A computationally efficient approach for template matching-based ...
Indian Academy of Sciences (India)
In this paper, a new computationally efficient image registration method is ...... the proposed method requires less computational time as compared to traditional methods. ... Zitová B and Flusser J 2003 Image registration methods: A survey.
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.
Computationally efficient model predictive control algorithms a neural network approach
Ławryńczuk, Maciej
2014-01-01
This book thoroughly discusses computationally efficient (suboptimal) Model Predictive Control (MPC) techniques based on neural models. The subjects treated include: · A few types of suboptimal MPC algorithms in which a linear approximation of the model or of the predicted trajectory is successively calculated on-line and used for prediction. · Implementation details of the MPC algorithms for feedforward perceptron neural models, neural Hammerstein models, neural Wiener models and state-space neural models. · The MPC algorithms based on neural multi-models (inspired by the idea of predictive control). · The MPC algorithms with neural approximation with no on-line linearization. · The MPC algorithms with guaranteed stability and robustness. · Cooperation between the MPC algorithms and set-point optimization. Thanks to linearization (or neural approximation), the presented suboptimal algorithms do not require d...
Directory of Open Access Journals (Sweden)
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.
Adams, M.; Kempka, T.; Chabab, E.; Ziegler, M.
2018-02-01
Estimating the efficiency and sustainability of geological subsurface utilization, i.e., Carbon Capture and Storage (CCS) requires an integrated risk assessment approach, considering the occurring coupled processes, beside others, the potential reactivation of existing faults. In this context, hydraulic and mechanical parameter uncertainties as well as different injection rates have to be considered and quantified to elaborate reliable environmental impact assessments. Consequently, the required sensitivity analyses consume significant computational time due to the high number of realizations that have to be carried out. Due to the high computational costs of two-way coupled simulations in large-scale 3D multiphase fluid flow systems, these are not applicable for the purpose of uncertainty and risk assessments. Hence, an innovative semi-analytical hydromechanical coupling approach for hydraulic fault reactivation will be introduced. This approach determines the void ratio evolution in representative fault elements using one preliminary base simulation, considering one model geometry and one set of hydromechanical parameters. The void ratio development is then approximated and related to one reference pressure at the base of the fault. The parametrization of the resulting functions is then directly implemented into a multiphase fluid flow simulator to carry out the semi-analytical coupling for the simulation of hydromechanical processes. Hereby, the iterative parameter exchange between the multiphase and mechanical simulators is omitted, since the update of porosity and permeability is controlled by one reference pore pressure at the fault base. The suggested procedure is capable to reduce the computational time required by coupled hydromechanical simulations of a multitude of injection rates by a factor of up to 15.
Efficient approach to compute melting properties fully from ab initio with application to Cu
Zhu, Li-Fang; Grabowski, Blazej; Neugebauer, Jörg
2017-12-01
Applying thermodynamic integration within an ab initio-based free-energy approach is a state-of-the-art method to calculate melting points of materials. However, the high computational cost and the reliance on a good reference system for calculating the liquid free energy have so far hindered a general application. To overcome these challenges, we propose the two-optimized references thermodynamic integration using Langevin dynamics (TOR-TILD) method in this work by extending the two-stage upsampled thermodynamic integration using Langevin dynamics (TU-TILD) method, which has been originally developed to obtain anharmonic free energies of solids, to the calculation of liquid free energies. The core idea of TOR-TILD is to fit two empirical potentials to the energies from density functional theory based molecular dynamics runs for the solid and the liquid phase and to use these potentials as reference systems for thermodynamic integration. Because the empirical potentials closely reproduce the ab initio system in the relevant part of the phase space the convergence of the thermodynamic integration is very rapid. Therefore, the proposed approach improves significantly the computational efficiency while preserving the required accuracy. As a test case, we apply TOR-TILD to fcc Cu computing not only the melting point but various other melting properties, such as the entropy and enthalpy of fusion and the volume change upon melting. The generalized gradient approximation (GGA) with the Perdew-Burke-Ernzerhof (PBE) exchange-correlation functional and the local-density approximation (LDA) are used. Using both functionals gives a reliable ab initio confidence interval for the melting point, the enthalpy of fusion, and entropy of fusion.
International Nuclear Information System (INIS)
Goto, Masahiro; Uezu, Kazuya; Aoshima, Atsushi; Koma, Yoshikazu
2002-05-01
In this study, efficient separation materials have been created by the computational approach. Based on the computational calculation, novel organophosphorus extractants, which have two functional moieties in the molecular structure, were developed for the recycle system of transuranium elements using liquid-liquid extraction. Furthermore, molecularly imprinted resins were prepared by the surface-imprint polymerization technique. Thorough this research project, we obtained two principal results: 1) design of novel extractants by computational approach, and 2) preparation of highly selective resins by the molecular imprinting technique. The synthesized extractants showed extremely high extractability to rare earth metals compared to those of commercially available extractants. The results of extraction equilibrium suggested that the structural effect of extractants is one of the key factors to enhance the selectivity and extractability in rare earth extractions. Furthermore, a computational analysis was carried out to evaluate the extraction properties for the extraction of rare earth metals by the synthesized extractants. The computer simulation was shown to be very useful for designing new extractants. The new concept to connect some functional moieties with a spacer is very useful and is a promising method to develop novel extractants for the treatment of nuclear fuel. In the second part, we proposed a novel molecular imprinting technique (surface template polymerization) for the separation of lanthanides and actinides. A surface-templated resin is prepared by an emulsion polymerization using an ion-binding (host) monomer, a resin matrix-forming monomer and the target Nd(III) metal ion. A host monomer which has amphiphilic nature forms a complex with a metal ion at the interface, and the complex remains as it is. After the matrix is polymerized, the coordination structure is 'imprinted' at the resin interface. Adsorption of Nd(III) and La(III) ions onto the
Energy Technology Data Exchange (ETDEWEB)
Arumugam, Kamesh [Old Dominion Univ., Norfolk, VA (United States)
2017-05-01
the parallel implementation challenges of such irregular applications on different HPC architectures. In particular, we use supervised learning to predict the computation structure and use it to address the control-ow and memory access irregularities in the parallel implementation of such applications on GPUs, Xeon Phis, and heterogeneous architectures composed of multi-core CPUs with GPUs or Xeon Phis. We use numerical simulation of charged particles beam dynamics simulation as a motivating example throughout the dissertation to present our new approach, though they should be equally applicable to a wide range of irregular applications. The machine learning approach presented here use predictive analytics and forecasting techniques to adaptively model and track the irregular memory access pattern at each time step of the simulation to anticipate the future memory access pattern. Access pattern forecasts can then be used to formulate optimization decisions during application execution which improves the performance of the application at a future time step based on the observations from earlier time steps. In heterogeneous architectures, forecasts can also be used to improve the memory performance and resource utilization of all the processing units to deliver a good aggregate performance. We used these optimization techniques and anticipation strategy to design a cache-aware, memory efficient parallel algorithm to address the irregularities in the parallel implementation of charged particles beam dynamics simulation on different HPC architectures. Experimental result using a diverse mix of HPC architectures shows that our approach in using anticipation strategy is effective in maximizing data reuse, ensuring workload balance, minimizing branch and memory divergence, and in improving resource utilization.
A structural approach to constructing perspective efficient and reliable human-computer interfaces
International Nuclear Information System (INIS)
Balint, L.
1989-01-01
The principles of human-computer interface (HCI) realizations are investigated with the aim of getting closer to a general framework and thus, to a more or less solid background of constructing perspective efficient, reliable and cost-effective human-computer interfaces. On the basis of characterizing and classifying the different HCI solutions, the fundamental problems of interface construction are pointed out especially with respect to human error occurrence possibilities. The evolution of HCI realizations is illustrated by summarizing the main properties of past, present and foreseeable future interface generations. HCI modeling is pointed out to be a crucial problem in theoretical and practical investigations. Suggestions concerning HCI structure (hierarchy and modularity), HCI functional dynamics (mapping from input to output information), minimization of human error caused system failures (error-tolerance, error-recovery and error-correcting) as well as cost-effective HCI design and realization methodology (universal and application-oriented vs. application-specific solutions) are presented. The concept of RISC-based and SCAMP-type HCI components is introduced with the aim of having a reduced interaction scheme in communication and a well defined architecture in HCI components' internal structure. HCI efficiency and reliability are dealt with, by taking into account complexity and flexibility. The application of fast computerized prototyping is also briefly investigated as an experimental device of achieving simple, parametrized, invariant HCI models. Finally, a concise outline of an approach of how to construct ideal HCI's is also suggested by emphasizing the open questions and the need of future work related to the proposals, as well. (author). 14 refs, 6 figs
Nussbaumer, Raphaël; Gloaguen, Erwan; Mariéthoz, Grégoire; Holliger, Klaus
2016-04-01
Bayesian sequential simulation (BSS) is a powerful geostatistical technique, which notably has shown significant potential for the assimilation of datasets that are diverse with regard to the spatial resolution and their relationship. However, these types of applications of BSS require a large number of realizations to adequately explore the solution space and to assess the corresponding uncertainties. Moreover, such simulations generally need to be performed on very fine grids in order to adequately exploit the technique's potential for characterizing heterogeneous environments. Correspondingly, the computational cost of BSS algorithms in their classical form is very high, which so far has limited an effective application of this method to large models and/or vast datasets. In this context, it is also important to note that the inherent assumption regarding the independence of the considered datasets is generally regarded as being too strong in the context of sequential simulation. To alleviate these problems, we have revisited the classical implementation of BSS and incorporated two key features to increase the computational efficiency. The first feature is a combined quadrant spiral - superblock search, which targets run-time savings on large grids and adds flexibility with regard to the selection of neighboring points using equal directional sampling and treating hard data and previously simulated points separately. The second feature is a constant path of simulation, which enhances the efficiency for multiple realizations. We have also modified the aggregation operator to be more flexible with regard to the assumption of independence of the considered datasets. This is achieved through log-linear pooling, which essentially allows for attributing weights to the various data components. Finally, a multi-grid simulating path was created to enforce large-scale variance and to allow for adapting parameters, such as, for example, the log-linear weights or the type
International Nuclear Information System (INIS)
Quinn, J.J.
1996-01-01
Geostatistical analysis of hydraulic head data is useful in producing unbiased contour plots of head estimates and relative errors. However, at most sites being characterized, monitoring wells are generally present at different densities, with clusters of wells in some areas and few wells elsewhere. The problem that arises when kriging data at different densities is in achieving adequate resolution of the grid while maintaining computational efficiency and working within software limitations. For the site considered, 113 data points were available over a 14-mi 2 study area, including 57 monitoring wells within an area of concern of 1.5 mi 2 . Variogram analyses of the data indicate a linear model with a negligible nugget effect. The geostatistical package used in the study allows a maximum grid of 100 by 100 cells. Two-dimensional kriging was performed for the entire study area with a 500-ft grid spacing, while the smaller zone was modeled separately with a 100-ft spacing. In this manner, grid cells for the dense area and the sparse area remained small relative to the well separation distances, and the maximum dimensions of the program were not exceeded. The spatial head results for the detailed zone were then nested into the regional output by use of a graphical, object-oriented database that performed the contouring of the geostatistical output. This study benefitted from the two-scale approach and from very fine geostatistical grid spacings relative to typical data separation distances. The combining of the sparse, regional results with those from the finer-resolution area of concern yielded contours that honored the actual data at every measurement location. The method applied in this study can also be used to generate reproducible, unbiased representations of other types of spatial data
Mittra, R.; Rushdi, A.
1979-01-01
An approach for computing the geometrical optic fields reflected from a numerically specified surface is presented. The approach includes the step of deriving a specular point and begins with computing the reflected rays off the surface at the points where their coordinates, as well as the partial derivatives (or equivalently, the direction of the normal), are numerically specified. Then, a cluster of three adjacent rays are chosen to define a 'mean ray' and the divergence factor associated with this mean ray. Finally, the ampilitude, phase, and vector direction of the reflected field at a given observation point are derived by associating this point with the nearest mean ray and determining its position relative to such a ray.
Efficient computation of hashes
International Nuclear Information System (INIS)
Lopes, Raul H C; Franqueira, Virginia N L; Hobson, Peter R
2014-01-01
The sequential computation of hashes at the core of many distributed storage systems and found, for example, in grid services can hinder efficiency in service quality and even pose security challenges that can only be addressed by the use of parallel hash tree modes. The main contributions of this paper are, first, the identification of several efficiency and security challenges posed by the use of sequential hash computation based on the Merkle-Damgard engine. In addition, alternatives for the parallel computation of hash trees are discussed, and a prototype for a new parallel implementation of the Keccak function, the SHA-3 winner, is introduced.
Energy Technology Data Exchange (ETDEWEB)
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
Nonlinear mechanics of non-rigid origami: an efficient computational approach
Liu, K.; Paulino, G. H.
2017-10-01
Origami-inspired designs possess attractive applications to science and engineering (e.g. deployable, self-assembling, adaptable systems). The special geometric arrangement of panels and creases gives rise to unique mechanical properties of origami, such as reconfigurability, making origami designs well suited for tunable structures. Although often being ignored, origami structures exhibit additional soft modes beyond rigid folding due to the flexibility of thin sheets that further influence their behaviour. Actual behaviour of origami structures usually involves significant geometric nonlinearity, which amplifies the influence of additional soft modes. To investigate the nonlinear mechanics of origami structures with deformable panels, we present a structural engineering approach for simulating the nonlinear response of non-rigid origami structures. In this paper, we propose a fully nonlinear, displacement-based implicit formulation for performing static/quasi-static analyses of non-rigid origami structures based on `bar-and-hinge' models. The formulation itself leads to an efficient and robust numerical implementation. Agreement between real models and numerical simulations demonstrates the ability of the proposed approach to capture key features of origami behaviour.
An efficient approach for improving virtual machine placement in cloud computing environment
Ghobaei-Arani, Mostafa; Shamsi, Mahboubeh; Rahmanian, Ali A.
2017-11-01
The ever increasing demand for the cloud services requires more data centres. The power consumption in the data centres is a challenging problem for cloud computing, which has not been considered properly by the data centre developer companies. Especially, large data centres struggle with the power cost and the Greenhouse gases production. Hence, employing the power efficient mechanisms are necessary to optimise the mentioned effects. Moreover, virtual machine (VM) placement can be used as an effective method to reduce the power consumption in data centres. In this paper by grouping both virtual and physical machines, and taking into account the maximum absolute deviation during the VM placement, the power consumption as well as the service level agreement (SLA) deviation in data centres are reduced. To this end, the best-fit decreasing algorithm is utilised in the simulation to reduce the power consumption by about 5% compared to the modified best-fit decreasing algorithm, and at the same time, the SLA violation is improved by 6%. Finally, the learning automata are used to a trade-off between power consumption reduction from one side, and SLA violation percentage from the other side.
Schumacher, F.; Friederich, W.; Lamara, S.
2016-02-01
We present a new conceptual approach to scattering-integral-based seismic full waveform inversion (FWI) that allows a flexible, extendable, modular and both computationally and storage-efficient numerical implementation. To achieve maximum modularity and extendability, interactions between the three fundamental steps carried out sequentially in each iteration of the inversion procedure, namely, solving the forward problem, computing waveform sensitivity kernels and deriving a model update, are kept at an absolute minimum and are implemented by dedicated interfaces. To realize storage efficiency and maximum flexibility, the spatial discretization of the inverted earth model is allowed to be completely independent of the spatial discretization employed by the forward solver. For computational efficiency reasons, the inversion is done in the frequency domain. The benefits of our approach are as follows: (1) Each of the three stages of an iteration is realized by a stand-alone software program. In this way, we avoid the monolithic, unflexible and hard-to-modify codes that have often been written for solving inverse problems. (2) The solution of the forward problem, required for kernel computation, can be obtained by any wave propagation modelling code giving users maximum flexibility in choosing the forward modelling method. Both time-domain and frequency-domain approaches can be used. (3) Forward solvers typically demand spatial discretizations that are significantly denser than actually desired for the inverted model. Exploiting this fact by pre-integrating the kernels allows a dramatic reduction of disk space and makes kernel storage feasible. No assumptions are made on the spatial discretization scheme employed by the forward solver. (4) In addition, working in the frequency domain effectively reduces the amount of data, the number of kernels to be computed and the number of equations to be solved. (5) Updating the model by solving a large equation system can be
Directory of Open Access Journals (Sweden)
Sofia D Karamintziou
Full Text Available Advances in the field of closed-loop neuromodulation call for analysis and modeling approaches capable of confronting challenges related to the complex neuronal response to stimulation and the presence of strong internal and measurement noise in neural recordings. Here we elaborate on the algorithmic aspects of a noise-resistant closed-loop subthalamic nucleus deep brain stimulation system for advanced Parkinson's disease and treatment-refractory obsessive-compulsive disorder, ensuring remarkable performance in terms of both efficiency and selectivity of stimulation, as well as in terms of computational speed. First, we propose an efficient method drawn from dynamical systems theory, for the reliable assessment of significant nonlinear coupling between beta and high-frequency subthalamic neuronal activity, as a biomarker for feedback control. Further, we present a model-based strategy through which optimal parameters of stimulation for minimum energy desynchronizing control of neuronal activity are being identified. The strategy integrates stochastic modeling and derivative-free optimization of neural dynamics based on quadratic modeling. On the basis of numerical simulations, we demonstrate the potential of the presented modeling approach to identify, at a relatively low computational cost, stimulation settings potentially associated with a significantly higher degree of efficiency and selectivity compared with stimulation settings determined post-operatively. Our data reinforce the hypothesis that model-based control strategies are crucial for the design of novel stimulation protocols at the backstage of clinical applications.
Karamintziou, Sofia D; Custódio, Ana Luísa; Piallat, Brigitte; Polosan, Mircea; Chabardès, Stéphan; Stathis, Pantelis G; Tagaris, George A; Sakas, Damianos E; Polychronaki, Georgia E; Tsirogiannis, George L; David, Olivier; Nikita, Konstantina S
2017-01-01
Advances in the field of closed-loop neuromodulation call for analysis and modeling approaches capable of confronting challenges related to the complex neuronal response to stimulation and the presence of strong internal and measurement noise in neural recordings. Here we elaborate on the algorithmic aspects of a noise-resistant closed-loop subthalamic nucleus deep brain stimulation system for advanced Parkinson's disease and treatment-refractory obsessive-compulsive disorder, ensuring remarkable performance in terms of both efficiency and selectivity of stimulation, as well as in terms of computational speed. First, we propose an efficient method drawn from dynamical systems theory, for the reliable assessment of significant nonlinear coupling between beta and high-frequency subthalamic neuronal activity, as a biomarker for feedback control. Further, we present a model-based strategy through which optimal parameters of stimulation for minimum energy desynchronizing control of neuronal activity are being identified. The strategy integrates stochastic modeling and derivative-free optimization of neural dynamics based on quadratic modeling. On the basis of numerical simulations, we demonstrate the potential of the presented modeling approach to identify, at a relatively low computational cost, stimulation settings potentially associated with a significantly higher degree of efficiency and selectivity compared with stimulation settings determined post-operatively. Our data reinforce the hypothesis that model-based control strategies are crucial for the design of novel stimulation protocols at the backstage of clinical applications.
Zhang, Haibin; Wang, Yan; Zhang, Xiuzhen; Lim, Ee-Peng
2013-01-01
In e-commerce environments, the trustworthiness of a seller is utterly important to potential buyers, especially when the seller is unknown to them. Most existing trust evaluation models compute a single value to reflect the general trust level of a seller without taking any transaction context information into account. In this paper, we first present a trust vector consisting of three values for Contextual Transaction Trust (CTT). In the computation of three CTT values, the identified three ...
Energy Technology Data Exchange (ETDEWEB)
Olmos, Luis; Perez-Arriaga, Ignacio J. [Instituto de Investigacion Tecnologica, Universidad Pontificia Comillas, Alberto Aguilera, 23, 28015 Madrid (Spain)
2009-12-15
This paper presents a comprehensive design of electricity transmission charges that are meant to recover regulated network costs. In addition, these charges must be able to meet a set of inter-related objectives. Most importantly, they should encourage potential network users to internalize transmission costs in their location decisions, while interfering as least as possible with the short-term behaviour of the agents in the power system, since this should be left to regulatory instruments in the operation time range. The paper also addresses all those implementation issues that are essential for the sound design of a system of transmission network charges: stability and predictability of the charges; fair and efficient split between generation and demand charges; temporary measures to account for the low loading of most new lines; number and definition of the scenarios to be employed for the calculation and format of the final charges to be adopted: capacity, energy or per customer charges. The application of the proposed method is illustrated with a realistic numerical example that is based on a single scenario of the 2006 winter peak in the Spanish power system. (author)
International Nuclear Information System (INIS)
Yeo, Seung Gu; Kim, Eun Seog
2013-01-01
This study aimed to investigate efficient approaches for determining internal target volume (ITV) from four-dimensional computed tomography (4D CT) images used in stereotactic body radiotherapy (SBRT) for patients with early-stage non-small cell lung cancer (NSCLC). 4D CT images were analyzed for 15 patients who received SBRT for stage I NSCLC. Three different ITVs were determined as follows: combining clinical target volume (CTV) from all 10 respiratory phases (ITV 10Phases ); combining CTV from four respiratory phases, including two extreme phases (0% and 50%) plus two intermediate phases (20% and 70%) (ITV 4Phases ); and combining CTV from two extreme phases (ITV 2Phases ). The matching index (MI) of ITV 4Phases and ITV 2Phases was defined as the ratio of ITV 4Phases and ITV 2Phases , respectively, to the ITV 10Phases . The tumor motion index (TMI) was defined as the ratio of ITV 10Phases to CTV mean , which was the mean of 10 CTVs delineated on 10 respiratory phases. The ITVs were significantly different in the order of ITV 10Phases , ITV 4Phases , and ITV 2Phases (all p 4Phases was significantly higher than that of ITV 2Phases (p 4Phases was inversely related to TMI (r = -0.569, p = 0.034). In a subgroup with low TMI (n = 7), ITV 4Phases was not statistically different from ITV 10Phases (p = 0.192) and its MI was significantly higher than that of ITV 2Phases (p = 0.016). The ITV 4Phases may be an efficient approach alternative to optimal ITV 10Phases in SBRT for early-stage NSCLC with less tumor motion.
Abusamra, Heba; Bajic, Vladimir B.
2016-01-01
decrease the computational time and cost, but also improve the classification performance. Among different approaches of feature selection methods, however most of them suffer from several problems such as lack of robustness, validation issues etc. Here, we
Efficient computation of argumentation semantics
Liao, Beishui
2013-01-01
Efficient Computation of Argumentation Semantics addresses argumentation semantics and systems, introducing readers to cutting-edge decomposition methods that drive increasingly efficient logic computation in AI and intelligent systems. Such complex and distributed systems are increasingly used in the automation and transportation systems field, and particularly autonomous systems, as well as more generic intelligent computation research. The Series in Intelligent Systems publishes titles that cover state-of-the-art knowledge and the latest advances in research and development in intelligen
Wolfs, Vincent; Willems, Patrick
2015-04-01
Water managers rely increasingly on mathematical simulation models that represent individual parts of the water system, such as the river, sewer system or waste water treatment plant. The current evolution towards integral water management requires the integration of these distinct components, leading to an increased model scale and scope. Besides this growing model complexity, certain applications gained interest and importance, such as uncertainty and sensitivity analyses, auto-calibration of models and real time control. All these applications share the need for models with a very limited calculation time, either for performing a large number of simulations, or a long term simulation followed by a statistical post-processing of the results. The use of the commonly applied detailed models that solve (part of) the de Saint-Venant equations is infeasible for these applications or such integrated modelling due to several reasons, of which a too long simulation time and the inability to couple submodels made in different software environments are the main ones. Instead, practitioners must use simplified models for these purposes. These models are characterized by empirical relationships and sacrifice model detail and accuracy for increased computational efficiency. The presented research discusses the development of a flexible integral modelling platform that complies with the following three key requirements: (1) Include a modelling approach for water quantity predictions for rivers, floodplains, sewer systems and rainfall runoff routing that require a minimal calculation time; (2) A fast and semi-automatic model configuration, thereby making maximum use of data of existing detailed models and measurements; (3) Have a calculation scheme based on open source code to allow for future extensions or the coupling with other models. First, a novel and flexible modular modelling approach based on the storage cell concept was developed. This approach divides each
International Nuclear Information System (INIS)
Khatir, Zinedine; Paton, Joe; Thompson, Harvey; Kapur, Nik; Toropov, Vassili
2013-01-01
Highlights: ► A scientific framework for optimising oven operating conditions is presented. ► Experiments measuring local convective heat transfer coefficient are undertaken. ► An energy efficiency model is developed with experimentally calibrated CFD analysis. ► Designing ovens with optimum heat transfer coefficients reduces energy use. ► Results demonstrate a strong case to design and manufacture energy optimised ovens. - Abstract: Changing legislation and rising energy costs are bringing the need for efficient baking processes into much sharper focus. High-speed air impingement bread-baking ovens are complex systems using air flow to transfer heat to the product. In this paper, computational fluid dynamics (CFD) is combined with experimental analysis to develop a rigorous scientific framework for the rapid generation of forced convection oven designs. A design parameterisation of a three-dimensional generic oven model is carried out for a wide range of oven sizes and flow conditions to optimise desirable features such as temperature uniformity throughout the oven, energy efficiency and manufacturability. Coupled with the computational model, a series of experiments measuring the local convective heat transfer coefficient (h c ) are undertaken. The facility used for the heat transfer experiments is representative of a scaled-down production oven where the air temperature and velocity as well as important physical constraints such as nozzle dimensions and nozzle-to-surface distance can be varied. An efficient energy model is developed using a CFD analysis calibrated using experimentally determined inputs. Results from a range of oven designs are presented together with ensuing energy usage and savings
Energy Technology Data Exchange (ETDEWEB)
Granovsky, Alexander A., E-mail: alex.granovsky@gmail.com [Firefly project, Moscow, 117593 Moscow (Russian Federation)
2015-12-21
We present a new, very efficient semi-numerical approach for the computation of state-specific nuclear gradients of a generic state-averaged multi-configuration self consistent field wavefunction. Our approach eliminates the costly coupled-perturbed multi-configuration Hartree-Fock step as well as the associated integral transformation stage. The details of the implementation within the Firefly quantum chemistry package are discussed and several sample applications are given. The new approach is routinely applicable to geometry optimization of molecular systems with 1000+ basis functions using a standalone multi-core workstation.
International Nuclear Information System (INIS)
Granovsky, Alexander A.
2015-01-01
We present a new, very efficient semi-numerical approach for the computation of state-specific nuclear gradients of a generic state-averaged multi-configuration self consistent field wavefunction. Our approach eliminates the costly coupled-perturbed multi-configuration Hartree-Fock step as well as the associated integral transformation stage. The details of the implementation within the Firefly quantum chemistry package are discussed and several sample applications are given. The new approach is routinely applicable to geometry optimization of molecular systems with 1000+ basis functions using a standalone multi-core workstation
Granovsky, Alexander A
2015-12-21
We present a new, very efficient semi-numerical approach for the computation of state-specific nuclear gradients of a generic state-averaged multi-configuration self consistent field wavefunction. Our approach eliminates the costly coupled-perturbed multi-configuration Hartree-Fock step as well as the associated integral transformation stage. The details of the implementation within the Firefly quantum chemistry package are discussed and several sample applications are given. The new approach is routinely applicable to geometry optimization of molecular systems with 1000+ basis functions using a standalone multi-core workstation.
GATE: Improving the computational efficiency
International Nuclear Information System (INIS)
Staelens, S.; De Beenhouwer, J.; Kruecker, D.; Maigne, L.; Rannou, F.; Ferrer, L.; D'Asseler, Y.; Buvat, I.; Lemahieu, I.
2006-01-01
GATE is a software dedicated to Monte Carlo simulations in Single Photon Emission Computed Tomography (SPECT) and Positron Emission Tomography (PET). An important disadvantage of those simulations is the fundamental burden of computation time. This manuscript describes three different techniques in order to improve the efficiency of those simulations. Firstly, the implementation of variance reduction techniques (VRTs), more specifically the incorporation of geometrical importance sampling, is discussed. After this, the newly designed cluster version of the GATE software is described. The experiments have shown that GATE simulations scale very well on a cluster of homogeneous computers. Finally, an elaboration on the deployment of GATE on the Enabling Grids for E-Science in Europe (EGEE) grid will conclude the description of efficiency enhancement efforts. The three aforementioned methods improve the efficiency of GATE to a large extent and make realistic patient-specific overnight Monte Carlo simulations achievable
Macías-Díaz, J E; Macías, Siegfried; Medina-Ramírez, I E
2013-12-01
In this manuscript, we present a computational model to approximate the solutions of a partial differential equation which describes the growth dynamics of microbial films. The numerical technique reported in this work is an explicit, nonlinear finite-difference methodology which is computationally implemented using Newton's method. Our scheme is compared numerically against an implicit, linear finite-difference discretization of the same partial differential equation, whose computer coding requires an implementation of the stabilized bi-conjugate gradient method. Our numerical results evince that the nonlinear approach results in a more efficient approximation to the solutions of the biofilm model considered, and demands less computer memory. Moreover, the positivity of initial profiles is preserved in the practice by the nonlinear scheme proposed. Copyright © 2013 Elsevier Ltd. All rights reserved.
Efficient computation of Laguerre polynomials
A. Gil (Amparo); J. Segura (Javier); N.M. Temme (Nico)
2017-01-01
textabstractAn efficient algorithm and a Fortran 90 module (LaguerrePol) for computing Laguerre polynomials . Ln(α)(z) are presented. The standard three-term recurrence relation satisfied by the polynomials and different types of asymptotic expansions valid for . n large and . α small, are used
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
A primer on the energy efficiency of computing
Energy Technology Data Exchange (ETDEWEB)
Koomey, Jonathan G. [Research Fellow, Steyer-Taylor Center for Energy Policy and Finance, Stanford University (United States)
2015-03-30
The efficiency of computing at peak output has increased rapidly since the dawn of the computer age. This paper summarizes some of the key factors affecting the efficiency of computing in all usage modes. While there is still great potential for improving the efficiency of computing devices, we will need to alter how we do computing in the next few decades because we are finally approaching the limits of current technologies.
Olayan, Rawan S.
2017-11-23
Motivation Finding computationally drug-target interactions (DTIs) is a convenient strategy to identify new DTIs at low cost with reasonable accuracy. However, the current DTI prediction methods suffer the high false positive prediction rate. Results We developed DDR, a novel method that improves the DTI prediction accuracy. DDR is based on the use of a heterogeneous graph that contains known DTIs with multiple similarities between drugs and multiple similarities between target proteins. DDR applies non-linear similarity fusion method to combine different similarities. Before fusion, DDR performs a pre-processing step where a subset of similarities is selected in a heuristic process to obtain an optimized combination of similarities. Then, DDR applies a random forest model using different graph-based features extracted from the DTI heterogeneous graph. Using five repeats of 10-fold cross-validation, three testing setups, and the weighted average of area under the precision-recall curve (AUPR) scores, we show that DDR significantly reduces the AUPR score error relative to the next best start-of-the-art method for predicting DTIs by 34% when the drugs are new, by 23% when targets are new, and by 34% when the drugs and the targets are known but not all DTIs between them are not known. Using independent sources of evidence, we verify as correct 22 out of the top 25 DDR novel predictions. This suggests that DDR can be used as an efficient method to identify correct DTIs.
Directory of Open Access Journals (Sweden)
Zaikin Vladimir Genrikhovich
2012-12-01
Full Text Available The authors highlight three problems of the age of information technologies and proposes the strategy for their resolution in relation to the computer-aided design of civil engineering structures. The authors express their concerns in respect of globalization of software programmes designated for the analysis of civil engineering structures and employed outside of Russia. The problem of the poor quality of the input data has reached Russia. Lately, the rate of accidents of buildings and structures has been growing not only in Russia. Control over efficiency of design projects is hardly performed. This attitude should be changed. Development and introduction of CAD along with the application the efficient methods of projection of behaviour of building structures are in demand. Computer-aided calculations have the function of a logical nucleus, and they need proper control. The system approach to computer-aided calculations and technologies designated for the projection of accidents is formulated by the authors. Two tasks of the system approach and fundamentals of the strategy for its implementation are formulated. The study of cases of negative results of computer-aided design of engineering structures was performed and multi-component design patterns were developed. Conclusions concerning the results of researches aimed at regular and wide-scale implementation of the strategy fundamentals are formulated. Organizational and innovative actions concerning the projected behaviour of civil engineering structures proposed in the strategy are to facilitate: safety and reliability improvement of buildings and structures; saving of building materials and resources; improvement of labour efficiency of designers; modernization and improvement of accuracy of projected behaviour of buildings and building standards; closer ties between civil and building engineering researchers and construction companies; development of competitive environment to boost
Abusamra, Heba
2016-07-20
The native nature of high dimension low sample size of gene expression data make the classification task more challenging. Therefore, feature (gene) selection become an apparent need. Selecting a meaningful and relevant genes for classifier not only decrease the computational time and cost, but also improve the classification performance. Among different approaches of feature selection methods, however most of them suffer from several problems such as lack of robustness, validation issues etc. Here, we present a new feature selection technique that takes advantage of clustering both samples and genes. Materials and methods We used leukemia gene expression dataset [1]. The effectiveness of the selected features were evaluated by four different classification methods; support vector machines, k-nearest neighbor, random forest, and linear discriminate analysis. The method evaluate the importance and relevance of each gene cluster by summing the expression level for each gene belongs to this cluster. The gene cluster consider important, if it satisfies conditions depend on thresholds and percentage otherwise eliminated. Results Initial analysis identified 7120 differentially expressed genes of leukemia (Fig. 15a), after applying our feature selection methodology we end up with specific 1117 genes discriminating two classes of leukemia (Fig. 15b). Further applying the same method with more stringent higher positive and lower negative threshold condition, number reduced to 58 genes have be tested to evaluate the effectiveness of the method (Fig. 15c). The results of the four classification methods are summarized in Table 11. Conclusions The feature selection method gave good results with minimum classification error. Our heat-map result shows distinct pattern of refines genes discriminating between two classes of leukemia.
Efficient Secure Multiparty Subset Computation
Directory of Open Access Journals (Sweden)
Sufang Zhou
2017-01-01
Full Text Available Secure subset problem is important in secure multiparty computation, which is a vital field in cryptography. Most of the existing protocols for this problem can only keep the elements of one set private, while leaking the elements of the other set. In other words, they cannot solve the secure subset problem perfectly. While a few studies have addressed actual secure subsets, these protocols were mainly based on the oblivious polynomial evaluations with inefficient computation. In this study, we first design an efficient secure subset protocol for sets whose elements are drawn from a known set based on a new encoding method and homomorphic encryption scheme. If the elements of the sets are taken from a large domain, the existing protocol is inefficient. Using the Bloom filter and homomorphic encryption scheme, we further present an efficient protocol with linear computational complexity in the cardinality of the large set, and this is considered to be practical for inputs consisting of a large number of data. However, the second protocol that we design may yield a false positive. This probability can be rapidly decreased by reexecuting the protocol with different hash functions. Furthermore, we present the experimental performance analyses of these protocols.
International Nuclear Information System (INIS)
Nelke, T.; Dlugosch, C.; Olaverri Monreal, C.; Sachse, K.; Thuering, M.
2015-01-01
Prior to the use of computer-based instrumentation and control the evidence of sufficient safety, development methods and the suitability of man-machine interface must be provided. For this purpose, validation methods must be available, if possible supported by appropriate tools. Based on the multitude of the data which has to be taken into account it is important to generate technical documentation, to realize efficient operation and to prevent human based errors. An approach for computer based generation of user manuals for the operation of technical systems was developed in the VeNuS 2 project. A second goal was to develop an approach to evaluate the usability of safety relevant digital human-machine-interfaces (e.g. for nuclear industries). Therefore a software tool has been developed to assess aspects of usability of user interfaces by considering safety-related priorities. Additionally new or well known methods for provision of evidence of sufficient safety and usability for computer based systems shall be developed in a prototyped way.
Olayan, Rawan S.; Ashoor, Haitham; Bajic, Vladimir B.
2017-01-01
but not all DTIs between them are not known. Using independent sources of evidence, we verify as correct 22 out of the top 25 DDR novel predictions. This suggests that DDR can be used as an efficient method to identify correct DTIs.
An Efficient Monte Carlo Approach to Compute PageRank for Large Graphs on a Single PC
Directory of Open Access Journals (Sweden)
Sonobe Tomohiro
2016-03-01
Full Text Available This paper describes a novel Monte Carlo based random walk to compute PageRanks of nodes in a large graph on a single PC. The target graphs of this paper are ones whose size is larger than the physical memory. In such an environment, memory management is a difficult task for simulating the random walk among the nodes. We propose a novel method that partitions the graph into subgraphs in order to make them fit into the physical memory, and conducts the random walk for each subgraph. By evaluating the walks lazily, we can conduct the walks only in a subgraph and approximate the random walk by rotating the subgraphs. In computational experiments, the proposed method exhibits good performance for existing large graphs with several passes of the graph data.
Computationally Efficient Prediction of Ionic Liquid Properties
DEFF Research Database (Denmark)
Chaban, V. V.; Prezhdo, O. V.
2014-01-01
Due to fundamental differences, room-temperature ionic liquids (RTIL) are significantly more viscous than conventional molecular liquids and require long simulation times. At the same time, RTILs remain in the liquid state over a much broader temperature range than the ordinary liquids. We exploit...... to ambient temperatures. We numerically prove the validity of the proposed concept for density and ionic diffusion of four different RTILs. This simple method enhances the computational efficiency of the existing simulation approaches as applied to RTILs by more than an order of magnitude....
Structured Parallel Programming Patterns for Efficient Computation
McCool, Michael; Robison, Arch
2012-01-01
Programming is now parallel programming. Much as structured programming revolutionized traditional serial programming decades ago, a new kind of structured programming, based on patterns, is relevant to parallel programming today. Parallel computing experts and industry insiders Michael McCool, Arch Robison, and James Reinders describe how to design and implement maintainable and efficient parallel algorithms using a pattern-based approach. They present both theory and practice, and give detailed concrete examples using multiple programming models. Examples are primarily given using two of th
Efficient computation method of Jacobian matrix
International Nuclear Information System (INIS)
Sasaki, Shinobu
1995-05-01
As well known, the elements of the Jacobian matrix are complex trigonometric functions of the joint angles, resulting in a matrix of staggering complexity when we write it all out in one place. This article addresses that difficulties to this subject are overcome by using velocity representation. The main point is that its recursive algorithm and computer algebra technologies allow us to derive analytical formulation with no human intervention. Particularly, it is to be noted that as compared to previous results the elements are extremely simplified throughout the effective use of frame transformations. Furthermore, in case of a spherical wrist, it is shown that the present approach is computationally most efficient. Due to such advantages, the proposed method is useful in studying kinematically peculiar properties such as singularity problems. (author)
Power-efficient computer architectures recent advances
Själander, Magnus; Kaxiras, Stefanos
2014-01-01
As Moore's Law and Dennard scaling trends have slowed, the challenges of building high-performance computer architectures while maintaining acceptable power efficiency levels have heightened. Over the past ten years, architecture techniques for power efficiency have shifted from primarily focusing on module-level efficiencies, toward more holistic design styles based on parallelism and heterogeneity. This work highlights and synthesizes recent techniques and trends in power-efficient computer architecture.Table of Contents: Introduction / Voltage and Frequency Management / Heterogeneity and Sp
Energy efficient distributed computing systems
Lee, Young-Choon
2012-01-01
The energy consumption issue in distributed computing systems raises various monetary, environmental and system performance concerns. Electricity consumption in the US doubled from 2000 to 2005. From a financial and environmental standpoint, reducing the consumption of electricity is important, yet these reforms must not lead to performance degradation of the computing systems. These contradicting constraints create a suite of complex problems that need to be resolved in order to lead to 'greener' distributed computing systems. This book brings together a group of outsta
Efficient computation of spaced seeds
Directory of Open Access Journals (Sweden)
Ilie Silvana
2012-02-01
Full Text Available Abstract Background The most frequently used tools in bioinformatics are those searching for similarities, or local alignments, between biological sequences. Since the exact dynamic programming algorithm is quadratic, linear-time heuristics such as BLAST are used. Spaced seeds are much more sensitive than the consecutive seed of BLAST and using several seeds represents the current state of the art in approximate search for biological sequences. The most important aspect is computing highly sensitive seeds. Since the problem seems hard, heuristic algorithms are used. The leading software in the common Bernoulli model is the SpEED program. Findings SpEED uses a hill climbing method based on the overlap complexity heuristic. We propose a new algorithm for this heuristic that improves its speed by over one order of magnitude. We use the new implementation to compute improved seeds for several software programs. We compute as well multiple seeds of the same weight as MegaBLAST, that greatly improve its sensitivity. Conclusion Multiple spaced seeds are being successfully used in bioinformatics software programs. Enabling researchers to compute very fast high quality seeds will help expanding the range of their applications.
Efficient Resource Management in Cloud Computing
Rushikesh Shingade; Amit Patil; Shivam Suryawanshi; M. Venkatesan
2015-01-01
Cloud computing, one of the widely used technology to provide cloud services for users who are charged for receiving services. In the aspect of a maximum number of resources, evaluating the performance of Cloud resource management policies are difficult to optimize efficiently. There are different simulation toolkits available for simulation and modelling the Cloud computing environment like GridSim CloudAnalyst, CloudSim, GreenCloud, CloudAuction etc. In proposed Efficient Resource Manage...
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 ...
Computer architecture a quantitative approach
Hennessy, John L
2019-01-01
Computer Architecture: A Quantitative Approach, Sixth Edition has been considered essential reading by instructors, students and practitioners of computer design for over 20 years. The sixth edition of this classic textbook is fully revised with the latest developments in processor and system architecture. It now features examples from the RISC-V (RISC Five) instruction set architecture, a modern RISC instruction set developed and designed to be a free and openly adoptable standard. It also includes a new chapter on domain-specific architectures and an updated chapter on warehouse-scale computing that features the first public information on Google's newest WSC. True to its original mission of demystifying computer architecture, this edition continues the longstanding tradition of focusing on areas where the most exciting computing innovation is happening, while always keeping an emphasis on good engineering design.
Efficient GPU-based skyline computation
DEFF Research Database (Denmark)
Bøgh, Kenneth Sejdenfaden; Assent, Ira; Magnani, Matteo
2013-01-01
The skyline operator for multi-criteria search returns the most interesting points of a data set with respect to any monotone preference function. Existing work has almost exclusively focused on efficiently computing skylines on one or more CPUs, ignoring the high parallelism possible in GPUs. In...
Computational efficiency for the surface renewal method
Kelley, Jason; Higgins, Chad
2018-04-01
Measuring surface fluxes using the surface renewal (SR) method requires programmatic algorithms for tabulation, algebraic calculation, and data quality control. A number of different methods have been published describing automated calibration of SR parameters. Because the SR method utilizes high-frequency (10 Hz+) measurements, some steps in the flux calculation are computationally expensive, especially when automating SR to perform many iterations of these calculations. Several new algorithms were written that perform the required calculations more efficiently and rapidly, and that tested for sensitivity to length of flux averaging period, ability to measure over a large range of lag timescales, and overall computational efficiency. These algorithms utilize signal processing techniques and algebraic simplifications that demonstrate simple modifications that dramatically improve computational efficiency. The results here complement efforts by other authors to standardize a robust and accurate computational SR method. Increased speed of computation time grants flexibility to implementing the SR method, opening new avenues for SR to be used in research, for applied monitoring, and in novel field deployments.
