accurate Algorithms and Efficient Codes for Computational Aeroacoustics
Goodrich, John W.; Dyson, Rodger W.
1999-01-01
The simulation of sound generation and propagation in three space dimensions with realistic aircraft components is a very large time dependent computation with fine details. Simulations in open domains with embedded objects require accurate and robust algorithms for propagation, for artificial inflow and outflow boundaries, and for the definition of geometrically complex objects. The development, implementation, and validation of methods for solving these demanding problems is being done to support the NASA pillar goals for reducing aircraft noise levels. Our goal is to provide algorithms which are sufficiently accurate and efficient to produce usable results rapidly enough to allow design engineers to study the effects on sound levels of design changes in propulsion systems, and in the integration of propulsion systems with airframes. There is a lack of design tools for these purposes at this time. Our technical approach to this problem combines the development of new, algorithms with the use of Mathematica and Unix utilities to automate the algorithm development, code implementation, and validation. We use explicit methods to ensure effective implementation by domain decomposition for SPMD parallel computing. There are several orders of magnitude difference in the computational efficiencies of the algorithms which we have considered. We currently have new artificial inflow and outflow boundary conditions that are stable, accurate, and unobtrusive, with implementations that match the accuracy and efficiency of the propagation methods. The artificial numerical boundary treatments have been proven to have solutions which converge to the full open domain problems, so that the error from the boundary treatments can be driven as low as is required. The purpose of this paper is to briefly present a method for developing highly accurate algorithms for computational aeroacoustics, the use of computer automation in this process, and a brief survey of the algorithms that
Computational approaches to vision
Barrow, H. G.; Tenenbaum, J. M.
1986-01-01
Vision is examined in terms of a computational process, and the competence, structure, and control of computer vision systems are analyzed. Theoretical and experimental data on the formation of a computer vision system are discussed. Consideration is given to early vision, the recovery of intrinsic surface characteristics, higher levels of interpretation, and system integration and control. A computational visual processing model is proposed and its architecture and operation are described. Examples of state-of-the-art vision systems, which include some of the levels of representation and processing mechanisms, are presented.
Computational approaches to vision
Barrow, H. G.; Tenenbaum, J. M.
1986-01-01
Vision is examined in terms of a computational process, and the competence, structure, and control of computer vision systems are analyzed. Theoretical and experimental data on the formation of a computer vision system are discussed. Consideration is given to early vision, the recovery of intrinsic surface characteristics, higher levels of interpretation, and system integration and control. A computational visual processing model is proposed and its architecture and operation are described. Examples of state-of-the-art vision systems, which include some of the levels of representation and processing mechanisms, are presented.
A Distributed Weighted Voting Approach for Accurate Eye Center Estimation
Gagandeep Singh
2013-05-01
Full Text Available This paper proposes a novel approach for accurate estimation of eye center in face images. A distributed voting based approach in which every pixel votes is adopted for potential eye center candidates. The votes are distributed over a subset of pixels which lie in a direction which is opposite to gradient direction and the weightage of votes is distributed according to a novel mechanism. First, image is normalized to eliminate illumination variations and its edge map is generated using Canny edge detector. Distributed voting is applied on the edge image to generate different eye center candidates. Morphological closing and local maxima search are used to reduce the number of candidates. A classifier based on spatial and intensity information is used to choose the correct candidates for the locations of eye center. The proposed approach was tested on BioID face database and resulted in better Iris detection rate than the state-of-the-art. The proposed approach is robust against illumination variation, small pose variations, presence of eye glasses and partial occlusion of eyes.Defence Science Journal, 2013, 63(3, pp.292-297, DOI:http://dx.doi.org/10.14429/dsj.63.2763
Kearns, F L; Hudson, P S; Boresch, S; Woodcock, H L
2016-01-01
Enzyme activity is inherently linked to free energies of transition states, ligand binding, protonation/deprotonation, etc.; these free energies, and thus enzyme function, can be affected by residue mutations, allosterically induced conformational changes, and much more. Therefore, being able to predict free energies associated with enzymatic processes is critical to understanding and predicting their function. Free energy simulation (FES) has historically been a computational challenge as it requires both the accurate description of inter- and intramolecular interactions and adequate sampling of all relevant conformational degrees of freedom. The hybrid quantum mechanical molecular mechanical (QM/MM) framework is the current tool of choice when accurate computations of macromolecular systems are essential. Unfortunately, robust and efficient approaches that employ the high levels of computational theory needed to accurately describe many reactive processes (ie, ab initio, DFT), while also including explicit solvation effects and accounting for extensive conformational sampling are essentially nonexistent. In this chapter, we will give a brief overview of two recently developed methods that mitigate several major challenges associated with QM/MM FES: the QM non-Boltzmann Bennett's acceptance ratio method and the QM nonequilibrium work method. We will also describe usage of these methods to calculate free energies associated with (1) relative properties and (2) along reaction paths, using simple test cases with relevance to enzymes examples. © 2016 Elsevier Inc. All rights reserved.
Compiler for Fast, Accurate Mathematical Computing on Integer Processors Project
National Aeronautics and Space Administration — The proposers will develop a computer language compiler to enable inexpensive, low-power, integer-only processors to carry our mathematically-intensive comptutations...
An Integrative Approach to Accurate Vehicle Logo Detection
Hao Pan
2013-01-01
required for many applications in intelligent transportation systems and automatic surveillance. The task is challenging considering the small target of logos and the wide range of variability in shape, color, and illumination. A fast and reliable vehicle logo detection approach is proposed following visual attention mechanism from the human vision. Two prelogo detection steps, that is, vehicle region detection and a small RoI segmentation, rapidly focalize a small logo target. An enhanced Adaboost algorithm, together with two types of features of Haar and HOG, is proposed to detect vehicles. An RoI that covers logos is segmented based on our prior knowledge about the logos’ position relative to license plates, which can be accurately localized from frontal vehicle images. A two-stage cascade classier proceeds with the segmented RoI, using a hybrid of Gentle Adaboost and Support Vector Machine (SVM, resulting in precise logo positioning. Extensive experiments were conducted to verify the efficiency of the proposed scheme.
Towards accurate quantum simulations of large systems with small computers.
Yang, Yonggang
2017-01-24
Numerical simulations are important for many systems. In particular, various standard computer programs have been developed for solving the quantum Schrödinger equations. However, the accuracy of these calculations is limited by computer capabilities. In this work, an iterative method is introduced to enhance the accuracy of these numerical calculations, which is otherwise prohibitive by conventional methods. The method is easily implementable and general for many systems.
Towards accurate quantum simulations of large systems with small computers
Yang, Yonggang
2017-01-01
Numerical simulations are important for many systems. In particular, various standard computer programs have been developed for solving the quantum Schrödinger equations. However, the accuracy of these calculations is limited by computer capabilities. In this work, an iterative method is introduced to enhance the accuracy of these numerical calculations, which is otherwise prohibitive by conventional methods. The method is easily implementable and general for many systems. PMID:28117366
Puzzarini, Cristina; Biczysko, Malgorzata; Barone, Vincenzo; Peña, Isabel; Cabezas, Carlos; Alonso, José L.
2015-01-01
The computational composite scheme purposely set up for accurately describing the electronic structure and spectroscopic properties of small biomolecules has been applied to the first study of the rotational spectrum of 2-thiouracil. The experimental investigation was made possible thanks to the combination of the laser ablation technique with Fourier Transform Microwave spectrometers. The joint experimental – computational study allowed us to determine accurate molecular structure and spectroscopic properties for the title molecule, but more important, it demonstrates a reliable approach for the accurate investigation of isolated small biomolecules. PMID:24002739
Passeri, A. [Dipartimento di Fisiopatologia Clinica - Sezione di Medicina Nucleare, Universita` di Firenze (Italy); Formiconi, A.R. [Dipartimento di Fisiopatologia Clinica - Sezione di Medicina Nucleare, Universita` di Firenze (Italy); De Cristofaro, M.T.E.R. [Dipartimento di Fisiopatologia Clinica - Sezione di Medicina Nucleare, Universita` di Firenze (Italy); Pupi, A. [Dipartimento di Fisiopatologia Clinica - Sezione di Medicina Nucleare, Universita` di Firenze (Italy); Meldolesi, U. [Dipartimento di Fisiopatologia Clinica - Sezione di Medicina Nucleare, Universita` di Firenze (Italy)
1997-04-01
It is well known that the quantitative potential of emission computed tomography (ECT) relies on the ability to compensate for resolution, attenuation and scatter effects. Reconstruction algorithms which are able to take these effects into account are highly demanding in terms of computing resources. The reported work aimed to investigate the use of a parallel high-performance computing platform for ECT reconstruction taking into account an accurate model of the acquisition of single-photon emission tomographic (SPET) data. An iterative algorithm with an accurate model of the variable system response was ported on the MIMD (Multiple Instruction Multiple Data) parallel architecture of a 64-node Cray T3D massively parallel computer. The system was organized to make it easily accessible even from low-cost PC-based workstations through standard TCP/IP networking. A complete brain study of 30 (64 x 64) slices could be reconstructed from a set of 90 (64 x 64) projections with ten iterations of the conjugate gradients algorithm in 9 s, corresponding to an actual speed-up factor of 135. This work demonstrated the possibility of exploiting remote high-performance computing and networking resources from hospital sites by means of low-cost workstations using standard communication protocols without particular problems for routine use. The achievable speed-up factors allow the assessment of the clinical benefit of advanced reconstruction techniques which require a heavy computational burden for the compensation effects such as variable spatial resolution, scatter and attenuation. The possibility of using the same software on the same hardware platform with data acquired in different laboratories with various kinds of SPET instrumentation is appealing for software quality control and for the evaluation of the clinical impact of the reconstruction methods. (orig.). With 4 figs., 1 tab.
An Accurate and Computationally Efficient Model for Membrane-Type Circular-Symmetric Micro-Hotplates
Usman Khan
2014-04-01
Full Text Available Ideally, the design of high-performance micro-hotplates would require a large number of simulations because of the existence of many important design parameters as well as the possibly crucial effects of both spread and drift. However, the computational cost of FEM simulations, which are the only available tool for accurately predicting the temperature in micro-hotplates, is very high. As a result, micro-hotplate designers generally have no effective simulation-tools for the optimization. In order to circumvent these issues, here, we propose a model for practical circular-symmetric micro-hot-plates which takes advantage of modified Bessel functions, computationally efficient matrix-approach for considering the relevant boundary conditions, Taylor linearization for modeling the Joule heating and radiation losses, and external-region-segmentation strategy in order to accurately take into account radiation losses in the entire micro-hotplate. The proposed model is almost as accurate as FEM simulations and two to three orders of magnitude more computationally efficient (e.g., 45 s versus more than 8 h. The residual errors, which are mainly associated to the undesired heating in the electrical contacts, are small (e.g., few degrees Celsius for an 800 °C operating temperature and, for important analyses, almost constant. Therefore, we also introduce a computationally-easy single-FEM-compensation strategy in order to reduce the residual errors to about 1 °C. As illustrative examples of the power of our approach, we report the systematic investigation of a spread in the membrane thermal conductivity and of combined variations of both ambient and bulk temperatures. Our model enables a much faster characterization of micro-hotplates and, thus, a much more effective optimization prior to fabrication.
Tamma, Kumar K.; Railkar, Sudhir B.
1988-01-01
This paper represents an attempt to apply extensions of a hybrid transfinite element computational approach for accurately predicting thermoelastic stress waves. The applicability of the present formulations for capturing the thermal stress waves induced by boundary heating for the well known Danilovskaya problems is demonstrated. A unique feature of the proposed formulations for applicability to the Danilovskaya problem of thermal stress waves in elastic solids lies in the hybrid nature of the unified formulations and the development of special purpose transfinite elements in conjunction with the classical Galerkin techniques and transformation concepts. Numerical test cases validate the applicability and superior capability to capture the thermal stress waves induced due to boundary heating.
Zhao, Xiao-mei; Xie, Dong-fan; Li, Qi
2015-02-01
With the development of intelligent transport system, advanced information feedback strategies have been developed to reduce traffic congestion and enhance the capacity. However, previous strategies provide accurate information to travelers and our simulation results show that accurate information brings negative effects, especially in delay case. Because travelers prefer to the best condition route with accurate information, and delayed information cannot reflect current traffic condition but past. Then travelers make wrong routing decisions, causing the decrease of the capacity and the increase of oscillations and the system deviating from the equilibrium. To avoid the negative effect, bounded rationality is taken into account by introducing a boundedly rational threshold BR. When difference between two routes is less than the BR, routes have equal probability to be chosen. The bounded rationality is helpful to improve the efficiency in terms of capacity, oscillation and the gap deviating from the system equilibrium.
A new approach to constructing efficient stiffly accurate EPIRK methods
Rainwater, G.; Tokman, M.
2016-10-01
The structural flexibility of the exponential propagation iterative methods of Runge-Kutta type (EPIRK) enables construction of particularly efficient exponential time integrators. While the EPIRK methods have been shown to perform well on stiff problems, all of the schemes proposed up to now have been derived using classical order conditions. In this paper we extend the stiff order conditions and the convergence theory developed for the exponential Rosenbrock methods to the EPIRK integrators. We derive stiff order conditions for the EPIRK methods and develop algorithms to solve them to obtain specific schemes. Moreover, we propose a new approach to constructing particularly efficient EPIRK integrators that are optimized to work with an adaptive Krylov algorithm. We use a set of numerical examples to illustrate the computational advantages that the newly constructed EPIRK methods offer compared to previously proposed exponential integrators.
Approaches for the accurate definition of geological time boundaries
Schaltegger, Urs; Baresel, Björn; Ovtcharova, Maria; Goudemand, Nicolas; Bucher, Hugo
2015-04-01
Which strategies lead to the most precise and accurate date of a given geological boundary? Geological units are usually defined by the occurrence of characteristic taxa and hence boundaries between these geological units correspond to dramatic faunal and/or floral turnovers and they are primarily defined using first or last occurrences of index species, or ideally by the separation interval between two consecutive, characteristic associations of fossil taxa. These boundaries need to be defined in a way that enables their worldwide recognition and correlation across different stratigraphic successions, using tools as different as bio-, magneto-, and chemo-stratigraphy, and astrochronology. Sedimentary sequences can be dated in numerical terms by applying high-precision chemical-abrasion, isotope-dilution, thermal-ionization mass spectrometry (CA-ID-TIMS) U-Pb age determination to zircon (ZrSiO4) in intercalated volcanic ashes. But, though volcanic activity is common in geological history, ashes are not necessarily close to the boundary we would like to date precisely and accurately. In addition, U-Pb zircon data sets may be very complex and difficult to interpret in terms of the age of ash deposition. To overcome these difficulties we use a multi-proxy approach we applied to the precise and accurate dating of the Permo-Triassic and Early-Middle Triassic boundaries in South China. a) Dense sampling of ashes across the critical time interval and a sufficiently large number of analysed zircons per ash sample can guarantee the recognition of all system complexities. Geochronological datasets from U-Pb dating of volcanic zircon may indeed combine effects of i) post-crystallization Pb loss from percolation of hydrothermal fluids (even using chemical abrasion), with ii) age dispersion from prolonged residence of earlier crystallized zircon in the magmatic system. As a result, U-Pb dates of individual zircons are both apparently younger and older than the depositional age
Biomimetic Approach for Accurate, Real-Time Aerodynamic Coefficients Project
National Aeronautics and Space Administration — Aerodynamic and structural reliability and efficiency depends critically on the ability to accurately assess the aerodynamic loads and moments for each lifting...
On accurate computations of bound state properties in three- and four-electron atomic systems
Frolov, Alexei M
2016-01-01
Results of accurate computations of bound states in three- and four-electron atomic systems are discussed. Bound state properties of the four-electron lithium ion Li$^{-}$ in its ground $2^{2}S-$state are determined from the results of accurate, variational computations. We also consider a closely related problem of accurate numerical evaluation of the half-life of the beryllium-7 isotope. This problem is of paramount importance for modern radiochemistry.
A programming approach to computability
Kfoury, A J; Arbib, Michael A
1982-01-01
Computability theory is at the heart of theoretical computer science. Yet, ironically, many of its basic results were discovered by mathematical logicians prior to the development of the first stored-program computer. As a result, many texts on computability theory strike today's computer science students as far removed from their concerns. To remedy this, we base our approach to computability on the language of while-programs, a lean subset of PASCAL, and postpone consideration of such classic models as Turing machines, string-rewriting systems, and p. -recursive functions till the final chapter. Moreover, we balance the presentation of un solvability results such as the unsolvability of the Halting Problem with a presentation of the positive results of modern programming methodology, including the use of proof rules, and the denotational semantics of programs. Computer science seeks to provide a scientific basis for the study of information processing, the solution of problems by algorithms, and the design ...
Computational Approaches to Interface Design
Corker; Lebacqz, J. Victor (Technical Monitor)
1997-01-01
Tools which make use of computational processes - mathematical, algorithmic and/or knowledge-based - to perform portions of the design, evaluation and/or construction of interfaces have become increasingly available and powerful. Nevertheless, there is little agreement as to the appropriate role for a computational tool to play in the interface design process. Current tools fall into broad classes depending on which portions, and how much, of the design process they automate. The purpose of this panel is to review and generalize about computational approaches developed to date, discuss the tasks which for which they are suited, and suggest methods to enhance their utility and acceptance. Panel participants represent a wide diversity of application domains and methodologies. This should provide for lively discussion about implementation approaches, accuracy of design decisions, acceptability of representational tradeoffs and the optimal role for a computational tool to play in the interface design process.
Computational approaches to energy materials
Catlow, Richard; Walsh, Aron
2013-01-01
The development of materials for clean and efficient energy generation and storage is one of the most rapidly developing, multi-disciplinary areas of contemporary science, driven primarily by concerns over global warming, diminishing fossil-fuel reserves, the need for energy security, and increasing consumer demand for portable electronics. Computational methods are now an integral and indispensable part of the materials characterisation and development process. Computational Approaches to Energy Materials presents a detailed survey of current computational techniques for the
Ahmed, Ahfaz
2015-03-01
Gasoline is the most widely used fuel for light duty automobile transportation, but its molecular complexity makes it intractable to experimentally and computationally study the fundamental combustion properties. Therefore, surrogate fuels with a simpler molecular composition that represent real fuel behavior in one or more aspects are needed to enable repeatable experimental and computational combustion investigations. This study presents a novel computational methodology for formulating surrogates for FACE (fuels for advanced combustion engines) gasolines A and C by combining regression modeling with physical and chemical kinetics simulations. The computational methodology integrates simulation tools executed across different software platforms. Initially, the palette of surrogate species and carbon types for the target fuels were determined from a detailed hydrocarbon analysis (DHA). A regression algorithm implemented in MATLAB was linked to REFPROP for simulation of distillation curves and calculation of physical properties of surrogate compositions. The MATLAB code generates a surrogate composition at each iteration, which is then used to automatically generate CHEMKIN input files that are submitted to homogeneous batch reactor simulations for prediction of research octane number (RON). The regression algorithm determines the optimal surrogate composition to match the fuel properties of FACE A and C gasoline, specifically hydrogen/carbon (H/C) ratio, density, distillation characteristics, carbon types, and RON. The optimal surrogate fuel compositions obtained using the present computational approach was compared to the real fuel properties, as well as with surrogate compositions available in the literature. Experiments were conducted within a Cooperative Fuels Research (CFR) engine operating under controlled autoignition (CAI) mode to compare the formulated surrogates against the real fuels. Carbon monoxide measurements indicated that the proposed surrogates
Fast and Accurate Computation of Gauss--Legendre and Gauss--Jacobi Quadrature Nodes and Weights
Hale, Nicholas
2013-03-06
An efficient algorithm for the accurate computation of Gauss-Legendre and Gauss-Jacobi quadrature nodes and weights is presented. The algorithm is based on Newton\\'s root-finding method with initial guesses and function evaluations computed via asymptotic formulae. The n-point quadrature rule is computed in O(n) operations to an accuracy of essentially double precision for any n ≥ 100. © 2013 Society for Industrial and Applied Mathematics.
GRID COMPUTING AND CHECKPOINT APPROACH
Pankaj gupta
2011-05-01
Full Text Available Grid computing is a means of allocating the computational power of alarge number of computers to complex difficult computation or problem. Grid computing is a distributed computing paradigm thatdiffers from traditional distributed computing in that it is aimed toward large scale systems that even span organizational boundaries. In this paper we investigate the different techniques of fault tolerance which are used in many real time distributed systems. The main focus is on types of fault occurring in the system, fault detection techniques and the recovery techniques used. A fault can occur due to link failure, resource failure or by any other reason is to be tolerated for working the system smoothly and accurately. These faults can be detected and recovered by many techniques used accordingly. An appropriate fault detector can avoid loss due to system crash and reliable fault tolerance technique can save from system failure. This paper provides how these methods are applied to detect and tolerate faults from various Real Time Distributed Systems. The advantages of utilizing the check pointing functionality are obvious; however so far the Grid community has notdeveloped a widely accepted standard that would allow the Gridenvironment to consciously utilize low level check pointing packages.Therefore, such a standard named Grid Check pointing Architecture isbeing designed. The fault tolerance mechanism used here sets the jobcheckpoints based on the resource failure rate. If resource failureoccurs, the job is restarted from its last successful state using acheckpoint file from another grid resource. A critical aspect for anautomatic recovery is the availability of checkpoint files. A strategy to increase the availability of checkpoints is replication. Grid is a form distributed computing mainly to virtualizes and utilize geographically distributed idle resources. A grid is a distributed computational and storage environment often composed of
Computational Approaches to Vestibular Research
Ross, Muriel D.; Wade, Charles E. (Technical Monitor)
1994-01-01
The Biocomputation Center at NASA Ames Research Center is dedicated to a union between computational, experimental and theoretical approaches to the study of neuroscience and of life sciences in general. The current emphasis is on computer reconstruction and visualization of vestibular macular architecture in three-dimensions (3-D), and on mathematical modeling and computer simulation of neural activity in the functioning system. Our methods are being used to interpret the influence of spaceflight on mammalian vestibular maculas in a model system, that of the adult Sprague-Dawley rat. More than twenty 3-D reconstructions of type I and type II hair cells and their afferents have been completed by digitization of contours traced from serial sections photographed in a transmission electron microscope. This labor-intensive method has now been replace d by a semiautomated method developed in the Biocomputation Center in which conventional photography is eliminated. All viewing, storage and manipulation of original data is done using Silicon Graphics workstations. Recent improvements to the software include a new mesh generation method for connecting contours. This method will permit the investigator to describe any surface, regardless of complexity, including highly branched structures such as are routinely found in neurons. This same mesh can be used for 3-D, finite volume simulation of synapse activation and voltage spread on neuronal surfaces visualized via the reconstruction process. These simulations help the investigator interpret the relationship between neuroarchitecture and physiology, and are of assistance in determining which experiments will best test theoretical interpretations. Data are also used to develop abstract, 3-D models that dynamically display neuronal activity ongoing in the system. Finally, the same data can be used to visualize the neural tissue in a virtual environment. Our exhibit will depict capabilities of our computational approaches and
2014-10-08
models to compute accurately the molecular interactions between a mobile or stationary phase and a target substrate or analyte , which are fundamental...mobile or stationary phase and a target substrate or analyte , which are fundamental to diverse technologies, e.g., sensor or separation design. With...D. G., New Orleans, LA, April 9, 2013. 223rd Electrochemical Society Meeting, Continuum Solvation Models for Computational Electrochemistry
Computer Networks A Systems Approach
Peterson, Larry L
2011-01-01
This best-selling and classic book teaches you the key principles of computer networks with examples drawn from the real world of network and protocol design. Using the Internet as the primary example, the authors explain various protocols and networking technologies. Their systems-oriented approach encourages you to think about how individual network components fit into a larger, complex system of interactions. Whatever your perspective, whether it be that of an application developer, network administrator, or a designer of network equipment or protocols, you will come away with a "big pictur
Efficient and accurate P-value computation for Position Weight Matrices
Varré Jean-Stéphane
2007-12-01
Full Text Available Abstract Background Position Weight Matrices (PWMs are probabilistic representations of signals in sequences. They are widely used to model approximate patterns in DNA or in protein sequences. The usage of PWMs needs as a prerequisite to knowing the statistical significance of a word according to its score. This is done by defining the P-value of a score, which is the probability that the background model can achieve a score larger than or equal to the observed value. This gives rise to the following problem: Given a P-value, find the corresponding score threshold. Existing methods rely on dynamic programming or probability generating functions. For many examples of PWMs, they fail to give accurate results in a reasonable amount of time. Results The contribution of this paper is two fold. First, we study the theoretical complexity of the problem, and we prove that it is NP-hard. Then, we describe a novel algorithm that solves the P-value problem efficiently. The main idea is to use a series of discretized score distributions that improves the final result step by step until some convergence criterion is met. Moreover, the algorithm is capable of calculating the exact P-value without any error, even for matrices with non-integer coefficient values. The same approach is also used to devise an accurate algorithm for the reverse problem: finding the P-value for a given score. Both methods are implemented in a software called TFM-PVALUE, that is freely available. Conclusion We have tested TFM-PVALUE on a large set of PWMs representing transcription factor binding sites. Experimental results show that it achieves better performance in terms of computational time and precision than existing tools.
F. Djeffal; A. Ferdi; M. Chahdi
2012-01-01
The double gate (DG) silicon MOSFET with an extremely short-channel length has the appropriate features to constitute the devices for nanoscale circuit design.To develop a physical model for extremely scaled DG MOSFETs,the drain current in the channel must be accurately determined under the application of drain and gate voltages.However,modeling the transport mechanism for the nanoscale structures requires the use of overkill methods and models in terms of their complexity and computation time (self-consistent,quantum computations ).Therefore,new methods and techniques are required to overcome these constraints.In this paper,a new approach based on the fuzzy logic computation is proposed to investigate nanoscale DG MOSFETs.The proposed approach has been implemented in a device simulator to show the impact of the proposed approach on the nanoelectronic circuit design.The approach is general and thus is suitable for any type ofnanoscale structure investigation problems in the nanotechnology industry.
Computational approaches for drug discovery.
Hung, Che-Lun; Chen, Chi-Chun
2014-09-01
Cellular proteins are the mediators of multiple organism functions being involved in physiological mechanisms and disease. By discovering lead compounds that affect the function of target proteins, the target diseases or physiological mechanisms can be modulated. Based on knowledge of the ligand-receptor interaction, the chemical structures of leads can be modified to improve efficacy, selectivity and reduce side effects. One rational drug design technology, which enables drug discovery based on knowledge of target structures, functional properties and mechanisms, is computer-aided drug design (CADD). The application of CADD can be cost-effective using experiments to compare predicted and actual drug activity, the results from which can used iteratively to improve compound properties. The two major CADD-based approaches are structure-based drug design, where protein structures are required, and ligand-based drug design, where ligand and ligand activities can be used to design compounds interacting with the protein structure. Approaches in structure-based drug design include docking, de novo design, fragment-based drug discovery and structure-based pharmacophore modeling. Approaches in ligand-based drug design include quantitative structure-affinity relationship and pharmacophore modeling based on ligand properties. Based on whether the structure of the receptor and its interaction with the ligand are known, different design strategies can be seed. After lead compounds are generated, the rule of five can be used to assess whether these have drug-like properties. Several quality validation methods, such as cost function analysis, Fisher's cross-validation analysis and goodness of hit test, can be used to estimate the metrics of different drug design strategies. To further improve CADD performance, multi-computers and graphics processing units may be applied to reduce costs.
Computational Approaches to Vestibular Research
Ross, Muriel D.; Wade, Charles E. (Technical Monitor)
1994-01-01
The Biocomputation Center at NASA Ames Research Center is dedicated to a union between computational, experimental and theoretical approaches to the study of neuroscience and of life sciences in general. The current emphasis is on computer reconstruction and visualization of vestibular macular architecture in three-dimensions (3-D), and on mathematical modeling and computer simulation of neural activity in the functioning system. Our methods are being used to interpret the influence of spaceflight on mammalian vestibular maculas in a model system, that of the adult Sprague-Dawley rat. More than twenty 3-D reconstructions of type I and type II hair cells and their afferents have been completed by digitization of contours traced from serial sections photographed in a transmission electron microscope. This labor-intensive method has now been replace d by a semiautomated method developed in the Biocomputation Center in which conventional photography is eliminated. All viewing, storage and manipulation of original data is done using Silicon Graphics workstations. Recent improvements to the software include a new mesh generation method for connecting contours. This method will permit the investigator to describe any surface, regardless of complexity, including highly branched structures such as are routinely found in neurons. This same mesh can be used for 3-D, finite volume simulation of synapse activation and voltage spread on neuronal surfaces visualized via the reconstruction process. These simulations help the investigator interpret the relationship between neuroarchitecture and physiology, and are of assistance in determining which experiments will best test theoretical interpretations. Data are also used to develop abstract, 3-D models that dynamically display neuronal activity ongoing in the system. Finally, the same data can be used to visualize the neural tissue in a virtual environment. Our exhibit will depict capabilities of our computational approaches and
Fuzzy multiple linear regression: A computational approach
Juang, C. H.; Huang, X. H.; Fleming, J. W.
1992-01-01
This paper presents a new computational approach for performing fuzzy regression. In contrast to Bardossy's approach, the new approach, while dealing with fuzzy variables, closely follows the conventional regression technique. In this approach, treatment of fuzzy input is more 'computational' than 'symbolic.' The following sections first outline the formulation of the new approach, then deal with the implementation and computational scheme, and this is followed by examples to illustrate the new procedure.
Computational approach to Riemann surfaces
Klein, Christian
2011-01-01
This volume offers a well-structured overview of existent computational approaches to Riemann surfaces and those currently in development. The authors of the contributions represent the groups providing publically available numerical codes in this field. Thus this volume illustrates which software tools are available and how they can be used in practice. In addition examples for solutions to partial differential equations and in surface theory are presented. The intended audience of this book is twofold. It can be used as a textbook for a graduate course in numerics of Riemann surfaces, in which case the standard undergraduate background, i.e., calculus and linear algebra, is required. In particular, no knowledge of the theory of Riemann surfaces is expected; the necessary background in this theory is contained in the Introduction chapter. At the same time, this book is also intended for specialists in geometry and mathematical physics applying the theory of Riemann surfaces in their research. It is the first...
Computer-based personality judgments are more accurate than those made by humans
Youyou, Wu; Kosinski, Michal; Stillwell, David
2015-01-01
Judging others’ personalities is an essential skill in successful social living, as personality is a key driver behind people’s interactions, behaviors, and emotions. Although accurate personality judgments stem from social-cognitive skills, developments in machine learning show that computer models can also make valid judgments. This study compares the accuracy of human and computer-based personality judgments, using a sample of 86,220 volunteers who completed a 100-item personality questionnaire. We show that (i) computer predictions based on a generic digital footprint (Facebook Likes) are more accurate (r = 0.56) than those made by the participants’ Facebook friends using a personality questionnaire (r = 0.49); (ii) computer models show higher interjudge agreement; and (iii) computer personality judgments have higher external validity when predicting life outcomes such as substance use, political attitudes, and physical health; for some outcomes, they even outperform the self-rated personality scores. Computers outpacing humans in personality judgment presents significant opportunities and challenges in the areas of psychological assessment, marketing, and privacy. PMID:25583507
Computer-based personality judgments are more accurate than those made by humans.
Youyou, Wu; Kosinski, Michal; Stillwell, David
2015-01-27
Judging others' personalities is an essential skill in successful social living, as personality is a key driver behind people's interactions, behaviors, and emotions. Although accurate personality judgments stem from social-cognitive skills, developments in machine learning show that computer models can also make valid judgments. This study compares the accuracy of human and computer-based personality judgments, using a sample of 86,220 volunteers who completed a 100-item personality questionnaire. We show that (i) computer predictions based on a generic digital footprint (Facebook Likes) are more accurate (r = 0.56) than those made by the participants' Facebook friends using a personality questionnaire (r = 0.49); (ii) computer models show higher interjudge agreement; and (iii) computer personality judgments have higher external validity when predicting life outcomes such as substance use, political attitudes, and physical health; for some outcomes, they even outperform the self-rated personality scores. Computers outpacing humans in personality judgment presents significant opportunities and challenges in the areas of psychological assessment, marketing, and privacy.
Drmac, Z. [Univ. of Colorado, Boulder, CO (United States). Dept. of Computer Science
1997-07-01
In this paper the author considers how to compute the singular value decomposition (SVD) A = U{Sigma}V{sup {tau}} of A = [a{sub 1}, a{sub 2}] {element_of} R{sup mx2} accurately in floating point arithmetic. It is shown how to compute the Jacobi rotation V (the right singular vector matrix) and how to compute AV = U{Sigma} even if the floating point representation of V is the identity matrix. In the case (norm of (a{sub 1})){sub 2} {much_gt} (norm of (a{sub 2})){sub 2}, underflow can produce the identity matrix as the floating point value of V, even for a{sub 1}, a{sub 2} that are far from being mutually orthogonal. This can cause loss of accuracy and failure of convergence of the floating point implementation of the Jacobi method for computing the SVD. The modified Jacobi method recommended in this paper can be implemented as a reliable and highly accurate procedure for computing the SVD of general real matrices whenever the exact singular values do not exceed the underflow or overflow limits.
Improved patient size estimates for accurate dose calculations in abdomen computed tomography
Lee, Chang-Lae
2017-07-01
The radiation dose of CT (computed tomography) is generally represented by the CTDI (CT dose index). CTDI, however, does not accurately predict the actual patient doses for different human body sizes because it relies on a cylinder-shaped head (diameter : 16 cm) and body (diameter : 32 cm) phantom. The purpose of this study was to eliminate the drawbacks of the conventional CTDI and to provide more accurate radiation dose information. Projection radiographs were obtained from water cylinder phantoms of various sizes, and the sizes of the water cylinder phantoms were calculated and verified using attenuation profiles. The effective diameter was also calculated using the attenuation of the abdominal projection radiographs of 10 patients. When the results of the attenuation-based method and the geometry-based method shown were compared with the results of the reconstructed-axial-CT-image-based method, the effective diameter of the attenuation-based method was found to be similar to the effective diameter of the reconstructed-axial-CT-image-based method, with a difference of less than 3.8%, but the geometry-based method showed a difference of less than 11.4%. This paper proposes a new method of accurately computing the radiation dose of CT based on the patient sizes. This method computes and provides the exact patient dose before the CT scan, and can therefore be effectively used for imaging and dose control.
Yoshidome, Takashi; Ekimoto, Toru; Matubayasi, Nobuyuki; Harano, Yuichi; Kinoshita, Masahiro; Ikeguchi, Mitsunori
2015-05-07
The hydration free energy (HFE) is a crucially important physical quantity to discuss various chemical processes in aqueous solutions. Although an explicit-solvent computation with molecular dynamics (MD) simulations is a preferable treatment of the HFE, huge computational load has been inevitable for large, complex solutes like proteins. In the present paper, we propose an efficient computation method for the HFE. In our method, the HFE is computed as a sum of 〈UUV〉/2 (〈UUV〉 is the ensemble average of the sum of pair interaction energy between solute and water molecule) and the water reorganization term mainly reflecting the excluded volume effect. Since 〈UUV〉 can readily be computed through a MD of the system composed of solute and water, an efficient computation of the latter term leads to a reduction of computational load. We demonstrate that the water reorganization term can quantitatively be calculated using the morphometric approach (MA) which expresses the term as the linear combinations of the four geometric measures of a solute and the corresponding coefficients determined with the energy representation (ER) method. Since the MA enables us to finish the computation of the solvent reorganization term in less than 0.1 s once the coefficients are determined, the use of the MA enables us to provide an efficient computation of the HFE even for large, complex solutes. Through the applications, we find that our method has almost the same quantitative performance as the ER method with substantial reduction of the computational load.
Computer Architecture A Quantitative Approach
Hennessy, John L
2011-01-01
The computing world today is in the middle of a revolution: mobile clients and cloud computing have emerged as the dominant paradigms driving programming and hardware innovation today. The Fifth Edition of Computer Architecture focuses on this dramatic shift, exploring the ways in which software and technology in the cloud are accessed by cell phones, tablets, laptops, and other mobile computing devices. Each chapter includes two real-world examples, one mobile and one datacenter, to illustrate this revolutionary change.Updated to cover the mobile computing revolutionEmphasizes the two most im
Genetic crossovers are predicted accurately by the computed human recombination map.
Pavel P Khil
2010-01-01
Full Text Available Hotspots of meiotic recombination can change rapidly over time. This instability and the reported high level of inter-individual variation in meiotic recombination puts in question the accuracy of the calculated hotspot map, which is based on the summation of past genetic crossovers. To estimate the accuracy of the computed recombination rate map, we have mapped genetic crossovers to a median resolution of 70 Kb in 10 CEPH pedigrees. We then compared the positions of crossovers with the hotspots computed from HapMap data and performed extensive computer simulations to compare the observed distributions of crossovers with the distributions expected from the calculated recombination rate maps. Here we show that a population-averaged hotspot map computed from linkage disequilibrium data predicts well present-day genetic crossovers. We find that computed hotspot maps accurately estimate both the strength and the position of meiotic hotspots. An in-depth examination of not-predicted crossovers shows that they are preferentially located in regions where hotspots are found in other populations. In summary, we find that by combining several computed population-specific maps we can capture the variation in individual hotspots to generate a hotspot map that can predict almost all present-day genetic crossovers.
Multislice Computed Tomography Accurately Detects Stenosis in Coronary Artery Bypass Conduits
Duran, Cihan; Sagbas, Ertan; Caynak, Baris; Sanisoglu, Ilhan; Akpinar, Belhhan; Gulbaran, Murat
2007-01-01
The aim of this study was to evaluate the accuracy of multislice computed tomography in detecting graft stenosis or occlusion after coronary artery bypass grafting, using coronary angiography as the standard. From January 2005 through May 2006, 25 patients (19 men and 6 women; mean age, 54 ± 11.3 years) underwent diagnostic investigation of their bypass grafts by multislice computed tomography within 1 month of coronary angiography. The mean time elapsed after coronary artery bypass grafting was 6.2 years. In these 25 patients, we examined 65 bypass conduits (24 arterial and 41 venous) and 171 graft segments (the shaft, proximal anastomosis, and distal anastomosis). Compared with coronary angiography, the segment-based sensitivity, specificity, and positive and negative predictive values of multislice computed tomography in the evaluation of stenosis were 89%, 100%, 100%, and 99%, respectively. The patency rate for multislice compu-ted tomography was 85% (55/65: 3 arterial and 7 venous grafts were occluded), with 100% sensitivity and specificity. From these data, we conclude that multislice computed tomography can accurately evaluate the patency and stenosis of bypass grafts during outpatient follow-up. PMID:17948078
Computer Algebra, Instrumentation and the Anthropological Approach
Monaghan, John
2007-01-01
This article considers research and scholarship on the use of computer algebra in mathematics education following the instrumentation and the anthropological approaches. It outlines what these approaches are, positions them with regard to other approaches, examines tensions between the two approaches and makes suggestions for how work in this…
Computational approaches for urban environments
Helbich, M; Jokar Arsanjani, J; Leitner, M
2015-01-01
This book aims to promote the synergistic usage of advanced computational methodologies in close relationship to geospatial information across cities of different scales. A rich collection of chapters subsumes current research frontiers originating from disciplines such as geography, urban planning,
What is computation : An epistemic approach
Wiedermann, Jiří; van Leeuwen, Jan
2015-01-01
Traditionally, computations are seen as processes that transform information. Definitions of computation subsequently concentrate on a description of the mechanisms that lead to such processes. The bottleneck of this approach is twofold. First, it leads to a definition of computation that is too
What is computation : An epistemic approach
Wiedermann, Jiří; van Leeuwen, Jan
2015-01-01
Traditionally, computations are seen as processes that transform information. Definitions of computation subsequently concentrate on a description of the mechanisms that lead to such processes. The bottleneck of this approach is twofold. First, it leads to a definition of computation that is too bro
A particle-tracking approach for accurate material derivative measurements with tomographic PIV
Novara, Matteo; Scarano, Fulvio
2013-08-01
The evaluation of the instantaneous 3D pressure field from tomographic PIV data relies on the accurate estimate of the fluid velocity material derivative, i.e., the velocity time rate of change following a given fluid element. To date, techniques that reconstruct the fluid parcel trajectory from a time sequence of 3D velocity fields obtained with Tomo-PIV have already been introduced. However, an accurate evaluation of the fluid element acceleration requires trajectory reconstruction over a relatively long observation time, which reduces random errors. On the other hand, simple integration and finite difference techniques suffer from increasing truncation errors when complex trajectories need to be reconstructed over a long time interval. In principle, particle-tracking velocimetry techniques (3D-PTV) enable the accurate reconstruction of single particle trajectories over a long observation time. Nevertheless, PTV can be reliably performed only at limited particle image number density due to errors caused by overlapping particles. The particle image density can be substantially increased by use of tomographic PIV. In the present study, a technique to combine the higher information density of tomographic PIV and the accurate trajectory reconstruction of PTV is proposed (Tomo-3D-PTV). The particle-tracking algorithm is applied to the tracers detected in the 3D domain obtained by tomographic reconstruction. The 3D particle information is highly sparse and intersection of trajectories is virtually impossible. As a result, ambiguities in the particle path identification over subsequent recordings are easily avoided. Polynomial fitting functions are introduced that describe the particle position in time with sequences based on several recordings, leading to the reduction in truncation errors for complex trajectories. Moreover, the polynomial regression approach provides a reduction in the random errors due to the particle position measurement. Finally, the acceleration
Accurate Numerical Methods for Computing 2D and 3D Robot Workspace
Yi Cao
2011-12-01
Full Text Available Exact computation of the shape and size of robot manipulator workspace is very important for its analysis and optimum design. First, the drawbacks of the previous methods based on Monte Carlo are pointed out in the paper, and then improved strategies are presented systematically. In order to obtain more accurate boundary points of two-dimensional (2D robot workspace, the Beta distribution is adopted to generate random variables of robot joints. And then, the area of workspace is acquired by computing the area of the polygon what is a closed path by connecting the boundary points together. For comparing the errors of workspaces which are generated by the previous and the improved method from shape and size, one planar robot manipulator is taken as example. A spatial robot manipulator is used to illustrate that the methods can be used not only on planar robot manipulator, but also on the spatial. The optimal parameters are proposed in the paper to computer the shape and size of 2D and 3D workspace. Finally, we provided the computation time and discussed the generation of 3D workspace which is based on 3D reconstruction from the boundary points.
Bryant Jamie
2011-11-01
Full Text Available Abstract Background Self report of smoking status is potentially unreliable in certain situations and in high-risk populations. This study aimed to determine the accuracy and acceptability of computer administered self-report of smoking status among a low socioeconomic (SES population. Methods Clients attending a community service organisation for welfare support were invited to complete a cross-sectional touch screen computer health survey. Following survey completion, participants were invited to provide a breath sample to measure exposure to tobacco smoke in expired air. Sensitivity, specificity, positive predictive value and negative predictive value were calculated. Results Three hundred and eighty three participants completed the health survey, and 330 (86% provided a breath sample. Of participants included in the validation analysis, 59% reported being a daily or occasional smoker. Sensitivity was 94.4% and specificity 92.8%. The positive and negative predictive values were 94.9% and 92.0% respectively. The majority of participants reported that the touch screen survey was both enjoyable (79% and easy (88% to complete. Conclusions Computer administered self report is both acceptable and accurate as a method of assessing smoking status among low SES smokers in a community setting. Routine collection of health information using touch-screen computer has the potential to identify smokers and increase provision of support and referral in the community setting.
Antenna arrays a computational approach
Haupt, Randy L
2010-01-01
This book covers a wide range of antenna array topics that are becoming increasingly important in wireless applications, particularly in design and computer modeling. Signal processing and numerical modeling algorithms are explored, and MATLAB computer codes are provided for many of the design examples. Pictures of antenna arrays and components provided by industry and government sources are presented with explanations of how they work. Antenna Arrays is a valuable reference for practicing engineers and scientists in wireless communications, radar, and remote sensing, and an excellent textbook for advanced antenna courses.
An Accurate Approach to Large-Scale IP Traffic Matrix Estimation
Jiang, Dingde; Hu, Guangmin
This letter proposes a novel method of large-scale IP traffic matrix (TM) estimation, called algebraic reconstruction technique inference (ARTI), which is based on the partial flow measurement and Fratar model. In contrast to previous methods, ARTI can accurately capture the spatio-temporal correlations of TM. Moreover, ARTI is computationally simple since it uses the algebraic reconstruction technique. We use the real data from the Abilene network to validate ARTI. Simulation results show that ARTI can accurately estimate large-scale IP TM and track its dynamics.
Pineda, M.; Stamatakis, M.
2017-07-01
Modeling the kinetics of surface catalyzed reactions is essential for the design of reactors and chemical processes. The majority of microkinetic models employ mean-field approximations, which lead to an approximate description of catalytic kinetics by assuming spatially uncorrelated adsorbates. On the other hand, kinetic Monte Carlo (KMC) methods provide a discrete-space continuous-time stochastic formulation that enables an accurate treatment of spatial correlations in the adlayer, but at a significant computation cost. In this work, we use the so-called cluster mean-field approach to develop higher order approximations that systematically increase the accuracy of kinetic models by treating spatial correlations at a progressively higher level of detail. We further demonstrate our approach on a reduced model for NO oxidation incorporating first nearest-neighbor lateral interactions and construct a sequence of approximations of increasingly higher accuracy, which we compare with KMC and mean-field. The latter is found to perform rather poorly, overestimating the turnover frequency by several orders of magnitude for this system. On the other hand, our approximations, while more computationally intense than the traditional mean-field treatment, still achieve tremendous computational savings compared to KMC simulations, thereby opening the way for employing them in multiscale modeling frameworks.
Immune based computer virus detection approaches
TAN Ying; ZHANG Pengtao
2013-01-01
The computer virus is considered one of the most horrifying threats to the security of computer systems worldwide.The rapid development of evasion techniques used in virus causes the signature based computer virus detection techniques to be ineffective.Many novel computer virus detection approaches have been proposed in the past to cope with the ineffectiveness,mainly classified into three categories:static,dynamic and heuristics techniques.As the natural similarities between the biological immune system (BIS),computer security system (CSS),and the artificial immune system (AIS) were all developed as a new prototype in the community of anti-virus research.The immune mechanisms in the BIS provide the opportunities to construct computer virus detection models that are robust and adaptive with the ability to detect unseen viruses.In this paper,a variety of classic computer virus detection approaches were introduced and reviewed based on the background knowledge of the computer virus history.Next,a variety of immune based computer virus detection approaches were also discussed in detail.Promising experimental results suggest that the immune based computer virus detection approaches were able to detect new variants and unseen viruses at lower false positive rates,which have paved a new way for the anti-virus research.
Accurate and efficient computation of nonlocal potentials based on Gaussian-sum approximation
Exl, Lukas; Mauser, Norbert J.; Zhang, Yong
2016-12-01
We introduce an accurate and efficient method for the numerical evaluation of nonlocal potentials, including the 3D/2D Coulomb, 2D Poisson and 3D dipole-dipole potentials. Our method is based on a Gaussian-sum approximation of the singular convolution kernel combined with a Taylor expansion of the density. Starting from the convolution formulation of the nonlocal potential, for smooth and fast decaying densities, we make a full use of the Fourier pseudospectral (plane wave) approximation of the density and a separable Gaussian-sum approximation of the kernel in an interval where the singularity (the origin) is excluded. The potential is separated into a regular integral and a near-field singular correction integral. The first is computed with the Fourier pseudospectral method, while the latter is well resolved utilizing a low-order Taylor expansion of the density. Both parts are accelerated by fast Fourier transforms (FFT). The method is accurate (14-16 digits), efficient (O (Nlog N) complexity), low in storage, easily adaptable to other different kernels, applicable for anisotropic densities and highly parallelizable.
Accurate and efficient computation of nonlocal potentials based on Gaussian-sum approximation
Exl, Lukas; Zhang, Yong
2015-01-01
We introduce an accurate and efficient method for a class of nonlocal potential evaluations with free boundary condition, including the 3D/2D Coulomb, 2D Poisson and 3D dipolar potentials. Our method is based on a Gaussian-sum approximation of the singular convolution kernel and Taylor expansion of the density. Starting from the convolution formulation, for smooth and fast decaying densities, we make a full use of the Fourier pseudospectral (plane wave) approximation of the density and a separable Gaussian-sum approximation of the kernel in an interval where the singularity (the origin) is excluded. Hence, the potential is separated into a regular integral and a near-field singular correction integral, where the first integral is computed with the Fourier pseudospectral method and the latter singular one can be well resolved utilizing a low-order Taylor expansion of the density. Both evaluations can be accelerated by fast Fourier transforms (FFT). The new method is accurate (14-16 digits), efficient ($O(N \\lo...
Computational approaches for systems metabolomics.
Krumsiek, Jan; Bartel, Jörg; Theis, Fabian J
2016-06-01
Systems genetics is defined as the simultaneous assessment and analysis of multi-omics datasets. In the past few years, metabolomics has been established as a robust tool describing an important functional layer in this approach. The metabolome of a biological system represents an integrated state of genetic and environmental factors and has been referred to as a 'link between genotype and phenotype'. In this review, we summarize recent progresses in statistical analysis methods for metabolomics data in combination with other omics layers. We put a special focus on complex, multivariate statistical approaches as well as pathway-based and network-based analysis methods. Moreover, we outline current challenges and pitfalls of metabolomics-focused multi-omics analyses and discuss future steps for the field.
Li, Xiangrui; Lu, Zhong-Lin
2012-02-29
Display systems based on conventional computer graphics cards are capable of generating images with 8-bit gray level resolution. However, most experiments in vision research require displays with more than 12 bits of luminance resolution. Several solutions are available. Bit++ (1) and DataPixx (2) use the Digital Visual Interface (DVI) output from graphics cards and high resolution (14 or 16-bit) digital-to-analog converters to drive analog display devices. The VideoSwitcher (3) described here combines analog video signals from the red and blue channels of graphics cards with different weights using a passive resister network (4) and an active circuit to deliver identical video signals to the three channels of color monitors. The method provides an inexpensive way to enable high-resolution monochromatic displays using conventional graphics cards and analog monitors. It can also provide trigger signals that can be used to mark stimulus onsets, making it easy to synchronize visual displays with physiological recordings or response time measurements. Although computer keyboards and mice are frequently used in measuring response times (RT), the accuracy of these measurements is quite low. The RTbox is a specialized hardware and software solution for accurate RT measurements. Connected to the host computer through a USB connection, the driver of the RTbox is compatible with all conventional operating systems. It uses a microprocessor and high-resolution clock to record the identities and timing of button events, which are buffered until the host computer retrieves them. The recorded button events are not affected by potential timing uncertainties or biases associated with data transmission and processing in the host computer. The asynchronous storage greatly simplifies the design of user programs. Several methods are available to synchronize the clocks of the RTbox and the host computer. The RTbox can also receive external triggers and be used to measure RT with respect
Learning and geometry computational approaches
Smith, Carl
1996-01-01
The field of computational learning theory arose out of the desire to for mally understand the process of learning. As potential applications to artificial intelligence became apparent, the new field grew rapidly. The learning of geo metric objects became a natural area of study. The possibility of using learning techniques to compensate for unsolvability provided an attraction for individ uals with an immediate need to solve such difficult problems. Researchers at the Center for Night Vision were interested in solving the problem of interpreting data produced by a variety of sensors. Current vision techniques, which have a strong geometric component, can be used to extract features. However, these techniques fall short of useful recognition of the sensed objects. One potential solution is to incorporate learning techniques into the geometric manipulation of sensor data. As a first step toward realizing such a solution, the Systems Research Center at the University of Maryland, in conjunction with the C...
Cloud computing methods and practical approaches
Mahmood, Zaigham
2013-01-01
This book presents both state-of-the-art research developments and practical guidance on approaches, technologies and frameworks for the emerging cloud paradigm. Topics and features: presents the state of the art in cloud technologies, infrastructures, and service delivery and deployment models; discusses relevant theoretical frameworks, practical approaches and suggested methodologies; offers guidance and best practices for the development of cloud-based services and infrastructures, and examines management aspects of cloud computing; reviews consumer perspectives on mobile cloud computing an
Accurate Computation of Periodic Regions' Centers in the General M-Set with Integer Index Number
Wang Xingyuan
2010-01-01
Full Text Available This paper presents two methods for accurately computing the periodic regions' centers. One method fits for the general M-sets with integer index number, the other fits for the general M-sets with negative integer index number. Both methods improve the precision of computation by transforming the polynomial equations which determine the periodic regions' centers. We primarily discuss the general M-sets with negative integer index, and analyze the relationship between the number of periodic regions' centers on the principal symmetric axis and in the principal symmetric interior. We can get the centers' coordinates with at least 48 significant digits after the decimal point in both real and imaginary parts by applying the Newton's method to the transformed polynomial equation which determine the periodic regions' centers. In this paper, we list some centers' coordinates of general M-sets' k-periodic regions (k=3,4,5,6 for the index numbers α=−25,−24,…,−1 , all of which have highly numerical accuracy.
Angpow: a software for the fast computation of accurate tomographic power spectra
Campagne, J.-E.; Neveu, J.; Plaszczynski, S.
2017-06-01
Aims: The statistical distribution of galaxies is a powerful probe to constrain cosmological models and gravity. In particular, the matter power spectrum P(k) provides information about the cosmological distance evolution and the galaxy clustering. However the building of P(k) from galaxy catalogs requires a cosmological model to convert angles on the sky and redshifts into distances, which leads to difficulties when comparing data with predicted P(k) from other cosmological models, and for photometric surveys like the Large Synoptic Survey Telescope (LSST). The angular power spectrum Cℓ(z1,z2) between two bins located at redshift z1 and z2 contains the same information as the matter power spectrum, and is free from any cosmological assumption, but the prediction of Cℓ(z1,z2) from P(k) is a costly computation when performed precisely. Methods: The Angpow software aims at quickly and accurately computing the auto (z1 = z2) and cross (z1 ≠ z2) angular power spectra between redshift bins. We describe the developed algorithm based on developments on the Chebyshev polynomial basis and on the Clenshaw-Curtis quadrature method. We validate the results with other codes, and benchmark the performance. Results: Angpow is flexible and can handle any user-defined power spectra, transfer functions, and redshift selection windows. The code is fast enough to be embedded inside programs exploring large cosmological parameter spaces through the Cℓ(z1,z2) comparison with data. We emphasize that the Limber's approximation, often used to speed up the computation, gives incorrect Cℓ values for cross-correlations. The C++ code is available from http://https://gitlab.in2p3.fr/campagne/AngPow
Sheng, Qiwei; Matthews, Thomas P; Xia, Jun; Zhu, Liren; Wang, Lihong V; Anastasio, Mark A
2015-01-01
Photoacoustic computed tomography (PACT) is an emerging computed imaging modality that exploits optical contrast and ultrasonic detection principles to form images of the absorbed optical energy density within tissue. When the imaging system employs conventional piezoelectric ultrasonic transducers, the ideal photoacoustic (PA) signals are degraded by the transducers' acousto-electric impulse responses (EIRs) during the measurement process. If unaccounted for, this can degrade the accuracy of the reconstructed image. In principle, the effect of the EIRs on the measured PA signals can be ameliorated via deconvolution; images can be reconstructed subsequently by application of a reconstruction method that assumes an idealized EIR. Alternatively, the effect of the EIR can be incorporated into an imaging model and implicitly compensated for during reconstruction. In either case, the efficacy of the correction can be limited by errors in the assumed EIRs. In this work, a joint optimization approach to PACT image r...
An Efficient Approach for Computing Silhouette Coefficients
Moh'd B. Al- Zoubi
2008-01-01
Full Text Available One popular approach for finding the best number of clusters (K in a data set is through computing the silhouette coefficients. The silhouette coefficients for different values of K, are first found and then the maximum value of these coefficients is chosen. However, computing the silhouette coefficient for different Ks is a very time consuming process. This is due to the amount of CPU time spent on distance calculations. A proposed approach to compute the silhouette coefficient quickly had been presented. The approach was based on decreasing the number of addition operations when computing distances. The results were efficient and more than 50% of the CPU time was achieved when applied to different data sets.