Efficient quantum computing with weak measurements
International Nuclear Information System (INIS)
Lund, A P
2011-01-01
Projective measurements with high quantum efficiency are often assumed to be required for efficient circuit-based quantum computing. We argue that this is not the case and show that the fact that they are not required was actually known previously but was not deeply explored. We examine this issue by giving an example of how to perform the quantum-ordering-finding algorithm efficiently using non-local weak measurements considering that the measurements used are of bounded weakness and some fixed but arbitrary probability of success less than unity is required. We also show that it is possible to perform the same computation with only local weak measurements, but this must necessarily introduce an exponential overhead.
Efficient Multi-Party Computation over Rings
DEFF Research Database (Denmark)
Cramer, Ronald; Fehr, Serge; Ishai, Yuval
2003-01-01
Secure multi-party computation (MPC) is an active research area, and a wide range of literature can be found nowadays suggesting improvements and generalizations of existing protocols in various directions. However, all current techniques for secure MPC apply to functions that are represented by ...... the usefulness of the above results by presenting a novel application of MPC over (non-field) rings to the round-efficient secure computation of the maximum function. Basic Research in Computer Science (www.brics.dk), funded by the Danish National Research Foundation.......Secure multi-party computation (MPC) is an active research area, and a wide range of literature can be found nowadays suggesting improvements and generalizations of existing protocols in various directions. However, all current techniques for secure MPC apply to functions that are represented...... by (boolean or arithmetic) circuits over finite fields. We are motivated by two limitations of these techniques: – Generality. Existing protocols do not apply to computation over more general algebraic structures (except via a brute-force simulation of computation in these structures). – Efficiency. The best...
On the efficient parallel computation of Legendre transforms
Inda, M.A.; Bisseling, R.H.; Maslen, D.K.
2001-01-01
In this article, we discuss a parallel implementation of efficient algorithms for computation of Legendre polynomial transforms and other orthogonal polynomial transforms. We develop an approach to the Driscoll-Healy algorithm using polynomial arithmetic and present experimental results on the
On the efficient parallel computation of Legendre transforms
Inda, M.A.; Bisseling, R.H.; Maslen, D.K.
1999-01-01
In this article we discuss a parallel implementation of efficient algorithms for computation of Legendre polynomial transforms and other orthogonal polynomial transforms. We develop an approach to the Driscoll-Healy algorithm using polynomial arithmetic and present experimental results on the
Computer Architecture Techniques for Power-Efficiency
Kaxiras, Stefanos
2008-01-01
In the last few years, power dissipation has become an important design constraint, on par with performance, in the design of new computer systems. Whereas in the past, the primary job of the computer architect was to translate improvements in operating frequency and transistor count into performance, now power efficiency must be taken into account at every step of the design process. While for some time, architects have been successful in delivering 40% to 50% annual improvement in processor performance, costs that were previously brushed aside eventually caught up. The most critical of these
International Nuclear Information System (INIS)
Chao, K.S. Clifford; Bhide, Shreerang FRCR; Chen, Hansen; Asper, Joshua PAC; Bush, Steven; Franklin, Gregg; Kavadi, Vivek; Liengswangwong, Vichaivood; Gordon, William; Raben, Adam; Strasser, Jon; Koprowski, Christopher; Frank, Steven; Chronowski, Gregory; Ahamad, Anesa; Malyapa, Robert; Zhang Lifei; Dong Lei
2007-01-01
Purpose: To determine whether a computer-assisted target volume delineation (CAT) system using a deformable image registration approach can reduce the variation of target delineation among physicians with different head and neck (HN) IMRT experiences and reduce the time spent on the contouring process. Materials and Methods: We developed a deformable image registration method for mapping contours from a template case to a patient case with a similar tumor manifestation but different body configuration. Eight radiation oncologists with varying levels of clinical experience in HN IMRT performed target delineation on two HN cases, one with base-of-tongue (BOT) cancer and another with nasopharyngeal cancer (NPC), by first contouring from scratch and then by modifying the contours deformed by the CAT system. The gross target volumes were provided. Regions of interest for comparison included the clinical target volumes (CTVs) and normal organs. The volumetric and geometric variation of these regions of interest and the time spent on contouring were analyzed. Results: We found that the variation in delineating CTVs from scratch among the physicians was significant, and that using the CAT system reduced volumetric variation and improved geometric consistency in both BOT and NPC cases. The average timesaving when using the CAT system was 26% to 29% for more experienced physicians and 38% to 47% for the less experienced ones. Conclusions: A computer-assisted target volume delineation approach, using a deformable image-registration method with template contours, was able to reduce the variation among physicians with different experiences in HN IMRT while saving contouring time
Computer Architecture for Energy Efficient SFQ
2014-08-27
IBM Corporation (T.J. Watson Research Laboratory) 1101 Kitchawan Road Yorktown Heights, NY 10598 -0000 2 ABSTRACT Number of Papers published in peer...accomplished during this ARO-sponsored project at IBM Research to identify and model an energy efficient SFQ-based computer architecture. The... IBM Windsor Blue (WB), illustrated schematically in Figure 2. The basic building block of WB is a "tile" comprised of a 64-bit arithmetic logic unit
A Computationally Efficient Method for Polyphonic Pitch Estimation
Directory of Open Access Journals (Sweden)
Ruohua Zhou
2009-01-01
Full Text Available This paper presents a computationally efficient method for polyphonic pitch estimation. The method employs the Fast Resonator Time-Frequency Image (RTFI as the basic time-frequency analysis tool. The approach is composed of two main stages. First, a preliminary pitch estimation is obtained by means of a simple peak-picking procedure in the pitch energy spectrum. Such spectrum is calculated from the original RTFI energy spectrum according to harmonic grouping principles. Then the incorrect estimations are removed according to spectral irregularity and knowledge of the harmonic structures of the music notes played on commonly used music instruments. The new approach is compared with a variety of other frame-based polyphonic pitch estimation methods, and results demonstrate the high performance and computational efficiency of the approach.
A computationally efficient fuzzy control s
Directory of Open Access Journals (Sweden)
Abdel Badie Sharkawy
2013-12-01
Full Text Available This paper develops a decentralized fuzzy control scheme for MIMO nonlinear second order systems with application to robot manipulators via a combination of genetic algorithms (GAs and fuzzy systems. The controller for each degree of freedom (DOF consists of a feedforward fuzzy torque computing system and a feedback fuzzy PD system. The feedforward fuzzy system is trained and optimized off-line using GAs, whereas not only the parameters but also the structure of the fuzzy system is optimized. The feedback fuzzy PD system, on the other hand, is used to keep the closed-loop stable. The rule base consists of only four rules per each DOF. Furthermore, the fuzzy feedback system is decentralized and simplified leading to a computationally efficient control scheme. The proposed control scheme has the following advantages: (1 it needs no exact dynamics of the system and the computation is time-saving because of the simple structure of the fuzzy systems and (2 the controller is robust against various parameters and payload uncertainties. The computational complexity of the proposed control scheme has been analyzed and compared with previous works. Computer simulations show that this controller is effective in achieving the control goals.
Probabilistic Forecasting of Photovoltaic Generation: An Efficient Statistical Approach
DEFF Research Database (Denmark)
Wan, Can; Lin, Jin; Song, Yonghua
2017-01-01
This letter proposes a novel efficient probabilistic forecasting approach to accurately quantify the variability and uncertainty of the power production from photovoltaic (PV) systems. Distinguished from most existing models, a linear programming based prediction interval construction model for P...... power generation is proposed based on extreme learning machine and quantile regression, featuring high reliability and computational efficiency. The proposed approach is validated through the numerical studies on PV data from Denmark.......This letter proposes a novel efficient probabilistic forecasting approach to accurately quantify the variability and uncertainty of the power production from photovoltaic (PV) systems. Distinguished from most existing models, a linear programming based prediction interval construction model for PV...
MOBILE CLOUD COMPUTING APPLIED TO HEALTHCARE APPROACH
Omar AlSheikSalem
2016-01-01
In the past few years it was clear that mobile cloud computing was established via integrating both mobile computing and cloud computing to be add in both storage space and processing speed. Integrating healthcare applications and services is one of the vast data approaches that can be adapted to mobile cloud computing. This work proposes a framework of a global healthcare computing based combining both mobile computing and cloud computing. This approach leads to integrate all of ...
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
'Lean' approach gives greater efficiency.
Call, Roger
2014-02-01
Adapting the 'Lean' methodologies used for many years by many manufacturers on the production line - such as in the automotive industry - and deploying them in healthcare 'spaces' can, Roger Call, an architect at Herman Miller Healthcare in the US, argues, 'easily remedy many of the inefficiencies' found within a healthcare facility. In an article that first appeared in the September 2013 issue of The Australian Hospital Engineer, he explains how 'Lean' approaches such as the 'Toyota production system', and 'Six Sigma', can be harnessed to good effect in the healthcare sphere.
Dimensioning storage and computing clusters for efficient High Throughput Computing
CERN. Geneva
2012-01-01
Scientific experiments are producing huge amounts of data, and they continue increasing the size of their datasets and the total volume of data. These data are then processed by researchers belonging to large scientific collaborations, with the Large Hadron Collider being a good example. The focal point of Scientific Data Centres has shifted from coping efficiently with PetaByte scale storage to deliver quality data processing throughput. The dimensioning of the internal components in High Throughput Computing (HTC) data centers is of crucial importance to cope with all the activities demanded by the experiments, both the online (data acceptance) and the offline (data processing, simulation and user analysis). This requires a precise setup involving disk and tape storage services, a computing cluster and the internal networking to prevent bottlenecks, overloads and undesired slowness that lead to losses cpu cycles and batch jobs failures. In this paper we point out relevant features for running a successful s...
Efficient quantum circuits for one-way quantum computing.
Tanamoto, Tetsufumi; Liu, Yu-Xi; Hu, Xuedong; Nori, Franco
2009-03-13
While Ising-type interactions are ideal for implementing controlled phase flip gates in one-way quantum computing, natural interactions between solid-state qubits are most often described by either the XY or the Heisenberg models. We show an efficient way of generating cluster states directly using either the imaginary SWAP (iSWAP) gate for the XY model, or the sqrt[SWAP] gate for the Heisenberg model. Our approach thus makes one-way quantum computing more feasible for solid-state devices.
Energy Efficiency in Computing (1/2)
CERN. Geneva
2016-01-01
As manufacturers improve the silicon process, truly low energy computing is becoming a reality - both in servers and in the consumer space. This series of lectures covers a broad spectrum of aspects related to energy efficient computing - from circuits to datacentres. We will discuss common trade-offs and basic components, such as processors, memory and accelerators. We will also touch on the fundamentals of modern datacenter design and operation. Lecturer's short bio: Andrzej Nowak has 10 years of experience in computing technologies, primarily from CERN openlab and Intel. At CERN, he managed a research lab collaborating with Intel and was part of the openlab Chief Technology Office. Andrzej also worked closely and initiated projects with the private sector (e.g. HP and Google), as well as international research institutes, such as EPFL. Currently, Andrzej acts as a consultant on technology and innovation with TIK Services (http://tik.services), and runs a peer-to-peer lending start-up. NB! All Academic L...
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...
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.
Energy Efficiency in Computing (2/2)
CERN. Geneva
2016-01-01
We will start the second day of our energy efficient computing series with a brief discussion of software and the impact it has on energy consumption. A second major point of this lecture will be the current state of research and a few future technologies, ranging from mainstream (e.g. the Internet of Things) to exotic. Lecturer's short bio: Andrzej Nowak has 10 years of experience in computing technologies, primarily from CERN openlab and Intel. At CERN, he managed a research lab collaborating with Intel and was part of the openlab Chief Technology Office. Andrzej also worked closely and initiated projects with the private sector (e.g. HP and Google), as well as international research institutes, such as EPFL. Currently, Andrzej acts as a consultant on technology and innovation with TIK Services (http://tik.services), and runs a peer-to-peer lending start-up. NB! All Academic Lectures are recorded. No webcast! Because of a problem of the recording equipment, this lecture will be repeated for recording pu...
Convolutional networks for fast, energy-efficient neuromorphic computing.
Esser, Steven K; Merolla, Paul A; Arthur, John V; Cassidy, Andrew S; Appuswamy, Rathinakumar; Andreopoulos, Alexander; Berg, David J; McKinstry, Jeffrey L; Melano, Timothy; Barch, Davis R; di Nolfo, Carmelo; Datta, Pallab; Amir, Arnon; Taba, Brian; Flickner, Myron D; Modha, Dharmendra S
2016-10-11
Deep networks are now able to achieve human-level performance on a broad spectrum of recognition tasks. Independently, neuromorphic computing has now demonstrated unprecedented energy-efficiency through a new chip architecture based on spiking neurons, low precision synapses, and a scalable communication network. Here, we demonstrate that neuromorphic computing, despite its novel architectural primitives, can implement deep convolution networks that (i) approach state-of-the-art classification accuracy across eight standard datasets encompassing vision and speech, (ii) perform inference while preserving the hardware's underlying energy-efficiency and high throughput, running on the aforementioned datasets at between 1,200 and 2,600 frames/s and using between 25 and 275 mW (effectively >6,000 frames/s per Watt), and (iii) can be specified and trained using backpropagation with the same ease-of-use as contemporary deep learning. This approach allows the algorithmic power of deep learning to be merged with the efficiency of neuromorphic processors, bringing the promise of embedded, intelligent, brain-inspired computing one step closer.
Convolutional networks for fast, energy-efficient neuromorphic computing
Esser, Steven K.; Merolla, Paul A.; Arthur, John V.; Cassidy, Andrew S.; Appuswamy, Rathinakumar; Andreopoulos, Alexander; Berg, David J.; McKinstry, Jeffrey L.; Melano, Timothy; Barch, Davis R.; di Nolfo, Carmelo; Datta, Pallab; Amir, Arnon; Taba, Brian; Flickner, Myron D.; Modha, Dharmendra S.
2016-01-01
Deep networks are now able to achieve human-level performance on a broad spectrum of recognition tasks. Independently, neuromorphic computing has now demonstrated unprecedented energy-efficiency through a new chip architecture based on spiking neurons, low precision synapses, and a scalable communication network. Here, we demonstrate that neuromorphic computing, despite its novel architectural primitives, can implement deep convolution networks that (i) approach state-of-the-art classification accuracy across eight standard datasets encompassing vision and speech, (ii) perform inference while preserving the hardware’s underlying energy-efficiency and high throughput, running on the aforementioned datasets at between 1,200 and 2,600 frames/s and using between 25 and 275 mW (effectively >6,000 frames/s per Watt), and (iii) can be specified and trained using backpropagation with the same ease-of-use as contemporary deep learning. This approach allows the algorithmic power of deep learning to be merged with the efficiency of neuromorphic processors, bringing the promise of embedded, intelligent, brain-inspired computing one step closer. PMID:27651489
Dimensioning storage and computing clusters for efficient high throughput computing
International Nuclear Information System (INIS)
Accion, E; Bria, A; Bernabeu, G; Caubet, M; Delfino, M; Espinal, X; Merino, G; Lopez, F; Martinez, F; Planas, E
2012-01-01
Scientific experiments are producing huge amounts of data, and the size of their datasets and total volume of data continues increasing. These data are then processed by researchers belonging to large scientific collaborations, with the Large Hadron Collider being a good example. The focal point of scientific data centers has shifted from efficiently coping with PetaByte scale storage to deliver quality data processing throughput. The dimensioning of the internal components in High Throughput Computing (HTC) data centers is of crucial importance to cope with all the activities demanded by the experiments, both the online (data acceptance) and the offline (data processing, simulation and user analysis). This requires a precise setup involving disk and tape storage services, a computing cluster and the internal networking to prevent bottlenecks, overloads and undesired slowness that lead to losses cpu cycles and batch jobs failures. In this paper we point out relevant features for running a successful data storage and processing service in an intensive HTC environment.
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
Numerical aspects for efficient welding computational mechanics
Directory of Open Access Journals (Sweden)
Aburuga Tarek Kh.S.
2014-01-01
Full Text Available The effect of the residual stresses and strains is one of the most important parameter in the structure integrity assessment. A finite element model is constructed in order to simulate the multi passes mismatched submerged arc welding SAW which used in the welded tensile test specimen. Sequentially coupled thermal mechanical analysis is done by using ABAQUS software for calculating the residual stresses and distortion due to welding. In this work, three main issues were studied in order to reduce the time consuming during welding simulation which is the major problem in the computational welding mechanics (CWM. The first issue is dimensionality of the problem. Both two- and three-dimensional models are constructed for the same analysis type, shell element for two dimension simulation shows good performance comparing with brick element. The conventional method to calculate residual stress is by using implicit scheme that because of the welding and cooling time is relatively high. In this work, the author shows that it could use the explicit scheme with the mass scaling technique, and time consuming during the analysis will be reduced very efficiently. By using this new technique, it will be possible to simulate relatively large three dimensional structures.
Computation within the auxiliary field approach
International Nuclear Information System (INIS)
Baeurle, S.A.
2003-01-01
Recently, the classical auxiliary field methodology has been developed as a new simulation technique for performing calculations within the framework of classical statistical mechanics. Since the approach suffers from a sign problem, a judicious choice of the sampling algorithm, allowing a fast statistical convergence and an efficient generation of field configurations, is of fundamental importance for a successful simulation. In this paper we focus on the computational aspects of this simulation methodology. We introduce two different types of algorithms, the single-move auxiliary field Metropolis Monte Carlo algorithm and two new classes of force-based algorithms, which enable multiple-move propagation. In addition, to further optimize the sampling, we describe a preconditioning scheme, which permits to treat each field degree of freedom individually with regard to the evolution through the auxiliary field configuration space. Finally, we demonstrate the validity and assess the competitiveness of these algorithms on a representative practical example. We believe that they may also provide an interesting possibility for enhancing the computational efficiency of other auxiliary field methodologies
Quantum Computing and the Limits of the Efficiently Computable
CERN. Geneva
2015-01-01
I'll discuss how computational complexity---the study of what can and can't be feasibly computed---has been interacting with physics in interesting and unexpected ways. I'll first give a crash course about computer science's P vs. NP problem, as well as about the capabilities and limits of quantum computers. I'll then touch on speculative models of computation that would go even beyond quantum computers, using (for example) hypothetical nonlinearities in the Schrodinger equation. Finally, I'll discuss BosonSampling ---a proposal for a simple form of quantum computing, which nevertheless seems intractable to simulate using a classical computer---as well as the role of computational complexity in the black hole information puzzle.
Efficiently outsourcing multiparty computation under multiple keys
Peter, Andreas; Tews, Erik; Tews, Erik; Katzenbeisser, Stefan
2013-01-01
Secure multiparty computation enables a set of users to evaluate certain functionalities on their respective inputs while keeping these inputs encrypted throughout the computation. In many applications, however, outsourcing these computations to an untrusted server is desirable, so that the server
Efficient quantum computing using coherent photon conversion.
Langford, N K; Ramelow, S; Prevedel, R; Munro, W J; Milburn, G J; Zeilinger, A
2011-10-12
Single photons are excellent quantum information carriers: they were used in the earliest demonstrations of entanglement and in the production of the highest-quality entanglement reported so far. However, current schemes for preparing, processing and measuring them are inefficient. For example, down-conversion provides heralded, but randomly timed, single photons, and linear optics gates are inherently probabilistic. Here we introduce a deterministic process--coherent photon conversion (CPC)--that provides a new way to generate and process complex, multiquanta states for photonic quantum information applications. The technique uses classically pumped nonlinearities to induce coherent oscillations between orthogonal states of multiple quantum excitations. One example of CPC, based on a pumped four-wave-mixing interaction, is shown to yield a single, versatile process that provides a full set of photonic quantum processing tools. This set satisfies the DiVincenzo criteria for a scalable quantum computing architecture, including deterministic multiqubit entanglement gates (based on a novel form of photon-photon interaction), high-quality heralded single- and multiphoton states free from higher-order imperfections, and robust, high-efficiency detection. It can also be used to produce heralded multiphoton entanglement, create optically switchable quantum circuits and implement an improved form of down-conversion with reduced higher-order effects. Such tools are valuable building blocks for many quantum-enabled technologies. Finally, using photonic crystal fibres we experimentally demonstrate quantum correlations arising from a four-colour nonlinear process suitable for CPC and use these measurements to study the feasibility of reaching the deterministic regime with current technology. Our scheme, which is based on interacting bosonic fields, is not restricted to optical systems but could also be implemented in optomechanical, electromechanical and superconducting
Regional level approach for increasing energy efficiency
International Nuclear Information System (INIS)
Viholainen, Juha; Luoranen, Mika; Väisänen, Sanni; Niskanen, Antti; Horttanainen, Mika; Soukka, Risto
2016-01-01
Highlights: • Comprehensive snapshot of regional energy system for decision makers. • Connecting regional sustainability targets and energy planning. • Involving local players in energy planning. - Abstract: Actions for increasing the renewable share in the energy supply and improving both production and end-use energy efficiency are often built into the regional level sustainability targets. Because of this, many local stakeholders such as local governments, energy producers and distributors, industry, and public and private sector operators require information on the current state and development aspects of the regional energy efficiency. The drawback is that an overall view on the focal energy system operators, their energy interests, and future energy service needs in the region is often not available for the stakeholders. To support the local energy planning and management of the regional energy services, an approach for increasing the regional energy efficiency is being introduced. The presented approach can be seen as a solid framework for gathering the required data for energy efficiency analysis and also evaluating the energy system development, planned improvement actions, and the required energy services at the region. This study defines the theoretical structure of the energy efficiency approach and the required steps for revealing such energy system improvement actions that support the regional energy plan. To demonstrate the use of the approach, a case study of a Finnish small-town of Lohja is presented. In the case example, possible actions linked to the regional energy targets were evaluated with energy efficiency analysis. The results of the case example are system specific, but the conducted study can be seen as a justified example of generating easily attainable and transparent information on the impacts of different improvement actions on the regional energy system.
Efficient Minimum-Phase Prefilter Computation Using Fast QL-Factorization
DEFF Research Database (Denmark)
Hansen, Morten; Christensen, Lars P.B.
2009-01-01
This paper presents a novel approach for computing both the minimum-phase filter and the associated all-pass filter in a computationally efficient way using the fast QL-factorization. A desirable property of this approach is that the complexity is independent on the size of the matrix which is QL...
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
An Efficient PageRank Approach for Urban Traffic Optimization
Directory of Open Access Journals (Sweden)
Florin Pop
2012-01-01
to determine optimal decisions for each traffic light, based on the solution given by Larry Page for page ranking in Web environment (Page et al. (1999. Our approach is similar with work presented by Sheng-Chung et al. (2009 and Yousef et al. (2010. We consider that the traffic lights are controlled by servers and a score for each road is computed based on efficient PageRank approach and is used in cost function to determine optimal decisions. We demonstrate that the cumulative contribution of each car in the traffic respects the main constrain of PageRank approach, preserving all the properties of matrix consider in our model.
Perspective: Memcomputing: Leveraging memory and physics to compute efficiently
Di Ventra, Massimiliano; Traversa, Fabio L.
2018-05-01
It is well known that physical phenomena may be of great help in computing some difficult problems efficiently. A typical example is prime factorization that may be solved in polynomial time by exploiting quantum entanglement on a quantum computer. There are, however, other types of (non-quantum) physical properties that one may leverage to compute efficiently a wide range of hard problems. In this perspective, we discuss how to employ one such property, memory (time non-locality), in a novel physics-based approach to computation: Memcomputing. In particular, we focus on digital memcomputing machines (DMMs) that are scalable. DMMs can be realized with non-linear dynamical systems with memory. The latter property allows the realization of a new type of Boolean logic, one that is self-organizing. Self-organizing logic gates are "terminal-agnostic," namely, they do not distinguish between the input and output terminals. When appropriately assembled to represent a given combinatorial/optimization problem, the corresponding self-organizing circuit converges to the equilibrium points that express the solutions of the problem at hand. In doing so, DMMs take advantage of the long-range order that develops during the transient dynamics. This collective dynamical behavior, reminiscent of a phase transition, or even the "edge of chaos," is mediated by families of classical trajectories (instantons) that connect critical points of increasing stability in the system's phase space. The topological character of the solution search renders DMMs robust against noise and structural disorder. Since DMMs are non-quantum systems described by ordinary differential equations, not only can they be built in hardware with the available technology, they can also be simulated efficiently on modern classical computers. As an example, we will show the polynomial-time solution of the subset-sum problem for the worst cases, and point to other types of hard problems where simulations of DMMs
Integrative approaches to computational biomedicine
Coveney, Peter V.; Diaz-Zuccarini, Vanessa; Graf, Norbert; Hunter, Peter; Kohl, Peter; Tegner, Jesper; Viceconti, Marco
2013-01-01
The new discipline of computational biomedicine is concerned with the application of computer-based techniques and particularly modelling and simulation to human health. Since 2007, this discipline has been synonymous, in Europe, with the name given to the European Union's ambitious investment in integrating these techniques with the eventual aim of modelling the human body as a whole: the virtual physiological human. This programme and its successors are expected, over the next decades, to transform the study and practice of healthcare, moving it towards the priorities known as ‘4P's’: predictive, preventative, personalized and participatory medicine.
Infinitesimal symmetries: a computational approach
International Nuclear Information System (INIS)
Kersten, P.H.M.
1985-01-01
This thesis is concerned with computational aspects in the determination of infinitesimal symmetries and Lie-Baecklund transformations of differential equations. Moreover some problems are calculated explicitly. A brief introduction to some concepts in the theory of symmetries and Lie-Baecklund transformations, relevant for this thesis, are given. The mathematical formalism is shortly reviewed. The jet bundle formulation is chosen, in which, by its algebraic nature, objects can be described very precisely. Consequently it is appropriate for implementation. A number of procedures are discussed, which enable to carry through computations with the help of a computer. These computations are very extensive in practice. The Lie algebras of infinitesimal symmetries of a number of differential equations in Mathematical Physics are established and some of their applications are discussed, i.e., Maxwell equations, nonlinear diffusion equation, nonlinear Schroedinger equation, nonlinear Dirac equations and self dual SU(2) Yang-Mills equations. Lie-Baecklund transformations of Burgers' equation, Classical Boussinesq equation and the Massive Thirring Model are determined. Furthermore, nonlocal Lie-Baecklund transformations of the last equation are derived. (orig.)
Computational approach in zeolite science
Pidko, E.A.; Santen, van R.A.; Chester, A.W.; Derouane, E.G.
2009-01-01
This chapter presents an overview of different computational methods and their application to various fields of zeolite chemistry. We will discuss static lattice methods based on interatomic potentials to predict zeolite structures and topologies, Monte Carlo simulations for the investigation of
Role of computational efficiency in process simulation
Directory of Open Access Journals (Sweden)
Kurt Strand
1989-07-01
Full Text Available It is demonstrated how efficient numerical algorithms may be combined to yield a powerful environment for analysing and simulating dynamic systems. The importance of using efficient numerical algorithms is emphasized and demonstrated through examples from the petrochemical industry.
Holistic Approach to Data Center Energy Efficiency
Energy Technology Data Exchange (ETDEWEB)
Hammond, Steven W [National Renewable Energy Laboratory (NREL), Golden, CO (United States)
2017-09-18
This presentation discusses NREL's Energy System Integrations Facility and NREL's holistic design approach to sustainable data centers that led to the world's most energy-efficient data center. It describes Peregrine, a warm water liquid cooled supercomputer, waste heat reuse in the data center, demonstrated PUE and ERE, and lessons learned during four years of operation.
Stochastic Control of Energy Efficient Buildings: A Semidefinite Programming Approach
Energy Technology Data Exchange (ETDEWEB)
Ma, Xiao [ORNL; Dong, Jin [ORNL; Djouadi, Seddik M [ORNL; Nutaro, James J [ORNL; Kuruganti, Teja [ORNL
2015-01-01
The key goal in energy efficient buildings is to reduce energy consumption of Heating, Ventilation, and Air- Conditioning (HVAC) systems while maintaining a comfortable temperature and humidity in the building. This paper proposes a novel stochastic control approach for achieving joint performance and power control of HVAC. We employ a constrained Stochastic Linear Quadratic Control (cSLQC) by minimizing a quadratic cost function with a disturbance assumed to be Gaussian. The problem is formulated to minimize the expected cost subject to a linear constraint and a probabilistic constraint. By using cSLQC, the problem is reduced to a semidefinite optimization problem, where the optimal control can be computed efficiently by Semidefinite programming (SDP). Simulation results are provided to demonstrate the effectiveness and power efficiency by utilizing the proposed control approach.
Computer Architecture A Quantitative Approach
Hennessy, John L
2007-01-01
The era of seemingly unlimited growth in processor performance is over: single chip architectures can no longer overcome the performance limitations imposed by the power they consume and the heat they generate. Today, Intel and other semiconductor firms are abandoning the single fast processor model in favor of multi-core microprocessors--chips that combine two or more processors in a single package. In the fourth edition of Computer Architecture, the authors focus on this historic shift, increasing their coverage of multiprocessors and exploring the most effective ways of achieving parallelis
Computational Approaches to Simulation and Optimization of Global Aircraft Trajectories
Ng, Hok Kwan; Sridhar, Banavar
2016-01-01
This study examines three possible approaches to improving the speed in generating wind-optimal routes for air traffic at the national or global level. They are: (a) using the resources of a supercomputer, (b) running the computations on multiple commercially available computers and (c) implementing those same algorithms into NASAs Future ATM Concepts Evaluation Tool (FACET) and compares those to a standard implementation run on a single CPU. Wind-optimal aircraft trajectories are computed using global air traffic schedules. The run time and wait time on the supercomputer for trajectory optimization using various numbers of CPUs ranging from 80 to 10,240 units are compared with the total computational time for running the same computation on a single desktop computer and on multiple commercially available computers for potential computational enhancement through parallel processing on the computer clusters. This study also re-implements the trajectory optimization algorithm for further reduction of computational time through algorithm modifications and integrates that with FACET to facilitate the use of the new features which calculate time-optimal routes between worldwide airport pairs in a wind field for use with existing FACET applications. The implementations of trajectory optimization algorithms use MATLAB, Python, and Java programming languages. The performance evaluations are done by comparing their computational efficiencies and based on the potential application of optimized trajectories. The paper shows that in the absence of special privileges on a supercomputer, a cluster of commercially available computers provides a feasible approach for national and global air traffic system studies.
IMPROVING TACONITE PROCESSING PLANT EFFICIENCY BY COMPUTER SIMULATION, Final Report
Energy Technology Data Exchange (ETDEWEB)
William M. Bond; Salih Ersayin
2007-03-30
This project involved industrial scale testing of a mineral processing simulator to improve the efficiency of a taconite processing plant, namely the Minorca mine. The Concentrator Modeling Center at the Coleraine Minerals Research Laboratory, University of Minnesota Duluth, enhanced the capabilities of available software, Usim Pac, by developing mathematical models needed for accurate simulation of taconite plants. This project provided funding for this technology to prove itself in the industrial environment. As the first step, data representing existing plant conditions were collected by sampling and sample analysis. Data were then balanced and provided a basis for assessing the efficiency of individual devices and the plant, and also for performing simulations aimed at improving plant efficiency. Performance evaluation served as a guide in developing alternative process strategies for more efficient production. A large number of computer simulations were then performed to quantify the benefits and effects of implementing these alternative schemes. Modification of makeup ball size was selected as the most feasible option for the target performance improvement. This was combined with replacement of existing hydrocyclones with more efficient ones. After plant implementation of these modifications, plant sampling surveys were carried out to validate findings of the simulation-based study. Plant data showed very good agreement with the simulated data, confirming results of simulation. After the implementation of modifications in the plant, several upstream bottlenecks became visible. Despite these bottlenecks limiting full capacity, concentrator energy improvement of 7% was obtained. Further improvements in energy efficiency are expected in the near future. The success of this project demonstrated the feasibility of a simulation-based approach. Currently, the Center provides simulation-based service to all the iron ore mining companies operating in northern
Efficient Parallel Engineering Computing on Linux Workstations
Lou, John Z.
2010-01-01
A C software module has been developed that creates lightweight processes (LWPs) dynamically to achieve parallel computing performance in a variety of engineering simulation and analysis applications to support NASA and DoD project tasks. The required interface between the module and the application it supports is simple, minimal and almost completely transparent to the user applications, and it can achieve nearly ideal computing speed-up on multi-CPU engineering workstations of all operating system platforms. The module can be integrated into an existing application (C, C++, Fortran and others) either as part of a compiled module or as a dynamically linked library (DLL).
Computation of the efficiency distribution of a multichannel focusing collimator
International Nuclear Information System (INIS)
Balasubramanian, A.; Venkateswaran, T.V.
1977-01-01
This article describes two computer methods of calculating the point source efficiency distribution functions of a focusing collimator with round tapered holes. The first method which computes only the geometric efficiency distribution is adequate for low energy collimators while the second method which computes both geometric and penetration efficiencies can be made use of for medium and high energy collimators. The scatter contribution to the efficiency is not taken into account. In the first method the efficiency distribution of a single cone of the collimator is obtained and the data are used for computing the distribution of the whole collimator. For high energy collimator the entire detector region is imagined to be divided into elemental areas. Efficiency of the elemental area is computed after suitably weighting for the penetration within the collimator septa, which is determined by three dimensional geometric techniques. The method of computing the line source efficiency distribution from point source distribution is also explained. The formulations have been tested by computing the efficiency distribution of several commercial collimators and collimators fabricated by us. (Auth.)
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...
Computationally efficient prediction of area per lipid
DEFF Research Database (Denmark)
Chaban, Vitaly V.
2014-01-01
dynamics increases exponentially with respect to temperature. APL dependence on temperature is linear over an entire temperature range. I provide numerical evidence that thermal expansion coefficient of a lipid bilayer can be computed at elevated temperatures and extrapolated to the temperature of interest...
Efficient multigrid computation of steady hypersonic flows
Koren, B.; Hemker, P.W.; Murthy, T.K.S.
1991-01-01
In steady hypersonic flow computations, Newton iteration as a local relaxation procedure and nonlinear multigrid iteration as an acceleration procedure may both easily fail. In the present chapter, same remedies are presented for overcoming these problems. The equations considered are the steady,
Efficient Computations and Representations of Visible Surfaces.
1979-12-01
position as stated. The smooth contour generator may lie along a sharp ridge, for instance. Richards & Stevens -28- 6m lace contout s ?S ,.......... ceoonec...From understanding computation to understanding neural circuitry. Neurosci. Res. Prog. Bull. 13. 470-488. Metelli, F. 1970 An algebraic development of
Synthesis of Efficient Structures for Concurrent Computation.
1983-10-01
formal presentation of these techniques, called virtualisation and aggregation, can be found n [King-83$. 113.2 Census Functions Trees perform broadcast... Functions .. .. .. .. ... .... ... ... .... ... ... ....... 6 4 User-Assisted Aggregation .. .. .. .. ... ... ... .... ... .. .......... 6 5 Parallel...6. Simple Parallel Structure for Broadcasting .. .. .. .. .. . ... .. . .. . .... 4 Figure 7. Internal Structure of a Prefix Computation Network
Computationally efficient methods for digital control
Guerreiro Tome Antunes, D.J.; Hespanha, J.P.; Silvestre, C.J.; Kataria, N.; Brewer, F.
2008-01-01
The problem of designing a digital controller is considered with the novelty of explicitly taking into account the computation cost of the controller implementation. A class of controller emulation methods inspired by numerical analysis is proposed. Through various examples it is shown that these
Materials Approach to Fuel Efficient Tires
Energy Technology Data Exchange (ETDEWEB)
Votruba-Drzal, Peter [PPG Industries, Monroeville, PA (United States); Kornish, Brian [PPG Industries, Monroeville, PA (United States)
2015-06-30
The objective of this project was to design, develop, and demonstrate fuel efficient and safety regulation compliant tire filler and barrier coating technologies that will improve overall fuel efficiency by at least 2%. The program developed and validated two complementary approaches to improving fuel efficiency through tire improvements. The first technology was a modified silica-based product that is 15% lower in cost and/or enables a 10% improvement in tread wear while maintaining the already demonstrated minimum of 2% improvement in average fuel efficiency. The second technology was a barrier coating with reduced oxygen transmission rate compared to the state-of-the-art halobutyl rubber inner liners that will provide extended placarded tire pressure retention at significantly reduced material usage. A lower-permeance, thinner inner liner coating which retains tire pressure was expected to deliver the additional 2% reduction in fleet fuel consumption. From the 2006 Transportation Research Board Report1, a 10 percent reduction in rolling resistance can reduce consumer fuel expenditures by 1 to 2 percent for typical vehicles. This savings is equivalent to 6 to 12 gallons per year. A 1 psi drop in inflation pressure increases the tire's rolling resistance by about 1.4 percent.
Quantum Computing: a Quantum Group Approach
Wang, Zhenghan
2013-01-01
There is compelling theoretical evidence that quantum physics will change the face of information science. Exciting progress has been made during the last two decades towards the building of a large scale quantum computer. A quantum group approach stands out as a promising route to this holy grail, and provides hope that we may have quantum computers in our future.
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
Statistically and Computationally Efficient Estimating Equations for Large Spatial Datasets
Sun, Ying
2014-11-07
For Gaussian process models, likelihood based methods are often difficult to use with large irregularly spaced spatial datasets, because exact calculations of the likelihood for n observations require O(n3) operations and O(n2) memory. Various approximation methods have been developed to address the computational difficulties. In this paper, we propose new unbiased estimating equations based on score equation approximations that are both computationally and statistically efficient. We replace the inverse covariance matrix that appears in the score equations by a sparse matrix to approximate the quadratic forms, then set the resulting quadratic forms equal to their expected values to obtain unbiased estimating equations. The sparse matrix is constructed by a sparse inverse Cholesky approach to approximate the inverse covariance matrix. The statistical efficiency of the resulting unbiased estimating equations are evaluated both in theory and by numerical studies. Our methods are applied to nearly 90,000 satellite-based measurements of water vapor levels over a region in the Southeast Pacific Ocean.
Statistically and Computationally Efficient Estimating Equations for Large Spatial Datasets
Sun, Ying; Stein, Michael L.
2014-01-01
For Gaussian process models, likelihood based methods are often difficult to use with large irregularly spaced spatial datasets, because exact calculations of the likelihood for n observations require O(n3) operations and O(n2) memory. Various approximation methods have been developed to address the computational difficulties. In this paper, we propose new unbiased estimating equations based on score equation approximations that are both computationally and statistically efficient. We replace the inverse covariance matrix that appears in the score equations by a sparse matrix to approximate the quadratic forms, then set the resulting quadratic forms equal to their expected values to obtain unbiased estimating equations. The sparse matrix is constructed by a sparse inverse Cholesky approach to approximate the inverse covariance matrix. The statistical efficiency of the resulting unbiased estimating equations are evaluated both in theory and by numerical studies. Our methods are applied to nearly 90,000 satellite-based measurements of water vapor levels over a region in the Southeast Pacific Ocean.
Cell sorting using efficient light shaping approaches
DEFF Research Database (Denmark)
Banas, Andrew; Palima, Darwin; Villangca, Mark Jayson
2016-01-01
distributions aimed at the positions of the detected cells. Furthermore, the beam shaping freedom provided by GPC can allow optimizations in the beam’s propagation and its interaction with the catapulted cells. © (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading...... is gentler, less invasive and more economical compared to conventional FACS systems. As cells are less responsive to plastic or glass beads commonly used in the optical manipulation literature, and since laser safety would be an issue in clinical use, we develop efficient approaches in utilizing lasers...... and light modulation devices. The Generalized Phase Contrast (GPC) method that can be used for efficiently illuminating spatial light modulators or creating well-defined contiguous optical traps is supplemented by diffractive techniques capable of integrating the available light and creating 2D or 3D beam...
Efficient Parallel Kernel Solvers for Computational Fluid Dynamics Applications
Sun, Xian-He
1997-01-01
Distributed-memory parallel computers dominate today's parallel computing arena. These machines, such as Intel Paragon, IBM SP2, and Cray Origin2OO, have successfully delivered high performance computing power for solving some of the so-called "grand-challenge" problems. Despite initial success, parallel machines have not been widely accepted in production engineering environments due to the complexity of parallel programming. On a parallel computing system, a task has to be partitioned and distributed appropriately among processors to reduce communication cost and to attain load balance. More importantly, even with careful partitioning and mapping, the performance of an algorithm may still be unsatisfactory, since conventional sequential algorithms may be serial in nature and may not be implemented efficiently on parallel machines. In many cases, new algorithms have to be introduced to increase parallel performance. In order to achieve optimal performance, in addition to partitioning and mapping, a careful performance study should be conducted for a given application to find a good algorithm-machine combination. This process, however, is usually painful and elusive. The goal of this project is to design and develop efficient parallel algorithms for highly accurate Computational Fluid Dynamics (CFD) simulations and other engineering applications. The work plan is 1) developing highly accurate parallel numerical algorithms, 2) conduct preliminary testing to verify the effectiveness and potential of these algorithms, 3) incorporate newly developed algorithms into actual simulation packages. The work plan has well achieved. Two highly accurate, efficient Poisson solvers have been developed and tested based on two different approaches: (1) Adopting a mathematical geometry which has a better capacity to describe the fluid, (2) Using compact scheme to gain high order accuracy in numerical discretization. The previously developed Parallel Diagonal Dominant (PDD) algorithm
Multiscale approaches to high efficiency photovoltaics
Directory of Open Access Journals (Sweden)
Connolly James Patrick
2016-01-01
Full Text Available While renewable energies are achieving parity around the globe, efforts to reach higher solar cell efficiencies becomes ever more difficult as they approach the limiting efficiency. The so-called third generation concepts attempt to break this limit through a combination of novel physical processes and new materials and concepts in organic and inorganic systems. Some examples of semi-empirical modelling in the field are reviewed, in particular for multispectral solar cells on silicon (French ANR project MultiSolSi. Their achievements are outlined, and the limits of these approaches shown. This introduces the main topic of this contribution, which is the use of multiscale experimental and theoretical techniques to go beyond the semi-empirical understanding of these systems. This approach has already led to great advances at modelling which have led to modelling software, which is widely known. Yet, a survey of the topic reveals a fragmentation of efforts across disciplines, firstly, such as organic and inorganic fields, but also between the high efficiency concepts such as hot carrier cells and intermediate band concepts. We show how this obstacle to the resolution of practical research obstacles may be lifted by inter-disciplinary cooperation across length scales, and across experimental and theoretical fields, and finally across materials systems. We present a European COST Action “MultiscaleSolar” kicking off in early 2015, which brings together experimental and theoretical partners in order to develop multiscale research in organic and inorganic materials. The goal of this defragmentation and interdisciplinary collaboration is to develop understanding across length scales, which will enable the full potential of third generation concepts to be evaluated in practise, for societal and industrial applications.
Efficient Computer Implementations of Fast Fourier Transforms.
1980-12-01
fit in computer? Yes, continue (9) Determine fastest algorithm between WFTA and PFA from Table 4.6. For N=420, WFTA PFA Mult 1296 2528 Add 11352 10956...real adds = 24tN/4 + 2(3tN/4) = 15tN/2 (G.8) 260 All odd prime C<ictors ciual to or (,rater than 5 iso the general transform section. Based on the
Cognitive Approaches for Medicine in Cloud Computing.