When do perturbative approaches accurately capture the dynamics of complex quantum systems?
Fruchtman, Amir; Lambert, Neill; Gauger, Erik M.
2016-06-01
Understanding the dynamics of higher-dimensional quantum systems embedded in a complex environment remains a significant theoretical challenge. While several approaches yielding numerically converged solutions exist, these are computationally expensive and often provide only limited physical insight. Here we address the question: when do more intuitive and simpler-to-compute second-order perturbative approaches provide adequate accuracy? We develop a simple analytical criterion and verify its validity for the case of the much-studied FMO dynamics as well as the canonical spin-boson model.
Kepp, Kasper Planeta; Ooi, Bee Lean; Christensen, Hans Erik Mølager
2007-01-01
This work describes the computation and accurate reproduction of subtle shifts in reduction potentials for two mutants of the iron-sulfur protein Pyrococcus furiosus ferredoxin. The computational models involved only first-sphere ligands and differed with respect to one ligand, either acetate (as...
Toward exascale computing through neuromorphic approaches.
James, Conrad D.
2010-09-01
While individual neurons function at relatively low firing rates, naturally-occurring nervous systems not only surpass manmade systems in computing power, but accomplish this feat using relatively little energy. It is asserted that the next major breakthrough in computing power will be achieved through application of neuromorphic approaches that mimic the mechanisms by which neural systems integrate and store massive quantities of data for real-time decision making. The proposed LDRD provides a conceptual foundation for SNL to make unique advances toward exascale computing. First, a team consisting of experts from the HPC, MESA, cognitive and biological sciences and nanotechnology domains will be coordinated to conduct an exercise with the outcome being a concept for applying neuromorphic computing to achieve exascale computing. It is anticipated that this concept will involve innovative extension and integration of SNL capabilities in MicroFab, material sciences, high-performance computing, and modeling and simulation of neural processes/systems.
Accurate computation of surface stresses and forces with immersed boundary methods
Goza, Andres; Liska, Sebastian; Morley, Benjamin; Colonius, Tim
2016-09-01
Many immersed boundary methods solve for surface stresses that impose the velocity boundary conditions on an immersed body. These surface stresses may contain spurious oscillations that make them ill-suited for representing the physical surface stresses on the body. Moreover, these inaccurate stresses often lead to unphysical oscillations in the history of integrated surface forces such as the coefficient of lift. While the errors in the surface stresses and forces do not necessarily affect the convergence of the velocity field, it is desirable, especially in fluid-structure interaction problems, to obtain smooth and convergent stress distributions on the surface. To this end, we show that the equation for the surface stresses is an integral equation of the first kind whose ill-posedness is the source of spurious oscillations in the stresses. We also demonstrate that for sufficiently smooth delta functions, the oscillations may be filtered out to obtain physically accurate surface stresses. The filtering is applied as a post-processing procedure, so that the convergence of the velocity field is unaffected. We demonstrate the efficacy of the method by computing stresses and forces that converge to the physical stresses and forces for several test problems.
Accurate computation and interpretation of spin-dependent properties in metalloproteins
Rodriguez, Jorge
2006-03-01
Nature uses the properties of open-shell transition metal ions to carry out a variety of functions associated with vital life processes. Mononuclear and binuclear iron centers, in particular, are intriguing structural motifs present in many heme and non-heme proteins. Hemerythrin and methane monooxigenase, for example, are members of the latter class whose diiron active sites display magnetic ordering. We have developed a computational protocol based on spin density functional theory (SDFT) to accurately predict physico-chemical parameters of metal sites in proteins and bioinorganic complexes which traditionally had only been determined from experiment. We have used this new methodology to perform a comprehensive study of the electronic structure and magnetic properties of heme and non-heme iron proteins and related model compounds. We have been able to predict with a high degree of accuracy spectroscopic (Mössbauer, EPR, UV-vis, Raman) and magnetization parameters of iron proteins and, at the same time, gained unprecedented microscopic understanding of their physico-chemical properties. Our results have allowed us to establish important correlations between the electronic structure, geometry, spectroscopic data, and biochemical function of heme and non- heme iron proteins.
Toward accurate tooth segmentation from computed tomography images using a hybrid level set model
Gan, Yangzhou; Zhao, Qunfei [Department of Automation, Shanghai Jiao Tong University, and Key Laboratory of System Control and Information Processing, Ministry of Education of China, Shanghai 200240 (China); Xia, Zeyang, E-mail: zy.xia@siat.ac.cn, E-mail: jing.xiong@siat.ac.cn; Hu, Ying [Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, and The Chinese University of Hong Kong, Shenzhen 518055 (China); Xiong, Jing, E-mail: zy.xia@siat.ac.cn, E-mail: jing.xiong@siat.ac.cn [Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 510855 (China); Zhang, Jianwei [TAMS, Department of Informatics, University of Hamburg, Hamburg 22527 (Germany)
2015-01-15
Purpose: A three-dimensional (3D) model of the teeth provides important information for orthodontic diagnosis and treatment planning. Tooth segmentation is an essential step in generating the 3D digital model from computed tomography (CT) images. The aim of this study is to develop an accurate and efficient tooth segmentation method from CT images. Methods: The 3D dental CT volumetric images are segmented slice by slice in a two-dimensional (2D) transverse plane. The 2D segmentation is composed of a manual initialization step and an automatic slice by slice segmentation step. In the manual initialization step, the user manually picks a starting slice and selects a seed point for each tooth in this slice. In the automatic slice segmentation step, a developed hybrid level set model is applied to segment tooth contours from each slice. Tooth contour propagation strategy is employed to initialize the level set function automatically. Cone beam CT (CBCT) images of two subjects were used to tune the parameters. Images of 16 additional subjects were used to validate the performance of the method. Volume overlap metrics and surface distance metrics were adopted to assess the segmentation accuracy quantitatively. The volume overlap metrics were volume difference (VD, mm{sup 3}) and Dice similarity coefficient (DSC, %). The surface distance metrics were average symmetric surface distance (ASSD, mm), RMS (root mean square) symmetric surface distance (RMSSSD, mm), and maximum symmetric surface distance (MSSD, mm). Computation time was recorded to assess the efficiency. The performance of the proposed method has been compared with two state-of-the-art methods. Results: For the tested CBCT images, the VD, DSC, ASSD, RMSSSD, and MSSD for the incisor were 38.16 ± 12.94 mm{sup 3}, 88.82 ± 2.14%, 0.29 ± 0.03 mm, 0.32 ± 0.08 mm, and 1.25 ± 0.58 mm, respectively; the VD, DSC, ASSD, RMSSSD, and MSSD for the canine were 49.12 ± 9.33 mm{sup 3}, 91.57 ± 0.82%, 0.27 ± 0.02 mm, 0
A Big Data Approach to Computational Creativity
Varshney, Lav R; Varshney, Kush R; Bhattacharjya, Debarun; Schoergendorfer, Angela; Chee, Yi-Min
2013-01-01
Computational creativity is an emerging branch of artificial intelligence that places computers in the center of the creative process. Broadly, creativity involves a generative step to produce many ideas and a selective step to determine the ones that are the best. Many previous attempts at computational creativity, however, have not been able to achieve a valid selective step. This work shows how bringing data sources from the creative domain and from hedonic psychophysics together with big data analytics techniques can overcome this shortcoming to yield a system that can produce novel and high-quality creative artifacts. Our data-driven approach is demonstrated through a computational creativity system for culinary recipes and menus we developed and deployed, which can operate either autonomously or semi-autonomously with human interaction. We also comment on the volume, velocity, variety, and veracity of data in computational creativity.
Towards Lagrangian approach to quantum computations
Vlasov, A Yu
2003-01-01
In this work is discussed possibility and actuality of Lagrangian approach to quantum computations. Finite-dimensional Hilbert spaces used in this area provide some challenge for such consideration. The model discussed here can be considered as an analogue of Weyl quantization of field theory via path integral in L. D. Faddeev's approach. Weyl quantization is possible to use also in finite-dimensional case, and some formulas may be simply rewritten with change of integrals to finite sums. On the other hand, there are specific difficulties relevant to finite case. This work has some allusions with phase space models of quantum computations developed last time by different authors.
Computing Isolated Singular Solutions of Polynomial Systems Accurately: Case of Breadth One
Li, Nan
2010-01-01
We present a symbolic-numeric method to refine an approximate isolated singular solution $\\hat{\\mathbf{x}}=(\\hat{x}_{1}, \\ldots, \\hat{x}_{n})$ of a polynomial system $F=\\{f_1, \\ldots, f_n\\}$ when the Jacobian matrix of $F$ evaluated at $\\hat{\\mathbf{x}}$ has corank one approximately. Our new approach is based on the regularized Newton iteration and the computation of approximate Max Noether conditions satisfied at the singular solution. The size of matrices involved in our algorithm is bounded by $n \\times n$ and the algorithm converges quadratically if $\\hat{\\xx}$ is near the exact singular solution. The method has been implemented in Maple and can deal with both regular singularities and irregular singularities.
Stable, accurate and efficient computation of normal modes for horizontal stratified models
Wu, Bo; Chen, Xiaofei
2016-08-01
We propose an adaptive root-determining strategy that is very useful when dealing with trapped modes or Stoneley modes whose energies become very insignificant on the free surface in the presence of low-velocity layers or fluid layers in the model. Loss of modes in these cases or inaccuracy in the calculation of these modes may then be easily avoided. Built upon the generalized reflection/transmission coefficients, the concept of `family of secular functions' that we herein call `adaptive mode observers' is thus naturally introduced to implement this strategy, the underlying idea of which has been distinctly noted for the first time and may be generalized to other applications such as free oscillations or applied to other methods in use when these cases are encountered. Additionally, we have made further improvements upon the generalized reflection/transmission coefficient method; mode observers associated with only the free surface and low-velocity layers (and the fluid/solid interface if the model contains fluid layers) are adequate to guarantee no loss and high precision at the same time of any physically existent modes without excessive calculations. Finally, the conventional definition of the fundamental mode is reconsidered, which is entailed in the cases under study. Some computational aspects are remarked on. With the additional help afforded by our superior root-searching scheme and the possibility of speeding calculation using a less number of layers aided by the concept of `turning point', our algorithm is remarkably efficient as well as stable and accurate and can be used as a powerful tool for widely related applications.
Langer, Christoph; Lutz, M.; Kuehl, C.; Frey, N. [Christian-Albrechts-Universitaet Kiel, Department of Cardiology, Angiology and Critical Care Medicine, University Medical Center Schleswig-Holstein (Germany); Partner Site Hamburg/Kiel/Luebeck, DZHK (German Centre for Cardiovascular Research), Kiel (Germany); Both, M.; Sattler, B.; Jansen, O; Schaefer, P. [Christian-Albrechts-Universitaet Kiel, Department of Diagnostic Radiology, University Medical Center Schleswig-Holstein (Germany); Harders, H.; Eden, M. [Christian-Albrechts-Universitaet Kiel, Department of Cardiology, Angiology and Critical Care Medicine, University Medical Center Schleswig-Holstein (Germany)
2014-10-15
Late enhancement (LE) multi-slice computed tomography (leMDCT) was introduced for the visualization of (intra-) myocardial fibrosis in Hypertrophic Cardiomyopathy (HCM). LE is associated with adverse cardiac events. This analysis focuses on leMDCT derived LV muscle mass (LV-MM) which may be related to LE resulting in LE proportion for potential risk stratification in HCM. N=26 HCM-patients underwent leMDCT (64-slice-CT) and cardiovascular magnetic resonance (CMR). In leMDCT iodine contrast (Iopromid, 350 mg/mL; 150mL) was injected 7 minutes before imaging. Reconstructed short cardiac axis views served for planimetry. The study group was divided into three groups of varying LV-contrast. LeMDCT was correlated with CMR. The mean age was 64.2 ± 14 years. The groups of varying contrast differed in weight and body mass index (p < 0.05). In the group with good LV-contrast assessment of LV-MM resulted in 147.4 ± 64.8 g in leMDCT vs. 147.1 ± 65.9 in CMR (p > 0.05). In the group with sufficient contrast LV-MM appeared with 172 ± 30.8 g in leMDCT vs. 165.9 ± 37.8 in CMR (p > 0.05). Overall intra-/inter-observer variability of semiautomatic assessment of LV-MM showed an accuracy of 0.9 ± 8.6 g and 0.8 ± 9.2 g in leMDCT. All leMDCT-measures correlated well with CMR (r > 0.9). LeMDCT primarily performed for LE-visualization in HCM allows for accurate LV-volumetry including LV-MM in > 90 % of the cases. (orig.)
A novel fast and accurate pseudo-analytical simulation approach for MOAO
Gendron, É.; Charara, A.; Abdelfattah, A.; Gratadour, D.; Keyes, D.; Ltaief, H.; Morel, C.; Vidal, F.; Sevin, A.; Rousset, G.
2014-08-01
Multi-object adaptive optics (MOAO) is a novel adaptive optics (AO) technique for wide-field multi-object spectrographs (MOS). MOAO aims at applying dedicated wavefront corrections to numerous separated tiny patches spread over a large field of view (FOV), limited only by that of the telescope. The control of each deformable mirror (DM) is done individually using a tomographic reconstruction of the phase based on measurements from a number of wavefront sensors (WFS) pointing at natural and artificial guide stars in the field. We have developed a novel hybrid, pseudo-analytical simulation scheme, somewhere in between the end-to- end and purely analytical approaches, that allows us to simulate in detail the tomographic problem as well as noise and aliasing with a high fidelity, and including fitting and bandwidth errors thanks to a Fourier-based code. Our tomographic approach is based on the computation of the minimum mean square error (MMSE) reconstructor, from which we derive numerically the covariance matrix of the tomographic error, including aliasing and propagated noise. We are then able to simulate the point-spread function (PSF) associated to this covariance matrix of the residuals, like in PSF reconstruction algorithms. The advantage of our approach is that we compute the same tomographic reconstructor that would be computed when operating the real instrument, so that our developments open the way for a future on-sky implementation of the tomographic control, plus the joint PSF and performance estimation. The main challenge resides in the computation of the tomographic reconstructor which involves the inversion of a large matrix (typically 40 000 × 40 000 elements). To perform this computation efficiently, we chose an optimized approach based on the use of GPUs as accelerators and using an optimized linear algebra library: MORSE providing a significant speedup against standard CPU oriented libraries such as Intel MKL. Because the covariance matrix is
A novel fast and accurate pseudo-analytical simulation approach for MOAO
Gendron, É.
2014-08-04
Multi-object adaptive optics (MOAO) is a novel adaptive optics (AO) technique for wide-field multi-object spectrographs (MOS). MOAO aims at applying dedicated wavefront corrections to numerous separated tiny patches spread over a large field of view (FOV), limited only by that of the telescope. The control of each deformable mirror (DM) is done individually using a tomographic reconstruction of the phase based on measurements from a number of wavefront sensors (WFS) pointing at natural and artificial guide stars in the field. We have developed a novel hybrid, pseudo-analytical simulation scheme, somewhere in between the end-to- end and purely analytical approaches, that allows us to simulate in detail the tomographic problem as well as noise and aliasing with a high fidelity, and including fitting and bandwidth errors thanks to a Fourier-based code. Our tomographic approach is based on the computation of the minimum mean square error (MMSE) reconstructor, from which we derive numerically the covariance matrix of the tomographic error, including aliasing and propagated noise. We are then able to simulate the point-spread function (PSF) associated to this covariance matrix of the residuals, like in PSF reconstruction algorithms. The advantage of our approach is that we compute the same tomographic reconstructor that would be computed when operating the real instrument, so that our developments open the way for a future on-sky implementation of the tomographic control, plus the joint PSF and performance estimation. The main challenge resides in the computation of the tomographic reconstructor which involves the inversion of a large matrix (typically 40 000 × 40 000 elements). To perform this computation efficiently, we chose an optimized approach based on the use of GPUs as accelerators and using an optimized linear algebra library: MORSE providing a significant speedup against standard CPU oriented libraries such as Intel MKL. Because the covariance matrix is
Computer networking a top-down approach
Kurose, James
2017-01-01
Unique among computer networking texts, the Seventh Edition of the popular Computer Networking: A Top Down Approach builds on the author’s long tradition of teaching this complex subject through a layered approach in a “top-down manner.” The text works its way from the application layer down toward the physical layer, motivating readers by exposing them to important concepts early in their study of networking. Focusing on the Internet and the fundamentally important issues of networking, this text provides an excellent foundation for readers interested in computer science and electrical engineering, without requiring extensive knowledge of programming or mathematics. The Seventh Edition has been updated to reflect the most important and exciting recent advances in networking.
Hybrid soft computing approaches research and applications
Dutta, Paramartha; Chakraborty, Susanta
2016-01-01
The book provides a platform for dealing with the flaws and failings of the soft computing paradigm through different manifestations. The different chapters highlight the necessity of the hybrid soft computing methodology in general with emphasis on several application perspectives in particular. Typical examples include (a) Study of Economic Load Dispatch by Various Hybrid Optimization Techniques, (b) An Application of Color Magnetic Resonance Brain Image Segmentation by ParaOptiMUSIG activation Function, (c) Hybrid Rough-PSO Approach in Remote Sensing Imagery Analysis, (d) A Study and Analysis of Hybrid Intelligent Techniques for Breast Cancer Detection using Breast Thermograms, and (e) Hybridization of 2D-3D Images for Human Face Recognition. The elaborate findings of the chapters enhance the exhibition of the hybrid soft computing paradigm in the field of intelligent computing.
Tiwari, Saumya; Reddy, Vijaya B.; Bhargava, Rohit; Raman, Jaishankar
2015-01-01
Rejection is a common problem after cardiac transplants leading to significant number of adverse events and deaths, particularly in the first year of transplantation. The gold standard to identify rejection is endomyocardial biopsy. This technique is complex, cumbersome and requires a lot of expertise in the correct interpretation of stained biopsy sections. Traditional histopathology cannot be used actively or quickly during cardiac interventions or surgery. Our objective was to develop a stain-less approach using an emerging technology, Fourier transform infrared (FT-IR) spectroscopic imaging to identify different components of cardiac tissue by their chemical and molecular basis aided by computer recognition, rather than by visual examination using optical microscopy. We studied this technique in assessment of cardiac transplant rejection to evaluate efficacy in an example of complex cardiovascular pathology. We recorded data from human cardiac transplant patients’ biopsies, used a Bayesian classification protocol and developed a visualization scheme to observe chemical differences without the need of stains or human supervision. Using receiver operating characteristic curves, we observed probabilities of detection greater than 95% for four out of five histological classes at 10% probability of false alarm at the cellular level while correctly identifying samples with the hallmarks of the immune response in all cases. The efficacy of manual examination can be significantly increased by observing the inherent biochemical changes in tissues, which enables us to achieve greater diagnostic confidence in an automated, label-free manner. We developed a computational pathology system that gives high contrast images and seems superior to traditional staining procedures. This study is a prelude to the development of real time in situ imaging systems, which can assist interventionists and surgeons actively during procedures. PMID:25932912
Saumya Tiwari
Full Text Available Rejection is a common problem after cardiac transplants leading to significant number of adverse events and deaths, particularly in the first year of transplantation. The gold standard to identify rejection is endomyocardial biopsy. This technique is complex, cumbersome and requires a lot of expertise in the correct interpretation of stained biopsy sections. Traditional histopathology cannot be used actively or quickly during cardiac interventions or surgery. Our objective was to develop a stain-less approach using an emerging technology, Fourier transform infrared (FT-IR spectroscopic imaging to identify different components of cardiac tissue by their chemical and molecular basis aided by computer recognition, rather than by visual examination using optical microscopy. We studied this technique in assessment of cardiac transplant rejection to evaluate efficacy in an example of complex cardiovascular pathology. We recorded data from human cardiac transplant patients' biopsies, used a Bayesian classification protocol and developed a visualization scheme to observe chemical differences without the need of stains or human supervision. Using receiver operating characteristic curves, we observed probabilities of detection greater than 95% for four out of five histological classes at 10% probability of false alarm at the cellular level while correctly identifying samples with the hallmarks of the immune response in all cases. The efficacy of manual examination can be significantly increased by observing the inherent biochemical changes in tissues, which enables us to achieve greater diagnostic confidence in an automated, label-free manner. We developed a computational pathology system that gives high contrast images and seems superior to traditional staining procedures. This study is a prelude to the development of real time in situ imaging systems, which can assist interventionists and surgeons actively during procedures.
Accurate potential energy surfaces with a DFT+U(R) approach.
Kulik, Heather J; Marzari, Nicola
2011-11-21
We introduce an improvement to the Hubbard U augmented density functional approach known as DFT+U that incorporates variations in the value of self-consistently calculated, linear-response U with changes in geometry. This approach overcomes the one major shortcoming of previous DFT+U studies, i.e., the use of an averaged Hubbard U when comparing energies for different points along a potential energy surface is no longer required. While DFT+U is quite successful at providing accurate descriptions of localized electrons (e.g., d or f) by correcting self-interaction errors of standard exchange correlation functionals, we show several diatomic molecule examples where this position-dependent DFT+U(R) provides a significant two- to four-fold improvement over DFT+U predictions, when compared to accurate correlated quantum chemistry and experimental references. DFT+U(R) reduces errors in binding energies, frequencies, and equilibrium bond lengths by applying the linear-response, position-dependent U(R) at each configuration considered. This extension is most relevant where variations in U are large across the points being compared, as is the case with covalent diatomic molecules such as transition-metal oxides. We thus provide a tool for deciding whether a standard DFT+U approach is sufficient by determining the strength of the dependence of U on changes in coordinates. We also apply this approach to larger systems with greater degrees of freedom and demonstrate how DFT+U(R) may be applied automatically in relaxations, transition-state finding methods, and dynamics.
Unilateral hyperlucency of the lung: a systematic approach to accurate radiographic interpretation
Noh, Hyung Jun; Oh, Yu Whan; Choi, Eun Jung; Seo, Bo Kyung; Cho, Kyu Ran; Kang, Eun Young; Kim, Jung Hyuk [Korea University College of Medicine, Seoul (Korea, Republic of)
2002-12-01
The radiographic appearance of a unilateral hyperlucent lung is related to various conditions, the accurate radiographic interpretation of which requires a structured approach as well as an awareness of the spectrum of these entities. Firstly, it is important to determine whether a hyperlucent hemithorax is associated with artifacts resulting from rotation of the patient, grid cutoff, or the heel effect. The second step is to determine whether or not a hyperlucent lung is abnormal. Lung that is in fact normal may appear hyperlucent because of diffusely increased opacity of the opposite hemithorax. Thirdly, thoracic wall and soft tissue abnormalities such as mastectomy of Poland syndrome may cause hyperinflation. Lastly, abnormalities of lung parenchyma may result in hyperlucency. Lung abnormalities and be divided into two groups: a) obstructive or compensatory hyperinflation; and b) reduced vascular perfusion of the lung due to congenital or acquired vascular abnormalities. In this article, we describe and illustrate the imaging spectrum of these causes and outline a structured approach to accurate radiographic interpretation.
A Highly Accurate and Efficient Analytical Approach to Bridge Deck Free Vibration Analysis
D.J. Gorman
2000-01-01
Full Text Available The superposition method is employed to obtain an accurate analytical type solution for the free vibration frequencies and mode shapes of multi-span bridge decks. Free edge conditions are imposed on the long edges running in the direction of the deck. Inter-span support is of the simple (knife-edge type. The analysis is valid regardless of the number of spans or their individual lengths. Exact agreement is found when computed results are compared with known eigenvalues for bridge decks with all spans of equal length. Mode shapes and eigenvalues are presented for typical bridge decks of three and four span lengths. In each case torsional and non-torsional modes are studied.
Annecchione, Maria; Hatch, David; Hefford, Shane W.
2017-01-01
In this paper we investigate digital elevation model (DEM) sourcing requirements to compute gravity gradiometry terrain corrections accurate to 1 Eötvös (Eö) at observation heights of 80 m or more above ground. Such survey heights are typical in fixed-wing airborne surveying for resource exploration where the maximum signal-to-noise ratio is sought. We consider the accuracy of terrain corrections relevant for recent commercial airborne gravity gradiometry systems operating at the 10 Eö noise level and for future systems with a target noise level of 1 Eö. We focus on the requirements for the vertical gradient of the vertical component of gravity (Gdd) because this element of the gradient tensor is most commonly interpreted qualitatively and quantitatively. Terrain correction accuracy depends on the bare-earth DEM accuracy and spatial resolution. The bare-earth DEM accuracy and spatial resolution depends on its source. Two possible sources are considered: airborne LiDAR and Shuttle Radar Topography Mission (SRTM). The accuracy of an SRTM DEM is affected by vegetation height. The SRTM footprint is also larger and the DEM resolution is thus lower. However, resolution requirements relax as relief decreases. Publicly available LiDAR data and 1 arc-second and 3 arc-second SRTM data were selected over four study areas representing end member cases of vegetation cover and relief. The four study areas are presented as reference material for processing airborne gravity gradiometry data at the 1 Eö noise level with 50 m spatial resolution. From this investigation we find that to achieve 1 Eö accuracy in the terrain correction at 80 m height airborne LiDAR data are required even when terrain relief is a few tens of meters and the vegetation is sparse. However, as satellite ranging technologies progress bare-earth DEMs of sufficient accuracy and resolution may be sourced at lesser cost. We found that a bare-earth DEM of 10 m resolution and 2 m accuracy are sufficient for
Boelens, O.J.; Laban, M.; Beek, van C.M.; Leeden, van der R.
2001-01-01
In this report the contribution of the National Aerospace Laboratory NLR to the ’CFD Drag Pre- diction Workshop’ organized by the AIAA in Anaheim, CA, on June 9-10, 2001, is presented. This contribution consists of both the results of all test cases and a discussion on the accurate computation of dr
Handbook of computational approaches to counterterrorism
Subrahmanian, VS
2012-01-01
Terrorist groups throughout the world have been studied primarily through the use of social science methods. However, major advances in IT during the past decade have led to significant new ways of studying terrorist groups, making forecasts, learning models of their behaviour, and shaping policies about their behaviour. Handbook of Computational Approaches to Counterterrorism provides the first in-depth look at how advanced mathematics and modern computing technology is shaping the study of terrorist groups. This book includes contributions from world experts in the field, and presents extens
Efficient and Accurate Computational Framework for Injector Design and Analysis Project
National Aeronautics and Space Administration — CFD codes used to simulate upper stage expander cycle engines are not adequately mature to support design efforts. Rapid and accurate simulations require more...
Ambikasaran, Sivaram
2015-01-01
Using accurate multi-component diffusion treatment in numerical combustion studies remains formidable due to the computational cost associated with solving for diffusion velocities. To obtain the diffusion velocities, for low density gases, one needs to solve the Stefan-Maxwell equations along with the zero diffusion flux criteria, which scales as $\\mathcal{O}(N^3)$, when solved exactly. In this article, we propose an accurate, fast, direct and robust algorithm to compute multi-component diffusion velocities. To our knowledge, this is the first provably accurate algorithm (the solution can be obtained up to an arbitrary degree of precision) scaling at a computational complexity of $\\mathcal{O}(N)$ in finite precision. The key idea involves leveraging the fact that the matrix of the reciprocal of the binary diffusivities, $V$, is low rank, with its rank being independent of the number of species involved. The low rank representation of matrix $V$ is computed in a fast manner at a computational complexity of $\\...
Ustinov, E A
2014-10-01
Commensurate-incommensurate (C-IC) transition of krypton molecular layer on graphite received much attention in recent decades in theoretical and experimental researches. However, there still exists a possibility of generalization of the phenomenon from thermodynamic viewpoint on the basis of accurate molecular simulation. Recently, a new technique was developed for analysis of two-dimensional (2D) phase transitions in systems involving a crystalline phase, which is based on accounting for the effect of temperature and the chemical potential on the lattice constant of the 2D layer using the Gibbs-Duhem equation [E. A. Ustinov, J. Chem. Phys. 140, 074706 (2014)]. The technique has allowed for determination of phase diagrams of 2D argon layers on the uniform surface and in slit pores. This paper extends the developed methodology on systems accounting for the periodic modulation of the substrate potential. The main advantage of the developed approach is that it provides highly accurate evaluation of the chemical potential of crystalline layers, which allows reliable determination of temperature and other parameters of various 2D phase transitions. Applicability of the methodology is demonstrated on the krypton-graphite system. Analysis of phase diagram of the krypton molecular layer, thermodynamic functions of coexisting phases, and a method of prediction of adsorption isotherms is considered accounting for a compression of the graphite due to the krypton-carbon interaction. The temperature and heat of C-IC transition has been reliably determined for the gas-solid and solid-solid system.
Ustinov, E. A., E-mail: eustinov@mail.wplus.net [Ioffe Physical Technical Institute, 26 Polytechnicheskaya, St. Petersburg 194021 (Russian Federation)
2014-10-07
Commensurate–incommensurate (C-IC) transition of krypton molecular layer on graphite received much attention in recent decades in theoretical and experimental researches. However, there still exists a possibility of generalization of the phenomenon from thermodynamic viewpoint on the basis of accurate molecular simulation. Recently, a new technique was developed for analysis of two-dimensional (2D) phase transitions in systems involving a crystalline phase, which is based on accounting for the effect of temperature and the chemical potential on the lattice constant of the 2D layer using the Gibbs–Duhem equation [E. A. Ustinov, J. Chem. Phys. 140, 074706 (2014)]. The technique has allowed for determination of phase diagrams of 2D argon layers on the uniform surface and in slit pores. This paper extends the developed methodology on systems accounting for the periodic modulation of the substrate potential. The main advantage of the developed approach is that it provides highly accurate evaluation of the chemical potential of crystalline layers, which allows reliable determination of temperature and other parameters of various 2D phase transitions. Applicability of the methodology is demonstrated on the krypton–graphite system. Analysis of phase diagram of the krypton molecular layer, thermodynamic functions of coexisting phases, and a method of prediction of adsorption isotherms is considered accounting for a compression of the graphite due to the krypton–carbon interaction. The temperature and heat of C-IC transition has been reliably determined for the gas–solid and solid–solid system.
Novel computational approaches characterizing knee physiotherapy
Wangdo Kim; Veloso, Antonio P; Duarte Araujo; Kohles, Sean S.
2014-01-01
A knee joint’s longevity depends on the proper integration of structural components in an axial alignment. If just one of the components is abnormally off-axis, the biomechanical system fails, resulting in arthritis. The complexity of various failures in the knee joint has led orthopedic surgeons to select total knee replacement as a primary treatment. In many cases, this means sacrificing much of an otherwise normal joint. Here, we review novel computational approaches to describe knee physi...
Advanced computational approaches to biomedical engineering
Saha, Punam K; Basu, Subhadip
2014-01-01
There has been rapid growth in biomedical engineering in recent decades, given advancements in medical imaging and physiological modelling and sensing systems, coupled with immense growth in computational and network technology, analytic approaches, visualization and virtual-reality, man-machine interaction and automation. Biomedical engineering involves applying engineering principles to the medical and biological sciences and it comprises several topics including biomedicine, medical imaging, physiological modelling and sensing, instrumentation, real-time systems, automation and control, sig
Computational Approaches to Nucleic Acid Origami.
Jabbari, Hosna; Aminpour, Maral; Montemagno, Carlo
2015-10-12
Recent advances in experimental DNA origami have dramatically expanded the horizon of DNA nanotechnology. Complex 3D suprastructures have been designed and developed using DNA origami with applications in biomaterial science, nanomedicine, nanorobotics, and molecular computation. Ribonucleic acid (RNA) origami has recently been realized as a new approach. Similar to DNA, RNA molecules can be designed to form complex 3D structures through complementary base pairings. RNA origami structures are, however, more compact and more thermodynamically stable due to RNA's non-canonical base pairing and tertiary interactions. With all these advantages, the development of RNA origami lags behind DNA origami by a large gap. Furthermore, although computational methods have proven to be effective in designing DNA and RNA origami structures and in their evaluation, advances in computational nucleic acid origami is even more limited. In this paper, we review major milestones in experimental and computational DNA and RNA origami and present current challenges in these fields. We believe collaboration between experimental nanotechnologists and computer scientists are critical for advancing these new research paradigms.
Application of a polynomial spline in higher-order accurate viscous-flow computations
Turner, M. G.; Keith, J. S.; Ghia, K. N.; Ghia, U.
1982-01-01
A quartic spline, S(4,2), is proposed which overcomes some of the difficulties associated with the use of splines S(5,3) and S(3,1) and provides fourth-order accurate results with relatively few grid points. The accuracy of spline S(4,2) is comparable to or better than that of the fourth-order box scheme and the compact differencing scheme. The use of spline S(4,2) is suggested as a possible way of obtaining fourth-order accurate solutions to Navier-Stokes equations.
Esque, Jeremy; Cecchini, Marco
2015-04-23
The calculation of the free energy of conformation is key to understanding the function of biomolecules and has attracted significant interest in recent years. Here, we present an improvement of the confinement method that was designed for use in the context of explicit solvent MD simulations. The development involves an additional step in which the solvation free energy of the harmonically restrained conformers is accurately determined by multistage free energy perturbation simulations. As a test-case application, the newly introduced confinement/solvation free energy (CSF) approach was used to compute differences in free energy between conformers of the alanine dipeptide in explicit water. The results are in excellent agreement with reference calculations based on both converged molecular dynamics and umbrella sampling. To illustrate the general applicability of the method, conformational equilibria of met-enkephalin (5 aa) and deca-alanine (10 aa) in solution were also analyzed. In both cases, smoothly converged free-energy results were obtained in agreement with equilibrium sampling or literature calculations. These results demonstrate that the CSF method may provide conformational free-energy differences of biomolecules with small statistical errors (below 0.5 kcal/mol) and at a moderate computational cost even with a full representation of the solvent.
A novel PCR-based approach for accurate identification of Vibrio parahaemolyticus
Ruichao eLi
2016-01-01
Full Text Available A PCR-based assay was developed for more accurate identification of Vibrio parahaemolyticus through targeting the blaCARB-17 like element, an intrinsic β-lactamase gene that may also be regarded as a novel species-specific genetic marker of this organism. Phylogenetic analysis showed that blaCARB-17 like genes were more conservative than the tlh, toxR and atpA genes, the genetic markers commonly used as detection targets in identification of V. parahaemolyticus. Our data showed that this blaCARB-17-specific PCR-based detection approach consistently achieved 100% specificity, whereas PCR targeting the tlh, toxR and atpA genes occasionally produced false positive results. Furthermore, a positive result of this test is consistently associated with an intrinsic ampicillin resistance phenotype of the test organism, presumably conferred by the products of blaCARB-17 like genes. We envision that combined analysis of the unique genetic and phenotypic characteristics conferred by blaCARB-17 shall further enhance the detection specificity of this novel yet easy-to-use detection approach to a level superior to the conventional methods used in V. parahaemolyticus detection and identification.
A Novel PCR-Based Approach for Accurate Identification of Vibrio parahaemolyticus.
Li, Ruichao; Chiou, Jiachi; Chan, Edward Wai-Chi; Chen, Sheng
2016-01-01
A PCR-based assay was developed for more accurate identification of Vibrio parahaemolyticus through targeting the bla CARB-17 like element, an intrinsic β-lactamase gene that may also be regarded as a novel species-specific genetic marker of this organism. Homologous analysis showed that bla CARB-17 like genes were more conservative than the tlh, toxR and atpA genes, the genetic markers commonly used as detection targets in identification of V. parahaemolyticus. Our data showed that this bla CARB-17-specific PCR-based detection approach consistently achieved 100% specificity, whereas PCR targeting the tlh and atpA genes occasionally produced false positive results. Furthermore, a positive result of this test is consistently associated with an intrinsic ampicillin resistance phenotype of the test organism, presumably conferred by the products of bla CARB-17 like genes. We envision that combined analysis of the unique genetic and phenotypic characteristics conferred by bla CARB-17 shall further enhance the detection specificity of this novel yet easy-to-use detection approach to a level superior to the conventional methods used in V. parahaemolyticus detection and identification.
Computer Forensics Education - the Open Source Approach
Huebner, Ewa; Bem, Derek; Cheung, Hon
In this chapter we discuss the application of the open source software tools in computer forensics education at tertiary level. We argue that open source tools are more suitable than commercial tools, as they provide the opportunity for students to gain in-depth understanding and appreciation of the computer forensic process as opposed to familiarity with one software product, however complex and multi-functional. With the access to all source programs the students become more than just the consumers of the tools as future forensic investigators. They can also examine the code, understand the relationship between the binary images and relevant data structures, and in the process gain necessary background to become the future creators of new and improved forensic software tools. As a case study we present an advanced subject, Computer Forensics Workshop, which we designed for the Bachelor's degree in computer science at the University of Western Sydney. We based all laboratory work and the main take-home project in this subject on open source software tools. We found that without exception more than one suitable tool can be found to cover each topic in the curriculum adequately. We argue that this approach prepares students better for forensic field work, as they gain confidence to use a variety of tools, not just a single product they are familiar with.
Sharma, Vivek; Salwan, Richa; Sharma, P. N.; Gulati, Arvind
2017-01-01
Genome-wide studies of transcripts expression help in systematic monitoring of genes and allow targeting of candidate genes for future research. In contrast to relatively stable genomic data, the expression of genes is dynamic and regulated both at time and space level at different level in. The variation in the rate of translation is specific for each protein. Both the inherent nature of an mRNA molecule to be translated and the external environmental stimuli can affect the efficiency of the translation process. In biocontrol agents (BCAs), the molecular response at translational level may represents noise-like response of absolute transcript level and an adaptive response to physiological and pathological situations representing subset of mRNAs population actively translated in a cell. The molecular responses of biocontrol are complex and involve multistage regulation of number of genes. The use of high-throughput techniques has led to rapid increase in volume of transcriptomics data of Trichoderma. In general, almost half of the variations of transcriptome and protein level are due to translational control. Thus, studies are required to integrate raw information from different “omics” approaches for accurate depiction of translational response of BCAs in interaction with plants and plant pathogens. The studies on translational status of only active mRNAs bridging with proteome data will help in accurate characterization of only a subset of mRNAs actively engaged in translation. This review highlights the associated bottlenecks and use of state-of-the-art procedures in addressing the gap to accelerate future accomplishment of biocontrol mechanisms. PMID:28900417
Accurate and efficient computation of nonlocal potentials based on Gaussian-sum approximation
Exl, Lukas; Mauser, Norbert J.; Yong ZHANG
2015-01-01
We introduce an accurate and efficient method for a class of nonlocal potential evaluations with free boundary condition, including the 3D/2D Coulomb, 2D Poisson and 3D dipolar potentials. Our method is based on a Gaussian-sum approximation of the singular convolution kernel and Taylor expansion of the density. Starting from the convolution formulation, for smooth and fast decaying densities, we make a full use of the Fourier pseudospectral (plane wave) approximation of the density and a sepa...
Tweten, D J; Okamoto, R J; Bayly, P V
2017-01-17
To establish the essential requirements for characterization of a transversely isotropic material by magnetic resonance elastography (MRE). Three methods for characterizing nearly incompressible, transversely isotropic (ITI) materials were used to analyze data from closed-form expressions for traveling waves, finite-element (FE) simulations of waves in homogeneous ITI material, and FE simulations of waves in heterogeneous material. Key properties are the complex shear modulus μ2 , shear anisotropy ϕ=μ1/μ2-1, and tensile anisotropy ζ=E1/E2-1. Each method provided good estimates of ITI parameters when both slow and fast shear waves with multiple propagation directions were present. No method gave accurate estimates when the displacement field contained only slow shear waves, only fast shear waves, or waves with only a single propagation direction. Methods based on directional filtering are robust to noise and include explicit checks of propagation and polarization. Curl-based methods led to more accurate estimates in low noise conditions. Parameter estimation in heterogeneous materials is challenging for all methods. Multiple shear waves, both slow and fast, with different propagation directions, must be present in the displacement field for accurate parameter estimates in ITI materials. Experimental design and data analysis can ensure that these requirements are met. Magn Reson Med, 2017. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.
Computational approaches to analogical reasoning current trends
Richard, Gilles
2014-01-01
Analogical reasoning is known as a powerful mode for drawing plausible conclusions and solving problems. It has been the topic of a huge number of works by philosophers, anthropologists, linguists, psychologists, and computer scientists. As such, it has been early studied in artificial intelligence, with a particular renewal of interest in the last decade. The present volume provides a structured view of current research trends on computational approaches to analogical reasoning. It starts with an overview of the field, with an extensive bibliography. The 14 collected contributions cover a large scope of issues. First, the use of analogical proportions and analogies is explained and discussed in various natural language processing problems, as well as in automated deduction. Then, different formal frameworks for handling analogies are presented, dealing with case-based reasoning, heuristic-driven theory projection, commonsense reasoning about incomplete rule bases, logical proportions induced by similarity an...
An Approach to Ad hoc Cloud Computing
Kirby, Graham; Macdonald, Angus; Fernandes, Alvaro
2010-01-01
We consider how underused computing resources within an enterprise may be harnessed to improve utilization and create an elastic computing infrastructure. Most current cloud provision involves a data center model, in which clusters of machines are dedicated to running cloud infrastructure software. We propose an additional model, the ad hoc cloud, in which infrastructure software is distributed over resources harvested from machines already in existence within an enterprise. In contrast to the data center cloud model, resource levels are not established a priori, nor are resources dedicated exclusively to the cloud while in use. A participating machine is not dedicated to the cloud, but has some other primary purpose such as running interactive processes for a particular user. We outline the major implementation challenges and one approach to tackling them.
Interacting electrons theory and computational approaches
Martin, Richard M; Ceperley, David M
2016-01-01
Recent progress in the theory and computation of electronic structure is bringing an unprecedented level of capability for research. Many-body methods are becoming essential tools vital for quantitative calculations and understanding materials phenomena in physics, chemistry, materials science and other fields. This book provides a unified exposition of the most-used tools: many-body perturbation theory, dynamical mean field theory and quantum Monte Carlo simulations. Each topic is introduced with a less technical overview for a broad readership, followed by in-depth descriptions and mathematical formulation. Practical guidelines, illustrations and exercises are chosen to enable readers to appreciate the complementary approaches, their relationships, and the advantages and disadvantages of each method. This book is designed for graduate students and researchers who want to use and understand these advanced computational tools, get a broad overview, and acquire a basis for participating in new developments.
A computational language approach to modeling prose recall in schizophrenia.
Rosenstein, Mark; Diaz-Asper, Catherine; Foltz, Peter W; Elvevåg, Brita
2014-06-01
Many cortical disorders are associated with memory problems. In schizophrenia, verbal memory deficits are a hallmark feature. However, the exact nature of this deficit remains elusive. Modeling aspects of language features used in memory recall have the potential to provide means for measuring these verbal processes. We employ computational language approaches to assess time-varying semantic and sequential properties of prose recall at various retrieval intervals (immediate, 30 min and 24 h later) in patients with schizophrenia, unaffected siblings and healthy unrelated control participants. First, we model the recall data to quantify the degradation of performance with increasing retrieval interval and the effect of diagnosis (i.e., group membership) on performance. Next we model the human scoring of recall performance using an n-gram language sequence technique, and then with a semantic feature based on Latent Semantic Analysis. These models show that automated analyses of the recalls can produce scores that accurately mimic human scoring. The final analysis addresses the validity of this approach by ascertaining the ability to predict group membership from models built on the two classes of language features. Taken individually, the semantic feature is most predictive, while a model combining the features improves accuracy of group membership prediction slightly above the semantic feature alone as well as over the human rating approach. We discuss the implications for cognitive neuroscience of such a computational approach in exploring the mechanisms of prose recall.
Sun, Y Y; Kim, Yong-Hyun; Lee, Kyuho; Zhang, S B
2008-10-21
Density functional theory (DFT) in the commonly used local density or generalized gradient approximation fails to describe van der Waals (vdW) interactions that are vital to organic, biological, and other molecular systems. Here, we propose a simple, efficient, yet accurate local atomic potential (LAP) approach, named DFT+LAP, for including vdW interactions in the framework of DFT. The LAPs for H, C, N, and O are generated by fitting the DFT+LAP potential energy curves of small molecule dimers to those obtained from coupled cluster calculations with single, double, and perturbatively treated triple excitations, CCSD(T). Excellent transferability of the LAPs is demonstrated by remarkable agreement with the JSCH-2005 benchmark database [P. Jurecka et al. Phys. Chem. Chem. Phys. 8, 1985 (2006)], which provides the interaction energies of CCSD(T) quality for 165 vdW and hydrogen-bonded complexes. For over 100 vdW dominant complexes in this database, our DFT+LAP calculations give a mean absolute deviation from the benchmark results less than 0.5 kcal/mol. The DFT+LAP approach involves no extra computational cost other than standard DFT calculations and no modification of existing DFT codes, which enables straightforward quantum simulations, such as ab initio molecular dynamics, on biomolecular systems, as well as on other organic systems.
Huré, J.-M.; Hersant, F.
2017-02-01
We compute the structure of a self-gravitating torus with polytropic equation of state (EOS) rotating in an imposed centrifugal potential. The Poisson solver is based on isotropic multigrid with optimal covering factor (fluid section-to-grid area ratio). We work at second order in the grid resolution for both finite difference and quadrature schemes. For soft EOS (i.e. polytropic index n ≥ 1), the underlying second order is naturally recovered for boundary values and any other integrated quantity sensitive to the mass density (mass, angular momentum, volume, virial parameter, etc.), i.e. errors vary with the number N of nodes per direction as ˜1/N2. This is, however, not observed for purely geometrical quantities (surface area, meridional section area, volume), unless a subgrid approach is considered (i.e. boundary detection). Equilibrium sequences are also much better described, especially close to critical rotation. Yet another technical effort is required for hard EOS (n < 1), due to infinite mass density gradients at the fluid surface. We fix the problem by using kernel splitting. Finally, we propose an accelerated version of the self-consistent field (SCF) algorithm based on a node-by-node pre-conditioning of the mass density at each step. The computing time is reduced by a factor of 2 typically, regardless of the polytropic index. There is a priori no obstacle to applying these results and techniques to ellipsoidal configurations and even to 3D configurations.
Krokhotin, Andrey; Dokholyan, Nikolay V
2015-01-01
Computational methods can provide significant insights into RNA structure and dynamics, bridging the gap in our understanding of the relationship between structure and biological function. Simulations enrich and enhance our understanding of data derived on the bench, as well as provide feasible alternatives to costly or technically challenging experiments. Coarse-grained computational models of RNA are especially important in this regard, as they allow analysis of events occurring in timescales relevant to RNA biological function, which are inaccessible through experimental methods alone. We have developed a three-bead coarse-grained model of RNA for discrete molecular dynamics simulations. This model is efficient in de novo prediction of short RNA tertiary structure, starting from RNA primary sequences of less than 50 nucleotides. To complement this model, we have incorporated additional base-pairing constraints and have developed a bias potential reliant on data obtained from hydroxyl probing experiments that guide RNA folding to its correct state. By introducing experimentally derived constraints to our computer simulations, we are able to make reliable predictions of RNA tertiary structures up to a few hundred nucleotides. Our refined model exemplifies a valuable benefit achieved through integration of computation and experimental methods.
Accurate Computed Enthalpies of Spin Crossover in Iron and Cobalt Complexes
Kepp, Kasper Planeta; Cirera, J
2009-01-01
Despite their importance in many chemical processes, the relative energies of spin states of transition metal complexes have so far been haunted by large computational errors. By the use of six functionals, B3LYP, BP86, TPSS, TPSSh, M06L, and M06L, this work studies nine complexes (seven with iron...
Ng, C. N.; Chu, T. P.; Wu, Huasheng; Tong, S. Y.; Huang, Hong
1997-03-01
We compare multiple scattering results of angle-resolved photoelectron diffraction spectra between the exact slab method and the separable propagator perturbation method. In the slab method,footnote C.H. Li, A.R. Lubinsky and S.Y. Tong, Phys. Rev. B17, 3128 (1978). the source wave and multiple scattering within the strong scattering atomic layers are expanded in spherical waves while interlayer scattering is expressed in plane waves. The transformation between spherical waves and plane waves is done exactly. The plane waves are then matched across the solid-vacuum interface to a single outgoing plane wave in the detector's direction. The separable propagator perturbation approach uses two approximations: (i) A separable representation of the Green's function propagator and (ii) A perturbation expansion of multiple scattering terms. Results of c(2x2) S-Ni(001) show that this approximate method fails to converge due to the very slow convergence of the separable representation for scattering angles less than 90^circ. However, this method is accurate in the backscattering regime and may be applied to XAFS calculations.(J.J. Rehr and R.C. Albers, Phys. Rev. B41, 8139 (1990).) The use of this method for angle-resolved photoelectron diffraction spectra is substantially less reliable.
Li, Xin; Tu, Yaoquan; Tian, He; Ågren, Hans
2010-03-01
Metal ions play essential roles in biological processes and have attracted much attention in both experimental and theoretical fields. By using the molecular dynamics simulation technology, we here present a fitting-refining procedure for deriving Lennard-Jones parameters of aqua metal ions toward the ultimate goal of accurately reproducing the experimentally observed hydration free energies and structures. The polarizable SWM4-DP water model {proposed by Lamoureux et al. [J. Chem. Phys. 119, 5185 (2003)]} is used to properly describe the polarization effects of water molecules that interact with the ions. The Lennard-Jones parameters of the metal ions are first obtained by fitting the quantum mechanical potential energies of the hexahydrated complex and are subsequently refined through comparison between the calculated and experimentally measured hydration free energies and structures. In general, the derived Lennard-Jones parameters for the metal ions are found to reproduce hydration free energies accurately and to predict hydration structures that are in good agreement with experimental observations. Dynamical properties are also well reproduced by the derived Lennard-Jones parameters.
Solubility of nonelectrolytes: a first-principles computational approach.
Jackson, Nicholas E; Chen, Lin X; Ratner, Mark A
2014-05-15
Using a combination of classical molecular dynamics and symmetry adapted intermolecular perturbation theory, we develop a high-accuracy computational method for examining the solubility energetics of nonelectrolytes. This approach is used to accurately compute the cohesive energy density and Hildebrand solubility parameters of 26 molecular liquids. The energy decomposition of symmetry adapted perturbation theory is then utilized to develop multicomponent Hansen-like solubility parameters. These parameters are shown to reproduce the solvent categorizations (nonpolar, polar aprotic, or polar protic) of all molecular liquids studied while lending quantitative rigor to these qualitative categorizations via the introduction of simple, easily computable parameters. Notably, we find that by monitoring the first-order exchange energy contribution to the total interaction energy, one can rigorously determine the hydrogen bonding character of a molecular liquid. Finally, this method is applied to compute explicitly the Flory interaction parameter and the free energy of mixing for two different small molecule mixtures, reproducing the known miscibilities. This methodology represents an important step toward the prediction of molecular solubility from first principles.
Chaoying Bai; Rui Zhao; Stewart Greenhalgh
2009-01-01
A novel hybrid approach for earthquake location is proposed which uses a combined coarse global search and fine local inversion with a minimum search routine, plus an examination of the root mean squares (RMS) error distribution. The method exploits the advantages of network ray tracing and robust formulation of the Frechet derivatives to simultaneously update all possible initial source parameters around most local minima (including the global minimum) in the solution space, and finally to determine the likely global solution. Several synthetic examples involving a 3-D complex velocity model and a challenging source-receiver layout are used to demonstrate the capability of the newly-developed method. This new global-local hybrid solution technique not only incorporates the significant benefits of our recently published hypocenter determination procedure for multiple earthquake parameters, but also offers the attractive features of global optimal searching in the RMS travel time error distribution. Unlike the traditional global search method, for example, the Monte Carlo approach, where millions of tests have to be done to find the final global solution, the new method only conducts a matrix inversion type local search but does it multiple times simultaneously throughout the model volume to seek a global solution. The search is aided by inspection of the RMS error distribution. Benchmark tests against two popular approaches, the direct grid search method and the oct-tree important sampling method, indicate that the hybrid global-local inversion yields comparable location accuracy and is not sensitive to modest level of noise data, but more importantly it offers two-order of magnitude speed-up in computational effort. Such an improvement, combined with high accuracy, make it a promising hypocenter determination scheme in earthquake early warning, tsunami early warning, rapid hazard assessment and emergency response after strong earthquake occurrence.
Accurate computation of Galerkin double surface integrals in the 3-D boundary element method
Adelman, Ross; Duraiswami, Ramani
2015-01-01
Many boundary element integral equation kernels are based on the Green's functions of the Laplace and Helmholtz equations in three dimensions. These include, for example, the Laplace, Helmholtz, elasticity, Stokes, and Maxwell's equations. Integral equation formulations lead to more compact, but dense linear systems. These dense systems are often solved iteratively via Krylov subspace methods, which may be accelerated via the fast multipole method. There are advantages to Galerkin formulations for such integral equations, as they treat problems associated with kernel singularity, and lead to symmetric and better conditioned matrices. However, the Galerkin method requires each entry in the system matrix to be created via the computation of a double surface integral over one or more pairs of triangles. There are a number of semi-analytical methods to treat these integrals, which all have some issues, and are discussed in this paper. We present novel methods to compute all the integrals that arise in Galerkin fo...
Identification of Suitable Grid Size for Accurate Computation of Run-up Height
Manasa Ranjan Behera
2010-09-01
Full Text Available A numerical investigation has been carried out to obtain a non-dimensional grid size (grid size/ tsunami base width for the near shore discretisation of computational domains for long wave modelling. A 1D domain has been considered in which, the flow has been solved by 1D shallow water equations with vertically integrated flow variables. The sensitivity study of the grid size was carried out in the 1D channel with an open boundary at one end and shelf boundary at the other end. The grid size was varied from 10 m to 1000 m and its effect on the computation of the tsunami run-up along the shoreline has been investigated. The non-dimensional grid size for the computation of run-up was optimised by comparing the non-dimensional run-up (tsunami run-up/initial tsunami height and a threshold value of 5.0e-4 was obtained. Further, the study was extended to real scenario by adopting various grids for the shelf region of northern Tamil Nadu coast, south east coast of India in 2D and a suitable grid size was obtained.
Ellison, Donald; Conway, Bruce; Englander, Jacob
2015-01-01
A significant body of work exists showing that providing a nonlinear programming (NLP) solver with expressions for the problem constraint gradient substantially increases the speed of program execution and can also improve the robustness of convergence, especially for local optimizers. Calculation of these derivatives is often accomplished through the computation of spacecraft's state transition matrix (STM). If the two-body gravitational model is employed as is often done in the context of preliminary design, closed form expressions for these derivatives may be provided. If a high fidelity dynamics model, that might include perturbing forces such as the gravitational effect from multiple third bodies and solar radiation pressure is used then these STM's must be computed numerically. We present a method for the power hardward model and a full ephemeris model. An adaptive-step embedded eight order Dormand-Prince numerical integrator is discussed and a method for the computation of the time of flight derivatives in this framework is presented. The use of these numerically calculated derivatieves offer a substantial improvement over finite differencing in the context of a global optimizer. Specifically the inclusion of these STM's into the low thrust missiondesign tool chain in use at NASA Goddard Spaceflight Center allows for an increased preliminary mission design cadence.
Necessary conditions for accurate computations of three-body partial decay widths
Garrido, E; Fedorov, D V
2008-01-01
The partial width for decay of a resonance into three fragments is largely determined at distances where the energy is smaller than the effective potential producing the corresponding wave function. At short distances the many-body properties are accounted for by preformation or spectroscopic factors. We use the adiabatic expansion method combined with the WKB approximation to obtain the indispensable cluster model wave functions at intermediate and larger distances. We test the concept by deriving conditions for the minimal basis expressed in terms of partial waves and radial nodes. We compare results for different effective interactions and methods. Agreement is found with experimental values for a sufficiently large basis. We illustrate the ideas with realistic examples from $\\alpha$-emission of $^{12}$C and two-proton emission of $^{17}$Ne. Basis requirements for accurate momentum distributions are briefly discussed.
Necessary conditions for accurate computations of three-body partial decay widths
Garrido, E.; Jensen, A. S.; Fedorov, D. V.
2008-09-01
The partial width for decay of a resonance into three fragments is largely determined at distances where the energy is smaller than the effective potential producing the corresponding wave function. At short distances the many-body properties are accounted for by preformation or spectroscopic factors. We use the adiabatic expansion method combined with the WKB approximation to obtain the indispensable cluster model wave functions at intermediate and larger distances. We test the concept by deriving conditions for the minimal basis expressed in terms of partial waves and radial nodes. We compare results for different effective interactions and methods. Agreement is found with experimental values for a sufficiently large basis. We illustrate the ideas with realistic examples from α emission of C12 and two-proton emission of Ne17. Basis requirements for accurate momentum distributions are briefly discussed.
Accurate computation of surface stresses and forces with immersed boundary methods
Goza, Andres; Morley, Benjamin; Colonius, Tim
2016-01-01
Many immersed boundary methods solve for surface stresses that impose the velocity boundary conditions on an immersed body. These surface stresses may contain spurious oscillations that make them ill-suited for representing the physical surface stresses on the body. Moreover, these inaccurate stresses often lead to unphysical oscillations in the history of integrated surface forces such as the coefficient of lift. While the errors in the surface stresses and forces do not necessarily affect the convergence of the velocity field, it is desirable, especially in fluid-structure interaction problems, to obtain smooth and convergent stress distributions on the surface. To this end, we show that the equation for the surface stresses is an integral equation of the first kind whose ill-posedness is the source of spurious oscillations in the stresses. We also demonstrate that for sufficiently smooth delta functions, the oscillations may be filtered out to obtain physically accurate surface stresses. The filtering is a...
Osei-Kuffuor, Daniel [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Fattebert, Jean-Luc [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
2014-01-01
We present the first truly scalable first-principles molecular dynamics algorithm with O(N) complexity and controllable accuracy, capable of simulating systems with finite band gaps of sizes that were previously impossible with this degree of accuracy. By avoiding global communications, we provide a practical computational scheme capable of extreme scalability. Accuracy is controlled by the mesh spacing of the finite difference discretization, the size of the localization regions in which the electronic wave functions are confined, and a cutoff beyond which the components of the overlap matrix can be omitted when computing selected elements of its inverse. We demonstrate the algorithm's excellent parallel scaling for up to 101 952 atoms on 23 328 processors, with a wall-clock time of the order of 1 min per molecular dynamics time step and numerical error on the forces of less than 7x10^{-4} Ha/Bohr.
Osei-Kuffuor, Daniel; Fattebert, Jean-Luc
2014-01-31
We present the first truly scalable first-principles molecular dynamics algorithm with O(N) complexity and controllable accuracy, capable of simulating systems with finite band gaps of sizes that were previously impossible with this degree of accuracy. By avoiding global communications, we provide a practical computational scheme capable of extreme scalability. Accuracy is controlled by the mesh spacing of the finite difference discretization, the size of the localization regions in which the electronic wave functions are confined, and a cutoff beyond which the components of the overlap matrix can be omitted when computing selected elements of its inverse. We demonstrate the algorithm's excellent parallel scaling for up to 101,952 atoms on 23,328 processors, with a wall-clock time of the order of 1 min per molecular dynamics time step and numerical error on the forces of less than 7×10(-4) Ha/Bohr.
无
2008-01-01
A recursive algorithm is adopted for the computation of dyadic Green's functions in three-dimensional stratified uniaxial anisotropic media with arbitrary number of layers. Three linear equation groups for computing the coefficients of the Sommerfeld integrals are obtained according to the continuity condition of electric and magnetic fields across the interface between different layers, which are in correspondence with the TM wave produced by a vertical unit electric dipole and the TE or TM wave produced by a horizontal unit electric dipole, respectively. All the linear equation groups can be solved via the recursive algorithm. The dyadic Green's functions with source point and field point being in any layer can be conveniently obtained by merely changing the position of the elements within the source term of the linear equation groups. The problem of singularities occurring in the Sommerfeld integrals is efficiently solved by deforming the integration path in the complex plane. The expression of the dyadic Green's functions provided by this paper is terse in form and is easy to be programmed, and it does not overflow. Theoretical analysis and numerical examples show the accuracy and effectivity of the algorithm.
Novel computational approaches characterizing knee physiotherapy
Wangdo Kim
2014-01-01
Full Text Available A knee joint’s longevity depends on the proper integration of structural components in an axial alignment. If just one of the components is abnormally off-axis, the biomechanical system fails, resulting in arthritis. The complexity of various failures in the knee joint has led orthopedic surgeons to select total knee replacement as a primary treatment. In many cases, this means sacrificing much of an otherwise normal joint. Here, we review novel computational approaches to describe knee physiotherapy by introducing a new dimension of foot loading to the knee axis alignment producing an improved functional status of the patient. New physiotherapeutic applications are then possible by aligning foot loading with the functional axis of the knee joint during the treatment of patients with osteoarthritis.
Music Genre Classification Systems - A Computational Approach
Ahrendt, Peter
2006-01-01
Automatic music genre classification is the classification of a piece of music into its corresponding genre (such as jazz or rock) by a computer. It is considered to be a cornerstone of the research area Music Information Retrieval (MIR) and closely linked to the other areas in MIR. It is thought...... that MIR will be a key element in the processing, searching and retrieval of digital music in the near future. This dissertation is concerned with music genre classification systems and in particular systems which use the raw audio signal as input to estimate the corresponding genre. This is in contrast...... to systems which use e.g. a symbolic representation or textual information about the music. The approach to music genre classification systems has here been system-oriented. In other words, all the different aspects of the systems have been considered and it is emphasized that the systems should...
A computational approach to negative priming
Schrobsdorff, H.; Ihrke, M.; Kabisch, B.; Behrendt, J.; Hasselhorn, M.; Herrmann, J. Michael
2007-09-01
Priming is characterized by a sensitivity of reaction times to the sequence of stimuli in psychophysical experiments. The reduction of the reaction time observed in positive priming is well-known and experimentally understood (Scarborough et al., J. Exp. Psycholol: Hum. Percept. Perform., 3, pp. 1-17, 1977). Negative priming—the opposite effect—is experimentally less tangible (Fox, Psychonom. Bull. Rev., 2, pp. 145-173, 1995). The dependence on subtle parameter changes (such as response-stimulus interval) usually varies. The sensitivity of the negative priming effect bears great potential for applications in research in fields such as memory, selective attention, and ageing effects. We develop and analyse a computational realization, CISAM, of a recent psychological model for action decision making, the ISAM (Kabisch, PhD thesis, Friedrich-Schiller-Universitat, 2003), which is sensitive to priming conditions. With the dynamical systems approach of the CISAM, we show that a single adaptive threshold mechanism is sufficient to explain both positive and negative priming effects. This is achieved by comparing results obtained by the computational modelling with experimental data from our laboratory. The implementation provides a rich base from which testable predictions can be derived, e.g. with respect to hitherto untested stimulus combinations (e.g. single-object trials).
Kemp, James Herbert (Inventor); Talukder, Ashit (Inventor); Lambert, James (Inventor); Lam, Raymond (Inventor)
2008-01-01
A computer-implemented system and method of intra-oral analysis for measuring plaque removal is disclosed. The system includes hardware for real-time image acquisition and software to store the acquired images on a patient-by-patient basis. The system implements algorithms to segment teeth of interest from surrounding gum, and uses a real-time image-based morphing procedure to automatically overlay a grid onto each segmented tooth. Pattern recognition methods are used to classify plaque from surrounding gum and enamel, while ignoring glare effects due to the reflection of camera light and ambient light from enamel regions. The system integrates these components into a single software suite with an easy-to-use graphical user interface (GUI) that allows users to do an end-to-end run of a patient record, including tooth segmentation of all teeth, grid morphing of each segmented tooth, and plaque classification of each tooth image.
A novel class of highly efficient and accurate time-integrators in nonlinear computational mechanics
Wang, Xuechuan; Atluri, Satya N.
2017-05-01
A new class of time-integrators is presented for strongly nonlinear dynamical systems. These algorithms are far superior to the currently common time integrators in computational efficiency and accuracy. These three algorithms are based on a local variational iteration method applied over a finite interval of time. By using Chebyshev polynomials as trial functions and Dirac-Delta functions as the test functions over the finite time interval, the three algorithms are developed into three different discrete time-integrators through the collocation method. These time integrators are labeled as Chebyshev local iterative collocation methods. Through examples of the forced Duffing oscillator, the Lorenz system, and the multiple coupled Duffing equations (which arise as semi-discrete equations for beams, plates and shells undergoing large deformations), it is shown that the new algorithms are far superior to the 4th order Runge-Kutta and ODE45 of MATLAB, in predicting the chaotic responses of strongly nonlinear dynamical systems.
submitter A model for the accurate computation of the lateral scattering of protons in water
Bellinzona, EV; Embriaco, A; Ferrari, A; Fontana, A; Mairani, A; Parodi, K; Rotondi, A; Sala, P; Tessonnier, T
2016-01-01
A pencil beam model for the calculation of the lateral scattering in water of protons for any therapeutic energy and depth is presented. It is based on the full Molière theory, taking into account the energy loss and the effects of mixtures and compounds. Concerning the electromagnetic part, the model has no free parameters and is in very good agreement with the FLUKA Monte Carlo (MC) code. The effects of the nuclear interactions are parametrized with a two-parameter tail function, adjusted on MC data calculated with FLUKA. The model, after the convolution with the beam and the detector response, is in agreement with recent proton data in water from HIT. The model gives results with the same accuracy of the MC codes based on Molière theory, with a much shorter computing time.
A novel class of highly efficient and accurate time-integrators in nonlinear computational mechanics
Wang, Xuechuan; Atluri, Satya N.
2017-01-01
A new class of time-integrators is presented for strongly nonlinear dynamical systems. These algorithms are far superior to the currently common time integrators in computational efficiency and accuracy. These three algorithms are based on a local variational iteration method applied over a finite interval of time. By using Chebyshev polynomials as trial functions and Dirac-Delta functions as the test functions over the finite time interval, the three algorithms are developed into three different discrete time-integrators through the collocation method. These time integrators are labeled as Chebyshev local iterative collocation methods. Through examples of the forced Duffing oscillator, the Lorenz system, and the multiple coupled Duffing equations (which arise as semi-discrete equations for beams, plates and shells undergoing large deformations), it is shown that the new algorithms are far superior to the 4th order Runge-Kutta and ODE45 of MATLAB, in predicting the chaotic responses of strongly nonlinear dynamical systems.
A fast and accurate method to compute the mass return from multiple stellar populations
Calura, F; Nipoti, C
2013-01-01
The mass returned to the ambient medium by aging stellar populations over cosmological times sums up to a significant fraction (20% - 30% or more) of their initial mass. This continuous mass injection plays a fundamental role in phenomena such as galaxy formation and evolution, fueling of supermassive black holes in galaxies and the consequent (negative and positive) feedback phenomena, and the origin of multiple stellar populations in globular clusters. In numerical simulations the calculation of the mass return can be time consuming, since it requires at each time step the evaluation of a convolution integral over the whole star formation history, so the computational time increases quadratically with the number of time-steps. The situation can be especially critical in hydrodynamical simulations, where different grid points are characterized by different star formation histories, and the gas cooling and heating times are shorter by orders of magnitude than the characteristic stellar lifetimes. In this pape...
Fast accurate computation of the fully nonlinear solitary surface gravity waves
Clamond, Didier
2013-01-01
In this short note, we present an easy to implement and fast algorithm for the computation of the steady solitary gravity wave solution of the free surface Euler equations in irrotational motion. First, the problem is reformulated in a fixed domain using the conformal mapping technique. Second, the problem is reduced to a single equation for the free surface. Third, this equation is solved using Petviashvili's iterations together with pseudo-spectral discretisation. This method has a super-linear complexity, since the most demanding operations can be performed using a FFT algorithm. Moreover, when this algorithm is combined with the multi-precision arithmetics, the results can be obtained to any arbitrary accuracy.
Quick, Accurate, Smart: 3D Computer Vision Technology Helps Assessing Confined Animals' Behaviour.
Shanis Barnard
Full Text Available Mankind directly controls the environment and lifestyles of several domestic species for purposes ranging from production and research to conservation and companionship. These environments and lifestyles may not offer these animals the best quality of life. Behaviour is a direct reflection of how the animal is coping with its environment. Behavioural indicators are thus among the preferred parameters to assess welfare. However, behavioural recording (usually from video can be very time consuming and the accuracy and reliability of the output rely on the experience and background of the observers. The outburst of new video technology and computer image processing gives the basis for promising solutions. In this pilot study, we present a new prototype software able to automatically infer the behaviour of dogs housed in kennels from 3D visual data and through structured machine learning frameworks. Depth information acquired through 3D features, body part detection and training are the key elements that allow the machine to recognise postures, trajectories inside the kennel and patterns of movement that can be later labelled at convenience. The main innovation of the software is its ability to automatically cluster frequently observed temporal patterns of movement without any pre-set ethogram. Conversely, when common patterns are defined through training, a deviation from normal behaviour in time or between individuals could be assessed. The software accuracy in correctly detecting the dogs' behaviour was checked through a validation process. An automatic behaviour recognition system, independent from human subjectivity, could add scientific knowledge on animals' quality of life in confinement as well as saving time and resources. This 3D framework was designed to be invariant to the dog's shape and size and could be extended to farm, laboratory and zoo quadrupeds in artificial housing. The computer vision technique applied to this software is
Quick, Accurate, Smart: 3D Computer Vision Technology Helps Assessing Confined Animals' Behaviour.
Barnard, Shanis; Calderara, Simone; Pistocchi, Simone; Cucchiara, Rita; Podaliri-Vulpiani, Michele; Messori, Stefano; Ferri, Nicola
2016-01-01
Mankind directly controls the environment and lifestyles of several domestic species for purposes ranging from production and research to conservation and companionship. These environments and lifestyles may not offer these animals the best quality of life. Behaviour is a direct reflection of how the animal is coping with its environment. Behavioural indicators are thus among the preferred parameters to assess welfare. However, behavioural recording (usually from video) can be very time consuming and the accuracy and reliability of the output rely on the experience and background of the observers. The outburst of new video technology and computer image processing gives the basis for promising solutions. In this pilot study, we present a new prototype software able to automatically infer the behaviour of dogs housed in kennels from 3D visual data and through structured machine learning frameworks. Depth information acquired through 3D features, body part detection and training are the key elements that allow the machine to recognise postures, trajectories inside the kennel and patterns of movement that can be later labelled at convenience. The main innovation of the software is its ability to automatically cluster frequently observed temporal patterns of movement without any pre-set ethogram. Conversely, when common patterns are defined through training, a deviation from normal behaviour in time or between individuals could be assessed. The software accuracy in correctly detecting the dogs' behaviour was checked through a validation process. An automatic behaviour recognition system, independent from human subjectivity, could add scientific knowledge on animals' quality of life in confinement as well as saving time and resources. This 3D framework was designed to be invariant to the dog's shape and size and could be extended to farm, laboratory and zoo quadrupeds in artificial housing. The computer vision technique applied to this software is innovative in non
Quick, Accurate, Smart: 3D Computer Vision Technology Helps Assessing Confined Animals’ Behaviour
Calderara, Simone; Pistocchi, Simone; Cucchiara, Rita; Podaliri-Vulpiani, Michele; Messori, Stefano; Ferri, Nicola
2016-01-01
Mankind directly controls the environment and lifestyles of several domestic species for purposes ranging from production and research to conservation and companionship. These environments and lifestyles may not offer these animals the best quality of life. Behaviour is a direct reflection of how the animal is coping with its environment. Behavioural indicators are thus among the preferred parameters to assess welfare. However, behavioural recording (usually from video) can be very time consuming and the accuracy and reliability of the output rely on the experience and background of the observers. The outburst of new video technology and computer image processing gives the basis for promising solutions. In this pilot study, we present a new prototype software able to automatically infer the behaviour of dogs housed in kennels from 3D visual data and through structured machine learning frameworks. Depth information acquired through 3D features, body part detection and training are the key elements that allow the machine to recognise postures, trajectories inside the kennel and patterns of movement that can be later labelled at convenience. The main innovation of the software is its ability to automatically cluster frequently observed temporal patterns of movement without any pre-set ethogram. Conversely, when common patterns are defined through training, a deviation from normal behaviour in time or between individuals could be assessed. The software accuracy in correctly detecting the dogs’ behaviour was checked through a validation process. An automatic behaviour recognition system, independent from human subjectivity, could add scientific knowledge on animals’ quality of life in confinement as well as saving time and resources. This 3D framework was designed to be invariant to the dog’s shape and size and could be extended to farm, laboratory and zoo quadrupeds in artificial housing. The computer vision technique applied to this software is innovative in non
Time-Accurate Computational Fluid Dynamics Simulation of a Pair of Moving Solid Rocket Boosters
Strutzenberg, Louise L.; Williams, Brandon R.
2011-01-01
Since the Columbia accident, the threat to the Shuttle launch vehicle from debris during the liftoff timeframe has been assessed by the Liftoff Debris Team at NASA/MSFC. In addition to engineering methods of analysis, CFD-generated flow fields during the liftoff timeframe have been used in conjunction with 3-DOF debris transport methods to predict the motion of liftoff debris. Early models made use of a quasi-steady flow field approximation with the vehicle positioned at a fixed location relative to the ground; however, a moving overset mesh capability has recently been developed for the Loci/CHEM CFD software which enables higher-fidelity simulation of the Shuttle transient plume startup and liftoff environment. The present work details the simulation of the launch pad and mobile launch platform (MLP) with truncated solid rocket boosters (SRBs) moving in a prescribed liftoff trajectory derived from Shuttle flight measurements. Using Loci/CHEM, time-accurate RANS and hybrid RANS/LES simulations were performed for the timeframe T0+0 to T0+3.5 seconds, which consists of SRB startup to a vehicle altitude of approximately 90 feet above the MLP. Analysis of the transient flowfield focuses on the evolution of the SRB plumes in the MLP plume holes and the flame trench, impingement on the flame deflector, and especially impingment on the MLP deck resulting in upward flow which is a transport mechanism for debris. The results show excellent qualitative agreement with the visual record from past Shuttle flights, and comparisons to pressure measurements in the flame trench and on the MLP provide confidence in these simulation capabilities.
Analysis of computational models for an accurate study of electronic excitations in GFP
Schwabe, Tobias; Beerepoot, Maarten; Olsen, Jógvan Magnus Haugaard
2015-01-01
Using the chromophore of the green fluorescent protein (GFP), the performance of a hybrid RI-CC2 / polarizable embedding (PE) model is tested against a quantum chemical cluster pproach. Moreover, the effect of the rest of the protein environment is studied by systematically increasing the size...... that the treatment of only a small region around the chromophore is only by coincidence a good approximation. Therefore, such cluster approaches should be used with care. Based on our results, we suggest that polarizable embedding models, including a large part of the environment to describe its effect...
Blueprinting Approach in Support of Cloud Computing
Willem-Jan van den Heuvel
2012-03-01
Full Text Available Current cloud service offerings, i.e., Software-as-a-service (SaaS, Platform-as-a-service (PaaS and Infrastructure-as-a-service (IaaS offerings are often provided as monolithic, one-size-fits-all solutions and give little or no room for customization. This limits the ability of Service-based Application (SBA developers to configure and syndicate offerings from multiple SaaS, PaaS, and IaaS providers to address their application requirements. Furthermore, combining different independent cloud services necessitates a uniform description format that facilitates the design, customization, and composition. Cloud Blueprinting is a novel approach that allows SBA developers to easily design, configure and deploy virtual SBA payloads on virtual machines and resource pools on the cloud. We propose the Blueprint concept as a uniform abstract description for cloud service offerings that may cross different cloud computing layers, i.e., SaaS, PaaS and IaaS. To support developers with the SBA design and development in the cloud, this paper introduces a formal Blueprint Template for unambiguously describing a blueprint, as well as a Blueprint Lifecycle that guides developers through the manipulation, composition and deployment of different blueprints for an SBA. Finally, the empirical evaluation of the blueprinting approach within an EC’s FP7 project is reported and an associated blueprint prototype implementation is presented.
Highly Accurate Frequency Calculations of Crab Cavities Using the VORPAL Computational Framework
Austin, T.M.; /Tech-X, Boulder; Cary, J.R.; /Tech-X, Boulder /Colorado U.; Bellantoni, L.; /Argonne
2009-05-01
We have applied the Werner-Cary method [J. Comp. Phys. 227, 5200-5214 (2008)] for extracting modes and mode frequencies from time-domain simulations of crab cavities, as are needed for the ILC and the beam delivery system of the LHC. This method for frequency extraction relies on a small number of simulations, and post-processing using the SVD algorithm with Tikhonov regularization. The time-domain simulations were carried out using the VORPAL computational framework, which is based on the eminently scalable finite-difference time-domain algorithm. A validation study was performed on an aluminum model of the 3.9 GHz RF separators built originally at Fermi National Accelerator Laboratory in the US. Comparisons with measurements of the A15 cavity show that this method can provide accuracy to within 0.01% of experimental results after accounting for manufacturing imperfections. To capture the near degeneracies two simulations, requiring in total a few hours on 600 processors were employed. This method has applications across many areas including obtaining MHD spectra from time-domain simulations.
Yuqing He
2014-01-01
Full Text Available Autonomous maneuvering flight control of rotor-flying robots (RFR is a challenging problem due to the highly complicated structure of its model and significant uncertainties regarding many aspects of the field. As a consequence, it is difficult in many cases to decide whether or not a flight maneuver trajectory is feasible. It is necessary to conduct an analysis of the flight maneuvering ability of an RFR prior to test flight. Our aim in this paper is to use a numerical method called algorithm differentiation (AD to solve this problem. The basic idea is to compute the internal state (i.e., attitude angles and angular rates and input profiles based on predetermined maneuvering trajectory information denoted by the outputs (i.e., positions and yaw angle and their higher-order derivatives. For this purpose, we first present a model of the RFR system and show that it is flat. We then cast the procedure for obtaining the required state/input based on the desired outputs as a static optimization problem, which is solved using AD and a derivative based optimization algorithm. Finally, we test our proposed method using a flight maneuver trajectory to verify its performance.
Bangga, Galih; Weihing, Pascal; Lutz, Thorsten; Krämer, Ewald [University of Stuttgart, Stuttgart (Germany)
2017-05-15
The present study focuses on the impact of grid for accurate prediction of the MEXICO rotor under stalled conditions. Two different blade mesh topologies, O and C-H meshes, and two different grid resolutions are tested for several time step sizes. The simulations are carried out using Delayed detached-eddy simulation (DDES) with two eddy viscosity RANS turbulence models, namely Spalart- Allmaras (SA) and Menter Shear stress transport (SST) k-ω. A high order spatial discretization, WENO (Weighted essentially non- oscillatory) scheme, is used in these computations. The results are validated against measurement data with regards to the sectional loads and the chordwise pressure distributions. The C-H mesh topology is observed to give the best results employing the SST k-ω turbulence model, but the computational cost is more expensive as the grid contains a wake block that increases the number of cells.
Efficient and accurate computation of electric field dyadic Green's function in layered media
Cho, Min Hyung
2016-01-01
Concise and explicit formulas for dyadic Green's functions, representing the electric and magnetic fields due to a dipole source placed in layered media, are derived in this paper. First, the electric and magnetic fields in the spectral domain for the half space are expressed using Fresnel reflection and transmission coefficients. Each component of electric field in the spectral domain constitutes the spectral Green's function in layered media. The Green's function in the spatial domain is then recovered involving Sommerfeld integrals for each component in the spectral domain. By using Bessel identities, the number of Sommerfeld integrals are reduced, resulting in much simpler and more efficient formulas for numerical implementation compared with previous results. This approach is extended to the three-layer Green's function. In addition, the singular part of the Green's function is naturally separated out so that integral equation methods developed for free space Green's functions can be used with minimal mo...
Li, Xin; Han, Xingpeng; Sun, Wei; Wang, Meng; Jing, Guohui
2016-01-01
Background To evaluate the role of computed tomography (CT) in preoperative diagnosis of intrathymic cyst and small thymoma, and determine the best CT threshold for distinguish intrathymic cyst from small thymoma. Methods We retrospectively reviewed the medical records of 30 patients (17 intrathymic cyst and 13 small thymoma) who had undergone mediastinal masses resection (with diameter less than 3 cm) under thoracoscope between January 2014 and July 2015 at our hospital. Clinical and CT features were compared and receiver-operating characteristics curve (ROC) analysis was performed. Results The CT value of small thymoma [39.5 HU (IQR, 33.7–42.2 HU)] was significantly higher than intrathymic cyst [25.8 HU (IQR, 22.3–29.3 HU), P=0.004]. When CT value was 31.2 HU, it could act as a threshold for identification of small thymoma and intrathymic cyst (the sensitivity and specificity was 92.3% and 82.4%, respectively). The ΔCT value of enhanced CT value with the non-enhanced CT value was significantly different between small thymoma [18.7 HU (IQR, 10.9–19.0 HU)] and intrathymic cyst [4.3 HU (IQR, 3.0–11.7 HU), P=0.04]. The density was more homogenous in intrathymic cyst than small thymoma, and the contour of the intrathymic cyst was more smoothly than small thymoma. Conclusions Preoperative CT scans could help clinicians to identify intrathymic cyst and small thymoma, and we recommend 31.2 HU as the best thresholds. Contrast-enhanced CT scans is useful for further identification of the two diseases. PMID:27621863
Hrubý Jan
2012-04-01
Full Text Available Mathematical modeling of the non-equilibrium condensing transonic steam flow in the complex 3D geometry of a steam turbine is a demanding problem both concerning the physical concepts and the required computational power. Available accurate formulations of steam properties IAPWS-95 and IAPWS-IF97 require much computation time. For this reason, the modelers often accept the unrealistic ideal-gas behavior. Here we present a computation scheme based on a piecewise, thermodynamically consistent representation of the IAPWS-95 formulation. Density and internal energy are chosen as independent variables to avoid variable transformations and iterations. On the contrary to the previous Tabular Taylor Series Expansion Method, the pressure and temperature are continuous functions of the independent variables, which is a desirable property for the solution of the differential equations of the mass, energy, and momentum conservation for both phases.
Yi, Sha-Sha; Pan, Cong; Hu, Zhong-Han
2015-12-01
Modern computer simulations of biological systems often involve an explicit treatment of the complex interactions among a large number of molecules. While it is straightforward to compute the short-ranged Van der Waals interaction in classical molecular dynamics simulations, it has been a long-lasting issue to develop accurate methods for the longranged Coulomb interaction. In this short review, we discuss three types of methodologies for the accurate treatment of electrostatics in simulations of explicit molecules: truncation-type methods, Ewald-type methods, and mean-field-type methods. Throughout the discussion, we brief the formulations and developments of these methods, emphasize the intrinsic connections among the three types of methods, and focus on the existing problems which are often associated with the boundary conditions of electrostatics. This brief survey is summarized with a short perspective on future trends along the method developments and applications in the field of biological simulations. Project supported by the National Natural Science Foundation of China (Grant Nos. 91127015 and 21522304) and the Open Project from the State Key Laboratory of Theoretical Physics, and the Innovation Project from the State Key Laboratory of Supramolecular Structure and Materials.
Chavanon, O; Barbe, C; Troccaz, J; Carrat, L; Ribuot, C; Noirclerc, M; Maitrasse, B; Blin, D
1999-06-01
In the field of percutaneous access to soft tissues, our project was to improve classical pericardiocentesis by performing accurate guidance to a selected target, according to a model of the pericardial effusion acquired through three-dimensional (3D) data recording. Required hardware is an echocardiographic device and a needle, both linked to a 3D localizer, and a computer. After acquiring echographic data, a modeling procedure allows definition of the optimal puncture strategy, taking into consideration the mobility of the heart, by determining a stable region, whatever the period of the cardiac cycle. A passive guidance system is then used to reach the planned target accurately, generally a site in the middle of the stable region. After validation on a dynamic phantom and a feasibility study in dogs, an accuracy and reliability analysis protocol was realized on pigs with experimental pericardial effusion. Ten consecutive successful punctures using various trajectories were performed on eight pigs. Nonbloody liquid was collected from pericardial effusions in the stable region (5 to 9 mm wide) within 10 to 15 minutes from echographic acquisition to drainage. Accuracy of at least 2.5 mm was demonstrated. This study demonstrates the feasibility of computer-assisted pericardiocentesis. Beyond the simple improvement of the current technique, this method could be a new way to reach the heart or a new tool for percutaneous access and image-guided puncture of soft tissues. Further investigation will be necessary before routine human application.
Manz, Thomas A; Sholl, David S
2011-12-13
The partitioning of electron spin density among atoms in a material gives atomic spin moments (ASMs), which are important for understanding magnetic properties. We compare ASMs computed using different population analysis methods and introduce a method for computing density derived electrostatic and chemical (DDEC) ASMs. Bader and DDEC ASMs can be computed for periodic and nonperiodic materials with either collinear or noncollinear magnetism, while natural population analysis (NPA) ASMs can be computed for nonperiodic materials with collinear magnetism. Our results show Bader, DDEC, and (where applicable) NPA methods give similar ASMs, but different net atomic charges. Because they are optimized to reproduce both the magnetic field and the chemical states of atoms in a material, DDEC ASMs are especially suitable for constructing interaction potentials for atomistic simulations. We describe the computation of accurate ASMs for (a) a variety of systems using collinear and noncollinear spin DFT, (b) highly correlated materials (e.g., magnetite) using DFT+U, and (c) various spin states of ozone using coupled cluster expansions. The computed ASMs are in good agreement with available experimental results for a variety of periodic and nonperiodic materials. Examples considered include the antiferromagnetic metal organic framework Cu3(BTC)2, several ozone spin states, mono- and binuclear transition metal complexes, ferri- and ferro-magnetic solids (e.g., Fe3O4, Fe3Si), and simple molecular systems. We briefly discuss the theory of exchange-correlation functionals for studying noncollinear magnetism. A method for finding the ground state of systems with highly noncollinear magnetism is introduced. We use these methods to study the spin-orbit coupling potential energy surface of the single molecule magnet Fe4C40H52N4O12, which has highly noncollinear magnetism, and find that it contains unusual features that give a new interpretation to experimental data.
Noyes, Ben F.; Mokaberi, Babak; Mandoy, Ram; Pate, Alex; Huijgen, Ralph; McBurney, Mike; Chen, Owen
2017-03-01
Reducing overlay error via an accurate APC feedback system is one of the main challenges in high volume production of the current and future nodes in the semiconductor industry. The overlay feedback system directly affects the number of dies meeting overlay specification and the number of layers requiring dedicated exposure tools through the fabrication flow. Increasing the former number and reducing the latter number is beneficial for the overall efficiency and yield of the fabrication process. An overlay feedback system requires accurate determination of the overlay error, or fingerprint, on exposed wafers in order to determine corrections to be automatically and dynamically applied to the exposure of future wafers. Since current and future nodes require correction per exposure (CPE), the resolution of the overlay fingerprint must be high enough to accommodate CPE in the overlay feedback system, or overlay control module (OCM). Determining a high resolution fingerprint from measured data requires extremely dense overlay sampling that takes a significant amount of measurement time. For static corrections this is acceptable, but in an automated dynamic correction system this method creates extreme bottlenecks for the throughput of said system as new lots have to wait until the previous lot is measured. One solution is using a less dense overlay sampling scheme and employing computationally up-sampled data to a dense fingerprint. That method uses a global fingerprint model over the entire wafer; measured localized overlay errors are therefore not always represented in its up-sampled output. This paper will discuss a hybrid system shown in Fig. 1 that combines a computationally up-sampled fingerprint with the measured data to more accurately capture the actual fingerprint, including local overlay errors. Such a hybrid system is shown to result in reduced modelled residuals while determining the fingerprint, and better on-product overlay performance.
Kory, Carol L.
1999-01-01
The phenomenal growth of commercial communications has created a great demand for traveling-wave tube (TWT) amplifiers. Although the helix slow-wave circuit remains the mainstay of the TWT industry because of its exceptionally wide bandwidth, until recently it has been impossible to accurately analyze a helical TWT using its exact dimensions because of the complexity of its geometrical structure. For the first time, an accurate three-dimensional helical model was developed that allows accurate prediction of TWT cold-test characteristics including operating frequency, interaction impedance, and attenuation. This computational model, which was developed at the NASA Lewis Research Center, allows TWT designers to obtain a more accurate value of interaction impedance than is possible using experimental methods. Obtaining helical slow-wave circuit interaction impedance is an important part of the design process for a TWT because it is related to the gain and efficiency of the tube. This impedance cannot be measured directly; thus, conventional methods involve perturbing a helical circuit with a cylindrical dielectric rod placed on the central axis of the circuit and obtaining the difference in resonant frequency between the perturbed and unperturbed circuits. A mathematical relationship has been derived between this frequency difference and the interaction impedance (ref. 1). However, because of the complex configuration of the helical circuit, deriving this relationship involves several approximations. In addition, this experimental procedure is time-consuming and expensive, but until recently it was widely accepted as the most accurate means of determining interaction impedance. The advent of an accurate three-dimensional helical circuit model (ref. 2) made it possible for Lewis researchers to fully investigate standard approximations made in deriving the relationship between measured perturbation data and interaction impedance. The most prominent approximations made
Yokogawa, Daisuke; Ono, Kohei; Sato, Hirofumi; Sakaki, Shigeyoshi
2011-11-14
The ligand exchange process of cis-platin in aqueous solution was studied using RISM-SCF-SEDD (reference interaction site model-self-consistent field with spatial electron density distribution) method, a hybrid approach of quantum chemistry and statistical mechanics. The analytical nature of RISM theory enables us to compute accurate reaction free energy in aqueous solution based on CCSD(T), together with the microscopic solvation structure around the complex. We found that the solvation effect is indispensable to promote the dissociation of the chloride anion from the complex.
A semantic-web approach for modeling computing infrastructures
M. Ghijsen; J. van der Ham; P. Grosso; C. Dumitru; H. Zhu; Z. Zhao; C. de Laat
2013-01-01
This paper describes our approach to modeling computing infrastructures. Our main contribution is the Infrastructure and Network Description Language (INDL) ontology. The aim of INDL is to provide technology independent descriptions of computing infrastructures, including the physical resources as w
Accurate Time-Dependent Traveling-Wave Tube Model Developed for Computational Bit-Error-Rate Testing
Kory, Carol L.
2001-01-01
The phenomenal growth of the satellite communications industry has created a large demand for traveling-wave tubes (TWT's) operating with unprecedented specifications requiring the design and production of many novel devices in record time. To achieve this, the TWT industry heavily relies on computational modeling. However, the TWT industry's computational modeling capabilities need to be improved because there are often discrepancies between measured TWT data and that predicted by conventional two-dimensional helical TWT interaction codes. This limits the analysis and design of novel devices or TWT's with parameters differing from what is conventionally manufactured. In addition, the inaccuracy of current computational tools limits achievable TWT performance because optimized designs require highly accurate models. To address these concerns, a fully three-dimensional, time-dependent, helical TWT interaction model was developed using the electromagnetic particle-in-cell code MAFIA (Solution of MAxwell's equations by the Finite-Integration-Algorithm). The model includes a short section of helical slow-wave circuit with excitation fed by radiofrequency input/output couplers, and an electron beam contained by periodic permanent magnet focusing. A cutaway view of several turns of the three-dimensional helical slow-wave circuit with input/output couplers is shown. This has been shown to be more accurate than conventionally used two-dimensional models. The growth of the communications industry has also imposed a demand for increased data rates for the transmission of large volumes of data. To achieve increased data rates, complex modulation and multiple access techniques are employed requiring minimum distortion of the signal as it is passed through the TWT. Thus, intersymbol interference (ISI) becomes a major consideration, as well as suspected causes such as reflections within the TWT. To experimentally investigate effects of the physical TWT on ISI would be
Gray, Alan [The University of Edinburgh, Edinburgh EH9 3JZ, Scotland (United Kingdom); Harlen, Oliver G. [University of Leeds, Leeds LS2 9JT (United Kingdom); Harris, Sarah A., E-mail: s.a.harris@leeds.ac.uk [University of Leeds, Leeds LS2 9JT (United Kingdom); University of Leeds, Leeds LS2 9JT (United Kingdom); Khalid, Syma; Leung, Yuk Ming [University of Southampton, Southampton SO17 1BJ (United Kingdom); Lonsdale, Richard [Max-Planck-Institut für Kohlenforschung, Kaiser-Wilhelm-Platz 1, 45470 Mülheim an der Ruhr (Germany); Philipps-Universität Marburg, Hans-Meerwein Strasse, 35032 Marburg (Germany); Mulholland, Adrian J. [University of Bristol, Bristol BS8 1TS (United Kingdom); Pearson, Arwen R. [University of Leeds, Leeds LS2 9JT (United Kingdom); University of Hamburg, Hamburg (Germany); Read, Daniel J.; Richardson, Robin A. [University of Leeds, Leeds LS2 9JT (United Kingdom); The University of Edinburgh, Edinburgh EH9 3JZ, Scotland (United Kingdom)
2015-01-01
The current computational techniques available for biomolecular simulation are described, and the successes and limitations of each with reference to the experimental biophysical methods that they complement are presented. Despite huge advances in the computational techniques available for simulating biomolecules at the quantum-mechanical, atomistic and coarse-grained levels, there is still a widespread perception amongst the experimental community that these calculations are highly specialist and are not generally applicable by researchers outside the theoretical community. In this article, the successes and limitations of biomolecular simulation and the further developments that are likely in the near future are discussed. A brief overview is also provided of the experimental biophysical methods that are commonly used to probe biomolecular structure and dynamics, and the accuracy of the information that can be obtained from each is compared with that from modelling. It is concluded that progress towards an accurate spatial and temporal model of biomacromolecules requires a combination of all of these biophysical techniques, both experimental and computational.
Thornburg, Jonathan
2010-01-01
If a small "particle" of mass $\\mu M$ (with $\\mu \\ll 1$) orbits a Schwarzschild or Kerr black hole of mass $M$, the particle is subject to an $\\O(\\mu)$ radiation-reaction "self-force". Here I argue that it's valuable to compute this self-force highly accurately (relative error of $\\ltsim 10^{-6}$) and efficiently, and I describe techniques for doing this and for obtaining and validating error estimates for the computation. I use an adaptive-mesh-refinement (AMR) time-domain numerical integration of the perturbation equations in the Barack-Ori mode-sum regularization formalism; this is efficient, yet allows easy generalization to arbitrary particle orbits. I focus on the model problem of a scalar particle in a circular geodesic orbit in Schwarzschild spacetime. The mode-sum formalism gives the self-force as an infinite sum of regularized spherical-harmonic modes $\\sum_{\\ell=0}^\\infty F_{\\ell,\\reg}$, with $F_{\\ell,\\reg}$ (and an "internal" error estimate) computed numerically for $\\ell \\ltsim 30$ and estimated ...
Ettore Taverna; Henri Ufenast; Laura Broffoni; Guido Garavaglia
2013-01-01
The Latarjet procedure is a confirmed method for the treatment of shoulder instability in the presence of bone loss. It is a challenging procedure for which a key point is the correct placement of the coracoid graft onto the glenoid neck. We here present our technique for an athroscopically assisted Latarjet procedure with a new drill guide, permitting an accurate and reproducible positioning of the coracoid graft, with optimal compression of the graft onto the glenoid neck due to the perfect...
Ettore Taverna; Henri Ufenast; Laura Broffoni; Guido Garavaglia
2013-01-01
The Latarjet procedure is a confirmed method for the treatment of shoulder instability in the presence of bone loss. It is a challenging procedure for which a key point is the correct placement of the coracoid graft onto the glenoid neck. We here present our technique for an athroscopically assisted Latarjet procedure with a new drill guide, permitting an accurate and reproducible positioning of the coracoid graft, with optimal compression of the graft onto the glenoid neck due to the perfect...
Theodore D. Katsilieris
2017-03-01
Full Text Available The terrestrial optical wireless communication links have attracted significant research and commercial worldwide interest over the last few years due to the fact that they offer very high and secure data rate transmission with relatively low installation and operational costs, and without need of licensing. However, since the propagation path of the information signal, i.e., the laser beam, is the atmosphere, their effectivity affects the atmospheric conditions strongly in the specific area. Thus, system performance depends significantly on the rain, the fog, the hail, the atmospheric turbulence, etc. Due to the influence of these effects, it is necessary to study, theoretically and numerically, very carefully before the installation of such a communication system. In this work, we present exactly and accurately approximate mathematical expressions for the estimation of the average capacity and the outage probability performance metrics, as functions of the link’s parameters, the transmitted power, the attenuation due to the fog, the ambient noise and the atmospheric turbulence phenomenon. The latter causes the scintillation effect, which results in random and fast fluctuations of the irradiance at the receiver’s end. These fluctuations can be studied accurately with statistical methods. Thus, in this work, we use either the lognormal or the gamma–gamma distribution for weak or moderate to strong turbulence conditions, respectively. Moreover, using the derived mathematical expressions, we design, accomplish and present a computational tool for the estimation of these systems’ performances, while also taking into account the parameter of the link and the atmospheric conditions. Furthermore, in order to increase the accuracy of the presented tool, for the cases where the obtained analytical mathematical expressions are complex, the performance results are verified with the numerical estimation of the appropriate integrals. Finally, using
Iwai, Toshinori; Omura, Susumu; Honda, Koji; Yamashita, Yosuke; Shibutani, Naoki; Fujita, Koichi; Takasu, Hikaru; Murata, Shogo; Tohnai, Iwai
2017-01-01
Bimaxillary orthognathic surgery has been widely performed to achieve optimal functional and esthetic outcomes in patients with dentofacial deformity. Although Le Fort I osteotomy is generally performed before bilateral sagittal split osteotomy (BSSO) in the surgery, in several situations BSSO should be performed first. However, it is very difficult during bimaxillary orthognathic surgery to maintain an accurate centric relation of the condyle and decide the ideal vertical dimension from the skull base to the mandible. We have previously applied a straight locking miniplate (SLM) technique that permits accurate superior maxillary repositioning without the need for intraoperative measurements in bimaxillary orthognathic surgery. Here we describe the application of this technique for accurate bimaxillary repositioning in a mandible-first approach where the SLMs also serve as a condylar positioning device in bimaxillary orthognathic surgery.
Ettore Taverna
2013-01-01
Full Text Available The Latarjet procedure is a confirmed method for the treatment of shoulder instability in the presence of bone loss. It is a challenging procedure for which a key point is the correct placement of the coracoid graft onto the glenoid neck. We here present our technique for an athroscopically assisted Latarjet procedure with a new drill guide, permitting an accurate and reproducible positioning of the coracoid graft, with optimal compression of the graft onto the glenoid neck due to the perfect position of the screws: perpendicular to the graft and the glenoid neck and parallel between them.
Taverna, Ettore; Ufenast, Henri; Broffoni, Laura; Garavaglia, Guido
2013-07-01
The Latarjet procedure is a confirmed method for the treatment of shoulder instability in the presence of bone loss. It is a challenging procedure for which a key point is the correct placement of the coracoid graft onto the glenoid neck. We here present our technique for an athroscopically assisted Latarjet procedure with a new drill guide, permitting an accurate and reproducible positioning of the coracoid graft, with optimal compression of the graft onto the glenoid neck due to the perfect position of the screws: perpendicular to the graft and the glenoid neck and parallel between them.
COMPUTER APPROACHES TO WHEAT HIGH-THROUGHPUT PHENOTYPING
Afonnikov D.
2012-08-01
Full Text Available The growing need for rapid and accurate approaches for large-scale assessment of phenotypic characters in plants becomes more and more obvious in the studies looking into relationships between genotype and phenotype. This need is due to the advent of high throughput methods for analysis of genomes. Nowadays, any genetic experiment involves data on thousands and dozens of thousands of plants. Traditional ways of assessing most phenotypic characteristics (those with reliance on the eye, the touch, the ruler are little effective on samples of such sizes. Modern approaches seek to take advantage of automated phenotyping, which warrants a much more rapid data acquisition, higher accuracy of the assessment of phenotypic features, measurement of new parameters of these features and exclusion of human subjectivity from the process. Additionally, automation allows measurement data to be rapidly loaded into computer databases, which reduces data processing time.In this work, we present the WheatPGE information system designed to solve the problem of integration of genotypic and phenotypic data and parameters of the environment, as well as to analyze the relationships between the genotype and phenotype in wheat. The system is used to consolidate miscellaneous data on a plant for storing and processing various morphological traits and genotypes of wheat plants as well as data on various environmental factors. The system is available at www.wheatdb.org. Its potential in genetic experiments has been demonstrated in high-throughput phenotyping of wheat leaf pubescence.
Accurate Vehicle Location System Using RFID, an Internet of Things Approach.
Prinsloo, Jaco; Malekian, Reza
2016-06-04
Modern infrastructure, such as dense urban areas and underground tunnels, can effectively block all GPS signals, which implies that effective position triangulation will not be achieved. The main problem that is addressed in this project is the design and implementation of an accurate vehicle location system using radio-frequency identification (RFID) technology in combination with GPS and the Global system for Mobile communication (GSM) technology, in order to provide a solution to the limitation discussed above. In essence, autonomous vehicle tracking will be facilitated with the use of RFID technology where GPS signals are non-existent. The design of the system and the results are reflected in this paper. An extensive literature study was done on the field known as the Internet of Things, as well as various topics that covered the integration of independent technology in order to address a specific challenge. The proposed system is then designed and implemented. An RFID transponder was successfully designed and a read range of approximately 31 cm was obtained in the low frequency communication range (125 kHz to 134 kHz). The proposed system was designed, implemented, and field tested and it was found that a vehicle could be accurately located and tracked. It is also found that the antenna size of both the RFID reader unit and RFID transponder plays a critical role in the maximum communication range that can be achieved.
Accurate Vehicle Location System Using RFID, an Internet of Things Approach
Jaco Prinsloo
2016-06-01
Full Text Available Modern infrastructure, such as dense urban areas and underground tunnels, can effectively block all GPS signals, which implies that effective position triangulation will not be achieved. The main problem that is addressed in this project is the design and implementation of an accurate vehicle location system using radio-frequency identification (RFID technology in combination with GPS and the Global system for Mobile communication (GSM technology, in order to provide a solution to the limitation discussed above. In essence, autonomous vehicle tracking will be facilitated with the use of RFID technology where GPS signals are non-existent. The design of the system and the results are reflected in this paper. An extensive literature study was done on the field known as the Internet of Things, as well as various topics that covered the integration of independent technology in order to address a specific challenge. The proposed system is then designed and implemented. An RFID transponder was successfully designed and a read range of approximately 31 cm was obtained in the low frequency communication range (125 kHz to 134 kHz. The proposed system was designed, implemented, and field tested and it was found that a vehicle could be accurately located and tracked. It is also found that the antenna size of both the RFID reader unit and RFID transponder plays a critical role in the maximum communication range that can be achieved.
Fast and Accurate Electronic Excitations in Cyanines with the Many-Body Bethe-Salpeter Approach.
Boulanger, Paul; Jacquemin, Denis; Duchemin, Ivan; Blase, Xavier
2014-03-11
The accurate prediction of the optical signatures of cyanine derivatives remains an important challenge in theoretical chemistry. Indeed, up to now, only the most expensive quantum chemical methods (CAS-PT2, CC, DMC, etc.) yield consistent and accurate data, impeding the applications on real-life molecules. Here, we investigate the lowest lying singlet excitation energies of increasingly long cyanine dyes within the GW and Bethe-Salpeter Green's function many-body perturbation theory. Our results are in remarkable agreement with available coupled-cluster (exCC3) data, bringing these two single-reference perturbation techniques within a 0.05 eV maximum discrepancy. By comparison, available TD-DFT calculations with various semilocal, global, or range-separated hybrid functionals, overshoot the transition energies by a typical error of 0.3-0.6 eV. The obtained accuracy is achieved with a parameter-free formalism that offers similar accuracy for metallic or insulating, finite size or extended systems.
Computer networks ISE a systems approach
Peterson, Larry L
2007-01-01
Computer Networks, 4E is the only introductory computer networking book written by authors who have had first-hand experience with many of the protocols discussed in the book, who have actually designed some of them as well, and who are still actively designing the computer networks today. This newly revised edition continues to provide an enduring, practical understanding of networks and their building blocks through rich, example-based instruction. The authors' focus is on the why of network design, not just the specifications comprising today's systems but how key technologies and p
London, Nir; Ambroggio, Xavier
2014-02-01
Computational protein design efforts aim to create novel proteins and functions in an automated manner and, in the process, these efforts shed light on the factors shaping natural proteins. The focus of these efforts has progressed from the interior of proteins to their surface and the design of functions, such as binding or catalysis. Here we examine progress in the development of robust methods for the computational design of non-natural interactions between proteins and molecular targets such as other proteins or small molecules. This problem is referred to as the de novo computational design of interactions. Recent successful efforts in de novo enzyme design and the de novo design of protein-protein interactions open a path towards solving this problem. We examine the common themes in these efforts, and review recent studies aimed at understanding the nature of successes and failures in the de novo computational design of interactions. While several approaches culminated in success, the use of a well-defined structural model for a specific binding interaction in particular has emerged as a key strategy for a successful design, and is therefore reviewed with special consideration. Copyright © 2013 Elsevier Inc. All rights reserved.
Human Computer Interaction: An intellectual approach
Kuntal Saroha
2011-08-01
Full Text Available This paper discusses the research that has been done in thefield of Human Computer Interaction (HCI relating tohuman psychology. Human-computer interaction (HCI isthe study of how people design, implement, and useinteractive computer systems and how computers affectindividuals, organizations, and society. This encompassesnot only ease of use but also new interaction techniques forsupporting user tasks, providing better access toinformation, and creating more powerful forms ofcommunication. It involves input and output devices andthe interaction techniques that use them; how information ispresented and requested; how the computer’s actions arecontrolled and monitored; all forms of help, documentation,and training; the tools used to design, build, test, andevaluate user interfaces; and the processes that developersfollow when creating Interfaces.
Computer science approach to quantum control
Janzing, D.
2006-07-01
Whereas it is obvious that every computation process is a physical process it has hardly been recognized that many complex physical processes bear similarities to computation processes. This is in particular true for the control of physical systems on the nanoscopic level: usually the system can only be accessed via a rather limited set of elementary control operations and for many purposes only a concatenation of a large number of these basic operations will implement the desired process. This concatenation is in many cases quite similar to building complex programs from elementary steps and principles for designing algorithm may thus be a paradigm for designing control processes. For instance, one can decrease the temperature of one part of a molecule by transferring its heat to the remaining part where it is then dissipated to the environment. But the implementation of such a process involves a complex sequence of electromagnetic pulses. This work considers several hypothetical control processes on the nanoscopic level and show their analogy to computation processes. We show that measuring certain types of quantum observables is such a complex task that every instrument that is able to perform it would necessarily be an extremely powerful computer. Likewise, the implementation of a heat engine on the nanoscale requires to process the heat in a way that is similar to information processing and it can be shown that heat engines with maximal efficiency would be powerful computers, too. In the same way as problems in computer science can be classified by complexity classes we can also classify control problems according to their complexity. Moreover, we directly relate these complexity classes for control problems to the classes in computer science. Unifying notions of complexity in computer science and physics has therefore two aspects: on the one hand, computer science methods help to analyze the complexity of physical processes. On the other hand, reasonable
Computational dynamics for robotics systems using a non-strict computational approach
Orin, David E.; Wong, Ho-Cheung; Sadayappan, P.
1989-01-01
A Non-Strict computational approach for real-time robotics control computations is proposed. In contrast to the traditional approach to scheduling such computations, based strictly on task dependence relations, the proposed approach relaxes precedence constraints and scheduling is guided instead by the relative sensitivity of the outputs with respect to the various paths in the task graph. An example of the computation of the Inverse Dynamics of a simple inverted pendulum is used to demonstrate the reduction in effective computational latency through use of the Non-Strict approach. A speedup of 5 has been obtained when the processes of the task graph are scheduled to reduce the latency along the crucial path of the computation. While error is introduced by the relaxation of precedence constraints, the Non-Strict approach has a smaller error than the conventional Strict approach for a wide range of input conditions.
An Accurate and Generic Testing Approach to Vehicle Stability Parameters Based on GPS and INS
Zhibin Miao
2015-12-01
Full Text Available With the development of the vehicle industry, controlling stability has become more and more important. Techniques of evaluating vehicle stability are in high demand. As a common method, usually GPS sensors and INS sensors are applied to measure vehicle stability parameters by fusing data from the two system sensors. Although prior model parameters should be recognized in a Kalman filter, it is usually used to fuse data from multi-sensors. In this paper, a robust, intelligent and precise method to the measurement of vehicle stability is proposed. First, a fuzzy interpolation method is proposed, along with a four-wheel vehicle dynamic model. Second, a two-stage Kalman filter, which fuses the data from GPS and INS, is established. Next, this approach is applied to a case study vehicle to measure yaw rate and sideslip angle. The results show the advantages of the approach. Finally, a simulation and real experiment is made to verify the advantages of this approach. The experimental results showed the merits of this method for measuring vehicle stability, and the approach can meet the design requirements of a vehicle stability controller.
Baiardi, Alberto; Bloino, Julien; Barone, Vincenzo
2015-07-14
The interpretation and analysis of experimental resonance-Raman (RR) spectra can be significantly facilitated by vibronic computations based on reliable quantum-mechanical (QM) methods. With the aim of improving the description of large and flexible molecules, our recent time-dependent formulation to compute vibrationally resolved electronic spectra, based on Cartesian coordinates, has been extended to support internal coordinates. A set of nonredundant delocalized coordinates is automatically generated from the molecular connectivity thanks to a new general and robust procedure. In order to validate our implementation, a series of molecules has been used as test cases. Among them, rigid systems show that normal modes based on Cartesian and delocalized internal coordinates provide equivalent results, but the latter set is much more convenient and reliable for systems characterized by strong geometric deformations associated with the electronic transition. The so-called Z-matrix internal coordinates, which perform well for chain molecules, are also shown to be poorly suited in the presence of cycles or nonstandard structures.
A. D. Zarrabi
2010-12-01
Full Text Available PURPOSE: To design a simple, cost-effective system for gaining rapid and accurate calyceal access during percutaneous nephrolithotomy (PCNL. MATERIALS AND METHODS: The design consists of a low-cost, light-weight, portable mechanical gantry with a needle guiding device. Using C-arm fluoroscopy, two images of the contrast-filled renal collecting system are obtained: at 0-degrees (perpendicular to the kidney and 20-degrees. These images are relayed to a laptop computer containing the software and graphic user interface for selecting the targeted calyx. The software provides numerical settings for the 3 axes of the gantry, which are used to position the needle guiding device. The needle is advanced through the guide to the depth calculated by the software, thus puncturing the targeted calyx. Testing of the system was performed on 2 target types: 1 radiolucent plastic tubes the approximate size of a renal calyx (5 or 10 mm in diameter, 30 mm in length; and 2 foam-occluded, contrast-filled porcine kidneys. RESULTS: Tests using target type 1 with 10 mm diameter (n = 14 and 5 mm diameter (n = 7 tubes resulted in a 100% targeting success rate, with a mean procedure duration of 10 minutes. Tests using target type 2 (n = 2 were both successful, with accurate puncturing of the selected renal calyx, and a mean procedure duration of 15 minutes. CONCLUSIONS: The mechanical gantry system described in this paper is low-cost, portable, light-weight, and simple to set up and operate. C-arm fluoroscopy is limited to two images, thus reducing radiation exposure significantly. Testing of the system showed an extremely high degree of accuracy in gaining precise access to a targeted renal calyx.
Uncertainty in biology a computational modeling approach
Gomez-Cabrero, David
2016-01-01
Computational modeling of biomedical processes is gaining more and more weight in the current research into the etiology of biomedical problems and potential treatment strategies. Computational modeling allows to reduce, refine and replace animal experimentation as well as to translate findings obtained in these experiments to the human background. However these biomedical problems are inherently complex with a myriad of influencing factors, which strongly complicates the model building and validation process. This book wants to address four main issues related to the building and validation of computational models of biomedical processes: Modeling establishment under uncertainty Model selection and parameter fitting Sensitivity analysis and model adaptation Model predictions under uncertainty In each of the abovementioned areas, the book discusses a number of key-techniques by means of a general theoretical description followed by one or more practical examples. This book is intended for graduate stude...