Ogiela, Urszula; Takizawa, Makoto; Ogiela, Lidia
2018-03-03
This paper will present the application potential of the cognitive approach to data interpretation, with special reference to medical areas. The possibilities of using the meaning approach to data description and analysis will be proposed for data analysis tasks in Cloud Computing. The methods of cognitive data management in Cloud Computing are aimed to support the processes of protecting data against unauthorised takeover and they serve to enhance the data management processes. The accomplishment of the proposed tasks will be the definition of algorithms for the execution of meaning data interpretation processes in safe Cloud Computing. • We proposed a cognitive methods for data description. • Proposed a techniques for secure data in Cloud Computing. • Application of cognitive approaches for medicine was described.
An efficient numerical approach to electrostatic microelectromechanical system simulation
International Nuclear Information System (INIS)
Pu, Li
2009-01-01
Computational analysis of electrostatic microelectromechanical systems (MEMS) requires an electrostatic analysis to compute the electrostatic forces acting on micromechanical structures and a mechanical analysis to compute the deformation of micromechanical structures. Typically, the mechanical analysis is performed on an undeformed geometry. However, the electrostatic analysis is performed on the deformed position of microstructures. In this paper, a new efficient approach to self-consistent analysis of electrostatic MEMS in the small deformation case is presented. In this approach, when the microstructures undergo small deformations, the surface charge densities on the deformed geometry can be computed without updating the geometry of the microstructures. This algorithm is based on the linear mode shapes of a microstructure as basis functions. A boundary integral equation for the electrostatic problem is expanded into a Taylor series around the undeformed configuration, and a new coupled-field equation is presented. This approach is validated by comparing its results with the results available in the literature and ANSYS solutions, and shows attractive features comparable to ANSYS. (general)
Toward exascale computing through neuromorphic approaches.
Energy Technology Data Exchange (ETDEWEB)
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.
Efficient approach for reliability-based optimization based on weighted importance sampling approach
International Nuclear Information System (INIS)
Yuan, Xiukai; Lu, Zhenzhou
2014-01-01
An efficient methodology is presented to perform the reliability-based optimization (RBO). It is based on an efficient weighted approach for constructing an approximation of the failure probability as an explicit function of the design variables which is referred to as the ‘failure probability function (FPF)’. It expresses the FPF as a weighted sum of sample values obtained in the simulation-based reliability analysis. The required computational effort for decoupling in each iteration is just single reliability analysis. After the approximation of the FPF is established, the target RBO problem can be decoupled into a deterministic one. Meanwhile, the proposed weighted approach is combined with a decoupling approach and a sequential approximate optimization framework. Engineering examples are given to demonstrate the efficiency and accuracy of the presented methodology
An efficient multiple particle filter based on the variational Bayesian approach
Ait-El-Fquih, Boujemaa; Hoteit, Ibrahim
2015-01-01
) approach to propose a new MPF, the VBMPF. The proposed filter is computationally more efficient since the propagation of each particle requires generating one (new) particle only, while in the standard MPFs a set of (children) particles needs
Fast and efficient indexing approach for object recognition
Hefnawy, Alaa; Mashali, Samia A.; Rashwan, Mohsen; Fikri, Magdi
1999-08-01
This paper introduces a fast and efficient indexing approach for both 2D and 3D model-based object recognition in the presence of rotation, translation, and scale variations of objects. The indexing entries are computed after preprocessing the data by Haar wavelet decomposition. The scheme is based on a unified image feature detection approach based on Zernike moments. A set of low level features, e.g. high precision edges, gray level corners, are estimated by a set of orthogonal Zernike moments, calculated locally around every image point. A high dimensional, highly descriptive indexing entries are then calculated based on the correlation of these local features and employed for fast access to the model database to generate hypotheses. A list of the most candidate models is then presented by evaluating the hypotheses. Experimental results are included to demonstrate the effectiveness of the proposed indexing approach.
Computational fluid dynamics a practical approach
Tu, Jiyuan; Liu, Chaoqun
2018-01-01
Computational Fluid Dynamics: A Practical Approach, Third Edition, is an introduction to CFD fundamentals and commercial CFD software to solve engineering problems. The book is designed for a wide variety of engineering students new to CFD, and for practicing engineers learning CFD for the first time. Combining an appropriate level of mathematical background, worked examples, computer screen shots, and step-by-step processes, this book walks the reader through modeling and computing, as well as interpreting CFD results. This new edition has been updated throughout, with new content and improved figures, examples and problems.
Computational neuropharmacology: dynamical approaches in drug discovery.
Aradi, Ildiko; Erdi, Péter
2006-05-01
Computational approaches that adopt dynamical models are widely accepted in basic and clinical neuroscience research as indispensable tools with which to understand normal and pathological neuronal mechanisms. Although computer-aided techniques have been used in pharmaceutical research (e.g. in structure- and ligand-based drug design), the power of dynamical models has not yet been exploited in drug discovery. We suggest that dynamical system theory and computational neuroscience--integrated with well-established, conventional molecular and electrophysiological methods--offer a broad perspective in drug discovery and in the search for novel targets and strategies for the treatment of neurological and psychiatric diseases.
Energy efficiency of computer power supply units - Final report
Energy Technology Data Exchange (ETDEWEB)
Aebischer, B. [cepe - Centre for Energy Policy and Economics, Swiss Federal Institute of Technology Zuerich, Zuerich (Switzerland); Huser, H. [Encontrol GmbH, Niederrohrdorf (Switzerland)
2002-11-15
This final report for the Swiss Federal Office of Energy (SFOE) takes a look at the efficiency of computer power supply units, which decreases rapidly during average computer use. The background and the purpose of the project are examined. The power supplies for personal computers are discussed and the testing arrangement used is described. Efficiency, power-factor and operating points of the units are examined. Potentials for improvement and measures to be taken are discussed. Also, action to be taken by those involved in the design and operation of such power units is proposed. Finally, recommendations for further work are made.
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.
Computing with memory for energy-efficient robust systems
Paul, Somnath
2013-01-01
This book analyzes energy and reliability as major challenges faced by designers of computing frameworks in the nanometer technology regime. The authors describe the existing solutions to address these challenges and then reveal a new reconfigurable computing platform, which leverages high-density nanoscale memory for both data storage and computation to maximize the energy-efficiency and reliability. The energy and reliability benefits of this new paradigm are illustrated and the design challenges are discussed. Various hardware and software aspects of this exciting computing paradigm are de
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.
An efficient algebraic approach to observability analysis in state estimation
Energy Technology Data Exchange (ETDEWEB)
Pruneda, R.E.; Solares, C.; Conejo, A.J. [University of Castilla-La Mancha, 13071 Ciudad Real (Spain); Castillo, E. [University of Cantabria, 39005 Santander (Spain)
2010-03-15
An efficient and compact algebraic approach to state estimation observability is proposed. It is based on transferring rows to columns and vice versa in the Jacobian measurement matrix. The proposed methodology provides a unified approach to observability checking, critical measurement identification, determination of observable islands, and selection of pseudo-measurements to restore observability. Additionally, the observability information obtained from a given set of measurements can provide directly the observability obtained from any subset of measurements of the given set. Several examples are used to illustrate the capabilities of the proposed methodology, and results from a large case study are presented to demonstrate the appropriate computational behavior of the proposed algorithms. Finally, some conclusions are drawn. (author)
Positive Wigner functions render classical simulation of quantum computation efficient.
Mari, A; Eisert, J
2012-12-07
We show that quantum circuits where the initial state and all the following quantum operations can be represented by positive Wigner functions can be classically efficiently simulated. This is true both for continuous-variable as well as discrete variable systems in odd prime dimensions, two cases which will be treated on entirely the same footing. Noting the fact that Clifford and Gaussian operations preserve the positivity of the Wigner function, our result generalizes the Gottesman-Knill theorem. Our algorithm provides a way of sampling from the output distribution of a computation or a simulation, including the efficient sampling from an approximate output distribution in the case of sampling imperfections for initial states, gates, or measurements. In this sense, this work highlights the role of the positive Wigner function as separating classically efficiently simulable systems from those that are potentially universal for quantum computing and simulation, and it emphasizes the role of negativity of the Wigner function as a computational resource.
Computer science approach to quantum control
International Nuclear Information System (INIS)
Janzing, D.
2006-01-01
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
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
Alternative approaches to evaluation of cow efficiency
African Journals Online (AJOL)
anonymous
2017-01-26
Jan 26, 2017 ... Indexes that are consistent with the econometric definition of efficiency and seek to ... defined as ratios, such as the biological efficiency metric calf weight/cow weight. Dinkel & Brown ..... Biometrics 15, 469-485. Scholtz, M.M.& ...
On efficiently computing multigroup multi-layer neutron reflection and transmission conditions
International Nuclear Information System (INIS)
Abreu, Marcos P. de
2007-01-01
In this article, we present an algorithm for efficient computation of multigroup discrete ordinates neutron reflection and transmission conditions, which replace a multi-layered boundary region in neutron multiplication eigenvalue computations with no spatial truncation error. In contrast to the independent layer-by-layer algorithm considered thus far in our computations, the algorithm here is based on an inductive approach developed by the present author for deriving neutron reflection and transmission conditions for a nonactive boundary region with an arbitrary number of arbitrarily thick layers. With this new algorithm, we were able to increase significantly the computational efficiency of our spectral diamond-spectral Green's function method for solving multigroup neutron multiplication eigenvalue problems with multi-layered boundary regions. We provide comparative results for a two-group reactor core model to illustrate the increased efficiency of our spectral method, and we conclude this article with a number of general remarks. (author)
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.
Computationally efficient clustering of audio-visual meeting data
Hung, H.; Friedland, G.; Yeo, C.; Shao, L.; Shan, C.; Luo, J.; Etoh, M.
2010-01-01
This chapter presents novel computationally efficient algorithms to extract semantically meaningful acoustic and visual events related to each of the participants in a group discussion using the example of business meeting recordings. The recording setup involves relatively few audio-visual sensors,
Efficient Computation of Casimir Interactions between Arbitrary 3D Objects
International Nuclear Information System (INIS)
Reid, M. T. Homer; Rodriguez, Alejandro W.; White, Jacob; Johnson, Steven G.
2009-01-01
We introduce an efficient technique for computing Casimir energies and forces between objects of arbitrarily complex 3D geometries. In contrast to other recently developed methods, our technique easily handles nonspheroidal, nonaxisymmetric objects, and objects with sharp corners. Using our new technique, we obtain the first predictions of Casimir interactions in a number of experimentally relevant geometries, including crossed cylinders and tetrahedral nanoparticles.
Octopus: embracing the energy efficiency of handheld multimedia computers
Havinga, Paul J.M.; Smit, Gerardus Johannes Maria
1999-01-01
In the MOBY DICK project we develop and define the architecture of a new generation of mobile hand-held computers called Mobile Digital Companions. The Companions must meet several major requirements: high performance, energy efficient, a notion of Quality of Service (QoS), small size, and low
Computationally Efficient Clustering of Audio-Visual Meeting Data
Hung, Hayley; Friedland, Gerald; Yeo, Chuohao
This chapter presents novel computationally efficient algorithms to extract semantically meaningful acoustic and visual events related to each of the participants in a group discussion using the example of business meeting recordings. The recording setup involves relatively few audio-visual sensors, comprising a limited number of cameras and microphones. We first demonstrate computationally efficient algorithms that can identify who spoke and when, a problem in speech processing known as speaker diarization. We also extract visual activity features efficiently from MPEG4 video by taking advantage of the processing that was already done for video compression. Then, we present a method of associating the audio-visual data together so that the content of each participant can be managed individually. The methods presented in this article can be used as a principal component that enables many higher-level semantic analysis tasks needed in search, retrieval, and navigation.
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.
Introducing Computational Approaches in Intermediate Mechanics
Cook, David M.
2006-12-01
In the winter of 2003, we at Lawrence University moved Lagrangian mechanics and rigid body dynamics from a required sophomore course to an elective junior/senior course, freeing 40% of the time for computational approaches to ordinary differential equations (trajectory problems, the large amplitude pendulum, non-linear dynamics); evaluation of integrals (finding centers of mass and moment of inertia tensors, calculating gravitational potentials for various sources); and finding eigenvalues and eigenvectors of matrices (diagonalizing the moment of inertia tensor, finding principal axes), and to generating graphical displays of computed results. Further, students begin to use LaTeX to prepare some of their submitted problem solutions. Placed in the middle of the sophomore year, this course provides the background that permits faculty members as appropriate to assign computer-based exercises in subsequent courses. Further, students are encouraged to use our Computational Physics Laboratory on their own initiative whenever that use seems appropriate. (Curricular development supported in part by the W. M. Keck Foundation, the National Science Foundation, and Lawrence University.)
Efficient computation of clipped Voronoi diagram for mesh generation
Yan, Dongming
2013-04-01
The Voronoi diagram is a fundamental geometric structure widely used in various fields, especially in computer graphics and geometry computing. For a set of points in a compact domain (i.e. a bounded and closed 2D region or a 3D volume), some Voronoi cells of their Voronoi diagram are infinite or partially outside of the domain, but in practice only the parts of the cells inside the domain are needed, as when computing the centroidal Voronoi tessellation. Such a Voronoi diagram confined to a compact domain is called a clipped Voronoi diagram. We present an efficient algorithm to compute the clipped Voronoi diagram for a set of sites with respect to a compact 2D region or a 3D volume. We also apply the proposed method to optimal mesh generation based on the centroidal Voronoi tessellation. Crown Copyright © 2011 Published by Elsevier Ltd. All rights reserved.
Efficient computation of clipped Voronoi diagram for mesh generation
Yan, Dongming; Wang, Wen Ping; Lé vy, Bruno L.; Liu, Yang
2013-01-01
The Voronoi diagram is a fundamental geometric structure widely used in various fields, especially in computer graphics and geometry computing. For a set of points in a compact domain (i.e. a bounded and closed 2D region or a 3D volume), some Voronoi cells of their Voronoi diagram are infinite or partially outside of the domain, but in practice only the parts of the cells inside the domain are needed, as when computing the centroidal Voronoi tessellation. Such a Voronoi diagram confined to a compact domain is called a clipped Voronoi diagram. We present an efficient algorithm to compute the clipped Voronoi diagram for a set of sites with respect to a compact 2D region or a 3D volume. We also apply the proposed method to optimal mesh generation based on the centroidal Voronoi tessellation. Crown Copyright © 2011 Published by Elsevier Ltd. All rights reserved.
An Efficient Approach for Identifying Stable Lobes with Discretization Method
Directory of Open Access Journals (Sweden)
Baohai Wu
2013-01-01
Full Text Available This paper presents a new approach for quick identification of chatter stability lobes with discretization method. Firstly, three different kinds of stability regions are defined: absolute stable region, valid region, and invalid region. Secondly, while identifying the chatter stability lobes, three different regions within the chatter stability lobes are identified with relatively large time intervals. Thirdly, stability boundary within the valid regions is finely calculated to get exact chatter stability lobes. The proposed method only needs to test a small portion of spindle speed and cutting depth set; about 89% computation time is savedcompared with full discretization method. It spends only about10 minutes to get exact chatter stability lobes. Since, based on discretization method, the proposed method can be used for different immersion cutting including low immersion cutting process, the proposed method can be directly implemented in the workshop to promote machining parameters selection efficiency.
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.
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...
Efficient technique for computational design of thermoelectric materials
Núñez-Valdez, Maribel; Allahyari, Zahed; Fan, Tao; Oganov, Artem R.
2018-01-01
Efficient thermoelectric materials are highly desirable, and the quest for finding them has intensified as they could be promising alternatives to fossil energy sources. Here we present a general first-principles approach to predict, in multicomponent systems, efficient thermoelectric compounds. The method combines a robust evolutionary algorithm, a Pareto multiobjective optimization, density functional theory and a Boltzmann semi-classical calculation of thermoelectric efficiency. To test the performance and reliability of our overall framework, we use the well-known system Bi2Te3-Sb2Te3.
Approaches of Improving University Assets Management Efficiency
Wang, Jingliang
2015-01-01
University assets management, as an important content of modern university management, is generally confronted with the issue of low efficiency. Currently, to address the problems exposed in university assets management and take appropriate modification measures is an urgent issue in front of Chinese university assets management sectors. In this…
Directory of Open Access Journals (Sweden)
JongBeom Lim
2018-01-01
Full Text Available Many artificial intelligence applications often require a huge amount of computing resources. As a result, cloud computing adoption rates are increasing in the artificial intelligence field. To support the demand for artificial intelligence applications and guarantee the service level agreement, cloud computing should provide not only computing resources but also fundamental mechanisms for efficient computing. In this regard, a snapshot protocol has been used to create a consistent snapshot of the global state in cloud computing environments. However, the existing snapshot protocols are not optimized in the context of artificial intelligence applications, where large-scale iterative computation is the norm. In this paper, we present a distributed snapshot protocol for efficient artificial intelligence computation in cloud computing environments. The proposed snapshot protocol is based on a distributed algorithm to run interconnected multiple nodes in a scalable fashion. Our snapshot protocol is able to deal with artificial intelligence applications, in which a large number of computing nodes are running. We reveal that our distributed snapshot protocol guarantees the correctness, safety, and liveness conditions.
Energy-efficient computing and networking. Revised selected papers
Energy Technology Data Exchange (ETDEWEB)
Hatziargyriou, Nikos; Dimeas, Aris [Ethnikon Metsovion Polytechneion, Athens (Greece); Weidlich, Anke (eds.) [SAP Research Center, Karlsruhe (Germany); Tomtsi, Thomai
2011-07-01
This book constitutes the postproceedings of the First International Conference on Energy-Efficient Computing and Networking, E-Energy, held in Passau, Germany in April 2010. The 23 revised papers presented were carefully reviewed and selected for inclusion in the post-proceedings. The papers are organized in topical sections on energy market and algorithms, ICT technology for the energy market, implementation of smart grid and smart home technology, microgrids and energy management, and energy efficiency through distributed energy management and buildings. (orig.)
Secure Computation, I/O-Efficient Algorithms and Distributed Signatures
DEFF Research Database (Denmark)
Damgård, Ivan Bjerre; Kölker, Jonas; Toft, Tomas
2012-01-01
values of form r, gr for random secret-shared r ∈ ℤq and gr in a group of order q. This costs a constant number of exponentiation per player per value generated, even if less than n/3 players are malicious. This can be used for efficient distributed computing of Schnorr signatures. We further develop...... the technique so we can sign secret data in a distributed fashion at essentially the same cost....
Improving computational efficiency of Monte Carlo simulations with variance reduction
International Nuclear Information System (INIS)
Turner, A.; Davis, A.
2013-01-01
CCFE perform Monte-Carlo transport simulations on large and complex tokamak models such as ITER. Such simulations are challenging since streaming and deep penetration effects are equally important. In order to make such simulations tractable, both variance reduction (VR) techniques and parallel computing are used. It has been found that the application of VR techniques in such models significantly reduces the efficiency of parallel computation due to 'long histories'. VR in MCNP can be accomplished using energy-dependent weight windows. The weight window represents an 'average behaviour' of particles, and large deviations in the arriving weight of a particle give rise to extreme amounts of splitting being performed and a long history. When running on parallel clusters, a long history can have a detrimental effect on the parallel efficiency - if one process is computing the long history, the other CPUs complete their batch of histories and wait idle. Furthermore some long histories have been found to be effectively intractable. To combat this effect, CCFE has developed an adaptation of MCNP which dynamically adjusts the WW where a large weight deviation is encountered. The method effectively 'de-optimises' the WW, reducing the VR performance but this is offset by a significant increase in parallel efficiency. Testing with a simple geometry has shown the method does not bias the result. This 'long history method' has enabled CCFE to significantly improve the performance of MCNP calculations for ITER on parallel clusters, and will be beneficial for any geometry combining streaming and deep penetration effects. (authors)
Efficient MATLAB computations with sparse and factored tensors.
Energy Technology Data Exchange (ETDEWEB)
Bader, Brett William; Kolda, Tamara Gibson (Sandia National Lab, Livermore, CA)
2006-12-01
In this paper, the term tensor refers simply to a multidimensional or N-way array, and we consider how specially structured tensors allow for efficient storage and computation. First, we study sparse tensors, which have the property that the vast majority of the elements are zero. We propose storing sparse tensors using coordinate format and describe the computational efficiency of this scheme for various mathematical operations, including those typical to tensor decomposition algorithms. Second, we study factored tensors, which have the property that they can be assembled from more basic components. We consider two specific types: a Tucker tensor can be expressed as the product of a core tensor (which itself may be dense, sparse, or factored) and a matrix along each mode, and a Kruskal tensor can be expressed as the sum of rank-1 tensors. We are interested in the case where the storage of the components is less than the storage of the full tensor, and we demonstrate that many elementary operations can be computed using only the components. All of the efficiencies described in this paper are implemented in the Tensor Toolbox for MATLAB.
An energy-efficient failure detector for vehicular cloud computing.
Liu, Jiaxi; Wu, Zhibo; Dong, Jian; Wu, Jin; Wen, Dongxin
2018-01-01
Failure detectors are one of the fundamental components for maintaining the high availability of vehicular cloud computing. In vehicular cloud computing, lots of RSUs are deployed along the road to improve the connectivity. Many of them are equipped with solar battery due to the unavailability or excess expense of wired electrical power. So it is important to reduce the battery consumption of RSU. However, the existing failure detection algorithms are not designed to save battery consumption RSU. To solve this problem, a new energy-efficient failure detector 2E-FD has been proposed specifically for vehicular cloud computing. 2E-FD does not only provide acceptable failure detection service, but also saves the battery consumption of RSU. Through the comparative experiments, the results show that our failure detector has better performance in terms of speed, accuracy and battery consumption.
Power-Efficient Computing: Experiences from the COSA Project
Directory of Open Access Journals (Sweden)
Daniele Cesini
2017-01-01
Full Text Available Energy consumption is today one of the most relevant issues in operating HPC systems for scientific applications. The use of unconventional computing systems is therefore of great interest for several scientific communities looking for a better tradeoff between time-to-solution and energy-to-solution. In this context, the performance assessment of processors with a high ratio of performance per watt is necessary to understand how to realize energy-efficient computing systems for scientific applications, using this class of processors. Computing On SOC Architecture (COSA is a three-year project (2015–2017 funded by the Scientific Commission V of the Italian Institute for Nuclear Physics (INFN, which aims to investigate the performance and the total cost of ownership offered by computing systems based on commodity low-power Systems on Chip (SoCs and high energy-efficient systems based on GP-GPUs. In this work, we present the results of the project analyzing the performance of several scientific applications on several GPU- and SoC-based systems. We also describe the methodology we have used to measure energy performance and the tools we have implemented to monitor the power drained by applications while running.
International Nuclear Information System (INIS)
Kamalzare, Mahmoud; Johnson, Erik A; Wojtkiewicz, Steven F
2014-01-01
Designing control strategies for smart structures, such as those with semiactive devices, is complicated by the nonlinear nature of the feedback control, secondary clipping control and other additional requirements such as device saturation. The usual design approach resorts to large-scale simulation parameter studies that are computationally expensive. The authors have previously developed an approach for state-feedback semiactive clipped-optimal control design, based on a nonlinear Volterra integral equation that provides for the computationally efficient simulation of such systems. This paper expands the applicability of the approach by demonstrating that it can also be adapted to accommodate more realistic cases when, instead of full state feedback, only a limited set of noisy response measurements is available to the controller. This extension requires incorporating a Kalman filter (KF) estimator, which is linear, into the nominal model of the uncontrolled system. The efficacy of the approach is demonstrated by a numerical study of a 100-degree-of-freedom frame model, excited by a filtered Gaussian random excitation, with noisy acceleration sensor measurements to determine the semiactive control commands. The results show that the proposed method can improve computational efficiency by more than two orders of magnitude relative to a conventional solver, while retaining a comparable level of accuracy. Further, the proposed approach is shown to be similarly efficient for an extensive Monte Carlo simulation to evaluate the effects of sensor noise levels and KF tuning on the accuracy of the response. (paper)
Efficient computation of smoothing splines via adaptive basis sampling
Ma, Ping
2015-06-24
© 2015 Biometrika Trust. Smoothing splines provide flexible nonparametric regression estimators. However, the high computational cost of smoothing splines for large datasets has hindered their wide application. In this article, we develop a new method, named adaptive basis sampling, for efficient computation of smoothing splines in super-large samples. Except for the univariate case where the Reinsch algorithm is applicable, a smoothing spline for a regression problem with sample size n can be expressed as a linear combination of n basis functions and its computational complexity is generally O(n^{3}). We achieve a more scalable computation in the multivariate case by evaluating the smoothing spline using a smaller set of basis functions, obtained by an adaptive sampling scheme that uses values of the response variable. Our asymptotic analysis shows that smoothing splines computed via adaptive basis sampling converge to the true function at the same rate as full basis smoothing splines. Using simulation studies and a large-scale deep earth core-mantle boundary imaging study, we show that the proposed method outperforms a sampling method that does not use the values of response variables.
Efficient computation of smoothing splines via adaptive basis sampling
Ma, Ping; Huang, Jianhua Z.; Zhang, Nan
2015-01-01
© 2015 Biometrika Trust. Smoothing splines provide flexible nonparametric regression estimators. However, the high computational cost of smoothing splines for large datasets has hindered their wide application. In this article, we develop a new method, named adaptive basis sampling, for efficient computation of smoothing splines in super-large samples. Except for the univariate case where the Reinsch algorithm is applicable, a smoothing spline for a regression problem with sample size n can be expressed as a linear combination of n basis functions and its computational complexity is generally O(n^{3}). We achieve a more scalable computation in the multivariate case by evaluating the smoothing spline using a smaller set of basis functions, obtained by an adaptive sampling scheme that uses values of the response variable. Our asymptotic analysis shows that smoothing splines computed via adaptive basis sampling converge to the true function at the same rate as full basis smoothing splines. Using simulation studies and a large-scale deep earth core-mantle boundary imaging study, we show that the proposed method outperforms a sampling method that does not use the values of response variables.
Energy efficient hybrid computing systems using spin devices
Sharad, Mrigank
Emerging spin-devices like magnetic tunnel junctions (MTJ's), spin-valves and domain wall magnets (DWM) have opened new avenues for spin-based logic design. This work explored potential computing applications which can exploit such devices for higher energy-efficiency and performance. The proposed applications involve hybrid design schemes, where charge-based devices supplement the spin-devices, to gain large benefits at the system level. As an example, lateral spin valves (LSV) involve switching of nanomagnets using spin-polarized current injection through a metallic channel such as Cu. Such spin-torque based devices possess several interesting properties that can be exploited for ultra-low power computation. Analog characteristic of spin current facilitate non-Boolean computation like majority evaluation that can be used to model a neuron. The magneto-metallic neurons can operate at ultra-low terminal voltage of ˜20mV, thereby resulting in small computation power. Moreover, since nano-magnets inherently act as memory elements, these devices can facilitate integration of logic and memory in interesting ways. The spin based neurons can be integrated with CMOS and other emerging devices leading to different classes of neuromorphic/non-Von-Neumann architectures. The spin-based designs involve `mixed-mode' processing and hence can provide very compact and ultra-low energy solutions for complex computation blocks, both digital as well as analog. Such low-power, hybrid designs can be suitable for various data processing applications like cognitive computing, associative memory, and currentmode on-chip global interconnects. Simulation results for these applications based on device-circuit co-simulation framework predict more than ˜100x improvement in computation energy as compared to state of the art CMOS design, for optimal spin-device parameters.
Novel computational approaches characterizing knee physiotherapy
Directory of Open Access Journals (Sweden)
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
DEFF Research Database (Denmark)
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 animal breeding.
Berger-Wolf, Tanya Y; Moore, Cristopher; Saia, Jared
2007-02-07
We propose a computational model of mating strategies for controlled animal breeding programs. A mating strategy in a controlled breeding program is a heuristic with some optimization criteria as a goal. Thus, it is appropriate to use the computational tools available for analysis of optimization heuristics. In this paper, we propose the first discrete model of the controlled animal breeding problem and analyse heuristics for two possible objectives: (1) breeding for maximum diversity and (2) breeding a target individual. These two goals are representative of conservation biology and agricultural livestock management, respectively. We evaluate several mating strategies and provide upper and lower bounds for the expected number of matings. While the population parameters may vary and can change the actual number of matings for a particular strategy, the order of magnitude of the number of expected matings and the relative competitiveness of the mating heuristics remains the same. Thus, our simple discrete model of the animal breeding problem provides a novel viable and robust approach to designing and comparing breeding strategies in captive populations.
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).
Improving robustness and computational efficiency using modern C++
International Nuclear Information System (INIS)
Paterno, M; Kowalkowski, J; Green, C
2014-01-01
For nearly two decades, the C++ programming language has been the dominant programming language for experimental HEP. The publication of ISO/IEC 14882:2011, the current version of the international standard for the C++ programming language, makes available a variety of language and library facilities for improving the robustness, expressiveness, and computational efficiency of C++ code. However, much of the C++ written by the experimental HEP community does not take advantage of the features of the language to obtain these benefits, either due to lack of familiarity with these features or concern that these features must somehow be computationally inefficient. In this paper, we address some of the features of modern C+-+, and show how they can be used to make programs that are both robust and computationally efficient. We compare and contrast simple yet realistic examples of some common implementation patterns in C, currently-typical C++, and modern C++, and show (when necessary, down to the level of generated assembly language code) the quality of the executable code produced by recent C++ compilers, with the aim of allowing the HEP community to make informed decisions on the costs and benefits of the use of modern C++.
An efficient and extensible approach for compressing phylogenetic trees
Matthews, Suzanne J
2011-01-01
Background: Biologists require new algorithms to efficiently compress and store their large collections of phylogenetic trees. Our previous work showed that TreeZip is a promising approach for compressing phylogenetic trees. In this paper, we extend our TreeZip algorithm by handling trees with weighted branches. Furthermore, by using the compressed TreeZip file as input, we have designed an extensible decompressor that can extract subcollections of trees, compute majority and strict consensus trees, and merge tree collections using set operations such as union, intersection, and set difference.Results: On unweighted phylogenetic trees, TreeZip is able to compress Newick files in excess of 98%. On weighted phylogenetic trees, TreeZip is able to compress a Newick file by at least 73%. TreeZip can be combined with 7zip with little overhead, allowing space savings in excess of 99% (unweighted) and 92%(weighted). Unlike TreeZip, 7zip is not immune to branch rotations, and performs worse as the level of variability in the Newick string representation increases. Finally, since the TreeZip compressed text (TRZ) file contains all the semantic information in a collection of trees, we can easily filter and decompress a subset of trees of interest (such as the set of unique trees), or build the resulting consensus tree in a matter of seconds. We also show the ease of which set operations can be performed on TRZ files, at speeds quicker than those performed on Newick or 7zip compressed Newick files, and without loss of space savings.Conclusions: TreeZip is an efficient approach for compressing large collections of phylogenetic trees. The semantic and compact nature of the TRZ file allow it to be operated upon directly and quickly, without a need to decompress the original Newick file. We believe that TreeZip will be vital for compressing and archiving trees in the biological community. © 2011 Matthews and Williams; licensee BioMed Central Ltd.
An efficient and extensible approach for compressing phylogenetic trees.
Matthews, Suzanne J; Williams, Tiffani L
2011-10-18
Biologists require new algorithms to efficiently compress and store their large collections of phylogenetic trees. Our previous work showed that TreeZip is a promising approach for compressing phylogenetic trees. In this paper, we extend our TreeZip algorithm by handling trees with weighted branches. Furthermore, by using the compressed TreeZip file as input, we have designed an extensible decompressor that can extract subcollections of trees, compute majority and strict consensus trees, and merge tree collections using set operations such as union, intersection, and set difference. On unweighted phylogenetic trees, TreeZip is able to compress Newick files in excess of 98%. On weighted phylogenetic trees, TreeZip is able to compress a Newick file by at least 73%. TreeZip can be combined with 7zip with little overhead, allowing space savings in excess of 99% (unweighted) and 92%(weighted). Unlike TreeZip, 7zip is not immune to branch rotations, and performs worse as the level of variability in the Newick string representation increases. Finally, since the TreeZip compressed text (TRZ) file contains all the semantic information in a collection of trees, we can easily filter and decompress a subset of trees of interest (such as the set of unique trees), or build the resulting consensus tree in a matter of seconds. We also show the ease of which set operations can be performed on TRZ files, at speeds quicker than those performed on Newick or 7zip compressed Newick files, and without loss of space savings. TreeZip is an efficient approach for compressing large collections of phylogenetic trees. The semantic and compact nature of the TRZ file allow it to be operated upon directly and quickly, without a need to decompress the original Newick file. We believe that TreeZip will be vital for compressing and archiving trees in the biological community.
Energy Technology Data Exchange (ETDEWEB)
Abhyankar, Shrirang [Argonne National Lab. (ANL), Argonne, IL (United States); Anitescu, Mihai [Argonne National Lab. (ANL), Argonne, IL (United States); Constantinescu, Emil [Argonne National Lab. (ANL), Argonne, IL (United States); Zhang, Hong [Argonne National Lab. (ANL), Argonne, IL (United States)
2016-03-31
Sensitivity analysis is an important tool to describe power system dynamic behavior in response to parameter variations. It is a central component in preventive and corrective control applications. The existing approaches for sensitivity calculations, namely, finite-difference and forward sensitivity analysis, require a computational effort that increases linearly with the number of sensitivity parameters. In this work, we investigate, implement, and test a discrete adjoint sensitivity approach whose computational effort is effectively independent of the number of sensitivity parameters. The proposed approach is highly efficient for calculating trajectory sensitivities of larger systems and is consistent, within machine precision, with the function whose sensitivity we are seeking. This is an essential feature for use in optimization applications. Moreover, our approach includes a consistent treatment of systems with switching, such as DC exciters, by deriving and implementing the adjoint jump conditions that arise from state and time-dependent discontinuities. The accuracy and the computational efficiency of the proposed approach are demonstrated in comparison with the forward sensitivity analysis approach.
Blueprinting Approach in Support of Cloud Computing
Directory of Open Access Journals (Sweden)
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.
Efficient Skyline Computation in Structured Peer-to-Peer Systems
DEFF Research Database (Denmark)
Cui, Bin; Chen, Lijiang; Xu, Linhao
2009-01-01
An increasing number of large-scale applications exploit peer-to-peer network architecture to provide highly scalable and flexible services. Among these applications, data management in peer-to-peer systems is one of the interesting domains. In this paper, we investigate the multidimensional...... skyline computation problem on a structured peer-to-peer network. In order to achieve low communication cost and quick response time, we utilize the iMinMax(\\theta ) method to transform high-dimensional data to one-dimensional value and distribute the data in a structured peer-to-peer network called BATON....... Thereafter, we propose a progressive algorithm with adaptive filter technique for efficient skyline computation in this environment. We further discuss some optimization techniques for the algorithm, and summarize the key principles of our algorithm into a query routing protocol with detailed analysis...
Adding computationally efficient realism to Monte Carlo turbulence simulation
Campbell, C. W.
1985-01-01
Frequently in aerospace vehicle flight simulation, random turbulence is generated using the assumption that the craft is small compared to the length scales of turbulence. The turbulence is presumed to vary only along the flight path of the vehicle but not across the vehicle span. The addition of the realism of three-dimensionality is a worthy goal, but any such attempt will not gain acceptance in the simulator community unless it is computationally efficient. A concept for adding three-dimensional realism with a minimum of computational complexity is presented. The concept involves the use of close rational approximations to irrational spectra and cross-spectra so that systems of stable, explicit difference equations can be used to generate the turbulence.
Graphics processor efficiency for realization of rapid tabular computations
International Nuclear Information System (INIS)
Dudnik, V.A.; Kudryavtsev, V.I.; Us, S.A.; Shestakov, M.V.
2016-01-01
Capabilities of graphics processing units (GPU) and central processing units (CPU) have been investigated for realization of fast-calculation algorithms with the use of tabulated functions. The realization of tabulated functions is exemplified by the GPU/CPU architecture-based processors. Comparison is made between the operating efficiencies of GPU and CPU, employed for tabular calculations at different conditions of use. Recommendations are formulated for the use of graphical and central processors to speed up scientific and engineering computations through the use of tabulated functions
Efficient quantum algorithm for computing n-time correlation functions.
Pedernales, J S; Di Candia, R; Egusquiza, I L; Casanova, J; Solano, E
2014-07-11
We propose a method for computing n-time correlation functions of arbitrary spinorial, fermionic, and bosonic operators, consisting of an efficient quantum algorithm that encodes these correlations in an initially added ancillary qubit for probe and control tasks. For spinorial and fermionic systems, the reconstruction of arbitrary n-time correlation functions requires the measurement of two ancilla observables, while for bosonic variables time derivatives of the same observables are needed. Finally, we provide examples applicable to different quantum platforms in the frame of the linear response theory.
Computationally Efficient and Noise Robust DOA and Pitch Estimation
DEFF Research Database (Denmark)
Karimian-Azari, Sam; Jensen, Jesper Rindom; Christensen, Mads Græsbøll
2016-01-01
Many natural signals, such as voiced speech and some musical instruments, are approximately periodic over short intervals. These signals are often described in mathematics by the sum of sinusoids (harmonics) with frequencies that are proportional to the fundamental frequency, or pitch. In sensor...... a joint DOA and pitch estimator. In white Gaussian noise, we derive even more computationally efficient solutions which are designed using the narrowband power spectrum of the harmonics. Numerical results reveal the performance of the estimators in colored noise compared with the Cram\\'{e}r-Rao lower...
Efficient Use of Preisach Hysteresis Model in Computer Aided Design
Directory of Open Access Journals (Sweden)
IONITA, V.
2013-05-01
Full Text Available The paper presents a practical detailed analysis regarding the use of the classical Preisach hysteresis model, covering all the steps, from measuring the necessary data for the model identification to the implementation in a software code for Computer Aided Design (CAD in Electrical Engineering. An efficient numerical method is proposed and the hysteresis modeling accuracy is tested on magnetic recording materials. The procedure includes the correction of the experimental data, which are used for the hysteresis model identification, taking into account the demagnetizing effect for the sample that is measured in an open-circuit device (a vibrating sample magnetometer.
An efficient and extensible approach for compressing phylogenetic trees
Matthews, Suzanne J; Williams, Tiffani L
2011-01-01
Background: Biologists require new algorithms to efficiently compress and store their large collections of phylogenetic trees. Our previous work showed that TreeZip is a promising approach for compressing phylogenetic trees. In this paper, we extend
Investigating the Multi-memetic Mind Evolutionary Computation Algorithm Efficiency
Directory of Open Access Journals (Sweden)
M. K. Sakharov
2017-01-01
Full Text Available In solving practically significant problems of global optimization, the objective function is often of high dimensionality and computational complexity and of nontrivial landscape as well. Studies show that often one optimization method is not enough for solving such problems efficiently - hybridization of several optimization methods is necessary.One of the most promising contemporary trends in this field are memetic algorithms (MA, which can be viewed as a combination of the population-based search for a global optimum and the procedures for a local refinement of solutions (memes, provided by a synergy. Since there are relatively few theoretical studies concerning the MA configuration, which is advisable for use to solve the black-box optimization problems, many researchers tend just to adaptive algorithms, which for search select the most efficient methods of local optimization for the certain domains of the search space.The article proposes a multi-memetic modification of a simple SMEC algorithm, using random hyper-heuristics. Presents the software algorithm and memes used (Nelder-Mead method, method of random hyper-sphere surface search, Hooke-Jeeves method. Conducts a comparative study of the efficiency of the proposed algorithm depending on the set and the number of memes. The study has been carried out using Rastrigin, Rosenbrock, and Zakharov multidimensional test functions. Computational experiments have been carried out for all possible combinations of memes and for each meme individually.According to results of study, conducted by the multi-start method, the combinations of memes, comprising the Hooke-Jeeves method, were successful. These results prove a rapid convergence of the method to a local optimum in comparison with other memes, since all methods perform the fixed number of iterations at the most.The analysis of the average number of iterations shows that using the most efficient sets of memes allows us to find the optimal
Understanding Plant Nitrogen Metabolism through Metabolomics and Computational Approaches
Directory of Open Access Journals (Sweden)
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.
New approach for calibration the efficiency of HPGe detectors
International Nuclear Information System (INIS)
Alnour, I.A.; Wagiran, H.; Suhaimi Hamzah; Siong, W.B.; Mohd Suhaimi Elias
2013-01-01
Full-text: This work evaluates the efficiency calibrating of HPGe detector coupled with Canberra GC3018 with Genie 2000 software and Ortec GEM25-76-XLB-C with Gamma Vision software; available at Neutron activation analysis laboratory in Malaysian Nuclear Agency (NM). The efficiency calibration curve was constructed from measurement of an IAEA, standard gamma point sources set composed by 214 Am, 57 Co, 133 Ba, 152 Eu, 137 Cs and 60 Co. The efficiency calibrations were performed for three different geometries: 5, 10 and 15 cm distances from the end cap detector. The polynomial parameters functions were simulated through a computer program, MATLAB in order to find an accurate fit to the experimental data points. The efficiency equation was established from the known fitted parameters which allow for the efficiency evaluation at particular energy of interest. The study shows that significant deviations in the efficiency, depending on the source-detector distance and photon energy. (author)
Energy Technology Data Exchange (ETDEWEB)
Adly, A.A., E-mail: adlyamr@gmail.com [Electrical Power and Machines Dept., Faculty of Engineering, Cairo University, Giza 12613 (Egypt); Abd-El-Hafiz, S.K. [Engineering Mathematics Department, Faculty of Engineering, Cairo University, Giza 12613 (Egypt)
2017-07-15
Highlights: • An approach to simulate hysteresis while taking shape anisotropy into consideration. • Utilizing the ensemble of triangular sub-regions hysteresis models in field computation. • A novel tool capable of carrying out field computation while keeping track of hysteresis losses. • The approach may be extended for 3D tetra-hedra sub-volumes. - Abstract: Field computation in media exhibiting hysteresis is crucial to a variety of applications such as magnetic recording processes and accurate determination of core losses in power devices. Recently, Hopfield neural networks (HNN) have been successfully configured to construct scalar and vector hysteresis models. This paper presents an efficient hysteresis modeling methodology and its implementation in field computation applications. The methodology is based on the application of the integral equation approach on discretized triangular magnetic sub-regions. Within every triangular sub-region, hysteresis properties are realized using a 3-node HNN. Details of the approach and sample computation results are given in the paper.
Computationally efficient implementation of combustion chemistry in parallel PDF calculations
International Nuclear Information System (INIS)
Lu Liuyan; Lantz, Steven R.; Ren Zhuyin; Pope, Stephen B.