Human brain mapping: Experimental and computational approaches
Wood, C.C.; George, J.S.; Schmidt, D.M.; Aine, C.J. [Los Alamos National Lab., NM (US); Sanders, J. [Albuquerque VA Medical Center, NM (US); Belliveau, J. [Massachusetts General Hospital, Boston, MA (US)
1998-11-01
This is the final report of a three-year, Laboratory-Directed Research and Development (LDRD) project at the Los Alamos National Laboratory (LANL). This program developed project combined Los Alamos' and collaborators' strengths in noninvasive brain imaging and high performance computing to develop potential contributions to the multi-agency Human Brain Project led by the National Institute of Mental Health. The experimental component of the project emphasized the optimization of spatial and temporal resolution of functional brain imaging by combining: (a) structural MRI measurements of brain anatomy; (b) functional MRI measurements of blood flow and oxygenation; and (c) MEG measurements of time-resolved neuronal population currents. The computational component of the project emphasized development of a high-resolution 3-D volumetric model of the brain based on anatomical MRI, in which structural and functional information from multiple imaging modalities can be integrated into a single computational framework for modeling, visualization, and database representation.
Human brain mapping: Experimental and computational approaches
Wood, C.C.; George, J.S.; Schmidt, D.M.; Aine, C.J. [Los Alamos National Lab., NM (US); Sanders, J. [Albuquerque VA Medical Center, NM (US); Belliveau, J. [Massachusetts General Hospital, Boston, MA (US)
1998-11-01
This is the final report of a three-year, Laboratory-Directed Research and Development (LDRD) project at the Los Alamos National Laboratory (LANL). This program developed project combined Los Alamos' and collaborators' strengths in noninvasive brain imaging and high performance computing to develop potential contributions to the multi-agency Human Brain Project led by the National Institute of Mental Health. The experimental component of the project emphasized the optimization of spatial and temporal resolution of functional brain imaging by combining: (a) structural MRI measurements of brain anatomy; (b) functional MRI measurements of blood flow and oxygenation; and (c) MEG measurements of time-resolved neuronal population currents. The computational component of the project emphasized development of a high-resolution 3-D volumetric model of the brain based on anatomical MRI, in which structural and functional information from multiple imaging modalities can be integrated into a single computational framework for modeling, visualization, and database representation.
Computational Models of Spreadsheet Development: Basis for Educational Approaches
Hodnigg, Karin; Mittermeir, Roland T
2008-01-01
Among the multiple causes of high error rates in spreadsheets, lack of proper training and of deep understanding of the computational model upon which spreadsheet computations rest might not be the least issue. The paper addresses this problem by presenting a didactical model focussing on cell interaction, thus exceeding the atomicity of cell computations. The approach is motivated by an investigation how different spreadsheet systems handle certain computational issues implied from moving cells, copy-paste operations, or recursion.
Accurate characterization of weak neutron fields by using a Bayesian approach.
Medkour Ishak-Boushaki, G; Allab, M
2017-04-01
A Bayesian analysis of data derived from neutron spectrometric measurements provides the advantage of determining rigorously integral physical quantities characterizing the neutron field and their respective related uncertainties. The first and essential step in a Bayesian approach is the parameterization of the investigated neutron spectrum. The aim of this paper is to investigate the sensitivity of the Bayesian results, mainly the neutron dose H(*)(10) required for radiation protection purposes and its correlated uncertainty, to the selected neutron spectrum parameterization.
Heterogeneous Computing in Economics: A Simplified Approach
Dziubinski, Matt P.; Grassi, Stefano
This paper shows the potential of heterogeneous computing in solving dynamic equilibrium models in economics. We illustrate the power and simplicity of the C++ Accelerated Massive Parallelism recently introduced by Microsoft. Starting from the same exercise as Aldrich et al. (2011) we document a ...
Molecular electromagnetism a computational chemistry approach
Sauer, Stephan P A
2011-01-01
A textbook for a one-semester course for students in chemistry physics and nanotechnology, this book examines the interaction of molecules with electric and magnetic fields as, for example in light. The book provides the necessary background knowledge for simulating these interactions on computers with modern quantum chemical software.
Milman, Mark H
2005-12-01
Astrometric measurements using stellar interferometry rely on precise measurement of the central white light fringe to accurately obtain the optical pathlength difference of incoming starlight to the two arms of the interferometer. One standard approach to stellar interferometry uses a channeled spectrum to determine phases at a number of different wavelengths that are then converted to the pathlength delay. When throughput is low these channels are broadened to improve the signal-to-noise ratio. Ultimately the ability to use monochromatic models and algorithms in each of the channels to extract phase becomes problematic and knowledge of the spectrum must be incorporated to achieve the accuracies required of the astrometric measurements. To accomplish this an optimization problem is posed to estimate simultaneously the pathlength delay and spectrum of the source. Moreover, the nature of the parameterization of the spectrum that is introduced circumvents the need to solve directly for these parameters so that the optimization problem reduces to a scalar problem in just the pathlength delay variable. A number of examples are given to show the robustness of the approach.
Kovarik, Libor; Stevens, Andrew J.; Liyu, Andrey V.; Browning, Nigel D.
2016-10-17
Aberration correction for scanning transmission electron microscopes (STEM) has dramatically increased spatial image resolution for beam-stable materials, but it is the sample stability rather than the microscope that often limits the practical resolution of STEM images. To extract physical information from images of beam sensitive materials it is becoming clear that there is a critical dose/dose-rate below which the images can be interpreted as representative of the pristine material, while above it the observation is dominated by beam effects. Here we describe an experimental approach for sparse sampling in the STEM and in-painting image reconstruction in order to reduce the electron dose/dose-rate to the sample during imaging. By characterizing the induction limited rise-time and hysteresis in scan coils, we show that sparse line-hopping approach to scan randomization can be implemented that optimizes both the speed of the scan and the amount of the sample that needs to be illuminated by the beam. The dose and acquisition time for the sparse sampling is shown to be effectively decreased by factor of 5x relative to conventional acquisition, permitting imaging of beam sensitive materials to be obtained without changing the microscope operating parameters. The use of sparse line-hopping scan to acquire STEM images is demonstrated with atomic resolution aberration corrected Z-contrast images of CaCO3, a material that is traditionally difficult to image by TEM/STEM because of dose issues.
Efficient and accurate approach to modeling the microstructure and defect properties of LaCoO3
Buckeridge, J.; Taylor, F. H.; Catlow, C. R. A.
2016-04-01
Complex perovskite oxides are promising materials for cathode layers in solid oxide fuel cells. Such materials have intricate electronic, magnetic, and crystalline structures that prove challenging to model accurately. We analyze a wide range of standard density functional theory approaches to modeling a highly promising system, the perovskite LaCoO3, focusing on optimizing the Hubbard U parameter to treat the self-interaction of the B-site cation's d states, in order to determine the most appropriate method to study defect formation and the effect of spin on local structure. By calculating structural and electronic properties for different magnetic states we determine that U =4 eV for Co in LaCoO3 agrees best with available experiments. We demonstrate that the generalized gradient approximation (PBEsol +U ) is most appropriate for studying structure versus spin state, while the local density approximation (LDA +U ) is most appropriate for determining accurate energetics for defect properties.
Fu, Jian; Tan, Renbo; Chen, Liyuan
2014-01-01
X-ray differential phase-contrast computed tomography (DPC-CT) is a powerful physical and biochemical analysis tool. In practical applications, there are often challenges for DPC-CT due to insufficient data caused by few-view, bad or missing detector channels, or limited scanning angular range. They occur quite frequently because of experimental constraints from imaging hardware, scanning geometry, and the exposure dose delivered to living specimens. In this work, we analyze the influence of incomplete data on DPC-CT image reconstruction. Then, a reconstruction method is developed and investigated for incomplete data DPC-CT. It is based on an algebraic iteration reconstruction technique, which minimizes the image total variation and permits accurate tomographic imaging with less data. This work comprises a numerical study of the method and its experimental verification using a dataset measured at the W2 beamline of the storage ring DORIS III equipped with a Talbot-Lau interferometer. The numerical and experimental results demonstrate that the presented method can handle incomplete data. It will be of interest for a wide range of DPC-CT applications in medicine, biology, and nondestructive testing.
Computational Approach To Understanding Autism Spectrum Disorders
Włodzisław Duch
2012-01-01
Full Text Available Every year the prevalence of Autism Spectrum of Disorders (ASD is rising. Is there a unifying mechanism of various ASD cases at the genetic, molecular, cellular or systems level? The hypothesis advanced in this paper is focused on neural dysfunctions that lead to problems with attention in autistic people. Simulations of attractor neural networks performing cognitive functions help to assess system long-term neurodynamics. The Fuzzy Symbolic Dynamics (FSD technique is used for the visualization of attractors in the semantic layer of the neural model of reading. Large-scale simulations of brain structures characterized by a high order of complexity requires enormous computational power, especially if biologically motivated neuron models are used to investigate the inﬂuence of cellular structure dysfunctions on the network dynamics. Such simulations have to be implemented on computer clusters in a grid-based architectures
Music Genre Classification Systems - A Computational Approach
Ahrendt, Peter; Hansen, Lars Kai
2006-01-01
Automatic music genre classification is the classification of a piece of music into its corresponding genre (such as jazz or rock) by a computer. It is considered to be a cornerstone of the research area Music Information Retrieval (MIR) and closely linked to the other areas in MIR. It is thought that MIR will be a key element in the processing, searching and retrieval of digital music in the near future. This dissertation is concerned with music genre classification systems and in particular...
Soulez, Ferréol; Denis, Loïc; Fournier, Corinne; Thiébaut, Eric; Goepfert, Charles
2007-04-01
We propose a microparticle localization scheme in digital holography. Most conventional digital holography methods are based on Fresnel transform and present several problems such as twin-image noise, border effects, and other effects. To avoid these difficulties, we propose an inverse-problem approach, which yields the optimal particle set that best models the observed hologram image. We resolve this global optimization problem by conventional particle detection followed by a local refinement for each particle. Results for both simulated and real digital holograms show strong improvement in the localization of the particles, particularly along the depth dimension. In our simulations, the position precision is > or =1 microm rms. Our results also show that the localization precision does not deteriorate for particles near the edge of the field of view.
Computational Thinking and Practice - A Generic Approach to Computing in Danish High Schools
Caspersen, Michael E.; Nowack, Palle
2014-01-01
Internationally, there is a growing awareness on the necessity of providing relevant computing education in schools, particularly high schools. We present a new and generic approach to Computing in Danish High Schools based on a conceptual framework derived from ideas related to computational thi...
Robust and Accurate Modeling Approaches for Migraine Per-Patient Prediction from Ambulatory Data
Josué Pagán
2015-06-01
Full Text Available Migraine is one of the most wide-spread neurological disorders, and its medical treatment represents a high percentage of the costs of health systems. In some patients, characteristic symptoms that precede the headache appear. However, they are nonspecific, and their prediction horizon is unknown and pretty variable; hence, these symptoms are almost useless for prediction, and they are not useful to advance the intake of drugs to be effective and neutralize the pain. To solve this problem, this paper sets up a realistic monitoring scenario where hemodynamic variables from real patients are monitored in ambulatory conditions with a wireless body sensor network (WBSN. The acquired data are used to evaluate the predictive capabilities and robustness against noise and failures in sensors of several modeling approaches. The obtained results encourage the development of per-patient models based on state-space models (N4SID that are capable of providing average forecast windows of 47 min and a low rate of false positives.
Robust and Accurate Modeling Approaches for Migraine Per-Patient Prediction from Ambulatory Data
Pagán, Josué; Irene De Orbe, M.; Gago, Ana; Sobrado, Mónica; Risco-Martín, José L.; Vivancos Mora, J.; Moya, José M.; Ayala, José L.
2015-01-01
Migraine is one of the most wide-spread neurological disorders, and its medical treatment represents a high percentage of the costs of health systems. In some patients, characteristic symptoms that precede the headache appear. However, they are nonspecific, and their prediction horizon is unknown and pretty variable; hence, these symptoms are almost useless for prediction, and they are not useful to advance the intake of drugs to be effective and neutralize the pain. To solve this problem, this paper sets up a realistic monitoring scenario where hemodynamic variables from real patients are monitored in ambulatory conditions with a wireless body sensor network (WBSN). The acquired data are used to evaluate the predictive capabilities and robustness against noise and failures in sensors of several modeling approaches. The obtained results encourage the development of per-patient models based on state-space models (N4SID) that are capable of providing average forecast windows of 47 min and a low rate of false positives. PMID:26134103
Acoustic gravity waves: A computational approach
Hariharan, S. I.; Dutt, P. K.
1987-01-01
This paper discusses numerical solutions of a hyperbolic initial boundary value problem that arises from acoustic wave propagation in the atmosphere. Field equations are derived from the atmospheric fluid flow governed by the Euler equations. The resulting original problem is nonlinear. A first order linearized version of the problem is used for computational purposes. The main difficulty in the problem as with any open boundary problem is in obtaining stable boundary conditions. Approximate boundary conditions are derived and shown to be stable. Numerical results are presented to verify the effectiveness of these boundary conditions.
Kong, Hao; Ma, Zhuoran; Wang, Song; Gong, Xiaoyun; Zhang, Sichun; Zhang, Xinrong
2014-08-05
With the inspiration of an ancient Chinese poison test approach, we report a rapid hydrogen sulfide detection strategy in specific areas of live cells using silver needles with good spatial resolution of 2 × 2 μm(2). Besides the accurate-localization ability, this reflection-based strategy also has attractive merits of convenience and robust response when free pretreatment and short detection time are concerned. The success of endogenous H2S level evaluation in cellular cytoplasm and nuclear of human A549 cells promises the application potential of our strategy in scientific research and medical diagnosis.
Global computational algebraic topology approach for diffusion
Auclair-Fortier, Marie-Flavie; Ziou, Djemel; Allili, Madjid
2004-05-01
One physical process involved in many computer vision problems is the heat diffusion process. Such Partial differential equations are continuous and have to be discretized by some techniques, mostly mathematical processes like finite differences or finite elements. The continuous domain is subdivided into sub-domains in which there is only one value. The diffusion equation comes from the energy conservation then it is valid on a whole domain. We use the global equation instead of discretize the PDE obtained by a limit process on this global equation. To encode these physical global values over pixels of different dimensions, we use a computational algebraic topology (CAT)-based image model. This model has been proposed by Ziou and Allili and used for the deformation of curves and optical flow. It introduces the image support as a decomposition in terms of points, edges, surfaces, volumes, etc. Images of any dimensions can then be handled. After decomposing the physical principles of the heat transfer into basic laws, we recall the CAT-based image model and use it to encode the basic laws. We then present experimental results for nonlinear graylevel diffusion for denoising, ensuring thin features preservation.
A complex network approach to cloud computing
Travieso, Gonzalo; Bruno, Odemir Martinez; Costa, Luciano da Fontoura
2015-01-01
Cloud computing has become an important means to speed up computing. One problem influencing heavily the performance of such systems is the choice of nodes as servers responsible for executing the users' tasks. In this article we report how complex networks can be used to model such a problem. More specifically, we investigate the performance of the processing respectively to cloud systems underlain by Erdos-Renyi and Barabasi-Albert topology containing two servers. Cloud networks involving two communities not necessarily of the same size are also considered in our analysis. The performance of each configuration is quantified in terms of two indices: the cost of communication between the user and the nearest server, and the balance of the distribution of tasks between the two servers. Regarding the latter index, the ER topology provides better performance than the BA case for smaller average degrees and opposite behavior for larger average degrees. With respect to the cost, smaller values are found in the BA ...
Computational approaches to homogeneous gold catalysis.
Faza, Olalla Nieto; López, Carlos Silva
2015-01-01
Homogenous gold catalysis has been exploding for the last decade at an outstanding pace. The best described reactivity of Au(I) and Au(III) species is based on gold's properties as a soft Lewis acid, but new reactivity patterns have recently emerged which further expand the range of transformations achievable using gold catalysis, with examples of dual gold activation, hydrogenation reactions, or Au(I)/Au(III) catalytic cycles.In this scenario, to develop fully all these new possibilities, the use of computational tools to understand at an atomistic level of detail the complete role of gold as a catalyst is unavoidable. In this work we aim to provide a comprehensive review of the available benchmark works on methodological options to study homogenous gold catalysis in the hope that this effort can help guide the choice of method in future mechanistic studies involving gold complexes. This is relevant because a representative number of current mechanistic studies still use methods which have been reported as inappropriate and dangerously inaccurate for this chemistry.Together with this, we describe a number of recent mechanistic studies where computational chemistry has provided relevant insights into non-conventional reaction paths, unexpected selectivities or novel reactivity, which illustrate the complexity behind gold-mediated organic chemistry.
Q-P Wave traveltime computation by an iterative approach
Ma, Xuxin
2013-01-01
In this work, we present a new approach to compute anisotropic traveltime based on solving successively elliptical isotropic traveltimes. The method shows good accuracy and is very simple to implement.
C. Sun
2010-03-01
obtained from RS retrieval, which was in accordance with previous studies (Jamieson, 1982; Dugas and Ainsworth, 1985; Benson et al., 1992; Pereira and Nova, 1992.
After the data fusion, the correlation (R^{2}=0.8516 between the monthly runoff obtained from the simulation based on ET retrieval and the observed data was higher than that (R^{2}=0.8411 between the data obtained from the PM-based ET simulation and the observed data. As for the RMSE, the result (RMSE=26.0860 between the simulated runoff based on ET retrieval and the observed data was also superior to the result (RMSE=35.71904 between the simulated runoff obtained with PM-based ET and the observed data. As for the MBE parameter, the result (MBE=−8.6578 for the RS retrieval method was obviously better than that (MBE=−22.7313 for the PM-based method. The comparison of them showed that the RS retrieval had better adaptivity and higher accuracy than the PM-based method, and the new approach based on data fusion and the distributed hydrological model was feasible, reliable and worth being studied further.
The fundamentals of computational intelligence system approach
Zgurovsky, Mikhail Z
2017-01-01
This monograph is dedicated to the systematic presentation of main trends, technologies and methods of computational intelligence (CI). The book pays big attention to novel important CI technology- fuzzy logic (FL) systems and fuzzy neural networks (FNN). Different FNN including new class of FNN- cascade neo-fuzzy neural networks are considered and their training algorithms are described and analyzed. The applications of FNN to the forecast in macroeconomics and at stock markets are examined. The book presents the problem of portfolio optimization under uncertainty, the novel theory of fuzzy portfolio optimization free of drawbacks of classical model of Markovitz as well as an application for portfolios optimization at Ukrainian, Russian and American stock exchanges. The book also presents the problem of corporations bankruptcy risk forecasting under incomplete and fuzzy information, as well as new methods based on fuzzy sets theory and fuzzy neural networks and results of their application for bankruptcy ris...
A polyhedral approach to computing border bases
Braun, Gábor
2009-01-01
Border bases can be considered to be the natural extension of Gr\\"obner bases that have several advantages. Unfortunately, to date the classical border basis algorithm relies on (degree-compatible) term orderings and implicitly on reduced Gr\\"obner bases. We adapt the classical border basis algorithm to allow for calculating border bases for arbitrary degree-compatible order ideals, which is \\emph{independent} from term orderings. Moreover, the algorithm also supports calculating degree-compatible order ideals with \\emph{preference} on contained elements, even though finding a preferred order ideal is NP-hard. Effectively we retain degree-compatibility only to successively extend our computation degree-by-degree. The adaptation is based on our polyhedral characterization: order ideals that support a border basis correspond one-to-one to integral points of the order ideal polytope. This establishes a crucial connection between the ideal and the combinatorial structure of the associated factor spaces.
Biologically motivated computationally intensive approaches to image pattern recognition
Petkov, Nikolay
1995-01-01
This paper presents some of the research activities of the research group in vision as a grand challenge problem whose solution is estimated to need the power of Tflop/s computers and for which computational methods have yet to be developed. The concerned approaches are biologically motivated, in th
An Approach to Dynamic Provisioning of Social and Computational Services
Bonino da Silva Santos, Luiz Olavo; Sorathia, Vikram; Ferreira Pires, Luis; Sinderen, van Marten
2010-01-01
Service-Oriented Computing (SOC) builds upon the intuitive notion of service already known and used in our society for a long time. SOC-related approaches are based on computer-executable functional units that often represent automation of services that exist at the social level, i.e., services at t
Yildiz, Dilan; Bozkaya, Uğur
2016-01-30
The extended Koopmans' theorem (EKT) provides a straightforward way to compute ionization potentials and electron affinities from any level of theory. Although it is widely applied to ionization potentials, the EKT approach has not been applied to evaluation of the chemical reactivity. We present the first benchmarking study to investigate the performance of the EKT methods for predictions of chemical potentials (μ) (hence electronegativities), chemical hardnesses (η), and electrophilicity indices (ω). We assess the performance of the EKT approaches for post-Hartree-Fock methods, such as Møller-Plesset perturbation theory, the coupled-electron pair theory, and their orbital-optimized counterparts for the evaluation of the chemical reactivity. Especially, results of the orbital-optimized coupled-electron pair theory method (with the aug-cc-pVQZ basis set) for predictions of the chemical reactivity are very promising; the corresponding mean absolute errors are 0.16, 0.28, and 0.09 eV for μ, η, and ω, respectively. © 2015 Wiley Periodicals, Inc.
General approaches in ensemble quantum computing
V Vimalan; N Chandrakumar
2008-01-01
We have developed methodology for NMR quantum computing focusing on enhancing the efficiency of initialization, of logic gate implementation and of readout. Our general strategy involves the application of rotating frame pulse sequences to prepare pseudopure states and to perform logic operations. We demonstrate experimentally our methodology for both homonuclear and heteronuclear spin ensembles. On model two-spin systems, the initialization time of one of our sequences is three-fourths (in the heteronuclear case) or one-fourth (in the homonuclear case), of the typical pulsed free precession sequences, attaining the same initialization efficiency. We have implemented the logical SWAP operation in homonuclear AMX spin systems using selective isotropic mixing, reducing the duration taken to a third compared to the standard re-focused INEPT-type sequence. We introduce the 1D version for readout of the rotating frame SWAP operation, in an attempt to reduce readout time. We further demonstrate the Hadamard mode of 1D SWAP, which offers 2N-fold reduction in experiment time for a system with -working bits, attaining the same sensitivity as the standard 1D version.
Delay Computation Using Fuzzy Logic Approach
Ramasesh G. R.
2012-10-01
Full Text Available The paper presents practical application of fuzzy sets and system theory in predicting delay, with reasonable accuracy, a wide range of factors pertaining to construction projects. In this paper we shall use fuzzy logic to predict delays on account of Delayed supplies and Labor shortage. It is observed that the project scheduling software use either deterministic method or probabilistic method for computation of schedule durations, delays, lags and other parameters. In other words, these methods use only quantitative inputs leaving-out the qualitative aspects associated with individual activity of work. The qualitative aspect viz., the expertise of the mason or the lack of experience can have a significant impact on the assessed duration. Such qualitative aspects do not find adequate representation in the Project Scheduling software. A realistic project is considered for which a PERT chart has been prepared using showing all the major activities in reasonable detail. This project has been periodically updated until its completion. It is observed that some of the activities are delayed due to extraneous factors resulting in the overall delay of the project. The software has the capability to calculate the overall delay through CPM (Critical Path Method when each of the activity-delays is reported. We shall now demonstrate that by using fuzzy logic, these delays could have been predicted well in advance.
Multivariate analysis: A statistical approach for computations
Michu, Sachin; Kaushik, Vandana
2014-10-01
Multivariate analysis is a type of multivariate statistical approach commonly used in, automotive diagnosis, education evaluating clusters in finance etc and more recently in the health-related professions. The objective of the paper is to provide a detailed exploratory discussion about factor analysis (FA) in image retrieval method and correlation analysis (CA) of network traffic. Image retrieval methods aim to retrieve relevant images from a collected database, based on their content. The problem is made more difficult due to the high dimension of the variable space in which the images are represented. Multivariate correlation analysis proposes an anomaly detection and analysis method based on the correlation coefficient matrix. Anomaly behaviors in the network include the various attacks on the network like DDOs attacks and network scanning.
Aluminium in Biological Environments: A Computational Approach
Mujika, Jon I; Rezabal, Elixabete; Mercero, Jose M; Ruipérez, Fernando; Costa, Dominique; Ugalde, Jesus M; Lopez, Xabier
2014-01-01
The increased availability of aluminium in biological environments, due to human intervention in the last century, raises concerns on the effects that this so far “excluded from biology” metal might have on living organisms. Consequently, the bioinorganic chemistry of aluminium has emerged as a very active field of research. This review will focus on our contributions to this field, based on computational studies that can yield an understanding of the aluminum biochemistry at a molecular level. Aluminium can interact and be stabilized in biological environments by complexing with both low molecular mass chelants and high molecular mass peptides. The speciation of the metal is, nonetheless, dictated by the hydrolytic species dominant in each case and which vary according to the pH condition of the medium. In blood, citrate and serum transferrin are identified as the main low molecular mass and high molecular mass molecules interacting with aluminium. The complexation of aluminium to citrate and the subsequent changes exerted on the deprotonation pathways of its tritable groups will be discussed along with the mechanisms for the intake and release of aluminium in serum transferrin at two pH conditions, physiological neutral and endosomatic acidic. Aluminium can substitute other metals, in particular magnesium, in protein buried sites and trigger conformational disorder and alteration of the protonation states of the protein's sidechains. A detailed account of the interaction of aluminium with proteic sidechains will be given. Finally, it will be described how alumnium can exert oxidative stress by stabilizing superoxide radicals either as mononuclear aluminium or clustered in boehmite. The possibility of promotion of Fenton reaction, and production of hydroxyl radicals will also be discussed. PMID:24757505
Numerical Methods for Stochastic Computations A Spectral Method Approach
Xiu, Dongbin
2010-01-01
The first graduate-level textbook to focus on fundamental aspects of numerical methods for stochastic computations, this book describes the class of numerical methods based on generalized polynomial chaos (gPC). These fast, efficient, and accurate methods are an extension of the classical spectral methods of high-dimensional random spaces. Designed to simulate complex systems subject to random inputs, these methods are widely used in many areas of computer science and engineering. The book introduces polynomial approximation theory and probability theory; describes the basic theory of gPC meth
Mutations that Cause Human Disease: A Computational/Experimental Approach
Beernink, P; Barsky, D; Pesavento, B
2006-01-11
International genome sequencing projects have produced billions of nucleotides (letters) of DNA sequence data, including the complete genome sequences of 74 organisms. These genome sequences have created many new scientific opportunities, including the ability to identify sequence variations among individuals within a species. These genetic differences, which are known as single nucleotide polymorphisms (SNPs), are particularly important in understanding the genetic basis for disease susceptibility. Since the report of the complete human genome sequence, over two million human SNPs have been identified, including a large-scale comparison of an entire chromosome from twenty individuals. Of the protein coding SNPs (cSNPs), approximately half leads to a single amino acid change in the encoded protein (non-synonymous coding SNPs). Most of these changes are functionally silent, while the remainder negatively impact the protein and sometimes cause human disease. To date, over 550 SNPs have been found to cause single locus (monogenic) diseases and many others have been associated with polygenic diseases. SNPs have been linked to specific human diseases, including late-onset Parkinson disease, autism, rheumatoid arthritis and cancer. The ability to predict accurately the effects of these SNPs on protein function would represent a major advance toward understanding these diseases. To date several attempts have been made toward predicting the effects of such mutations. The most successful of these is a computational approach called ''Sorting Intolerant From Tolerant'' (SIFT). This method uses sequence conservation among many similar proteins to predict which residues in a protein are functionally important. However, this method suffers from several limitations. First, a query sequence must have a sufficient number of relatives to infer sequence conservation. Second, this method does not make use of or provide any information on protein structure, which
Mobile Cloud Computing: A Review on Smartphone Augmentation Approaches
Abolfazli, Saeid; Gani, Abdullah
2012-01-01
Smartphones have recently gained significant popularity in heavy mobile processing while users are increasing their expectations toward rich computing experience. However, resource limitations and current mobile computing advancements hinder this vision. Therefore, resource-intensive application execution remains a challenging task in mobile computing that necessitates device augmentation. In this article, smartphone augmentation approaches are reviewed and classified in two main groups, namely hardware and software. Generating high-end hardware is a subset of hardware augmentation approaches, whereas conserving local resource and reducing resource requirements approaches are grouped under software augmentation methods. Our study advocates that consreving smartphones' native resources, which is mainly done via task offloading, is more appropriate for already-developed applications than new ones, due to costly re-development process. Cloud computing has recently obtained momentous ground as one of the major co...
Convergence Analysis of a Class of Computational Intelligence Approaches
Junfeng Chen
2013-01-01
Full Text Available Computational intelligence approaches is a relatively new interdisciplinary field of research with many promising application areas. Although the computational intelligence approaches have gained huge popularity, it is difficult to analyze the convergence. In this paper, a computational model is built up for a class of computational intelligence approaches represented by the canonical forms of generic algorithms, ant colony optimization, and particle swarm optimization in order to describe the common features of these algorithms. And then, two quantification indices, that is, the variation rate and the progress rate, are defined, respectively, to indicate the variety and the optimality of the solution sets generated in the search process of the model. Moreover, we give four types of probabilistic convergence for the solution set updating sequences, and their relations are discussed. Finally, the sufficient conditions are derived for the almost sure weak convergence and the almost sure strong convergence of the model by introducing the martingale theory into the Markov chain analysis.
What is intrinsic motivation? A typology of computational approaches
Pierre-Yves Oudeyer
2009-11-01
Full Text Available Intrinsic motivation, the causal mechanism for spontaneous exploration and curiosity, is a central concept in developmental psychology. It has been argued to be a crucial mechanism for open-ended cognitive development in humans, and as such has gathered a growing interest from developmental roboticists in the recent years. The goal of this paper is threefold. First, it provides a synthesis of the different approaches of intrinsic motivation in psychology. Second, by interpreting these approaches in a computational reinforcement learning framework, we argue that they are not operational and even sometimes inconsistent. Third, we set the ground for a systematic operational study of intrinsic motivation by presenting a formal typology of possible computational approaches. This typology is partly based on existing computational models, but also presents new ways of conceptualizing intrinsic motivation. We argue that this kind of computational typology might be useful for opening new avenues for research both in psychology and developmental robotics.
Gan, Chenquan; Yang, Xiaofan; Liu, Wanping; Zhu, Qingyi; Jin, Jian; He, Li
2014-08-01
Based on the assumption that external computers (particularly, infected external computers) are connected to the Internet, and by considering the influence of the Internet topology on computer virus spreading, this paper establishes a novel computer virus propagation model with a complex-network approach. This model possesses a unique (viral) equilibrium which is globally attractive. Some numerical simulations are also given to illustrate this result. Further study shows that the computers with higher node degrees are more susceptible to infection than those with lower node degrees. In this regard, some appropriate protective measures are suggested.
An Integrated Computer-Aided Approach for Environmental Studies
Gani, Rafiqul; Chen, Fei; Jaksland, Cecilia;
1997-01-01
A general framework for an integrated computer-aided approach to solve process design, control, and environmental problems simultaneously is presented. Physicochemical properties and their relationships to the molecular structure play an important role in the proposed integrated approach. The scope...... and applicability of the integrated approach is highlighted through examples involving estimation of properties and environmental pollution prevention. The importance of mixture effects on some environmentally important properties is also demonstrated....
Immonen, Taina; Gibson, Richard; Leitner, Thomas; Miller, Melanie A; Arts, Eric J; Somersalo, Erkki; Calvetti, Daniela
2012-11-01
We present a new hybrid stochastic-deterministic, spatially distributed computational model to simulate growth competition assays on a relatively immobile monolayer of peripheral blood mononuclear cells (PBMCs), commonly used for determining ex vivo fitness of human immunodeficiency virus type-1 (HIV-1). The novel features of our approach include incorporation of viral diffusion through a deterministic diffusion model while simulating cellular dynamics via a stochastic Markov chain model. The model accounts for multiple infections of target cells, CD4-downregulation, and the delay between the infection of a cell and the production of new virus particles. The minimum threshold level of infection induced by a virus inoculum is determined via a series of dilution experiments, and is used to determine the probability of infection of a susceptible cell as a function of local virus density. We illustrate how this model can be used for estimating the distribution of cells infected by either a single virus type or two competing viruses. Our model captures experimentally observed variation in the fitness difference between two virus strains, and suggests a way to minimize variation and dual infection in experiments.
Liang, Yufeng; Vinson, John; Pemmaraju, Sri; Drisdell, Walter S.; Shirley, Eric L.; Prendergast, David
2017-03-01
Constrained-occupancy delta-self-consistent-field (Δ SCF ) methods and many-body perturbation theories (MBPT) are two strategies for obtaining electronic excitations from first principles. Using the two distinct approaches, we study the O 1 s core excitations that have become increasingly important for characterizing transition-metal oxides and understanding strong electronic correlation. The Δ SCF approach, in its current single-particle form, systematically underestimates the pre-edge intensity for chosen oxides, despite its success in weakly correlated systems. By contrast, the Bethe-Salpeter equation within MBPT predicts much better line shapes. This motivates one to reexamine the many-electron dynamics of x-ray excitations. We find that the single-particle Δ SCF approach can be rectified by explicitly calculating many-electron transition amplitudes, producing x-ray spectra in excellent agreement with experiments. This study paves the way to accurately predict x-ray near-edge spectral fingerprints for physics and materials science beyond the Bethe-Salpether equation.
Computational Thinking and Practice - A Generic Approach to Computing in Danish High Schools
Caspersen, Michael E.; Nowack, Palle
2014-01-01
Internationally, there is a growing awareness on the necessity of providing relevant computing education in schools, particularly high schools. We present a new and generic approach to Computing in Danish High Schools based on a conceptual framework derived from ideas related to computational...... thinking. We present two main theses on which the subject is based, and we present the included knowledge areas and didactical design principles. Finally we summarize the status and future plans for the subject and related development projects....
Estrada, T; Zhang, B; Cicotti, P; Armen, R S; Taufer, M
2012-07-01
We present a scalable and accurate method for classifying protein-ligand binding geometries in molecular docking. Our method is a three-step process: the first step encodes the geometry of a three-dimensional (3D) ligand conformation into a single 3D point in the space; the second step builds an octree by assigning an octant identifier to every single point in the space under consideration; and the third step performs an octree-based clustering on the reduced conformation space and identifies the most dense octant. We adapt our method for MapReduce and implement it in Hadoop. The load-balancing, fault-tolerance, and scalability in MapReduce allow screening of very large conformation spaces not approachable with traditional clustering methods. We analyze results for docking trials for 23 protein-ligand complexes for HIV protease, 21 protein-ligand complexes for Trypsin, and 12 protein-ligand complexes for P38alpha kinase. We also analyze cross docking trials for 24 ligands, each docking into 24 protein conformations of the HIV protease, and receptor ensemble docking trials for 24 ligands, each docking in a pool of HIV protease receptors. Our method demonstrates significant improvement over energy-only scoring for the accurate identification of native ligand geometries in all these docking assessments. The advantages of our clustering approach make it attractive for complex applications in real-world drug design efforts. We demonstrate that our method is particularly useful for clustering docking results using a minimal ensemble of representative protein conformational states (receptor ensemble docking), which is now a common strategy to address protein flexibility in molecular docking.
Computational experiment approach to advanced secondary mathematics curriculum
Abramovich, Sergei
2014-01-01
This book promotes the experimental mathematics approach in the context of secondary mathematics curriculum by exploring mathematical models depending on parameters that were typically considered advanced in the pre-digital education era. This approach, by drawing on the power of computers to perform numerical computations and graphical constructions, stimulates formal learning of mathematics through making sense of a computational experiment. It allows one (in the spirit of Freudenthal) to bridge serious mathematical content and contemporary teaching practice. In other words, the notion of teaching experiment can be extended to include a true mathematical experiment. When used appropriately, the approach creates conditions for collateral learning (in the spirit of Dewey) to occur including the development of skills important for engineering applications of mathematics. In the context of a mathematics teacher education program, this book addresses a call for the preparation of teachers capable of utilizing mo...
An approach to computing direction relations between separated object groups
Yan, H.; Wang, Z.; Li, J.
2013-09-01
Direction relations between object groups play an important role in qualitative spatial reasoning, spatial computation and spatial recognition. However, none of existing models can be used to compute direction relations between object groups. To fill this gap, an approach to computing direction relations between separated object groups is proposed in this paper, which is theoretically based on gestalt principles and the idea of multi-directions. The approach firstly triangulates the two object groups, and then it constructs the Voronoi diagram between the two groups using the triangular network. After this, the normal of each Voronoi edge is calculated, and the quantitative expression of the direction relations is constructed. Finally, the quantitative direction relations are transformed into qualitative ones. The psychological experiments show that the proposed approach can obtain direction relations both between two single objects and between two object groups, and the results are correct from the point of view of spatial cognition.
A tale of three bio-inspired computational approaches
Schaffer, J. David
2014-05-01
I will provide a high level walk-through for three computational approaches derived from Nature. First, evolutionary computation implements what we may call the "mother of all adaptive processes." Some variants on the basic algorithms will be sketched and some lessons I have gleaned from three decades of working with EC will be covered. Then neural networks, computational approaches that have long been studied as possible ways to make "thinking machines", an old dream of man's, and based upon the only known existing example of intelligence. Then, a little overview of attempts to combine these two approaches that some hope will allow us to evolve machines we could never hand-craft. Finally, I will touch on artificial immune systems, Nature's highly sophisticated defense mechanism, that has emerged in two major stages, the innate and the adaptive immune systems. This technology is finding applications in the cyber security world.
The Formal Approach to Computer Game Rule Development Automation
Elena, A
2009-01-01
Computer game rules development is one of the weakly automated tasks in game development. This paper gives an overview of the ongoing research project which deals with automation of rules development for turn-based strategy computer games. Rules are the basic elements of these games. This paper proposes a new approach to automation including visual formal rules model creation, model verification and modelbased code generation.
The process group approach to reliable distributed computing
Birman, Kenneth P.
1992-01-01
The difficulty of developing reliable distribution software is an impediment to applying distributed computing technology in many settings. Experience with the ISIS system suggests that a structured approach based on virtually synchronous process groups yields systems that are substantially easier to develop, exploit sophisticated forms of cooperative computation, and achieve high reliability. Six years of research on ISIS, describing the model, its implementation challenges, and the types of applications to which ISIS has been applied are reviewed.
Li, Qiang; Zhang, Wei; Guan, Xin; Bai, Yu; Jia, Jing
2014-01-01
The intima-media thickness (IMT) of common carotid artery (CCA) can serve as an important indicator for the assessment of cardiovascular diseases (CVDs). In this paper an improved approach for automatic IMT measurement with low complexity and high accuracy is presented. 100 ultrasound images from 100 patients were tested with the proposed approach. The ground truth (GT) of the IMT was manually measured for six times and averaged, while the automatic segmented (AS) IMT was computed by the algorithm proposed in this paper. The mean difference±standard deviation between AS and GT IMT is 0.0231±0.0348 mm, and the correlation coefficient between them is 0.9629. The computational time is 0.3223 s per image with MATLAB under Windows XP on an Intel Core 2 Duo CPU E7500 @2.93 GHz. The proposed algorithm has the potential to achieve real-time measurement under Visual Studio.
Qiang Li
2014-01-01
Full Text Available The intima-media thickness (IMT of common carotid artery (CCA can serve as an important indicator for the assessment of cardiovascular diseases (CVDs. In this paper an improved approach for automatic IMT measurement with low complexity and high accuracy is presented. 100 ultrasound images from 100 patients were tested with the proposed approach. The ground truth (GT of the IMT was manually measured for six times and averaged, while the automatic segmented (AS IMT was computed by the algorithm proposed in this paper. The mean difference ± standard deviation between AS and GT IMT is 0.0231 ± 0.0348 mm, and the correlation coefficient between them is 0.9629. The computational time is 0.3223 s per image with MATLAB under Windows XP on an Intel Core 2 Duo CPU E7500 @2.93 GHz. The proposed algorithm has the potential to achieve real-time measurement under Visual Studio.
Computational biomechanics for medicine new approaches and new applications
Miller, Karol; Wittek, Adam; Nielsen, Poul
2015-01-01
The Computational Biomechanics for Medicine titles provide an opportunity for specialists in computational biomechanics to present their latest methodologiesand advancements. Thisvolumecomprises twelve of the newest approaches and applications of computational biomechanics, from researchers in Australia, New Zealand, USA, France, Spain and Switzerland. Some of the interesting topics discussed are:real-time simulations; growth and remodelling of soft tissues; inverse and meshless solutions; medical image analysis; and patient-specific solid mechanics simulations. One of the greatest challenges facing the computational engineering community is to extend the success of computational mechanics to fields outside traditional engineering, in particular to biology, the biomedical sciences, and medicine. We hope the research presented within this book series will contribute to overcoming this grand challenge.
A distributed computing approach to mission operations support. [for spacecraft
Larsen, R. L.
1975-01-01
Computing mission operation support includes orbit determination, attitude processing, maneuver computation, resource scheduling, etc. The large-scale third-generation distributed computer network discussed is capable of fulfilling these dynamic requirements. It is shown that distribution of resources and control leads to increased reliability, and exhibits potential for incremental growth. Through functional specialization, a distributed system may be tuned to very specific operational requirements. Fundamental to the approach is the notion of process-to-process communication, which is effected through a high-bandwidth communications network. Both resource-sharing and load-sharing may be realized in the system.
Zhiheng Wang
Full Text Available The precise prediction of protein intrinsically disordered regions, which play a crucial role in biological procedures, is a necessary prerequisite to further the understanding of the principles and mechanisms of protein function. Here, we propose a novel predictor, DisoMCS, which is a more accurate predictor of protein intrinsically disordered regions. The DisoMCS bases on an original multi-class conservative score (MCS obtained by sequence-order/disorder alignment. Initially, near-disorder regions are defined on fragments located at both the terminus of an ordered region connecting a disordered region. Then the multi-class conservative score is generated by sequence alignment against a known structure database and represented as order, near-disorder and disorder conservative scores. The MCS of each amino acid has three elements: order, near-disorder and disorder profiles. Finally, the MCS is exploited as features to identify disordered regions in sequences. DisoMCS utilizes a non-redundant data set as the training set, MCS and predicted secondary structure as features, and a conditional random field as the classification algorithm. In predicted near-disorder regions a residue is determined as an order or a disorder according to the optimized decision threshold. DisoMCS was evaluated by cross-validation, large-scale prediction, independent tests and CASP (Critical Assessment of Techniques for Protein Structure Prediction tests. All results confirmed that DisoMCS was very competitive in terms of accuracy of prediction when compared with well-established publicly available disordered region predictors. It also indicated our approach was more accurate when a query has higher homologous with the knowledge database.The DisoMCS is available at http://cal.tongji.edu.cn/disorder/.
Oyedepo, Gbenga A; Wilson, Angela K
2010-08-26
The correlation consistent Composite Approach, ccCA [ Deyonker , N. J. ; Cundari , T. R. ; Wilson , A. K. J. Chem. Phys. 2006 , 124 , 114104 ] has been demonstrated to predict accurate thermochemical properties of chemical species that can be described by a single configurational reference state, and at reduced computational cost, as compared with ab initio methods such as CCSD(T) used in combination with large basis sets. We have developed three variants of a multireference equivalent of this successful theoretical model. The method, called the multireference correlation consistent composite approach (MR-ccCA), is designed to predict the thermochemical properties of reactive intermediates, excited state species, and transition states to within chemical accuracy (e.g., 1 kcal/mol for enthalpies of formation) of reliable experimental values. In this study, we have demonstrated the utility of MR-ccCA: (1) in the determination of the adiabatic singlet-triplet energy separations and enthalpies of formation for the ground states for a set of diradicals and unsaturated compounds, and (2) in the prediction of energetic barriers to internal rotation, in ethylene and its heavier congener, disilene. Additionally, we have utilized MR-ccCA to predict the enthalpies of formation of the low-lying excited states of all the species considered. MR-ccCA is shown to give quantitative results without reliance upon empirically derived parameters, making it suitable for application to study novel chemical systems with significant nondynamical correlation effects.
Corrado Lodovico Galli
Full Text Available Our research is aimed at devising and assessing a computational approach to evaluate the affinity of endocrine active substances (EASs and their metabolites towards the ligand binding domain (LBD of the androgen receptor (AR in three distantly related species: human, rat, and zebrafish. We computed the affinity for all the selected molecules following a computational approach based on molecular modelling and docking. Three different classes of molecules with well-known endocrine activity (iprodione, procymidone, vinclozolin, and a selection of their metabolites were evaluated. Our approach was demonstrated useful as the first step of chemical safety evaluation since ligand-target interaction is a necessary condition for exerting any biological effect. Moreover, a different sensitivity concerning AR LBD was computed for the tested species (rat being the least sensitive of the three. This evidence suggests that, in order not to over-/under-estimate the risks connected with the use of a chemical entity, further in vitro and/or in vivo tests should be carried out only after an accurate evaluation of the most suitable cellular system or animal species. The introduction of in silico approaches to evaluate hazard can accelerate discovery and innovation with a lower economic effort than with a fully wet strategy.
A multidisciplinary approach to solving computer related vision problems.
Long, Jennifer; Helland, Magne
2012-09-01
This paper proposes a multidisciplinary approach to solving computer related vision issues by including optometry as a part of the problem-solving team. Computer workstation design is increasing in complexity. There are at least ten different professions who contribute to workstation design or who provide advice to improve worker comfort, safety and efficiency. Optometrists have a role identifying and solving computer-related vision issues and in prescribing appropriate optical devices. However, it is possible that advice given by optometrists to improve visual comfort may conflict with other requirements and demands within the workplace. A multidisciplinary approach has been advocated for solving computer related vision issues. There are opportunities for optometrists to collaborate with ergonomists, who coordinate information from physical, cognitive and organisational disciplines to enact holistic solutions to problems. This paper proposes a model of collaboration and examples of successful partnerships at a number of professional levels including individual relationships between optometrists and ergonomists when they have mutual clients/patients, in undergraduate and postgraduate education and in research. There is also scope for dialogue between optometry and ergonomics professional associations. A multidisciplinary approach offers the opportunity to solve vision related computer issues in a cohesive, rather than fragmented way. Further exploration is required to understand the barriers to these professional relationships. © 2012 The College of Optometrists.
Martin, Y. L.
The performance of quantitative analysis of 1D NMR spectra depends greatly on the choice of the NMR signal model. Complex least-squares analysis is well suited for optimizing the quantitative determination of spectra containing a limited number of signals (20). From a general point of view it is concluded, on the basis of mathematical considerations and numerical simulations, that, in the absence of truncation of the free-induction decay, complex least-squares curve fitting either in the time or in the frequency domain and linear-prediction methods are in fact nearly equivalent and give identical results. However, in the situation considered, complex least-squares analysis in the frequency domain is more flexible since it enables the quality of convergence to be appraised at every resonance position. An efficient data-processing strategy has been developed which makes use of an approximate conjugate-gradient algorithm. All spectral parameters (frequency, damping factors, amplitudes, phases, initial delay associated with intensity, and phase parameters of a baseline correction) are simultaneously managed in an integrated approach which is fully automatable. The behavior of the error as a function of the signal-to-noise ratio is theoretically estimated, and the influence of apodization is discussed. The least-squares curve fitting is theoretically proved to be the most accurate approach for quantitative analysis of 1D NMR data acquired with reasonable signal-to-noise ratio. The method enables complex spectral residuals to be sorted out. These residuals, which can be cumulated thanks to the possibility of correcting for frequency shifts and phase errors, extract systematic components, such as isotopic satellite lines, and characterize the shape and the intensity of the spectral distortion with respect to the Lorentzian model. This distortion is shown to be nearly independent of the chemical species, of the nature of the molecular site, and of the type of nucleus, but
Assessing Trustworthiness in Social Media: A Social Computing Approach
2015-11-17
31-May-2015 Approved for Public Release; Distribution Unlimited Final Report: Assessing Trustworthiness in Social Media : A Social Computing Approach... media . We propose to investigate research issues related to social media trustworthiness and its assessment by leveraging social research methods...attributes of interest associated with a particular social media user related to the received information. This tool provides a way to combine different
A Unitifed Computational Approach to Oxide Aging Processes
Bowman, D.J.; Fleetwood, D.M.; Hjalmarson, H.P.; Schultz, P.A.
1999-01-27
In this paper we describe a unified, hierarchical computational approach to aging and reliability problems caused by materials changes in the oxide layers of Si-based microelectronic devices. We apply this method to a particular low-dose-rate radiation effects problem
Pedagogical Approaches to Teaching with Computer Simulations in Science Education
Rutten, N.P.G.; van der Veen, Johan (CTIT); van Joolingen, Wouter; McBride, Ron; Searson, Michael
2013-01-01
For this study we interviewed 24 physics teachers about their opinions on teaching with computer simulations. The purpose of this study is to investigate whether it is possible to distinguish different types of teaching approaches. Our results indicate the existence of two types. The first type is
A Computationally Based Approach to Homogenizing Advanced Alloys
Jablonski, P D; Cowen, C J
2011-02-27
We have developed a computationally based approach to optimizing the homogenization heat treatment of complex alloys. The Scheil module within the Thermo-Calc software is used to predict the as-cast segregation present within alloys, and DICTRA (Diffusion Controlled TRAnsformations) is used to model the homogenization kinetics as a function of time, temperature and microstructural scale. We will discuss this approach as it is applied to both Ni based superalloys as well as the more complex (computationally) case of alloys that solidify with more than one matrix phase as a result of segregation. Such is the case typically observed in martensitic steels. With these alloys it is doubly important to homogenize them correctly, especially at the laboratory scale, since they are austenitic at high temperature and thus constituent elements will diffuse slowly. The computationally designed heat treatment and the subsequent verification real castings are presented.
Sengupta, Arkajyoti; Ramabhadran, Raghunath O; Raghavachari, Krishnan
2014-08-14
In this study we have used the connectivity-based hierarchy (CBH) method to derive accurate heats of formation of a range of biomolecules, 18 amino acids and 10 barbituric acid/uracil derivatives. The hierarchy is based on the connectivity of the different atoms in a large molecule. It results in error-cancellation reaction schemes that are automated, general, and can be readily used for a broad range of organic molecules and biomolecules. Herein, we first locate stable conformational and tautomeric forms of these biomolecules using an accurate level of theory (viz. CCSD(T)/6-311++G(3df,2p)). Subsequently, the heats of formation of the amino acids are evaluated using the CBH-1 and CBH-2 schemes and routinely employed density functionals or wave function-based methods. The calculated heats of formation obtained herein using modest levels of theory and are in very good agreement with those obtained using more expensive W1-F12 and W2-F12 methods on amino acids and G3 results on barbituric acid derivatives. Overall, the present study (a) highlights the small effect of including multiple conformers in determining the heats of formation of biomolecules and (b) in concurrence with previous CBH studies, proves that use of the more effective error-cancelling isoatomic scheme (CBH-2) results in more accurate heats of formation with modestly sized basis sets along with common density functionals or wave function-based methods.
Computer Forensics for Graduate Accountants: A Motivational Curriculum Design Approach
Grover Kearns
2010-06-01
Full Text Available Computer forensics involves the investigation of digital sources to acquire evidence that can be used in a court of law. It can also be used to identify and respond to threats to hosts and systems. Accountants use computer forensics to investigate computer crime or misuse, theft of trade secrets, theft of or destruction of intellectual property, and fraud. Education of accountants to use forensic tools is a goal of the AICPA (American Institute of Certified Public Accountants. Accounting students, however, may not view information technology as vital to their career paths and need motivation to acquire forensic knowledge and skills. This paper presents a curriculum design methodology for teaching graduate accounting students computer forensics. The methodology is tested using perceptions of the students about the success of the methodology and their acquisition of forensics knowledge and skills. An important component of the pedagogical approach is the use of an annotated list of over 50 forensic web-based tools.
Efficient Approach for Load Balancing in Virtual Cloud Computing Environment
Harvinder singh
2014-10-01
Full Text Available Cloud computing technology is changing the focus of IT world and it is becoming famous because of its great characteristics. Load balancing is one of the main challenges in cloud computing for distributing workloads across multiple computers or a computer cluster, network links, central processing units, disk drives, or other resources. Successful load balancing optimizes resource use, maximizes throughput, minimizes response time, and avoids overload. The objective of this paper to propose an approach for scheduling algorithms that can maintain the load balancing and provides better improved strategies through efficient job scheduling and modified resource allocation techniques. The results discussed in this paper, based on existing round robin, least connection, throttled load balance, fastest response time and a new proposed algorithm fastest with least connection scheduling algorithms. This new algorithm identifies the overall response time and data centre processing time is improved as well as cost is reduced in comparison to the existing scheduling parameters.
EFFICIENT APPROACH FOR LOAD BALANCING IN VIRTUAL CLOUD COMPUTING ENVIRONMENT
Harvinder Singh
2015-10-01
Full Text Available Cloud computing technology is changing the focus of IT world and it is becoming famous because of its great characteristics. Load balancing is one of the main challenges in cloud computing for distributing workloads across multiple computers or a computer cluster, network links, central processing units, disk drives, or other resources. Successful load balancing optimizes resource use, maximizes throughput, minimizes response time, and avoids overload. The objective of this paper to propose an approach for scheduling algorithms that can maintain the load balancing and provides better improved strategies through efficient job scheduling and modified resource allocation techniques. The results discussed in this paper, based on existing round robin, least connection, throttled load balance, fastest response time and a new proposed algorithm fastest with least connection scheduling algorithms. This new algorithm identifies the overall response time and data centre processing time is improved as well as cost is reduced in comparison to the existing scheduling parameters.
A GPU-Computing Approach to Solar Stokes Profile Inversion
Harker, Brian J
2012-01-01
We present a new computational approach to the inversion of solar photospheric Stokes polarization profiles, under the Milne-Eddington model, for vector magnetography. Our code, named GENESIS (GENEtic Stokes Inversion Strategy), employs multi-threaded parallel-processing techniques to harness the computing power of graphics processing units GPUs, along with algorithms designed to exploit the inherent parallelism of the Stokes inversion problem. Using a genetic algorithm (GA) engineered specifically for use with a GPU, we produce full-disc maps of the photospheric vector magnetic field from polarized spectral line observations recorded by the Synoptic Optical Long-term Investigations of the Sun (SOLIS) Vector Spectromagnetograph (VSM) instrument. We show the advantages of pairing a population-parallel genetic algorithm with data-parallel GPU-computing techniques, and present an overview of the Stokes inversion problem, including a description of our adaptation to the GPU-computing paradigm. Full-disc vector ma...
Cloud Computing – A Unified Approach for Surveillance Issues
Rachana, C. R.; Banu, Reshma, Dr.; Ahammed, G. F. Ali, Dr.; Parameshachari, B. D., Dr.
2017-08-01
Cloud computing describes highly scalable resources provided as an external service via the Internet on a basis of pay-per-use. From the economic point of view, the main attractiveness of cloud computing is that users only use what they need, and only pay for what they actually use. Resources are available for access from the cloud at any time, and from any location through networks. Cloud computing is gradually replacing the traditional Information Technology Infrastructure. Securing data is one of the leading concerns and biggest issue for cloud computing. Privacy of information is always a crucial pointespecially when an individual’s personalinformation or sensitive information is beingstored in the organization. It is indeed true that today; cloud authorization systems are notrobust enough. This paper presents a unified approach for analyzing the various security issues and techniques to overcome the challenges in the cloud environment.
Lee, Y. C.; Thompson, H. M.; Gaskell, P. H.
2009-12-01
FILMPAR is a highly efficient and portable parallel multigrid algorithm for solving a discretised form of the lubrication approximation to three-dimensional, gravity-driven, continuous thin film free-surface flow over substrates containing micro-scale topography. While generally applicable to problems involving heterogeneous and distributed features, for illustrative purposes the algorithm is benchmarked on a distributed memory IBM BlueGene/P computing platform for the case of flow over a single trench topography, enabling direct comparison with complementary experimental data and existing serial multigrid solutions. Parallel performance is assessed as a function of the number of processors employed and shown to lead to super-linear behaviour for the production of mesh-independent solutions. In addition, the approach is used to solve for the case of flow over a complex inter-connected topographical feature and a description provided of how FILMPAR could be adapted relatively simply to solve for a wider class of related thin film flow problems. Program summaryProgram title: FILMPAR Catalogue identifier: AEEL_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEEL_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 530 421 No. of bytes in distributed program, including test data, etc.: 1 960 313 Distribution format: tar.gz Programming language: C++ and MPI Computer: Desktop, server Operating system: Unix/Linux Mac OS X Has the code been vectorised or parallelised?: Yes. Tested with up to 128 processors RAM: 512 MBytes Classification: 12 External routines: GNU C/C++, MPI Nature of problem: Thin film flows over functional substrates containing well-defined single and complex topographical features are of enormous significance, having a wide variety of engineering
Cloud computing approaches to accelerate drug discovery value chain.
Garg, Vibhav; Arora, Suchir; Gupta, Chitra
2011-12-01
Continued advancements in the area of technology have helped high throughput screening (HTS) evolve from a linear to parallel approach by performing system level screening. Advanced experimental methods used for HTS at various steps of drug discovery (i.e. target identification, target validation, lead identification and lead validation) can generate data of the order of terabytes. As a consequence, there is pressing need to store, manage, mine and analyze this data to identify informational tags. This need is again posing challenges to computer scientists to offer the matching hardware and software infrastructure, while managing the varying degree of desired computational power. Therefore, the potential of "On-Demand Hardware" and "Software as a Service (SAAS)" delivery mechanisms cannot be denied. This on-demand computing, largely referred to as Cloud Computing, is now transforming the drug discovery research. Also, integration of Cloud computing with parallel computing is certainly expanding its footprint in the life sciences community. The speed, efficiency and cost effectiveness have made cloud computing a 'good to have tool' for researchers, providing them significant flexibility, allowing them to focus on the 'what' of science and not the 'how'. Once reached to its maturity, Discovery-Cloud would fit best to manage drug discovery and clinical development data, generated using advanced HTS techniques, hence supporting the vision of personalized medicine.
Computational intelligence approaches for pattern discovery in biological systems.
Fogel, Gary B
2008-07-01
Biology, chemistry and medicine are faced by tremendous challenges caused by an overwhelming amount of data and the need for rapid interpretation. Computational intelligence (CI) approaches such as artificial neural networks, fuzzy systems and evolutionary computation are being used with increasing frequency to contend with this problem, in light of noise, non-linearity and temporal dynamics in the data. Such methods can be used to develop robust models of processes either on their own or in combination with standard statistical approaches. This is especially true for database mining, where modeling is a key component of scientific understanding. This review provides an introduction to current CI methods, their application to biological problems, and concludes with a commentary about the anticipated impact of these approaches in bioinformatics.
An engineering based approach for hydraulic computations in river flows
Di Francesco, S.; Biscarini, C.; Pierleoni, A.; Manciola, P.
2016-06-01
This paper presents an engineering based approach for hydraulic risk evaluation. The aim of the research is to identify a criteria for the choice of the simplest and appropriate model to use in different scenarios varying the characteristics of main river channel. The complete flow field, generally expressed in terms of pressure, velocities, accelerations can be described through a three dimensional approach that consider all the flow properties varying in all directions. In many practical applications for river flow studies, however, the greatest changes occur only in two dimensions or even only in one. In these cases the use of simplified approaches can lead to accurate results, with easy to build and faster simulations. The study has been conducted taking in account a dimensionless parameter of channels (ratio of curvature radius and width of the channel (R/B).
Neuromolecular computing: a new approach to human brain evolution.
Wallace, R; Price, H
1999-09-01
Evolutionary approaches in human cognitive neurobiology traditionally emphasize macroscopic structures. It may soon be possible to supplement these studies with models of human information-processing of the molecular level. Thin-film, simulation, fluorescence microscopy, and high-resolution X-ray crystallographic studies provide evidence for transiently organized neural membrane molecular systems with possible computational properties. This review article examines evidence for hydrophobic-mismatch molecular interactions within phospholipid microdomains of a neural membrane bilayer. It is proposed that these interactions are a massively parallel algorithm which can rapidly compute near-optimal solutions to complex cognitive and physiological problems. Coupling of microdomain activity to permenant ion movements at ligand-gated and voltage-gated channels permits the conversion of molecular computations into neuron frequency codes. Evidence for microdomain transport of proteins to specific locations within the bilayer suggests that neuromolecular computation may be under some genetic control and thus modifiable by natural selection. A possible experimental approach for examining evolutionary changes in neuromolecular computation is briefly discussed.
Computing 3-D steady supersonic flow via a new Lagrangian approach
Loh, C. Y.; Liou, M.-S.
1993-01-01
The new Lagrangian method introduced by Loh and Hui (1990) is extended for 3-D steady supersonic flow computation. Details of the conservation form, the implementation of the local Riemann solver, and the Godunov and the high resolution TVD schemes are presented. The new approach is robust yet accurate, capable of handling complicated geometry and reactions between discontinuous waves. It keeps all the advantages claimed in the 2-D method of Loh and Hui, e.g., crisp resolution for a slip surface (contact discontinuity) and automatic grid generation along the stream.
Shi, Guangyuan; Li, Song; Huang, Ke; Li, Zile; Zheng, Guoxing
2016-10-01
We have developed a new numerical ray-tracing approach for LIDAR signal power function computation, in which the light round-trip propagation is analyzed by geometrical optics and a simple experiment is employed to acquire the laser intensity distribution. It is relatively more accurate and flexible than previous methods. We emphatically discuss the relationship between the inclined angle and the dynamic range of detector output signal in biaxial LIDAR system. Results indicate that an appropriate negative angle can compress the signal dynamic range. This technique has been successfully proved by comparison with real measurements.
One approach for evaluating the Distributed Computing Design System (DCDS)
Ellis, J. T.
1985-01-01
The Distributed Computer Design System (DCDS) provides an integrated environment to support the life cycle of developing real-time distributed computing systems. The primary focus of DCDS is to significantly increase system reliability and software development productivity, and to minimize schedule and cost risk. DCDS consists of integrated methodologies, languages, and tools to support the life cycle of developing distributed software and systems. Smooth and well-defined transistions from phase to phase, language to language, and tool to tool provide a unique and unified environment. An approach to evaluating DCDS highlights its benefits.
An evolutionary computational approach for the dynamic Stackelberg competition problems
Lorena Arboleda-Castro
2016-06-01
Full Text Available Stackelberg competition models are an important family of economical decision problems from game theory, in which the main goal is to find optimal strategies between two competitors taking into account their hierarchy relationship. Although these models have been widely studied in the past, it is important to note that very few works deal with uncertainty scenarios, especially those that vary over time. In this regard, the present research studies this topic and proposes a computational method for solving efficiently dynamic Stackelberg competition models. The computational experiments suggest that the proposed approach is effective for problems of this nature.
The DYNAMO Simulation Language--An Alternate Approach to Computer Science Education.
Bronson, Richard
1986-01-01
Suggests the use of computer simulation of continuous systems as a problem solving approach to computer languages. Outlines the procedures that the system dynamics approach employs in computer simulations. Explains the advantages of the special purpose language, DYNAMO. (ML)
A computational thermodynamics approach to the Gibbs-Thomson effect
Shahandeh, Sina [Department of Material Science and Engineering, Sharif University of Technology, Tehran (Iran, Islamic Republic of)]. E-mail: sinashahandeh@yahoo.com; Nategh, Said [Department of Material Science and Engineering, Sharif University of Technology, Tehran (Iran, Islamic Republic of)
2007-01-15
In two-phase system, curvature of interface leads to increase of solute concentration in matrix. This effect plays a significant role in solidification, precipitation, nucleation and growth and coarsening. There are number of models and formulas for Gibbs-Thomson effect in binary alloys. In this paper with the help of CALPHAD calculations, new approach for describing this effect in binary and multicomponent systems is proposed. In this generalized method no traditional simplifying assumption are considered and this yield to more accurate result for Gibbs-Thomson phenomenon. This model is compared with previous formulas in some case alloying systems.
Sesé, Luis M
2012-06-28
A systematic study of the direct computation of the isothermal compressibility of normal quantum fluids is presented by analyzing the solving of the Ornstein-Zernike integral (OZ2) equation for the pair correlations between the path-integral necklace centroids. A number of issues related to the accuracy that can be achieved via this sort of procedure have been addressed, paying particular attention to the finite-N effects and to the definition of significant error bars for the estimates of isothermal compressibilities. Extensive path-integral Monte Carlo computations for the quantum hard-sphere fluid (QHS) have been performed in the (N, V, T) ensemble under temperature and density conditions for which dispersion effects dominate the quantum behavior. These computations have served to obtain the centroid correlations, which have been processed further via the numerical solving of the OZ2 equation. To do so, Baxter-Dixon-Hutchinson's variational procedure, complemented with Baumketner-Hiwatari's grand-canonical corrections, has been used. The virial equation of state has also been obtained and several comparisons between different versions of the QHS equation of state have been made. The results show the reliability of the procedure based on isothermal compressibilities discussed herein, which can then be regarded as a useful and quick means of obtaining the equation of state for fluids under quantum conditions involving strong repulsive interactions.
Computational Approach for Multi Performances Optimization of EDM
Yusoff Yusliza
2016-01-01
Full Text Available This paper proposes a new computational approach employed in obtaining optimal parameters of multi performances EDM. Regression and artificial neural network (ANN are used as the modeling techniques meanwhile multi objective genetic algorithm (multiGA is used as the optimization technique. Orthogonal array L256 is implemented in the procedure of network function and network architecture selection. Experimental studies are carried out to verify the machining performances suggested by this approach. The highest MRR value obtained from OrthoANN – MPR – MultiGA is 205.619 mg/min and the lowest Ra value is 0.0223μm.
Computer Mechatronics: A Radical Approach to Mechatronics Education
Nilsson, Martin
2005-01-01
This paper describes some distinguishing features of a course on mechatronics, based on computer science. We propose a teaching approach called Controlled Problem-Based Learning (CPBL). We have applied this method on three generations (2003-2005) of mainly fourth-year undergraduate students at Lund University (LTH). Although students found the course difficult, there were no dropouts, and all students attended the examination 2005.
COMPTEL skymapping: a new approach using parallel computing
Strong, A.W.; Bloemen, H.; Diehl, R.; Hermsen, W.; Schoenfelder, V.
1998-01-01
Large-scale skymapping with COMPTEL using the full survey database presents challenging problems on account of the complex response and time-variable background. A new approach which attempts to address some of these problems is described, in which the information about each observation is preserved throughout the analysis. In this method, a maximum-entropy algorithm is used to determine image and background simultaneously. Because of the extreme computing requirements, the method has been im...
Review: the physiological and computational approaches for atherosclerosis treatment.
Wang, Wuchen; Lee, Yugyung; Lee, Chi H
2013-09-01
The cardiovascular disease has long been an issue that causes severe loss in population, especially those conditions associated with arterial malfunction, being attributable to atherosclerosis and subsequent thrombotic formation. This article reviews the physiological mechanisms that underline the transition from plaque formation in atherosclerotic process to platelet aggregation and eventually thrombosis. The physiological and computational approaches, such as percutaneous coronary intervention and stent design modeling, to detect, evaluate and mitigate this malicious progression were also discussed.
A spline-based approach for computing spatial impulse responses.
Ellis, Michael A; Guenther, Drake; Walker, William F
2007-05-01
Computer simulations are an essential tool for the design of phased-array ultrasonic imaging systems. FIELD II, which determines the two-way temporal response of a transducer at a point in space, is the current de facto standard for ultrasound simulation tools. However, the need often arises to obtain two-way spatial responses at a single point in time, a set of dimensions for which FIELD II is not well optimized. This paper describes an analytical approach for computing the two-way, far-field, spatial impulse response from rectangular transducer elements under arbitrary excitation. The described approach determines the response as the sum of polynomial functions, making computational implementation quite straightforward. The proposed algorithm, named DELFI, was implemented as a C routine under Matlab and results were compared to those obtained under similar conditions from the well-established FIELD II program. Under the specific conditions tested here, the proposed algorithm was approximately 142 times faster than FIELD II for computing spatial sensitivity functions with similar amounts of error. For temporal sensitivity functions with similar amounts of error, the proposed algorithm was about 1.7 times slower than FIELD II using rectangular elements and 19.2 times faster than FIELD II using triangular elements. DELFI is shown to be an attractive complement to FIELD II, especially when spatial responses are needed at a specific point in time.
Archiving Software Systems: Approaches to Preserve Computational Capabilities
King, T. A.
2014-12-01
A great deal of effort is made to preserve scientific data. Not only because data is knowledge, but it is often costly to acquire and is sometimes collected under unique circumstances. Another part of the science enterprise is the development of software to process and analyze the data. Developed software is also a large investment and worthy of preservation. However, the long term preservation of software presents some challenges. Software often requires a specific technology stack to operate. This can include software, operating systems and hardware dependencies. One past approach to preserve computational capabilities is to maintain ancient hardware long past its typical viability. On an archive horizon of 100 years, this is not feasible. Another approach to preserve computational capabilities is to archive source code. While this can preserve details of the implementation and algorithms, it may not be possible to reproduce the technology stack needed to compile and run the resulting applications. This future forward dilemma has a solution. Technology used to create clouds and process big data can also be used to archive and preserve computational capabilities. We explore how basic hardware, virtual machines, containers and appropriate metadata can be used to preserve computational capabilities and to archive functional software systems. In conjunction with data archives, this provides scientist with both the data and capability to reproduce the processing and analysis used to generate past scientific results.
Development of a computationally efficient urban modeling approach
Wolfs, Vincent; Murla, Damian; Ntegeka, Victor;
2016-01-01
This paper presents a parsimonious and data-driven modelling approach to simulate urban floods. Flood levels simulated by detailed 1D-2D hydrodynamic models can be emulated using the presented conceptual modelling approach with a very short calculation time. In addition, the model detail can...... be adjust-ed, allowing the modeller to focus on flood-prone locations. This results in efficiently parameterized models that can be tailored to applications. The simulated flood levels are transformed into flood extent maps using a high resolution (0.5-meter) digital terrain model in GIS. To illustrate...... the developed methodology, a case study for the city of Ghent in Belgium is elaborated. The configured conceptual model mimics the flood levels of a detailed 1D-2D hydrodynamic InfoWorks ICM model accurately, while the calculation time is an order of magnitude of 106 times shorter than the original highly...
Huré, J -M
2016-01-01
We compute the structure of a self-gravitating torus with polytropic equation-of-state (EOS) rotating in an imposed centrifugal potential. The Poisson-solver is based on isotropic multigrid with optimal covering factor (fluid section-to-grid area ratio). We work at $2$nd-order in the grid resolution for both finite difference and quadrature schemes. For soft EOS (i.e. polytropic index $n \\ge 1$), the underlying $2$nd-order is naturally recovered for Boundary Values (BVs) and any other integrated quantity sensitive to the mass density (mass, angular momentum, volume, Virial Parameter, etc.), i.e. errors vary with the number $N$ of nodes per direction as $\\sim 1/N^2$. This is, however, not observed for purely geometrical quantities (surface area, meridional section area, volume), unless a subgrid approach is considered (i.e. boundary detection). Equilibrium sequences are also much better described, especially close to critical rotation. Yet another technical effort is required for hard EOS ($n < 1$), due to ...
Gunaydin, Hakan; Acevedo, Orlando; Jorgensen, William L; Houk, K N
2007-05-01
The energetics of methyl-transfer reactions from dimethylammonium, tetramethylammonium, and trimethylsulfonium to dimethylamine were computed with density functional theory, MP2, CBS-QB3, and quantum mechanics/molecular mechanics (QM/MM) Monte Carlo methods. At the CBS-QB3 level, the gas-phase activation enthalpies are computed to be 9.9, 15.3, and 7.9 kcal/mol, respectively. MP2/6-31+G(d,p) activation enthalpies are in best agreement with the CBS-QB3 results. The effects of aqueous solvation on these reactions were studied with polarizable continuum model, generalized Born/surface area (GB/SA), and QM/MM Monte Carlo simulations utilizing free-energy perturbation theory in which the PDDG/PM3 semiempirical Hamiltonian for the QM and explicit TIP4P water molecules in the MM region were used. In the aqueous phase, all of these reactions proceed more slowly when compared to the gas phase, since the charged reactants are stabilized more than the transition structure geometries with delocalized positive charges. In order to obtain the aqueous-phase activation free energies, the gas-phase activation free energies were corrected with the solvation free energies obtained from single-point conductor-like polarizable continuum model and GB/SA calculations for the stationary points along the reaction coordinate.
Harb, Moussab
2015-08-26
Using accurate first-principles quantum calculations based on DFT (including the perturbation theory DFPT) with the range-separated hybrid HSE06 exchange-correlation functional, we predict essential fundamental properties (such as bandgap, optical absorption coefficient, dielectric constant, charge carrier effective masses and exciton binding energy) of two stable monoclinic vanadium oxynitride (VON) semiconductor crystals for solar energy conversion applications. In addition to the predicted band gaps in the optimal range for making single-junction solar cells, both polymorphs exhibit relatively high absorption efficiencies in the visible range, high dielectric constants, high charge carrier mobilities and much lower exciton binding energies than the thermal energy at room temperature. Moreover, their optical absorption, dielectric and exciton dissociation properties are found to be better than those obtained for semiconductors frequently utilized in photovoltaic devices like Si, CdTe and GaAs. These novel results offer a great opportunity for this stoichiometric VON material to be properly synthesized and considered as a new good candidate for photovoltaic applications.
Probabilistic Damage Characterization Using the Computationally-Efficient Bayesian Approach
Warner, James E.; Hochhalter, Jacob D.
2016-01-01
This work presents a computationally-ecient approach for damage determination that quanti es uncertainty in the provided diagnosis. Given strain sensor data that are polluted with measurement errors, Bayesian inference is used to estimate the location, size, and orientation of damage. This approach uses Bayes' Theorem to combine any prior knowledge an analyst may have about the nature of the damage with information provided implicitly by the strain sensor data to form a posterior probability distribution over possible damage states. The unknown damage parameters are then estimated based on samples drawn numerically from this distribution using a Markov Chain Monte Carlo (MCMC) sampling algorithm. Several modi cations are made to the traditional Bayesian inference approach to provide signi cant computational speedup. First, an ecient surrogate model is constructed using sparse grid interpolation to replace a costly nite element model that must otherwise be evaluated for each sample drawn with MCMC. Next, the standard Bayesian posterior distribution is modi ed using a weighted likelihood formulation, which is shown to improve the convergence of the sampling process. Finally, a robust MCMC algorithm, Delayed Rejection Adaptive Metropolis (DRAM), is adopted to sample the probability distribution more eciently. Numerical examples demonstrate that the proposed framework e ectively provides damage estimates with uncertainty quanti cation and can yield orders of magnitude speedup over standard Bayesian approaches.
Carrington, David Bradley [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Waters, Jiajia [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2017-01-05
KIVA-hpFE is a high performance computer software for solving the physics of multi-species and multiphase turbulent reactive flow in complex geometries having immersed moving parts. The code is written in Fortran 90/95 and can be used on any computer platform with any popular complier. The code is in two versions, a serial version and a parallel version utilizing MPICH2 type Message Passing Interface (MPI or Intel MPI) for solving distributed domains. The parallel version is at least 30x faster than the serial version and much faster than our previous generation of parallel engine modeling software, by many factors. The 5th generation algorithm construction is a Galerkin type Finite Element Method (FEM) solving conservative momentum, species, and energy transport equations along with two-equation turbulent model k-ω Reynolds Averaged Navier-Stokes (RANS) model and a Vreman type dynamic Large Eddy Simulation (LES) method. The LES method is capable modeling transitional flow from laminar to fully turbulent; therefore, this LES method does not require special hybrid or blending to walls. The FEM projection method also uses a Petrov-Galerkin (P-G) stabilization along with pressure stabilization. We employ hierarchical basis sets, constructed on the fly with enrichment in areas associated with relatively larger error as determined by error estimation methods. In addition, when not using the hp-adaptive module, the code employs Lagrangian basis or shape functions. The shape functions are constructed for hexahedral, prismatic and tetrahedral elements. The software is designed to solve many types of reactive flow problems, from burners to internal combustion engines and turbines. In addition, the formulation allows for direct integration of solid bodies (conjugate heat transfer), as in heat transfer through housings, parts, cylinders. It can also easily be extended to stress modeling of solids, used in fluid structure interactions problems, solidification, porous media
Sommer, Kelsey; Izzo, Rick L.; Shepard, Lauren; Podgorsak, Alexander R.; Rudin, Stephen; Siddiqui, Adnan H.; Wilson, Michael F.; Angel, Erin; Said, Zaid; Springer, Michael; Ionita, Ciprian N.
2017-03-01
3D printing has been used to create complex arterial phantoms to advance device testing and physiological condition evaluation. Stereolithographic (STL) files of patient-specific cardiovascular anatomy are acquired to build cardiac vasculature through advanced mesh-manipulation techniques. Management of distal branches in the arterial tree is important to make such phantoms practicable. We investigated methods to manage the distal arterial flow resistance and pressure thus creating physiologically and geometrically accurate phantoms that can be used for simulations of image-guided interventional procedures with new devices. Patient specific CT data were imported into a Vital Imaging workstation, segmented, and exported as STL files. Using a mesh-manipulation program (Meshmixer) we created flow models of the coronary tree. Distal arteries were connected to a compliance chamber. The phantom was then printed using a Stratasys Connex3 multimaterial printer: the vessel in TangoPlus and the fluid flow simulation chamber in Vero. The model was connected to a programmable pump and pressure sensors measured flow characteristics through the phantoms. Physiological flow simulations for patient-specific vasculature were done for six cardiac models (three different vasculatures comparing two new designs). For the coronary phantom we obtained physiologically relevant waves which oscillated between 80 and 120 mmHg and a flow rate of 125 ml/min, within the literature reported values. The pressure wave was similar with those acquired in human patients. Thus we demonstrated that 3D printed phantoms can be used not only to reproduce the correct patient anatomy for device testing in image-guided interventions, but also for physiological simulations. This has great potential to advance treatment assessment and diagnosis.
A Computer Vision Approach to Identify Einstein Rings and Arcs
Lee, Chien-Hsiu
2017-03-01
Einstein rings are rare gems of strong lensing phenomena; the ring images can be used to probe the underlying lens gravitational potential at every position angles, tightly constraining the lens mass profile. In addition, the magnified images also enable us to probe high-z galaxies with enhanced resolution and signal-to-noise ratios. However, only a handful of Einstein rings have been reported, either from serendipitous discoveries or or visual inspections of hundred thousands of massive galaxies or galaxy clusters. In the era of large sky surveys, an automated approach to identify ring pattern in the big data to come is in high demand. Here, we present an Einstein ring recognition approach based on computer vision techniques. The workhorse is the circle Hough transform that recognise circular patterns or arcs in the images. We propose a two-tier approach by first pre-selecting massive galaxies associated with multiple blue objects as possible lens, than use Hough transform to identify circular pattern. As a proof-of-concept, we apply our approach to SDSS, with a high completeness, albeit with low purity. We also apply our approach to other lenses in DES, HSC-SSP, and UltraVISTA survey, illustrating the versatility of our approach.
Computational neuroscience approach to biomarkers and treatments for mental disorders.
Yahata, Noriaki; Kasai, Kiyoto; Kawato, Mitsuo
2017-04-01
Psychiatry research has long experienced a stagnation stemming from a lack of understanding of the neurobiological underpinnings of phenomenologically defined mental disorders. Recently, the application of computational neuroscience to psychiatry research has shown great promise in establishing a link between phenomenological and pathophysiological aspects of mental disorders, thereby recasting current nosology in more biologically meaningful dimensions. In this review, we highlight recent investigations into computational neuroscience that have undertaken either theory- or data-driven approaches to quantitatively delineate the mechanisms of mental disorders. The theory-driven approach, including reinforcement learning models, plays an integrative role in this process by enabling correspondence between behavior and disorder-specific alterations at multiple levels of brain organization, ranging from molecules to cells to circuits. Previous studies have explicated a plethora of defining symptoms of mental disorders, including anhedonia, inattention, and poor executive function. The data-driven approach, on the other hand, is an emerging field in computational neuroscience seeking to identify disorder-specific features among high-dimensional big data. Remarkably, various machine-learning techniques have been applied to neuroimaging data, and the extracted disorder-specific features have been used for automatic case-control classification. For many disorders, the reported accuracies have reached 90% or more. However, we note that rigorous tests on independent cohorts are critically required to translate this research into clinical applications. Finally, we discuss the utility of the disorder-specific features found by the data-driven approach to psychiatric therapies, including neurofeedback. Such developments will allow simultaneous diagnosis and treatment of mental disorders using neuroimaging, thereby establishing 'theranostics' for the first time in clinical
SPINET: A Parallel Computing Approach to Spine Simulations
Peter G. Kropf
1996-01-01
Full Text Available Research in scientitic programming enables us to realize more and more complex applications, and on the other hand, application-driven demands on computing methods and power are continuously growing. Therefore, interdisciplinary approaches become more widely used. The interdisciplinary SPINET project presented in this article applies modern scientific computing tools to biomechanical simulations: parallel computing and symbolic and modern functional programming. The target application is the human spine. Simulations of the spine help us to investigate and better understand the mechanisms of back pain and spinal injury. Two approaches have been used: the first uses the finite element method for high-performance simulations of static biomechanical models, and the second generates a simulation developmenttool for experimenting with different dynamic models. A finite element program for static analysis has been parallelized for the MUSIC machine. To solve the sparse system of linear equations, a conjugate gradient solver (iterative method and a frontal solver (direct method have been implemented. The preprocessor required for the frontal solver is written in the modern functional programming language SML, the solver itself in C, thus exploiting the characteristic advantages of both functional and imperative programming. The speedup analysis of both solvers show very satisfactory results for this irregular problem. A mixed symbolic-numeric environment for rigid body system simulations is presented. It automatically generates C code from a problem specification expressed by the Lagrange formalism using Maple.
Understanding Plant Nitrogen Metabolism through Metabolomics and Computational Approaches
Perrin H. Beatty
2016-10-01
Full Text Available A comprehensive understanding of plant metabolism could provide a direct mechanism for improving nitrogen use efficiency (NUE in crops. One of the major barriers to achieving this outcome is our poor understanding of the complex metabolic networks, physiological factors, and signaling mechanisms that affect NUE in agricultural settings. However, an exciting collection of computational and experimental approaches has begun to elucidate whole-plant nitrogen usage and provides an avenue for connecting nitrogen-related phenotypes to genes. Herein, we describe how metabolomics, computational models of metabolism, and flux balance analysis have been harnessed to advance our understanding of plant nitrogen metabolism. We introduce a model describing the complex flow of nitrogen through crops in a real-world agricultural setting and describe how experimental metabolomics data, such as isotope labeling rates and analyses of nutrient uptake, can be used to refine these models. In summary, the metabolomics/computational approach offers an exciting mechanism for understanding NUE that may ultimately lead to more effective crop management and engineered plants with higher yields.
Dybeck, Eric C; Schieber, Natalie P; Shirts, Michael R
2016-08-09
We examine the free energies of three benzene polymorphs as a function of temperature in the point-charge OPLS-AA and GROMOS54A7 potentials as well as the polarizable AMOEBA09 potential. For this system, using a polarizable Hamiltonian instead of the cheaper point-charge potentials is shown to have a significantly smaller effect on the stability at 250 K than on the lattice energy at 0 K. The benzene I polymorph is found to be the most stable crystal structure in all three potentials examined and at all temperatures examined. For each potential, we report the free energies over a range of temperatures and discuss the added value of using full free energy methods over the minimized lattice energy to determine the relative crystal stability at finite temperatures. The free energies in the polarizable Hamiltonian are efficiently calculated using samples collected in a cheaper point-charge potential. The polarizable free energies are estimated from the point-charge trajectories using Boltzmann reweighting with MBAR. The high configuration-space overlap necessary for efficient Boltzmann reweighting is achieved by designing point-charge potentials with intramolecular parameters matching those in the expensive polarizable Hamiltonian. Finally, we compare the computational cost of this indirect reweighted free energy estimate to the cost of simulating directly in the expensive polarizable Hamiltonian.
Bedogni, Alberto; Fedele, Stefano; Bedogni, Giorgio; Scoletta, Matteo; Favia, Gianfranco; Colella, Giuseppe; Agrillo, Alessandro; Bettini, Giordana; Di Fede, Olga; Oteri, Giacomo; Fusco, Vittorio; Gabriele, Mario; Ottolenghi, Livia; Valsecchi, Stefano; Porter, Stephen; Petruzzi, Massimo; Arduino, Paolo; D'Amato, Salvatore; Ungari, Claudio; Fung Polly, Pok-Lam; Saia, Giorgia; Campisi, Giuseppina
2014-09-01
Management of osteonecrosis of the jaw associated with antiresorptive agents is challenging, and outcomes are unpredictable. The severity of disease is the main guide to management, and can help to predict prognosis. Most available staging systems for osteonecrosis, including the widely-used American Association of Oral and Maxillofacial Surgeons (AAOMS) system, classify severity on the basis of clinical and radiographic findings. However, clinical inspection and radiography are limited in their ability to identify the extent of necrotic bone disease compared with computed tomography (CT). We have organised a large multicentre retrospective study (known as MISSION) to investigate the agreement between the AAOMS staging system and the extent of osteonecrosis of the jaw (focal compared with diffuse involvement of bone) as detected on CT. We studied 799 patients with detailed clinical phenotyping who had CT images taken. Features of diffuse bone disease were identified on CT within all AAOMS stages (20%, 8%, 48%, and 24% of patients in stages 0, 1, 2, and 3, respectively). Of the patients classified as stage 0, 110/192 (57%) had diffuse disease on CT, and about 1 in 3 with CT evidence of diffuse bone disease was misclassified by the AAOMS system as having stages 0 and 1 osteonecrosis. In addition, more than a third of patients with AAOMS stage 2 (142/405, 35%) had focal bone disease on CT. We conclude that the AAOMS staging system does not correctly identify the extent of bony disease in patients with osteonecrosis of the jaw.
Dyar, M. Darby; McCanta, Molly; Breves, Elly; Carey, C. J.; Lanzirotti, Antonio
2016-03-01
Pre-edge features in the K absorption edge of X-ray absorption spectra are commonly used to predict Fe3+ valence state in silicate glasses. However, this study shows that using the entire spectral region from the pre-edge into the extended X-ray absorption fine-structure region provides more accurate results when combined with multivariate analysis techniques. The least absolute shrinkage and selection operator (lasso) regression technique yields %Fe3+ values that are accurate to ±3.6% absolute when the full spectral region is employed. This method can be used across a broad range of glass compositions, is easily automated, and is demonstrated to yield accurate results from different synchrotrons. It will enable future studies involving X-ray mapping of redox gradients on standard thin sections at 1 × 1 μm pixel sizes.
Dyar, M. Darby; McCanta, Molly; Breves, Elly; Carey, C. J.; Lanzirotti, Antonio
2016-03-01
Pre-edge features in the K absorption edge of X-ray absorption spectra are commonly used to predict Fe^{3+} valence state in silicate glasses. However, this study shows that using the entire spectral region from the pre-edge into the extended X-ray absorption fine-structure region provides more accurate results when combined with multivariate analysis techniques. The least absolute shrinkage and selection operator (lasso) regression technique yields %Fe^{3+} values that are accurate to ±3.6% absolute when the full spectral region is employed. This method can be used across a broad range of glass compositions, is easily automated, and is demonstrated to yield accurate results from different synchrotrons. It will enable future studies involving X-ray mapping of redox gradients on standard thin sections at 1 × 1 μm pixel sizes.
Thomas, Peter B. M.; Baltrušaitis, Tadas; Robinson, Peter; Vivian, Anthony J.
2016-01-01
Purpose We validate a video-based method of head posture measurement. Methods The Cambridge Face Tracker uses neural networks (constrained local neural fields) to recognize facial features in video. The relative position of these facial features is used to calculate head posture. First, we assess the accuracy of this approach against videos in three research databases where each frame is tagged with a precisely measured head posture. Second, we compare our method to a commercially available mechanical device, the Cervical Range of Motion device: four subjects each adopted 43 distinct head postures that were measured using both methods. Results The Cambridge Face Tracker achieved confident facial recognition in 92% of the approximately 38,000 frames of video from the three databases. The respective mean error in absolute head posture was 3.34°, 3.86°, and 2.81°, with a median error of 1.97°, 2.16°, and 1.96°. The accuracy decreased with more extreme head posture. Comparing The Cambridge Face Tracker to the Cervical Range of Motion Device gave correlation coefficients of 0.99 (P < 0.0001), 0.96 (P < 0.0001), and 0.99 (P < 0.0001) for yaw, pitch, and roll, respectively. Conclusions The Cambridge Face Tracker performs well under real-world conditions and within the range of normally-encountered head posture. It allows useful quantification of head posture in real time or from precaptured video. Its performance is similar to that of a clinically validated mechanical device. It has significant advantages over other approaches in that subjects do not need to wear any apparatus, and it requires only low cost, easy-to-setup consumer electronics. Translational Relevance Noncontact assessment of head posture allows more complete clinical assessment of patients, and could benefit surgical planning in future. PMID:27730008
Thomas, Peter B M; Baltrušaitis, Tadas; Robinson, Peter; Vivian, Anthony J
2016-09-01
We validate a video-based method of head posture measurement. The Cambridge Face Tracker uses neural networks (constrained local neural fields) to recognize facial features in video. The relative position of these facial features is used to calculate head posture. First, we assess the accuracy of this approach against videos in three research databases where each frame is tagged with a precisely measured head posture. Second, we compare our method to a commercially available mechanical device, the Cervical Range of Motion device: four subjects each adopted 43 distinct head postures that were measured using both methods. The Cambridge Face Tracker achieved confident facial recognition in 92% of the approximately 38,000 frames of video from the three databases. The respective mean error in absolute head posture was 3.34°, 3.86°, and 2.81°, with a median error of 1.97°, 2.16°, and 1.96°. The accuracy decreased with more extreme head posture. Comparing The Cambridge Face Tracker to the Cervical Range of Motion Device gave correlation coefficients of 0.99 (P Cambridge Face Tracker performs well under real-world conditions and within the range of normally-encountered head posture. It allows useful quantification of head posture in real time or from precaptured video. Its performance is similar to that of a clinically validated mechanical device. It has significant advantages over other approaches in that subjects do not need to wear any apparatus, and it requires only low cost, easy-to-setup consumer electronics. Noncontact assessment of head posture allows more complete clinical assessment of patients, and could benefit surgical planning in future.
[Computer work and De Quervain's tenosynovitis: an evidence based approach].
Gigante, M R; Martinotti, I; Cirla, P E
2012-01-01
The debate around the role of the work at personal computer as cause of De Quervain's Tenosynovitis was developed partially, without considering multidisciplinary available data. A systematic review of the literature, using an evidence-based approach, was performed. In disorders associated with the use of VDU, we must distinguish those at the upper limbs and among them those related to an overload. Experimental studies on the occurrence of De Quervain's Tenosynovitis are quite limited, as well as clinically are quite difficult to prove the professional etiology, considering the interference due to other activities of daily living or to the biological susceptibility (i.e. anatomical variability, sex, age, exercise). At present there is no evidence of any connection between De Quervain syndrome and time of use of the personal computer or keyboard, limited evidence of correlation is found with time using a mouse. No data are available regarding the use exclusively or predominantly for personal laptops or mobile "smart phone".
Identifying Pathogenicity Islands in Bacterial Pathogenomics Using Computational Approaches
Dongsheng Che
2014-01-01
Full Text Available High-throughput sequencing technologies have made it possible to study bacteria through analyzing their genome sequences. For instance, comparative genome sequence analyses can reveal the phenomenon such as gene loss, gene gain, or gene exchange in a genome. By analyzing pathogenic bacterial genomes, we can discover that pathogenic genomic regions in many pathogenic bacteria are horizontally transferred from other bacteria, and these regions are also known as pathogenicity islands (PAIs. PAIs have some detectable properties, such as having different genomic signatures than the rest of the host genomes, and containing mobility genes so that they can be integrated into the host genome. In this review, we will discuss various pathogenicity island-associated features and current computational approaches for the identification of PAIs. Existing pathogenicity island databases and related computational resources will also be discussed, so that researchers may find it to be useful for the studies of bacterial evolution and pathogenicity mechanisms.
Benchmarking of computer codes and approaches for modeling exposure scenarios
Seitz, R.R. [EG and G Idaho, Inc., Idaho Falls, ID (United States); Rittmann, P.D.; Wood, M.I. [Westinghouse Hanford Co., Richland, WA (United States); Cook, J.R. [Westinghouse Savannah River Co., Aiken, SC (United States)
1994-08-01
The US Department of Energy Headquarters established a performance assessment task team (PATT) to integrate the activities of DOE sites that are preparing performance assessments for the disposal of newly generated low-level waste. The PATT chartered a subteam with the task of comparing computer codes and exposure scenarios used for dose calculations in performance assessments. This report documents the efforts of the subteam. Computer codes considered in the comparison include GENII, PATHRAE-EPA, MICROSHIELD, and ISOSHLD. Calculations were also conducted using spreadsheets to provide a comparison at the most fundamental level. Calculations and modeling approaches are compared for unit radionuclide concentrations in water and soil for the ingestion, inhalation, and external dose pathways. Over 30 tables comparing inputs and results are provided.
Computational approaches for rational design of proteins with novel functionalities
Manish Kumar Tiwari
2012-09-01
Full Text Available Proteins are the most multifaceted macromolecules in living systems and have various important functions, including structural, catalytic, sensory, and regulatory functions. Rational design of enzymes is a great challenge to our understanding of protein structure and physical chemistry and has numerous potential applications. Protein design algorithms have been applied to design or engineer proteins that fold, fold faster, catalyze, catalyze faster, signal, and adopt preferred conformational states. The field of de novo protein design, although only a few decades old, is beginning to produce exciting results. Developments in this field are already having a significant impact on biotechnology and chemical biology. The application of powerful computational methods for functional protein designing has recently succeeded at engineering target activities. Here, we review recently reported de novo functional proteins that were developed using various protein design approaches, including rational design, computational optimization, and selection from combinatorial libraries, highlighting recent advances and successes.
Computational approaches for rational design of proteins with novel functionalities.
Tiwari, Manish Kumar; Singh, Ranjitha; Singh, Raushan Kumar; Kim, In-Won; Lee, Jung-Kul
2012-01-01
Proteins are the most multifaceted macromolecules in living systems and have various important functions, including structural, catalytic, sensory, and regulatory functions. Rational design of enzymes is a great challenge to our understanding of protein structure and physical chemistry and has numerous potential applications. Protein design algorithms have been applied to design or engineer proteins that fold, fold faster, catalyze, catalyze faster, signal, and adopt preferred conformational states. The field of de novo protein design, although only a few decades old, is beginning to produce exciting results. Developments in this field are already having a significant impact on biotechnology and chemical biology. The application of powerful computational methods for functional protein designing has recently succeeded at engineering target activities. Here, we review recently reported de novo functional proteins that were developed using various protein design approaches, including rational design, computational optimization, and selection from combinatorial libraries, highlighting recent advances and successes.
Anjuli A Shah; Nisha I Sainani; Avinash Kambadakone Ramesh; Zarine K Shah; Vikram Deshpande; Peter F Hahn; Dushyant V Sahani
2009-01-01
AIM:To identify multi-detector computed tomography (MDCT) features mos t predi c t i ve of serous cystadenomas (SCAs),correlating with histopathology,and to study the impact of cyst size and MDCT technique on reader performance.METHODS:The MDCT scans of 164 patients with surgically verified pancreatic cystic lesions were reviewed by two readers to study the predictive value of various morphological features for establishing a diagnosis of SCAs.Accuracy in lesion characterization and reader confidence were correlated with lesion size (≤3 cm or ≥3 cm) and scanning protocols (dedicated vs routine).RESULTS:28/164 cysts (mean size,39 mm;range,8-92 mm) were diagnosed as SCA on pathology.The MDCT features predictive of diagnosis of SCA were microcystic appearance (22/28,78.6%),surface lobulations (25/28,89.3%) and central scar (9/28,32.4%).Stepwise logistic regression analysis showed that only microcystic appearance was significant for CT diagnosis of SCA (P=0.0001).The sensitivity,specificity and PPV of central scar and of combined microcystic appearance and lobulations were 32.4%/100%/100% and 68%/100%/100%,respectively.The reader confidence was higher for lesions>3 cm (P=0.02) and for MDCT scans performed using thin collimation (1.25-2.5 mm) compared to routine 5 mm collimation exams (P>0.05).CONCLUSION:Central scar on MDCT is diagnostic of SCA but is seen in only one third of SCAs.Microcystic morphology is the most significant CT feature in diagnosis of SCA.A combination of microcystic appearance and surface lobulations offers accuracy comparable to central scar with higher sensitivity.
Computational systems biology approaches to anti-angiogenic cancer therapeutics.
Finley, Stacey D; Chu, Liang-Hui; Popel, Aleksander S
2015-02-01
Angiogenesis is an exquisitely regulated process that is required for physiological processes and is also important in numerous diseases. Tumors utilize angiogenesis to generate the vascular network needed to supply the cancer cells with nutrients and oxygen, and many cancer drugs aim to inhibit tumor angiogenesis. Anti-angiogenic therapy involves inhibiting multiple cell types, molecular targets, and intracellular signaling pathways. Computational tools are useful in guiding treatment strategies, predicting the response to treatment, and identifying new targets of interest. Here, we describe progress that has been made in applying mathematical modeling and bioinformatics approaches to study anti-angiogenic therapeutics in cancer.
Approaches to Computer Modeling of Phosphate Hide-Out.
1984-06-28
phosphate acts as a buffer to keep pH at a value above which acid corrosion occurs . and below which caustic corrosion becomes significant. Difficulties are...ionization of dihydrogen phosphate : HIPO - + + 1PO, K (B-7) H+ + - £Iao 1/1, (B-8) H , PO4 - + O- - H0 4 + H20 K/Kw (0-9) 19 * Such zero heat...OF STANDARDS-1963-A +. .0 0 0 9t~ - 4 NRL Memorandum Report 5361 4 Approaches to Computer Modeling of Phosphate Hide-Out K. A. S. HARDY AND J. C
A Dynamic Bayesian Approach to Computational Laban Shape Quality Analysis
Dilip Swaminathan
2009-01-01
kinesiology. LMA (especially Effort/Shape emphasizes how internal feelings and intentions govern the patterning of movement throughout the whole body. As we argue, a complex understanding of intention via LMA is necessary for human-computer interaction to become embodied in ways that resemble interaction in the physical world. We thus introduce a novel, flexible Bayesian fusion approach for identifying LMA Shape qualities from raw motion capture data in real time. The method uses a dynamic Bayesian network (DBN to fuse movement features across the body and across time and as we discuss can be readily adapted for low-cost video. It has delivered excellent performance in preliminary studies comprising improvisatory movements. Our approach has been incorporated in Response, a mixed-reality environment where users interact via natural, full-body human movement and enhance their bodily-kinesthetic awareness through immersive sound and light feedback, with applications to kinesiology training, Parkinson's patient rehabilitation, interactive dance, and many other areas.
Exploiting Self-organization in Bioengineered Systems: A Computational Approach.
Davis, Delin; Doloman, Anna; Podgorski, Gregory J; Vargis, Elizabeth; Flann, Nicholas S
2017-01-01
The productivity of bioengineered cell factories is limited by inefficiencies in nutrient delivery and waste and product removal. Current solution approaches explore changes in the physical configurations of the bioreactors. This work investigates the possibilities of exploiting self-organizing vascular networks to support producer cells within the factory. A computational model simulates de novo vascular development of endothelial-like cells and the resultant network functioning to deliver nutrients and extract product and waste from the cell culture. Microbial factories with vascular networks are evaluated for their scalability, robustness, and productivity compared to the cell factories without a vascular network. Initial studies demonstrate that at least an order of magnitude increase in production is possible, the system can be scaled up, and the self-organization of an efficient vascular network is robust. The work suggests that bioengineered multicellularity may offer efficiency improvements difficult to achieve with physical engineering approaches.
Stochastic Computational Approach for Complex Nonlinear Ordinary Differential Equations
Junaid Ali Khan; Muhammad Asif Zahoor Raja; Ijaz Mansoor Qureshi
2011-01-01
@@ We present an evolutionary computational approach for the solution of nonlinear ordinary differential equations (NLODEs).The mathematical modeling is performed by a feed-forward artificial neural network that defines an unsupervised error.The training of these networks is achieved by a hybrid intelligent algorithm, a combination of global search with genetic algorithm and local search by pattern search technique.The applicability of this approach ranges from single order NLODEs, to systems of coupled differential equations.We illustrate the method by solving a variety of model problems and present comparisons with solutions obtained by exact methods and classical numerical methods.The solution is provided on a continuous finite time interval unlike the other numerical techniques with comparable accuracy.With the advent of neuroprocessors and digital signal processors the method becomes particularly interesting due to the expected essential gains in the execution speed.%We present an evolutionary computational approach for the solution of nonlinear ordinary differential equations (NLODEs). The mathematical modeling is performed by a feed-forward artificial neural network that defines an unsupervised error. The training of these networks is achieved by a hybrid intelligent algorithm, a combination of global search with genetic algorithm and local search by pattern search technique. The applicability of this approach ranges from single order NLODEs, to systems of coupled differential equations. We illustrate the method by solving a variety of model problems and present comparisons with solutions obtained by exact methods and classical numerical methods. The solution is provided on a continuous finite time interval unlike the other numerical techniques with comparable accuracy. With the advent of neuroprocessors and digital signal processors the method becomes particularly interesting due to the expected essential gains in the execution speed.
A new approach in CHP steam turbines thermodynamic cycles computations
Grković Vojin R.
2012-01-01
Full Text Available This paper presents a new approach in mathematical modeling of thermodynamic cycles and electric power of utility district-heating and cogeneration steam turbines. The approach is based on the application of the dimensionless mass flows, which describe the thermodynamic cycle of a combined heat and power steam turbine. The mass flows are calculated relative to the mass flow to low pressure turbine. The procedure introduces the extraction mass flow load parameter νh which clearly indicates the energy transformation process, as well as the cogeneration turbine design features, but also its fitness for the electrical energy system requirements. The presented approach allows fast computations, as well as direct calculation of the selected energy efficiency indicators. The approach is exemplified with the calculation results of the district heat power to electric power ratio, as well as the cycle efficiency, versus νh. The influence of νh on the conformity of a combined heat and power turbine to the grid requirements is also analyzed and discussed. [Projekat Ministarstva nauke Republike Srbije, br. 33049: Development of CHP demonstration plant with gasification of biomass
An Approach for Location privacy in Pervasive Computing Environment
Sudheer Kumar Singh
2010-05-01
Full Text Available This paper focus on location privacy in location based services, Location privacy is a particular type of information privacy that can be defined as the ability to prevent others from learning one’s current or past location. Many systems such as GPS implicitly and automatically give its users location privacy. Once user sends his or her current location to the application server, Application server stores current locations of users in application server database. User can not delete or modify his or her location data after sending once to application server. Addressing this problem, Here in this paper, we are giving theoretical concept for protecting location privacy in pervasive computing environment. This approach based on user anonymity based location privacy. Going through the basic user anonymity based a location privacy approach that uses trusted proxy. By analysis of this approach, we propose an improvement over it using dummy-locations of users and also dummies of requested services by users from the application server. In this paper, this approach reduces the user’s overheads to extracting necessary information from reply message coming from application server. In this approach, user send a message having (current location and ID+ requested service to the trusted proxy and trusted proxy generates dummies location related to current location and also generates temporary pseudonym corresponding to real ID of users. After Analysis of this approach wehave found on problem with requested service. Addressing this problem, we improve our method by using dummies of requested service generated by trusted proxy. Trusted proxy generated Dummies (false position by dummies location algorithms.
Genetic braid optimization: A heuristic approach to compute quasiparticle braids
McDonald, Ross B.; Katzgraber, Helmut G.
2013-02-01
In topologically protected quantum computation, quantum gates can be carried out by adiabatically braiding two-dimensional quasiparticles, reminiscent of entangled world lines. Bonesteel [Phys. Rev. Lett.10.1103/PhysRevLett.95.140503 95, 140503 (2005)], as well as Leijnse and Flensberg [Phys. Rev. B10.1103/PhysRevB.86.104511 86, 104511 (2012)], recently provided schemes for computing quantum gates from quasiparticle braids. Mathematically, the problem of executing a gate becomes that of finding a product of the generators (matrices) in that set that approximates the gate best, up to an error. To date, efficient methods to compute these gates only strive to optimize for accuracy. We explore the possibility of using a generic approach applicable to a variety of braiding problems based on evolutionary (genetic) algorithms. The method efficiently finds optimal braids while allowing the user to optimize for the relative utilities of accuracy and/or length. Furthermore, when optimizing for error only, the method can quickly produce efficient braids.
Novel computational approaches for the analysis of cosmic magnetic fields
Saveliev, Andrey [Universitaet Hamburg, Hamburg (Germany); Keldysh Institut, Moskau (Russian Federation)
2016-07-01
In order to give a consistent picture of cosmic, i.e. galactic and extragalactic, magnetic fields, different approaches are possible and often even necessary. Here we present three of them: First, a semianalytic analysis of the time evolution of primordial magnetic fields from which their properties and, subsequently, the nature of present-day intergalactic magnetic fields may be deduced. Second, the use of high-performance computing infrastructure by developing powerful algorithms for (magneto-)hydrodynamic simulations and applying them to astrophysical problems. We are currently developing a code which applies kinetic schemes in massive parallel computing on high performance multiprocessor systems in a new way to calculate both hydro- and electrodynamic quantities. Finally, as a third approach, astroparticle physics might be used as magnetic fields leave imprints of their properties on charged particles transversing them. Here we focus on electromagnetic cascades by developing a software based on CRPropa which simulates the propagation of particles from such cascades through the intergalactic medium in three dimensions. This may in particular be used to obtain information about the helicity of extragalactic magnetic fields.
Computational approaches to understand cardiac electrophysiology and arrhythmias
Roberts, Byron N.; Yang, Pei-Chi; Behrens, Steven B.; Moreno, Jonathan D.
2012-01-01
Cardiac rhythms arise from electrical activity generated by precisely timed opening and closing of ion channels in individual cardiac myocytes. These impulses spread throughout the cardiac muscle to manifest as electrical waves in the whole heart. Regularity of electrical waves is critically important since they signal the heart muscle to contract, driving the primary function of the heart to act as a pump and deliver blood to the brain and vital organs. When electrical activity goes awry during a cardiac arrhythmia, the pump does not function, the brain does not receive oxygenated blood, and death ensues. For more than 50 years, mathematically based models of cardiac electrical activity have been used to improve understanding of basic mechanisms of normal and abnormal cardiac electrical function. Computer-based modeling approaches to understand cardiac activity are uniquely helpful because they allow for distillation of complex emergent behaviors into the key contributing components underlying them. Here we review the latest advances and novel concepts in the field as they relate to understanding the complex interplay between electrical, mechanical, structural, and genetic mechanisms during arrhythmia development at the level of ion channels, cells, and tissues. We also discuss the latest computational approaches to guiding arrhythmia therapy. PMID:22886409
Computational Approach to Dendritic Spine Taxonomy and Shape Transition Analysis
Bokota, Grzegorz; Magnowska, Marta; Kuśmierczyk, Tomasz; Łukasik, Michał; Roszkowska, Matylda; Plewczynski, Dariusz
2016-01-01
The common approach in morphological analysis of dendritic spines of mammalian neuronal cells is to categorize spines into subpopulations based on whether they are stubby, mushroom, thin, or filopodia shaped. The corresponding cellular models of synaptic plasticity, long-term potentiation, and long-term depression associate the synaptic strength with either spine enlargement or spine shrinkage. Although a variety of automatic spine segmentation and feature extraction methods were developed recently, no approaches allowing for an automatic and unbiased distinction between dendritic spine subpopulations and detailed computational models of spine behavior exist. We propose an automatic and statistically based method for the unsupervised construction of spine shape taxonomy based on arbitrary features. The taxonomy is then utilized in the newly introduced computational model of behavior, which relies on transitions between shapes. Models of different populations are compared using supplied bootstrap-based statistical tests. We compared two populations of spines at two time points. The first population was stimulated with long-term potentiation, and the other in the resting state was used as a control. The comparison of shape transition characteristics allowed us to identify the differences between population behaviors. Although some extreme changes were observed in the stimulated population, statistically significant differences were found only when whole models were compared. The source code of our software is freely available for non-commercial use1. Contact: d.plewczynski@cent.uw.edu.pl. PMID:28066226
Computing Optimal Stochastic Portfolio Execution Strategies: A Parametric Approach Using Simulations
Moazeni, Somayeh; Coleman, Thomas F.; Li, Yuying
2010-09-01
Computing optimal stochastic portfolio execution strategies under appropriate risk consideration presents great computational challenge. We investigate a parametric approach for computing optimal stochastic strategies using Monte Carlo simulations. This approach allows reduction in computational complexity by computing coefficients for a parametric representation of a stochastic dynamic strategy based on static optimization. Using this technique, constraints can be similarly handled using appropriate penalty functions. We illustrate the proposed approach to minimize the expected execution cost and Conditional Value-at-Risk (CVaR).
Soft computing approach for modeling power plant with a once-through boiler
Ghaffari, Ali; Chaibakhsh, Ali [Department of Mechanical Engineering, K.N. Toosi University of Technology, P.O. Box 16765-3381, Tehran, (Iran); Lucas, Caro [Department of Electrical and Computer Engineering, University of Tehran, P.O. Box 14318, Tehran, (Iran)
2007-09-15
In this paper, a soft computing approach is presented for modeling electrical power generating plants in order to characterize the essential dynamic behavior of the plant subsystems. The structure of the soft computing method consists of fuzzy logic, neural networks and genetic algorithms. The measured data from a complete set of field experiments is the basis for training the models including the extraction of linguistic rules and membership functions as well as adjusting the other parameters of the fuzzy model. The genetic algorithm is applied to the modeling approach in order to optimize the procedure of the training. Comparison between the responses of the proposed models with the responses of the plants validates the accuracy and performance of the modeling approach. A similar comparison between the responses of these models with the models obtained based on the thermodynamical and physical relations of the plant shows the effectiveness and feasibility of the developed model in terms of more accurate and less deviation between the responses of the models and the corresponding subsystems. (Author)
Itu, Lucian; Rapaka, Saikiran; Passerini, Tiziano; Georgescu, Bogdan; Schwemmer, Chris; Schoebinger, Max; Flohr, Thomas; Sharma, Puneet; Comaniciu, Dorin
2016-07-01
Fractional flow reserve (FFR) is a functional index quantifying the severity of coronary artery lesions and is clinically obtained using an invasive, catheter-based measurement. Recently, physics-based models have shown great promise in being able to noninvasively estimate FFR from patient-specific anatomical information, e.g., obtained from computed tomography scans of the heart and the coronary arteries. However, these models have high computational demand, limiting their clinical adoption. In this paper, we present a machine-learning-based model for predicting FFR as an alternative to physics-based approaches. The model is trained on a large database of synthetically generated coronary anatomies, where the target values are computed using the physics-based model. The trained model predicts FFR at each point along the centerline of the coronary tree, and its performance was assessed by comparing the predictions against physics-based computations and against invasively measured FFR for 87 patients and 125 lesions in total. Correlation between machine-learning and physics-based predictions was excellent (0.9994, P machine-learning algorithm with a sensitivity of 81.6%, a specificity of 83.9%, and an accuracy of 83.2%. The correlation was 0.729 (P machine-learning model on a workstation with 3.4-GHz Intel i7 8-core processor. Copyright © 2016 the American Physiological Society.
a Holistic Approach for Inspection of Civil Infrastructures Based on Computer Vision Techniques
Stentoumis, C.; Protopapadakis, E.; Doulamis, A.; Doulamis, N.