2009-01-01
In parallel calculations of combustion processes with realistic chemistry, the serial in situ adaptive tabulation (ISAT) algorithm [S.B. Pope, Computationally efficient implementation of combustion chemistry using in situ adaptive tabulation, Combustion Theory and Modelling, 1 (1997) 41-63; L. Lu, S.B. Pope, An improved algorithm for in situ adaptive tabulation, Journal of Computational Physics 228 (2009) 361-386] substantially speeds up the chemistry calculations on each processor. To improve the parallel efficiency of large ensembles of such calculations in parallel computations, in this work, the ISAT algorithm is extended to the multi-processor environment, with the aim of minimizing the wall clock time required for the whole ensemble. Parallel ISAT strategies are developed by combining the existing serial ISAT algorithm with different distribution strategies, namely purely local processing (PLP), uniformly random distribution (URAN), and preferential distribution (PREF). The distribution strategies enable the queued load redistribution of chemistry calculations among processors using message passing. They are implemented in the software x2f m pi, which is a Fortran 95 library for facilitating many parallel evaluations of a general vector function. The relative performance of the parallel ISAT strategies is investigated in different computational regimes via the PDF calculations of multiple partially stirred reactors burning methane/air mixtures. The results show that the performance of ISAT with a fixed distribution strategy strongly depends on certain computational regimes, based on how much memory is available and how much overlap exists between tabulated information on different processors. No one fixed strategy consistently achieves good performance in all the regimes. Therefore, an adaptive distribution strategy, which blends PLP, URAN and PREF, is devised and implemented. It yields consistently good performance in all regimes. In the adaptive parallel
Computationally efficient statistical differential equation modeling using homogenization
Hooten, Mevin B.; Garlick, Martha J.; Powell, James A.
2013-01-01
Statistical models using partial differential equations (PDEs) to describe dynamically evolving natural systems are appearing in the scientific literature with some regularity in recent years. Often such studies seek to characterize the dynamics of temporal or spatio-temporal phenomena such as invasive species, consumer-resource interactions, community evolution, and resource selection. Specifically, in the spatial setting, data are often available at varying spatial and temporal scales. Additionally, the necessary numerical integration of a PDE may be computationally infeasible over the spatial support of interest. We present an approach to impose computationally advantageous changes of support in statistical implementations of PDE models and demonstrate its utility through simulation using a form of PDE known as “ecological diffusion.” We also apply a statistical ecological diffusion model to a data set involving the spread of mountain pine beetle (Dendroctonus ponderosae) in Idaho, USA.
A Computational Framework for Efficient Low Temperature Plasma Simulations
Verma, Abhishek Kumar; Venkattraman, Ayyaswamy
2016-10-01
Over the past years, scientific computing has emerged as an essential tool for the investigation and prediction of low temperature plasmas (LTP) applications which includes electronics, nanomaterial synthesis, metamaterials etc. To further explore the LTP behavior with greater fidelity, we present a computational toolbox developed to perform LTP simulations. This framework will allow us to enhance our understanding of multiscale plasma phenomenon using high performance computing tools mainly based on OpenFOAM FVM distribution. Although aimed at microplasma simulations, the modular framework is able to perform multiscale, multiphysics simulations of physical systems comprises of LTP. Some salient introductory features are capability to perform parallel, 3D simulations of LTP applications on unstructured meshes. Performance of the solver is tested based on numerical results assessing accuracy and efficiency of benchmarks for problems in microdischarge devices. Numerical simulation of microplasma reactor at atmospheric pressure with hemispherical dielectric coated electrodes will be discussed and hence, provide an overview of applicability and future scope of this framework.
Gentzsch, Wolfgang
1986-01-01
The GAMM Committee for Numerical Methods in Fluid Mechanics organizes workshops which should bring together experts of a narrow field of computational fluid dynamics (CFD) to exchange ideas and experiences in order to speed-up the development in this field. In this sense it was suggested that a workshop should treat the solution of CFD problems on vector computers. Thus we organized a workshop with the title "The efficient use of vector computers with emphasis on computational fluid dynamics". The workshop took place at the Computing Centre of the University of Karlsruhe, March 13-15,1985. The participation had been restricted to 22 people of 7 countries. 18 papers have been presented. In the announcement of the workshop we wrote: "Fluid mechanics has actively stimulated the development of superfast vector computers like the CRAY's or CYBER 205. Now these computers on their turn stimulate the development of new algorithms which result in a high degree of vectorization (sca1ar/vectorized execution-time). But w...
Efficient universal computing architectures for decoding neural activity.
Directory of Open Access Journals (Sweden)
Benjamin I Rapoport
Full Text Available The ability to decode neural activity into meaningful control signals for prosthetic devices is critical to the development of clinically useful brain- machine interfaces (BMIs. Such systems require input from tens to hundreds of brain-implanted recording electrodes in order to deliver robust and accurate performance; in serving that primary function they should also minimize power dissipation in order to avoid damaging neural tissue; and they should transmit data wirelessly in order to minimize the risk of infection associated with chronic, transcutaneous implants. Electronic architectures for brain- machine interfaces must therefore minimize size and power consumption, while maximizing the ability to compress data to be transmitted over limited-bandwidth wireless channels. Here we present a system of extremely low computational complexity, designed for real-time decoding of neural signals, and suited for highly scalable implantable systems. Our programmable architecture is an explicit implementation of a universal computing machine emulating the dynamics of a network of integrate-and-fire neurons; it requires no arithmetic operations except for counting, and decodes neural signals using only computationally inexpensive logic operations. The simplicity of this architecture does not compromise its ability to compress raw neural data by factors greater than [Formula: see text]. We describe a set of decoding algorithms based on this computational architecture, one designed to operate within an implanted system, minimizing its power consumption and data transmission bandwidth; and a complementary set of algorithms for learning, programming the decoder, and postprocessing the decoded output, designed to operate in an external, nonimplanted unit. The implementation of the implantable portion is estimated to require fewer than 5000 operations per second. A proof-of-concept, 32-channel field-programmable gate array (FPGA implementation of this portion
Role of Soft Computing Approaches in HealthCare Domain: A Mini Review.
Gambhir, Shalini; Malik, Sanjay Kumar; Kumar, Yugal
2016-12-01
In the present era, soft computing approaches play a vital role in solving the different kinds of problems and provide promising solutions. Due to popularity of soft computing approaches, these approaches have also been applied in healthcare data for effectively diagnosing the diseases and obtaining better results in comparison to traditional approaches. Soft computing approaches have the ability to adapt itself according to problem domain. Another aspect is a good balance between exploration and exploitation processes. These aspects make soft computing approaches more powerful, reliable and efficient. The above mentioned characteristics make the soft computing approaches more suitable and competent for health care data. The first objective of this review paper is to identify the various soft computing approaches which are used for diagnosing and predicting the diseases. Second objective is to identify various diseases for which these approaches are applied. Third objective is to categories the soft computing approaches for clinical support system. In literature, it is found that large number of soft computing approaches have been applied for effectively diagnosing and predicting the diseases from healthcare data. Some of these are particle swarm optimization, genetic algorithm, artificial neural network, support vector machine etc. A detailed discussion on these approaches are presented in literature section. This work summarizes various soft computing approaches used in healthcare domain in last one decade. These approaches are categorized in five different categories based on the methodology, these are classification model based system, expert system, fuzzy and neuro fuzzy system, rule based system and case based system. Lot of techniques are discussed in above mentioned categories and all discussed techniques are summarized in the form of tables also. This work also focuses on accuracy rate of soft computing technique and tabular information is provided for
a Recursive Approach to Compute Normal Forms
HSU, L.; MIN, L. J.; FAVRETTO, L.
2001-06-01
Normal forms are instrumental in the analysis of dynamical systems described by ordinary differential equations, particularly when singularities close to a bifurcation are to be characterized. However, the computation of a normal form up to an arbitrary order is numerically hard. This paper focuses on the computer programming of some recursive formulas developed earlier to compute higher order normal forms. A computer program to reduce the system to its normal form on a center manifold is developed using the Maple symbolic language. However, it should be stressed that the program relies essentially on recursive numerical computations, while symbolic calculations are used only for minor tasks. Some strategies are proposed to save computation time. Examples are presented to illustrate the application of the program to obtain high order normalization or to handle systems with large dimension.
Prediction of Protein Thermostability by an Efficient Neural Network Approach
Directory of Open Access Journals (Sweden)
Jalal Rezaeenour
2016-10-01
Full Text Available Introduction: Manipulation of protein stability is important for understanding the principles that govern protein thermostability, both in basic research and industrial applications. Various data mining techniques exist for prediction of thermostable proteins. Furthermore, ANN methods have attracted significant attention for prediction of thermostability, because they constitute an appropriate approach to mapping the non-linear input-output relationships and massive parallel computing. Method: An Extreme Learning Machine (ELM was applied to estimate thermal behavior of 1289 proteins. In the proposed algorithm, the parameters of ELM were optimized using a Genetic Algorithm (GA, which tuned a set of input variables, hidden layer biases, and input weights, to and enhance the prediction performance. The method was executed on a set of amino acids, yielding a total of 613 protein features. A number of feature selection algorithms were used to build subsets of the features. A total of 1289 protein samples and 613 protein features were calculated from UniProt database to understand features contributing to the enzymes’ thermostability and find out the main features that influence this valuable characteristic. Results:At the primary structure level, Gln, Glu and polar were the features that mostly contributed to protein thermostability. At the secondary structure level, Helix_S, Coil, and charged_Coil were the most important features affecting protein thermostability. These results suggest that the thermostability of proteins is mainly associated with primary structural features of the protein. According to the results, the influence of primary structure on the thermostabilty of a protein was more important than that of the secondary structure. It is shown that prediction accuracy of ELM (mean square error can improve dramatically using GA with error rates RMSE=0.004 and MAPE=0.1003. Conclusion: The proposed approach for forecasting problem
Energy Technology Data Exchange (ETDEWEB)
Hough, Patricia Diane (Sandia National Laboratories, Livermore, CA); Gray, Genetha Anne (Sandia National Laboratories, Livermore, CA); Castro, Joseph Pete Jr. (; .); Giunta, Anthony Andrew
2006-01-01
Many engineering application problems use optimization algorithms in conjunction with numerical simulators to search for solutions. The formulation of relevant objective functions and constraints dictate possible optimization algorithms. Often, a gradient based approach is not possible since objective functions and constraints can be nonlinear, nonconvex, non-differentiable, or even discontinuous and the simulations involved can be computationally expensive. Moreover, computational efficiency and accuracy are desirable and also influence the choice of solution method. With the advent and increasing availability of massively parallel computers, computational speed has increased tremendously. Unfortunately, the numerical and model complexities of many problems still demand significant computational resources. Moreover, in optimization, these expenses can be a limiting factor since obtaining solutions often requires the completion of numerous computationally intensive simulations. Therefore, we propose a multifidelity optimization algorithm (MFO) designed to improve the computational efficiency of an optimization method for a wide range of applications. In developing the MFO algorithm, we take advantage of the interactions between multi fidelity models to develop a dynamic and computational time saving optimization algorithm. First, a direct search method is applied to the high fidelity model over a reduced design space. In conjunction with this search, a specialized oracle is employed to map the design space of this high fidelity model to that of a computationally cheaper low fidelity model using space mapping techniques. Then, in the low fidelity space, an optimum is obtained using gradient or non-gradient based optimization, and it is mapped back to the high fidelity space. In this paper, we describe the theory and implementation details of our MFO algorithm. We also demonstrate our MFO method on some example problems and on two applications: earth penetrators and
Error characterization for asynchronous computations: Proxy equation approach
Sallai, Gabriella; Mittal, Ankita; Girimaji, Sharath
2017-11-01
Numerical techniques for asynchronous fluid flow simulations are currently under development to enable efficient utilization of massively parallel computers. These numerical approaches attempt to accurately solve time evolution of transport equations using spatial information at different time levels. The truncation error of asynchronous methods can be divided into two parts: delay dependent (EA) or asynchronous error and delay independent (ES) or synchronous error. The focus of this study is a specific asynchronous error mitigation technique called proxy-equation approach. The aim of this study is to examine these errors as a function of the characteristic wavelength of the solution. Mitigation of asynchronous effects requires that the asynchronous error be smaller than synchronous truncation error. For a simple convection-diffusion equation, proxy-equation error analysis identifies critical initial wave-number, λc. At smaller wave numbers, synchronous error are larger than asynchronous errors. We examine various approaches to increase the value of λc in order to improve the range of applicability of proxy-equation approach.
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
CREATIVE APPROACHES TO COMPUTER SCIENCE EDUCATION
Directory of Open Access Journals (Sweden)
V. B. Raspopov
2010-04-01
Full Text Available Using the example of PPS «Toolbox of multimedia lessons «For Children About Chopin» we demonstrate the possibility of involving creative students in developing the software packages for educational purposes. Similar projects can be assigned to school and college students studying computer sciences and informatics, and implemented under the teachers’ supervision, as advanced assignments or thesis projects as a part of a high school course IT or Computer Sciences, a college course of Applied Scientific Research, or as a part of preparation for students’ participation in the Computer Science competitions or IT- competitions of Youth Academy of Sciences ( MAN in Russian or in Ukrainian.
An efficient and general numerical method to compute steady uniform vortices
Luzzatto-Fegiz, Paolo; Williamson, Charles H. K.
2011-07-01
Steady uniform vortices are widely used to represent high Reynolds number flows, yet their efficient computation still presents some challenges. Existing Newton iteration methods become inefficient as the vortices develop fine-scale features; in addition, these methods cannot, in general, find solutions with specified Casimir invariants. On the other hand, available relaxation approaches are computationally inexpensive, but can fail to converge to a solution. In this paper, we overcome these limitations by introducing a new discretization, based on an inverse-velocity map, which radically increases the efficiency of Newton iteration methods. In addition, we introduce a procedure to prescribe Casimirs and remove the degeneracies in the steady vorticity equation, thus ensuring convergence for general vortex configurations. We illustrate our methodology by considering several unbounded flows involving one or two vortices. Our method enables the computation, for the first time, of steady vortices that do not exhibit any geometric symmetry. In addition, we discover that, as the limiting vortex state for each flow is approached, each family of solutions traces a clockwise spiral in a bifurcation plot consisting of a velocity-impulse diagram. By the recently introduced "IVI diagram" stability approach [Phys. Rev. Lett. 104 (2010) 044504], each turn of this spiral is associated with a loss of stability for the steady flows. Such spiral structure is suggested to be a universal feature of steady, uniform-vorticity flows.
A strategy for improved computational efficiency of the method of anchored distributions
Over, Matthew William; Yang, Yarong; Chen, Xingyuan; Rubin, Yoram
2013-06-01
This paper proposes a strategy for improving the computational efficiency of model inversion using the method of anchored distributions (MAD) by "bundling" similar model parametrizations in the likelihood function. Inferring the likelihood function typically requires a large number of forward model (FM) simulations for each possible model parametrization; as a result, the process is quite expensive. To ease this prohibitive cost, we present an approximation for the likelihood function called bundling that relaxes the requirement for high quantities of FM simulations. This approximation redefines the conditional statement of the likelihood function as the probability of a set of similar model parametrizations "bundle" replicating field measurements, which we show is neither a model reduction nor a sampling approach to improving the computational efficiency of model inversion. To evaluate the effectiveness of these modifications, we compare the quality of predictions and computational cost of bundling relative to a baseline MAD inversion of 3-D flow and transport model parameters. Additionally, to aid understanding of the implementation we provide a tutorial for bundling in the form of a sample data set and script for the R statistical computing language. For our synthetic experiment, bundling achieved a 35% reduction in overall computational cost and had a limited negative impact on predicted probability distributions of the model parameters. Strategies for minimizing error in the bundling approximation, for enforcing similarity among the sets of model parametrizations, and for identifying convergence of the likelihood function are also presented.
Efficient O(N) recursive computation of the operational space inertial matrix
International Nuclear Information System (INIS)
Lilly, K.W.; Orin, D.E.
1993-01-01
The operational space inertia matrix Λ reflects the dynamic properties of a robot manipulator to its tip. In the control domain, it may be used to decouple force and/or motion control about the manipulator workspace axes. The matrix Λ also plays an important role in the development of efficient algorithms for the dynamic simulation of closed-chain robotic mechanisms, including simple closed-chain mechanisms such as multiple manipulator systems and walking machines. The traditional approach used to compute Λ has a computational complexity of O(N 3 ) for an N degree-of-freedom manipulator. This paper presents the development of a recursive algorithm for computing the operational space inertia matrix (OSIM) that reduces the computational complexity to O(N). This algorithm, the inertia propagation method, is based on a single recursion that begins at the base of the manipulator and progresses out to the last link. Also applicable to redundant systems and mechanisms with multiple-degree-of-freedom joints, the inertia propagation method is the most efficient method known for computing Λ for N ≥ 6. The numerical accuracy of the algorithm is discussed for a PUMA 560 robot with a fixed base
Modeling Techniques for a Computational Efficient Dynamic Turbofan Engine Model
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Rory A. Roberts
2014-01-01
Full Text Available A transient two-stream engine model has been developed. Individual component models developed exclusively in MATLAB/Simulink including the fan, high pressure compressor, combustor, high pressure turbine, low pressure turbine, plenum volumes, and exit nozzle have been combined to investigate the behavior of a turbofan two-stream engine. Special attention has been paid to the development of transient capabilities throughout the model, increasing physics model, eliminating algebraic constraints, and reducing simulation time through enabling the use of advanced numerical solvers. The lessening of computation time is paramount for conducting future aircraft system-level design trade studies and optimization. The new engine model is simulated for a fuel perturbation and a specified mission while tracking critical parameters. These results, as well as the simulation times, are presented. The new approach significantly reduces the simulation time.
Efficient Computational Design of a Scaffold for Cartilage Cell Regeneration
DEFF Research Database (Denmark)
Tajsoleiman, Tannaz; Jafar Abdekhodaie, Mohammad; Gernaey, Krist V.
2018-01-01
Due to the sensitivity of mammalian cell cultures, understanding the influence of operating conditions during a tissue generation procedure is crucial. In this regard, a detailed study of scaffold based cell culture under a perfusion flow is presented with the aid of mathematical modelling...... and computational fluid dynamics (CFD). With respect to the complexity of the case study, this work focuses solely on the effect of nutrient and metabolite concentrations, and the possible influence of fluid-induced shear stress on a targeted cell (cartilage) culture. The simulation set up gives the possibility...... of predicting the cell culture behavior under various operating conditions and scaffold designs. Thereby, the exploitation of the predictive simulation into a newly developed stochastic routine provides the opportunity of exploring improved scaffold geometry designs. This approach was applied on a common type...
Efficient Variational Approaches for Deformable Registration of Images
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Mehmet Ali Akinlar
2012-01-01
Full Text Available Dirichlet, anisotropic, and Huber regularization terms are presented for efficient registration of deformable images. Image registration, an ill-posed optimization problem, is solved using a gradient-descent-based method and some fundamental theorems in calculus of variations. Euler-Lagrange equations with homogeneous Neumann boundary conditions are obtained. These equations are discretized by multigrid and finite difference numerical techniques. The method is applied to the registration of brain MR images of size 65×65. Computational results indicate that the presented method is quite fast and efficient in the registration of deformable medical images.
An efficient method for computing the absorption of solar radiation by water vapor
Chou, M.-D.; Arking, A.
1981-01-01
Chou and Arking (1980) have developed a fast but accurate method for computing the IR cooling rate due to water vapor. Using a similar approach, the considered investigation develops a method for computing the heating rates due to the absorption of solar radiation by water vapor in the wavelength range from 4 to 8.3 micrometers. The validity of the method is verified by comparison with line-by-line calculations. An outline is provided of an efficient method for transmittance and flux computations based upon actual line parameters. High speed is achieved by employing a one-parameter scaling approximation to convert an inhomogeneous path into an equivalent homogeneous path at suitably chosen reference conditions.
Computational and Experimental Approaches to Visual Aesthetics
Brachmann, Anselm; Redies, Christoph
2017-01-01
Aesthetics has been the subject of long-standing debates by philosophers and psychologists alike. In psychology, it is generally agreed that aesthetic experience results from an interaction between perception, cognition, and emotion. By experimental means, this triad has been studied in the field of experimental aesthetics, which aims to gain a better understanding of how aesthetic experience relates to fundamental principles of human visual perception and brain processes. Recently, researchers in computer vision have also gained interest in the topic, giving rise to the field of computational aesthetics. With computing hardware and methodology developing at a high pace, the modeling of perceptually relevant aspect of aesthetic stimuli has a huge potential. In this review, we present an overview of recent developments in computational aesthetics and how they relate to experimental studies. In the first part, we cover topics such as the prediction of ratings, style and artist identification as well as computational methods in art history, such as the detection of influences among artists or forgeries. We also describe currently used computational algorithms, such as classifiers and deep neural networks. In the second part, we summarize results from the field of experimental aesthetics and cover several isolated image properties that are believed to have a effect on the aesthetic appeal of visual stimuli. Their relation to each other and to findings from computational aesthetics are discussed. Moreover, we compare the strategies in the two fields of research and suggest that both fields would greatly profit from a joined research effort. We hope to encourage researchers from both disciplines to work more closely together in order to understand visual aesthetics from an integrated point of view. PMID:29184491
Petra, Cosmin G.; Schenk, Olaf; Lubin, Miles; Gä ertner, Klaus
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.
Efficient quantum computation in a network with probabilistic gates and logical encoding
DEFF Research Database (Denmark)
Borregaard, J.; Sørensen, A. S.; Cirac, J. I.
2017-01-01
An approach to efficient quantum computation with probabilistic gates is proposed and analyzed in both a local and nonlocal setting. It combines heralded gates previously studied for atom or atomlike qubits with logical encoding from linear optical quantum computation in order to perform high......-fidelity quantum gates across a quantum network. The error-detecting properties of the heralded operations ensure high fidelity while the encoding makes it possible to correct for failed attempts such that deterministic and high-quality gates can be achieved. Importantly, this is robust to photon loss, which...... is typically the main obstacle to photonic-based quantum information processing. Overall this approach opens a path toward quantum networks with atomic nodes and photonic links....
Efficiently computing exact geodesic loops within finite steps.
Xin, Shi-Qing; He, Ying; Fu, Chi-Wing
2012-06-01
Closed geodesics, or geodesic loops, are crucial to the study of differential topology and differential geometry. Although the existence and properties of closed geodesics on smooth surfaces have been widely studied in mathematics community, relatively little progress has been made on how to compute them on polygonal surfaces. Most existing algorithms simply consider the mesh as a graph and so the resultant loops are restricted only on mesh edges, which are far from the actual geodesics. This paper is the first to prove the existence and uniqueness of geodesic loop restricted on a closed face sequence; it contributes also with an efficient algorithm to iteratively evolve an initial closed path on a given mesh into an exact geodesic loop within finite steps. Our proposed algorithm takes only an O(k) space complexity and an O(mk) time complexity (experimentally), where m is the number of vertices in the region bounded by the initial loop and the resultant geodesic loop, and k is the average number of edges in the edge sequences that the evolving loop passes through. In contrast to the existing geodesic curvature flow methods which compute an approximate geodesic loop within a predefined threshold, our method is exact and can apply directly to triangular meshes without needing to solve any differential equation with a numerical solver; it can run at interactive speed, e.g., in the order of milliseconds, for a mesh with around 50K vertices, and hence, significantly outperforms existing algorithms. Actually, our algorithm could run at interactive speed even for larger meshes. Besides the complexity of the input mesh, the geometric shape could also affect the number of evolving steps, i.e., the performance. We motivate our algorithm with an interactive shape segmentation example shown later in the paper.
An Efficient Integer Coding and Computing Method for Multiscale Time Segment
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TONG Xiaochong
2016-12-01
Full Text Available This article focus on the exist problem and status of current time segment coding, proposed a new set of approach about time segment coding: multi-scale time segment integer coding (MTSIC. This approach utilized the tree structure and the sort by size formed among integer, it reflected the relationship among the multi-scale time segments: order, include/contained, intersection, etc., and finally achieved an unity integer coding processing for multi-scale time. On this foundation, this research also studied the computing method for calculating the time relationships of MTSIC, to support an efficient calculation and query based on the time segment, and preliminary discussed the application method and prospect of MTSIC. The test indicated that, the implement of MTSIC is convenient and reliable, and the transformation between it and the traditional method is convenient, it has the very high efficiency in query and calculating.
Unified commutation-pruning technique for efficient computation of composite DFTs
Castro-Palazuelos, David E.; Medina-Melendrez, Modesto Gpe.; Torres-Roman, Deni L.; Shkvarko, Yuriy V.
2015-12-01
An efficient computation of a composite length discrete Fourier transform (DFT), as well as a fast Fourier transform (FFT) of both time and space data sequences in uncertain (non-sparse or sparse) computational scenarios, requires specific processing algorithms. Traditional algorithms typically employ some pruning methods without any commutations, which prevents them from attaining the potential computational efficiency. In this paper, we propose an alternative unified approach with automatic commutations between three computational modalities aimed at efficient computations of the pruned DFTs adapted for variable composite lengths of the non-sparse input-output data. The first modality is an implementation of the direct computation of a composite length DFT, the second one employs the second-order recursive filtering method, and the third one performs the new pruned decomposed transform. The pruned decomposed transform algorithm performs the decimation in time or space (DIT) data acquisition domain and, then, decimation in frequency (DIF). The unified combination of these three algorithms is addressed as the DFTCOMM technique. Based on the treatment of the combinational-type hypotheses testing optimization problem of preferable allocations between all feasible commuting-pruning modalities, we have found the global optimal solution to the pruning problem that always requires a fewer or, at most, the same number of arithmetic operations than other feasible modalities. The DFTCOMM method outperforms the existing competing pruning techniques in the sense of attainable savings in the number of required arithmetic operations. It requires fewer or at most the same number of arithmetic operations for its execution than any other of the competing pruning methods reported in the literature. Finally, we provide the comparison of the DFTCOMM with the recently developed sparse fast Fourier transform (SFFT) algorithmic family. We feature that, in the sensing scenarios with
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
Gaussian Radial Basis Function for Efficient Computation of Forest Indirect Illumination
Abbas, Fayçal; Babahenini, Mohamed Chaouki
2018-06-01
Global illumination of natural scenes in real time like forests is one of the most complex problems to solve, because the multiple inter-reflections between the light and material of the objects composing the scene. The major problem that arises is the problem of visibility computation. In fact, the computing of visibility is carried out for all the set of leaves visible from the center of a given leaf, given the enormous number of leaves present in a tree, this computation performed for each leaf of the tree which also reduces performance. We describe a new approach that approximates visibility queries, which precede in two steps. The first step is to generate point cloud representing the foliage. We assume that the point cloud is composed of two classes (visible, not-visible) non-linearly separable. The second step is to perform a point cloud classification by applying the Gaussian radial basis function, which measures the similarity in term of distance between each leaf and a landmark leaf. It allows approximating the visibility requests to extract the leaves that will be used to calculate the amount of indirect illumination exchanged between neighbor leaves. Our approach allows efficiently treat the light exchanges in the scene of a forest, it allows a fast computation and produces images of good visual quality, all this takes advantage of the immense power of computation of the GPU.
Computational Approaches to Chemical Hazard Assessment
Luechtefeld, Thomas; Hartung, Thomas
2018-01-01
Summary Computational prediction of toxicity has reached new heights as a result of decades of growth in the magnitude and diversity of biological data. Public packages for statistics and machine learning make model creation faster. New theory in machine learning and cheminformatics enables integration of chemical structure, toxicogenomics, simulated and physical data in the prediction of chemical health hazards, and other toxicological information. Our earlier publications have characterized a toxicological dataset of unprecedented scale resulting from the European REACH legislation (Registration Evaluation Authorisation and Restriction of Chemicals). These publications dove into potential use cases for regulatory data and some models for exploiting this data. This article analyzes the options for the identification and categorization of chemicals, moves on to the derivation of descriptive features for chemicals, discusses different kinds of targets modeled in computational toxicology, and ends with a high-level perspective of the algorithms used to create computational toxicology models. PMID:29101769
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...
Measuring energy efficiency in economics: Shadow value approach
Khademvatani, Asgar
For decades, academic scholars and policy makers have commonly applied a simple average measure, energy intensity, for studying energy efficiency. In contrast, we introduce a distinctive marginal measure called energy shadow value (SV) for modeling energy efficiency drawn on economic theory. This thesis demonstrates energy SV advantages, conceptually and empirically, over the average measure recognizing marginal technical energy efficiency and unveiling allocative energy efficiency (energy SV to energy price). Using a dual profit function, the study illustrates how treating energy as quasi-fixed factor called quasi-fixed approach offers modeling advantages and is appropriate in developing an explicit model for energy efficiency. We address fallacies and misleading results using average measure and demonstrate energy SV advantage in inter- and intra-country energy efficiency comparison. Energy efficiency dynamics and determination of efficient allocation of energy use are shown through factors impacting energy SV: capital, technology, and environmental obligations. To validate the energy SV, we applied a dual restricted cost model using KLEM dataset for the 35 US sectors stretching from 1958 to 2000 and selected a sample of the four sectors. Following the empirical results, predicted wedges between energy price and the SV growth indicate a misallocation of energy use in stone, clay and glass (SCG) and communications (Com) sectors with more evidence in the SCG compared to the Com sector, showing overshoot in energy use relative to optimal paths and cost increases from sub-optimal energy use. The results show that energy productivity is a measure of technical efficiency and is void of information on the economic efficiency of energy use. Decomposing energy SV reveals that energy, capital and technology played key roles in energy SV increases helping to consider and analyze policy implications of energy efficiency improvement. Applying the marginal measure, we also
Discovering the Network Topology: An Efficient Approach for SDN
Directory of Open Access Journals (Sweden)
Leonardo OCHOA-ADAY
2016-11-01
Full Text Available Network topology is a physical description of the overall resources in the network. Collecting this information using efficient mechanisms becomes a critical task for important network functions such as routing, network management, quality of service (QoS, among many others. Recent technologies like Software-Defined Networks (SDN have emerged as promising approaches for managing the next generation networks. In order to ensure a proficient topology discovery service in SDN, we propose a simple agents-based mechanism. This mechanism improves the overall efficiency of the topology discovery process. In this paper, an algorithm for a novel Topology Discovery Protocol (SD-TDP is described. This protocol will be implemented in each switch through a software agent. Thus, this approach will provide a distributed solution to solve the problem of network topology discovery in a more simple and efficient way.
Approaching Engagement towards Human-Engaged Computing
DEFF Research Database (Denmark)
Niksirat, Kavous Salehzadeh; Sarcar, Sayan; Sun, Huatong
2018-01-01
Debates regarding the nature and role of HCI research and practice have intensified in recent years, given the ever increasingly intertwined relations between humans and technologies. The framework of Human-Engaged Computing (HEC) was proposed and developed over a series of scholarly workshops to...
Computational and mathematical approaches to societal transitions
J.S. Timmermans (Jos); F. Squazzoni (Flaminio); J. de Haan (Hans)
2008-01-01
textabstractAfter an introduction of the theoretical framework and concepts of transition studies, this article gives an overview of how structural change in social systems has been studied from various disciplinary perspectives. This overview first leads to the conclusion that computational and
Heterogeneous Computing in Economics: A Simplified Approach
DEFF Research Database (Denmark)
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 ...
A Constructive Induction Approach to Computer Immunology
1999-03-01
LVM98] Lamont, Gary B., David A. Van Veldhuizen , and Robert E Marmelstein, A Distributed Architecture for a Self-Adaptive Computer Virus...Artificial Intelligence, Herndon, VA, 1995. [MVL98] Marmelstein, Robert E., David A. Van Veldhuizen , and Gary B. Lamont. Modeling & Analysis
Computationally Efficient Nonlinear Bell Inequalities for Quantum Networks
Luo, Ming-Xing
2018-04-01
The correlations in quantum networks have attracted strong interest with new types of violations of the locality. The standard Bell inequalities cannot characterize the multipartite correlations that are generated by multiple sources. The main problem is that no computationally efficient method is available for constructing useful Bell inequalities for general quantum networks. In this work, we show a significant improvement by presenting new, explicit Bell-type inequalities for general networks including cyclic networks. These nonlinear inequalities are related to the matching problem of an equivalent unweighted bipartite graph that allows constructing a polynomial-time algorithm. For the quantum resources consisting of bipartite entangled pure states and generalized Greenberger-Horne-Zeilinger (GHZ) states, we prove the generic nonmultilocality of quantum networks with multiple independent observers using new Bell inequalities. The violations are maximal with respect to the presented Tsirelson's bound for Einstein-Podolsky-Rosen states and GHZ states. Moreover, these violations hold for Werner states or some general noisy states. Our results suggest that the presented Bell inequalities can be used to characterize experimental quantum networks.
NEW APPROACHES TO EFFICIENCY OF MASSIVE ONLINE COURSE
Directory of Open Access Journals (Sweden)
Liubov S. Lysitsina
2014-09-01
Full Text Available This paper is focused on efficiency of e-learning, in general, and massive online course in programming and information technology, in particular. Several innovative approaches and scenarios have been proposed, developed, implemented and verified by the authors, including 1 a new approach to organize and use automatic immediate feedback that significantly helps a learner to verify developed code and increases an efficiency of learning, 2 a new approach to construct learning interfaces – it is based on “develop a code – get a result – validate a code” technique, 3 three scenarios of visualization and verification of developed code, 4 a new multi-stage approach to solve complex programming assignments, 5 a new implementation of “perfectionism” game mechanics in a massive online course. Overall, due to implementation of proposed and developed approaches, the efficiency of massive online course has been considerably increased, particularly 1 the additional 27.9 % of students were able to complete successfully “Web design and development using HTML5 and CSS3” massive online course at ITMO University, and 2 based on feedback from 5588 students a “perfectionism” game mechanics noticeably improves students’ involvement into course activities and retention factor.
Efficiency of supply chain management. Strategic and operational approach
Directory of Open Access Journals (Sweden)
Grzegorz Lichocik
2013-06-01
Full Text Available Background: One of the most important issues subject to theoretical considerations and empirical studies is the measurement of efficiency of activities in logistics and supply chain management. Simultaneously, efficiency is one of the terms interpreted in an ambiguous and multi-aspect manner, depending on the subject of a study. The multitude of analytical dimensions of this term results in the fact that, apart from economic efficiency being the basic study area, other dimensions perceived as an added value by different groups of supply chain participants become more and more important. Methods: The objective of this paper is to attempt to explain the problem of supply chain management efficiency in the context of general theoretical considerations relating to supply chain management. The authors have also highlighted determinants and practical implications of supply chain management efficiency in strategic and operational contexts. The study employs critical analyses of logistics literature and the free-form interview with top management representatives of a company operating in the TSL sector. Results: We must find a comprehensive approach to supply chain efficiency including all analytical dimensions connected with real goods and services flow. An effective supply chain must be cost-effective (ensuring economic efficiency of a chain, functional (reducing processes, lean, minimising the number of links in the chain to the necessary ones, adapting supply chain participants' internal processes to a common objective based on its efficiency and ensuring high quality of services (customer-oriented logistics systems. Conclusions: Efficiency of supply chains is not only a task for which a logistics department is responsible as it is a strategic decision taken by the management as regards the method of future company's operation. Correctly planned and fulfilled logistics tasks may result in improving performance of a company as well as the whole
ALTERNATIVE APPROACHES TO EFFICIENCY EVALUATION OF HIGHER EDUCATION INSTITUTIONS
Directory of Open Access Journals (Sweden)
Furková, Andrea
2013-09-01
Full Text Available Evaluation of efficiency and ranking of higher education institutions is very popular and important topic of public policy. The assessment of the quality of higher education institutions can stimulate positive changes in higher education. In this study we focus on assessment and ranking of Slovak economic faculties. We try to apply two different quantitative approaches for evaluation Slovak economic faculties - Stochastic Frontier Analysis (SFA as an econometric approach and PROMETHEE II as multicriteria decision making method. Via SFA we examine faculties’ success from scientific point of view, i.e. their success in area of publications and citations. Next part of analysis deals with assessing of Slovak economic sciences faculties from overall point of view through the multicriteria decision making method. In the analysis we employ panel data covering 11 economic faculties observed over the period of 5 years. Our main aim is to point out other quantitative approaches to efficiency estimation of higher education institutions.
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
The Effect of Computer Automation on Institutional Review Board (IRB) Office Efficiency
Oder, Karl; Pittman, Stephanie
2015-01-01
Companies purchase computer systems to make their processes more efficient through automation. Some academic medical centers (AMC) have purchased computer systems for their institutional review boards (IRB) to increase efficiency and compliance with regulations. IRB computer systems are expensive to purchase, deploy, and maintain. An AMC should…
Computational and Game-Theoretic Approaches for Modeling Bounded Rationality
L. Waltman (Ludo)
2011-01-01
textabstractThis thesis studies various computational and game-theoretic approaches to economic modeling. Unlike traditional approaches to economic modeling, the approaches studied in this thesis do not rely on the assumption that economic agents behave in a fully rational way. Instead, economic
Computational Thinking and Practice - A Generic Approach to Computing in Danish High Schools
DEFF Research Database (Denmark)
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...
Machine learning and computer vision approaches for phenotypic profiling.
Grys, Ben T; Lo, Dara S; Sahin, Nil; Kraus, Oren Z; Morris, Quaid; Boone, Charles; Andrews, Brenda J
2017-01-02
With recent advances in high-throughput, automated microscopy, there has been an increased demand for effective computational strategies to analyze large-scale, image-based data. To this end, computer vision approaches have been applied to cell segmentation and feature extraction, whereas machine-learning approaches have been developed to aid in phenotypic classification and clustering of data acquired from biological images. Here, we provide an overview of the commonly used computer vision and machine-learning methods for generating and categorizing phenotypic profiles, highlighting the general biological utility of each approach. © 2017 Grys et al.
Balancing Accuracy and Computational Efficiency for Ternary Gas Hydrate Systems
White, M. D.
2011-12-01
phase transitions. This paper describes and demonstrates a numerical solution scheme for ternary hydrate systems that seeks a balance between accuracy and computational efficiency. This scheme uses a generalize cubic equation of state, functional forms for the hydrate equilibria and cage occupancies, variable switching scheme for phase transitions, and kinetic exchange of hydrate formers (i.e., CH4, CO2, and N2) between the mobile phases (i.e., aqueous, liquid CO2, and gas) and hydrate phase. Accuracy of the scheme will be evaluated by comparing property values and phase equilibria against experimental data. Computational efficiency of the scheme will be evaluated by comparing the base scheme against variants. The application of interest will the production of a natural gas hydrate deposit from a geologic formation, using the guest molecule exchange process; where, a mixture of CO2 and N2 are injected into the formation. During the guest-molecule exchange, CO2 and N2 will predominately replace CH4 in the large and small cages of the sI structure, respectively.
A computational approach to finding novel targets for existing drugs.
Directory of Open Access Journals (Sweden)
Yvonne Y Li
2011-09-01
Full Text Available Repositioning existing drugs for new therapeutic uses is an efficient approach to drug discovery. We have developed a computational drug repositioning pipeline to perform large-scale molecular docking of small molecule drugs against protein drug targets, in order to map the drug-target interaction space and find novel interactions. Our method emphasizes removing false positive interaction predictions using criteria from known interaction docking, consensus scoring, and specificity. In all, our database contains 252 human protein drug targets that we classify as reliable-for-docking as well as 4621 approved and experimental small molecule drugs from DrugBank. These were cross-docked, then filtered through stringent scoring criteria to select top drug-target interactions. In particular, we used MAPK14 and the kinase inhibitor BIM-8 as examples where our stringent thresholds enriched the predicted drug-target interactions with known interactions up to 20 times compared to standard score thresholds. We validated nilotinib as a potent MAPK14 inhibitor in vitro (IC50 40 nM, suggesting a potential use for this drug in treating inflammatory diseases. The published literature indicated experimental evidence for 31 of the top predicted interactions, highlighting the promising nature of our approach. Novel interactions discovered may lead to the drug being repositioned as a therapeutic treatment for its off-target's associated disease, added insight into the drug's mechanism of action, and added insight into the drug's side effects.
Computational approach to large quantum dynamical problems
International Nuclear Information System (INIS)
Friesner, R.A.; Brunet, J.P.; Wyatt, R.E.; Leforestier, C.; Binkley, S.
1987-01-01
The organizational structure is described for a new program that permits computations on a variety of quantum mechanical problems in chemical dynamics and spectroscopy. Particular attention is devoted to developing and using algorithms that exploit the capabilities of current vector supercomputers. A key component in this procedure is the recursive transformation of the large sparse Hamiltonian matrix into a much smaller tridiagonal matrix. An application to time-dependent laser molecule energy transfer is presented. Rate of energy deposition in the multimode molecule for systematic variations in the molecular intermode coupling parameters is emphasized
Computationally efficient models of neuromuscular recruitment and mechanics.
Song, D; Raphael, G; Lan, N; Loeb, G E
2008-06-01
We have improved the stability and computational efficiency of a physiologically realistic, virtual muscle (VM 3.*) model (Cheng et al 2000 J. Neurosci. Methods 101 117-30) by a simpler structure of lumped fiber types and a novel recruitment algorithm. In the new version (VM 4.0), the mathematical equations are reformulated into state-space representation and structured into a CMEX S-function in SIMULINK. A continuous recruitment scheme approximates the discrete recruitment of slow and fast motor units under physiological conditions. This makes it possible to predict force output during smooth recruitment and derecruitment without having to simulate explicitly a large number of independently recruited units. We removed the intermediate state variable, effective length (Leff), which had been introduced to model the delayed length dependency of the activation-frequency relationship, but which had little effect and could introduce instability under physiological conditions of use. Both of these changes greatly reduce the number of state variables with little loss of accuracy compared to the original VM. The performance of VM 4.0 was validated by comparison with VM 3.1.5 for both single-muscle force production and a multi-joint task. The improved VM 4.0 model is more suitable for the analysis of neural control of movements and for design of prosthetic systems to restore lost or impaired motor functions. VM 4.0 is available via the internet and includes options to use the original VM model, which remains useful for detailed simulations of single motor unit behavior.
Computationally efficient models of neuromuscular recruitment and mechanics
Song, D.; Raphael, G.; Lan, N.; Loeb, G. E.
2008-06-01
We have improved the stability and computational efficiency of a physiologically realistic, virtual muscle (VM 3.*) model (Cheng et al 2000 J. Neurosci. Methods 101 117-30) by a simpler structure of lumped fiber types and a novel recruitment algorithm. In the new version (VM 4.0), the mathematical equations are reformulated into state-space representation and structured into a CMEX S-function in SIMULINK. A continuous recruitment scheme approximates the discrete recruitment of slow and fast motor units under physiological conditions. This makes it possible to predict force output during smooth recruitment and derecruitment without having to simulate explicitly a large number of independently recruited units. We removed the intermediate state variable, effective length (Leff), which had been introduced to model the delayed length dependency of the activation-frequency relationship, but which had little effect and could introduce instability under physiological conditions of use. Both of these changes greatly reduce the number of state variables with little loss of accuracy compared to the original VM. The performance of VM 4.0 was validated by comparison with VM 3.1.5 for both single-muscle force production and a multi-joint task. The improved VM 4.0 model is more suitable for the analysis of neural control of movements and for design of prosthetic systems to restore lost or impaired motor functions. VM 4.0 is available via the internet and includes options to use the original VM model, which remains useful for detailed simulations of single motor unit behavior.
On a multiscale approach for filter efficiency simulations
Iliev, Oleg
2014-07-01
Filtration in general, and the dead end depth filtration of solid particles out of fluid in particular, is intrinsic multiscale problem. The deposition (capturing of particles) essentially depends on local velocity, on microgeometry (pore scale geometry) of the filtering medium and on the diameter distribution of the particles. The deposited (captured) particles change the microstructure of the porous media what leads to change of permeability. The changed permeability directly influences the velocity field and pressure distribution inside the filter element. To close the loop, we mention that the velocity influences the transport and deposition of particles. In certain cases one can evaluate the filtration efficiency considering only microscale or only macroscale models, but in general an accurate prediction of the filtration efficiency requires multiscale models and algorithms. This paper discusses the single scale and the multiscale models, and presents a fractional time step discretization algorithm for the multiscale problem. The velocity within the filter element is computed at macroscale, and is used as input for the solution of microscale problems at selected locations of the porous medium. The microscale problem is solved with respect to transport and capturing of individual particles, and its solution is postprocessed to provide permeability values for macroscale computations. Results from computational experiments with an oil filter are presented and discussed.