2016-06-01
In this work, it is examined the 2D recognition and 3D modelling of concrete tunnel cracks, through visual cues. At the time being, the structural integrity inspection of large-scale infrastructures is mainly performed through visual observations by human inspectors, who identify structural defects, rate them and, then, categorize their severity. The described approach targets at minimum human intervention, for autonomous inspection of civil infrastructures. The shortfalls of existing approaches in crack assessment are being addressed by proposing a novel detection scheme. Although efforts have been made in the field, synergies among proposed techniques are still missing. The holistic approach of this paper exploits the state of the art techniques of pattern recognition and stereo-matching, in order to build accurate 3D crack models. The innovation lies in the hybrid approach for the CNN detector initialization, and the use of the modified census transformation for stereo matching along with a binary fusion of two state-of-the-art optimization schemes. The described approach manages to deal with images of harsh radiometry, along with severe radiometric differences in the stereo pair. The effectiveness of this workflow is evaluated on a real dataset gathered in highway and railway tunnels. What is promising is that the computer vision workflow described in this work can be transferred, with adaptations of course, to other infrastructure such as pipelines, bridges and large industrial facilities that are in the need of continuous state assessment during their operational life cycle.
Computational approaches for microalgal biofuel optimization: a review.
Koussa, Joseph; Chaiboonchoe, Amphun; Salehi-Ashtiani, Kourosh
2014-01-01
The increased demand and consumption of fossil fuels have raised interest in finding renewable energy sources throughout the globe. Much focus has been placed on optimizing microorganisms and primarily microalgae, to efficiently produce compounds that can substitute for fossil fuels. However, the path to achieving economic feasibility is likely to require strain optimization through using available tools and technologies in the fields of systems and synthetic biology. Such approaches invoke a deep understanding of the metabolic networks of the organisms and their genomic and proteomic profiles. The advent of next generation sequencing and other high throughput methods has led to a major increase in availability of biological data. Integration of such disparate data can help define the emergent metabolic system properties, which is of crucial importance in addressing biofuel production optimization. Herein, we review major computational tools and approaches developed and used in order to potentially identify target genes, pathways, and reactions of particular interest to biofuel production in algae. As the use of these tools and approaches has not been fully implemented in algal biofuel research, the aim of this review is to highlight the potential utility of these resources toward their future implementation in algal research.
Computational Approaches for Microalgal Biofuel Optimization: A Review
Joseph Koussa
2014-01-01
Full Text Available The increased demand and consumption of fossil fuels have raised interest in finding renewable energy sources throughout the globe. Much focus has been placed on optimizing microorganisms and primarily microalgae, to efficiently produce compounds that can substitute for fossil fuels. However, the path to achieving economic feasibility is likely to require strain optimization through using available tools and technologies in the fields of systems and synthetic biology. Such approaches invoke a deep understanding of the metabolic networks of the organisms and their genomic and proteomic profiles. The advent of next generation sequencing and other high throughput methods has led to a major increase in availability of biological data. Integration of such disparate data can help define the emergent metabolic system properties, which is of crucial importance in addressing biofuel production optimization. Herein, we review major computational tools and approaches developed and used in order to potentially identify target genes, pathways, and reactions of particular interest to biofuel production in algae. As the use of these tools and approaches has not been fully implemented in algal biofuel research, the aim of this review is to highlight the potential utility of these resources toward their future implementation in algal research.
A Novel Approach of Load Balancing in Cloud Computing using Computational Intelligence
Shabnam Sharma
2016-02-01
Full Text Available Nature Inspired Meta-Heuristic algorithms are proved to be beneficial for solving real world combinatorial problems such as minimum spanning tree, knapsack problem, process planning problems, load balancing and many more. In this research work, existing meta-heuristic approaches are discussed. Due to astonishing feature of echolocation, bat algorithm has drawn major attention in recent years and is applicable in different applications such vehicle routing optimization, time-tabling in railway optimization problems, load balancing in cloud computing etc. Later, the biological behaviour of bats is explored and various areas of further research are discussed. Finally, the main objective of the research paper is to propose an algorithm for one of the most important application, which is load balancing in cloud computing environment.
Kostoglou, K.; Hadjipapas, A.; Lowet, E.; Roberts, M.; de Weerd, P.; Mitsis, G.D.
2014-01-01
Aims: The relationship between collective population activity (LFP) and spikes underpins network computation, yet it remains poorly understood. Previous studies utilized pre-defined LFP features to predict spiking from simultaneously recorded LFP, and have reported good prediction of spike bursts bu
Suggested Approaches to the Measurement of Computer Anxiety.
Toris, Carol
Psychologists can gain insight into human behavior by examining what people feel about, know about, and do with, computers. Two extreme reactions to computers are computer phobia, or anxiety, and computer addiction, or "hacking". A four-part questionnaire was developed to measure computer anxiety. The first part is a projective technique which…
Coen Pramono D
2005-03-01
Full Text Available Functional and aesthetic dysgnathia surgery requires accurate pre-surgical planning, including the surgical technique to be used related with the difference of anatomical structures amongst individuals. Programs that simulate the surgery become increasingly important. This can be mediated by using a surgical model, conventional x-rays as panoramic, cephalometric projections and another sophisticated method such as a three dimensional computed tomography (3 D-CT. A patient who had undergone double jaw surgeries with difficult anatomical landmarks was presented. In this case the mandible foramens were seen highly relatively related to the sigmoid notches. Therefore, ensuring the bone incisions in sagittal split was presumed to be difficult. A 3D-CT was made and considered to be very helpful in supporting the pre-operative diagnostic.
Palmquist, Anders; Shah, Furqan A; Emanuelsson, Lena; Omar, Omar; Suska, Felicia
2017-03-01
This paper investigates the application of X-ray micro-computed tomography (micro-CT) to accurately evaluate bone formation within 3D printed, porous Ti6Al4V implants manufactured using Electron Beam Melting (EBM), retrieved after six months of healing in sheep femur and tibia. All samples were scanned twice (i.e., before and after resin embedding), using fast, low-resolution scans (Skyscan 1172; Bruker micro-CT, Kontich, Belgium), and were analysed by 2D and 3D morphometry. The main questions posed were: (i) Can low resolution, fast scans provide morphometric data of bone formed inside (and around) metal implants with a complex, open-pore architecture?, (ii) Can micro-CT be used to accurately quantify both the bone area (BA) and bone-implant contact (BIC)?, (iii) What degree of error is introduced in the quantitative data by varying the threshold values?, and (iv) Does resin embedding influence the accuracy of the analysis? To validate the accuracy of micro-CT measurements, each data set was correlated with a corresponding centrally cut histological section. The results show that quantitative histomorphometry corresponds strongly with 3D measurements made by micro-CT, where a high correlation exists between the two techniques for bone area/volume measurements around and inside the porous network. On the contrary, the direct bone-implant contact is challenging to estimate accurately or reproducibly. Large errors may be introduced in micro-CT measurements when segmentation is performed without calibrating the data set against a corresponding histological section. Generally, the bone area measurement is strongly influenced by the lower threshold limit, while the upper threshold limit has little or no effect. Resin embedding does not compromise the accuracy of micro-CT measurements, although there is a change in the contrast distributions and optimisation of the threshold ranges is required. Copyright © 2016 Elsevier Ltd. All rights reserved.
A T Borojeni, Azadeh; Frank-Ito, Dennis O; Kimbell, Julia S; Rhee, John S; Garcia, Guilherme J M
2017-05-01
Virtual surgery planning based on computational fluid dynamics (CFD) simulations has the potential to improve surgical outcomes for nasal airway obstruction patients, but the benefits of virtual surgery planning must outweigh the risks of radiation exposure. Cone beam computed tomography (CT) scans represent an attractive imaging modality for virtual surgery planning due to lower costs and lower radiation exposures compared with conventional CT scans. However, to minimize the radiation exposure, the cone beam CT sinusitis protocol sometimes images only the nasal cavity, excluding the nasopharynx. The goal of this study was to develop an idealized nasopharynx geometry for accurate representation of outlet boundary conditions when the nasopharynx geometry is unavailable. Anatomically accurate models of the nasopharynx created from 30 CT scans were intersected with planes rotated at different angles to obtain an average geometry. Cross sections of the idealized nasopharynx were approximated as ellipses with cross-sectional areas and aspect ratios equal to the average in the actual patient-specific models. CFD simulations were performed to investigate whether nasal airflow patterns were affected when the CT-based nasopharynx was replaced by the idealized nasopharynx in 10 nasal airway obstruction patients. Despite the simple form of the idealized geometry, all biophysical variables (nasal resistance, airflow rate, and heat fluxes) were very similar in the idealized vs patient-specific models. The results confirmed the expectation that the nasopharynx geometry has a minimal effect in the nasal airflow patterns during inspiration. The idealized nasopharynx geometry will be useful in future CFD studies of nasal airflow based on medical images that exclude the nasopharynx. Copyright © 2016 John Wiley & Sons, Ltd.
Computer Aided Interpretation Approach for Optical Tomographic Images
Klose, Christian D; Netz, Uwe; Beuthan, Juergen; Hielscher, Andreas H
2010-01-01
A computer-aided interpretation approach is proposed to detect rheumatic arthritis (RA) of human finger joints in optical tomographic images. The image interpretation method employs a multi-variate signal detection analysis aided by a machine learning classification algorithm, called Self-Organizing Mapping (SOM). Unlike in previous studies, this allows for combining multiple physical image parameters, such as minimum and maximum values of the absorption coefficient for identifying affected and not affected joints. Classification performances obtained by the proposed method were evaluated in terms of sensitivity, specificity, Youden index, and mutual information. Different methods (i.e., clinical diagnostics, ultrasound imaging, magnet resonance imaging and inspection of optical tomographic images), were used as "ground truth"-benchmarks to determine the performance of image interpretations. Using data from 100 finger joints, findings suggest that some parameter combinations lead to higher sensitivities while...
Local-basis-function approach to computed tomography
Hanson, K. M.; Wecksung, G. W.
1985-12-01
In the local basis-function approach, a reconstruction is represented as a linear expansion of basis functions, which are arranged on a rectangular grid and possess a local region of support. The basis functions considered here are positive and may overlap. It is found that basis functions based on cubic B-splines offer significant improvements in the calculational accuracy that can be achieved with iterative tomographic reconstruction algorithms. By employing repetitive basis functions, the computational effort involved in these algorithms can be minimized through the use of tabulated values for the line or strip integrals over a single-basis function. The local nature of the basis functions reduces the difficulties associated with applying local constraints on reconstruction values, such as upper and lower limits. Since a reconstruction is specified everywhere by a set of coefficients, display of a coarsely represented image does not require an arbitrary choice of an interpolation function.
Computational Approaches for Probing the Formation of Atmospheric Molecular Clusters
Elm, Jonas
the performance of computational strategies in order to identify a sturdy methodology, which should be applicable for handling various issues related to atmospheric cluster formation. Density functional theory (DFT) is applied to study individual cluster formation steps. Utilizing large test sets of numerous...... atmospheric clusters I evaluate the performance of different DFT functionals, with a specific focus on how to control potential errors associated with the calculation of single point energies and evaluation of the thermal contribution to the Gibbs free energy. Using DFT I study two candidate systems (glycine...... acid could thereby enhance the further growth of an existing cluster by condensing on the surface. Conclusively, I find that the performance of a single DFT functional can lead to an inadequate description of investigated atmospheric systems and thereby recommend a joint DFT (J-DFT) approach...
A computational approach to mechanistic and predictive toxicology of pesticides
Kongsbak, Kristine Grønning; Vinggaard, Anne Marie; Hadrup, Niels
2014-01-01
Emerging challenges of managing and interpreting large amounts of complex biological data have given rise to the growing field of computational biology. We investigated the applicability of an integrated systems toxicology approach on five selected pesticides to get an overview of their modes...... of action in humans, to group them according to their modes of action, and to hypothesize on their potential effects on human health. We extracted human proteins associated to prochloraz, tebuconazole, epoxiconazole, procymidone, and mancozeb and enriched each protein set by using a high confidence human...... protein interactome. Then, we explored modes of action of the chemicals, by integrating protein-disease information to the resulting protein networks. The dominating human adverse effects affected were reproductive disorders followed by adrenal diseases. Our results indicated that prochloraz, tebuconazole...
Computational approaches to substrate-based cell motility
Ziebert, Falko; Aranson, Igor S.
2016-07-01
Substrate-based crawling motility of eukaryotic cells is essential for many biological functions, both in developing and mature organisms. Motility dysfunctions are involved in several life-threatening pathologies such as cancer and metastasis. Motile cells are also a natural realisation of active, self-propelled 'particles', a popular research topic in nonequilibrium physics. Finally, from the materials perspective, assemblies of motile cells and evolving tissues constitute a class of adaptive self-healing materials that respond to the topography, elasticity and surface chemistry of the environment and react to external stimuli. Although a comprehensive understanding of substrate-based cell motility remains elusive, progress has been achieved recently in its modelling on the whole-cell level. Here we survey the most recent advances in computational approaches to cell movement and demonstrate how these models improve our understanding of complex self-organised systems such as living cells.
Systems approaches to computational modeling of the oral microbiome
Dimiter V. Dimitrov
2013-07-01
Full Text Available Current microbiome research has generated tremendous amounts of data providing snapshots of molecular activity in a variety of organisms, environments, and cell types. However, turning this knowledge into whole system level of understanding on pathways and processes has proven to be a challenging task. In this review we highlight the applicability of bioinformatics and visualization techniques to large collections of data in order to better understand the information that contains related diet – oral microbiome – host mucosal transcriptome interactions. In particular we focus on systems biology of Porphyromonas gingivalis in the context of high throughput computational methods tightly integrated with translational systems medicine. Those approaches have applications for both basic research, where we can direct specific laboratory experiments in model organisms and cell cultures, to human disease, where we can validate new mechanisms and biomarkers for prevention and treatment of chronic disorders
Computer Modeling of Violent Intent: A Content Analysis Approach
Sanfilippo, Antonio P.; Mcgrath, Liam R.; Bell, Eric B.
2014-01-03
We present a computational approach to modeling the intent of a communication source representing a group or an individual to engage in violent behavior. Our aim is to identify and rank aspects of radical rhetoric that are endogenously related to violent intent to predict the potential for violence as encoded in written or spoken language. We use correlations between contentious rhetoric and the propensity for violent behavior found in documents from radical terrorist and non-terrorist groups and individuals to train and evaluate models of violent intent. We then apply these models to unseen instances of linguistic behavior to detect signs of contention that have a positive correlation with violent intent factors. Of particular interest is the application of violent intent models to social media, such as Twitter, that have proved to serve as effective channels in furthering sociopolitical change.
Leaching from Heterogeneous Heck Catalysts: A Computational Approach
无
2002-01-01
The possibility of carrying out a purely heterogeneous Heck reaction in practice without Pd leaching has been previously considered by a number of research groups but no general consent has yet arrived. Here, the reaction was, for the first time, evaluated by a simple computational approach. Modelling experiments were performed on one of the initial catalytic steps: phenyl halides attachment on Pd (111) to (100) and (111) to (111) ridges of a Pd crystal. Three surface structures of resulting [PhPdX] were identified as possible reactive intermediates. Following potential energy minimisation calculations based on a universal force field, the relative stabilities of these surface species were then determined. Results showed the most stable species to be one in which a Pd ridge atom is removed from the Pd crystal structure, suggesting Pd leaching induced by phenyl halides is energetically favourable.
A computational approach for deciphering the organization of glycosaminoglycans.
Jean L Spencer
Full Text Available BACKGROUND: Increasing evidence has revealed important roles for complex glycans as mediators of normal and pathological processes. Glycosaminoglycans are a class of glycans that bind and regulate the function of a wide array of proteins at the cell-extracellular matrix interface. The specific sequence and chemical organization of these polymers likely define function; however, identification of the structure-function relationships of glycosaminoglycans has been met with challenges associated with the unique level of complexity and the nontemplate-driven biosynthesis of these biopolymers. METHODOLOGY/PRINCIPAL FINDINGS: To address these challenges, we have devised a computational approach to predict fine structure and patterns of domain organization of the specific glycosaminoglycan, heparan sulfate (HS. Using chemical composition data obtained after complete and partial digestion of mixtures of HS chains with specific degradative enzymes, the computational analysis produces populations of theoretical HS chains with structures that meet both biosynthesis and enzyme degradation rules. The model performs these operations through a modular format consisting of input/output sections and three routines called chainmaker, chainbreaker, and chainsorter. We applied this methodology to analyze HS preparations isolated from pulmonary fibroblasts and epithelial cells. Significant differences in the general organization of these two HS preparations were observed, with HS from epithelial cells having a greater frequency of highly sulfated domains. Epithelial HS also showed a higher density of specific HS domains that have been associated with inhibition of neutrophil elastase. Experimental analysis of elastase inhibition was consistent with the model predictions and demonstrated that HS from epithelial cells had greater inhibitory activity than HS from fibroblasts. CONCLUSIONS/SIGNIFICANCE: This model establishes the conceptual framework for a new class of
A computational approach for deciphering the organization of glycosaminoglycans.
Spencer, Jean L; Bernanke, Joel A; Buczek-Thomas, Jo Ann; Nugent, Matthew A
2010-02-23
Increasing evidence has revealed important roles for complex glycans as mediators of normal and pathological processes. Glycosaminoglycans are a class of glycans that bind and regulate the function of a wide array of proteins at the cell-extracellular matrix interface. The specific sequence and chemical organization of these polymers likely define function; however, identification of the structure-function relationships of glycosaminoglycans has been met with challenges associated with the unique level of complexity and the nontemplate-driven biosynthesis of these biopolymers. To address these challenges, we have devised a computational approach to predict fine structure and patterns of domain organization of the specific glycosaminoglycan, heparan sulfate (HS). Using chemical composition data obtained after complete and partial digestion of mixtures of HS chains with specific degradative enzymes, the computational analysis produces populations of theoretical HS chains with structures that meet both biosynthesis and enzyme degradation rules. The model performs these operations through a modular format consisting of input/output sections and three routines called chainmaker, chainbreaker, and chainsorter. We applied this methodology to analyze HS preparations isolated from pulmonary fibroblasts and epithelial cells. Significant differences in the general organization of these two HS preparations were observed, with HS from epithelial cells having a greater frequency of highly sulfated domains. Epithelial HS also showed a higher density of specific HS domains that have been associated with inhibition of neutrophil elastase. Experimental analysis of elastase inhibition was consistent with the model predictions and demonstrated that HS from epithelial cells had greater inhibitory activity than HS from fibroblasts. This model establishes the conceptual framework for a new class of computational tools to use to assess patterns of domain organization within
An Organic Computing Approach to Self-organising Robot Ensembles
Sebastian Albrecht von Mammen
2016-11-01
Full Text Available Similar to the Autonomous Computing initiative, that has mainly been advancing techniques for self-optimisation focussing on computing systems and infrastructures, Organic Computing (OC has been driving the development of system design concepts and algorithms for self-adaptive systems at large. Examples of application domains include, for instance, traffic management and control, cloud services, communication protocols, and robotic systems. Such an OC system typically consists of a potentially large set of autonomous and self-managed entities, where each entity acts with a local decision horizon. By means of cooperation of the individual entities, the behaviour of the entire ensemble system is derived. In this article, we present our work on how autonomous, adaptive robot ensembles can benefit from OC technology. Our elaborations are aligned with the different layers of an observer/controller framework which provides the foundation for the individuals' adaptivity at system design-level. Relying on an extended Learning Classifier System (XCS in combination with adequate simulation techniques, this basic system design empowers robot individuals to improve their individual and collaborative performances, e.g. by means of adapting to changing goals and conditions.Not only for the sake of generalisability, but also because of its enormous transformative potential, we stage our research in the domain of robot ensembles that are typically comprised of several quad-rotors and that organise themselves to fulfil spatial tasks such as maintenance of building facades or the collaborative search for mobile targets. Our elaborations detail the architectural concept, provide examples of individual self-optimisation as well as of the optimisation of collaborative efforts, and we show how the user can control the ensembles at multiple levels of abstraction. We conclude with a summary of our approach and an outlook on possible future steps.
Cloud computing approaches for prediction of ligand binding poses and pathways.
Lawrenz, Morgan; Shukla, Diwakar; Pande, Vijay S
2015-01-22
We describe an innovative protocol for ab initio prediction of ligand crystallographic binding poses and highly effective analysis of large datasets generated for protein-ligand dynamics. We include a procedure for setup and performance of distributed molecular dynamics simulations on cloud computing architectures, a model for efficient analysis of simulation data, and a metric for evaluation of model convergence. We give accurate binding pose predictions for five ligands ranging in affinity from 7 nM to > 200 μM for the immunophilin protein FKBP12, for expedited results in cases where experimental structures are difficult to produce. Our approach goes beyond single, low energy ligand poses to give quantitative kinetic information that can inform protein engineering and ligand design.
Examples of computational approaches for elliptic, possibly multiscale PDEs with random inputs
Le Bris, Claude; Legoll, Frédéric
2017-01-01
We overview a series of recent works addressing numerical simulations of partial differential equations in the presence of some elements of randomness. The specific equations manipulated are linear elliptic, and arise in the context of multiscale problems, but the purpose is more general. On a set of prototypical situations, we investigate two critical issues present in many settings: variance reduction techniques to obtain sufficiently accurate results at a limited computational cost when solving PDEs with random coefficients, and finite element techniques that are sufficiently flexible to carry over to geometries with random fluctuations. Some elements of theoretical analysis and numerical analysis are briefly mentioned. Numerical experiments, although simple, provide convincing evidence of the efficiency of the approaches.
Fathi Kazerooni, Anahita; Mohseni, Meysam; Rezaei, Sahar; Bakhshandehpour, Gholamreza; Saligheh Rad, Hamidreza
2015-02-01
Glioblastoma multiforme (GBM) brain tumor is heterogeneous in nature, so its quantification depends on how to accurately segment different parts of the tumor, i.e. viable tumor, edema and necrosis. This procedure becomes more effective when metabolic and functional information, provided by physiological magnetic resonance (MR) imaging modalities, like diffusion-weighted-imaging (DWI) and perfusion-weighted-imaging (PWI), is incorporated with the anatomical magnetic resonance imaging (MRI). In this preliminary tumor quantification work, the idea is to characterize different regions of GBM tumors in an MRI-based semi-automatic multi-parametric approach to achieve more accurate characterization of pathogenic regions. For this purpose, three MR sequences, namely T2-weighted imaging (anatomical MR imaging), PWI and DWI of thirteen GBM patients, were acquired. To enhance the delineation of the boundaries of each pathogenic region (peri-tumoral edema, viable tumor and necrosis), the spatial fuzzy C-means algorithm is combined with the region growing method. The results show that exploiting the multi-parametric approach along with the proposed semi-automatic segmentation method can differentiate various tumorous regions with over 80 % sensitivity, specificity and dice score. The proposed MRI-based multi-parametric segmentation approach has the potential to accurately segment tumorous regions, leading to an efficient design of the pre-surgical treatment planning.
Towards scalable quantum communication and computation: Novel approaches and realizations
Jiang, Liang
Quantum information science involves exploration of fundamental laws of quantum mechanics for information processing tasks. This thesis presents several new approaches towards scalable quantum information processing. First, we consider a hybrid approach to scalable quantum computation, based on an optically connected network of few-qubit quantum registers. Specifically, we develop a novel scheme for scalable quantum computation that is robust against various imperfections. To justify that nitrogen-vacancy (NV) color centers in diamond can be a promising realization of the few-qubit quantum register, we show how to isolate a few proximal nuclear spins from the rest of the environment and use them for the quantum register. We also demonstrate experimentally that the nuclear spin coherence is only weakly perturbed under optical illumination, which allows us to implement quantum logical operations that use the nuclear spins to assist the repetitive-readout of the electronic spin. Using this technique, we demonstrate more than two-fold improvement in signal-to-noise ratio. Apart from direct application to enhance the sensitivity of the NV-based nano-magnetometer, this experiment represents an important step towards the realization of robust quantum information processors using electronic and nuclear spin qubits. We then study realizations of quantum repeaters for long distance quantum communication. Specifically, we develop an efficient scheme for quantum repeaters based on atomic ensembles. We use dynamic programming to optimize various quantum repeater protocols. In addition, we propose a new protocol of quantum repeater with encoding, which efficiently uses local resources (about 100 qubits) to identify and correct errors, to achieve fast one-way quantum communication over long distances. Finally, we explore quantum systems with topological order. Such systems can exhibit remarkable phenomena such as quasiparticles with anyonic statistics and have been proposed as
Computer-Aided Approaches for Targeting HIVgp41
William J. Allen
2012-08-01
Full Text Available Virus-cell fusion is the primary means by which the human immunodeficiency virus-1 (HIV delivers its genetic material into the human T-cell host. Fusion is mediated in large part by the viral glycoprotein 41 (gp41 which advances through four distinct conformational states: (i native, (ii pre-hairpin intermediate, (iii fusion active (fusogenic, and (iv post-fusion. The pre-hairpin intermediate is a particularly attractive step for therapeutic intervention given that gp41 N-terminal heptad repeat (NHR and C‑terminal heptad repeat (CHR domains are transiently exposed prior to the formation of a six-helix bundle required for fusion. Most peptide-based inhibitors, including the FDA‑approved drug T20, target the intermediate and there are significant efforts to develop small molecule alternatives. Here, we review current approaches to studying interactions of inhibitors with gp41 with an emphasis on atomic-level computer modeling methods including molecular dynamics, free energy analysis, and docking. Atomistic modeling yields a unique level of structural and energetic detail, complementary to experimental approaches, which will be important for the design of improved next generation anti-HIV drugs.
Brounstein, Anna; Hacihaliloglu, Ilker; Guy, Pierre; Hodgson, Antony; Abugharbieh, Rafeef
2015-12-01
Automatic, accurate and real-time registration is an important step in providing effective guidance and successful anatomic restoration in ultrasound (US)-based computer assisted orthopedic surgery. We propose a method in which local phase-based bone surfaces, extracted from intra-operative US data, are registered to pre-operatively segmented computed tomography data. Extracted bone surfaces are downsampled and reinforced with high curvature features. A novel hierarchical simplification algorithm is used to further optimize the point clouds. The final point clouds are represented as Gaussian mixture models and iteratively matched by minimizing the dissimilarity between them using an L2 metric. For 44 clinical data sets from 25 pelvic fracture patients and 49 phantom data sets, we report mean surface registration accuracies of 0.31 and 0.77 mm, respectively, with an average registration time of 1.41 s. Our results suggest the viability and potential of the chosen method for real-time intra-operative registration in orthopedic surgery.
Human Computer Interaction Approach in Developing Customer Relationship Management
Mohd H.N.M. Nasir
2008-01-01
Full Text Available Problem statement: Many published studies have found that more than 50% of Customer Relationship Management (CRM system implementations have failed due to the failure of system usability and does not fulfilled user expectation. This study presented the issues that contributed to the failures of CRM system and proposed a prototype of CRM system developed using Human Computer Interaction approaches in order to resolve the identified issues. Approach: In order to capture the users' requirements, a single in-depth case study of a multinational company was chosen in this research, in which the background, current conditions and environmental interactions were observed, recorded and analyzed for stages of patterns in relation to internal and external influences. Some techniques of blended data gathering which are interviews, naturalistic observation and studying user documentation were employed and then the prototype of CRM system was developed which incorporated User-Centered Design (UCD approach, Hierarchical Task Analysis (HTA, metaphor and identification of users' behaviors and characteristics. The implementation of these techniques, were then measured in terms of usability. Results: Based on the usability testing conducted, the results showed that most of the users agreed that the system is comfortable to work with by taking the quality attributes of learnability, memorizeablity, utility, sortability, font, visualization, user metaphor, information easy view and color as measurement parameters. Conclusions/Recommendations: By combining all these techniques, a comfort level for the users that leads to user satisfaction and higher usability degree can be achieved in a proposed CRM system. Thus, it is important that the companies should put usability quality attribute into a consideration before developing or procuring CRM system to ensure the implementation successfulness of the CRM system.
An evolutionary computation approach to examine functional brain plasticity
Arnab eRoy
2016-04-01
Full Text Available One common research goal in systems neurosciences is to understand how the functional relationship between a pair of regions of interest (ROIs evolves over time. Examining neural connectivity in this way is well-suited for the study of developmental processes, learning, and even in recovery or treatment designs in response to injury. For most fMRI based studies, the strength of the functional relationship between two ROIs is defined as the correlation between the average signal representing each region. The drawback to this approach is that much information is lost due to averaging heterogeneous voxels, and therefore, the functional relationship between a ROI-pair that evolve at a spatial scale much finer than the ROIs remain undetected. To address this shortcoming, we introduce a novel evolutionary computation (EC based voxel-level procedure to examine functional plasticity between an investigator defined ROI-pair by simultaneously using subject-specific BOLD-fMRI data collected from two sessions seperated by finite duration of time. This data-driven procedure detects a sub-region composed of spatially connected voxels from each ROI (a so-called sub-regional-pair such that the pair shows a significant gain/loss of functional relationship strength across the two time points. The procedure is recursive and iteratively finds all statistically significant sub-regional-pairs within the ROIs. Using this approach, we examine functional plasticity between the default mode network (DMN and the executive control network (ECN during recovery from traumatic brain injury (TBI; the study includes 14 TBI and 12 healthy control subjects. We demonstrate that the EC based procedure is able to detect functional plasticity where a traditional averaging based approach fails. The subject-specific plasticity estimates obtained using the EC-procedure are highly consistent across multiple runs. Group-level analyses using these plasticity estimates showed an increase in
Vineet Kumar
2016-01-01
Full Text Available Iris segmentation in the iris recognition systems is a challenging task under noncooperative environments. The iris segmentation is a process of detecting the pupil, iris’s outer boundary, and eyelids in the iris image. In this paper, we propose a pupil localization method for locating the pupils in the non-close-up and frontal-view iris images that are captured under near-infrared (NIR illuminations and contain the noise, such as specular and lighting reflection spots, eyeglasses, nonuniform illumination, low contrast, and occlusions by the eyelids, eyelashes, and eyebrow hair. In the proposed method, first, a novel edge-map is created from the iris image, which is based on combining the conventional thresholding and edge detection based segmentation techniques, and then, the general circular Hough transform (CHT is used to find the pupil circle parameters in the edge-map. Our main contribution in this research is a novel edge-map creation technique, which reduces the false edges drastically in the edge-map of the iris image and makes the pupil localization in the noisy NIR images more accurate, fast, robust, and simple. The proposed method was tested with three iris databases: CASIA-Iris-Thousand (version 4.0, CASIA-Iris-Lamp (version 3.0, and MMU (version 2.0. The average accuracy of the proposed method is 99.72% and average time cost per image is 0.727 sec.
An Automatic Approach to Detect Software Anomalies in Cloud Computing Using Pragmatic Bayes Approach
Nethaji V
2014-06-01
Full Text Available Software detection of anomalies is a vital element of operations in data centers and service clouds. Statistical Process Control (SPC cloud charts sense routine anomalies and their root causes are identified based on the differential profiling strategy. By automating the tasks, most of the manual overhead incurred in detecting the software anomalies and the analysis time are reduced to a larger extent but detailed analysis of profiling data are not performed in most of the cases. On the other hand, the cloud scheduler judges both the requirements of the user and the available infrastructure to equivalent their requirements. OpenStack prototype works on cloud trust management which provides the scheduler but complexity occurs when hosting the cloud system. At the same time, Trusted Computing Base (TCB of a computing node does not achieve the scalability measure. This unique paradigm brings about many software anomalies, which have not been well studied. This work, a Pragmatic Bayes approach studies the problem of detecting software anomalies and ensures scalability by comparing information at the current time to historical data. In particular, PB approach uses the two component Gaussian mixture to deviations at current time in cloud environment. The introduction of Gaussian mixture in PB approach achieves higher scalability measure which involves supervising massive number of cells and fast enough to be potentially useful in many streaming scenarios. Wherein previous works has been ensured for scheduling often lacks of scalability, this paper shows the superiority of the method using a Bayes per section error rate procedure through simulation, and provides the detailed analysis of profiling data in the marginal distributions using the Amazon EC2 dataset. Extensive performance analysis shows that the PB approach is highly efficient in terms of runtime, scalability, software anomaly detection ratio, CPU utilization, density rate, and computational
Khatami, F.; Weide, van der E.T.A.; Hoeijmakers, H.W.M.
2015-01-01
In this paper a numerical simulation of unsteady sheet cavitation is presented as it occurs on an NACA-0015 hydrofoil. The computational approach is based on the Euler equations for unsteady compressible flow, using an equilibrium cavitation model of Schnerr, Schmidt, and Saurel. It was found that f
Krishna Kumar, P; Araki, Tadashi; Rajan, Jeny; Saba, Luca; Lavra, Francesco; Ikeda, Nobutaka; Sharma, Aditya M; Shafique, Shoaib; Nicolaides, Andrew; Laird, John R; Gupta, Ajay; Suri, Jasjit S
2016-12-10
Monitoring of cerebrovascular diseases via carotid ultrasound has started to become a routine. The measurement of image-based lumen diameter (LD) or inter-adventitial diameter (IAD) is a promising approach for quantification of the degree of stenosis. The manual measurements of LD/IAD are not reliable, subjective and slow. The curvature associated with the vessels along with non-uniformity in the plaque growth poses further challenges. This study uses a novel and generalized approach for automated LD and IAD measurement based on a combination of spatial transformation and scale-space. In this iterative procedure, the scale-space is first used to get the lumen axis which is then used with spatial image transformation paradigm to get a transformed image. The scale-space is then reapplied to retrieve the lumen region and boundary in the transformed framework. Then, inverse transformation is applied to display the results in original image framework. Two hundred and two patients' left and right common carotid artery (404 carotid images) B-mode ultrasound images were retrospectively analyzed. The validation of our algorithm has done against the two manual expert tracings. The coefficient of correlation between the two manual tracings for LD was 0.98 (p < 0.0001) and 0.99 (p < 0.0001), respectively. The precision of merit between the manual expert tracings and the automated system was 97.7 and 98.7%, respectively. The experimental analysis demonstrated superior performance of the proposed method over conventional approaches. Several statistical tests demonstrated the stability and reliability of the automated system.
Om Prakash Gurjar
2016-03-01
Full Text Available Purpose: Various factors cause geometric uncertainties during prostate radiotherapy, including interfractional and intrafractional patient motions, organ motion, and daily setup errors. This may lead to increased normal tissue complications when a high dose to the prostate is administered. More-accurate treatment delivery is possible with daily imaging and localization of the prostate. This study aims to measure the shift of the prostate by using kilovoltage (kV cone beam computed tomography (CBCT after position verification by kV orthogonal portal imaging (OPI.Methods: Position verification in 10 patients with prostate cancer was performed by using OPI followed by CBCT before treatment delivery in 25 sessions per patient. In each session, OPI was performed by using an on-board imaging (OBI system and pelvic bone-to-pelvic bone matching was performed. After applying the noted shift by using OPI, CBCT was performed by using the OBI system and prostate-to-prostate matching was performed. The isocenter shifts along all three translational directions in both techniques were combined into a three-dimensional (3-D iso-displacement vector (IDV.Results: The mean (SD IDV (in centimeters calculated during the 250 imaging sessions was 0.931 (0.598, median 0.825 for OPI and 0.515 (336, median 0.43 for CBCT, p-value was less than 0.0001 which shows extremely statistical significant difference.Conclusion: Even after bone-to-bone matching by using OPI, a significant shift in prostate was observed on CBCT. This study concludes that imaging with CBCT provides a more accurate prostate localization than the OPI technique. Hence, CBCT should be chosen as the preferred imaging technique.
Cruz-Roa, Angel; Gilmore, Hannah; Basavanhally, Ajay; Feldman, Michael; Ganesan, Shridar; Shih, Natalie N. C.; Tomaszewski, John; González, Fabio A.; Madabhushi, Anant
2017-04-01
With the increasing ability to routinely and rapidly digitize whole slide images with slide scanners, there has been interest in developing computerized image analysis algorithms for automated detection of disease extent from digital pathology images. The manual identification of presence and extent of breast cancer by a pathologist is critical for patient management for tumor staging and assessing treatment response. However, this process is tedious and subject to inter- and intra-reader variability. For computerized methods to be useful as decision support tools, they need to be resilient to data acquired from different sources, different staining and cutting protocols and different scanners. The objective of this study was to evaluate the accuracy and robustness of a deep learning-based method to automatically identify the extent of invasive tumor on digitized images. Here, we present a new method that employs a convolutional neural network for detecting presence of invasive tumor on whole slide images. Our approach involves training the classifier on nearly 400 exemplars from multiple different sites, and scanners, and then independently validating on almost 200 cases from The Cancer Genome Atlas. Our approach yielded a Dice coefficient of 75.86%, a positive predictive value of 71.62% and a negative predictive value of 96.77% in terms of pixel-by-pixel evaluation compared to manually annotated regions of invasive ductal carcinoma.
A Near-Term Quantum Computing Approach for Hard Computational Problems in Space Exploration
Smelyanskiy, Vadim N; Knysh, Sergey I; Williams, Colin P; Johnson, Mark W; Thom, Murray C; Macready, William G; Pudenz, Kristen L
2012-01-01
In this article, we show how to map a sampling of the hardest artificial intelligence problems in space exploration onto equivalent Ising models that then can be attacked using quantum annealing implemented in D-Wave machine. We overview the existing results as well as propose new Ising model implementations for quantum annealing. We review supervised and unsupervised learning algorithms for classification and clustering with applications to feature identification and anomaly detection. We introduce algorithms for data fusion and image matching for remote sensing applications. We overview planning problems for space exploration mission applications and algorithms for diagnostics and recovery with applications to deep space missions. We describe combinatorial optimization algorithms for task assignment in the context of autonomous unmanned exploration. Finally, we discuss the ways to circumvent the limitation of the Ising mapping using a "blackbox" approach based on ideas from probabilistic computing. In this ...
Ihrig, Arvid Conrad; Wieferink, Jürgen; Zhang, Igor Ying; Ropo, Matti; Ren, Xinguo; Rinke, Patrick; Scheffler, Matthias; Blum, Volker
2015-09-01
A key component in calculations of exchange and correlation energies is the Coulomb operator, which requires the evaluation of two-electron integrals. For localized basis sets, these four-center integrals are most efficiently evaluated with the resolution of identity (RI) technique, which expands basis-function products in an auxiliary basis. In this work we show the practical applicability of a localized RI-variant (‘RI-LVL’), which expands products of basis functions only in the subset of those auxiliary basis functions which are located at the same atoms as the basis functions. We demonstrate the accuracy of RI-LVL for Hartree-Fock calculations, for the PBE0 hybrid density functional, as well as for RPA and MP2 perturbation theory. Molecular test sets used include the S22 set of weakly interacting molecules, the G3 test set, as well as the G2-1 and BH76 test sets, and heavy elements including titanium dioxide, copper and gold clusters. Our RI-LVL implementation paves the way for linear-scaling RI-based hybrid functional calculations for large systems and for all-electron many-body perturbation theory with significantly reduced computational and memory cost.
Computational Approach for Epitaxial Polymorph Stabilization through Substrate Selection
Ding, Hong; Dwaraknath, Shyam S.; Garten, Lauren; Ndione, Paul; Ginley, David; Persson, Kristin A.
2016-05-25
With the ultimate goal of finding new polymorphs through targeted synthesis conditions and techniques, we outline a computational framework to select optimal substrates for epitaxial growth using first principle calculations of formation energies, elastic strain energy, and topological information. To demonstrate the approach, we study the stabilization of metastable VO2 compounds which provides a rich chemical and structural polymorph space. We find that common polymorph statistics, lattice matching, and energy above hull considerations recommends homostructural growth on TiO2 substrates, where the VO2 brookite phase would be preferentially grown on the a-c TiO2 brookite plane while the columbite and anatase structures favor the a-b plane on the respective TiO2 phases. Overall, we find that a model which incorporates a geometric unit cell area matching between the substrate and the target film as well as the resulting strain energy density of the film provide qualitative agreement with experimental observations for the heterostructural growth of known VO2 polymorphs: rutile, A and B phases. The minimal interfacial geometry matching and estimated strain energy criteria provide several suggestions for substrates and substrate-film orientations for the heterostructural growth of the hitherto hypothetical anatase, brookite, and columbite polymorphs. These criteria serve as a preliminary guidance for the experimental efforts stabilizing new materials and/or polymorphs through epitaxy. The current screening algorithm is being integrated within the Materials Project online framework and data and hence publicly available.
Computer-aided interpretation approach for optical tomographic images
Klose, Christian D.; Klose, Alexander D.; Netz, Uwe J.; Scheel, Alexander K.; Beuthan, Jürgen; Hielscher, Andreas H.
2010-11-01
A computer-aided interpretation approach is proposed to detect rheumatic arthritis (RA) in human finger joints using optical tomographic images. The image interpretation method employs a classification algorithm that makes use of a so-called self-organizing mapping scheme to classify fingers as either affected or unaffected by RA. Unlike in previous studies, this allows for combining multiple image features, such as minimum and maximum values of the absorption coefficient for identifying affected and not affected joints. Classification performances obtained by the proposed method were evaluated in terms of sensitivity, specificity, Youden index, and mutual information. Different methods (i.e., clinical diagnostics, ultrasound imaging, magnet resonance imaging, and inspection of optical tomographic images), were used to produce ground truth benchmarks to determine the performance of image interpretations. Using data from 100 finger joints, findings suggest that some parameter combinations lead to higher sensitivities, while others to higher specificities when compared to single parameter classifications employed in previous studies. Maximum performances are reached when combining the minimum/maximum ratio of the absorption coefficient and image variance. In this case, sensitivities and specificities over 0.9 can be achieved. These values are much higher than values obtained when only single parameter classifications were used, where sensitivities and specificities remained well below 0.8.
Lexical is as lexical does: computational approaches to lexical representation
Woollams, Anna M.
2015-01-01
In much of neuroimaging and neuropsychology, regions of the brain have been associated with ‘lexical representation’, with little consideration as to what this cognitive construct actually denotes. Within current computational models of word recognition, there are a number of different approaches to the representation of lexical knowledge. Structural lexical representations, found in original theories of word recognition, have been instantiated in modern localist models. However, such a representational scheme lacks neural plausibility in terms of economy and flexibility. Connectionist models have therefore adopted distributed representations of form and meaning. Semantic representations in connectionist models necessarily encode lexical knowledge. Yet when equipped with recurrent connections, connectionist models can also develop attractors for familiar forms that function as lexical representations. Current behavioural, neuropsychological and neuroimaging evidence shows a clear role for semantic information, but also suggests some modality- and task-specific lexical representations. A variety of connectionist architectures could implement these distributed functional representations, and further experimental and simulation work is required to discriminate between these alternatives. Future conceptualisations of lexical representations will therefore emerge from a synergy between modelling and neuroscience. PMID:25893204
Dielectric properties of periodic heterostructures: A computational electrostatics approach
Brosseau, C.; Beroual, A.
1999-04-01
The dielectric properties of heterogeneous materials for various condensed-matter systems are important for several technologies, e.g. impregnated polymers for high-density capacitors, polymer carbon black mixtures for automotive tires and current limiters in circuit protection. These multiscale systems lead to challenging problems of connecting microstructural features (shape, spatial arrangement and size distribution of inclusions) to macroscopic materials response (permittivity, conductivity). In this paper, we briefly discuss an ab initio computational electrostatics approach, based either on the use of the field calculation package FLUX3D (or FLUX2D) and a conventional finite elements method, or the use of the field calculation package PHI3D and the resolution of boundary integral equations, for calculating the effective permittivity of two-component dielectric heterostructures. Numerical results concerning inclusions of permittivity \\varepsilon_1 with various geometrical shapes periodically arranged in a host matrix of permittivity \\varepsilon_2 are provided. Next we discuss these results in terms of phenomenological mixing laws, analytical theory and connectedness. During the pursuit of these activities, several interesting phenomena were discovered that will stimulate further investigation.
Applying a cloud computing approach to storage architectures for spacecraft
Baldor, Sue A.; Quiroz, Carlos; Wood, Paul
As sensor technologies, processor speeds, and memory densities increase, spacecraft command, control, processing, and data storage systems have grown in complexity to take advantage of these improvements and expand the possible missions of spacecraft. Spacecraft systems engineers are increasingly looking for novel ways to address this growth in complexity and mitigate associated risks. Looking to conventional computing, many solutions have been executed to solve both the problem of complexity and heterogeneity in systems. In particular, the cloud-based paradigm provides a solution for distributing applications and storage capabilities across multiple platforms. In this paper, we propose utilizing a cloud-like architecture to provide a scalable mechanism for providing mass storage in spacecraft networks that can be reused on multiple spacecraft systems. By presenting a consistent interface to applications and devices that request data to be stored, complex systems designed by multiple organizations may be more readily integrated. Behind the abstraction, the cloud storage capability would manage wear-leveling, power consumption, and other attributes related to the physical memory devices, critical components in any mass storage solution for spacecraft. Our approach employs SpaceWire networks and SpaceWire-capable devices, although the concept could easily be extended to non-heterogeneous networks consisting of multiple spacecraft and potentially the ground segment.
Trischan, John
Rapid deforestation has been occurring in Southeast Asia for majority of the last quarter century. This is due in large by the expansion of oil palm plantations. These plantations fill the need globally for the palm oil they provide. On the other hand, they are removing some of the last remaining primary rainforests on the planet. The issue concerning the ongoing demise of rainforests in the region involves the availability of data in order to monitor the expansion of palm, at the cost of rainforest. Providing a simplified approach to mapping oil palm plantations in hopes of spreading palm analysis regionally in an effort to obtain a better grasp on the land use dynamics. Using spatial filtering techniques, the complexity of radar data are simplified in order to use for palm detection.
An Educational Approach to Computationally Modeling Dynamical Systems
Chodroff, Leah; O'Neal, Tim M.; Long, David A.; Hemkin, Sheryl
2009-01-01
Chemists have used computational science methodologies for a number of decades and their utility continues to be unabated. For this reason we developed an advanced lab in computational chemistry in which students gain understanding of general strengths and weaknesses of computation-based chemistry by working through a specific research problem.…
Computational modeling of bone density profiles in response to gait: a subject-specific approach.
Pang, Henry; Shiwalkar, Abhishek P; Madormo, Chris M; Taylor, Rebecca E; Andriacchi, Thomas P; Kuhl, Ellen
2012-03-01
The goal of this study is to explore the potential of computational growth models to predict bone density profiles in the proximal tibia in response to gait-induced loading. From a modeling point of view, we design a finite element-based computational algorithm using the theory of open system thermodynamics. In this algorithm, the biological problem, the balance of mass, is solved locally on the integration point level, while the mechanical problem, the balance of linear momentum, is solved globally on the node point level. Specifically, the local bone mineral density is treated as an internal variable, which is allowed to change in response to mechanical loading. From an experimental point of view, we perform a subject-specific gait analysis to identify the relevant forces during walking using an inverse dynamics approach. These forces are directly applied as loads in the finite element simulation. To validate the model, we take a Dual-Energy X-ray Absorptiometry scan of the subject's right knee from which we create a geometric model of the proximal tibia. For qualitative validation, we compare the computationally predicted density profiles to the bone mineral density extracted from this scan. For quantitative validation, we adopt the region of interest method and determine the density values at fourteen discrete locations using standard and custom-designed image analysis tools. Qualitatively, our two- and three-dimensional density predictions are in excellent agreement with the experimental measurements. Quantitatively, errors are less than 3% for the two-dimensional analysis and less than 10% for the three-dimensional analysis. The proposed approach has the potential to ultimately improve the long-term success of possible treatment options for chronic diseases such as osteoarthritis on a patient-specific basis by accurately addressing the complex interactions between ambulatory loads and tissue changes.
The Metacognitive Approach to Computer Education: Making Explicit the Learning Journey
Phelps, Renata
2007-01-01
This paper presents a theoretical and practical exploration of a metacognitive approach to computer education, developed through a three-year action research project. It is argued that the approach contrasts significantly with often-employed directive and competency-based approaches to computer education and is more appropriate in addressing the…
Approaching the Computational Color Constancy as a Classification Problem through Deep Learning
Oh, Seoung Wug; Kim, Seon Joo
2016-01-01
Computational color constancy refers to the problem of computing the illuminant color so that the images of a scene under varying illumination can be normalized to an image under the canonical illumination. In this paper, we adopt a deep learning framework for the illumination estimation problem. The proposed method works under the assumption of uniform illumination over the scene and aims for the accurate illuminant color computation. Specifically, we trained the convolutional neural network...
Neese, Frank; Wennmohs, Frank; Hansen, Andreas
2009-03-01
Coupled-electron pair approximations (CEPAs) and coupled-pair functionals (CPFs) have been popular in the 1970s and 1980s and have yielded excellent results for small molecules. Recently, interest in CEPA and CPF methods has been renewed. It has been shown that these methods lead to competitive thermochemical, kinetic, and structural predictions. They greatly surpass second order Møller-Plesset and popular density functional theory based approaches in accuracy and are intermediate in quality between CCSD and CCSD(T) in extended benchmark studies. In this work an efficient production level implementation of the closed shell CEPA and CPF methods is reported that can be applied to medium sized molecules in the range of 50-100 atoms and up to about 2000 basis functions. The internal space is spanned by localized internal orbitals. The external space is greatly compressed through the method of pair natural orbitals (PNOs) that was also introduced by the pioneers of the CEPA approaches. Our implementation also makes extended use of density fitting (or resolution of the identity) techniques in order to speed up the laborious integral transformations. The method is called local pair natural orbital CEPA (LPNO-CEPA) (LPNO-CPF). The implementation is centered around the concepts of electron pairs and matrix operations. Altogether three cutoff parameters are introduced that control the size of the significant pair list, the average number of PNOs per electron pair, and the number of contributing basis functions per PNO. With the conservatively chosen default values of these thresholds, the method recovers about 99.8% of the canonical correlation energy. This translates to absolute deviations from the canonical result of only a few kcal mol-1. Extended numerical test calculations demonstrate that LPNO-CEPA (LPNO-CPF) has essentially the same accuracy as parent CEPA (CPF) methods for thermochemistry, kinetics, weak interactions, and potential energy surfaces but is up to 500
Gol Mohammadi, N.; Bandyszak, T.; Goldsteen, A.; Kalogiros, C.; Weyer, T.; Moffie, M.; Nasser, B.; Surridge, M
2015-01-01
The analysis of existing software evaluation techniques reveals the need for evidence-based evaluation of systems’ trustworthiness. This paper aims at evaluating trustworthiness of socio-technical systems during design-time. Our approach combines two existing evaluation techniques: a computa-tional approach and a risk management approach. The risk-based approach identifies threats to trustworthiness on an abstract level. Computational ap-proaches are applied to evaluate the expected end-to-en...
Human Computation An Integrated Approach to Learning from the Crowd
Law, Edith
2011-01-01
Human computation is a new and evolving research area that centers around harnessing human intelligence to solve computational problems that are beyond the scope of existing Artificial Intelligence (AI) algorithms. With the growth of the Web, human computation systems can now leverage the abilities of an unprecedented number of people via the Web to perform complex computation. There are various genres of human computation applications that exist today. Games with a purpose (e.g., the ESP Game) specifically target online gamers who generate useful data (e.g., image tags) while playing an enjoy
A Monomial Chaos Approach for Efficient Uncertainty Quantification in Computational Fluid Dynamics
Witteveen, J.A.S.; Bijl, H.
2006-01-01
A monomial chaos approach is proposed for efficient uncertainty quantification in nonlinear computational problems. Propagating uncertainty through nonlinear equations can still be computationally intensive for existing uncertainty quantification methods. It usually results in a set of nonlinear equ
De Backer, A; van den Bos, K H W; Van den Broek, W; Sijbers, J; Van Aert, S
2016-12-01
An efficient model-based estimation algorithm is introduced to quantify the atomic column positions and intensities from atomic resolution (scanning) transmission electron microscopy ((S)TEM) images. This algorithm uses the least squares estimator on image segments containing individual columns fully accounting for overlap between neighbouring columns, enabling the analysis of a large field of view. For this algorithm, the accuracy and precision with which measurements for the atomic column positions and scattering cross-sections from annular dark field (ADF) STEM images can be estimated, has been investigated. The highest attainable precision is reached even for low dose images. Furthermore, the advantages of the model-based approach taking into account overlap between neighbouring columns are highlighted. This is done for the estimation of the distance between two neighbouring columns as a function of their distance and for the estimation of the scattering cross-section which is compared to the integrated intensity from a Voronoi cell. To provide end-users this well-established quantification method, a user friendly program, StatSTEM, is developed which is freely available under a GNU public license.
Je, U. K.; Cho, H. M.; Cho, H. S.; Park, Y. O.; Park, C. K.; Lim, H. W.; Kim, K. S.; Kim, G. A.; Park, S. Y.; Woo, T. H.; Choi, S. I.
2016-02-01
In this paper, we propose a new/next-generation type of CT examinations, the so-called Interior Computed Tomography (ICT), which may presumably lead to dose reduction to the patient outside the target region-of-interest (ROI), in dental x-ray imaging. Here an x-ray beam from each projection position covers only a relatively small ROI containing a target of diagnosis from the examined structure, leading to imaging benefits such as decreasing scatters and system cost as well as reducing imaging dose. We considered the compressed-sensing (CS) framework, rather than common filtered-backprojection (FBP)-based algorithms, for more accurate ICT reconstruction. We implemented a CS-based ICT algorithm and performed a systematic simulation to investigate the imaging characteristics. Simulation conditions of two ROI ratios of 0.28 and 0.14 between the target and the whole phantom sizes and four projection numbers of 360, 180, 90, and 45 were tested. We successfully reconstructed ICT images of substantially high image quality by using the CS framework even with few-view projection data, still preserving sharp edges in the images.
Jitaru, Petru, E-mail: Petru.Jitaru@lne.fr [Laboratoire National de Metrologie et d' Essais (LNE), Department of Biomedical and Inorganic Chemistry, 1 rue Gaston Boissier, 75015 Paris (France); Goenaga-Infante, Heidi [LGC Limited, Queens Road, Teddington, TW11 OLY, Middlesex (United Kingdom); Vaslin-Reimann, Sophie; Fisicaro, Paola [Laboratoire National de Metrologie et d' Essais (LNE), Department of Biomedical and Inorganic Chemistry, 1 rue Gaston Boissier, 75015 Paris (France)
2010-01-11
In this paper, two different methods are for the first time systematically compared for the determination of selenium in human serum selenoalbumin (SeAlb). Firstly, SeAlb was enzymatically hydrolyzed and the resulting selenomethionine (SeMet) was quantified using species-specific isotope dilution (SSID) with reversed phase-HPLC (RP-HPLC) hyphenated to (collision/reaction cell) inductively coupled plasma-quadrupole mass spectrometry (CRC ICP-QMS). In order to assess the enzymatic hydrolysis yield, SeAlb was determined as an intact protein by affinity-HPLC (AF-HPLC) coupled to CRC ICP-QMS. Using this approach, glutathione peroxidase (GPx) and selenoprotein P (SelP) (the two selenoproteins present in serum) were also determined within the same chromatographic run. The levels of selenium associated with SeAlb in three serum materials, namely BCR-637, Seronorm level 1 and Seronorm level 2, obtained using both methods were in a good agreement. Verification of the absence of free SeMet, which interferes with the SeAlb determination (down to the amino acid level), in such materials was addressed by analyzing the fraction of GPx, partially purified by AF-HPLC, using RP-HPLC (GPx only) and size exclusion-HPLC (SE-HPLC) coupled to CRC ICP-QMS. The latter methodology was also used for the investigation of the presence of selenium species other than the selenoproteins in the (AF-HPLC) SelP and SeAlb fractions; the same selenium peaks were detected in both control and BCR-637 serum with a difference in age of ca. 12 years. It is also for the first time that the concentrations of selenium associated with SeAlb, GPx and SelP species in such commercially available serums (only certified or having indicative levels of total selenium content) are reported. Such indicative values can be used for reference purposes in future validation of speciation methods for selenium in human serum and/or inter-laboratory comparisons.
A computational intelligence approach to the Mars Precision Landing problem
Birge, Brian Kent, III
Various proposed Mars missions, such as the Mars Sample Return Mission (MRSR) and the Mars Smart Lander (MSL), require precise re-entry terminal position and velocity states. This is to achieve mission objectives including rendezvous with a previous landed mission, or reaching a particular geographic landmark. The current state of the art footprint is in the magnitude of kilometers. For this research a Mars Precision Landing is achieved with a landed footprint of no more than 100 meters, for a set of initial entry conditions representing worst guess dispersions. Obstacles to reducing the landed footprint include trajectory dispersions due to initial atmospheric entry conditions (entry angle, parachute deployment height, etc.), environment (wind, atmospheric density, etc.), parachute deployment dynamics, unavoidable injection error (propagated error from launch on), etc. Weather and atmospheric models have been developed. Three descent scenarios have been examined. First, terminal re-entry is achieved via a ballistic parachute with concurrent thrusting events while on the parachute, followed by a gravity turn. Second, terminal re-entry is achieved via a ballistic parachute followed by gravity turn to hover and then thrust vector to desired location. Third, a guided parafoil approach followed by vectored thrusting to reach terminal velocity is examined. The guided parafoil is determined to be the best architecture. The purpose of this study is to examine the feasibility of using a computational intelligence strategy to facilitate precision planetary re-entry, specifically to take an approach that is somewhat more intuitive and less rigid, and see where it leads. The test problems used for all research are variations on proposed Mars landing mission scenarios developed by NASA. A relatively recent method of evolutionary computation is Particle Swarm Optimization (PSO), which can be considered to be in the same general class as Genetic Algorithms. An improvement over
A computational toy model for shallow landslides: Molecular dynamics approach
Martelloni, Gianluca; Bagnoli, Franco; Massaro, Emanuele
2013-09-01
The aim of this paper is to propose a 2D computational algorithm for modeling the triggering and propagation of shallow landslides caused by rainfall. We used a molecular dynamics (MD) approach, similar to the discrete element method (DEM), that is suitable to model granular material and to observe the trajectory of a single particle, so to possibly identify its dynamical properties. We consider that the triggering of shallow landslides is caused by the decrease of the static friction along the sliding surface due to water infiltration by rainfall. Thence the triggering is caused by the two following conditions: (a) a threshold speed of the particles and (b) a condition on the static friction, between the particles and the slope surface, based on the Mohr-Coulomb failure criterion. The latter static condition is used in the geotechnical model to estimate the possibility of landslide triggering. The interaction force between particles is modeled, in the absence of experimental data, by means of a potential similar to the Lennard-Jones one. The viscosity is also introduced in the model and for a large range of values of the model's parameters, we observe a characteristic velocity pattern, with acceleration increments, typical of real landslides. The results of simulations are quite promising: the energy and time triggering distribution of local avalanches show a power law distribution, analogous to the observed Gutenberg-Richter and Omori power law distributions for earthquakes. Finally, it is possible to apply the method of the inverse surface displacement velocity [4] for predicting the failure time.
Ben Issaid, Chaouki
2017-07-28
When assessing the performance of the free space optical (FSO) communication systems, the outage probability encountered is generally very small, and thereby the use of nave Monte Carlo simulations becomes prohibitively expensive. To estimate these rare event probabilities, we propose in this work an importance sampling approach which is based on the exponential twisting technique to offer fast and accurate results. In fact, we consider a variety of turbulence regimes, and we investigate the outage probability of FSO communication systems, under a generalized pointing error model based on the Beckmann distribution, for both single and multihop scenarios. Selected numerical simulations are presented to show the accuracy and the efficiency of our approach compared to naive Monte Carlo.
Rybynok, V O; Kyriacou, P A [City University, London (United Kingdom)
2007-10-15
Diabetes is one of the biggest health challenges of the 21st century. The obesity epidemic, sedentary lifestyles and an ageing population mean prevalence of the condition is currently doubling every generation. Diabetes is associated with serious chronic ill health, disability and premature mortality. Long-term complications including heart disease, stroke, blindness, kidney disease and amputations, make the greatest contribution to the costs of diabetes care. Many of these long-term effects could be avoided with earlier, more effective monitoring and treatment. Currently, blood glucose can only be monitored through the use of invasive techniques. To date there is no widely accepted and readily available non-invasive monitoring technique to measure blood glucose despite the many attempts. This paper challenges one of the most difficult non-invasive monitoring techniques, that of blood glucose, and proposes a new novel approach that will enable the accurate, and calibration free estimation of glucose concentration in blood. This approach is based on spectroscopic techniques and a new adaptive modelling scheme. The theoretical implementation and the effectiveness of the adaptive modelling scheme for this application has been described and a detailed mathematical evaluation has been employed to prove that such a scheme has the capability of extracting accurately the concentration of glucose from a complex biological media.
Gesture Recognition by Computer Vision: An Integral Approach
Lichtenauer, J.F.
2009-01-01
The fundamental objective of this Ph.D. thesis is to gain more insight into what is involved in the practical application of a computer vision system, when the conditions of use cannot be controlled completely. The basic assumption is that research on isolated aspects of computer vision often leads
Computer Science Contests for Secondary School Students: Approaches to Classification
Wolfgang POHL
2006-04-01
Full Text Available The International Olympiad in Informatics currently provides a model which is imitated by the majority of contests for secondary school students in Informatics or Computer Science. However, the IOI model can be criticized, and alternative contest models exist. To support the discussion about contests in Computer Science, several dimensions for characterizing and classifying contests are suggested.
Gesture Recognition by Computer Vision: An Integral Approach
Lichtenauer, J.F.
2009-01-01
The fundamental objective of this Ph.D. thesis is to gain more insight into what is involved in the practical application of a computer vision system, when the conditions of use cannot be controlled completely. The basic assumption is that research on isolated aspects of computer vision often leads
Overview of Computer Simulation Modeling Approaches and Methods
Robert E. Manning; Robert M. Itami; David N. Cole; Randy Gimblett
2005-01-01
The field of simulation modeling has grown greatly with recent advances in computer hardware and software. Much of this work has involved large scientific and industrial applications for which substantial financial resources are available. However, advances in object-oriented programming and simulation methodology, concurrent with dramatic increases in computer...
Riviere, Jim E.; Scoglio, Caterina; Sahneh, Faryad D.; Monteiro-Riviere, Nancy A.
2013-01-01
The field of nanomaterial pharmacokinetics is in its infancy, with major advances largely restricted by a lack of biologically relevant metrics, fundamental differences between particles and small molecules of organic chemicals and drugs relative to biological processes involved in disposition, a scarcity of sufficiently rich and characterized in vivo data and a lack of computational approaches to integrating nanomaterial properties to biological endpoints. A central concept that links nanomaterial properties to biological disposition, in addition to their colloidal properties, is the tendency to form a biocorona which modulates biological interactions including cellular uptake and biodistribution. Pharmacokinetic models must take this crucial process into consideration to accurately predict in vivo disposition, especially when extrapolating from laboratory animals to humans since allometric principles may not be applicable. The dynamics of corona formation, which modulates biological interactions including cellular uptake and biodistribution, is thereby a crucial process involved in the rate and extent of biodisposition. The challenge will be to develop a quantitative metric that characterizes a nanoparticle's surface adsorption forces that are important for predicting biocorona dynamics. These types of integrative quantitative approaches discussed in this paper for the dynamics of corona formation must be developed before realistic engineered nanomaterial risk assessment can be accomplished.
Discovery of novel hydrogen storage materials: an atomic scale computational approach.
Wolverton, C; Siegel, Donald J; Akbarzadeh, A R; Ozoliņš, V
2008-02-13
Practical hydrogen storage for mobile applications requires materials that exhibit high hydrogen densities, low decomposition temperatures, and fast kinetics for absorption and desorption. Unfortunately, no reversible materials are currently known that possess all of these attributes. Here we present an overview of our recent efforts aimed at developing a first-principles computational approach to the discovery of novel hydrogen storage materials. Such an approach requires several key capabilities to be effective: (i) accurate prediction of decomposition thermodynamics, (ii) prediction of crystal structures for unknown hydrides, and (iii) prediction of preferred decomposition pathways. We present examples that illustrate each of these three capabilities: (i) prediction of hydriding enthalpies and free energies across a wide range of hydride materials, (ii) prediction of low energy crystal structures for complex hydrides (such as Ca(AlH(4))(2) CaAlH(5), and Li(2)NH), and (iii) predicted decomposition pathways for Li(4)BN(3)H(10) and destabilized systems based on combinations of LiBH(4), Ca(BH(4))(2) and metal hydrides. For the destabilized systems, we propose a set of thermodynamic guidelines to help identify thermodynamically viable reactions. These capabilities have led to the prediction of several novel high density hydrogen storage materials and reactions.
Investigation of Stent Implant Mechanics Using Linear Analytical and Computational Approach.
Yang, Hua; Fortier, Aleksandra; Horne, Kyle; Mohammad, Atif; Banerjee, Subhash; Han, Hai-Chao
2017-03-01
Stent implants are essential in restoring normal blood flow in atherosclerotic arteries. Recent studies have shown high failure rates of stent implants in superficial femoral artery (SFA) as a result of dynamic loading environment imposed on the stent implants by the diseased arterial wall and turbulent blood flow. There are variety of stent designs and materials currently on the market however, there is no clear understanding if specific stent design is suitable with the material that is manufactured from and if this combination can sustain the life-cycle that the stent implants need to undergo once inside the artery. Lack of studies have been presented that relate stent mechanical properties with stent geometry and material used. This study presents linear theoretical and computational modeling approach that determines stent mechanical properties with effective stiffness of the deployed stent. Effective stiffness of the stent has been accurately derived based on stent structure design and loading in axial and radial directions. A rhombus stent structure was selected for this study due to its more common use and produced by main stream manufacturers. The derived theoretical model was validated using numerical finite element modeling approach. Results from this study can lead to preliminary insight towards understanding of stent deformation based on stent geometry, material properties and artery wall pressure; and how to carefully match stent's geometry with suitable material for long life cycle, increased strength, and reliable performance of stent implants.
Development of Computer Science Disciplines - A Social Network Analysis Approach
Pham, Manh Cuong; Jarke, Matthias
2011-01-01
In contrast to many other scientific disciplines, computer science considers conference publications. Conferences have the advantage of providing fast publication of papers and of bringing researchers together to present and discuss the paper with peers. Previous work on knowledge mapping focused on the map of all sciences or a particular domain based on ISI published JCR (Journal Citation Report). Although this data covers most of important journals, it lacks computer science conference and workshop proceedings. That results in an imprecise and incomplete analysis of the computer science knowledge. This paper presents an analysis on the computer science knowledge network constructed from all types of publications, aiming at providing a complete view of computer science research. Based on the combination of two important digital libraries (DBLP and CiteSeerX), we study the knowledge network created at journal/conference level using citation linkage, to identify the development of sub-disciplines. We investiga...
Heinz, Hendrik
2014-06-18
Adsorption of biomolecules and polymers to inorganic nanostructures plays a major role in the design of novel materials and therapeutics. The behavior of flexible molecules on solid surfaces at a scale of 1-1000 nm remains difficult and expensive to monitor using current laboratory techniques, while playing a critical role in energy conversion and composite materials as well as in understanding the origin of diseases. Approaches to implement key surface features and pH in molecular models of solids are explained, and distinct mechanisms of peptide recognition on metal nanostructures, silica and apatite surfaces in solution are described as illustrative examples. The influence of surface energies, specific surface features and protonation states on the structure of aqueous interfaces and selective biomolecular adsorption is found to be critical, comparable to the well-known influence of the charge state and pH of proteins and surfactants on their conformations and assembly. The representation of such details in molecular models according to experimental data and available chemical knowledge enables accurate simulations of unknown complex interfaces in atomic resolution in quantitative agreement with independent experimental measurements. In this context, the benefits of a uniform force field for all material classes and of a mineral surface structure database are discussed.
Development of a computationally efficient urban flood modelling approach
Wolfs, Vincent; Ntegeka, Victor; Murla, Damian
the developed methodology, a case study for the city of Ghent in Belgium is elaborated. The configured conceptual model mimics the flood levels of a detailed 1D-2D hydrodynamic InfoWorks ICM model accurately, while the calculation time is an order of magnitude of 106 times shorter than the original highly...
Computational approaches to predict bacteriophage-host relationships
Edwards, R.A.; McNair, K.; Faust, K.; Raes, J.; Dutilh, B.E.
2016-01-01
Metagenomics has changed the face of virus discovery by enabling the accurate identification of viral genome sequences without requiring isolation of the viruses. As a result, metagenomic virus discovery leaves the first and most fundamental question about any novel virus unanswered: What host does
Lowe, Jeremiah T; Testa, Edward J; Li, Xinning; Miller, Suzanne; DeAngelis, Joseph P; Jawa, Andrew
2017-04-01
Computed tomography (CT) scan is the standard for the preoperative assessment of glenoid version and morphology before total shoulder arthroplasty. However, the capacity of magnetic resonance imaging (MRI) to visualize bone morphology has improved with advancing technology. The purpose of this study was to compare the accuracy of MRI to CT for assessment of glenoid version and Walch classification. Three fellowship-trained shoulder surgeons assessed glenoid version and Walch classification of 30 patients with primary shoulder osteoarthritis who received both CT and MRI scans before total shoulder arthroplasty. Version measurements, Walch classification, and observer agreement were compared. Mean glenoid version was -15.5° and -18.6° by CT and MRI, respectively (P = .17). Interobserver reliability coefficients were good for both imaging modalities (CT, 0.73; MRI, 0.62). Intraobserver coefficients were good to excellent for CT (range, 0.76-0.87) and good for MRI (range, 0.75-0.79). For Walch classification, interobserver reliability for both modalities was merely fair, whereas intraobserver reliability was moderate to good. Although identification of type A1, A2, and B1 was nearly identical between CT and MRI, there was observer disagreement on type B2 (P = .001) and C glenoids (P = .03). Specifically, MRI underidentified type B2 and overidentified type C compared with CT. MRI is largely comparable to CT scan for evaluation of the glenoid, with similar measurements of version and identification of less extreme Walch glenoids. However, MRI is less accurate at distinguishing between type B2 and C glenoids. Copyright © 2017 Journal of Shoulder and Elbow Surgery Board of Trustees. Published by Elsevier Inc. All rights reserved.
Methodical Approaches to Teaching of Computer Modeling in Computer Science Course
Rakhimzhanova, B. Lyazzat; Issabayeva, N. Darazha; Khakimova, Tiyshtik; Bolyskhanova, J. Madina
2015-01-01
The purpose of this study was to justify of the formation technique of representation of modeling methodology at computer science lessons. The necessity of studying computer modeling is that the current trends of strengthening of general education and worldview functions of computer science define the necessity of additional research of the…
Gupta, Vipin; Kale, Amit; Sundar, Hari
2012-03-01
In this paper we propose a novel approach based on multi-stage random forests to address problems faced by traditional vessel segmentation algorithms on account of image artifacts such as stitches organ shadows etc.. Our approach consists of collecting a very large number of training data consisting of positive and negative examples of valid seed points. The method makes use of a 14x14 window around a putative seed point. For this window three types of feature vectors are computed viz. vesselness, eigenvalue and a novel effective margin feature. A random forest RF is trained for each of the feature vectors. At run time the three RFs are applied in succession to a putative seed point generated by a naiive vessel detection algorithm based on vesselness. Our approach will prune this set of putative seed points to correctly identify true seed points thereby avoiding false positives. We demonstrate the effectiveness of our algorithm on a large dataset of angio images.
A Human-Centred Tangible approach to learning Computational Thinking
Tommaso Turchi
2016-08-01
Full Text Available Computational Thinking has recently become a focus of many teaching and research domains; it encapsulates those thinking skills integral to solving complex problems using a computer, thus being widely applicable in our society. It is influencing research across many disciplines and also coming into the limelight of education, mostly thanks to public initiatives such as the Hour of Code. In this paper we present our arguments for promoting Computational Thinking in education through the Human-centred paradigm of Tangible End-User Development, namely by exploiting objects whose interactions with the physical environment are mapped to digital actions performed on the system.
Loss tolerant one-way quantum computation -- a horticultural approach
Varnava, M; Rudolph, T; Varnava, Michael; Browne, Daniel E.; Rudolph, Terry
2005-01-01
We introduce a scheme for fault tolerantly dealing with losses in cluster state computation that can tolerate up to 50% qubit loss. This is achieved passively - no coherent measurements or coherent correction is required. We then use this procedure within a specific linear optical quantum computation proposal to show that: (i) given perfect sources, detector inefficiencies of up to 50% can be tolerated and (ii) given perfect detectors, the purity of the photon source (overlap of the photonic wavefunction with the desired single mode) need only be greater than 66.6% for efficient computation to be possible.
An introduction to statistical computing a simulation-based approach
Voss, Jochen
2014-01-01
A comprehensive introduction to sampling-based methods in statistical computing The use of computers in mathematics and statistics has opened up a wide range of techniques for studying otherwise intractable problems. Sampling-based simulation techniques are now an invaluable tool for exploring statistical models. This book gives a comprehensive introduction to the exciting area of sampling-based methods. An Introduction to Statistical Computing introduces the classical topics of random number generation and Monte Carlo methods. It also includes some advanced met
Reflections on John Monaghan's "Computer Algebra, Instrumentation, and the Anthropological Approach"
Blume, Glen
2007-01-01
Reactions to John Monaghan's "Computer Algebra, Instrumentation and the Anthropological Approach" focus on a variety of issues related to the ergonomic approach (instrumentation) and anthropological approach to mathematical activity and practice. These include uses of the term technique; several possibilities for integration of the two approaches;…
Wolverton, Christopher [Northwestern Univ., Evanston, IL (United States). Dept. of Materials Science and Engineering; Ozolins, Vidvuds [Univ. of California, Los Angeles, CA (United States). Dept. of Materials Science and Engineering; Kung, Harold H. [Northwestern Univ., Evanston, IL (United States). Dept. of Chemical and Biological Engineering; Yang, Jun [Ford Scientific Research Lab., Dearborn, MI (United States); Hwang, Sonjong [California Inst. of Technology (CalTech), Pasadena, CA (United States). Dept. of Chemistry and Chemical Engineering; Shore, Sheldon [The Ohio State Univ., Columbus, OH (United States). Dept. of Chemistry and Biochemistry
2016-11-28
The objective of the proposed program is to discover novel mixed hydrides for hydrogen storage, which enable the DOE 2010 system-level goals. Our goal is to find a material that desorbs 8.5 wt.% H_{2} or more at temperatures below 85°C. The research program will combine first-principles calculations of reaction thermodynamics and kinetics with material and catalyst synthesis, testing, and characterization. We will combine materials from distinct categories (e.g., chemical and complex hydrides) to form novel multicomponent reactions. Systems to be studied include mixtures of complex hydrides and chemical hydrides [e.g. LiNH^{2+}NH_{3}BH_{3}] and nitrogen-hydrogen based borohydrides [e.g. Al(BH_{4})_{3}(NH_{3})_{3}]. The 2010 and 2015 FreedomCAR/DOE targets for hydrogen storage systems are very challenging, and cannot be met with existing materials. The vast majority of the work to date has delineated materials into various classes, e.g., complex and metal hydrides, chemical hydrides, and sorbents. However, very recent studies indicate that mixtures of storage materials, particularly mixtures between various classes, hold promise to achieve technological attributes that materials within an individual class cannot reach. Our project involves a systematic, rational approach to designing novel multicomponent mixtures of materials with fast hydrogenation/dehydrogenation kinetics and favorable thermodynamics using a combination of state-of-the-art scientific computing and experimentation. We will use the accurate predictive power of first-principles modeling to understand the thermodynamic and microscopic kinetic processes involved in hydrogen release and uptake and to design new material/catalyst systems with improved properties. Detailed characterization and atomic-scale catalysis experiments will elucidate the effect of dopants and nanoscale catalysts in achieving fast kinetics and reversibility. And
Parallel MMF: a Multiresolution Approach to Matrix Computation
Kondor, Risi; Teneva, Nedelina; Mudrakarta, Pramod K.
2015-01-01
Multiresolution Matrix Factorization (MMF) was recently introduced as a method for finding multiscale structure and defining wavelets on graphs/matrices. In this paper we derive pMMF, a parallel algorithm for computing the MMF factorization. Empirically, the running time of pMMF scales linearly in the dimension for sparse matrices. We argue that this makes pMMF a valuable new computational primitive in its own right, and present experiments on using pMMF for two distinct purposes: compressing...
AVES: A Computer Cluster System approach for INTEGRAL Scientific Analysis
Federici, M.; Martino, B. L.; Natalucci, L.; Umbertini, P.
The AVES computing system, based on an "Cluster" architecture is a fully integrated, low cost computing facility dedicated to the archiving and analysis of the INTEGRAL data. AVES is a modular system that uses the software resource manager (SLURM) and allows almost unlimited expandibility (65,536 nodes and hundreds of thousands of processors); actually is composed by 30 Personal Computers with Quad-Cores CPU able to reach the computing power of 300 Giga Flops (300x10{9} Floating point Operations Per Second), with 120 GB of RAM and 7.5 Tera Bytes (TB) of storage memory in UFS configuration plus 6 TB for users area. AVES was designed and built to solve growing problems raised from the analysis of the large data amount accumulated by the INTEGRAL mission (actually about 9 TB) and due to increase every year. The used analysis software is the OSA package, distributed by the ISDC in Geneva. This is a very complex package consisting of dozens of programs that can not be converted to parallel computing. To overcome this limitation we developed a series of programs to distribute the workload analysis on the various nodes making AVES automatically divide the analysis in N jobs sent to N cores. This solution thus produces a result similar to that obtained by the parallel computing configuration. In support of this we have developed tools that allow a flexible use of the scientific software and quality control of on-line data storing. The AVES software package is constituted by about 50 specific programs. Thus the whole computing time, compared to that provided by a Personal Computer with single processor, has been enhanced up to a factor 70.
Match and Move, an Approach to Data Parallel Computing
1992-10-01
Blelloch, Siddhartha Chatterjee, Jay Sippelstein, and Marco Zagha. CVL: a C Vector Library. School of Computer Science, Carnegie Mellon University...CBZ90] Siddhartha Chatterjee, Guy E. Blelloch, and Marco Zagha. Scan primitives for vector computers. In Proceedings Supercomputing , November 1990...Cha91] Siddhartha Chatterjee. Compiling data-parallel programs for efficient execution on shared-memory multiprocessors. PhD thesis, Carnegie Mellon
Computational challenges of structure-based approaches applied to HIV.
Forli, Stefano; Olson, Arthur J
2015-01-01
Here, we review some of the opportunities and challenges that we face in computational modeling of HIV therapeutic targets and structural biology, both in terms of methodology development and structure-based drug design (SBDD). Computational methods have provided fundamental support to HIV research since the initial structural studies, helping to unravel details of HIV biology. Computational models have proved to be a powerful tool to analyze and understand the impact of mutations and to overcome their structural and functional influence in drug resistance. With the availability of structural data, in silico experiments have been instrumental in exploiting and improving interactions between drugs and viral targets, such as HIV protease, reverse transcriptase, and integrase. Issues such as viral target dynamics and mutational variability, as well as the role of water and estimates of binding free energy in characterizing ligand interactions, are areas of active computational research. Ever-increasing computational resources and theoretical and algorithmic advances have played a significant role in progress to date, and we envision a continually expanding role for computational methods in our understanding of HIV biology and SBDD in the future.
S. Sofana Reka
2016-09-01
Full Text Available This paper proposes a cloud computing framework in smart grid environment by creating small integrated energy hub supporting real time computing for handling huge storage of data. A stochastic programming approach model is developed with cloud computing scheme for effective demand side management (DSM in smart grid. Simulation results are obtained using GUI interface and Gurobi optimizer in Matlab in order to reduce the electricity demand by creating energy networks in a smart hub approach.
Challenges and possible approaches: towards the petaflops computers
Depei QIAN; Danfeng ZHU
2009-01-01
In parallel with the R&D efforts in USA and Eu-rope, China's National High-tech R&D program has setup its goal in developing petaflops computers. Researchers and engineers world-wide are looking for appropriate methods and technologies to achieve the petaflops computer system. Based on discussion on important design issues in devel-oping the petafiops computer, this paper raises the major technological challenges including the memory wall, low power system design, interconnects, and programming sup-port, etc. Current efforts in addressing some of these chal-lenges and in pursuing possible solutions for developing the petaflops systems are presented. Several existing systems are briefly introduced as examples, including Roadrunner, Cray XT5 jaguar, Dawning 5000A/6000, and Lenovo DeepComp 7000. Architectures proposed by Chinese researchers for im-plementing the petaflops computer are also introduced. Ad-vantages of the architecture as well as the difficulties in its implementation are discussed. Finally, future research direc-tion in development of high productivity computing systems is discussed.
Hudson, Phillip S; White, Justin K; Kearns, Fiona L; Hodoscek, Milan; Boresch, Stefan; Lee Woodcock, H
2015-05-01
Accurately modeling condensed phase processes is one of computation's most difficult challenges. Include the possibility that conformational dynamics may be coupled to chemical reactions, where multiscale (i.e., QM/MM) methods are needed, and this task becomes even more daunting. Free energy simulations (i.e., molecular dynamics), multiscale modeling, and reweighting schemes. Herein, we present two new approaches for mitigating the aforementioned challenges. The first is a new chain-of-replica method (off-path simulations, OPS) for computing potentials of mean force (PMFs) along an easily defined reaction coordinate. This development is coupled with a new distributed, highly-parallel replica framework (REPDstr) within the CHARMM package. Validation of these new schemes is carried out on two processes that undergo conformational changes. First is the simple torsional rotation of butane, while a much more challenging glycosidic rotation (in vacuo and solvated) is the second. Additionally, a new approach that greatly improves (i.e., possibly an order of magnitude) the efficiency of computing QM/MM PMFs is introduced and compared to standard schemes. Our efforts are grounded in the recently developed method for efficiently computing QM-based free energies (i.e., QM-Non-Boltzmann Bennett, QM-NBB). Again, we validate this new technique by computing the QM/MM PMF of butane's torsional rotation. The OPS-REPDstr method is a promising new approach that overcomes many limitations of standard pathway simulations in CHARMM. The combination of QM-NBB with pathway techniques is very promising as it offers significant advantages over current procedures. Efficiently computing potentials of mean force is a major, unresolved, area of interest. This article is part of a Special Issue entitled Recent developments of molecular dynamics. Copyright © 2014. Published by Elsevier B.V.
The use of computational approaches in inhaler development.
Wong, William; Fletcher, David F; Traini, Daniela; Chan, Hak-Kim; Young, Paul M
2012-03-30
Computational Fluid Dynamics (CFD) and Discrete Element Modelling (DEM) studies relevant to inhaled drug delivery are reviewed. CFD is widely used in device design to determine airflow patterns and turbulence levels. CFD is also used to simulate particles and droplets, which are subjected to various forces, turbulence and wall interactions. These studies can now be performed routinely because of the availability of commercial software containing high quality turbulence and particle models. DEM allows for the modelling of agglomerate break-up upon interaction with a wall or due to shear in the flow. However, the computational cost is high and the number of particles that can be simulated is minimal compared with the number present in typical inhaled formulations. Therefore DEM is currently limited to fundamental studies of break-up mechanisms. With decreasing computational limitations, simulations combining CFD and DEM that can address outstanding issues in agglomerate break-up and dispersion will be possible.
Computer Mediated Learning: An Example of an Approach.
Arcavi, Abraham; Hadas, Nurit
2000-01-01
There are several possible approaches in which dynamic computerized environments play a significant and possibly unique role in supporting innovative learning trajectories in mathematics in general and geometry in particular. Describes an approach based on a problem situation and some experiences using it with students and teachers. (Contains 15…
Development of a computationally efficient urban modeling approach
Wolfs, Vincent; Murla, Damian; Ntegeka, Victor
2016-01-01
This paper presents a parsimonious and data-driven modelling approach to simulate urban floods. Flood levels simulated by detailed 1D-2D hydrodynamic models can be emulated using the presented conceptual modelling approach with a very short calculation time. In addition, the model detail can be a...
Hu, X.; Zhang, Y.
2007-05-01
The Weather Research and Forecast/Chemistry Model (WRF/Chem) that simulates chemistry simultaneously with meteorology has recently been developed for real-time forecasting by the U.S. National Center for Atmospheric Research (NCAR) and National Oceanic & Atmospheric Administration (NOAA). As one of the six air quality models, WRF/Chem with a modal aerosol module has been applied for ozone and PM2.5 ensemble forecasts over eastern North America as part of the 2004 New England Air Quality Study (NEAQS) program (NEAQS-2004). Significant differences exist in the partitioning of volatile species (e.g., ammonium and nitrate) simulated by the six models. Model biases are partially attributed to the equilibrium assumption used in the gas/particles mass transfer approach in some models. Development of a more accurate, yet computationally- efficient gas/particle mass transfer approach for three-dimensional (3-D) applications, in particular, real-time forecasting, is therefore warranted. Model of Aerosol Dynamics, Reaction, Ionization, and Dissolution (MADRID) has been implemented into WRF/Chem (referred to as WRF/Chem-MADRID). WRF/Chem-MADRID offers three gas/particle partitioning treatments: equilibrium, kinetic, and hybrid approaches. The equilibrium approach is computationally-efficient and commonly used in 3-D air quality models but less accurate under certain conditions (e.g., in the presence of coarse, reactive particles such as PM containing sea-salts in the coastal areas). The kinetic approach is accurate but computationally-expensive, limiting its 3-D applications. The hybrid approach attempts to provide a compromise between merits and drawbacks of the two approaches by treating fine PM (typically MADRID has recently been developed for 3-D applications based on an Analytical Predictor of Condensation (referred to as kinetic/APC). In this study, WRF/Chem-MADRID with the kinetic/APC approach will be further evaluated along with the equilibrium and hybrid approaches
Giner, Emmanuel; Tenti, Lorenzo; Angeli, Celestino; Ferré, Nicolas
2017-02-14
The present paper reports an original computational strategy for the computation of the isotropic hyperfine coupling constants (hcc). The algorithm proposed here is based on an approach recently introduced by some of the authors, namely, the first-order breathing orbital self-consistent field (FOBO-SCF). The approach is an almost parameter-free wave function method capable to accurately treat the spin delocalization together with the spin polarization effects while staying in a restricted formalism and avoiding spin contamination. The efficiency of the method is tested on a series of small radicals, among which four nitroxide radicals and the comparison with high-level ab initio methods show very encouraging results. On the basis of these results, the method is then applied to compute the hcc of a challenging system, namely, the DEPMPO-OOH radical in various conformations. The reference values obtained on such a large system allows us to validate a cheap computational method based on density functional theory (DFT). Another interesting feature of the model applied here is that it allows for the rationalization of the results according to a relatively simple scheme based on a two-step mechanism. More precisely, the results are analyzed in terms of two separated contributions: first the spin delocalization and then the spin polarization.
Zajenkowski, Marcin; Styla, Rafal; Szymanik, Jakub
2011-01-01
We compared the processing of natural language quantifiers in a group of patients with schizophrenia and a healthy control group. In both groups, the difficulty of the quantifiers was consistent with computational predictions, and patients with schizophrenia took more time to solve the problems. However, they were significantly less accurate only…
Simulation of quantum computation : A deterministic event-based approach
Michielsen, K; De Raedt, K; De Raedt, H
2005-01-01
We demonstrate that locally connected networks of machines that have primitive learning capabilities can be used to perform a deterministic, event-based simulation of quantum computation. We present simulation results for basic quantum operations such as the Hadamard and the controlled-NOT gate, and
Exploring polymorphism in molecular crystals with a computational approach
Ende, J.A. van den
2016-01-01
Different crystal structures can possess different properties and therefore the control of polymorphism in molecular crystals is a goal in multiple industries, e.g. the pharmaceutical industry. Part I of this thesis is a computational study at the molecular scale of a particular solid-solid polymorp
Linguistics, Computers, and the Language Teacher. A Communicative Approach.
Underwood, John H.
This analysis of the state of the art of computer programs and programming for language teaching has two parts. In the first part, an overview of the theory and practice of language teaching, Noam Chomsky's view of language, and the implications and problems of generative theory are presented. The theory behind the input model of language…
Individual Differences in Learning Computer Programming: A Social Cognitive Approach
Akar, Sacide Guzin Mazman; Altun, Arif
2017-01-01
The purpose of this study is to investigate and conceptualize the ranks of importance of social cognitive variables on university students' computer programming performances. Spatial ability, working memory, self-efficacy, gender, prior knowledge and the universities students attend were taken as variables to be analyzed. The study has been…
A Knowledge-Intensive Approach to Computer Vision Systems
Koenderink-Ketelaars, N.J.J.P.
2010-01-01
This thesis focusses on the modelling of knowledge-intensive computer vision tasks. Knowledge-intensive tasks are tasks that require a high level of expert knowledge to be performed successfully. Such tasks are generally performed by a task expert. Task experts have a lot of experience in performing
Exploring polymorphism in molecular crystals with a computational approach
Ende, J.A. van den
2016-01-01
Different crystal structures can possess different properties and therefore the control of polymorphism in molecular crystals is a goal in multiple industries, e.g. the pharmaceutical industry. Part I of this thesis is a computational study at the molecular scale of a particular solid-solid
Statistical Learning of Phonetic Categories: Insights from a Computational Approach
McMurray, Bob; Aslin, Richard N.; Toscano, Joseph C.
2009-01-01
Recent evidence (Maye, Werker & Gerken, 2002) suggests that statistical learning may be an important mechanism for the acquisition of phonetic categories in the infant's native language. We examined the sufficiency of this hypothesis and its implications for development by implementing a statistical learning mechanism in a computational model…
R for cloud computing an approach for data scientists
Ohri, A
2014-01-01
R for Cloud Computing looks at some of the tasks performed by business analysts on the desktop (PC era) and helps the user navigate the wealth of information in R and its 4000 packages as well as transition the same analytics using the cloud. With this information the reader can select both cloud vendors and the sometimes confusing cloud ecosystem as well as the R packages that can help process the analytical tasks with minimum effort and cost, and maximum usefulness and customization. The use of Graphical User Interfaces (GUI) and Step by Step screenshot tutorials is emphasized in this book to lessen the famous learning curve in learning R and some of the needless confusion created in cloud computing that hinders its widespread adoption. This will help you kick-start analytics on the cloud including chapters on cloud computing, R, common tasks performed in analytics, scrutiny of big data analytics, and setting up and navigating cloud providers. Readers are exposed to a breadth of cloud computing ch...
A New Approach: Computer-Assisted Problem-Solving Systems
Gok, Tolga
2010-01-01
Computer-assisted problem solving systems are rapidly growing in educational use and with the advent of the Internet. These systems allow students to do their homework and solve problems online with the help of programs like Blackboard, WebAssign and LON-CAPA program etc. There are benefits and drawbacks of these systems. In this study, the…
Affective brain-computer interfaces: neuroscientific approaches to affect detection
Mühl, C.; Heylen, Dirk K.J.; Nijholt, Antinus; Calvo, Rafael; D'Mello, Sidney K.; Gratch, Jonathan; Kappas, Arvid
The brain is involved in the registration, evaluation, and representation of emotional events and in the subsequent planning and execution of appropriate actions. Novel interface technologies—so-called affective brain-computer interfaces (aBCI)—can use this rich neural information, occurring in
Linguistics, Computers, and the Language Teacher. A Communicative Approach.
Underwood, John H.
This analysis of the state of the art of computer programs and programming for language teaching has two parts. In the first part, an overview of the theory and practice of language teaching, Noam Chomsky's view of language, and the implications and problems of generative theory are presented. The theory behind the input model of language…
Nested Transactions: An Approach to Reliable Distributed Computing.
1981-04-01
Undoubtedly such universal use of computers and rapid exchange of information will have a dramatic impact: social , economic, and political. Distributed...level tiansaction, these committed inferiors are SLJ C.e’,ssfulI inferiors of the top-level transaction, too. Therefore q will indeed get a commint
Ko, Soon Heum [Linkoeping University, Linkoeping (Sweden); Kim, Na Yong; Nikitopoulos, Dimitris E.; Moldovan, Dorel [Louisiana State University, Baton Rouge (United States); Jha, Shantenu [Rutgers University, Piscataway (United States)
2014-01-15
Numerical approaches are presented to minimize the statistical errors inherently present due to finite sampling and the presence of thermal fluctuations in the molecular region of a hybrid computational fluid dynamics (CFD) - molecular dynamics (MD) flow solution. Near the fluid-solid interface the hybrid CFD-MD simulation approach provides a more accurate solution, especially in the presence of significant molecular-level phenomena, than the traditional continuum-based simulation techniques. It also involves less computational cost than the pure particle-based MD. Despite these advantages the hybrid CFD-MD methodology has been applied mostly in flow studies at high velocities, mainly because of the higher statistical errors associated with low velocities. As an alternative to the costly increase of the size of the MD region to decrease statistical errors, we investigate a few numerical approaches that reduce sampling noise of the solution at moderate-velocities. These methods are based on sampling of multiple simulation replicas and linear regression of multiple spatial/temporal samples. We discuss the advantages and disadvantages of each technique in the perspective of solution accuracy and computational cost.
James, Conrad D.; Schiess, Adrian B.; Howell, Jamie; Baca, Michael J.; Partridge, L. Donald; Finnegan, Patrick Sean; Wolfley, Steven L.; Dagel, Daryl James; Spahn, Olga Blum; Harper, Jason C.; Pohl, Kenneth Roy; Mickel, Patrick R.; Lohn, Andrew; Marinella, Matthew
2013-10-01
The human brain (volume=1200cm3) consumes 20W and is capable of performing > 10^16 operations/s. Current supercomputer technology has reached 1015 operations/s, yet it requires 1500m^3 and 3MW, giving the brain a 10^12 advantage in operations/s/W/cm^3. Thus, to reach exascale computation, two achievements are required: 1) improved understanding of computation in biological tissue, and 2) a paradigm shift towards neuromorphic computing where hardware circuits mimic properties of neural tissue. To address 1), we will interrogate corticostriatal networks in mouse brain tissue slices, specifically with regard to their frequency filtering capabilities as a function of input stimulus. To address 2), we will instantiate biological computing characteristics such as multi-bit storage into hardware devices with future computational and memory applications. Resistive memory devices will be modeled, designed, and fabricated in the MESA facility in consultation with our internal and external collaborators.
Design of new and potent diethyl thiobarbiturates as urease inhibitors: a computational approach.
Wadood, Abdul; Riaz, Muhammad; Mulk, Amir Ul; Khan, Momin; Haleem, Sobia Ahsan; Shams, Sulaiman; Gul, Sahib; Ahmed, Ayaz; Qasim, Muhammad; Ali, Farman; Ul-Haq, Zaheer
2014-01-01
Urease is an important enzyme both in agriculture and medicine research. Strategies based on urease inhibition is critically considered as the first line treatment of infections caused by urease producing bacteria. Since, urease possess agro-chemical and medicinal importance, thus, it is necessary to search for the novel compounds capable of inhibiting this enzyme. Several computational methods were employed to design novel and potent urease inhibitors in this work. First docking simulations of known compounds consists of a set of arylidine barbiturates (termed as reference) were performed on the Bacillus pasteurii (BP) urease. Subsequently, two fold strategies were used to design new compounds against urease. Stage 1 comprised of the energy minimization of enzyme-ligand complexes of reference compounds and the accurate prediction of the molecular mechanics generalized born (MMGB) interaction energies. In the second stage, new urease inhibitors were then designed by the substitution of different groups consecutively in the aryl ring of the thiobarbiturates and N, N-diethyl thiobarbiturates of the reference ligands.. The enzyme-ligand complexes with lowest interaction energies or energies close to the calculated interaction energies of the reference molecules, were selected for the consequent chemical manipulation. This was followed by the substitution of different groups on the 2 and 5 positions of the aryl ring. As a result, several new and potent diethyl thiobarbiturates were predicted as urease inhibitors. This approach reflects a logical progression for early stage drug discovery that can be exploited to successfully identify potential drug candidates.
Computing pKa Values with a Mixing Hamiltonian Quantum Mechanical/Molecular Mechanical Approach.
Liu, Yang; Fan, Xiaoli; Jin, Yingdi; Hu, Xiangqian; Hu, Hao
2013-09-10
Accurate computation of the pKa value of a compound in solution is important but challenging. Here, a new mixing quantum mechanical/molecular mechanical (QM/MM) Hamiltonian method is developed to simulate the free-energy change associated with the protonation/deprotonation processes in solution. The mixing Hamiltonian method is designed for efficient quantum mechanical free-energy simulations by alchemically varying the nuclear potential, i.e., the nuclear charge of the transforming nucleus. In pKa calculation, the charge on the proton is varied in fraction between 0 and 1, corresponding to the fully deprotonated and protonated states, respectively. Inspired by the mixing potential QM/MM free energy simulation method developed previously [H. Hu and W. T. Yang, J. Chem. Phys. 2005, 123, 041102], this method succeeds many advantages of a large class of λ-coupled free-energy simulation methods and the linear combination of atomic potential approach. Theory and technique details of this method, along with the calculation results of the pKa of methanol and methanethiol molecules in aqueous solution, are reported. The results show satisfactory agreement with the experimental data.
Simon Boitard
2016-03-01
Full Text Available Inferring the ancestral dynamics of effective population size is a long-standing question in population genetics, which can now be tackled much more accurately thanks to the massive genomic data available in many species. Several promising methods that take advantage of whole-genome sequences have been recently developed in this context. However, they can only be applied to rather small samples, which limits their ability to estimate recent population size history. Besides, they can be very sensitive to sequencing or phasing errors. Here we introduce a new approximate Bayesian computation approach named PopSizeABC that allows estimating the evolution of the effective population size through time, using a large sample of complete genomes. This sample is summarized using the folded allele frequency spectrum and the average zygotic linkage disequilibrium at different bins of physical distance, two classes of statistics that are widely used in population genetics and can be easily computed from unphased and unpolarized SNP data. Our approach provides accurate estimations of past population sizes, from the very first generations before present back to the expected time to the most recent common ancestor of the sample, as shown by simulations under a wide range of demographic scenarios. When applied to samples of 15 or 25 complete genomes in four cattle breeds (Angus, Fleckvieh, Holstein and Jersey, PopSizeABC revealed a series of population declines, related to historical events such as domestication or modern breed creation. We further highlight that our approach is robust to sequencing errors, provided summary statistics are computed from SNPs with common alleles.
Computational morphology a computational geometric approach to the analysis of form
Toussaint, GT
1988-01-01
Computational Geometry is a new discipline of computer science that deals with the design and analysis of algorithms for solving geometric problems. There are many areas of study in different disciplines which, while being of a geometric nature, have as their main component the extraction of a description of the shape or form of the input data. This notion is more imprecise and subjective than pure geometry. Such fields include cluster analysis in statistics, computer vision and pattern recognition, and the measurement of form and form-change in such areas as stereology and developmental biolo
Computational Approaches for Probing the Formation of Atmospheric Molecular Clusters
Elm, Jonas
This thesis presents the investigation of atmospheric molecular clusters using computational methods. Previous investigations have focused on solving problems related to atmospheric nucleation, and have not been targeted at the performance of the applied methods. This thesis focuses on assessing...... the performance of computational strategies in order to identify a sturdy methodology, which should be applicable for handling various issues related to atmospheric cluster formation. Density functional theory (DFT) is applied to study individual cluster formation steps. Utilizing large test sets of numerous...... and pinic acid) for atmospheric cluster formation. Glycine is found to have a similar potential as ammonia in enhancing atmospheric nucleation. Pinic acid molecules form favourable clusters with sulfuric acid, but with formation free energies which are too low to explain observed nucleation rates. Pinic...
TOWARD HIGHLY SECURE AND AUTONOMIC COMPUTING SYSTEMS: A HIERARCHICAL APPROACH
Lee, Hsien-Hsin S
2010-05-11
The overall objective of this research project is to develop novel architectural techniques as well as system software to achieve a highly secure and intrusion-tolerant computing system. Such system will be autonomous, self-adapting, introspective, with self-healing capability under the circumstances of improper operations, abnormal workloads, and malicious attacks. The scope of this research includes: (1) System-wide, unified introspection techniques for autonomic systems, (2) Secure information-flow microarchitecture, (3) Memory-centric security architecture, (4) Authentication control and its implication to security, (5) Digital right management, (5) Microarchitectural denial-of-service attacks on shared resources. During the period of the project, we developed several architectural techniques and system software for achieving a robust, secure, and reliable computing system toward our goal.
Computational Model of Music Sight Reading: A Reinforcement Learning Approach
Yahya, Keyvan
2010-01-01
Although the Music Sight Reading process usually has been studied from the cognitive or neurological view points, but the computational learning methods like the Reinforcement Learning have not yet been used to modeling of such processes. In this paper with regards to essential properties of our specific problem, we consider the value function concept and will indicate that the optimum policy can be obtained by the method we offer without to be getting involved with computing of the complex value functions which are in most of cases inexact. Also, the algorithm we will offer here is somehow a PDE based algorithm which is associated with a stochastic optimization programming and we consider that in this case, this one is more applicable than the normative algorithms like temporal difference method.
Distance Based Asynchronous Recovery Approach In Mobile Computing Environment
Yogita Khatri,
2012-06-01
Full Text Available A mobile computing system is a distributed system in which at least one of the processes is mobile. They are constrained by lack of stable storage, low network bandwidth, mobility, frequent disconnection andlimited battery life. Checkpointing is one of the commonly used techniques to provide fault tolerance in mobile computing environment. In order to suit the mobile environment a distance based recovery schemeis proposed which is based on checkpointing and message logging. After the system recovers from failures, only the failed processes rollback and restart from their respective recent checkpoints, independent of the others. The salient feature of this scheme is to reduce the transfer and recovery cost. While the mobile host moves with in a specific range, recovery information is not moved and thus only be transferred nearby if the mobile host moves out of certain range.
Analysis of diabetic retinopathy biomarker VEGF gene by computational approaches
Jayashree Sadasivam; Ramesh, N.; K. Vijayalakshmi; Vinni Viridi; Shiva prasad
2012-01-01
Diabetic retinopathy, the most common diabetic eye disease, is caused by changes in the blood vessels of the retina which remains the major cause. It is characterized by vascular permeability and increased tissue ischemia and angiogenesis. One of the biomarker for Diabetic retinopathy has been identified as Vascular Endothelial Growth Factor ( VEGF )gene by computational analysis. VEGF is a sub-family of growth factors, the platelet-derived growth factor family of cystine-knot growth factors...
Modeling Cu2+-Aβ complexes from computational approaches
Alí-Torres, Jorge; Mirats, Andrea; Maréchal, Jean-Didier; Rodríguez-Santiago, Luis; Sodupe, Mariona
2015-09-01
Amyloid plaques formation and oxidative stress are two key events in the pathology of the Alzheimer disease (AD), in which metal cations have been shown to play an important role. In particular, the interaction of the redox active Cu2+ metal cation with Aβ has been found to interfere in amyloid aggregation and to lead to reactive oxygen species (ROS). A detailed knowledge of the electronic and molecular structure of Cu2+-Aβ complexes is thus important to get a better understanding of the role of these complexes in the development and progression of the AD disease. The computational treatment of these systems requires a combination of several available computational methodologies, because two fundamental aspects have to be addressed: the metal coordination sphere and the conformation adopted by the peptide upon copper binding. In this paper we review the main computational strategies used to deal with the Cu2+-Aβ coordination and build plausible Cu2+-Aβ models that will afterwards allow determining physicochemical properties of interest, such as their redox potential.
Modeling Cu2+-Aβ complexes from computational approaches
Jorge Alí-Torres
2015-09-01
Full Text Available Amyloid plaques formation and oxidative stress are two key events in the pathology of the Alzheimer disease (AD, in which metal cations have been shown to play an important role. In particular, the interaction of the redox active Cu2+ metal cation with Aβ has been found to interfere in amyloid aggregation and to lead to reactive oxygen species (ROS. A detailed knowledge of the electronic and molecular structure of Cu2+-Aβ complexes is thus important to get a better understanding of the role of these complexes in the development and progression of the AD disease. The computational treatment of these systems requires a combination of several available computational methodologies, because two fundamental aspects have to be addressed: the metal coordination sphere and the conformation adopted by the peptide upon copper binding. In this paper we review the main computational strategies used to deal with the Cu2+-Aβ coordination and build plausible Cu2+-Aβ models that will afterwards allow determining physicochemical properties of interest, such as their redox potential.
Modeling Cu{sup 2+}-Aβ complexes from computational approaches
Alí-Torres, Jorge [Departamento de Química, Universidad Nacional de Colombia- Sede Bogotá, 111321 (Colombia); Mirats, Andrea; Maréchal, Jean-Didier; Rodríguez-Santiago, Luis; Sodupe, Mariona, E-mail: Mariona.Sodupe@uab.cat [Departament de Química, Universitat Autònoma de Barcelona, 08193 Bellaterra, Barcelona (Spain)
2015-09-15
Amyloid plaques formation and oxidative stress are two key events in the pathology of the Alzheimer disease (AD), in which metal cations have been shown to play an important role. In particular, the interaction of the redox active Cu{sup 2+} metal cation with Aβ has been found to interfere in amyloid aggregation and to lead to reactive oxygen species (ROS). A detailed knowledge of the electronic and molecular structure of Cu{sup 2+}-Aβ complexes is thus important to get a better understanding of the role of these complexes in the development and progression of the AD disease. The computational treatment of these systems requires a combination of several available computational methodologies, because two fundamental aspects have to be addressed: the metal coordination sphere and the conformation adopted by the peptide upon copper binding. In this paper we review the main computational strategies used to deal with the Cu{sup 2+}-Aβ coordination and build plausible Cu{sup 2+}-Aβ models that will afterwards allow determining physicochemical properties of interest, such as their redox potential.
Pancreatic trauma: The role of computed tomography for guiding therapeutic approach
Marco; Moschetta; Michele; Telegrafo; Valeria; Malagnino; Laura; Mappa; Amato; A; Stabile; Ianora; Dario; Dabbicco; Antonio; Margari; Giuseppe; Angelelli
2015-01-01
AIM: To evaluate the role of computed tomography(CT) for diagnosing traumatic injuries of the pancreas and guiding the therapeutic approach.METHODS: CT exams of 6740 patients admitted to our Emergency Department between May 2005 and January 2013 for abdominal trauma were retrospectively evaluated. Patients were identified through a search of our electronic archive system by using such terms as "pancreatic injury", "pancreatic contusion", "pancreatic laceration", "peri-pancreatic fluid", "pancreatic active bleeding". All CT examinations were performed before and after the intravenous injection of contrast material using a 16-slice multidetector row computed tomography scanner. The data sets were retrospectively analyzed by two radiologists in consensus searching for specific signs of pancreatic injury(parenchymal fracture and laceration, focal or diffuse pancreatic enlargement/edema, pancreatic hematoma, active bleeding, fluid between splenic vein and pancreas) and non-specific signs(inflammatory changes in peri-pancreatic fat and mesentery, fluid surrounding the superior mesentericartery, thickening of the left anterior renal fascia, pancreatic ductal dilatation, acute pseudocyst formation/peri-pancreatic fluid collection, fluid in the anterior and posterior pararenal spaces, fluid in transverse mesocolon and lesser sac, hemorrhage into peri-pancreatic fat, mesocolon and mesentery, extraperitoneal fluid, intraperitoneal fluid).RESULTS: One hundred and thirty-six/Six thousand seven hundred and forty(2%) patients showed CT signs of pancreatic trauma. Eight/one hundred and thirty-six(6%) patients underwent surgical treatment and the pancreatic injures were confirmed in all cases. Only in 6/8 patients treated with surgical approach, pancreatic duct damage was suggested in the radiological reports and surgically confirmed in all cases. In 128/136(94%) patients who underwent non-operative treatment CT images showed pancreatic edema in 97 patients, hematoma in 31 patients
A Computer Vision Approach to Object Tracking and Counting
Sergiu Mezei
2010-09-01
Full Text Available This paper, introduces a new method for counting people or more generally objects that enter or exit a certain area/building or perimeter. We propose an algorithm (method that analyzes a video sequence, detects moving objects and their moving direction and filters them according to some criteria (ex only humans. As result one obtains in and out counters for objects passing the defined perimeter. Automatic object counting is a growing size application in many industry/commerce areas. Counting can be used in statistical analysis and optimal activity scheduling methods. One of the main applications is the approximation of the number of persons passing trough, or reaching a certain area: airports (customs, shopping centers and malls and sports or cultural activities with high attendance. The main purpose is to offer an accurate estimation while still keeping the anonymity of the visitors.
Computational Approach to Diarylprolinol-Silyl Ethers in Aminocatalysis.
Halskov, Kim Søholm; Donslund, Bjarke S; Paz, Bruno Matos; Jørgensen, Karl Anker
2016-05-17
Asymmetric organocatalysis has witnessed a remarkable development since its "re-birth" in the beginning of the millenium. In this rapidly growing field, computational investigations have proven to be an important contribution for the elucidation of mechanisms and rationalizations of the stereochemical outcomes of many of the reaction concepts developed. The improved understanding of mechanistic details has facilitated the further advancement of the field. The diarylprolinol-silyl ethers have since their introduction been one of the most applied catalysts in asymmetric aminocatalysis due to their robustness and generality. Although aminocatalytic methods at first glance appear to follow relatively simple mechanistic principles, more comprehensive computational studies have shown that this notion in some cases is deceiving and that more complex pathways might be operating. In this Account, the application of density functional theory (DFT) and other computational methods on systems catalyzed by the diarylprolinol-silyl ethers is described. It will be illustrated how computational investigations have shed light on the structure and reactivity of important intermediates in aminocatalysis, such as enamines and iminium ions formed from aldehydes and α,β-unsaturated aldehydes, respectively. Enamine and iminium ion catalysis can be classified as HOMO-raising and LUMO-lowering activation modes. In these systems, the exclusive reactivity through one of the possible intermediates is often a requisite for achieving high stereoselectivity; therefore, the appreciation of subtle energy differences has been vital for the efficient development of new stereoselective reactions. The diarylprolinol-silyl ethers have also allowed for novel activation modes for unsaturated aldehydes, which have opened up avenues for the development of new remote functionalization reactions of poly-unsaturated carbonyl compounds via di-, tri-, and tetraenamine intermediates and vinylogous iminium ions
Tucker, Laura Jane
Under the harsh conditions of limited nutrient and hard growth surface, Paenibacillus dendritiformis in agar plates form two classes of patterns (morphotypes). The first class, called the dendritic morphotype, has radially directed branches. The second class, called the chiral morphotype, exhibits uniform handedness. The dendritic morphotype has been modeled successfully using a continuum model on a regular lattice; however, a suitable computational approach was not known to solve a continuum chiral model. This work details a new computational approach to solving the chiral continuum model of pattern formation in P. dendritiformis. The approach utilizes a random computational lattice and new methods for calculating certain derivative terms found in the model.
Computational approaches to metabolic engineering utilizing systems biology and synthetic biology.
Fong, Stephen S
2014-08-01
Metabolic engineering modifies cellular function to address various biochemical applications. Underlying metabolic engineering efforts are a host of tools and knowledge that are integrated to enable successful outcomes. Concurrent development of computational and experimental tools has enabled different approaches to metabolic engineering. One approach is to leverage knowledge and computational tools to prospectively predict designs to achieve the desired outcome. An alternative approach is to utilize combinatorial experimental tools to empirically explore the range of cellular function and to screen for desired traits. This mini-review focuses on computational systems biology and synthetic biology tools that can be used in combination for prospective in silico strain design.
A Computer Simulation Modeling Approach to Estimating Utility in Several Air Force Specialties
1992-05-01
AL-TR-1992-0006 AD-A252 322 /II" A COMPUTER SIMULATION MODELING A APPROACH TO ESTIMATING UTILITY IN R SEVERAL AIR FORCE SPECIALTIES M Brice M. Stone...I 2. REPORT DATE 3. REPORT TYPE AND DATES COVERED IU 1Q::l.n1 Umrjh 1100 4. TITLE AND SUBTITLE S. FUNDING NUMBERS A Computer Simulation Modeling Approach...I DTIC TAB 0 Unannounced 0 justificatlon- By Distribut On . Availability Codes Avai an /r Dist Special v A COMPUTER SIMULATION MODELING APPROACH TO
Computational approach for calculating bound states in quantum field theory
Lv, Q. Z.; Norris, S.; Brennan, R.; Stefanovich, E.; Su, Q.; Grobe, R.
2016-09-01
We propose a nonperturbative approach to calculate bound-state energies and wave functions for quantum field theoretical models. It is based on the direct diagonalization of the corresponding quantum field theoretical Hamiltonian in an effectively discretized and truncated Hilbert space. We illustrate this approach for a Yukawa-like interaction between fermions and bosons in one spatial dimension and show where it agrees with the traditional method based on the potential picture and where it deviates due to recoil and radiative corrections. This method permits us also to obtain some insight into the spatial characteristics of the distribution of the fermions in the ground state, such as the bremsstrahlung-induced widening.