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 complex network approach to cloud computing
International Nuclear Information System (INIS)
Travieso, Gonzalo; Ruggiero, Carlos Antônio; Bruno, Odemir Martinez; Costa, Luciano da Fontoura
2016-01-01
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 clients’ 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 underlaid by Erdős–Rényi (ER) and Barabási-Albert (BA) 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 the cost of communication between the client and the nearest server, and the balance of the distribution of tasks between the two servers. Regarding the latter, the ER topology provides better performance than the BA for smaller average degrees and opposite behaviour for larger average degrees. With respect to cost, smaller values are found in the BA topology irrespective of the average degree. In addition, we also verified that it is easier to find good servers in ER than in BA networks. Surprisingly, balance and cost are not too much affected by the presence of communities. However, for a well-defined community network, we found that it is important to assign each server to a different community so as to achieve better performance. (paper: interdisciplinary statistical mechanics )
A New Approach to Practical Active-Secure Two-Party Computation
DEFF Research Database (Denmark)
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...... a number of novel techniques for relating the outputs and inputs of OTs in a larger construction. We also report on an implementation of this approach, that shows that our protocol is more efficient than any previous one: For big enough circuits, we can evaluate more than 20000 Boolean gates per second...
Tarim, S.A.; Ozen, U.; Dogru, M.K.; Rossi, R.
2011-01-01
We provide an efficient computational approach to solve the mixed integer programming (MIP) model developed by Tarim and Kingsman [8] for solving a stochastic lot-sizing problem with service level constraints under the static–dynamic uncertainty strategy. The effectiveness of the proposed method
A Dynamic BI–Orthogonal Field Equation Approach to Efficient Bayesian Inversion
Directory of Open Access Journals (Sweden)
Tagade Piyush M.
2017-06-01
Full Text Available This paper proposes a novel computationally efficient stochastic spectral projection based approach to Bayesian inversion of a computer simulator with high dimensional parametric and model structure uncertainty. The proposed method is based on the decomposition of the solution into its mean and a random field using a generic Karhunen-Loève expansion. The random field is represented as a convolution of separable Hilbert spaces in stochastic and spatial dimensions that are spectrally represented using respective orthogonal bases. In particular, the present paper investigates generalized polynomial chaos bases for the stochastic dimension and eigenfunction bases for the spatial dimension. Dynamic orthogonality is used to derive closed-form equations for the time evolution of mean, spatial and the stochastic fields. The resultant system of equations consists of a partial differential equation (PDE that defines the dynamic evolution of the mean, a set of PDEs to define the time evolution of eigenfunction bases, while a set of ordinary differential equations (ODEs define dynamics of the stochastic field. This system of dynamic evolution equations efficiently propagates the prior parametric uncertainty to the system response. The resulting bi-orthogonal expansion of the system response is used to reformulate the Bayesian inference for efficient exploration of the posterior distribution. The efficacy of the proposed method is investigated for calibration of a 2D transient diffusion simulator with an uncertain source location and diffusivity. The computational efficiency of the method is demonstrated against a Monte Carlo method and a generalized polynomial chaos approach.
The green computing book tackling energy efficiency at large scale
Feng, Wu-chun
2014-01-01
Low-Power, Massively Parallel, Energy-Efficient Supercomputers The Blue Gene TeamCompiler-Driven Energy Efficiency Mahmut Kandemir and Shekhar Srikantaiah An Adaptive Run-Time System for Improving Energy Efficiency Chung-Hsing Hsu, Wu-chun Feng, and Stephen W. PooleEnergy-Efficient Multithreading through Run-Time Adaptation Exploring Trade-Offs between Energy Savings and Reliability in Storage Systems Ali R. Butt, Puranjoy Bhattacharjee, Guanying Wang, and Chris GniadyCross-Layer Power Management Zhikui Wang and Parthasarathy Ranganathan Energy-Efficient Virtualized Systems Ripal Nathuji and K
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 two-stage DEA approach for environmental efficiency measurement.
Song, Malin; Wang, Shuhong; Liu, Wei
2014-05-01
The slacks-based measure (SBM) model based on the constant returns to scale has achieved some good results in addressing the undesirable outputs, such as waste water and water gas, in measuring environmental efficiency. However, the traditional SBM model cannot deal with the scenario in which desirable outputs are constant. Based on the axiomatic theory of productivity, this paper carries out a systematic research on the SBM model considering undesirable outputs, and further expands the SBM model from the perspective of network analysis. The new model can not only perform efficiency evaluation considering undesirable outputs, but also calculate desirable and undesirable outputs separately. The latter advantage successfully solves the "dependence" problem of outputs, that is, we can not increase the desirable outputs without producing any undesirable outputs. The following illustration shows that the efficiency values obtained by two-stage approach are smaller than those obtained by the traditional SBM model. Our approach provides a more profound analysis on how to improve environmental efficiency of the decision making units.
Valasek, Lukas; Glasa, Jan
2017-12-01
Current fire simulation systems are capable to utilize advantages of high-performance computer (HPC) platforms available and to model fires efficiently in parallel. In this paper, efficiency of a corridor fire simulation on a HPC computer cluster is discussed. The parallel MPI version of Fire Dynamics Simulator is used for testing efficiency of selected strategies of allocation of computational resources of the cluster using a greater number of computational cores. Simulation results indicate that if the number of cores used is not equal to a multiple of the total number of cluster node cores there are allocation strategies which provide more efficient calculations.
Q-P Wave traveltime computation by an iterative approach
Ma, Xuxin; Alkhalifah, Tariq Ali
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.
Integration of case study approach, project design and computer ...
African Journals Online (AJOL)
Integration of case study approach, project design and computer modeling in managerial accounting education ... Journal of Fundamental and Applied Sciences ... in the Laboratory of Management Accounting and Controlling Systems at the ...
Fractal approach to computer-analytical modelling of tree crown
International Nuclear Information System (INIS)
Berezovskaya, F.S.; Karev, G.P.; Kisliuk, O.F.; Khlebopros, R.G.; Tcelniker, Yu.L.
1993-09-01
In this paper we discuss three approaches to the modeling of a tree crown development. These approaches are experimental (i.e. regressive), theoretical (i.e. analytical) and simulation (i.e. computer) modeling. The common assumption of these is that a tree can be regarded as one of the fractal objects which is the collection of semi-similar objects and combines the properties of two- and three-dimensional bodies. We show that a fractal measure of crown can be used as the link between the mathematical models of crown growth and light propagation through canopy. The computer approach gives the possibility to visualize a crown development and to calibrate the model on experimental data. In the paper different stages of the above-mentioned approaches are described. The experimental data for spruce, the description of computer system for modeling and the variant of computer model are presented. (author). 9 refs, 4 figs
A Novel Energy-Efficient Approach for Human Activity Recognition.
Zheng, Lingxiang; Wu, Dihong; Ruan, Xiaoyang; Weng, Shaolin; Peng, Ao; Tang, Biyu; Lu, Hai; Shi, Haibin; Zheng, Huiru
2017-09-08
In this paper, we propose a novel energy-efficient approach for mobile activity recognition system (ARS) to detect human activities. The proposed energy-efficient ARS, using low sampling rates, can achieve high recognition accuracy and low energy consumption. A novel classifier that integrates hierarchical support vector machine and context-based classification (HSVMCC) is presented to achieve a high accuracy of activity recognition when the sampling rate is less than the activity frequency, i.e., the Nyquist sampling theorem is not satisfied. We tested the proposed energy-efficient approach with the data collected from 20 volunteers (14 males and six females) and the average recognition accuracy of around 96.0% was achieved. Results show that using a low sampling rate of 1Hz can save 17.3% and 59.6% of energy compared with the sampling rates of 5 Hz and 50 Hz. The proposed low sampling rate approach can greatly reduce the power consumption while maintaining high activity recognition accuracy. The composition of power consumption in online ARS is also investigated in this paper.
A Hybrid Node Scheduling Approach Based on Energy Efficient Chain Routing for WSN
Directory of Open Access Journals (Sweden)
Yimei Kang
2014-04-01
Full Text Available Energy efficiency is usually a significant goal in wireless sensor networks (WSNs. In this work, an energy efficient chain (EEC data routing approach is first presented. The coverage and connectivity of WSNs are discussed based on EEC. A hybrid node scheduling approach is then proposed. It includes sleep scheduling for cyclically monitoring regions of interest in time-driven modes and wakeup scheduling for tracking emergency events in event-driven modes. A failure rate is introduced to the sleep scheduling to improve the reliability of the system. A wakeup sensor threshold and a sleep time threshold are introduced in the wakeup scheduling to reduce the consumption of energy to the possible extent. The results of the simulation show that the proposed algorithm can extend the effective lifetime of the network to twice that of PEAS. In addition, the proposed methods are computing efficient because they are very simple to implement.
Computationally efficient method for optical simulation of solar cells and their applications
Semenikhin, I.; Zanuccoli, M.; Fiegna, C.; Vyurkov, V.; Sangiorgi, E.
2013-01-01
This paper presents two novel implementations of the Differential method to solve the Maxwell equations in nanostructured optoelectronic solid state devices. The first proposed implementation is based on an improved and computationally efficient T-matrix formulation that adopts multiple-precision arithmetic to tackle the numerical instability problem which arises due to evanescent modes. The second implementation adopts the iterative approach that allows to achieve low computational complexity O(N logN) or better. The proposed algorithms may work with structures with arbitrary spatial variation of the permittivity. The developed two-dimensional numerical simulator is applied to analyze the dependence of the absorption characteristics of a thin silicon slab on the morphology of the front interface and on the angle of incidence of the radiation with respect to the device surface.
Computationally efficient SVM multi-class image recognition with confidence measures
International Nuclear Information System (INIS)
Makili, Lazaro; Vega, Jesus; Dormido-Canto, Sebastian; Pastor, Ignacio; Murari, Andrea
2011-01-01
Typically, machine learning methods produce non-qualified estimates, i.e. the accuracy and reliability of the predictions are not provided. Transductive predictors are very recent classifiers able to provide, simultaneously with the prediction, a couple of values (confidence and credibility) to reflect the quality of the prediction. Usually, a drawback of the transductive techniques for huge datasets and large dimensionality is the high computational time. To overcome this issue, a more efficient classifier has been used in a multi-class image classification problem in the TJ-II stellarator database. It is based on the creation of a hash function to generate several 'one versus the rest' classifiers for every class. By using Support Vector Machines as the underlying classifier, a comparison between the pure transductive approach and the new method has been performed. In both cases, the success rates are high and the computation time with the new method is up to 0.4 times the old one.
Fast Ss-Ilm a Computationally Efficient Algorithm to Discover Socially Important Locations
Dokuz, A. S.; Celik, M.
2017-11-01
Socially important locations are places which are frequently visited by social media users in their social media lifetime. Discovering socially important locations provide several valuable information about user behaviours on social media networking sites. However, discovering socially important locations are challenging due to data volume and dimensions, spatial and temporal calculations, location sparseness in social media datasets, and inefficiency of current algorithms. In the literature, several studies are conducted to discover important locations, however, the proposed approaches do not work in computationally efficient manner. In this study, we propose Fast SS-ILM algorithm by modifying the algorithm of SS-ILM to mine socially important locations efficiently. Experimental results show that proposed Fast SS-ILM algorithm decreases execution time of socially important locations discovery process up to 20 %.
Ivanov, Mikhail V; Babikov, Dmitri
2012-05-14
Efficient method is proposed for computing thermal rate constant of recombination reaction that proceeds according to the energy transfer mechanism, when an energized molecule is formed from reactants first, and is stabilized later by collision with quencher. The mixed quantum-classical theory for the collisional energy transfer and the ro-vibrational energy flow [M. Ivanov and D. Babikov, J. Chem. Phys. 134, 144107 (2011)] is employed to treat the dynamics of molecule + quencher collision. Efficiency is achieved by sampling simultaneously (i) the thermal collision energy, (ii) the impact parameter, and (iii) the incident direction of quencher, as well as (iv) the rotational state of energized molecule. This approach is applied to calculate third-order rate constant of the recombination reaction that forms the (16)O(18)O(16)O isotopomer of ozone. Comparison of the predicted rate vs. experimental result is presented.
FAST SS-ILM: A COMPUTATIONALLY EFFICIENT ALGORITHM TO DISCOVER SOCIALLY IMPORTANT LOCATIONS
Directory of Open Access Journals (Sweden)
A. S. Dokuz
2017-11-01
Full Text Available Socially important locations are places which are frequently visited by social media users in their social media lifetime. Discovering socially important locations provide several valuable information about user behaviours on social media networking sites. However, discovering socially important locations are challenging due to data volume and dimensions, spatial and temporal calculations, location sparseness in social media datasets, and inefficiency of current algorithms. In the literature, several studies are conducted to discover important locations, however, the proposed approaches do not work in computationally efficient manner. In this study, we propose Fast SS-ILM algorithm by modifying the algorithm of SS-ILM to mine socially important locations efficiently. Experimental results show that proposed Fast SS-ILM algorithm decreases execution time of socially important locations discovery process up to 20 %.
Bioinspired Computational Approach to Missing Value Estimation
Directory of Open Access Journals (Sweden)
Israel Edem Agbehadji
2018-01-01
Full Text Available Missing data occurs when values of variables in a dataset are not stored. Estimating these missing values is a significant step during the data cleansing phase of a big data management approach. The reason of missing data may be due to nonresponse or omitted entries. If these missing data are not handled properly, this may create inaccurate results during data analysis. Although a traditional method such as maximum likelihood method extrapolates missing values, this paper proposes a bioinspired method based on the behavior of birds, specifically the Kestrel bird. This paper describes the behavior and characteristics of the Kestrel bird, a bioinspired approach, in modeling an algorithm to estimate missing values. The proposed algorithm (KSA was compared with WSAMP, Firefly, and BAT algorithm. The results were evaluated using the mean of absolute error (MAE. A statistical test (Wilcoxon signed-rank test and Friedman test was conducted to test the performance of the algorithms. The results of Wilcoxon test indicate that time does not have a significant effect on the performance, and the quality of estimation between the paired algorithms was significant; the results of Friedman test ranked KSA as the best evolutionary algorithm.
Computational fluid dynamics in ventilation: Practical approach
Fontaine, J. R.
The potential of computation fluid dynamics (CFD) for conceiving ventilation systems is shown through the simulation of five practical cases. The following examples are considered: capture of pollutants on a surface treating tank equipped with a unilateral suction slot in the presence of a disturbing air draft opposed to suction; dispersion of solid aerosols inside fume cupboards; performances comparison of two general ventilation systems in a silkscreen printing workshop; ventilation of a large open painting area; and oil fog removal inside a mechanical engineering workshop. Whereas the two first problems are analyzed through two dimensional numerical simulations, the three other cases require three dimensional modeling. For the surface treating tank case, numerical results are compared to laboratory experiment data. All simulations are carried out using EOL, a CFD software specially devised to deal with air quality problems in industrial ventilated premises. It contains many analysis tools to interpret the results in terms familiar to the industrial hygienist. Much experimental work has been engaged to validate the predictions of EOL for ventilation flows.
Efficient computation in adaptive artificial spiking neural networks
D. Zambrano (Davide); R.B.P. Nusselder (Roeland); H.S. Scholte; S.M. Bohte (Sander)
2017-01-01
textabstractArtificial Neural Networks (ANNs) are bio-inspired models of neural computation that have proven highly effective. Still, ANNs lack a natural notion of time, and neural units in ANNs exchange analog values in a frame-based manner, a computationally and energetically inefficient form of
Energy efficiency and the law: A multidisciplinary approach
Directory of Open Access Journals (Sweden)
Willemien du Plessis
2015-01-01
Full Text Available South Africa is an energy-intensive country. The inefficient use of, mostly, coal-generated energy is the cause of South Africa's per capita contribution to greenhouse gas emissions, pollution and environmental degradation and negative health impacts. The inefficient use of the country's energy also amounts to the injudicious use of natural resources. Improvements in energy efficiency are an important strategy to stabilise the country's energy crisis. Government responded to this challenge by introducing measures such as policies and legislation to change energy consumption patterns by, amongst others, incentivising the transition to improved energy efficiencies. A central tenet underpinning this review is that the law and energy nexus requires a multidisciplinary approach as well as a multi-pronged adoption of diverse policy instruments to effectively transform the country's energy use patterns. Numerous, innovative instruments are introduced by relevant legislation to encourage the transformation of energy generation and consumption patterns of South Africans. One such innovative instrument is the ISO 50001 energy management standard. It is a voluntary instrument, to plan for, measure and verify energy-efficiency improvements. These improvements may also trigger tax concessions. In this paper, the nature and extent of the various policy instruments and legislation that relate to energy efficiency are explored, while the interactions between the law and the voluntary ISO 50001 standard and between the law and the other academic disciplines are highlighted. The introduction of energy-efficiency measures into law requires a multidisciplinary approach, as lawyers may be challenged to address the scientific and technical elements that characterise these legal measures and instruments. Inputs by several other disciplines such as engineering, mathematics or statistics, accounting, environmental management and auditing may be needed. Law is often
A New Approach to Practical Active-Secure Two-Party Computation
DEFF Research Database (Denmark)
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 number of novel techniques for relating the outputs and inputs of OTs in a larger construction....
Convergence Analysis of a Class of Computational Intelligence Approaches
Directory of Open Access Journals (Sweden)
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.
Constellation modulation - an approach to increase spectral efficiency.
Dash, Soumya Sunder; Pythoud, Frederic; Hillerkuss, David; Baeuerle, Benedikt; Josten, Arne; Leuchtmann, Pascal; Leuthold, Juerg
2017-07-10
Constellation modulation (CM) is introduced as a new degree of freedom to increase the spectral efficiency and to further approach the Shannon limit. Constellation modulation is the art of encoding information not only in the symbols within a constellation but also by encoding information by selecting a constellation from a set of constellations that are switched from time to time. The set of constellations is not limited to sets of partitions from a given constellation but can e.g., be obtained from an existing constellation by applying geometrical transformations such as rotations, translations, scaling, or even more abstract transformations. The architecture of the transmitter and the receiver allows for constellation modulation to be used on top of existing modulations with little penalties on the bit-error ratio (BER) or on the required signal-to-noise ratio (SNR). The spectral bandwidth used by this modulation scheme is identical to the original modulation. Simulations demonstrate a particular advantage of the scheme for low SNR situations. So, for instance, it is demonstrated by simulation that a spectral efficiency increases by up to 33% and 20% can be obtained at a BER of 10 -3 and 2×10 -2 for a regular BPSK modulation format, respectively. Applying constellation modulation, we derive a most power efficient 4D-CM-BPSK modulation format that provides a spectral efficiency of 0.7 bit/s/Hz for an SNR of 0.2 dB at a BER of 2 × 10 -2 .
Efficient and robust cell detection: A structured regression approach.
Xie, Yuanpu; Xing, Fuyong; Shi, Xiaoshuang; Kong, Xiangfei; Su, Hai; Yang, Lin
2018-02-01
Efficient and robust cell detection serves as a critical prerequisite for many subsequent biomedical image analysis methods and computer-aided diagnosis (CAD). It remains a challenging task due to touching cells, inhomogeneous background noise, and large variations in cell sizes and shapes. In addition, the ever-increasing amount of available datasets and the high resolution of whole-slice scanned images pose a further demand for efficient processing algorithms. In this paper, we present a novel structured regression model based on a proposed fully residual convolutional neural network for efficient cell detection. For each testing image, our model learns to produce a dense proximity map that exhibits higher responses at locations near cell centers. Our method only requires a few training images with weak annotations (just one dot indicating the cell centroids). We have extensively evaluated our method using four different datasets, covering different microscopy staining methods (e.g., H & E or Ki-67 staining) or image acquisition techniques (e.g., bright-filed image or phase contrast). Experimental results demonstrate the superiority of our method over existing state of the art methods in terms of both detection accuracy and running time. Copyright © 2017. Published by Elsevier B.V.
Directory of Open Access Journals (Sweden)
JONG WOON KIM
2014-04-01
In this paper, we introduce a modified scattering kernel approach to avoid the unnecessarily repeated calculations involved with the scattering source calculation, and used it with parallel computing to effectively reduce the computation time. Its computational efficiency was tested for three-dimensional full-coupled photon-electron transport problems using our computer program which solves the multi-group discrete ordinates transport equation by using the discontinuous finite element method with unstructured tetrahedral meshes for complicated geometrical problems. The numerical tests show that we can improve speed up to 17∼42 times for the elapsed time per iteration using the modified scattering kernel, not only in the single CPU calculation but also in the parallel computing with several CPUs.
Evaluating Efficiencies of Dual AAV Approaches for Retinal Targeting
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Livia S. Carvalho
2017-09-01
Full Text Available Retinal gene therapy has come a long way in the last few decades and the development and improvement of new gene delivery technologies has been exponential. The recent promising results from the first clinical trials for inherited retinal degeneration due to mutations in RPE65 have provided a major breakthrough in the field and have helped cement the use of recombinant adeno-associated viruses (AAV as the major tool for retinal gene supplementation. One of the key problems of AAV however, is its limited capacity for packaging genomic information to a maximum of around 4.8 kb. Previous studies have demonstrated that homologous recombination and/or inverted terminal repeat (ITR mediated concatemerization of two overlapping AAV vectors can partially overcome the size limitation and help deliver larger transgenes. The aim of this study was to investigate and compare the use of different AAV dual-vector approaches in the mouse retina using a systematic approach comparing efficiencies in vitro and in vivo using a unique oversized reporter construct. We show that the hybrid approach relying on vector genome concatemerization by highly recombinogenic sequences and ITRs sequence overlap offers the best levels of reconstitution both in vitro and in vivo compared to trans-splicing and overlap strategies. Our data also demonstrate that dose and vector serotype do not affect reconstitution efficiency but a discrepancy between mRNA and protein expression data suggests a bottleneck affecting translation.
Efficient one-way quantum computations for quantum error correction
International Nuclear Information System (INIS)
Huang Wei; Wei Zhaohui
2009-01-01
We show how to explicitly construct an O(nd) size and constant quantum depth circuit which encodes any given n-qubit stabilizer code with d generators. Our construction is derived using the graphic description for stabilizer codes and the one-way quantum computation model. Our result demonstrates how to use cluster states as scalable resources for many multi-qubit entangled states and how to use the one-way quantum computation model to improve the design of quantum algorithms.
Accurate and efficient computation of synchrotron radiation functions
International Nuclear Information System (INIS)
MacLeod, Allan J.
2000-01-01
We consider the computation of three functions which appear in the theory of synchrotron radiation. These are F(x)=x∫x∞K 5/3 (y) dy))F p (x)=xK 2/3 (x) and G p (x)=x 1/3 K 1/3 (x), where K ν denotes a modified Bessel function. Chebyshev series coefficients are given which enable the functions to be computed with an accuracy of up to 15 sig. figures
An efficient algorithm for nucleolus and prekernel computation in some classes of TU-games
Faigle, U.; Kern, Walter; Kuipers, J.
1998-01-01
We consider classes of TU-games. We show that we can efficiently compute an allocation in the intersection of the prekernel and the least core of the game if we can efficiently compute the minimum excess for any given allocation. In the case where the prekernel of the game contains exactly one core
The energy efficiency paradox revisited through a partial observability approach
International Nuclear Information System (INIS)
Kounetas, Kostas; Tsekouras, Kostas
2008-01-01
The present paper examines the energy efficiency paradox demonstrated in Greek manufacturing firms through a partial observability approach. The data set used has resulted from a survey carried out among 161 energy-saving technology firm adopters. Maximum likelihood estimates that arise from an incidental truncation model reveal that the adoption of the energy-saving technologies is indeed strongly correlated to the returns of assets that are required in order to undertake the corresponding investments. The source of the energy efficiency paradox lies within a wide range of factors. Policy schemes that aim to increase the adoption rate of energy-saving technologies within the field of manufacturing are significantly affected by differences in the size of firms. Finally, mixed policies seem to be more effective than policies that are only capital subsidy or regulation oriented
An Integrated Computer-Aided Approach for Environmental Studies
DEFF Research Database (Denmark)
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 sco...... 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....
A new computationally-efficient computer program for simulating spectral gamma-ray logs
International Nuclear Information System (INIS)
Conaway, J.G.
1995-01-01
Several techniques to improve the accuracy of radionuclide concentration estimates as a function of depth from gamma-ray logs have appeared in the literature. Much of that work was driven by interest in uranium as an economic mineral. More recently, the problem of mapping and monitoring artificial gamma-emitting contaminants in the ground has rekindled interest in improving the accuracy of radioelement concentration estimates from gamma-ray logs. We are looking at new approaches to accomplishing such improvements. The first step in this effort has been to develop a new computational model of a spectral gamma-ray logging sonde in a borehole environment. The model supports attenuation in any combination of materials arranged in 2-D cylindrical geometry, including any combination of attenuating materials in the borehole, formation, and logging sonde. The model can also handle any distribution of sources in the formation. The model considers unscattered radiation only, as represented by the background-corrected area under a given spectral photopeak as a function of depth. Benchmark calculations using the standard Monte Carlo model MCNP show excellent agreement with total gamma flux estimates with a computation time of about 0.01% of the time required for the MCNP calculations. This model lacks the flexibility of MCNP, although for this application a great deal can be accomplished without that flexibility
Energy-Efficient FPGA-Based Parallel Quasi-Stochastic Computing
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Ramu Seva
2017-11-01
Full Text Available The high performance of FPGA (Field Programmable Gate Array in image processing applications is justified by its flexible reconfigurability, its inherent parallel nature and the availability of a large amount of internal memories. Lately, the Stochastic Computing (SC paradigm has been found to be significantly advantageous in certain application domains including image processing because of its lower hardware complexity and power consumption. However, its viability is deemed to be limited due to its serial bitstream processing and excessive run-time requirement for convergence. To address these issues, a novel approach is proposed in this work where an energy-efficient implementation of SC is accomplished by introducing fast-converging Quasi-Stochastic Number Generators (QSNGs and parallel stochastic bitstream processing, which are well suited to leverage FPGA’s reconfigurability and abundant internal memory resources. The proposed approach has been tested on the Virtex-4 FPGA, and results have been compared with the serial and parallel implementations of conventional stochastic computation using the well-known SC edge detection and multiplication circuits. Results prove that by using this approach, execution time, as well as the power consumption are decreased by a factor of 3.5 and 4.5 for the edge detection circuit and multiplication circuit, respectively.
[A motivational approach of cognitive efficiency in nursing home residents].
Clément, Evelyne; Vivicorsi, Bruno; Altintas, Emin; Guerrien, Alain
2014-06-01
Despite a widespread concern with self-determined motivation (behavior is engaged in "out of pleasure" or "out of choice and valued as being important") and psychological adjustment in later life (well-being, satisfaction in life, meaning of life, or self-esteem), very little is known about the existence and nature of the links between self-determined motivation and cognitive efficiency. The aim of the present study was to investigate theses links in nursing home residents in the framework of the Self-determination theory (SDT) (Deci & Ryan, 2002), in which motivational profile of a person is determined by the combination of different kinds of motivation. We hypothesized that self-determined motivation would lead to higher cognitive efficiency. Participants. 39 (32 women and 7 men) elderly nursing home residents (m= 83.6 ± 9.3 year old) without any neurological or psychiatric disorders (DSM IV) or depression or anxiety (Hamilton depression rating scales) were included in the study. Methods. Cognitive efficiency was evaluated by two brief neuropsychological tests, the Mini mental state examination (MMSE) and the Frontal assessment battery (FAB). The motivational profile was assessed by the Elderly motivation scale (Vallerand & 0'Connor, 1991) which includes four subscales assessing self- and non-self determined motivation to engage oneself in different domains of daily life activity. Results. The neuropsychological scores were positively and significantly correlated to self-determined extrinsic motivation (behavior is engaged in "out of choice" and valued as being important), and the global self-determination index (self-determined motivational profile) was the best predictor of the cognitive efficiency. Conclusion. The results support the SDT interest for a qualitative assessment of the motivation of the elderly people and suggest that a motivational approach of cognitive efficiency could help to interpret cognitive performances exhibited during neuropsychological
Computer Adaptive Testing, Big Data and Algorithmic Approaches to Education
Thompson, Greg
2017-01-01
This article critically considers the promise of computer adaptive testing (CAT) and digital data to provide better and quicker data that will improve the quality, efficiency and effectiveness of schooling. In particular, it uses the case of the Australian NAPLAN test that will become an online, adaptive test from 2016. The article argues that…
Limits on efficient computation in the physical world
Aaronson, Scott Joel
More than a speculative technology, quantum computing seems to challenge our most basic intuitions about how the physical world should behave. In this thesis I show that, while some intuitions from classical computer science must be jettisoned in the light of modern physics, many others emerge nearly unscathed; and I use powerful tools from computational complexity theory to help determine which are which. In the first part of the thesis, I attack the common belief that quantum computing resembles classical exponential parallelism, by showing that quantum computers would face serious limitations on a wider range of problems than was previously known. In particular, any quantum algorithm that solves the collision problem---that of deciding whether a sequence of n integers is one-to-one or two-to-one---must query the sequence O (n1/5) times. This resolves a question that was open for years; previously no lower bound better than constant was known. A corollary is that there is no "black-box" quantum algorithm to break cryptographic hash functions or solve the Graph Isomorphism problem in polynomial time. I also show that relative to an oracle, quantum computers could not solve NP-complete problems in polynomial time, even with the help of nonuniform "quantum advice states"; and that any quantum algorithm needs O (2n/4/n) queries to find a local minimum of a black-box function on the n-dimensional hypercube. Surprisingly, the latter result also leads to new classical lower bounds for the local search problem. Finally, I give new lower bounds on quantum one-way communication complexity, and on the quantum query complexity of total Boolean functions and recursive Fourier sampling. The second part of the thesis studies the relationship of the quantum computing model to physical reality. I first examine the arguments of Leonid Levin, Stephen Wolfram, and others who believe quantum computing to be fundamentally impossible. I find their arguments unconvincing without a "Sure
Tanaka, T.; Tachikawa, Y.; Ichikawa, Y.; Yorozu, K.
2017-12-01
Flood is one of the most hazardous disasters and causes serious damage to people and property around the world. To prevent/mitigate flood damage through early warning system and/or river management planning, numerical modelling of flood-inundation processes is essential. In a literature, flood-inundation models have been extensively developed and improved to achieve flood flow simulation with complex topography at high resolution. With increasing demands on flood-inundation modelling, its computational burden is now one of the key issues. Improvements of computational efficiency of full shallow water equations are made from various perspectives such as approximations of the momentum equations, parallelization technique, and coarsening approaches. To support these techniques and more improve the computational efficiency of flood-inundation simulations, this study proposes an Automatic Domain Updating (ADU) method of 2-D flood-inundation simulation. The ADU method traces the wet and dry interface and automatically updates the simulation domain in response to the progress and recession of flood propagation. The updating algorithm is as follow: first, to register the simulation cells potentially flooded at initial stage (such as floodplains nearby river channels), and then if a registered cell is flooded, to register its surrounding cells. The time for this additional process is saved by checking only cells at wet and dry interface. The computation time is reduced by skipping the processing time of non-flooded area. This algorithm is easily applied to any types of 2-D flood inundation models. The proposed ADU method is implemented to 2-D local inertial equations for the Yodo River basin, Japan. Case studies for two flood events show that the simulation is finished within two to 10 times smaller time showing the same result as that without the ADU method.
Directory of Open Access Journals (Sweden)
Sarim Ahmed
2018-06-01
Full Text Available A venturi scrubber is an important element of Filtered Containment Venting System (FCVS for the removal of aerosols in contaminated air. The present work involves computational fluid dynamics (CFD study of dust particle removal efficiency of a venturi scrubber operating in self-priming mode using ANSYS CFX. Titanium oxide (TiO2 particles having sizes of 1 micron have been taken as dust particles. CFD methodology to simulate the venturi scrubber has been first developed. The cascade atomization and breakup (CAB model has been used to predict deformation of water droplets, whereas the Eulerian–Lagrangian approach has been used to handle multiphase flow involving air, dust, and water. The developed methodology has been applied to simulate venturi scrubber geometry taken from the literature. Dust particle removal efficiency has been calculated for forced feed operation of venturi scrubber and found to be in good agreement with the results available in the literature. In the second part, venturi scrubber along with a tank has been modeled in CFX, and transient simulations have been performed to study self-priming phenomenon. Self-priming has been observed by plotting the velocity vector fields of water. Suction of water in the venturi scrubber occurred due to the difference between static pressure in the venturi scrubber and the hydrostatic pressure of water inside the tank. Dust particle removal efficiency has been calculated for inlet air velocities of 1 m/s and 3 m/s. It has been observed that removal efficiency is higher in case of higher inlet air velocity. Keywords: Computational Fluid Dynamics, Dust Particles, Filtered Containment Venting System, Self-priming Venturi Scrubber, Venturi Scrubber
Energy Efficiency - Spectral Efficiency Trade-off: A Multiobjective Optimization Approach
Amin, Osama
2015-04-23
In this paper, we consider the resource allocation problem for energy efficiency (EE) - spectral efficiency (SE) trade-off. Unlike traditional research that uses the EE as an objective function and imposes constraints either on the SE or achievable rate, we propound a multiobjective optimization approach that can flexibly switch between the EE and SE functions or change the priority level of each function using a trade-off parameter. Our dynamic approach is more tractable than the conventional approaches and more convenient to realistic communication applications and scenarios. We prove that the multiobjective optimization of the EE and SE is equivalent to a simple problem that maximizes the achievable rate/SE and minimizes the total power consumption. Then we apply the generalized framework of the resource allocation for the EE-SE trade-off to optimally allocate the subcarriers’ power for orthogonal frequency division multiplexing (OFDM) with imperfect channel estimation. Finally, we use numerical results to discuss the choice of the trade-off parameter and study the effect of the estimation error, transmission power budget and channel-to-noise ratio on the multiobjective optimization.
Energy Technology Data Exchange (ETDEWEB)
Menkveld, M.; Jablonska, B. [ECN Beleidsstudies, Petten (Netherlands)
2013-05-15
Article 5 of the Energy Efficiency Directive (EED) is an annual obligation to renovate 3% of the building stock of central government. After renovation the buildings will meet the minimum energy performance requirements laid down in Article 4 of the EPBD. The Directive gives room to an alternative approach to achieve the same savings. The Ministry of Interior Affairs has asked ECN to assist with this alternative approach. ECN calculated what saving are achieved with the 3% renovation obligation under the directive. Then ECN looked for the possibilities for an alternative approach to achieve the same savings [Dutch] In artikel 5 van de Energie Efficiency Directive (EED) staat een verplichting om jaarlijks 3% van de gebouwvoorraad van de centrale overheid te renoveren. Die 3% van de gebouwvoorraad moet na renovatie voldoen aan de minimum eisen inzake energieprestatie die door het betreffende lidstaat zijn vastgelegd op grond van artikel 4 in de EPBD. De verplichting betreft gebouwen die in bezit en in gebruik zijn van de rijksoverheid met een gebruiksoppervlakte groter dan 500 m{sup 2}, vanaf juli 2015 groter dan 250 m{sup 2}. De gebouwen die eigendom zijn van de Rijksgebouwendienst betreft kantoren van rijksdiensten, gerechtsgebouwen, gebouwen van douane en politie en gevangenissen. Van de gebouwen van Defensie hoeven alleen kantoren en legeringsgebouwen aan de verplichting te voldoen.
Energy Efficiency - Spectral Efficiency Trade-off: A Multiobjective Optimization Approach
Amin, Osama; Bedeer, Ebrahim; Ahmed, Mohamed; Dobre, Octavia
2015-01-01
In this paper, we consider the resource allocation problem for energy efficiency (EE) - spectral efficiency (SE) trade-off. Unlike traditional research that uses the EE as an objective function and imposes constraints either on the SE or achievable rate, we propound a multiobjective optimization approach that can flexibly switch between the EE and SE functions or change the priority level of each function using a trade-off parameter. Our dynamic approach is more tractable than the conventional approaches and more convenient to realistic communication applications and scenarios. We prove that the multiobjective optimization of the EE and SE is equivalent to a simple problem that maximizes the achievable rate/SE and minimizes the total power consumption. Then we apply the generalized framework of the resource allocation for the EE-SE trade-off to optimally allocate the subcarriers’ power for orthogonal frequency division multiplexing (OFDM) with imperfect channel estimation. Finally, we use numerical results to discuss the choice of the trade-off parameter and study the effect of the estimation error, transmission power budget and channel-to-noise ratio on the multiobjective optimization.
Energy Efficiency in Logistics: An Interactive Approach to Capacity Utilisation
Directory of Open Access Journals (Sweden)
Jessica Wehner
2018-05-01
Full Text Available Logistics operations are energy-consuming and impact the environment negatively. Improving energy efficiency in logistics is crucial for environmental sustainability and can be achieved by increasing the utilisation of capacity. This paper takes an interactive approach to capacity utilisation, to contribute to sustainable freight transport and logistics, by identifying its causes and mitigations. From literature, a conceptual framework was developed to highlight different system levels in the logistics system, in which the energy efficiency improvement potential can be found and that are summarised in the categories activities, actors, and areas. Through semi-structured interviews with representatives of nine companies, empirical data was collected to validate the framework of the causes of the unutilised capacity and proposed mitigations. The results suggest that activities, such as inflexibilities and limited information sharing as well as actors’ over-delivery of logistics services, incorrect price setting, and sales campaigns can cause unutilised capacity, and that problem areas include i.a. poor integration of reversed logistics and the last mile. The paper contributes by categorising causes of unutilised capacity and linking them to mitigations in a framework, providing a critical view towards fill rates, highlighting the need for a standardised approach to measure environmental impact that enables comparison between companies and underlining that costs are not an appropriate indicator for measuring environmental impact.
Demonstration of an efficient cooling approach for SBIRS-Low
Nieczkoski, S. J.; Myers, E. A.
2002-05-01
The Space Based Infrared System-Low (SBIRS-Low) segment is a near-term Air Force program for developing and deploying a constellation of low-earth orbiting observation satellites with gimbaled optics cooled to cryogenic temperatures. The optical system design and requirements present unique challenges that make conventional cooling approaches both complicated and risky. The Cryocooler Interface System (CIS) provides a remote, efficient, and interference-free means of cooling the SBIRS-Low optics. Technology Applications Inc. (TAI), through a two-phase Small Business Innovative Research (SBIR) program with Air Force Research Laboratory (AFRL), has taken the CIS from initial concept feasibility through the design, build, and test of a prototype system. This paper presents the development and demonstration testing of the prototype CIS. Prototype system testing has demonstrated the high efficiency of this cooling approach, making it an attractive option for SBIRS-Low and other sensitive optical and detector systems that require low-impact cryogenic cooling.
An Efficient Context-Aware Privacy Preserving Approach for Smartphones
Directory of Open Access Journals (Sweden)
Lichen Zhang
2017-01-01
Full Text Available With the proliferation of smartphones and the usage of the smartphone apps, privacy preservation has become an important issue. The existing privacy preservation approaches for smartphones usually have less efficiency due to the absent consideration of the active defense policies and temporal correlations between contexts related to users. In this paper, through modeling the temporal correlations among contexts, we formalize the privacy preservation problem to an optimization problem and prove its correctness and the optimality through theoretical analysis. To further speed up the running time, we transform the original optimization problem to an approximate optimal problem, a linear programming problem. By resolving the linear programming problem, an efficient context-aware privacy preserving algorithm (CAPP is designed, which adopts active defense policy and decides how to release the current context of a user to maximize the level of quality of service (QoS of context-aware apps with privacy preservation. The conducted extensive simulations on real dataset demonstrate the improved performance of CAPP over other traditional approaches.
Computational methods for more fuel-efficient ship
Koren, B.
2008-01-01
The flow of water around a ship powered by a combustion engine is a key factor in the ship's fuel consumption. The simulation of flow patterns around ship hulls is therefore an important aspect of ship design. While lengthy computations are required for such simulations, research by Jeroen Wackers
Efficient computation in networks of spiking neurons: simulations and theory
International Nuclear Information System (INIS)
Natschlaeger, T.
1999-01-01
One of the most prominent features of biological neural systems is that individual neurons communicate via short electrical pulses, the so called action potentials or spikes. In this thesis we investigate possible mechanisms which can in principle explain how complex computations in spiking neural networks (SNN) can be performed very fast, i.e. within a few 10 milliseconds. Some of these models are based on the assumption that relevant information is encoded by the timing of individual spikes (temporal coding). We will also discuss a model which is based on a population code and still is able to perform fast complex computations. In their natural environment biological neural systems have to process signals with a rich temporal structure. Hence it is an interesting question how neural systems process time series. In this context we explore possible links between biophysical characteristics of single neurons (refractory behavior, connectivity, time course of postsynaptic potentials) and synapses (unreliability, dynamics) on the one hand and possible computations on times series on the other hand. Furthermore we describe a general model of computation that exploits dynamic synapses. This model provides a general framework for understanding how neural systems process time-varying signals. (author)
Efficient Numerical Methods for Stochastic Differential Equations in Computational Finance
Happola, Juho
2017-09-19
Stochastic Differential Equations (SDE) offer a rich framework to model the probabilistic evolution of the state of a system. Numerical approximation methods are typically needed in evaluating relevant Quantities of Interest arising from such models. In this dissertation, we present novel effective methods for evaluating Quantities of Interest relevant to computational finance when the state of the system is described by an SDE.
An Efficient Virtual Machine Consolidation Scheme for Multimedia Cloud Computing.
Han, Guangjie; Que, Wenhui; Jia, Gangyong; Shu, Lei
2016-02-18
Cloud computing has innovated the IT industry in recent years, as it can delivery subscription-based services to users in the pay-as-you-go model. Meanwhile, multimedia cloud computing is emerging based on cloud computing to provide a variety of media services on the Internet. However, with the growing popularity of multimedia cloud computing, its large energy consumption cannot only contribute to greenhouse gas emissions, but also result in the rising of cloud users' costs. Therefore, the multimedia cloud providers should try to minimize its energy consumption as much as possible while satisfying the consumers' resource requirements and guaranteeing quality of service (QoS). In this paper, we have proposed a remaining utilization-aware (RUA) algorithm for virtual machine (VM) placement, and a power-aware algorithm (PA) is proposed to find proper hosts to shut down for energy saving. These two algorithms have been combined and applied to cloud data centers for completing the process of VM consolidation. Simulation results have shown that there exists a trade-off between the cloud data center's energy consumption and service-level agreement (SLA) violations. Besides, the RUA algorithm is able to deal with variable workload to prevent hosts from overloading after VM placement and to reduce the SLA violations dramatically.
Unwrapping ADMM: Efficient Distributed Computing via Transpose Reduction
2016-05-11
applications of the Split Bregman method: Segmen- tation and surface reconstruction. J. Sci. Comput., 45:272– 293, October 2010. [17] Stephen Boyd and...Garcia, Gretchen Greene, Fabrizia Guglielmetti, Christopher Hanley, George Hawkins , et al. The second-generation guide star cata- log: description
Efficient Computation of Exposure Profiles for Counterparty Credit Risk
de Graaf, C.S.L.; Feng, Q.; Kandhai, D.; Oosterlee, C.W.