Computer-aided diagnostic approach of dermoscopy images acquiring relevant features
Castillejos-Fernández, H.; Franco-Arcega, A.; López-Ortega, O.
2016-09-01
In skin cancer detection, automated analysis of borders, colors, and structures of a lesion relies upon an accurate segmentation process and it is an important first step in any Computer-Aided Diagnosis (CAD) system. However, irregular and disperse lesion borders, low contrast, artifacts in images and variety of colors within the interest region make the problem difficult. In this paper, we propose an efficient approach of automatic classification which considers specific lesion features. First, for the selection of lesion skin we employ the segmentation algorithm W-FCM.1 Then, in the feature extraction stage we consider several aspects: the area of the lesion, which is calculated by correlating axes and we calculate the specific the value of asymmetry in both axes. For color analysis we employ an ensemble of clusterers including K-Means, Fuzzy K-Means and Kohonep maps, all of which estimate the presence of one or more colors defined in ABCD rule and the values for each of the segmented colors. Another aspect to consider is the type of structures that appear in the lesion Those are defined by using the ell-known GLCM method. During the classification stage we compare several methods in order to define if the lesion is benign or malignant. An important contribution of the current approach in segmentation-classification problem resides in the use of information from all color channels together, as well as the measure of each color in the lesion and the axes correlation. The segmentation and classification measures have been performed using sensibility, specificity, accuracy and AUC metric over a set of dermoscopy images from ISDIS data set
A computational approach to chemical etiologies of diabetes
Audouze, Karine Marie Laure; Brunak, Søren; Grandjean, Philippe
2013-01-01
, and perfluorooctanoic acid. For these substances we integrated disease and pathway annotations on top of protein interactions to reveal possible pathogenetic pathways that deserve empirical testing. The approach is general and can address other public health concerns in addition to identifying diabetogenic chemicals...
Electromagnetic space-time crystals. II. Fractal computational approach
Borzdov, G. N.
2014-01-01
A fractal approach to numerical analysis of electromagnetic space-time crystals, created by three standing plane harmonic waves with mutually orthogonal phase planes and the same frequency, is presented. Finite models of electromagnetic crystals are introduced, which make possible to obtain various approximate solutions of the Dirac equation. A criterion for evaluating accuracy of these approximate solutions is suggested.
Electromagnetic space-time crystals. II. Fractal computational approach
2014-01-01
A fractal approach to numerical analysis of electromagnetic space-time crystals, created by three standing plane harmonic waves with mutually orthogonal phase planes and the same frequency, is presented. Finite models of electromagnetic crystals are introduced, which make possible to obtain various approximate solutions of the Dirac equation. A criterion for evaluating accuracy of these approximate solutions is suggested.
Synergy between experimental and computational approaches to homogeneous photoredox catalysis.
Demissie, Taye B; Hansen, Jørn H
2016-07-01
In this Frontiers article, we highlight how state-of-the-art density functional theory calculations can contribute to the field of homogeneous photoredox catalysis. We discuss challenges in the fields and potential solutions to be found at the interface between theory and experiment. The exciting opportunities and insights that can arise through such an interdisciplinary approach are highlighted.
Diffusive Wave Approximation to the Shallow Water Equations: Computational Approach
Collier, Nathan
2011-05-14
We discuss the use of time adaptivity applied to the one dimensional diffusive wave approximation to the shallow water equations. A simple and computationally economical error estimator is discussed which enables time-step size adaptivity. This robust adaptive time discretization corrects the initial time step size to achieve a user specified bound on the discretization error and allows time step size variations of several orders of magnitude. In particular, in the one dimensional results presented in this work feature a change of four orders of magnitudes for the time step over the entire simulation.
Essential algorithms a practical approach to computer algorithms
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
A computer simulation approach to measurement of human control strategy
Green, J.; Davenport, E. L.; Engler, H. F.; Sears, W. E., III
1982-01-01
Human control strategy is measured through use of a psychologically-based computer simulation which reflects a broader theory of control behavior. The simulation is called the human operator performance emulator, or HOPE. HOPE was designed to emulate control learning in a one-dimensional preview tracking task and to measure control strategy in that setting. When given a numerical representation of a track and information about current position in relation to that track, HOPE generates positions for a stick controlling the cursor to be moved along the track. In other words, HOPE generates control stick behavior corresponding to that which might be used by a person learning preview tracking.
Computer simulation modeling of abnormal behavior: a program approach.
Reilly, K D; Freese, M R; Rowe, P B
1984-07-01
A need for modeling abnormal behavior on a comprehensive, systematic basis exists. Computer modeling and simulation tools offer especially good opportunities to establish such a program of studies. Issues concern deciding which modeling tools to use, how to relate models to behavioral data, what level of modeling to employ, and how to articulate theory to facilitate such modeling. Four levels or types of modeling, two qualitative and two quantitative, are identified. Their properties are examined and interrelated to include illustrative applications to the study of abnormal behavior, with an emphasis on schizophrenia.
Efficient and accurate fragmentation methods.
Pruitt, Spencer R; Bertoni, Colleen; Brorsen, Kurt R; Gordon, Mark S
2014-09-16
Conspectus Three novel fragmentation methods that are available in the electronic structure program GAMESS (general atomic and molecular electronic structure system) are discussed in this Account. The fragment molecular orbital (FMO) method can be combined with any electronic structure method to perform accurate calculations on large molecular species with no reliance on capping atoms or empirical parameters. The FMO method is highly scalable and can take advantage of massively parallel computer systems. For example, the method has been shown to scale nearly linearly on up to 131 000 processor cores for calculations on large water clusters. There have been many applications of the FMO method to large molecular clusters, to biomolecules (e.g., proteins), and to materials that are used as heterogeneous catalysts. The effective fragment potential (EFP) method is a model potential approach that is fully derived from first principles and has no empirically fitted parameters. Consequently, an EFP can be generated for any molecule by a simple preparatory GAMESS calculation. The EFP method provides accurate descriptions of all types of intermolecular interactions, including Coulombic interactions, polarization/induction, exchange repulsion, dispersion, and charge transfer. The EFP method has been applied successfully to the study of liquid water, π-stacking in substituted benzenes and in DNA base pairs, solvent effects on positive and negative ions, electronic spectra and dynamics, non-adiabatic phenomena in electronic excited states, and nonlinear excited state properties. The effective fragment molecular orbital (EFMO) method is a merger of the FMO and EFP methods, in which interfragment interactions are described by the EFP potential, rather than the less accurate electrostatic potential. The use of EFP in this manner facilitates the use of a smaller value for the distance cut-off (Rcut). Rcut determines the distance at which EFP interactions replace fully quantum
A uniform approach for programming distributed heterogeneous computing systems.
Grasso, Ivan; Pellegrini, Simone; Cosenza, Biagio; Fahringer, Thomas
2014-12-01
Large-scale compute clusters of heterogeneous nodes equipped with multi-core CPUs and GPUs are getting increasingly popular in the scientific community. However, such systems require a combination of different programming paradigms making application development very challenging. In this article we introduce libWater, a library-based extension of the OpenCL programming model that simplifies the development of heterogeneous distributed applications. libWater consists of a simple interface, which is a transparent abstraction of the underlying distributed architecture, offering advanced features such as inter-context and inter-node device synchronization. It provides a runtime system which tracks dependency information enforced by event synchronization to dynamically build a DAG of commands, on which we automatically apply two optimizations: collective communication pattern detection and device-host-device copy removal. We assess libWater's performance in three compute clusters available from the Vienna Scientific Cluster, the Barcelona Supercomputing Center and the University of Innsbruck, demonstrating improved performance and scaling with different test applications and configurations.
Cognitive control in majority search: A computational modeling approach
Hongbin eWang
2011-02-01
Full Text Available Despite the importance of cognitive control in many cognitive tasks involving uncertainty, the computational mechanisms of cognitive control in response to uncertainty remain unclear. In this study, we develop biologically realistic neural network models to investigate the instantiation of cognitive control in a majority function task, where one determines the category to which the majority of items in a group belong. Two models are constructed, both of which include the same set of modules representing task-relevant brain functions and share the same model structure. However, with a critical change of a model parameter setting, the two models implement two different underlying algorithms: one for grouping search (where a subgroup of items are sampled and re-sampled until a congruent sample is found and the other for self-terminating search (where the items are scanned and counted one-by-one until the majority is decided. The two algorithms hold distinct implications for the involvement of cognitive control. The modeling results show that while both models are able to perform the task, the grouping search model fit the human data better than the self-terminating search model. An examination of the dynamics underlying model performance reveals how cognitive control might be instantiated in the brain via the V4-ACC-LPFC-IPS loop for computing the majority function.
One-loop kink mass shifts: a computational approach
Alonso-Izquierdo, Alberto
2011-01-01
In this paper we develop a procedure to compute the one-loop quantum correction to the kink masses in generic (1+1)-dimensional one-component scalar field theoretical models. The procedure uses the generalized zeta function regularization method helped by the Gilkey-de Witt asymptotic expansion of the heat function via Mellin's transform. We find a formula for the one-loop kink mass shift that depends only on the part of the energy density with no field derivatives, evaluated by means of a symbolic software algorithm that automates the computation. The improved algorithm with respect to earlier work in this subject has been tested in the sine-Gordon and $\\lambda(\\phi)_2^4$ models. The quantum corrections of the sG-soliton and $\\lambda(\\phi^4)_2$-kink masses have been estimated with a relative error of 0.00006% and 0.00007% respectively. Thereafter, the algorithm is applied to other models. In particular, an interesting one-parametric family of double sine-Gordon models interpolating between the ordinary sine-...
Cognitive control in majority search: a computational modeling approach.
Wang, Hongbin; Liu, Xun; Fan, Jin
2011-01-01
Despite the importance of cognitive control in many cognitive tasks involving uncertainty, the computational mechanisms of cognitive control in response to uncertainty remain unclear. In this study, we develop biologically realistic neural network models to investigate the instantiation of cognitive control in a majority function task, where one determines the category to which the majority of items in a group belong. Two models are constructed, both of which include the same set of modules representing task-relevant brain functions and share the same model structure. However, with a critical change of a model parameter setting, the two models implement two different underlying algorithms: one for grouping search (where a subgroup of items are sampled and re-sampled until a congruent sample is found) and the other for self-terminating search (where the items are scanned and counted one-by-one until the majority is decided). The two algorithms hold distinct implications for the involvement of cognitive control. The modeling results show that while both models are able to perform the task, the grouping search model fit the human data better than the self-terminating search model. An examination of the dynamics underlying model performance reveals how cognitive control might be instantiated in the brain for computing the majority function.
A Hybrid Approach Towards Intrusion Detection Based on Artificial Immune System and Soft Computing
Sanyal, Sugata
2012-01-01
A number of works in the field of intrusion detection have been based on Artificial Immune System and Soft Computing. Artificial Immune System based approaches attempt to leverage the adaptability, error tolerance, self- monitoring and distributed nature of Human Immune Systems. Whereas Soft Computing based approaches are instrumental in developing fuzzy rule based systems for detecting intrusions. They are computationally intensive and apply machine learning (both supervised and unsupervised) techniques to detect intrusions in a given system. A combination of these two approaches could provide significant advantages for intrusion detection. In this paper we attempt to leverage the adaptability of Artificial Immune System and the computation intensive nature of Soft Computing to develop a system that can effectively detect intrusions in a given network.
A Computational Differential Geometry Approach to Grid Generation
Liseikin, Vladimir D
2007-01-01
The process of breaking up a physical domain into smaller sub-domains, known as meshing, facilitates the numerical solution of partial differential equations used to simulate physical systems. This monograph gives a detailed treatment of applications of geometric methods to advanced grid technology. It focuses on and describes a comprehensive approach based on the numerical solution of inverted Beltramian and diffusion equations with respect to monitor metrics for generating both structured and unstructured grids in domains and on surfaces. In this second edition the author takes a more detailed and practice-oriented approach towards explaining how to implement the method by: Employing geometric and numerical analyses of monitor metrics as the basis for developing efficient tools for controlling grid properties. Describing new grid generation codes based on finite differences for generating both structured and unstructured surface and domain grids. Providing examples of applications of the codes to the genera...
Model Convolution: A Computational Approach to Digital Image Interpretation
Gardner, Melissa K.; Sprague, Brian L.; Pearson, Chad G.; Cosgrove, Benjamin D.; Bicek, Andrew D.; Bloom, Kerry; Salmon, E. D.
2010-01-01
Digital fluorescence microscopy is commonly used to track individual proteins and their dynamics in living cells. However, extracting molecule-specific information from fluorescence images is often limited by the noise and blur intrinsic to the cell and the imaging system. Here we discuss a method called “model-convolution,” which uses experimentally measured noise and blur to simulate the process of imaging fluorescent proteins whose spatial distribution cannot be resolved. We then compare model-convolution to the more standard approach of experimental deconvolution. In some circumstances, standard experimental deconvolution approaches fail to yield the correct underlying fluorophore distribution. In these situations, model-convolution removes the uncertainty associated with deconvolution and therefore allows direct statistical comparison of experimental and theoretical data. Thus, if there are structural constraints on molecular organization, the model-convolution method better utilizes information gathered via fluorescence microscopy, and naturally integrates experiment and theory. PMID:20461132
A computational approach to handle complex microstructure geometries
Moës, Nicolas; Cloirec, Mathieu; Cartraud, Patrice; Remacle, Jean-François
2003-01-01
International audience; In multiscale analysis of components, there is usually a need to solve micro-structures with complex geometries. In this paper, we use the extended finite element method (X-FEM) to solve scales involving complex geometries. The X-FEM allows one to use meshes not necessarily matchingthe physical surface of the problem while retaining the accuracy of the classical finite element approach. For material interfaces, this is achieved by introducing a new enrichment strategy....
Chacón, Enrique, E-mail: echacon@icmm.csic.es [Instituto de Ciencia de Materiales de Madrid, CSIC, 28049 Madrid, Spain and Instituto de Ciencia de Materiales Nicolás Cabrera, Universidad Autónoma de Madrid, Madrid 28049 (Spain); Tarazona, Pedro, E-mail: pedro.tarazona@uam.es [Departamento de Física Teórica de la Materia Condensada, Condensed Matter Physics Center (IFIMAC), and Instituto de Ciencia de Materiales Nicolás Cabrera, Universidad Autónoma de Madrid, Madrid 28049 (Spain); Bresme, Fernando, E-mail: f.bresme@imperial.ac.uk [Department of Chemistry, Imperial College London, SW7 2AZ London (United Kingdom)
2015-07-21
We present a new computational approach to quantify the area per lipid and the area compressibility modulus of biological membranes. Our method relies on the analysis of the membrane fluctuations using our recently introduced coupled undulatory (CU) mode [Tarazona et al., J. Chem. Phys. 139, 094902 (2013)], which provides excellent estimates of the bending modulus of model membranes. Unlike the projected area, widely used in computer simulations of membranes, the CU area is thermodynamically consistent. This new area definition makes it possible to accurately estimate the area of the undulating bilayer, and the area per lipid, by excluding any contributions related to the phospholipid protrusions. We find that the area per phospholipid and the area compressibility modulus features a negligible dependence with system size, making possible their computation using truly small bilayers, involving a few hundred lipids. The area compressibility modulus obtained from the analysis of the CU area fluctuations is fully consistent with the Hooke’s law route. Unlike existing methods, our approach relies on a single simulation, and no a priori knowledge of the bending modulus is required. We illustrate our method by analyzing 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine bilayers using the coarse grained MARTINI force-field. The area per lipid and area compressibility modulus obtained with our method and the MARTINI forcefield are consistent with previous studies of these bilayers.
Environmental models are products of the computer architecture and software tools available at the time of development. Scientifically sound algorithms may persist in their original state even as system architectures and software development approaches evolve and progress. Dating...
Method in computer ethics: Towards a multi-level interdisciplinary approach
Brey, Philip
2000-01-01
This essay considers methodological aspects ofcomputer ethics and argues for a multi-levelinterdisciplinary approach with a central role forwhat is called disclosive computer ethics. Disclosivecomputer ethics is concerned with the moraldeciphering of embedded values and norms in computersystems, app
Environmental models are products of the computer architecture and software tools available at the time of development. Scientifically sound algorithms may persist in their original state even as system architectures and software development approaches evolve and progress. Dating...
Soft computing approach to pattern classification and object recognition a unified concept
Ray, Kumar S
2012-01-01
Soft Computing Approach to Pattern Classification and Object Recognition establishes an innovative, unified approach to supervised pattern classification and model-based occluded object recognition. The book also surveys various soft computing tools, fuzzy relational calculus (FRC), genetic algorithm (GA) and multilayer perceptron (MLP) to provide a strong foundation for the reader. The supervised approach to pattern classification and model-based approach to occluded object recognition are treated in one framework , one based on either a conventional interpretation or a new interpretation of
A computationally efficient approach for template matching-based image registration
Vilas H Gaidhane; Yogesh V Hote; Vijander Singh
2014-04-01
Image registration using template matching is an important step in image processing. In this paper, a simple, robust and computationally efficient approach is presented. The proposed approach is based on the properties of a normalized covariance matrix. The main advantage of the proposed approach is that the image matching can be achieved without calculating eigenvalues and eigenvectors of a covariance matrix, hence reduces the computational complexity. The experimental results show that the proposed approach performs better in the presence of various noises and rigid geometric transformations.
A computational approach to the twin paradox in curved spacetime
Fung, Kenneth K H; Lewis, Geraint F; Wu, Xiaofeng
2016-01-01
Despite being a major component in the teaching of special relativity, the twin `paradox' is generally not examined in courses on general relativity. Due to the complexity of analytical solutions to the problem, the paradox is often neglected entirely, and students are left with an incomplete understanding of the relativistic behaviour of time. This article outlines a project, undertaken by undergraduate physics students at the University of Sydney, in which a novel computational method was derived in order to predict the time experienced by a twin following a number of paths between two given spacetime coordinates. By utilising this method, it is possible to make clear to students that following a geodesic in curved spacetime does not always result in the greatest experienced proper time.
Computational Approaches for Modeling the Multiphysics in Pultrusion Process
Carlone, P.; Baran, Ismet; Hattel, Jesper Henri;
2013-01-01
Pultrusion is a continuousmanufacturing process used to produce high strength composite profiles with constant cross section.The mutual interactions between heat transfer, resin flow and cure reaction, variation in the material properties, and stress/distortion evolutions strongly affect...... the process dynamics together with the mechanical properties and the geometrical precision of the final product. In the present work, pultrusion process simulations are performed for a unidirectional (UD) graphite/epoxy composite rod including several processing physics, such as fluid flow, heat transfer......, chemical reaction, and solid mechanics. The pressure increase and the resin flow at the tapered inlet of the die are calculated by means of a computational fluid dynamics (CFD) finite volume model. Several models, based on different homogenization levels and solution schemes, are proposed and compared...
A Computational Approach to Politeness with Application to Social Factors
Danescu-Niculescu-Mizil, Cristian; Jurafsky, Dan; Leskovec, Jure; Potts, Christopher
2013-01-01
We propose a computational framework for identifying linguistic aspects of politeness. Our starting point is a new corpus of requests annotated for politeness, which we use to evaluate aspects of politeness theory and to uncover new interactions between politeness markers and context. These findings guide our construction of a classifier with domain-independent lexical and syntactic features operationalizing key components of politeness theory, such as indirection, deference, impersonalization and modality. Our classifier achieves close to human performance and is effective across domains. We use our framework to study the relationship between politeness and social power, showing that polite Wikipedia editors are more likely to achieve high status through elections, but, once elevated, they become less polite. We see a similar negative correlation between politeness and power on Stack Exchange, where users at the top of the reputation scale are less polite than those at the bottom. Finally, we apply our class...
A computational approach to the twin paradox in curved spacetime
Fung, Kenneth K. H.; Clark, Hamish A.; Lewis, Geraint F.; Wu, Xiaofeng
2016-09-01
Despite being a major component in the teaching of special relativity, the twin ‘paradox’ is generally not examined in courses on general relativity. Due to the complexity of analytical solutions to the problem, the paradox is often neglected entirely, and students are left with an incomplete understanding of the relativistic behaviour of time. This article outlines a project, undertaken by undergraduate physics students at the University of Sydney, in which a novel computational method was derived in order to predict the time experienced by a twin following a number of paths between two given spacetime coordinates. By utilising this method, it is possible to make clear to students that following a geodesic in curved spacetime does not always result in the greatest experienced proper time.
Crack Propagation in Honeycomb Cellular Materials: A Computational Approach
Marco Paggi
2012-02-01
Full Text Available Computational models based on the finite element method and linear or nonlinear fracture mechanics are herein proposed to study the mechanical response of functionally designed cellular components. It is demonstrated that, via a suitable tailoring of the properties of interfaces present in the meso- and micro-structures, the tensile strength can be substantially increased as compared to that of a standard polycrystalline material. Moreover, numerical examples regarding the structural response of these components when subjected to loading conditions typical of cutting operations are provided. As a general trend, the occurrence of tortuous crack paths is highly favorable: stable crack propagation can be achieved in case of critical crack growth, whereas an increased fatigue life can be obtained for a sub-critical crack propagation.
MADLVF: An Energy Efficient Resource Utilization Approach for Cloud Computing
J.K. Verma
2014-06-01
Full Text Available Last few decades have remained the witness of steeper growth in demand for higher computational power. It is merely due to shift from the industrial age to Information and Communication Technology (ICT age which was marginally the result of digital revolution. Such trend in demand caused establishment of large-scale data centers situated at geographically apart locations. These large-scale data centers consume a large amount of electrical energy which results into very high operating cost and large amount of carbon dioxide (CO2 emission due to resource underutilization. We propose MADLVF algorithm to overcome the problems such as resource underutilization, high energy consumption, and large CO2 emissions. Further, we present a comparative study between the proposed algorithm and MADRS algorithms showing proposed methodology outperforms over the existing one in terms of energy consumption and the number of VM migrations.
Computational approaches for efficiently modelling of small atmospheric clusters
Elm, Jonas; Mikkelsen, Kurt Valentin
2014-01-01
Utilizing a comprehensive test set of 205 clusters of atmospheric relevance, we investigate how different DFT functionals (M06-2X, PW91, ωB97X-D) and basis sets (6-311++G(3df,3pd), 6-31++G(d,p), 6-31+G(d)) affect the thermal contribution to the Gibbs free energy and single point energy. Reducing...... the basis set used in the geometry and frequency calculation from 6-311++G(3df,3pd) → 6-31++G(d,p) implies a significant speed-up in computational time and only leads to small errors in the thermal contribution to the Gibbs free energy and subsequent coupled cluster single point energy calculation....
Economic growth rate management by soft computing approach
Maksimović, Goran; Jović, Srđan; Jovanović, Radomir
2017-01-01
Economic growth rate management is very important process in order to improve the economic stability of any country. The main goal of the study was to manage the impact of agriculture, manufacturing, industry and services on the economic growth rate prediction. Soft computing methodology was used in order to select the inputs influence on the economic growth rate prediction. It is known that the economic growth may be developed on the basis of combination of different factors. Gross domestic product (GDP) was used as economic growth indicator. It was found services have the highest impact on the GDP growth rate. On the contrary, the manufacturing has the smallest impact on the GDP growth rate.
Perturbation approach for nuclear magnetic resonance solid-state quantum computation
G. P. Berman
2003-01-01
Full Text Available A dynamics of a nuclear-spin quantum computer with a large number (L=1000 of qubits is considered using a perturbation approach. Small parameters are introduced and used to compute the error in an implementation of an entanglement between remote qubits, using a sequence of radio-frequency pulses. The error is computed up to the different orders of the perturbation theory and tested using exact numerical solution.
Kerfriden, Pierre; Goury, Olivier; Khac Chi, Hoang; Bordas, Stéphane
2014-01-01
Computational homogenisation is a widely spread technique to calculate the overall properties of a composite material from the knowledge of the constitutive laws of its microscopic constituents [1, 2]. Indeed, it relies on fewer assumptions than analytical or semi-analytical homogenisation approaches and can be used to coarse-grain a large range of micro-mechanical models. However, this accuracy comes at large computational costs, which prevents computational homogenisation from b...
A Two Layer Approach to the Computability and Complexity of Real Functions
Lambov, Branimir Zdravkov
2003-01-01
We present a new model for computability and complexity of real functions together with an implementation that it based on it. The model uses a two-layer approach in which low-type basic objects perform the computation of a real function, but, whenever needed, can be complemented with higher type...... in computable analysis, while the efficiency of the implementation is not compromised by the need to create and maintain higher-type objects....
Smith, Jordan Ned; Carver, Zana A.; Weber, Thomas J.; Timchalk, Charles
2017-04-11
A combination experimental and computational approach was developed to predict chemical transport into saliva. A serous-acinar chemical transport assay was established to measure chemical transport with non-physiological (standard cell culture medium) and physiological (using surrogate plasma and saliva medium) conditions using 3,5,6-trichloro-2-pyridinol (TCPy) a metabolite of the pesticide chlorpyrifos. High levels of TCPy protein binding was observed in cell culture medium and rat plasma resulting in different TCPy transport behaviors in the two experimental conditions. In the non-physiological transport experiment, TCPy reached equilibrium at equivalent concentrations in apical and basolateral chambers. At higher TCPy doses, increased unbound TCPy was observed, and TCPy concentrations in apical and basolateral chambers reached equilibrium faster than lower doses, suggesting only unbound TCPy is able to cross the cellular monolayer. In the physiological experiment, TCPy transport was slower than non-physiological conditions, and equilibrium was achieved at different concentrations in apical and basolateral chambers at a comparable ratio (0.034) to what was previously measured in rats dosed with TCPy (saliva:blood ratio: 0.049). A cellular transport computational model was developed based on TCPy protein binding kinetics and accurately simulated all transport experiments using different permeability coefficients for the two experimental conditions (1.4 vs 0.4 cm/hr for non-physiological and physiological experiments, respectively). The computational model was integrated into a physiologically based pharmacokinetic (PBPK) model and accurately predicted TCPy concentrations in saliva of rats dosed with TCPy. Overall, this study demonstrates an approach to predict chemical transport in saliva potentially increasing the utility of salivary biomonitoring in the future.
Tsakonas, Athanasios; Dounias, Georgios; Jantzen, Jan
2001-01-01
The paper suggests the combined use of different computational intelligence (CI) techniques in a hybrid scheme, as an effective approach to medical diagnosis. Getting to know the advantages and disadvantages of each computational intelligence technique in the recent years, the time has come for p...
Data analysis of asymmetric structures advanced approaches in computational statistics
Saito, Takayuki
2004-01-01
Data Analysis of Asymmetric Structures provides a comprehensive presentation of a variety of models and theories for the analysis of asymmetry and its applications and provides a wealth of new approaches in every section. It meets both the practical and theoretical needs of research professionals across a wide range of disciplines and considers data analysis in fields such as psychology, sociology, social science, ecology, and marketing. In seven comprehensive chapters this guide details theories, methods, and models for the analysis of asymmetric structures in a variety of disciplines and presents future opportunities and challenges affecting research developments and business applications.
Safe manning of merchant ships: an approach and computer tool
Alapetite, Alexandre; Kozin, Igor
2017-01-01
In the shipping industry, staffing expenses have become a vital competition parameter. In this paper, an approach and a software tool are presented to support decisions on the staffing of merchant ships. The tool is implemented in the form of a Web user interface that makes use of discrete-event...... simulation and allows estimation of the workload and of whether different scenarios are successfully performed taking account of the number of crewmembers, watch schedules, distribution of competencies, and others. The software library ‘SimManning’ at the core of the project is provided as open source...
Canonical approach to finite density QCD with multiple precision computation
Fukuda, Ryutaro; Oka, Shotaro
2015-01-01
We calculate the baryon chemical potential ($\\mu_B$) dependence of thermodynamic observables, i.e., pressure, baryon number density and susceptibility by lattice QCD using the canonical approach. We compare the results with those by the multi parameter reweighting (MPR) method; Both methods give very consistent values in the regions where errors of the MPR are under control. The canonical method gives reliable results over $\\mu_ B/T=3$,with $T$ being temperature. Multiple precision operations play an important roll in the evaluation of canonical partition functions.
Kanda, Takashi; Fujita, Masashi; Iida, Osamu; Masuda, Masaharu; Okamoto, Shin; Ishihara, Takayuki; Nanto, Kiyonori; Shiraki, Tatsuya; Takahara, Mitsuyoshi; Sakata, Yasushi; Uematsu, Masaaki
2015-01-01
Several non-invasive methods for measuring pulmonary vascular resistance (PVR) have been proposed to date, but they remain empirical, lacking sufficient accuracy to be used in clinical practice. The aims of this study were to propose a novel echocardiographic measurement of PVR based on a theoretical formula and investigate the feasibilty and accuracy of this method in patients with heart failure. Echocardiography was performed in 27 patients before right heart catheterization. Peak tricuspid regurgitation pressure gradient (TRPG), pulmonary regurgitation pressure gradient in end-diastole (PRPGed), and cardiac output derived from the time-velocity integral and the diameter in the left ventricular outflow tract (COLVOT) were measured. PVR based on a theoretical formula (PVRtheo) was calculated as (TRPG-PRPGed)/3COLVOTin Wood units (WU). The results were compared with PVR obtained by right heart catheterization (PVRcath) using linear regression and Bland-Altman analysis. Mean PVRcathwas 2.4±1.4 WU. PVRtheocorrelated well with PVRcath(r=0.83, P<0.001). On Bland-Altman analysis the mean difference was 0.1±0.7 WU. The limits of agreements were smaller than for other non-invasive estimations previously reported. The new echocardiographic approach based on a theoretical formula provides a non-invasive and accurate assessment of PVR in patients with heart failure.
Granular computing and decision-making interactive and iterative approaches
Chen, Shyi-Ming
2015-01-01
This volume is devoted to interactive and iterative processes of decision-making– I2 Fuzzy Decision Making, in brief. Decision-making is inherently interactive. Fuzzy sets help realize human-machine communication in an efficient way by facilitating a two-way interaction in a friendly and transparent manner. Human-centric interaction is of paramount relevance as a leading guiding design principle of decision support systems. The volume provides the reader with an updated and in-depth material on the conceptually appealing and practically sound methodology and practice of I2 Fuzzy Decision Making. The book engages a wealth of methods of fuzzy sets and Granular Computing, brings new concepts, architectures and practice of fuzzy decision-making providing the reader with various application studies. The book is aimed at a broad audience of researchers and practitioners in numerous disciplines in which decision-making processes play a pivotal role and serve as a vehicle to produce solutions to existing prob...
Localized tissue mineralization regulated by bone remodelling: A computational approach
Decco, Oscar; Adams, George; Cook, Richard B.; García Aznar, José Manuel
2017-01-01
Bone is a living tissue whose main mechanical function is to provide stiffness, strength and protection to the body. Both stiffness and strength depend on the mineralization of the organic matrix, which is constantly being remodelled by the coordinated action of the bone multicellular units (BMUs). Due to the dynamics of both remodelling and mineralization, each sample of bone is composed of structural units (osteons in cortical and packets in cancellous bone) created at different times, therefore presenting different levels of mineral content. In this work, a computational model is used to understand the feedback between the remodelling and the mineralization processes under different load conditions and bone porosities. This model considers that osteoclasts primarily resorb those parts of bone closer to the surface, which are younger and less mineralized than older inner ones. Under equilibrium loads, results show that bone volumes with both the highest and the lowest levels of porosity (cancellous and cortical respectively) tend to develop higher levels of mineral content compared to volumes with intermediate porosity, thus presenting higher material densities. In good agreement with recent experimental measurements, a boomerang-like pattern emerges when plotting apparent density at the tissue level versus material density at the bone material level. Overload and disuse states are studied too, resulting in a translation of the apparent–material density curve. Numerical results are discussed pointing to potential clinical applications. PMID:28306746
Computational approaches to 3D modeling of RNA
Laing, Christian; Schlick, Tamar, E-mail: schlick@nyu.ed [Department of Chemistry and Courant Institute of Mathematical Sciences, New York University, 251 Mercer Street, New York, NY 10012 (United States)
2010-07-21
Many exciting discoveries have recently revealed the versatility of RNA and its importance in a variety of functions within the cell. Since the structural features of RNA are of major importance to their biological function, there is much interest in predicting RNA structure, either in free form or in interaction with various ligands, including proteins, metabolites and other molecules. In recent years, an increasing number of researchers have developed novel RNA algorithms for predicting RNA secondary and tertiary structures. In this review, we describe current experimental and computational advances and discuss recent ideas that are transforming the traditional view of RNA folding. To evaluate the performance of the most recent RNA 3D folding algorithms, we provide a comparative study in order to test the performance of available 3D structure prediction algorithms for an RNA data set of 43 structures of various lengths and motifs. We find that the algorithms vary widely in terms of prediction quality across different RNA lengths and topologies; most predictions have very large root mean square deviations from the experimental structure. We conclude by outlining some suggestions for future RNA folding research. (topical review)
How damaged brains repeat words: a computational approach.
Nozari, Nazbanou; Dell, Gary S
2013-09-01
Two routes have been proposed for auditory repetition: a lexical route which activates a lexical item and retrieves its phonology, and a nonlexical route which maps input phonology directly onto output phonology. But when is the nonlexical route recruited? In a sample of 103 aphasic patients, we use computational models to select patients who do and do not recruit the nonlexical route, and compare them in light of three hypotheses: 1 - Lexical-phonological hypothesis: when the lexical route is weak, the nonlexical route is recruited. 2 - Nonlexical hypothesis: when the nonlexical route is weak, it is abandoned. 3 - Semantic-access hypothesis: when access to meaning fails, the nonlexical route is recruited. In neurocognitive terms, hypotheses 1 and 2 identify different aspects of the intactness of the dorsal stream, while the third hypothesis focuses on the ventral stream. Our findings (and a subsequent meta-analysis of four studies) support hypotheses 2 and 3. Ultimately, we claim that the choice about whether to recruit the nonlexical route is guided, not by assessment of production abilities that support repetition, but instead by relying on accessible cues, namely whether the speaker understands the word, or can remember its sequence of phonemes. Copyright © 2013 Elsevier Inc. All rights reserved.
Strategic Cognitive Sequencing: A Computational Cognitive Neuroscience Approach
Seth A. Herd
2013-01-01
Full Text Available We address strategic cognitive sequencing, the “outer loop” of human cognition: how the brain decides what cognitive process to apply at a given moment to solve complex, multistep cognitive tasks. We argue that this topic has been neglected relative to its importance for systematic reasons but that recent work on how individual brain systems accomplish their computations has set the stage for productively addressing how brain regions coordinate over time to accomplish our most impressive thinking. We present four preliminary neural network models. The first addresses how the prefrontal cortex (PFC and basal ganglia (BG cooperate to perform trial-and-error learning of short sequences; the next, how several areas of PFC learn to make predictions of likely reward, and how this contributes to the BG making decisions at the level of strategies. The third models address how PFC, BG, parietal cortex, and hippocampus can work together to memorize sequences of cognitive actions from instruction (or “self-instruction”. The last shows how a constraint satisfaction process can find useful plans. The PFC maintains current and goal states and associates from both of these to find a “bridging” state, an abstract plan. We discuss how these processes could work together to produce strategic cognitive sequencing and discuss future directions in this area.
Flexibility and practicality graz brain-computer interface approach.
Scherer, Reinhold; Müller-Putz, Gernot R; Pfurtscheller, Gert
2009-01-01
"Graz brain-computer interface (BCI)" transforms changes in oscillatory electroencephalogram (EEG) activity into control signals for external devices and feedback. Steady-state evoked potentials (SSEPs) and event-related desynchronization (ERD) are employed to encode user messages. User-specific setup and training are important issues for robust and reliable classification. Furthermore, in order to implement small and thus affordable systems, focus is put on the minimization of the number of EEG sensors. The system also supports the self-paced operation mode, that is, users have on-demand access to the system at any time and can autonomously initiate communication. Flexibility, usability, and practicality are essential to increase user acceptance. Here, we illustrate the possibilities offered by now from EEG-based communication. Results of several studies with able-bodied and disabled individuals performed inside the laboratory and in real-world environments are presented; their characteristics are shown and open issues are mentioned. The applications include the control of neuroprostheses and spelling devices, the interaction with Virtual Reality, and the operation of off-the-shelf software such as Google Earth.
Non-racemic mixture model: a computational approach.
Polanco, Carlos; Buhse, Thomas
2017-01-01
The behavior of a slight chiral bias in favor of l-amino acids over d-amino acids was studied in an evolutionary mathematical model generating mixed chiral peptide hexamers. The simulations aimed to reproduce a very generalized prebiotic scenario involving a specified couple of amino acid enantiomers and a possible asymmetric amplification through autocatalytic peptide self-replication while forming small multimers of a defined length. Our simplified model allowed the observation of a small ascending but not conclusive tendency in the l-amino acid over the d-amino acid profile for the resulting mixed chiral hexamers in computer simulations of 100 peptide generations. This simulation was carried out by changing the chiral bias from 1% to 3%, in three stages of 15, 50 and 100 generations to observe any alteration that could mean a drastic change in behavior. So far, our simulations lead to the assumption that under the exposure of very slight non-racemic conditions, a significant bias between l- and d-amino acids, as present in our biosphere, was unlikely generated under prebiotic conditions if autocatalytic peptide self-replication was the main or the only driving force of chiral auto-amplification.
A computational toy model for shallow landslides: Molecular Dynamics approach
Martelloni, Gianluca; Massaro, Emanuele
2012-01-01
The aim of this paper is to propose a 2D computational algorithm for modeling of the trigger and the propagation of shallow landslides caused by rainfall. We used a Molecular Dynamics (MD) inspired model, similar to discrete element method (DEM), that is suitable to model granular material and to observe the trajectory of single particle, so to identify its dynamical properties. We consider that the triggering of shallow landslides is caused by the decrease of the static friction along the sliding surface due to water infiltration by rainfall. Thence the triggering is caused by two following conditions: (a) a threshold speed of the particles and (b) a condition on the static friction, between particles and slope surface, based on the Mohr-Coulomb failure criterion. The latter static condition is used in the geotechnical model to estimate the possibility of landslide triggering. Finally the interaction force between particles is defined trough a potential that, in the absence of experimental data, we have mode...
Fault-tolerant quantum computation -- a dynamical systems approach
Fern, J; Simic, S; Sastry, S; Fern, Jesse; Kempe, Julia; Simic, Slobodan; Sastry, Shankar
2004-01-01
We apply a dynamical systems approach to concatenation of quantum error correcting codes, extending and generalizing the results of Rahn et al. [8] to both diagonal and nondiagonal channels. Our point of view is global: instead of focusing on particular types of noise channels, we study the geometry of the coding map as a discrete-time dynamical system on the entire space of noise channels. In the case of diagonal channels, we show that any code with distance at least three corrects (in the infinite concatenation limit) an open set of errors. For CSS codes, we give a more precise characterization of that set. We show how to incorporate noise in the gates, thus completing the framework. We derive some general bounds for noise channels, which allows us to analyze several codes in detail.
Computational Approaches to Consecutive Pattern Avoidance in Permutations
Nakamura, Brian
2011-01-01
In recent years, there has been increasing interest in consecutive pattern avoidance in permutations. In this paper, we introduce two approaches to counting permutations that avoid a set of prescribed patterns consecutively. These algoritms have been implemented in the accompanying Maple package CAV, which can be downloaded from the author's website. As a byproduct of the first algorithm, we have a theorem giving a sufficient condition for when two pattern sets are strongly (consecutively) Wilf-Equivalent. For the implementation of the second algorithm, we define the cluster tail generating function and show that it always satisfies a certain functional equation. We also explain how the CAV package can be used to approximate asymptotic constants for single pattern avoidance.
A zero-dimensional approach to compute real radicals
Silke J. Spang
2008-04-01
Full Text Available The notion of real radicals is a fundamental tool in Real Algebraic Geometry. It takes the role of the radical ideal in Complex Algebraic Geometry. In this article I shall describe the zero-dimensional approach and efficiency improvement I have found during the work on my diploma thesis at the University of Kaiserslautern (cf. [6]. The main focus of this article is on maximal ideals and the properties they have to fulfil to be real. New theorems and properties about maximal ideals are introduced which yield an heuristic prepare_max which splits the maximal ideals into three classes, namely real, not real and the class where we can't be sure whether they are real or not. For the latter we have to apply a coordinate change into general position until we are sure about realness. Finally this constructs a randomized algorithm for real radicals. The underlying theorems and algorithms are described in detail.
Partial order approach to compute shortest paths in multimodal networks
Ensor, Andrew
2011-01-01
Many networked systems involve multiple modes of transport. Such systems are called multimodal, and examples include logistic networks, biomedical phenomena, manufacturing process and telecommunication networks. Existing techniques for determining optimal paths in multimodal networks have either required heuristics or else application-specific constraints to obtain tractable problems, removing the multimodal traits of the network during analysis. In this paper weighted coloured--edge graphs are introduced to model multimodal networks, where colours represent the modes of transportation. Optimal paths are selected using a partial order that compares the weights in each colour, resulting in a Pareto optimal set of shortest paths. This approach is shown to be tractable through experimental analyses for random and real multimodal networks without the need to apply heuristics or constraints.
Computer Mediated Social Network Approach to Software Support and Maintenance
2010-06-01
mathematics (Euler, 1741; Sachs, Stiebitz, & Wilson, 1988), philosophy ( Durkheim , 2001), the social science domain (Granovetter 1973; 1983; Milgram, 1967...to philosophy ( Durkheim , 2001), to the strength of the connections a (Granovetter 1973; Granovetter, 1983) and the number of connections (Milgram...Qualitative, quantitative, and mixed method approaches (Second ed.) Sage Publications Inc. Durkheim , É. (2001). The elementary forms of religious life, New
Moskon, Miha; Mraz, Miha
2014-01-01
We present several measures that can be used in de novo computational design of biological systems with information processing capabilities. Their main purpose is to objectively evaluate the behavior and identify the biological information processing structures with the best dynamical properties. They can be used to define constraints that allow one to simplify the design of more complex biological systems. These measures can be applied to existent computational design approaches in synthetic biology, i.e., rational and automatic design approaches. We demonstrate their use on a) the computational models of several basic information processing structures implemented with gene regulatory networks and b) on a modular design of a synchronous toggle switch.
Data science in R a case studies approach to computational reasoning and problem solving
Nolan, Deborah
2015-01-01
Effectively Access, Transform, Manipulate, Visualize, and Reason about Data and ComputationData Science in R: A Case Studies Approach to Computational Reasoning and Problem Solving illustrates the details involved in solving real computational problems encountered in data analysis. It reveals the dynamic and iterative process by which data analysts approach a problem and reason about different ways of implementing solutions. The book's collection of projects, comprehensive sample solutions, and follow-up exercises encompass practical topics pertaining to data processing, including: Non-standar
Wang, Mengyu; Brigham, John C.
2017-03-01
A computationally efficient gradient-based optimization approach for inverse material characterization from incomplete system response measurements that can utilize a generally applicable parameterization (e.g., finite element-type parameterization) is presented and evaluated. The key to this inverse characterization algorithm is the use of a direct inversion strategy with Gappy proper orthogonal decomposition (POD) response field estimation to initialize the inverse solution estimate prior to gradient-based optimization. Gappy POD is used to estimate the complete (i.e., all components over the entire spatial domain) system response field from incomplete (e.g., partial spatial distribution) measurements obtained from some type of system testing along with some amount of a priori information regarding the potential distribution of the unknown material property. The estimated complete system response is used within a physics-based direct inversion procedure with a finite element-type parameterization to estimate the spatial distribution of the desired unknown material property with minimal computational expense. Then, this estimated spatial distribution of the unknown material property is used to initialize a gradient-based optimization approach, which uses the adjoint method for computationally efficient gradient calculations, to produce the final estimate of the material property distribution. The three-step [(1) Gappy POD, (2) direct inversion, and (3) gradient-based optimization] inverse characterization approach is evaluated through simulated test problems based on the characterization of elastic modulus distributions with localized variations (e.g., inclusions) within simple structures. Overall, this inverse characterization approach is shown to efficiently and consistently provide accurate inverse characterization estimates for material property distributions from incomplete response field measurements. Moreover, the solution procedure is shown to be capable
Petra, Cosmin G.
2014-01-01
We present a scalable approach and implementation for solving stochastic optimization problems on high-performance computers. In this work we revisit the sparse linear algebra computations of the parallel solver PIPS with the goal of improving the shared-memory performance and decreasing the time to solution. These computations consist of solving sparse linear systems with multiple sparse right-hand sides and are needed in our Schur-complement decomposition approach to compute the contribution of each scenario to the Schur matrix. Our novel approach uses an incomplete augmented factorization implemented within the PARDISO linear solver and an outer BiCGStab iteration to efficiently absorb pivot perturbations occurring during factorization. This approach is capable of both efficiently using the cores inside a computational node and exploiting sparsity of the right-hand sides. We report on the performance of the approach on highperformance computers when solving stochastic unit commitment problems of unprecedented size (billions of variables and constraints) that arise in the optimization and control of electrical power grids. Our numerical experiments suggest that supercomputers can be efficiently used to solve power grid stochastic optimization problems with thousands of scenarios under the strict "real-time" requirements of power grid operators. To our knowledge, this has not been possible prior to the present work. © 2014 Society for Industrial and Applied Mathematics.
A New Approach to Practical Active-Secure Two-Party Computation
Nielsen, Jesper Buus; Nordholt, Peter Sebastian; Orlandi, Claudio
2012-01-01
We propose a new approach to practical two-party computation secure against an active adversary. All prior practical protocols were based on Yao’s garbled circuits. We use an OT-based approach and get efficiency via OT extension in the random oracle model. To get a practical protocol we introduce...
A New Approach to Practical Active-Secure Two-Party Computation
Nielsen, Jesper Buus; Nordholt, Peter Sebastian; Orlandi, Claudio
2011-01-01
We propose a new approach to practical two-party computation secure against an active adversary. All prior practical protocols were based on Yao's garbled circuits. We use an OT-based approach and get efficiency via OT extension in the random oracle model. To get a practical protocol we introduce...
Hwang, Gwo-Jen; Sung, Han-Yu; Hung, Chun-Ming; Yang, Li-Hsueh; Huang, Iwen
2013-01-01
Educational computer games have been recognized as being a promising approach for motivating students to learn. Nevertheless, previous studies have shown that without proper learning strategies or supportive models, the learning achievement of students might not be as good as expected. In this study, a knowledge engineering approach is proposed…
Fillippi, Anthony [Texas A& M University; Bhaduri, Budhendra L [ORNL; Naughton, III, Thomas J [ORNL; King, Amy L [ORNL; Scott, Stephen L [ORNL; Guneralp, Inci [Texas A& M University
2012-01-01
For aquatic studies, radiative transfer (RT) modeling can be used to compute hyperspectral above-surface remote sensing reflectance that can be utilized for inverse model development. Inverse models can provide bathymetry and inherent- and bottom-optical property estimation. Because measured oceanic field/organic datasets are often spatio-temporally sparse, synthetic data generation is useful in yielding sufficiently large datasets for inversion model development; however, these forward-modeled data are computationally expensive and time-consuming to generate. This study establishes the magnitude of wall-clock-time savings achieved for performing large, aquatic RT batch-runs using parallel computing versus a sequential approach. Given 2,600 simulations and identical compute-node characteristics, sequential architecture required {approx}100 hours until termination, whereas a parallel approach required only {approx}2.5 hours (42 compute nodes) - a 40x speed-up. Tools developed for this parallel execution are discussed.
Filippi, Anthony M [ORNL; Bhaduri, Budhendra L [ORNL; Naughton, III, Thomas J [ORNL; King, Amy L [ORNL; Scott, Stephen L [ORNL; Guneralp, Inci [Texas A& M University
2012-01-01
Abstract For aquatic studies, radiative transfer (RT) modeling can be used to compute hyperspectral above-surface remote sensing reflectance that can be utilized for inverse model development. Inverse models can provide bathymetry and inherent-and bottom-optical property estimation. Because measured oceanic field/organic datasets are often spatio-temporally sparse, synthetic data generation is useful in yielding sufficiently large datasets for inversion model development; however, these forward-modeled data are computationally expensive and time-consuming to generate. This study establishes the magnitude of wall-clock-time savings achieved for performing large, aquatic RT batch-runs using parallel computing versus a sequential approach. Given 2,600 simulations and identical compute-node characteristics, sequential architecture required ~100 hours until termination, whereas a parallel approach required only ~2.5 hours (42 compute nodes) a 40x speed-up. Tools developed for this parallel execution are discussed.
A Novel Approach for Reduce Energy Consumption in Mobile Cloud Computing
Najmeh Moghadasi
2015-09-01
Full Text Available In recent years, using mobile devices has a special place in human life and applicability of these devices leads to increased number of users. Business companies have integrated them with cloud computing technology and have provided mobile cloud in order to improve using mobile devices and overcome the energy consumption of mobile devices. In mobile cloud computing, computations and storages of mobile devices applications are transferred to cloud data centers and mobile devices are used merely as user interface to access services. Therefore, cloud computing will help to reduce energy consumption of mobile devices. In this paper, a new approach is given to reduce energy consumption of based on Learning Automata in mobile cloud computing. Simulation results show that our proposed approach dramatically saves energy consumption through determining the appropriate location for application.
An integrative computational approach for prioritization of genomic variants.
Inna Dubchak
Full Text Available An essential step in the discovery of molecular mechanisms contributing to disease phenotypes and efficient experimental planning is the development of weighted hypotheses that estimate the functional effects of sequence variants discovered by high-throughput genomics. With the increasing specialization of the bioinformatics resources, creating analytical workflows that seamlessly integrate data and bioinformatics tools developed by multiple groups becomes inevitable. Here we present a case study of a use of the distributed analytical environment integrating four complementary specialized resources, namely the Lynx platform, VISTA RViewer, the Developmental Brain Disorders Database (DBDB, and the RaptorX server, for the identification of high-confidence candidate genes contributing to pathogenesis of spina bifida. The analysis resulted in prediction and validation of deleterious mutations in the SLC19A placental transporter in mothers of the affected children that causes narrowing of the outlet channel and therefore leads to the reduced folate permeation rate. The described approach also enabled correct identification of several genes, previously shown to contribute to pathogenesis of spina bifida, and suggestion of additional genes for experimental validations. The study demonstrates that the seamless integration of bioinformatics resources enables fast and efficient prioritization and characterization of genomic factors and molecular networks contributing to the phenotypes of interest.
An Integrative Computational Approach for Prioritization of Genomic Variants
Wang, Sheng; Meyden, Cem; Sulakhe, Dinanath; Poliakov, Alexander; Börnigen, Daniela; Xie, Bingqing; Taylor, Andrew; Ma, Jianzhu; Paciorkowski, Alex R.; Mirzaa, Ghayda M.; Dave, Paul; Agam, Gady; Xu, Jinbo; Al-Gazali, Lihadh; Mason, Christopher E.; Ross, M. Elizabeth; Maltsev, Natalia; Gilliam, T. Conrad
2014-01-01
An essential step in the discovery of molecular mechanisms contributing to disease phenotypes and efficient experimental planning is the development of weighted hypotheses that estimate the functional effects of sequence variants discovered by high-throughput genomics. With the increasing specialization of the bioinformatics resources, creating analytical workflows that seamlessly integrate data and bioinformatics tools developed by multiple groups becomes inevitable. Here we present a case study of a use of the distributed analytical environment integrating four complementary specialized resources, namely the Lynx platform, VISTA RViewer, the Developmental Brain Disorders Database (DBDB), and the RaptorX server, for the identification of high-confidence candidate genes contributing to pathogenesis of spina bifida. The analysis resulted in prediction and validation of deleterious mutations in the SLC19A placental transporter in mothers of the affected children that causes narrowing of the outlet channel and therefore leads to the reduced folate permeation rate. The described approach also enabled correct identification of several genes, previously shown to contribute to pathogenesis of spina bifida, and suggestion of additional genes for experimental validations. The study demonstrates that the seamless integration of bioinformatics resources enables fast and efficient prioritization and characterization of genomic factors and molecular networks contributing to the phenotypes of interest. PMID:25506935
Effects of artificial gravity on the cardiovascular system: Computational approach
Diaz Artiles, Ana; Heldt, Thomas; Young, Laurence R.
2016-09-01
steady-state cardiovascular behavior during sustained artificial gravity and exercise. Further validation of the model was performed using experimental data from the combined exercise and artificial gravity experiments conducted on the MIT CRC, and these results will be presented separately in future publications. This unique computational framework can be used to simulate a variety of centrifuge configuration and exercise intensities to improve understanding and inform decisions about future implementation of artificial gravity in space.
Energy-aware memory management for embedded multimedia systems a computer-aided design approach
Balasa, Florin
2011-01-01
Energy-Aware Memory Management for Embedded Multimedia Systems: A Computer-Aided Design Approach presents recent computer-aided design (CAD) ideas that address memory management tasks, particularly the optimization of energy consumption in the memory subsystem. It explains how to efficiently implement CAD solutions, including theoretical methods and novel algorithms. The book covers various energy-aware design techniques, including data-dependence analysis techniques, memory size estimation methods, extensions of mapping approaches, and memory banking approaches. It shows how these techniques
A computational approach to understand in vitro alveolar morphogenesis.
Sean H J Kim
Full Text Available Primary human alveolar type II (AT II epithelial cells maintained in Matrigel cultures form alveolar-like cysts (ALCs using a cytogenesis mechanism that is different from that of other studied epithelial cell types: neither proliferation nor death is involved. During ALC formation, AT II cells engage simultaneously in fundamentally different, but not fully characterized activities. Mechanisms enabling these activities and the roles they play during different process stages are virtually unknown. Identifying, characterizing, and understanding the activities and mechanisms are essential to achieving deeper insight into this fundamental feature of morphogenesis. That deeper insight is needed to answer important questions. When and how does an AT cell choose to switch from one activity to another? Why does it choose one action rather than another? We report obtaining plausible answers using a rigorous, multi-attribute modeling and simulation approach that leveraged earlier efforts by using new, agent and object-oriented capabilities. We discovered a set of cell-level operating principles that enabled in silico cells to self-organize and generate systemic cystogenesis phenomena that are quantitatively indistinguishable from those observed in vitro. Success required that the cell components be quasi-autonomous. As simulation time advances, each in silico cell autonomously updates its environment information to reclassify its condition. It then uses the axiomatic operating principles to execute just one action for each possible condition. The quasi-autonomous actions of individual in silico cells were sufficient for developing stable cyst-like structures. The results strengthen in silico to in vitro mappings at three levels: mechanisms, behaviors, and operating principles, thereby achieving a degree of validation and enabling answering the questions posed. We suggest that the in silico operating principles presented may have a biological counterpart
Glacial landscape evolution by subglacial quarrying: A multiscale computational approach
Ugelvig, Sofie V.; Egholm, David L.; Iverson, Neal R.
2016-11-01
Quarrying of bedrock is a primary agent of subglacial erosion. Although the mechanical theory behind the process has been studied for decades, it has proven difficult to formulate the governing principles so that large-scale landscape evolution models can be used to integrate erosion over time. The existing mechanical theory thus stands largely untested in its ability to explain postglacial topography. In this study we relate the physics of quarrying to long-term landscape evolution with a multiscale approach that connects meter-scale cavities to kilometer-scale glacial landscapes. By averaging the quarrying rate across many small-scale bedrock steps, we quantify how regional trends in basal sliding speed, effective pressure, and bed slope affect the rate of erosion. A sensitivity test indicates that a power law formulated in terms of these three variables provides an acceptable basis for quantifying regional-scale rates of quarrying. Our results highlight the strong influence of effective pressure, which intensifies quarrying by increasing the volume of the bed that is stressed by the ice and thereby the probability of rock failure. The resulting pressure dependency points to subglacial hydrology as a primary factor for influencing rates of quarrying and hence for shaping the bedrock topography under warm-based glaciers. When applied in a landscape evolution model, the erosion law for quarrying produces recognizable large-scale glacial landforms: U-shaped valleys, hanging valleys, and overdeepenings. The landforms produced are very similar to those predicted by more standard sliding-based erosion laws, but overall quarrying is more focused in valleys, and less effective at higher elevations.