2014-01-01
Three computational techniques for approximation of counterparty exposure for financial derivatives are presented. The exposure can be used to quantify so-called Credit Valuation Adjustment (CVA) and Potential Future Exposure (PFE), which are of utmost importance for modern risk management in the
Efficient computation of exposure profiles for counterparty credit risk
C.S.L. de Graaf (Kees); Q. Feng (Qian); B.D. Kandhai; C.W. Oosterlee (Cornelis)
2014-01-01
htmlabstractThree computational techniques for approximation of counterparty exposure for financial derivatives are presented. The exposure can be used to quantify so-called Credit Valuation Adjustment (CVA) and Potential Future Exposure (PFE), which are of utmost importance for modern risk
Efficient Numerical Methods for Stochastic Differential Equations in Computational Finance
Happola, Juho
2017-01-01
Stochastic Differential Equations (SDE) offer a rich framework to model the probabilistic evolution of the state of a system. Numerical approximation methods are typically needed in evaluating relevant Quantities of Interest arising from such models. In this dissertation, we present novel effective methods for evaluating Quantities of Interest relevant to computational finance when the state of the system is described by an SDE.
Using Weighted Graphs for Computationally Efficient WLAN Location Determination
DEFF Research Database (Denmark)
Thomsen, Bent; Hansen, Rene
2007-01-01
use of existing WLAN infrastructures. The technique consists of building a radio map of signal strength measurements which is searched to determine a position estimate. While the fingerprinting technique has produced good positioning accuracy results, the technique incurs a substantial computational...
Digging deeper on "deep" learning: A computational ecology approach.
Buscema, Massimo; Sacco, Pier Luigi
2017-01-01
We propose an alternative approach to "deep" learning that is based on computational ecologies of structurally diverse artificial neural networks, and on dynamic associative memory responses to stimuli. Rather than focusing on massive computation of many different examples of a single situation, we opt for model-based learning and adaptive flexibility. Cross-fertilization of learning processes across multiple domains is the fundamental feature of human intelligence that must inform "new" artificial intelligence.
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...
A Memory and Computation Efficient Sparse Level-Set Method
Laan, Wladimir J. van der; Jalba, Andrei C.; Roerdink, Jos B.T.M.
Since its introduction, the level set method has become the favorite technique for capturing and tracking moving interfaces, and found applications in a wide variety of scientific fields. In this paper we present efficient data structures and algorithms for tracking dynamic interfaces through the
Directory of Open Access Journals (Sweden)
Md. Rezaul Karim
2012-03-01
Full Text Available Mining interesting patterns from DNA sequences is one of the most challenging tasks in bioinformatics and computational biology. Maximal contiguous frequent patterns are preferable for expressing the function and structure of DNA sequences and hence can capture the common data characteristics among related sequences. Biologists are interested in finding frequent orderly arrangements of motifs that are responsible for similar expression of a group of genes. In order to reduce mining time and complexity, however, most existing sequence mining algorithms either focus on finding short DNA sequences or require explicit specification of sequence lengths in advance. The challenge is to find longer sequences without specifying sequence lengths in advance. In this paper, we propose an efficient approach to mining maximal contiguous frequent patterns from large DNA sequence datasets. The experimental results show that our proposed approach is memory-efficient and mines maximal contiguous frequent patterns within a reasonable time.
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.
PVT: an efficient computational procedure to speed up next-generation sequence analysis.
Maji, Ranjan Kumar; Sarkar, Arijita; Khatua, Sunirmal; Dasgupta, Subhasis; Ghosh, Zhumur
2014-06-04
High-throughput Next-Generation Sequencing (NGS) techniques are advancing genomics and molecular biology research. This technology generates substantially large data which puts up a major challenge to the scientists for an efficient, cost and time effective solution to analyse such data. Further, for the different types of NGS data, there are certain common challenging steps involved in analysing those data. Spliced alignment is one such fundamental step in NGS data analysis which is extremely computational intensive as well as time consuming. There exists serious problem even with the most widely used spliced alignment tools. TopHat is one such widely used spliced alignment tools which although supports multithreading, does not efficiently utilize computational resources in terms of CPU utilization and memory. Here we have introduced PVT (Pipelined Version of TopHat) where we take up a modular approach by breaking TopHat's serial execution into a pipeline of multiple stages, thereby increasing the degree of parallelization and computational resource utilization. Thus we address the discrepancies in TopHat so as to analyze large NGS data efficiently. We analysed the SRA dataset (SRX026839 and SRX026838) consisting of single end reads and SRA data SRR1027730 consisting of paired-end reads. We used TopHat v2.0.8 to analyse these datasets and noted the CPU usage, memory footprint and execution time during spliced alignment. With this basic information, we designed PVT, a pipelined version of TopHat that removes the redundant computational steps during 'spliced alignment' and breaks the job into a pipeline of multiple stages (each comprising of different step(s)) to improve its resource utilization, thus reducing the execution time. PVT provides an improvement over TopHat for spliced alignment of NGS data analysis. PVT thus resulted in the reduction of the execution time to ~23% for the single end read dataset. Further, PVT designed for paired end reads showed an
Directory of Open Access Journals (Sweden)
Supat Faarungsang
2017-04-01
Full Text Available The Reverse Threshold Model Theory (RTMT model was introduced based on limiting factor concepts, but its efficiency compared to the Conventional Model (CM has not been published. This investigation assessed the efficiency of RTMT compared to CM using computer simulation on the “One Laptop Per Child” computer and a desktop computer. Based on probability values, it was found that RTMT was more efficient than CM among eight treatment combinations and an earlier study verified that RTMT gives complete elimination of random error. Furthermore, RTMT has several advantages over CM and is therefore proposed to be applied to most research data.
Wireless-Uplinks-Based Energy-Efficient Scheduling in Mobile Cloud Computing
Xing Liu; Chaowei Yuan; Zhen Yang; Enda Peng
2015-01-01
Mobile cloud computing (MCC) combines cloud computing and mobile internet to improve the computational capabilities of resource-constrained mobile devices (MDs). In MCC, mobile users could not only improve the computational capability of MDs but also save operation consumption by offloading the mobile applications to the cloud. However, MCC faces the problem of energy efficiency because of time-varying channels when the offloading is being executed. In this paper, we address the issue of ener...
Efficient Strategy Computation in Zero-Sum Asymmetric Repeated Games
Li, Lichun
2017-03-06
Zero-sum asymmetric games model decision making scenarios involving two competing players who have different information about the game being played. A particular case is that of nested information, where one (informed) player has superior information over the other (uninformed) player. This paper considers the case of nested information in repeated zero-sum games and studies the computation of strategies for both the informed and uninformed players for finite-horizon and discounted infinite-horizon nested information games. For finite-horizon settings, we exploit that for both players, the security strategy, and also the opponent\\'s corresponding best response depend only on the informed player\\'s history of actions. Using this property, we refine the sequence form, and formulate an LP computation of player strategies that is linear in the size of the uninformed player\\'s action set. For the infinite-horizon discounted game, we construct LP formulations to compute the approximated security strategies for both players, and provide a bound on the performance difference between the approximated security strategies and the security strategies. Finally, we illustrate the results on a network interdiction game between an informed system administrator and uniformed intruder.
Wan, Shixiang; Zou, Quan
2017-01-01
Multiple sequence alignment (MSA) plays a key role in biological sequence analyses, especially in phylogenetic tree construction. Extreme increase in next-generation sequencing results in shortage of efficient ultra-large biological sequence alignment approaches for coping with different sequence types. Distributed and parallel computing represents a crucial technique for accelerating ultra-large (e.g. files more than 1 GB) sequence analyses. Based on HAlign and Spark distributed computing system, we implement a highly cost-efficient and time-efficient HAlign-II tool to address ultra-large multiple biological sequence alignment and phylogenetic tree construction. The experiments in the DNA and protein large scale data sets, which are more than 1GB files, showed that HAlign II could save time and space. It outperformed the current software tools. HAlign-II can efficiently carry out MSA and construct phylogenetic trees with ultra-large numbers of biological sequences. HAlign-II shows extremely high memory efficiency and scales well with increases in computing resource. THAlign-II provides a user-friendly web server based on our distributed computing infrastructure. HAlign-II with open-source codes and datasets was established at http://lab.malab.cn/soft/halign.
2013-05-01
Based on a recent study on cost efficient alternative bridge approach slab (BAS) designs (Thiagarajan et : al. 2010) has recommended three new BAS designs for possible implementation by MoDOT namely a) 20 feet cast-inplace : slab with sleeper slab (C...
Energy-efficient cloud computing : autonomic resource provisioning for datacenters
Tesfatsion, Selome Kostentinos
2018-01-01
Energy efficiency has become an increasingly important concern in data centers because of issues associated with energy consumption, such as capital costs, operating expenses, and environmental impact. While energy loss due to suboptimal use of facilities and non-IT equipment has largely been reduced through the use of best-practice technologies, addressing energy wastage in IT equipment still requires the design and implementation of energy-aware resource management systems. This thesis focu...
Efficient Numeric and Geometric Computations using Heterogeneous Shared Memory Architectures
2017-10-04
to the memory architectures of CPUs and GPUs to obtain good performance and result in good memory performance using cache management. These methods ...Accomplishments: The PI and students has developed new methods for path and ray tracing and their Report Date: 14-Oct-2017 INVESTIGATOR(S): Phone...The efficiency of our method makes it a good candidate for forming hybrid schemes with wave-based models. One possibility is to couple the ray curve
Energy Technology Data Exchange (ETDEWEB)
Ibrahim, Khaled Z. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Computational Research Division; Epifanovsky, Evgeny [Q-Chem, Inc., Pleasanton, CA (United States); Williams, Samuel W. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Computational Research Division; Krylov, Anna I. [Univ. of Southern California, Los Angeles, CA (United States). Dept. of Chemistry
2016-07-26
Coupled-cluster methods provide highly accurate models of molecular structure by explicit numerical calculation of tensors representing the correlation between electrons. These calculations are dominated by a sequence of tensor contractions, motivating the development of numerical libraries for such operations. While based on matrix-matrix multiplication, these libraries are specialized to exploit symmetries in the molecular structure and in electronic interactions, and thus reduce the size of the tensor representation and the complexity of contractions. The resulting algorithms are irregular and their parallelization has been previously achieved via the use of dynamic scheduling or specialized data decompositions. We introduce our efforts to extend the Libtensor framework to work in the distributed memory environment in a scalable and energy efficient manner. We achieve up to 240 speedup compared with the best optimized shared memory implementation. We attain scalability to hundreds of thousands of compute cores on three distributed-memory architectures, (Cray XC30&XC40, BlueGene/Q), and on a heterogeneous GPU-CPU system (Cray XK7). As the bottlenecks shift from being compute-bound DGEMM's to communication-bound collectives as the size of the molecular system scales, we adopt two radically different parallelization approaches for handling load-imbalance. Nevertheless, we preserve a uni ed interface to both programming models to maintain the productivity of computational quantum chemists.
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.
Energy Technology Data Exchange (ETDEWEB)
Hu, Rui, E-mail: rhu@anl.gov; Yu, Yiqi
2016-11-15
Highlights: • Developed a computationally efficient method for full-core conjugate heat transfer modeling of sodium fast reactors. • Applied fully-coupled JFNK solution scheme to avoid the operator-splitting errors. • The accuracy and efficiency of the method is confirmed with a 7-assembly test problem. • The effects of different spatial discretization schemes are investigated and compared to the RANS-based CFD simulations. - Abstract: For efficient and accurate temperature predictions of sodium fast reactor structures, a 3-D full-core conjugate heat transfer modeling capability is developed for an advanced system analysis tool, SAM. The hexagon lattice core is modeled with 1-D parallel channels representing the subassembly flow, and 2-D duct walls and inter-assembly gaps. The six sides of the hexagon duct wall and near-wall coolant region are modeled separately to account for different temperatures and heat transfer between coolant flow and each side of the duct wall. The Jacobian Free Newton Krylov (JFNK) solution method is applied to solve the fluid and solid field simultaneously in a fully coupled fashion. The 3-D full-core conjugate heat transfer modeling capability in SAM has been demonstrated by a verification test problem with 7 fuel assemblies in a hexagon lattice layout. Additionally, the SAM simulation results are compared with RANS-based CFD simulations. Very good agreements have been achieved between the results of the two approaches.
Computer based approach to fatigue analysis and design
International Nuclear Information System (INIS)
Comstock, T.R.; Bernard, T.; Nieb, J.
1979-01-01
An approach is presented which uses a mini-computer based system for data acquisition, analysis and graphic displays relative to fatigue life estimation and design. Procedures are developed for identifying an eliminating damaging events due to overall duty cycle, forced vibration and structural dynamic characteristics. Two case histories, weld failures in heavy vehicles and low cycle fan blade failures, are discussed to illustrate the overall approach. (orig.) 891 RW/orig. 892 RKD [de
An efficient approach to imaging underground hydraulic networks
Kumar, Mohi
2012-07-01
To better locate natural resources, treat pollution, and monitor underground networks associated with geothermal plants, nuclear waste repositories, and carbon dioxide sequestration sites, scientists need to be able to accurately characterize and image fluid seepage pathways below ground. With these images, scientists can gain knowledge of soil moisture content, the porosity of geologic formations, concentrations and locations of dissolved pollutants, and the locations of oil fields or buried liquid contaminants. Creating images of the unknown hydraulic environments underfoot is a difficult task that has typically relied on broad extrapolations from characteristics and tests of rock units penetrated by sparsely positioned boreholes. Such methods, however, cannot identify small-scale features and are very expensive to reproduce over a broad area. Further, the techniques through which information is extrapolated rely on clunky and mathematically complex statistical approaches requiring large amounts of computational power.
Environmental sciences and computations: a modular data based systems approach
International Nuclear Information System (INIS)
Crawford, T.V.; Bailey, C.E.
1975-07-01
A major computer code for environmental calculations is under development at the Savannah River Laboratory. The primary aim is to develop a flexible, efficient capability to calculate, for all significant pathways, the dose to man resulting from releases of radionuclides from the Savannah River Plant and from other existing and potential radioactive sources in the southeastern United States. The environmental sciences programs at SRP are described, with emphasis on the development of the calculational system. It is being developed as a modular data-based system within the framework of the larger JOSHUA Computer System, which provides data management, terminal, and job execution facilities. (U.S.)
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
International Nuclear Information System (INIS)
Ma, Duancheng; Friák, Martin; Pezold, Johann von; Raabe, Dierk; Neugebauer, Jörg
2015-01-01
We propose an approach for the computationally efficient and quantitatively accurate prediction of solid-solution strengthening. It combines the 2-D Peierls–Nabarro model and a recently developed solid-solution strengthening model. Solid-solution strengthening is examined with Al–Mg and Al–Li as representative alloy systems, demonstrating a good agreement between theory and experiments within the temperature range in which the dislocation motion is overdamped. Through a parametric study, two guideline maps of the misfit parameters against (i) the critical resolved shear stress, τ 0 , at 0 K and (ii) the energy barrier, ΔE b , against dislocation motion in a solid solution with randomly distributed solute atoms are created. With these two guideline maps, τ 0 at finite temperatures is predicted for other Al binary systems, and compared with available experiments, achieving good agreement
Work-Efficient Parallel Skyline Computation for the GPU
DEFF Research Database (Denmark)
Bøgh, Kenneth Sejdenfaden; Chester, Sean; Assent, Ira
2015-01-01
offers the potential for parallelizing skyline computation across thousands of cores. However, attempts to port skyline algorithms to the GPU have prioritized throughput and failed to outperform sequential algorithms. In this paper, we introduce a new skyline algorithm, designed for the GPU, that uses...... a global, static partitioning scheme. With the partitioning, we can permit controlled branching to exploit transitive relationships and avoid most point-to-point comparisons. The result is a non-traditional GPU algorithm, SkyAlign, that prioritizes work-effciency and respectable throughput, rather than...
Auditing energy use -a systematic approach for enhancing energy efficiency
International Nuclear Information System (INIS)
Ardhapnrkar, P.M.; Mahalle, A.M.
2005-01-01
Energy management is a critical activity in the developing as well as developed countries owing to constraints in the availability of primary energy resources and the increasing demand for energy from the industrial and non-industrial users. Energy consumption is a vital parameter that determines the economic growth of any country. An energy management system (EMS) can save money by allowing greater control over energy consuming equipment. The foundation for the energy program is the energy audit, which is the systematic study of factory or building to determine where and how well energy is being used. It is the nucleus of any successful energy saving program -it is tool, not a solution. Conventional energy conservation methods are mostly sporadic and lack a coordinated plan of action. Consequently only apparent systems are treated without the analysis of system interaction. Energy audit on the other hand, involves total system approach and aims at optimizing energy use efficiently for the entire plant. In the present paper a new approach to pursue energy conservation techniques is being discussed. The focus is mainly on the methodology of energy audit, energy use analysis, relating energy with the production, and reducing energy losses, etc. It is observe that with this systematic approach, if adopted, which consists of three essential segments namely capacity utilization fine-tuning of the equipment and technology up-gradation can result in phenomenal savings in the energy, building competitive edge for the industry. This approach along with commitment can provide the right impetus to reap the benefits of energy conservation on a sustained basis. (author)
From properties to materials: An efficient and simple approach.
Huwig, Kai; Fan, Chencheng; Springborg, Michael
2017-12-21
We present an inverse-design method, the poor man's materials optimization, that is designed to identify materials within a very large class with optimized values for a pre-chosen property. The method combines an efficient genetic-algorithm-based optimization, an automatic approach for generating modified molecules, a simple approach for calculating the property of interest, and a mathematical formulation of the quantity whose value shall be optimized. In order to illustrate the performance of our approach, we study the properties of organic molecules related to those used in dye-sensitized solar cells, whereby we, for the sake of proof of principle, consider benzene as a simple test system. Using a genetic algorithm, the substituents attached to the organic backbone are varied and the best performing molecules are identified. We consider several properties to describe the performance of organic molecules, including the HOMO-LUMO gap, the sunlight absorption, the spatial distance of the orbitals, and the reorganisation energy. The results show that our method is able to identify a large number of good candidate structures within a short time. In some cases, chemical/physical intuition can be used to rationalize the substitution pattern of the best structures, although this is not always possible. The present investigations provide a solid foundation for dealing with more complex and technically relevant systems such as porphyrins. Furthermore, our "properties first, materials second" approach is not limited to solar-energy harvesting but can be applied to many other fields, as briefly is discussed in the paper.
From properties to materials: An efficient and simple approach
Huwig, Kai; Fan, Chencheng; Springborg, Michael
2017-12-01
We present an inverse-design method, the poor man's materials optimization, that is designed to identify materials within a very large class with optimized values for a pre-chosen property. The method combines an efficient genetic-algorithm-based optimization, an automatic approach for generating modified molecules, a simple approach for calculating the property of interest, and a mathematical formulation of the quantity whose value shall be optimized. In order to illustrate the performance of our approach, we study the properties of organic molecules related to those used in dye-sensitized solar cells, whereby we, for the sake of proof of principle, consider benzene as a simple test system. Using a genetic algorithm, the substituents attached to the organic backbone are varied and the best performing molecules are identified. We consider several properties to describe the performance of organic molecules, including the HOMO-LUMO gap, the sunlight absorption, the spatial distance of the orbitals, and the reorganisation energy. The results show that our method is able to identify a large number of good candidate structures within a short time. In some cases, chemical/physical intuition can be used to rationalize the substitution pattern of the best structures, although this is not always possible. The present investigations provide a solid foundation for dealing with more complex and technically relevant systems such as porphyrins. Furthermore, our "properties first, materials second" approach is not limited to solar-energy harvesting but can be applied to many other fields, as briefly is discussed in the paper.
Supplementary Computer Generated Cueing to Enhance Air Traffic Controller Efficiency
2013-03-01
has its own characteristics that determine its capacity of reproducing rich information ( Daft and Lengel, 1984). According to this theory, specific...Economic Quantification. Daft , R., & Lengel, R. 1984. Information richness: A new approach to managerial behavior and organization design. Research in
Computer and Internet Addiction: Analysis and Classification of Approaches
Directory of Open Access Journals (Sweden)
Zaretskaya O.V.
2017-08-01
Full Text Available The theoretical analysis of modern research works on the problem of computer and Internet addiction is carried out. The main features of different approaches are outlined. The attempt is made to systematize researches conducted and to classify scientific approaches to the problem of Internet addiction. The author distinguishes nosological, cognitive-behavioral, socio-psychological and dialectical approaches. She justifies the need to use an approach that corresponds to the essence, goals and tasks of social psychology in the field of research as the problem of Internet addiction, and the dependent behavior in general. In the opinion of the author, this dialectical approach integrates the experience of research within the framework of the socio-psychological approach and focuses on the observed inconsistencies in the phenomenon of Internet addiction – the compensatory nature of Internet activity, when people who are interested in the Internet are in a dysfunctional life situation.
An Efficient Computational Technique for Fractal Vehicular Traffic Flow
Directory of Open Access Journals (Sweden)
Devendra Kumar
2018-04-01
Full Text Available In this work, we examine a fractal vehicular traffic flow problem. The partial differential equations describing a fractal vehicular traffic flow are solved with the aid of the local fractional homotopy perturbation Sumudu transform scheme and the local fractional reduced differential transform method. Some illustrative examples are taken to describe the success of the suggested techniques. The results derived with the aid of the suggested schemes reveal that the present schemes are very efficient for obtaining the non-differentiable solution to fractal vehicular traffic flow problem.
CERN. Geneva
2012-01-01
With Moore's Law alive and well, more and more parallelism is introduced into all computing platforms at all levels of integration and programming to achieve higher performance and energy efficiency. Especially in the area of High-Performance Computing (HPC) users can entertain a combination of different hardware and software parallel architectures and programming environments. Those technologies range from vectorization and SIMD computation over shared memory multi-threading (e.g. OpenMP) to distributed memory message passing (e.g. MPI) on cluster systems. We will discuss HPC industry trends and Intel's approach to it from processor/system architectures and research activities to hardware and software tools technologies. This includes the recently announced new Intel(r) Many Integrated Core (MIC) architecture for highly-parallel workloads and general purpose, energy efficient TFLOPS performance, some of its architectural features and its programming environment. At the end we will have a br...
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
New Approaches to Quantum Computing using Nuclear Magnetic Resonance Spectroscopy
International Nuclear Information System (INIS)
Colvin, M; Krishnan, V V
2003-01-01
The power of a quantum computer (QC) relies on the fundamental concept of the superposition in quantum mechanics and thus allowing an inherent large-scale parallelization of computation. In a QC, binary information embodied in a quantum system, such as spin degrees of freedom of a spin-1/2 particle forms the qubits (quantum mechanical bits), over which appropriate logical gates perform the computation. In classical computers, the basic unit of information is the bit, which can take a value of either 0 or 1. Bits are connected together by logic gates to form logic circuits to implement complex logical operations. The expansion of modern computers has been driven by the developments of faster, smaller and cheaper logic gates. As the size of the logic gates become smaller toward the level of atomic dimensions, the performance of such a system is no longer considered classical but is rather governed by quantum mechanics. Quantum computers offer the potentially superior prospect of solving computational problems that are intractable to classical computers such as efficient database searches and cryptography. A variety of algorithms have been developed recently, most notably Shor's algorithm for factorizing long numbers into prime factors in polynomial time and Grover's quantum search algorithm. The algorithms that were of only theoretical interest as recently, until several methods were proposed to build an experimental QC. These methods include, trapped ions, cavity-QED, coupled quantum dots, Josephson junctions, spin resonance transistors, linear optics and nuclear magnetic resonance. Nuclear magnetic resonance (NMR) is uniquely capable of constructing small QCs and several algorithms have been implemented successfully. NMR-QC differs from other implementations in one important way that it is not a single QC, but a statistical ensemble of them. Thus, quantum computing based on NMR is considered as ensemble quantum computing. In NMR quantum computing, the spins with
International Nuclear Information System (INIS)
Valadkhani, Abbas; Roshdi, Israfil; Smyth, Russell
2016-01-01
We propose a multiplicative environmental data envelopment analysis (ME-DEA) approach to measure the performance of 46 countries that generate most of the world's carbon dioxide (CO_2) emissions. In the model, we combine economic (labour and capital), environmental (freshwater) and energy inputs with a desirable output (GDP) and three undesirable outputs (CO_2, methane and nitrous oxide emissions). We rank each country according to the optimum use of its resources employing a multiplicative extension of environmental DEA models. By computing partial efficiency scores for each input and output separately, we thus identify major sources of inefficiency for all sample countries. Based on the partial efficiency scores obtained from the model, we define aggregate economic, energy and environmental efficiency indexes for 2002, 2007 and 2011, reflecting points in time before and after the official enactment of the Kyoto Protocol. We find that for most countries efficiency scores increase over this period. In addition, there exists a positive relationship between economic and environmental efficiency, although, at the same time, our results suggest that environmental efficiency cannot be realized without first reaching a certain threshold of economic efficiency. We also find support for the Paradox of Plenty, whereby an abundance of natural and energy resources results in their inefficient use. - Highlights: • This study proposes a multiplicative extension of environmental DEA models. • We examine how countries utilize energy, labour, capital and freshwater over time. • We measure how efficiently countries minimize the emissions of greenhouse gases. • Results support the Paradox of Plenty among 46 countries in 2002, 2007 and 2011. • Countries richest in oil and gas exhibited the worst energy efficiency.
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.
Computer Forensics for Graduate Accountants: A Motivational Curriculum Design Approach
Directory of Open Access Journals (Sweden)
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 relaxed-Jacobi smoothers for multigrid on parallel computers
Yang, Xiang; Mittal, Rajat
2017-03-01
In this Technical Note, we present a family of Jacobi-based multigrid smoothers suitable for the solution of discretized elliptic equations. These smoothers are based on the idea of scheduled-relaxation Jacobi proposed recently by Yang & Mittal (2014) [18] and employ two or three successive relaxed Jacobi iterations with relaxation factors derived so as to maximize the smoothing property of these iterations. The performance of these new smoothers measured in terms of convergence acceleration and computational workload, is assessed for multi-domain implementations typical of parallelized solvers, and compared to the lexicographic point Gauss-Seidel smoother. The tests include the geometric multigrid method on structured grids as well as the algebraic grid method on unstructured grids. The tests demonstrate that unlike Gauss-Seidel, the convergence of these Jacobi-based smoothers is unaffected by domain decomposition, and furthermore, they outperform the lexicographic Gauss-Seidel by factors that increase with domain partition count.
Cultural Distance-Aware Service Recommendation Approach in Mobile Edge Computing
Directory of Open Access Journals (Sweden)
Yan Li
2018-01-01
Full Text Available In the era of big data, traditional computing systems and paradigms are not efficient and even difficult to use. For high performance big data processing, mobile edge computing is emerging as a complement framework of cloud computing. In this new computing architecture, services are provided within a close proximity of mobile users by servers at the edge of network. Traditional collaborative filtering recommendation approach only focuses on the similarity extracted from the rating data, which may lead to an inaccuracy expression of user preference. In this paper, we propose a cultural distance-aware service recommendation approach which focuses on not only the similarity but also the local characteristics and preference of users. Our approach employs the cultural distance to express the user preference and combines it with similarity to predict the user ratings and recommend the services with higher rating. In addition, considering the extreme sparsity of the rating data, missing rating prediction based on collaboration filtering is introduced in our approach. The experimental results based on real-world datasets show that our approach outperforms the traditional recommendation approaches in terms of the reliability of recommendation.
An Efficient Approach to Screening Epigenome-Wide Data
Directory of Open Access Journals (Sweden)
Meredith A. Ray
2016-01-01
Full Text Available Screening cytosine-phosphate-guanine dinucleotide (CpG DNA methylation sites in association with some covariate(s is desired due to high dimensionality. We incorporate surrogate variable analyses (SVAs into (ordinary or robust linear regressions and utilize training and testing samples for nested validation to screen CpG sites. SVA is to account for variations in the methylation not explained by the specified covariate(s and adjust for confounding effects. To make it easier to users, this screening method is built into a user-friendly R package, ttScreening, with efficient algorithms implemented. Various simulations were implemented to examine the robustness and sensitivity of the method compared to the classical approaches controlling for multiple testing: the false discovery rates-based (FDR-based and the Bonferroni-based methods. The proposed approach in general performs better and has the potential to control both types I and II errors. We applied ttScreening to 383,998 CpG sites in association with maternal smoking, one of the leading factors for cancer risk.
Smoothing the payoff for efficient computation of Basket option prices
Bayer, Christian
2017-07-22
We consider the problem of pricing basket options in a multivariate Black–Scholes or Variance-Gamma model. From a numerical point of view, pricing such options corresponds to moderate and high-dimensional numerical integration problems with non-smooth integrands. Due to this lack of regularity, higher order numerical integration techniques may not be directly available, requiring the use of methods like Monte Carlo specifically designed to work for non-regular problems. We propose to use the inherent smoothing property of the density of the underlying in the above models to mollify the payoff function by means of an exact conditional expectation. The resulting conditional expectation is unbiased and yields a smooth integrand, which is amenable to the efficient use of adaptive sparse-grid cubature. Numerical examples indicate that the high-order method may perform orders of magnitude faster than Monte Carlo or Quasi Monte Carlo methods in dimensions up to 35.
The computational optimization of heat exchange efficiency in stack chimneys
Energy Technology Data Exchange (ETDEWEB)
Van Goch, T.A.J.
2012-02-15
For many industrial processes, the chimney is the final step before hot fumes, with high thermal energy content, are discharged into the atmosphere. Tapping into this energy and utilizing it for heating or cooling applications, could improve sustainability, efficiency and/or reduce operational costs. Alternatively, an unused chimney, like the monumental chimney at the Eindhoven University of Technology, could serve as an 'energy channeler' once more; it can enhance free cooling by exploiting the stack effect. This study aims to identify design parameters that influence annual heat exchange in such stack chimney applications and optimize these parameters for specific scenarios to maximize the performance. Performance is defined by annual heat exchange, system efficiency and costs. The energy required for the water pump as compared to the energy exchanged, defines the system efficiency, which is expressed in an efficiency coefficient (EC). This study is an example of applying building performance simulation (BPS) tools for decision support in the early phase of the design process. In this study, BPS tools are used to provide design guidance, performance evaluation and optimization. A general method for optimization of simulation models will be studied, and applied in two case studies with different applications (heating/cooling), namely; (1) CERES case: 'Eindhoven University of Technology monumental stack chimney equipped with a heat exchanger, rejects heat to load the cold source of the aquifer system on the campus of the university and/or provides free cooling to the CERES building'; and (2) Industrial case: 'Heat exchanger in an industrial stack chimney, which recoups heat for use in e.g. absorption cooling'. The main research question, addressing the concerns of both cases, is expressed as follows: 'what is the optimal set of design parameters so heat exchange in stack chimneys is optimized annually for the cases in which a
Stochastic congestion management in power markets using efficient scenario approaches
International Nuclear Information System (INIS)
Esmaili, Masoud; Amjady, Nima; Shayanfar, Heidar Ali
2010-01-01
Congestion management in electricity markets is traditionally performed using deterministic values of system parameters assuming a fixed network configuration. In this paper, a stochastic programming framework is proposed for congestion management considering the power system uncertainties comprising outage of generating units and transmission branches. The Forced Outage Rate of equipment is employed in the stochastic programming. Using the Monte Carlo simulation, possible scenarios of power system operating states are generated and a probability is assigned to each scenario. The performance of the ordinary as well as Lattice rank-1 and rank-2 Monte Carlo simulations is evaluated in the proposed congestion management framework. As a tradeoff between computation time and accuracy, scenario reduction based on the standard deviation of accepted scenarios is adopted. The stochastic congestion management solution is obtained by aggregating individual solutions of accepted scenarios. Congestion management using the proposed stochastic framework provides a more realistic solution compared with traditional deterministic solutions. Results of testing the proposed stochastic congestion management on the 24-bus reliability test system indicate the efficiency of the proposed framework.
Efficient Proximity Computation Techniques Using ZIP Code Data for Smart Cities †
Directory of Open Access Journals (Sweden)
Muhammad Harist Murdani
2018-03-01
Full Text Available In this paper, we are interested in computing ZIP code proximity from two perspectives, proximity between two ZIP codes (Ad-Hoc and neighborhood proximity (Top-K. Such a computation can be used for ZIP code-based target marketing as one of the smart city applications. A naïve approach to this computation is the usage of the distance between ZIP codes. We redefine a distance metric combining the centroid distance with the intersecting road network between ZIP codes by using a weighted sum method. Furthermore, we prove that the results of our combined approach conform to the characteristics of distance measurement. We have proposed a general and heuristic approach for computing Ad-Hoc proximity, while for computing Top-K proximity, we have proposed a general approach only. Our experimental results indicate that our approaches are verifiable and effective in reducing the execution time and search space.
Efficient Proximity Computation Techniques Using ZIP Code Data for Smart Cities †.
Murdani, Muhammad Harist; Kwon, Joonho; Choi, Yoon-Ho; Hong, Bonghee
2018-03-24
In this paper, we are interested in computing ZIP code proximity from two perspectives, proximity between two ZIP codes ( Ad-Hoc ) and neighborhood proximity ( Top-K ). Such a computation can be used for ZIP code-based target marketing as one of the smart city applications. A naïve approach to this computation is the usage of the distance between ZIP codes. We redefine a distance metric combining the centroid distance with the intersecting road network between ZIP codes by using a weighted sum method. Furthermore, we prove that the results of our combined approach conform to the characteristics of distance measurement. We have proposed a general and heuristic approach for computing Ad-Hoc proximity, while for computing Top-K proximity, we have proposed a general approach only. Our experimental results indicate that our approaches are verifiable and effective in reducing the execution time and search space.
The peak efficiency calibration of volume source using 152Eu point source in computer
International Nuclear Information System (INIS)
Shen Tingyun; Qian Jianfu; Nan Qinliang; Zhou Yanguo
1997-01-01
The author describes the method of the peak efficiency calibration of volume source by means of 152 Eu point source for HPGe γ spectrometer. The peak efficiency can be computed by Monte Carlo simulation, after inputting parameter of detector. The computation results are in agreement with the experimental results with an error of +-3.8%, with an exception one is about +-7.4%
Towards the Automatic Detection of Efficient Computing Assets in a Heterogeneous Cloud Environment
Iglesias, Jesus Omana; Stokes, Nicola; Ventresque, Anthony; Murphy, Liam, B.E.; Thorburn, James
2013-01-01
peer-reviewed In a heterogeneous cloud environment, the manual grading of computing assets is the first step in the process of configuring IT infrastructures to ensure optimal utilization of resources. Grading the efficiency of computing assets is however, a difficult, subjective and time consuming manual task. Thus, an automatic efficiency grading algorithm is highly desirable. In this paper, we compare the effectiveness of the different criteria used in the manual gr...
Duan, Lili; Liu, Xiao; Zhang, John Z H
2016-05-04
Efficient and reliable calculation of protein-ligand binding free energy is a grand challenge in computational biology and is of critical importance in drug design and many other molecular recognition problems. The main challenge lies in the calculation of entropic contribution to protein-ligand binding or interaction systems. In this report, we present a new interaction entropy method which is theoretically rigorous, computationally efficient, and numerically reliable for calculating entropic contribution to free energy in protein-ligand binding and other interaction processes. Drastically different from the widely employed but extremely expensive normal mode method for calculating entropy change in protein-ligand binding, the new method calculates the entropic component (interaction entropy or -TΔS) of the binding free energy directly from molecular dynamics simulation without any extra computational cost. Extensive study of over a dozen randomly selected protein-ligand binding systems demonstrated that this interaction entropy method is both computationally efficient and numerically reliable and is vastly superior to the standard normal mode approach. This interaction entropy paradigm introduces a novel and intuitive conceptual understanding of the entropic effect in protein-ligand binding and other general interaction systems as well as a practical method for highly efficient calculation of this effect.
An efficient network for interconnecting remote monitoring instruments and computers
International Nuclear Information System (INIS)
Halbig, J.K.; Gainer, K.E.; Klosterbuer, S.F.
1994-01-01
Remote monitoring instrumentation must be connected with computers and other instruments. The cost and intrusiveness of installing cables in new and existing plants presents problems for the facility and the International Atomic Energy Agency (IAEA). The authors have tested a network that could accomplish this interconnection using mass-produced commercial components developed for use in industrial applications. Unlike components in the hardware of most networks, the components--manufactured and distributed in North America, Europe, and Asia--lend themselves to small and low-powered applications. The heart of the network is a chip with three microprocessors and proprietary network software contained in Read Only Memory. In addition to all nonuser levels of protocol, the software also contains message authentication capabilities. This chip can be interfaced to a variety of transmission media, for example, RS-485 lines, fiber topic cables, rf waves, and standard ac power lines. The use of power lines as the transmission medium in a facility could significantly reduce cabling costs
Efficient universal quantum channel simulation in IBM's cloud quantum computer
Wei, Shi-Jie; Xin, Tao; Long, Gui-Lu
2018-07-01
The study of quantum channels is an important field and promises a wide range of applications, because any physical process can be represented as a quantum channel that transforms an initial state into a final state. Inspired by the method of performing non-unitary operators by the linear combination of unitary operations, we proposed a quantum algorithm for the simulation of the universal single-qubit channel, described by a convex combination of "quasi-extreme" channels corresponding to four Kraus operators, and is scalable to arbitrary higher dimension. We demonstrated the whole algorithm experimentally using the universal IBM cloud-based quantum computer and studied the properties of different qubit quantum channels. We illustrated the quantum capacity of the general qubit quantum channels, which quantifies the amount of quantum information that can be protected. The behavior of quantum capacity in different channels revealed which types of noise processes can support information transmission, and which types are too destructive to protect information. There was a general agreement between the theoretical predictions and the experiments, which strongly supports our method. By realizing the arbitrary qubit channel, this work provides a universally- accepted way to explore various properties of quantum channels and novel prospect for quantum communication.
Enabling Efficient Climate Science Workflows in High Performance Computing Environments
Krishnan, H.; Byna, S.; Wehner, M. F.; Gu, J.; O'Brien, T. A.; Loring, B.; Stone, D. A.; Collins, W.; Prabhat, M.; Liu, Y.; Johnson, J. N.; Paciorek, C. J.
2015-12-01
A typical climate science workflow often involves a combination of acquisition of data, modeling, simulation, analysis, visualization, publishing, and storage of results. Each of these tasks provide a myriad of challenges when running on a high performance computing environment such as Hopper or Edison at NERSC. Hurdles such as data transfer and management, job scheduling, parallel analysis routines, and publication require a lot of forethought and planning to ensure that proper quality control mechanisms are in place. These steps require effectively utilizing a combination of well tested and newly developed functionality to move data, perform analysis, apply statistical routines, and finally, serve results and tools to the greater scientific community. As part of the CAlibrated and Systematic Characterization, Attribution and Detection of Extremes (CASCADE) project we highlight a stack of tools our team utilizes and has developed to ensure that large scale simulation and analysis work are commonplace and provide operations that assist in everything from generation/procurement of data (HTAR/Globus) to automating publication of results to portals like the Earth Systems Grid Federation (ESGF), all while executing everything in between in a scalable environment in a task parallel way (MPI). We highlight the use and benefit of these tools by showing several climate science analysis use cases they have been applied to.
Narasimhan, Seetharam; Chiel, Hillel J; Bhunia, Swarup
2009-01-01
For implantable neural interface applications, it is important to compress data and analyze spike patterns across multiple channels in real time. Such a computational task for online neural data processing requires an innovative circuit-architecture level design approach for low-power, robust and area-efficient hardware implementation. Conventional microprocessor or Digital Signal Processing (DSP) chips would dissipate too much power and are too large in size for an implantable system. In this paper, we propose a novel hardware design approach, referred to as "Preferential Design" that exploits the nature of the neural signal processing algorithm to achieve a low-voltage, robust and area-efficient implementation using nanoscale process technology. The basic idea is to isolate the critical components with respect to system performance and design them more conservatively compared to the noncritical ones. This allows aggressive voltage scaling for low power operation while ensuring robustness and area efficiency. We have applied the proposed approach to a neural signal processing algorithm using the Discrete Wavelet Transform (DWT) and observed significant improvement in power and robustness over conventional design.
A kinematic approach for efficient and robust simulation of the cardiac beating motion.
Directory of Open Access Journals (Sweden)
Takashi Ijiri
Full Text Available Computer simulation techniques for cardiac beating motions potentially have many applications and a broad audience. However, most existing methods require enormous computational costs and often show unstable behavior for extreme parameter sets, which interrupts smooth simulation study and make it difficult to apply them to interactive applications. To address this issue, we present an efficient and robust framework for simulating the cardiac beating motion. The global cardiac motion is generated by the accumulation of local myocardial fiber contractions. We compute such local-to-global deformations using a kinematic approach; we divide a heart mesh model into overlapping local regions, contract them independently according to fiber orientation, and compute a global shape that satisfies contracted shapes of all local regions as much as possible. A comparison between our method and a physics-based method showed that our method can generate motion very close to that of a physics-based simulation. Our kinematic method has high controllability; the simulated ventricle-wall-contraction speed can be easily adjusted to that of a real heart by controlling local contraction timing. We demonstrate that our method achieves a highly realistic beating motion of a whole heart in real time on a consumer-level computer. Our method provides an important step to bridge a gap between cardiac simulations and interactive applications.
Combinatorial computational chemistry approach to the design of metal catalysts for deNOx
International Nuclear Information System (INIS)
Endou, Akira; Jung, Changho; Kusagaya, Tomonori; Kubo, Momoji; Selvam, Parasuraman; Miyamoto, Akira
2004-01-01
Combinatorial chemistry is an efficient technique for the synthesis and screening of a large number of compounds. Recently, we introduced the combinatorial approach to computational chemistry for catalyst design and proposed a new method called ''combinatorial computational chemistry''. In the present study, we have applied this combinatorial computational chemistry approach to the design of precious metal catalysts for deNO x . As the first step of the screening of the metal catalysts, we studied Rh, Pd, Ag, Ir, Pt, and Au clusters regarding the adsorption properties towards NO molecule. It was demonstrated that the energetically most stable adsorption state of NO on Ir model cluster, which was irrespective of both the shape and number of atoms including the model clusters
Computational Approaches to the Chemical Equilibrium Constant in Protein-ligand Binding.
Montalvo-Acosta, Joel José; Cecchini, Marco
2016-12-01
The physiological role played by protein-ligand recognition has motivated the development of several computational approaches to the ligand binding affinity. Some of them, termed rigorous, have a strong theoretical foundation but involve too much computation to be generally useful. Some others alleviate the computational burden by introducing strong approximations and/or empirical calibrations, which also limit their general use. Most importantly, there is no straightforward correlation between the predictive power and the level of approximation introduced. Here, we present a general framework for the quantitative interpretation of protein-ligand binding based on statistical mechanics. Within this framework, we re-derive self-consistently the fundamental equations of some popular approaches to the binding constant and pinpoint the inherent approximations. Our analysis represents a first step towards the development of variants with optimum accuracy/efficiency ratio for each stage of the drug discovery pipeline. © 2016 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.
International Nuclear Information System (INIS)
Vignes, J.
1986-01-01
Any result of algorithms provided by a computer always contains an error resulting from floating-point arithmetic round-off error propagation. Furthermore signal processing algorithms are also generally performed with data containing errors. The permutation-perturbation method, also known under the name CESTAC (controle et estimation stochastique d'arrondi de calcul) is a very efficient practical method for evaluating these errors and consequently for estimating the exact significant decimal figures of any result of algorithms performed on a computer. The stochastic approach of this method, its probabilistic proof, and the perfect agreement between the theoretical and practical aspects are described in this paper [fr
A computational approach to chemical etiologies of diabetes
DEFF Research Database (Denmark)
Audouze, Karine Marie Laure; Brunak, Søren; Grandjean, Philippe
2013-01-01
Computational meta-analysis can link environmental chemicals to genes and proteins involved in human diseases, thereby elucidating possible etiologies and pathogeneses of non-communicable diseases. We used an integrated computational systems biology approach to examine possible pathogenetic...... linkages in type 2 diabetes (T2D) through genome-wide associations, disease similarities, and published empirical evidence. Ten environmental chemicals were found to be potentially linked to T2D, the highest scores were observed for arsenic, 2,3,7,8-tetrachlorodibenzo-p-dioxin, hexachlorobenzene...
Computationally efficient thermal-mechanical modelling of selective laser melting
Yang, Yabin; Ayas, Can
2017-10-01
The Selective laser melting (SLM) is a powder based additive manufacturing (AM) method to produce high density metal parts with complex topology. However, part distortions and accompanying residual stresses deteriorates the mechanical reliability of SLM products. Modelling of the SLM process is anticipated to be instrumental for understanding and predicting the development of residual stress field during the build process. However, SLM process modelling requires determination of the heat transients within the part being built which is coupled to a mechanical boundary value problem to calculate displacement and residual stress fields. Thermal models associated with SLM are typically complex and computationally demanding. In this paper, we present a simple semi-analytical thermal-mechanical model, developed for SLM that represents the effect of laser scanning vectors with line heat sources. The temperature field within the part being build is attained by superposition of temperature field associated with line heat sources in a semi-infinite medium and a complimentary temperature field which accounts for the actual boundary conditions. An analytical solution of a line heat source in a semi-infinite medium is first described followed by the numerical procedure used for finding the complimentary temperature field. This analytical description of the line heat sources is able to capture the steep temperature gradients in the vicinity of the laser spot which is typically tens of micrometers. In turn, semi-analytical thermal model allows for having a relatively coarse discretisation of the complimentary temperature field. The temperature history determined is used to calculate the thermal strain induced on the SLM part. Finally, a mechanical model governed by elastic-plastic constitutive rule having isotropic hardening is used to predict the residual stresses.
Energy-Efficient Abundant-Data Computing: The N3XT 1,000X
Aly Mohamed M. Sabry; Gao Mingyu; Hills Gage; Lee Chi-Shuen; Pinter Greg; Shulaker Max M.; Wu Tony F.; Asheghi Mehdi; Bokor Jeff; Franchetti Franz; Goodson Kenneth E.; Kozyrakis Christos; Markov Igor; Olukotun Kunle; Pileggi Larry
2015-01-01
Next generation information technologies will process unprecedented amounts of loosely structured data that overwhelm existing computing systems. N3XT improves the energy efficiency of abundant data applications 1000 fold by using new logic and memory technologies 3D integration with fine grained connectivity and new architectures for computation immersed in memory.
Nitrogen efficiency of Dutch dairy farms : A shadow cost system approach
Reinhard, S.; Thijssen, G.J.
2000-01-01
In this paper we analyse the cost efficiency and nitrogen efficiency of an unbalanced panel of Dutch dairy farms. Nitrogen efficiency is defined as the ratio of minimal to observed use of nitrogen (N-containing inputs), conditional on output and quasi-fixed inputs. Nitrogen efficiency is computed in
Efficient approach to obtain free energy gradient using QM/MM MD simulation
International Nuclear Information System (INIS)
Asada, Toshio; Koseki, Shiro; Ando, Kanta
2015-01-01
The efficient computational approach denoted as charge and atom dipole response kernel (CDRK) model to consider polarization effects of the quantum mechanical (QM) region is described using the charge response and the atom dipole response kernels for free energy gradient (FEG) calculations in the quantum mechanical/molecular mechanical (QM/MM) method. CDRK model can reasonably reproduce energies and also energy gradients of QM and MM atoms obtained by expensive QM/MM calculations in a drastically reduced computational time. This model is applied on the acylation reaction in hydrated trypsin-BPTI complex to optimize the reaction path on the free energy surface by means of FEG and the nudged elastic band (NEB) method
An efficient multiple particle filter based on the variational Bayesian approach
Ait-El-Fquih, Boujemaa
2015-12-07
This paper addresses the filtering problem in large-dimensional systems, in which conventional particle filters (PFs) remain computationally prohibitive owing to the large number of particles needed to obtain reasonable performances. To overcome this drawback, a class of multiple particle filters (MPFs) has been recently introduced in which the state-space is split into low-dimensional subspaces, and then a separate PF is applied to each subspace. In this paper, we adopt the variational Bayesian (VB) approach to propose a new MPF, the VBMPF. The proposed filter is computationally more efficient since the propagation of each particle requires generating one (new) particle only, while in the standard MPFs a set of (children) particles needs to be generated. In a numerical test, the proposed VBMPF behaves better than the PF and MPF.
International Nuclear Information System (INIS)
Beltrán-Esteve, Mercedes; Reig-Martínez, Ernest; Estruch-Guitart, Vicent
2017-01-01
Sustainability analysis requires a joint assessment of environmental, social and economic aspects of production processes. Here we propose the use of Life Cycle Analysis (LCA), a metafrontier (MF) directional distance function (DDF) approach, and Data Envelopment Analysis (DEA), to assess technological and managerial differences in eco-efficiency between production systems. We use LCA to compute six environmental and health impacts associated with the production processes of nearly 200 Spanish citrus farms belonging to organic and conventional farming systems. DEA is then employed to obtain joint economic-environmental farm's scores that we refer to as eco-efficiency. DDF allows us to determine farms' global eco-efficiency scores, as well as eco-efficiency scores with respect to specific environmental impacts. Furthermore, the use of an MF helps us to disentangle technological and managerial eco-inefficiencies by comparing the eco-efficiency of both farming systems with regards to a common benchmark. Our core results suggest that the shift from conventional to organic farming technology would allow a potential reduction in environmental impacts of 80% without resulting in any decline in economic performance. In contrast, as regards farmers' managerial capacities, both systems display quite similar mean scores.
Energy Technology Data Exchange (ETDEWEB)
Beltrán-Esteve, Mercedes, E-mail: mercedes.beltran@uv.es [Department of Applied Economics II, University of Valencia (Spain); Reig-Martínez, Ernest [Department of Applied Economics II, University of Valencia, Ivie (Spain); Estruch-Guitart, Vicent [Department of Economy and Social Sciences, Polytechnic University of Valencia (Spain)
2017-03-15
Sustainability analysis requires a joint assessment of environmental, social and economic aspects of production processes. Here we propose the use of Life Cycle Analysis (LCA), a metafrontier (MF) directional distance function (DDF) approach, and Data Envelopment Analysis (DEA), to assess technological and managerial differences in eco-efficiency between production systems. We use LCA to compute six environmental and health impacts associated with the production processes of nearly 200 Spanish citrus farms belonging to organic and conventional farming systems. DEA is then employed to obtain joint economic-environmental farm's scores that we refer to as eco-efficiency. DDF allows us to determine farms' global eco-efficiency scores, as well as eco-efficiency scores with respect to specific environmental impacts. Furthermore, the use of an MF helps us to disentangle technological and managerial eco-inefficiencies by comparing the eco-efficiency of both farming systems with regards to a common benchmark. Our core results suggest that the shift from conventional to organic farming technology would allow a potential reduction in environmental impacts of 80% without resulting in any decline in economic performance. In contrast, as regards farmers' managerial capacities, both systems display quite similar mean scores.
A multiresolution approach to iterative reconstruction algorithms in X-ray computed tomography.
De Witte, Yoni; Vlassenbroeck, Jelle; Van Hoorebeke, Luc
2010-09-01
In computed tomography, the application of iterative reconstruction methods in practical situations is impeded by their high computational demands. Especially in high resolution X-ray computed tomography, where reconstruction volumes contain a high number of volume elements (several giga voxels), this computational burden prevents their actual breakthrough. Besides the large amount of calculations, iterative algorithms require the entire volume to be kept in memory during reconstruction, which quickly becomes cumbersome for large data sets. To overcome this obstacle, we present a novel multiresolution reconstruction, which greatly reduces the required amount of memory without significantly affecting the reconstructed image quality. It is shown that, combined with an efficient implementation on a graphical processing unit, the multiresolution approach enables the application of iterative algorithms in the reconstruction of large volumes at an acceptable speed using only limited resources.
The thermodynamic efficiency of computations made in cells across the range of life
Kempes, Christopher P.; Wolpert, David; Cohen, Zachary; Pérez-Mercader, Juan
2017-11-01
Biological organisms must perform computation as they grow, reproduce and evolve. Moreover, ever since Landauer's bound was proposed, it has been known that all computation has some thermodynamic cost-and that the same computation can be achieved with greater or smaller thermodynamic cost depending on how it is implemented. Accordingly an important issue concerning the evolution of life is assessing the thermodynamic efficiency of the computations performed by organisms. This issue is interesting both from the perspective of how close life has come to maximally efficient computation (presumably under the pressure of natural selection), and from the practical perspective of what efficiencies we might hope that engineered biological computers might achieve, especially in comparison with current computational systems. Here we show that the computational efficiency of translation, defined as free energy expended per amino acid operation, outperforms the best supercomputers by several orders of magnitude, and is only about an order of magnitude worse than the Landauer bound. However, this efficiency depends strongly on the size and architecture of the cell in question. In particular, we show that the useful efficiency of an amino acid operation, defined as the bulk energy per amino acid polymerization, decreases for increasing bacterial size and converges to the polymerization cost of the ribosome. This cost of the largest bacteria does not change in cells as we progress through the major evolutionary shifts to both single- and multicellular eukaryotes. However, the rates of total computation per unit mass are non-monotonic in bacteria with increasing cell size, and also change across different biological architectures, including the shift from unicellular to multicellular eukaryotes. This article is part of the themed issue 'Reconceptualizing the origins of life'.
Improving the Eco-Efficiency of High Performance Computing Clusters Using EECluster
Directory of Open Access Journals (Sweden)
Alberto Cocaña-Fernández
2016-03-01
Full Text Available As data and supercomputing centres increase their performance to improve service quality and target more ambitious challenges every day, their carbon footprint also continues to grow, and has already reached the magnitude of the aviation industry. Also, high power consumptions are building up to a remarkable bottleneck for the expansion of these infrastructures in economic terms due to the unavailability of sufficient energy sources. A substantial part of the problem is caused by current energy consumptions of High Performance Computing (HPC clusters. To alleviate this situation, we present in this work EECluster, a tool that integrates with multiple open-source Resource Management Systems to significantly reduce the carbon footprint of clusters by improving their energy efficiency. EECluster implements a dynamic power management mechanism based on Computational Intelligence techniques by learning a set of rules through multi-criteria evolutionary algorithms. This approach enables cluster operators to find the optimal balance between a reduction in the cluster energy consumptions, service quality, and number of reconfigurations. Experimental studies using both synthetic and actual workloads from a real world cluster support the adoption of this tool to reduce the carbon footprint of HPC clusters.
Ye, Kai; Kosters, Walter A; Ijzerman, Adriaan P
2007-03-15
Pattern discovery in protein sequences is often based on multiple sequence alignments (MSA). The procedure can be computationally intensive and often requires manual adjustment, which may be particularly difficult for a set of deviating sequences. In contrast, two algorithms, PRATT2 (http//www.ebi.ac.uk/pratt/) and TEIRESIAS (http://cbcsrv.watson.ibm.com/) are used to directly identify frequent patterns from unaligned biological sequences without an attempt to align them. Here we propose a new algorithm with more efficiency and more functionality than both PRATT2 and TEIRESIAS, and discuss some of its applications to G protein-coupled receptors, a protein family of important drug targets. In this study, we designed and implemented six algorithms to mine three different pattern types from either one or two datasets using a pattern growth approach. We compared our approach to PRATT2 and TEIRESIAS in efficiency, completeness and the diversity of pattern types. Compared to PRATT2, our approach is faster, capable of processing large datasets and able to identify the so-called type III patterns. Our approach is comparable to TEIRESIAS in the discovery of the so-called type I patterns but has additional functionality such as mining the so-called type II and type III patterns and finding discriminating patterns between two datasets. The source code for pattern growth algorithms and their pseudo-code are available at http://www.liacs.nl/home/kosters/pg/.
Pal, Partha S; Kar, R; Mandal, D; Ghoshal, S P
2015-11-01
This paper presents an efficient approach to identify different stable and practically useful Hammerstein models as well as unstable nonlinear process along with its stable closed loop counterpart with the help of an evolutionary algorithm as Colliding Bodies Optimization (CBO) optimization algorithm. The performance measures of the CBO based optimization approach such as precision, accuracy are justified with the minimum output mean square value (MSE) which signifies that the amount of bias and variance in the output domain are also the least. It is also observed that the optimization of output MSE in the presence of outliers has resulted in a very close estimation of the output parameters consistently, which also justifies the effective general applicability of the CBO algorithm towards the system identification problem and also establishes the practical usefulness of the applied approach. Optimum values of the MSEs, computational times and statistical information of the MSEs are all found to be the superior as compared with those of the other existing similar types of stochastic algorithms based approaches reported in different recent literature, which establish the robustness and efficiency of the applied CBO based identification scheme. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.
Efficient conjugate gradient algorithms for computation of the manipulator forward dynamics
Fijany, Amir; Scheid, Robert E.
1989-01-01
The applicability of conjugate gradient algorithms for computation of the manipulator forward dynamics is investigated. The redundancies in the previously proposed conjugate gradient algorithm are analyzed. A new version is developed which, by avoiding these redundancies, achieves a significantly greater efficiency. A preconditioned conjugate gradient algorithm is also presented. A diagonal matrix whose elements are the diagonal elements of the inertia matrix is proposed as the preconditioner. In order to increase the computational efficiency, an algorithm is developed which exploits the synergism between the computation of the diagonal elements of the inertia matrix and that required by the conjugate gradient algorithm.
Use of spatial symmetry in atomic--integral calculations: an efficient permutational approach
International Nuclear Information System (INIS)
Rouzo, H.L.
1979-01-01
The minimal number of independent nonzero atomic integrals that occur over arbitrarily oriented basis orbitals of the form R(r).Y/sub lm/(Ω) is theoretically derived. The corresponding method can be easily applied to any point group, including the molecular continuous groups C/sub infinity v/ and D/sub infinity h/. On the basis of this (theoretical) lower bound, the efficiency of the permutational approach in generating sets of independent integrals is discussed. It is proved that lobe orbitals are always more efficient than the familiar Cartesian Gaussians, in the sense that GLOS provide the shortest integral lists. Moreover, it appears that the new axial GLOS often lead to a number of integrals, which is the theoretical lower bound previously defined. With AGLOS, the numbers of two-electron integrals to be computed, stored, and processed are divided by factors 2.9 (NH 3 ), 4.2 (C 5 H 5 ), and 3.6 (C 6 H 6 ) with reference to the corresponding CGTOS calculations. Remembering that in the permutational approach, atomic integrals are directly computed without any four-indice transformation, it appears that its utilization in connection with AGLOS provides one of the most powerful tools for treating symmetrical species. 34 references
Measuring highway efficiency : A DEA approach and the Malquist index
Sarmento, Joaquim Miranda; Renneboog, Luc; Verga-Matos, Pedro
A growing concern exists regarding the efficiency of public resources spent in transport infrastructures. In this paper, we measure the efficiency of seven highway projects in Portugal over the past decade by means of a data envelopment analysis and the Malmquist productivity and efficiency indices.
Energy Technology Data Exchange (ETDEWEB)
Chiang, Patrick [Oregon State Univ., Corvallis, OR (United States)
2014-01-31
The research goal of this CAREER proposal is to develop energy-efficient, VLSI interconnect circuits and systems that will facilitate future massively-parallel, high-performance computing. Extreme-scale computing will exhibit massive parallelism on multiple vertical levels, from thou sands of computational units on a single processor to thousands of processors in a single data center. Unfortunately, the energy required to communicate between these units at every level (on chip, off-chip, off-rack) will be the critical limitation to energy efficiency. Therefore, the PI's career goal is to become a leading researcher in the design of energy-efficient VLSI interconnect for future computing systems.
WSRC approach to validation of criticality safety computer codes
International Nuclear Information System (INIS)
Finch, D.R.; Mincey, J.F.
1991-01-01
Recent hardware and operating system changes at Westinghouse Savannah River Site (WSRC) have necessitated review of the validation for JOSHUA criticality safety computer codes. As part of the planning for this effort, a policy for validation of JOSHUA and other criticality safety codes has been developed. This policy will be illustrated with the steps being taken at WSRC. The objective in validating a specific computational method is to reliably correlate its calculated neutron multiplication factor (K eff ) with known values over a well-defined set of neutronic conditions. Said another way, such correlations should be: (1) repeatable; (2) demonstrated with defined confidence; and (3) identify the range of neutronic conditions (area of applicability) for which the correlations are valid. The general approach to validation of computational methods at WSRC must encompass a large number of diverse types of fissile material processes in different operations. Special problems are presented in validating computational methods when very few experiments are available (such as for enriched uranium systems with principal second isotope 236 U). To cover all process conditions at WSRC, a broad validation approach has been used. Broad validation is based upon calculation of many experiments to span all possible ranges of reflection, nuclide concentrations, moderation ratios, etc. Narrow validation, in comparison, relies on calculations of a few experiments very near anticipated worst-case process conditions. The methods and problems of broad validation are discussed
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.
A SURVEY ON DOCUMENT CLUSTERING APPROACH FOR COMPUTER FORENSIC ANALYSIS
Monika Raghuvanshi*, Rahul Patel
2016-01-01
In a forensic analysis, large numbers of files are examined. Much of the information comprises of in unstructured format, so it’s quite difficult task for computer forensic to perform such analysis. That’s why to do the forensic analysis of document within a limited period of time require a special approach such as document clustering. This paper review different document clustering algorithms methodologies for example K-mean, K-medoid, single link, complete link, average link in accorandance...
Highly efficient computer algorithm for identifying layer thickness of atomically thin 2D materials
Lee, Jekwan; Cho, Seungwan; Park, Soohyun; Bae, Hyemin; Noh, Minji; Kim, Beom; In, Chihun; Yang, Seunghoon; Lee, Sooun; Seo, Seung Young; Kim, Jehyun; Lee, Chul-Ho; Shim, Woo-Young; Jo, Moon-Ho; Kim, Dohun; Choi, Hyunyong
2018-03-01
The fields of layered material research, such as transition-metal dichalcogenides (TMDs), have demonstrated that the optical, electrical and mechanical properties strongly depend on the layer number N. Thus, efficient and accurate determination of N is the most crucial step before the associated device fabrication. An existing experimental technique using an optical microscope is the most widely used one to identify N. However, a critical drawback of this approach is that it relies on extensive laboratory experiences to estimate N; it requires a very time-consuming image-searching task assisted by human eyes and secondary measurements such as atomic force microscopy and Raman spectroscopy, which are necessary to ensure N. In this work, we introduce a computer algorithm based on the image analysis of a quantized optical contrast. We show that our algorithm can apply to a wide variety of layered materials, including graphene, MoS2, and WS2 regardless of substrates. The algorithm largely consists of two parts. First, it sets up an appropriate boundary between target flakes and substrate. Second, to compute N, it automatically calculates the optical contrast using an adaptive RGB estimation process between each target, which results in a matrix with different integer Ns and returns a matrix map of Ns onto the target flake position. Using a conventional desktop computational power, the time taken to display the final N matrix was 1.8 s on average for the image size of 1280 pixels by 960 pixels and obtained a high accuracy of 90% (six estimation errors among 62 samples) when compared to the other methods. To show the effectiveness of our algorithm, we also apply it to TMD flakes transferred on optically transparent c-axis sapphire substrates and obtain a similar result of the accuracy of 94% (two estimation errors among 34 samples).
New Computational Approach to Electron Transport in Irregular Graphene Nanostructures
Mason, Douglas; Heller, Eric; Prendergast, David; Neaton, Jeffrey
2009-03-01
For novel graphene devices of nanoscale-to-macroscopic scale, many aspects of their transport properties are not easily understood due to difficulties in fabricating devices with regular edges. Here we develop a framework to efficiently calculate and potentially screen electronic transport properties of arbitrary nanoscale graphene device structures. A generalization of the established recursive Green's function method is presented, providing access to arbitrary device and lead geometries with substantial computer-time savings. Using single-orbital nearest-neighbor tight-binding models and the Green's function-Landauer scattering formalism, we will explore the transmission function of irregular two-dimensional graphene-based nanostructures with arbitrary lead orientation. Prepared by LBNL under contract DE-AC02-05CH11231 and supported by the U.S. Dept. of Energy Computer Science Graduate Fellowship under grant DE-FG02-97ER25308.
Do Energy Efficiency Standards Improve Quality? Evidence from a Revealed Preference Approach
Energy Technology Data Exchange (ETDEWEB)
Houde, Sebastien [Univ. of Maryland, College Park, MD (United States); Spurlock, C. Anna [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
2015-06-01
Minimum energy efficiency standards have occupied a central role in U.S. energy policy for more than three decades, but little is known about their welfare effects. In this paper, we employ a revealed preference approach to quantify the impact of past revisions in energy efficiency standards on product quality. The micro-foundation of our approach is a discrete choice model that allows us to compute a price-adjusted index of vertical quality. Focusing on the appliance market, we show that several standard revisions during the period 2001-2011 have led to an increase in quality. We also show that these standards have had a modest effect on prices, and in some cases they even led to decreases in prices. For revision events where overall quality increases and prices decrease, the consumer welfare effect of tightening the standards is unambiguously positive. Finally, we show that after controlling for the effect of improvement in energy efficiency, standards have induced an expansion of quality in the non-energy dimension. We discuss how imperfect competition can rationalize these results.
Hospital efficiency and transaction costs: a stochastic frontier approach.
Ludwig, Martijn; Groot, Wim; Van Merode, Frits
2009-07-01
The make-or-buy decision of organizations is an important issue in the transaction cost theory, but is usually not analyzed from an efficiency perspective. Hospitals frequently have to decide whether to outsource or not. The main question we address is: Is the make-or-buy decision affected by the efficiency of hospitals? A one-stage stochastic cost frontier equation is estimated for Dutch hospitals. The make-or-buy decisions of ten different hospital services are used as explanatory variables to explain efficiency of hospitals. It is found that for most services the make-or-buy decision is not related to efficiency. Kitchen services are an important exception to this. Large hospitals tend to outsource less, which is supported by efficiency reasons. For most hospital services, outsourcing does not significantly affect the efficiency of hospitals. The focus on the make-or-buy decision may therefore be less important than often assumed.
Efficiency analysis of Chinese industry: A directional distance function approach
International Nuclear Information System (INIS)
Watanabe, Michio; Tanaka, Katsuya
2007-01-01
Two efficiency measures of Chinese industry were estimated at the provincial level from 1994 to 2002, using a directional output distance function. One is a traditional efficiency measure that considers only desirable output, while the other considers both desirable and undesirable outputs simultaneously. A comparison of the two measures revealed that efficiency levels are biased only if desirable output is considered. Five coastal provinces/municipalities that have attracted a large amount of foreign direct investment are found to be the most efficient when only desirable output is considered, and also when both desirable and undesirable outputs are considered. However, omitting undesirable output tends to lead to an overestimate of industrial efficiency levels in Shandong, Sichuan, and Hebei provinces. We also found that a province's industrial structure has significant effects on its efficiency levels
Computational Approaches for Integrative Analysis of the Metabolome and Microbiome
Directory of Open Access Journals (Sweden)
Jasmine Chong
2017-11-01
Full Text Available The study of the microbiome, the totality of all microbes inhabiting the host or an environmental niche, has experienced exponential growth over the past few years. The microbiome contributes functional genes and metabolites, and is an important factor for maintaining health. In this context, metabolomics is increasingly applied to complement sequencing-based approaches (marker genes or shotgun metagenomics to enable resolution of microbiome-conferred functionalities associated with health. However, analyzing the resulting multi-omics data remains a significant challenge in current microbiome studies. In this review, we provide an overview of different computational approaches that have been used in recent years for integrative analysis of metabolome and microbiome data, ranging from statistical correlation analysis to metabolic network-based modeling approaches. Throughout the process, we strive to present a unified conceptual framework for multi-omics integration and interpretation, as well as point out potential future directions.
Stochastic Boolean networks: An efficient approach to modeling gene regulatory networks
Directory of Open Access Journals (Sweden)
Liang Jinghang
2012-08-01
Full Text Available Abstract Background Various computational models have been of interest due to their use in the modelling of gene regulatory networks (GRNs. As a logical model, probabilistic Boolean networks (PBNs consider molecular and genetic noise, so the study of PBNs provides significant insights into the understanding of the dynamics of GRNs. This will ultimately lead to advances in developing therapeutic methods that intervene in the process of disease development and progression. The applications of PBNs, however, are hindered by the complexities involved in the computation of the state transition matrix and the steady-state distribution of a PBN. For a PBN with n genes and N Boolean networks, the complexity to compute the state transition matrix is O(nN22n or O(nN2n for a sparse matrix. Results This paper presents a novel implementation of PBNs based on the notions of stochastic logic and stochastic computation. This stochastic implementation of a PBN is referred to as a stochastic Boolean network (SBN. An SBN provides an accurate and efficient simulation of a PBN without and with random gene perturbation. The state transition matrix is computed in an SBN with a complexity of O(nL2n, where L is a factor related to the stochastic sequence length. Since the minimum sequence length required for obtaining an evaluation accuracy approximately increases in a polynomial order with the number of genes, n, and the number of Boolean networks, N, usually increases exponentially with n, L is typically smaller than N, especially in a network with a large number of genes. Hence, the computational efficiency of an SBN is primarily limited by the number of genes, but not directly by the total possible number of Boolean networks. Furthermore, a time-frame expanded SBN enables an efficient analysis of the steady-state distribution of a PBN. These findings are supported by the simulation results of a simplified p53 network, several randomly generated networks and a
International Nuclear Information System (INIS)
Woodruff, S.B.
1994-01-01
The Transient Reactor Analysis Code (TRAC), which features a two-fluid treatment of thermal-hydraulics, is designed to model transients in water reactors and related facilities. One of the major computational costs associated with TRAC and similar codes is calculating constitutive coefficients. Although the formulations for these coefficients are local, the costs are flow-regime- or data-dependent; i.e., the computations needed for a given spatial node often vary widely as a function of time. Consequently, a fixed, uniform assignment of nodes to prallel processors will result in degraded computational efficiency due to the poor load balancing. A standard method for treating data-dependent models on vector architectures has been to use gather operations (or indirect adressing) to sort the nodes into subsets that (temporarily) share a common computational model. However, this method is not effective on distributed memory data parallel architectures, where indirect adressing involves expensive communication overhead. Another serious problem with this method involves software engineering challenges in the areas of maintainability and extensibility. For example, an implementation that was hand-tuned to achieve good computational efficiency would have to be rewritten whenever the decision tree governing the sorting was modified. Using an example based on the calculation of the wall-to-liquid and wall-to-vapor heat-transfer coefficients for three nonboiling flow regimes, we describe how the use of the Fortran 90 WHERE construct and automatic inlining of functions can be used to ameliorate this problem while improving both efficiency and software engineering. Unfortunately, a general automatic solution to the load-balancing problem associated with data-dependent computations is not yet available for massively parallel architectures. We discuss why developers should either wait for such solutions or consider alternative numerical algorithms, such as a neural network
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.
SPINET: A Parallel Computing Approach to Spine Simulations
Directory of Open Access Journals (Sweden)
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.
Computer-oriented approach to fault-tree construction
International Nuclear Information System (INIS)
Salem, S.L.; Apostolakis, G.E.; Okrent, D.
1976-11-01
A methodology for systematically constructing fault trees for general complex systems is developed and applied, via the Computer Automated Tree (CAT) program, to several systems. A means of representing component behavior by decision tables is presented. The method developed allows the modeling of components with various combinations of electrical, fluid and mechanical inputs and outputs. Each component can have multiple internal failure mechanisms which combine with the states of the inputs to produce the appropriate output states. The generality of this approach allows not only the modeling of hardware, but human actions and interactions as well. A procedure for constructing and editing fault trees, either manually or by computer, is described. The techniques employed result in a complete fault tree, in standard form, suitable for analysis by current computer codes. Methods of describing the system, defining boundary conditions and specifying complex TOP events are developed in order to set up the initial configuration for which the fault tree is to be constructed. The approach used allows rapid modifications of the decision tables and systems to facilitate the analysis and comparison of various refinements and changes in the system configuration and component modeling
A comparative approach to closed-loop computation.
Roth, E; Sponberg, S; Cowan, N J
2014-04-01
Neural computation is inescapably closed-loop: the nervous system processes sensory signals to shape motor output, and motor output consequently shapes sensory input. Technological advances have enabled neuroscientists to close, open, and alter feedback loops in a wide range of experimental preparations. The experimental capability of manipulating the topology-that is, how information can flow between subsystems-provides new opportunities to understand the mechanisms and computations underlying behavior. These experiments encompass a spectrum of approaches from fully open-loop, restrained preparations to the fully closed-loop character of free behavior. Control theory and system identification provide a clear computational framework for relating these experimental approaches. We describe recent progress and new directions for translating experiments at one level in this spectrum to predictions at another level. Operating across this spectrum can reveal new understanding of how low-level neural mechanisms relate to high-level function during closed-loop behavior. Copyright © 2013 Elsevier Ltd. All rights reserved.
Productive efficiency of tea industry: A stochastic frontier approach ...
African Journals Online (AJOL)
In an economy where recourses are scarce and opportunities for a new technology are lacking, studies will be able to show the possibility of raising productivity by improving the industry's efficiency. This study attempts to measure the status of technical efficiency of tea-producing industry for panel data in Bangladesh using ...
Computational approaches in the design of synthetic receptors - A review.
Cowen, Todd; Karim, Kal; Piletsky, Sergey
2016-09-14
The rational design of molecularly imprinted polymers (MIPs) has been a major contributor to their reputation as "plastic antibodies" - high affinity robust synthetic receptors which can be optimally designed, and produced for a much reduced cost than their biological equivalents. Computational design has become a routine procedure in the production of MIPs, and has led to major advances in functional monomer screening, selection of cross-linker and solvent, optimisation of monomer(s)-template ratio and selectivity analysis. In this review the various computational methods will be discussed with reference to all the published relevant literature since the end of 2013, with each article described by the target molecule, the computational approach applied (whether molecular mechanics/molecular dynamics, semi-empirical quantum mechanics, ab initio quantum mechanics (Hartree-Fock, Møller-Plesset, etc.) or DFT) and the purpose for which they were used. Detailed analysis is given to novel techniques including analysis of polymer binding sites, the use of novel screening programs and simulations of MIP polymerisation reaction. The further advances in molecular modelling and computational design of synthetic receptors in particular will have serious impact on the future of nanotechnology and biotechnology, permitting the further translation of MIPs into the realms of analytics and medical technology. Copyright © 2016 Elsevier B.V. All rights reserved.
Analytical and computational approaches to define the Aspergillus niger secretome
Energy Technology Data Exchange (ETDEWEB)
Tsang, Adrian; Butler, Gregory D.; Powlowski, Justin; Panisko, Ellen A.; Baker, Scott E.
2009-03-01
We used computational and mass spectrometric approaches to characterize the Aspergillus niger secretome. The 11,200 gene models predicted in the genome of A. niger strain ATCC 1015 were the data source for the analysis. Depending on the computational methods used, 691 to 881 proteins were predicted to be secreted proteins. We cultured A. niger in six different media and analyzed the extracellular proteins produced using mass spectrometry. A total of 222 proteins were identified, with 39 proteins expressed under all six conditions and 74 proteins expressed under only one condition. The secreted proteins identified by mass spectrometry were used to guide the correction of about 20 gene models. Additional analysis focused on extracellular enzymes of interest for biomass processing. Of the 63 glycoside hydrolases predicted to be capable of hydrolyzing cellulose, hemicellulose or pectin, 94% of the exo-acting enzymes and only 18% of the endo-acting enzymes were experimentally detected.
Identifying Pathogenicity Islands in Bacterial Pathogenomics Using Computational Approaches
Directory of Open Access Journals (Sweden)
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.
Fast reactor safety and computational thermo-fluid dynamics approaches
International Nuclear Information System (INIS)
Ninokata, Hisashi; Shimizu, Takeshi
1993-01-01
This article provides a brief description of the safety principle on which liquid metal cooled fast breeder reactors (LMFBRs) is based and the roles of computations in the safety practices. A number of thermohydraulics models have been developed to date that successfully describe several of the important types of fluids and materials motion encountered in the analysis of postulated accidents in LMFBRs. Most of these models use a mixture of implicit and explicit numerical solution techniques in solving a set of conservation equations formulated in Eulerian coordinates, with special techniques included to specific situations. Typical computational thermo-fluid dynamics approaches are discussed in particular areas of analyses of the physical phenomena relevant to the fuel subassembly thermohydraulics design and that involve describing the motion of molten materials in the core over a large scale. (orig.)
Benchmarking of computer codes and approaches for modeling exposure scenarios
International Nuclear Information System (INIS)
Seitz, R.R.; Rittmann, P.D.; Wood, M.I.; Cook, J.R.
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
Wireless-Uplinks-Based Energy-Efficient Scheduling in Mobile Cloud Computing
Directory of Open Access Journals (Sweden)
Xing Liu
2015-01-01
Full Text Available Mobile cloud computing (MCC combines cloud computing and mobile internet to improve the computational capabilities of resource-constrained mobile devices (MDs. In MCC, mobile users could not only improve the computational capability of MDs but also save operation consumption by offloading the mobile applications to the cloud. However, MCC faces the problem of energy efficiency because of time-varying channels when the offloading is being executed. In this paper, we address the issue of energy-efficient scheduling for wireless uplink in MCC. By introducing Lyapunov optimization, we first propose a scheduling algorithm that can dynamically choose channel to transmit data based on queue backlog and channel statistics. Then, we show that the proposed scheduling algorithm can make a tradeoff between queue backlog and energy consumption in a channel-aware MCC system. Simulation results show that the proposed scheduling algorithm can reduce the time average energy consumption for offloading compared to the existing algorithm.
Efficient and Flexible Computation of Many-Electron Wave Function Overlaps.
Plasser, Felix; Ruckenbauer, Matthias; Mai, Sebastian; Oppel, Markus; Marquetand, Philipp; González, Leticia
2016-03-08
A new algorithm for the computation of the overlap between many-electron wave functions is described. This algorithm allows for the extensive use of recurring intermediates and thus provides high computational efficiency. Because of the general formalism employed, overlaps can be computed for varying wave function types, molecular orbitals, basis sets, and molecular geometries. This paves the way for efficiently computing nonadiabatic interaction terms for dynamics simulations. In addition, other application areas can be envisaged, such as the comparison of wave functions constructed at different levels of theory. Aside from explaining the algorithm and evaluating the performance, a detailed analysis of the numerical stability of wave function overlaps is carried out, and strategies for overcoming potential severe pitfalls due to displaced atoms and truncated wave functions are presented.
Computational Approach for Studying Optical Properties of DNA Systems in Solution
DEFF Research Database (Denmark)
Nørby, Morten Steen; Svendsen, Casper Steinmann; Olsen, Jógvan Magnus Haugaard
2016-01-01
In this paper we present a study of the methodological aspects regarding calculations of optical properties for DNA systems in solution. Our computational approach will be built upon a fully polarizable QM/MM/Continuum model within a damped linear response theory framework. In this approach...... the environment is given a highly advanced description in terms of the electrostatic potential through the polarizable embedding model. Furthermore, bulk solvent effects are included in an efficient manner through a conductor-like screening model. With the aim of reducing the computational cost we develop a set...... of averaged partial charges and distributed isotropic dipole-dipole polarizabilities for DNA suitable for describing the classical region in ground-state and excited-state calculations. Calculations of the UV-spectrum of the 2-aminopurine optical probe embedded in a DNA double helical structure are presented...
Zhang, Hongqin; Tian, Xiangjun
2018-04-01
Ensemble-based data assimilation methods often use the so-called localization scheme to improve the representation of the ensemble background error covariance (Be). Extensive research has been undertaken to reduce the computational cost of these methods by using the localized ensemble samples to localize Be by means of a direct decomposition of the local correlation matrix C. However, the computational costs of the direct decomposition of the local correlation matrix C are still extremely high due to its high dimension. In this paper, we propose an efficient local correlation matrix decomposition approach based on the concept of alternating directions. This approach is intended to avoid direct decomposition of the correlation matrix. Instead, we first decompose the correlation matrix into 1-D correlation matrices in the three coordinate directions, then construct their empirical orthogonal function decomposition at low resolution. This procedure is followed by the 1-D spline interpolation process to transform the above decompositions to the high-resolution grid. Finally, an efficient correlation matrix decomposition is achieved by computing the very similar Kronecker product. We conducted a series of comparison experiments to illustrate the validity and accuracy of the proposed local correlation matrix decomposition approach. The effectiveness of the proposed correlation matrix decomposition approach and its efficient localization implementation of the nonlinear least-squares four-dimensional variational assimilation are further demonstrated by several groups of numerical experiments based on the Advanced Research Weather Research and Forecasting model.
Personalization of models with many model parameters: an efficient sensitivity analysis approach.
Donders, W P; Huberts, W; van de Vosse, F N; Delhaas, T
2015-10-01
Uncertainty quantification and global sensitivity analysis are indispensable for patient-specific applications of models that enhance diagnosis or aid decision-making. Variance-based sensitivity analysis methods, which apportion each fraction of the output uncertainty (variance) to the effects of individual input parameters or their interactions, are considered the gold standard. The variance portions are called the Sobol sensitivity indices and can be estimated by a Monte Carlo (MC) approach (e.g., Saltelli's method [1]) or by employing a metamodel (e.g., the (generalized) polynomial chaos expansion (gPCE) [2, 3]). All these methods require a large number of model evaluations when estimating the Sobol sensitivity indices for models with many parameters [4]. To reduce the computational cost, we introduce a two-step approach. In the first step, a subset of important parameters is identified for each output of interest using the screening method of Morris [5]. In the second step, a quantitative variance-based sensitivity analysis is performed using gPCE. Efficient sampling strategies are introduced to minimize the number of model runs required to obtain the sensitivity indices for models considering multiple outputs. The approach is tested using a model that was developed for predicting post-operative flows after creation of a vascular access for renal failure patients. We compare the sensitivity indices obtained with the novel two-step approach with those obtained from a reference analysis that applies Saltelli's MC method. The two-step approach was found to yield accurate estimates of the sensitivity indices at two orders of magnitude lower computational cost. Copyright © 2015 John Wiley & Sons, Ltd.
Approaching multiphase flows from the perspective of computational fluid dynamics
International Nuclear Information System (INIS)
Banas, A.O.
1992-01-01
Thermalhydraulic simulation methodologies based on subchannel and porous-medium concepts are briefly reviewed and contrasted with the general approach of Computational Fluid Dynamics (CFD). An outline of the advanced CFD methods for single-phase turbulent flows is followed by a short discussion of the unified formulation of averaged equations for turbulent and multiphase flows. Some of the recent applications of CFD at Chalk River Laboratories are discussed, and the complementary role of CFD with regard to the established thermalhydraulic methods of analysis is indicated. (author). 8 refs
International Nuclear Information System (INIS)
Woodruff, S.B.
1992-01-01
The Transient Reactor Analysis Code (TRAC), which features a two- fluid treatment of thermal-hydraulics, is designed to model transients in water reactors and related facilities. One of the major computational costs associated with TRAC and similar codes is calculating constitutive coefficients. Although the formulations for these coefficients are local the costs are flow-regime- or data-dependent; i.e., the computations needed for a given spatial node often vary widely as a function of time. Consequently, poor load balancing will degrade efficiency on either vector or data parallel architectures when the data are organized according to spatial location. Unfortunately, a general automatic solution to the load-balancing problem associated with data-dependent computations is not yet available for massively parallel architectures. This document discusses why developers algorithms, such as a neural net representation, that do not exhibit algorithms, such as a neural net representation, that do not exhibit load-balancing problems
Productive efficiency of tea industry: A stochastic frontier approach
African Journals Online (AJOL)
USER
2010-06-21
Jun 21, 2010 ... Key words: Technical efficiency, stochastic frontier, translog ... present low performance of the tea industry in Bangladesh. ... The Technical inefficiency effect .... administrative, technical, clerical, sales and purchase staff.
Efficient channel estimation in massive MIMO systems - a distributed approach
Al-Naffouri, Tareq Y.
2016-01-01
We present two efficient algorithms for distributed estimation of channels in massive MIMO systems. The two cases of 1) generic, and 2) sparse channels is considered. The algorithms estimate the impulse response for each channel observed
Evaluating efficiency of passenger railway stations: a DEA approach
Khadem Sameni, Melody; Preston, John; Khadem Sameni, Mona
2016-01-01
Stations are bottlenecks for railway transportation as they are where traffics merge and diverge. Numerous activities such as passengers boarding, alighting and interchanging, train formation and technical checks are also done at these points. The number of platforms is limited and it is vital to do all the work efficiently. For the first time in the literature, we implement a methodology based on data envelopment analysis which is benchmarked from ports and airport efficiency studies. It can...
A Modern Approach to the Efficient-Market Hypothesis
Gabriel Frahm
2013-01-01
Market efficiency at least requires the absence of weak arbitrage opportunities, but this is not sufficient to establish a situation where the market is sensitive, i.e., where it "fully reflects" or "rapidly adjusts to" some information flow including the evolution of asset prices. By contrast, No Weak Arbitrage together with market sensitivity is sufficient and necessary for a market to be informationally efficient.
Directory of Open Access Journals (Sweden)
Anna Gardeli
2017-11-01
Full Text Available Ongoing research is being conducted on appropriate course design, practices and teacher interventions for improving the efficiency of computer science and programming courses in K-12 education. The trend is towards a more constructivist problem-based learning approach. Computational thinking, which refers to formulating and solving problems in a form that can be efficiently processed by a computer, raises an important educational challenge. Our research aims to explore possible ways of enriching computer science teaching with a focus on development of computational thinking. We have prepared and evaluated a learning intervention for introducing computer programming to children between 10 and 14 years old; this involves students working in groups to program the behavior of the computer player of a well-known game. The programming process is split into two parts. First, students design a high-level version of their algorithm during an ‘unplugged’ pen & paper phase, and then they encode their solution as an executable program in a visual programming environment. Encouraging evaluation results have been achieved regarding the educational and motivational value of the proposed approach.
A hybrid model for the computationally-efficient simulation of the cerebellar granular layer
Directory of Open Access Journals (Sweden)
Anna eCattani
2016-04-01
Full Text Available The aim of the present paper is to efficiently describe the membrane potential dynamics of neural populations formed by species having a high density difference in specific brain areas. We propose a hybrid model whose main ingredients are a conductance-based model (ODE system and its continuous counterpart (PDE system obtained through a limit process in which the number of neurons confined in a bounded region of the brain tissue is sent to infinity. Specifically, in the discrete model, each cell is described by a set of time-dependent variables, whereas in the continuum model, cells are grouped into populations that are described by a set of continuous variables.Communications between populations, which translate into interactions among the discrete and the continuous models, are the essence of the hybrid model we present here. The cerebellum and cerebellum-like structures show in their granular layer a large difference in the relative density of neuronal species making them a natural testing ground for our hybrid model. By reconstructing the ensemble activity of the cerebellar granular layer network and by comparing our results to a more realistic computational network, we demonstrate that our description of the network activity, even though it is not biophysically detailed, is still capable of reproducing salient features of neural network dynamics. Our modeling approach yields a significant computational cost reduction by increasing the simulation speed at least $270$ times. The hybrid model reproduces interesting dynamics such as local microcircuit synchronization, traveling waves, center-surround and time-windowing.
Yu, Jieqing; Wu, Lixin; Hu, Qingsong; Yan, Zhigang; Zhang, Shaoliang
2017-12-01
Visibility computation is of great interest to location optimization, environmental planning, ecology, and tourism. Many algorithms have been developed for visibility computation. In this paper, we propose a novel method of visibility computation, called synthetic visual plane (SVP), to achieve better performance with respect to efficiency, accuracy, or both. The method uses a global horizon, which is a synthesis of line-of-sight information of all nearer points, to determine the visibility of a point, which makes it an accurate visibility method. We used discretization of horizon to gain a good performance in efficiency. After discretization, the accuracy and efficiency of SVP depends on the scale of discretization (i.e., zone width). The method is more accurate at smaller zone widths, but this requires a longer operating time. Users must strike a balance between accuracy and efficiency at their discretion. According to our experiments, SVP is less accurate but more efficient than R2 if the zone width is set to one grid. However, SVP becomes more accurate than R2 when the zone width is set to 1/24 grid, while it continues to perform as fast or faster than R2. Although SVP performs worse than reference plane and depth map with respect to efficiency, it is superior in accuracy to these other two algorithms.
Stochastic Computational Approach for Complex Nonlinear Ordinary Differential Equations
International Nuclear Information System (INIS)
Khan, Junaid Ali; Raja, Muhammad Asif Zahoor; Qureshi, Ijaz Mansoor
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. (general)
Microarray-based cancer prediction using soft computing approach.
Wang, Xiaosheng; Gotoh, Osamu
2009-05-26
One of the difficulties in using gene expression profiles to predict cancer is how to effectively select a few informative genes to construct accurate prediction models from thousands or ten thousands of genes. We screen highly discriminative genes and gene pairs to create simple prediction models involved in single genes or gene pairs on the basis of soft computing approach and rough set theory. Accurate cancerous prediction is obtained when we apply the simple prediction models for four cancerous gene expression datasets: CNS tumor, colon tumor, lung cancer and DLBCL. Some genes closely correlated with the pathogenesis of specific or general cancers are identified. In contrast with other models, our models are simple, effective and robust. Meanwhile, our models are interpretable for they are based on decision rules. Our results demonstrate that very simple models may perform well on cancerous molecular prediction and important gene markers of cancer can be detected if the gene selection approach is chosen reasonably.
A Dynamic Bayesian Approach to Computational Laban Shape Quality Analysis
Directory of Open Access Journals (Sweden)
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.
International Nuclear Information System (INIS)
Arnold, Alexander; Bruhns, Otto T; Reichling, Stefan; Mosler, Joern
2010-01-01
This paper is concerned with an efficient implementation suitable for the elastography inverse problem. More precisely, the novel algorithm allows us to compute the unknown stiffness distribution in soft tissue by means of the measured displacement field by considerably reducing the numerical cost compared to previous approaches. This is realized by combining and further elaborating variational mesh adaption with a clustering technique similar to those known from digital image compression. Within the variational mesh adaption, the underlying finite element discretization is only locally refined if this leads to a considerable improvement of the numerical solution. Additionally, the numerical complexity is reduced by the aforementioned clustering technique, in which the parameters describing the stiffness of the respective soft tissue are sorted according to a predefined number of intervals. By doing so, the number of unknowns associated with the elastography inverse problem can be chosen explicitly. A positive side effect of this method is the reduction of artificial noise in the data (smoothing of the solution). The performance and the rate of convergence of the resulting numerical formulation are critically analyzed by numerical examples.
Janetzke, David C.; Murthy, Durbha V.
1991-01-01
Aeroelastic analysis is multi-disciplinary and computationally expensive. Hence, it can greatly benefit from parallel processing. As part of an effort to develop an aeroelastic capability on a distributed memory transputer network, a parallel algorithm for the computation of aerodynamic influence coefficients is implemented on a network of 32 transputers. The aerodynamic influence coefficients are calculated using a 3-D unsteady aerodynamic model and a parallel discretization. Efficiencies up to 85 percent were demonstrated using 32 processors. The effect of subtask ordering, problem size, and network topology are presented. A comparison to results on a shared memory computer indicates that higher speedup is achieved on the distributed memory system.
Measuring economy-wide energy efficiency performance: A parametric frontier approach
International Nuclear Information System (INIS)
Zhou, P.; Ang, B.W.; Zhou, D.Q.
2012-01-01
This paper proposes a parametric frontier approach to estimating economy-wide energy efficiency performance from a production efficiency point of view. It uses the Shephard energy distance function to define an energy efficiency index and adopts the stochastic frontier analysis technique to estimate the index. A case study of measuring the economy-wide energy efficiency performance of a sample of OECD countries using the proposed approach is presented. It is found that the proposed parametric frontier approach has higher discriminating power in energy efficiency performance measurement compared to its nonparametric frontier counterparts.
An Efficient Semi-supervised Learning Approach to Predict SH2 Domain Mediated Interactions.
Kundu, Kousik; Backofen, Rolf
2017-01-01
Src homology 2 (SH2) domain is an important subclass of modular protein domains that plays an indispensable role in several biological processes in eukaryotes. SH2 domains specifically bind to the phosphotyrosine residue of their binding peptides to facilitate various molecular functions. For determining the subtle binding specificities of SH2 domains, it is very important to understand the intriguing mechanisms by which these domains recognize their target peptides in a complex cellular environment. There are several attempts have been made to predict SH2-peptide interactions using high-throughput data. However, these high-throughput data are often affected by a low signal to noise ratio. Furthermore, the prediction methods have several additional shortcomings, such as linearity problem, high computational complexity, etc. Thus, computational identification of SH2-peptide interactions using high-throughput data remains challenging. Here, we propose a machine learning approach based on an efficient semi-supervised learning technique for the prediction of 51 SH2 domain mediated interactions in the human proteome. In our study, we have successfully employed several strategies to tackle the major problems in computational identification of SH2-peptide interactions.
Computational intelligence approach for NOx emissions minimization in a coal-fired utility boiler
International Nuclear Information System (INIS)
Zhou Hao; Zheng Ligang; Cen Kefa
2010-01-01
The current work presented a computational intelligence approach used for minimizing NO x emissions in a 300 MW dual-furnaces coal-fired utility boiler. The fundamental idea behind this work included NO x emissions characteristics modeling and NO x emissions optimization. First, an objective function aiming at estimating NO x emissions characteristics from nineteen operating parameters of the studied boiler was represented by a support vector regression (SVR) model. Second, four levels of primary air velocities (PA) and six levels of secondary air velocities (SA) were regulated by using particle swarm optimization (PSO) so as to achieve low NO x emissions combustion. To reduce the time demanding, a more flexible stopping condition was used to improve the computational efficiency without the loss of the quality of the optimization results. The results showed that the proposed approach provided an effective way to reduce NO x emissions from 399.7 ppm to 269.3 ppm, which was much better than a genetic algorithm (GA) based method and was slightly better than an ant colony optimization (ACO) based approach reported in the earlier work. The main advantage of PSO was that the computational cost, typical of less than 25 s under a PC system, is much less than those required for ACO. This meant the proposed approach would be more applicable to online and real-time applications for NO x emissions minimization in actual power plant boilers.
Spin-neurons: A possible path to energy-efficient neuromorphic computers
Energy Technology Data Exchange (ETDEWEB)
Sharad, Mrigank; Fan, Deliang; Roy, Kaushik [School of Electrical and Computer Engineering, Purdue University, West Lafayette, Indiana 47907 (United States)
2013-12-21
Recent years have witnessed growing interest in the field of brain-inspired computing based on neural-network architectures. In order to translate the related algorithmic models into powerful, yet energy-efficient cognitive-computing hardware, computing-devices beyond CMOS may need to be explored. The suitability of such devices to this field of computing would strongly depend upon how closely their physical characteristics match with the essential computing primitives employed in such models. In this work, we discuss the rationale of applying emerging spin-torque devices for bio-inspired computing. Recent spin-torque experiments have shown the path to low-current, low-voltage, and high-speed magnetization switching in nano-scale magnetic devices. Such magneto-metallic, current-mode spin-torque switches can mimic the analog summing and “thresholding” operation of an artificial neuron with high energy-efficiency. Comparison with CMOS-based analog circuit-model of a neuron shows that “spin-neurons” (spin based circuit model of neurons) can achieve more than two orders of magnitude lower energy and beyond three orders of magnitude reduction in energy-delay product. The application of spin-neurons can therefore be an attractive option for neuromorphic computers of future.
Wang, Yuan; Chen, Zhidong; Sang, Xinzhu; Li, Hui; Zhao, Linmin
2018-03-01
Holographic displays can provide the complete optical wave field of a three-dimensional (3D) scene, including the depth perception. However, it often takes a long computation time to produce traditional computer-generated holograms (CGHs) without more complex and photorealistic rendering. The backward ray-tracing technique is able to render photorealistic high-quality images, which noticeably reduce the computation time achieved from the high-degree parallelism. Here, a high-efficiency photorealistic computer-generated hologram method is presented based on the ray-tracing technique. Rays are parallelly launched and traced under different illuminations and circumstances. Experimental results demonstrate the effectiveness of the proposed method. Compared with the traditional point cloud CGH, the computation time is decreased to 24 s to reconstruct a 3D object of 100 ×100 rays with continuous depth change.
New approaches for improving energy efficiency in the Brazilian industry
Directory of Open Access Journals (Sweden)
Paulo Henrique de Mello Santana
2016-11-01
Full Text Available The Brazilian government has been promoting energy efficiency measures for industry since the eighties but with very limited returns, as shown in this paper. The governments of some other countries dedicated much more effort and funds for this area and reached excellent results. The institutional arrangements and types of programmes adopted in these countries are briefly evaluated in the paper and provide valuable insights for several proposals put forward here to make more effective the Brazilian government actions directed to overcome market barriers and improve energy efficiency in the local industry. The proposed measures include the creation of Industrial Assessment Centres and an executive agency charged with the coordination of all energy efficiency programmes run by the Federal government. A large share of the Brazilian industry energy consumption comes from energy-intensive industrial branches. According to a recent survey, most of them have substantial energy conservation potentials. To materialize a fair amount of them, voluntary targets concerning energy efficiency gains should start to be negotiated between the Government and associations representing these industrial branches. Credit facilities and tax exemptions for energy-efficient equipment’s should be provided to stimulate the interest of the entrepreneurs and the setting-up of bolder targets.
Scaling production and improving efficiency in DEA: an interactive approach
Rödder, Wilhelm; Kleine, Andreas; Dellnitz, Andreas
2017-10-01
DEA models help a DMU to detect its (in-)efficiency and to improve activities, if necessary. Efficiency is only one economic aim for a decision-maker; however, up- or downsizing might be a second one. Improving efficiency is the main topic in DEA; the long-term strategy towards the right production size should attract our attention as well. Not always the management of a DMU primarily focuses on technical efficiency but rather is interested in gaining scale effects. In this paper, a formula for returns to scale (RTS) is developed, and this formula is even applicable for interior points of technology. Particularly, technical and scale inefficient DMUs need sophisticated instruments to improve their situation. Considering RTS as well as efficiency, in this paper, we give an advice for each DMU to find an economically reliable path from its actual situation to better activities and finally to most productive scale size (mpss), perhaps. For realizing this path, we propose an interactive algorithm, thus harmonizing the scientific findings and the interests of the management. Small numerical examples illustrate such paths for selected DMUs; an empirical application in theatre management completes the contribution.
Crowd Computing as a Cooperation Problem: An Evolutionary Approach
Christoforou, Evgenia; Fernández Anta, Antonio; Georgiou, Chryssis; Mosteiro, Miguel A.; Sánchez, Angel
2013-05-01
Cooperation is one of the socio-economic issues that has received more attention from the physics community. The problem has been mostly considered by studying games such as the Prisoner's Dilemma or the Public Goods Game. Here, we take a step forward by studying cooperation in the context of crowd computing. We introduce a model loosely based on Principal-agent theory in which people (workers) contribute to the solution of a distributed problem by computing answers and reporting to the problem proposer (master). To go beyond classical approaches involving the concept of Nash equilibrium, we work on an evolutionary framework in which both the master and the workers update their behavior through reinforcement learning. Using a Markov chain approach, we show theoretically that under certain----not very restrictive—conditions, the master can ensure the reliability of the answer resulting of the process. Then, we study the model by numerical simulations, finding that convergence, meaning that the system reaches a point in which it always produces reliable answers, may in general be much faster than the upper bounds given by the theoretical calculation. We also discuss the effects of the master's level of tolerance to defectors, about which the theory does not provide information. The discussion shows that the system works even with very large tolerances. We conclude with a discussion of our results and possible directions to carry this research further.
Novel computational approaches for the analysis of cosmic magnetic fields
Energy Technology Data Exchange (ETDEWEB)
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.
Low rank approach to computing first and higher order derivatives using automatic differentiation
International Nuclear Information System (INIS)
Reed, J. A.; Abdel-Khalik, H. S.; Utke, J.
2012-01-01
This manuscript outlines a new approach for increasing the efficiency of applying automatic differentiation (AD) to large scale computational models. By using the principles of the Efficient Subspace Method (ESM), low rank approximations of the derivatives for first and higher orders can be calculated using minimized computational resources. The output obtained from nuclear reactor calculations typically has a much smaller numerical rank compared to the number of inputs and outputs. This rank deficiency can be exploited to reduce the number of derivatives that need to be calculated using AD. The effective rank can be determined according to ESM by computing derivatives with AD at random inputs. Reduced or pseudo variables are then defined and new derivatives are calculated with respect to the pseudo variables. Two different AD packages are used: OpenAD and Rapsodia. OpenAD is used to determine the effective rank and the subspace that contains the derivatives. Rapsodia is then used to calculate derivatives with respect to the pseudo variables for the desired order. The overall approach is applied to two simple problems and to MATWS, a safety code for sodium cooled reactors. (authors)
Are the global REIT markets efficient by a new approach?
Directory of Open Access Journals (Sweden)
Fang Hao
2013-01-01
Full Text Available This study uses a panel KSS test by Nuri Ucar and Tolga Omay (2009, with a Fourier function based on the sequential panel selection method (SPSM procedure proposed by Georgios Chortareas and George Kapetanios (2009 to test the efficiency of REIT markets in 16 countries from 28 March 2008 to 27 June 2011. A Fourier approximation often captures the behavior of an unknown break, and testing for a unit root increases its power to do so. Moreover, SPSM can determine the mix of I(0 and I(1 series in a panel setting to clarify how many and which are random walk processes. Our empirical results demonstrate that REIT markets are efficient in all sampled countries except the UK. Our results imply that investors in countries with efficient REIT markets can adopt more passive portfolio strategies.
Implementation and efficiency of two geometric stiffening approaches
International Nuclear Information System (INIS)
Lugris, Urbano; Naya, Miguel A.; Perez, Jose A.; Cuadrado, Javier
2008-01-01
When the modeling of flexible bodies is required in multibody systems, the floating frame of reference formulations are probably the most efficient methods available. In the case of beams undergoing high speed rotations, the geometric stiffening effect can appear due to geometric nonlinearities, and it is often not captured by the aforementioned methods, since it is common to linearize the elastic forces assuming small deformations. The present work discusses the implementation of different existing methods developed to consider such geometric nonlinearities within a floating frame of reference formulation in natural coordinates, making emphasis on the relation between efficiency and accuracy of the resulting algorithms, seeking to provide practical criteria of use
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).
Directory of Open Access Journals (Sweden)
Nan-Hung Hsieh
2018-06-01
Full Text Available Traditionally, the solution to reduce parameter dimensionality in a physiologically-based pharmacokinetic (PBPK model is through expert judgment. However, this approach may lead to bias in parameter estimates and model predictions if important parameters are fixed at uncertain or inappropriate values. The purpose of this study was to explore the application of global sensitivity analysis (GSA to ascertain which parameters in the PBPK model are non-influential, and therefore can be assigned fixed values in Bayesian parameter estimation with minimal bias. We compared the elementary effect-based Morris method and three variance-based Sobol indices in their ability to distinguish “influential” parameters to be estimated and “non-influential” parameters to be fixed. We illustrated this approach using a published human PBPK model for acetaminophen (APAP and its two primary metabolites APAP-glucuronide and APAP-sulfate. We first applied GSA to the original published model, comparing Bayesian model calibration results using all the 21 originally calibrated model parameters (OMP, determined by “expert judgment”-based approach vs. the subset of original influential parameters (OIP, determined by GSA from the OMP. We then applied GSA to all the PBPK parameters, including those fixed in the published model, comparing the model calibration results using this full set of 58 model parameters (FMP vs. the full set influential parameters (FIP, determined by GSA from FMP. We also examined the impact of different cut-off points to distinguish the influential and non-influential parameters. We found that Sobol indices calculated by eFAST provided the best combination of reliability (consistency with other variance-based methods and efficiency (lowest computational cost to achieve convergence in identifying influential parameters. We identified several originally calibrated parameters that were not influential, and could be fixed to improve computational
An efficient algorithm to compute subsets of points in ℤ n
Pacheco Martínez, Ana María; Real Jurado, Pedro
2012-01-01
In this paper we show a more efficient algorithm than that in [8] to compute subsets of points non-congruent by isometries. This algorithm can be used to reconstruct the object from the digital image. Both algorithms are compared, highlighting the improvements obtained in terms of CPU time.
Efficient Computation of Transition State Resonances and Reaction Rates from a Quantum Normal Form
Schubert, Roman; Waalkens, Holger; Wiggins, Stephen
2006-01-01
A quantum version of a recent formulation of transition state theory in phase space is presented. The theory developed provides an algorithm to compute quantum reaction rates and the associated Gamov-Siegert resonances with very high accuracy. The algorithm is especially efficient for
Defect correction and multigrid for an efficient and accurate computation of airfoil flows
Koren, B.
1988-01-01
Results are presented for an efficient solution method for second-order accurate discretizations of the 2D steady Euler equations. The solution method is based on iterative defect correction. Several schemes are considered for the computation of the second-order defect. In each defect correction
A computationally efficient 3D finite-volume scheme for violent liquid–gas sloshing
CSIR Research Space (South Africa)
Oxtoby, Oliver F
2015-10-01
Full Text Available We describe a semi-implicit volume-of-fluid free-surface-modelling methodology for flow problems involving violent free-surface motion. For efficient computation, a hybrid-unstructured edge-based vertex-centred finite volume discretisation...
Novel approach for dam break flow modeling using computational intelligence
Seyedashraf, Omid; Mehrabi, Mohammad; Akhtari, Ali Akbar
2018-04-01
A new methodology based on the computational intelligence (CI) system is proposed and tested for modeling the classic 1D dam-break flow problem. The reason to seek for a new solution lies in the shortcomings of the existing analytical and numerical models. This includes the difficulty of using the exact solutions and the unwanted fluctuations, which arise in the numerical results. In this research, the application of the radial-basis-function (RBF) and multi-layer-perceptron (MLP) systems is detailed for the solution of twenty-nine dam-break scenarios. The models are developed using seven variables, i.e. the length of the channel, the depths of the up-and downstream sections, time, and distance as the inputs. Moreover, the depths and velocities of each computational node in the flow domain are considered as the model outputs. The models are validated against the analytical, and Lax-Wendroff and MacCormack FDM schemes. The findings indicate that the employed CI models are able to replicate the overall shape of the shock- and rarefaction-waves. Furthermore, the MLP system outperforms RBF and the tested numerical schemes. A new monolithic equation is proposed based on the best fitting model, which can be used as an efficient alternative to the existing piecewise analytic equations.
Alternative approaches to evaluation of cow efficiency | MacNeil ...
African Journals Online (AJOL)
Estimated breeding values based on the preceding results and using the maternal genetic effect on ADG as a proxy for the direct genetic effect on milk production were combined in six indexes of cow efficiency. These indexes sought to increase output and decrease input simultaneously, to increase output holding input ...
A direct mining approach to efficient constrained graph pattern discovery
DEFF Research Database (Denmark)
Zhu, Feida; Zhang, Zequn; Qu, Qiang
2013-01-01
Despite the wealth of research on frequent graph pattern mining, how to efficiently mine the complete set of those with constraints still poses a huge challenge to the existing algorithms mainly due to the inherent bottleneck in the mining paradigm. In essence, mining requests with explicitly-spe...
Efficient learning strategy of Chinese characters based on network approach.
Directory of Open Access Journals (Sweden)
Xiaoyong Yan
Full Text Available We develop an efficient learning strategy of Chinese characters based on the network of the hierarchical structural relations between Chinese characters. A more efficient strategy is that of learning the same number of useful Chinese characters in less effort or time. We construct a node-weighted network of Chinese characters, where character usage frequencies are used as node weights. Using this hierarchical node-weighted network, we propose a new learning method, the distributed node weight (DNW strategy, which is based on a new measure of nodes' importance that considers both the weight of the nodes and its location in the network hierarchical structure. Chinese character learning strategies, particularly their learning order, are analyzed as dynamical processes over the network. We compare the efficiency of three theoretical learning methods and two commonly used methods from mainstream Chinese textbooks, one for Chinese elementary school students and the other for students learning Chinese as a second language. We find that the DNW method significantly outperforms the others, implying that the efficiency of current learning methods of major textbooks can be greatly improved.
The Relative Efficiency of Charter Schools: A Cost Frontier Approach
Gronberg, Timothy J.; Jansen, Dennis W.; Taylor, Lori L.
2012-01-01
Charters represent an expansion of public school choice, offering free, publicly funded educational alternatives to traditional public schools. One relatively unexplored research question concerning charter schools asks whether charter schools are more efficient suppliers of educational services than are traditional public schools. The potential…
Efficient flow and human centred assembly by an interactive approach
Eikhout, S.M.; Helmes, R.B.M.; Rhijn, J.W. van
2004-01-01
Due to fluctuations on the market, manufacturing of many product variations, and wish for fine-tuning between production and assembly a fan and motor manufacturing company wanted to improve their assembly line. The aims were efficient flow and human centered assembly in the new product line.
Donders, S.; Pluymers, B.; Ragnarsson, P.; Hadjit, R.; Desmet, W.
2010-04-01
In the vehicle design process, design decisions are more and more based on virtual prototypes. Due to competitive and regulatory pressure, vehicle manufacturers are forced to improve product quality, to reduce time-to-market and to launch an increasing number of design variants on the global market. To speed up the design iteration process, substructuring and component mode synthesis (CMS) methods are commonly used, involving the analysis of substructure models and the synthesis of the substructure analysis results. Substructuring and CMS enable efficient decentralized collaboration across departments and allow to benefit from the availability of parallel computing environments. However, traditional CMS methods become prohibitively inefficient when substructures are coupled along large interfaces, i.e. with a large number of degrees of freedom (DOFs) at the interface between substructures. The reason is that the analysis of substructures involves the calculation of a number of enrichment vectors, one for each interface degree of freedom (DOF). Since large interfaces are common in vehicles (e.g. the continuous line connections to connect the body with the windshield, roof or floor), this interface bottleneck poses a clear limitation in the vehicle noise, vibration and harshness (NVH) design process. Therefore there is a need to describe the interface dynamics more efficiently. This paper presents a wave-based substructuring (WBS) approach, which allows reducing the interface representation between substructures in an assembly by expressing the interface DOFs in terms of a limited set of basis functions ("waves"). As the number of basis functions can be much lower than the number of interface DOFs, this greatly facilitates the substructure analysis procedure and results in faster design predictions. The waves are calculated once from a full nominal assembly analysis, but these nominal waves can be re-used for the assembly of modified components. The WBS approach thus
A computationally efficient OMP-based compressed sensing reconstruction for dynamic MRI
International Nuclear Information System (INIS)
Usman, M; Prieto, C; Schaeffter, T; Batchelor, P G; Odille, F; Atkinson, D
2011-01-01
Compressed sensing (CS) methods in MRI are computationally intensive. Thus, designing novel CS algorithms that can perform faster reconstructions is crucial for everyday applications. We propose a computationally efficient orthogonal matching pursuit (OMP)-based reconstruction, specifically suited to cardiac MR data. According to the energy distribution of a y-f space obtained from a sliding window reconstruction, we label the y-f space as static or dynamic. For static y-f space images, a computationally efficient masked OMP reconstruction is performed, whereas for dynamic y-f space images, standard OMP reconstruction is used. The proposed method was tested on a dynamic numerical phantom and two cardiac MR datasets. Depending on the field of view composition of the imaging data, compared to the standard OMP method, reconstruction speedup factors ranging from 1.5 to 2.5 are achieved. (note)
Labibian, Amir; Bahrami, Amir Hossein; Haghshenas, Javad
2017-09-01
This paper presents a computationally efficient algorithm for attitude estimation of remote a sensing satellite. In this study, gyro, magnetometer, sun sensor and star tracker are used in Extended Kalman Filter (EKF) structure for the purpose of Attitude Determination (AD). However, utilizing all of the measurement data simultaneously in EKF structure increases computational burden. Specifically, assuming n observation vectors, an inverse of a 3n×3n matrix is required for gain calculation. In order to solve this problem, an efficient version of EKF, namely Murrell's version, is employed. This method utilizes measurements separately at each sampling time for gain computation. Therefore, an inverse of a 3n×3n matrix is replaced by an inverse of a 3×3 matrix for each measurement vector. Moreover, gyro drifts during the time can reduce the pointing accuracy. Therefore, a calibration algorithm is utilized for estimation of the main gyro parameters.
On the Computation of the Efficient Frontier of the Portfolio Selection Problem
Directory of Open Access Journals (Sweden)
Clara Calvo
2012-01-01
Full Text Available An easy-to-use procedure is presented for improving the ε-constraint method for computing the efficient frontier of the portfolio selection problem endowed with additional cardinality and semicontinuous variable constraints. The proposed method provides not only a numerical plotting of the frontier but also an analytical description of it, including the explicit equations of the arcs of parabola it comprises and the change points between them. This information is useful for performing a sensitivity analysis as well as for providing additional criteria to the investor in order to select an efficient portfolio. Computational results are provided to test the efficiency of the algorithm and to illustrate its applications. The procedure has been implemented in Mathematica.
International Nuclear Information System (INIS)
Zhang Hongkun; Cen Song; Wang Haitao; Cheng Huanyu
2012-01-01
An efficient 3D approach is proposed for simulating the complicated responses of the multi-body structure in reactor core under seismic loading. By utilizing the rigid-body and connector functions of the software Abaqus, the multi-body structure of the reactor core is simplified as a mass-point system interlinked by spring-dashpot connectors. And reasonable schemes are used for determining various connector coefficients. Furthermore, a scripting program is also complied for the 3D parametric modeling. Numerical examples show that, the proposed method can not only produce the results which satisfy the engineering requirements, but also improve the computational efficiency more than 100 times. (authors)
Efficient fault tree handling - the Asea-Atom approach
International Nuclear Information System (INIS)
Ericsson, G.; Knochenhauer, M.; Mills, R.
1985-01-01
In recent years there has been a trend in Swedish Probabilistic Safety Analysis (PSA) work towards coordination of the tools and methods used, in order to facilitate exchange of information and review. Thus, standardized methods for fault tree drawing and basic event coding have been developed as well as a number of computer codes for fault tree handling. The computer code used by Asea-Atom is called SUPER-TREE. As indicated by the name, the key feature is the concept of one super tree containing all the information necessary in the fault tree analysis, i.e. system fault trees, sequence fault trees and component data base. The code has proved to allow great flexibility in the choice of level of detail in the analysis
Fleming, P.
1985-01-01
A design technique is proposed for linear regulators in which a feedback controller of fixed structure is chosen to minimize an integral quadratic objective function subject to the satisfaction of integral quadratic constraint functions. Application of a non-linear programming algorithm to this mathematically tractable formulation results in an efficient and useful computer-aided design tool. Particular attention is paid to computational efficiency and various recommendations are made. Two design examples illustrate the flexibility of the approach and highlight the special insight afforded to the designer.
The hipster approach for improving cloud system efficiency
Nishtala, Rajiv; Carpenter, Paul Matthew; Petrucci, Vinicius; Martorell Bofill, Xavier
2017-01-01
In 2013, U.S. data centers accounted for 2.2% of the country’s total electricity consumption, a figure that is projected to increase rapidly over the next decade. Many important data center workloads in cloud computing are interactive, and they demand strict levels of quality-of-service (QoS) to meet user expectations, making it challenging to optimize power consumption along with increasing performance demands. This article introduces Hipster, a technique that combines heuristics and rein...
The Approach to an Estimation of a Local Area Network Functioning Efficiency
Directory of Open Access Journals (Sweden)
M. M. Taraskin
2010-09-01
Full Text Available In the article authors call attention to a choice of system of metrics, which permits to take a qualitative assessment of local area network functioning efficiency in condition of computer attacks.
Energy Technology Data Exchange (ETDEWEB)
Liu, Zi-Kui [Pennsylvania State University; Gleeson, Brian [University of Pittsburgh; Shang, Shunli [Pennsylvania State University; Gheno, Thomas [University of Pittsburgh; Lindwall, Greta [Pennsylvania State University; Zhou, Bi-Cheng [Pennsylvania State University; Liu, Xuan [Pennsylvania State University; Ross, Austin [Pennsylvania State University
2018-04-23
This project developed computational tools that can complement and support experimental efforts in order to enable discovery and more efficient development of Ni-base structural materials and coatings. The project goal was reached through an integrated computation-predictive and experimental-validation approach, including first-principles calculations, thermodynamic CALPHAD (CALculation of PHAse Diagram), and experimental investigations on compositions relevant to Ni-base superalloys and coatings in terms of oxide layer growth and microstructure stabilities. The developed description included composition ranges typical for coating alloys and, hence, allow for prediction of thermodynamic properties for these material systems. The calculation of phase compositions, phase fraction, and phase stabilities, which are directly related to properties such as ductility and strength, was a valuable contribution, along with the collection of computational tools that are required to meet the increasing demands for strong, ductile and environmentally-protective coatings. Specifically, a suitable thermodynamic description for the Ni-Al-Cr-Co-Si-Hf-Y system was developed for bulk alloy and coating compositions. Experiments were performed to validate and refine the thermodynamics from the CALPHAD modeling approach. Additionally, alloys produced using predictions from the current computational models were studied in terms of their oxidation performance. Finally, results obtained from experiments aided in the development of a thermodynamic modeling automation tool called ESPEI/pycalphad - for more rapid discovery and development of new materials.
MRPack: Multi-Algorithm Execution Using Compute-Intensive Approach in MapReduce
2015-01-01
Large quantities of data have been generated from multiple sources at exponential rates in the last few years. These data are generated at high velocity as real time and streaming data in variety of formats. These characteristics give rise to challenges in its modeling, computation, and processing. Hadoop MapReduce (MR) is a well known data-intensive distributed processing framework using the distributed file system (DFS) for Big Data. Current implementations of MR only support execution of a single algorithm in the entire Hadoop cluster. In this paper, we propose MapReducePack (MRPack), a variation of MR that supports execution of a set of related algorithms in a single MR job. We exploit the computational capability of a cluster by increasing the compute-intensiveness of MapReduce while maintaining its data-intensive approach. It uses the available computing resources by dynamically managing the task assignment and intermediate data. Intermediate data from multiple algorithms are managed using multi-key and skew mitigation strategies. The performance study of the proposed system shows that it is time, I/O, and memory efficient compared to the default MapReduce. The proposed approach reduces the execution time by 200% with an approximate 50% decrease in I/O cost. Complexity and qualitative results analysis shows significant performance improvement. PMID:26305223
Engineering approach to model and compute electric power markets settlements
International Nuclear Information System (INIS)
Kumar, J.; Petrov, V.
2006-01-01
Back-office accounting settlement activities are an important part of market operations in Independent System Operator (ISO) organizations. A potential way to measure ISO market design correctness is to analyze how well market price signals create incentives or penalties for creating an efficient market to achieve market design goals. Market settlement rules are an important tool for implementing price signals which are fed back to participants via the settlement activities of the ISO. ISO's are currently faced with the challenge of high volumes of data resulting from the increasing size of markets and ever-changing market designs, as well as the growing complexity of wholesale energy settlement business rules. This paper analyzed the problem and presented a practical engineering solution using an approach based on mathematical formulation and modeling of large scale calculations. The paper also presented critical comments on various differences in settlement design approaches to electrical power market design, as well as further areas of development. The paper provided a brief introduction to the wholesale energy market settlement systems and discussed problem formulation. An actual settlement implementation framework and discussion of the results and conclusions were also presented. It was concluded that a proper engineering approach to this domain can yield satisfying results by formalizing wholesale energy settlements. Significant improvements were observed in the initial preparation phase, scoping and effort estimation, implementation and testing. 5 refs., 2 figs
Whole genome sequencing: an efficient approach to ensuring food safety
Lakicevic, B.; Nastasijevic, I.; Dimitrijevic, M.
2017-09-01
Whole genome sequencing is an effective, powerful tool that can be applied to a wide range of public health and food safety applications. A major difference between WGS and the traditional typing techniques is that WGS allows all genes to be included in the analysis, instead of a well-defined subset of genes or variable intergenic regions. Also, the use of WGS can facilitate the understanding of contamination/colonization routes of foodborne pathogens within the food production environment, and can also afford efficient tracking of pathogens’ entry routes and distribution from farm-to-consumer. Tracking foodborne pathogens in the food processing-distribution-retail-consumer continuum is of the utmost importance for facilitation of outbreak investigations and rapid action in controlling/preventing foodborne outbreaks. Therefore, WGS likely will replace most of the numerous workflows used in public health laboratories to characterize foodborne pathogens into one consolidated, efficient workflow.
Generalized Hurst exponent approach to efficiency in MENA markets
Sensoy, A.
2013-10-01
We study the time-varying efficiency of 15 Middle East and North African (MENA) stock markets by generalized Hurst exponent analysis of daily data with a rolling window technique. The study covers a time period of six years from January 2007 to December 2012. The results reveal that all MENA stock markets exhibit different degrees of long-range dependence varying over time and that the Arab Spring has had a negative effect on market efficiency in the region. The least inefficient market is found to be Turkey, followed by Israel, while the most inefficient markets are Iran, Tunisia, and UAE. Turkey and Israel show characteristics of developed financial markets. Reasons and implications are discussed.
Efficient approach to simulate EM loads on massive structures in ITER machine
Energy Technology Data Exchange (ETDEWEB)
Alekseev, A. [ITER Organization, Route de Vinon sur Verdon, 13115 St. Paul-Lez-Durance (France); Andreeva, Z.; Belov, A.; Belyakov, V.; Filatov, O. [D.V. Efremov Scientific Research Institute, 196641 St. Petersburg (Russian Federation); Gribov, Yu.; Ioki, K. [ITER Organization, Route de Vinon sur Verdon, 13115 St. Paul-Lez-Durance (France); Kukhtin, V.; Labusov, A.; Lamzin, E.; Lyublin, B.; Malkov, A.; Mazul, I. [D.V. Efremov Scientific Research Institute, 196641 St. Petersburg (Russian Federation); Rozov, V.; Sugihara, M. [ITER Organization, Route de Vinon sur Verdon, 13115 St. Paul-Lez-Durance (France); Sychevsky, S., E-mail: sytch@sintez.niiefa.spb.su [D.V. Efremov Scientific Research Institute, 196641 St. Petersburg (Russian Federation)
2013-10-15
Highlights: ► A modelling technique to predict EM loads in ITER conducting structures is presented. ► The technique provides low computational cost and parallel computations. ► Detailed models were built for the system “vacuum vessel, cryostat, thermal shields”. ► EM loads on massive in-vessel structures were simulated with the use of local models. ► A flexible combination of models enables desired accuracy of load distributions. -- Abstract: Operation of the ITER machine is associated with high electromagnetic (EM) loads. An essential contributor to EM loads is eddy currents induced in passive conductive structures. Reasoning from the ITER construction, a modelling technique has been developed and applied in computations to efficiently predict anticipated loads. The technique allows us to avoid building a global 3D finite-element (FE) model that requires meshing of the conducting structures and their vacuum environment into 3D solid elements that leads to high computational cost. The key features of the proposed technique are: (i) the use of an existing shell model for the system “vacuum vessel (VV), cryostat, and thermal shields (TS)” implementing the magnetic shell approach. A solution is obtained in terms of a single-component, in this case, vector electric potential taken within the conducting shells of the “VV + cryostat + TS” system. (ii) EM loads on in-vessel conducting structures are simulated with the use of local FE models. The local models use either the 3D solid body or shell approximations. Reasoning from the simulation efficiency, the local boundary conditions are put with respect to the total field or an external field. The use of an integral-differential formulation and special procedures ensures smooth and accurate simulated distributions of fields from current sources of any geometry. The local FE models have been developed and applied for EM analyses of a variety of the ITER components including the diagnostic systems
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…
Measuring efficiency of international crude oil markets: A multifractality approach
Niere, H. M.
2015-01-01
The three major international crude oil markets are treated as complex systems and their multifractal properties are explored. The study covers daily prices of Brent crude, OPEC reference basket and West Texas Intermediate (WTI) crude from January 2, 2003 to January 2, 2014. A multifractal detrended fluctuation analysis (MFDFA) is employed to extract the generalized Hurst exponents in each of the time series. The generalized Hurst exponent is used to measure the degree of multifractality which in turn is used to quantify the efficiency of the three international crude oil markets. To identify whether the source of multifractality is long-range correlations or broad fat-tail distributions, shuffled data and surrogated data corresponding to each of the time series are generated. Shuffled data are obtained by randomizing the order of the price returns data. This will destroy any long-range correlation of the time series. Surrogated data is produced using the Fourier-Detrended Fluctuation Analysis (F-DFA). This is done by randomizing the phases of the price returns data in Fourier space. This will normalize the distribution of the time series. The study found that for the three crude oil markets, there is a strong dependence of the generalized Hurst exponents with respect to the order of fluctuations. This shows that the daily price time series of the markets under study have signs of multifractality. Using the degree of multifractality as a measure of efficiency, the results show that WTI is the most efficient while OPEC is the least efficient market. This implies that OPEC has the highest likelihood to be manipulated among the three markets. This reflects the fact that Brent and WTI is a very competitive market hence, it has a higher level of complexity compared against OPEC, which has a large monopoly power. Comparing with shuffled data and surrogated data, the findings suggest that for all the three crude oil markets, the multifractality is mainly due to long
Efficient channel estimation in massive MIMO systems - a distributed approach
Al-Naffouri, Tareq Y.
2016-01-21
We present two efficient algorithms for distributed estimation of channels in massive MIMO systems. The two cases of 1) generic, and 2) sparse channels is considered. The algorithms estimate the impulse response for each channel observed by the antennas at the receiver (base station) in a coordinated manner by sharing minimal information among neighboring antennas. Simulations demonstrate the superior performance of the proposed methods as compared to other methods.
Tresley, Jonathan; Jose, Jean
2015-04-01
Osteoarthritis of the knee can be a debilitating and extremely painful condition. In patients who desire to postpone knee arthroplasty or in those who are not surgical candidates, percutaneous knee injection therapies have the potential to reduce pain and swelling, maintain joint mobility, and minimize disability. Published studies cite poor accuracy of intra-articular knee joint injections without imaging guidance. We present a sonographically guided posteromedial approach to intra-articular knee joint injections with 100% accuracy and no complications in a consecutive series of 67 patients undergoing subsequent computed tomographic or magnetic resonance arthrography. Although many other standard approaches are available, a posteromedial intra-articular technique is particularly useful in patients with a large body habitus and theoretically allows for simultaneous aspiration of Baker cysts with a single sterile preparation and without changing the patient's position. The posteromedial technique described in this paper is not compared or deemed superior to other standard approaches but, rather, is presented as a potentially safe and efficient alternative. © 2015 by the American Institute of Ultrasound in Medicine.
An exergy approach to efficiency evaluation of desalination
Ng, Kim Choon
2017-05-02
This paper presents an evaluation process efficiency based on the consumption of primary energy for all types of practical desalination methods available hitherto. The conventional performance ratio has, thus far, been defined with respect to the consumption of derived energy, such as the electricity or steam, which are susceptible to the conversion losses of power plants and boilers that burned the input primary fuels. As derived energies are usually expressed by the units, either kWh or Joules, these units cannot differentiate the grade of energy supplied to the processes accurately. In this paper, the specific energy consumption is revisited for the efficacy of all large-scale desalination plants. In today\\'s combined production of electricity and desalinated water, accomplished with advanced cogeneration concept, the input exergy of fuels is utilized optimally and efficiently in a temperature cascaded manner. By discerning the exergy destruction successively in the turbines and desalination processes, the relative contribution of primary energy to the processes can be accurately apportioned to the input primary energy. Although efficiency is not a law of thermodynamics, however, a common platform for expressing the figures of merit explicit to the efficacy of desalination processes can be developed meaningfully that has the thermodynamic rigor up to the ideal or thermodynamic limit of seawater desalination for all scientists and engineers to aspire to.
An exergy approach to efficiency evaluation of desalination
Ng, Kim Choon; Shahzad, Muhammad Wakil; Son, Hyuk Soo; Hamed, Osman A.
2017-05-01
This paper presents an evaluation process efficiency based on the consumption of primary energy for all types of practical desalination methods available hitherto. The conventional performance ratio has, thus far, been defined with respect to the consumption of derived energy, such as the electricity or steam, which are susceptible to the conversion losses of power plants and boilers that burned the input primary fuels. As derived energies are usually expressed by the units, either kWh or Joules, these units cannot differentiate the grade of energy supplied to the processes accurately. In this paper, the specific energy consumption is revisited for the efficacy of all large-scale desalination plants. In today's combined production of electricity and desalinated water, accomplished with advanced cogeneration concept, the input exergy of fuels is utilized optimally and efficiently in a temperature cascaded manner. By discerning the exergy destruction successively in the turbines and desalination processes, the relative contribution of primary energy to the processes can be accurately apportioned to the input primary energy. Although efficiency is not a law of thermodynamics, however, a common platform for expressing the figures of merit explicit to the efficacy of desalination processes can be developed meaningfully that has the thermodynamic rigor up to the ideal or thermodynamic limit of seawater desalination for all scientists and engineers to aspire to.
Evaluating the Management System Approach for Industrial Energy Efficiency Improvements
Directory of Open Access Journals (Sweden)
Thomas Zobel
2016-09-01
Full Text Available Voluntary environmental management systems (EMS based on the international standard ISO 14001 have become widespread globally in recent years. The purpose of this study is to assess the impact of voluntary management systems on energy efficiency in the Swedish manufacturing industry by means of objective industrial energy data derived from mandatory annual environmental reports. The study focuses on changes in energy efficiency over a period of 12 years and includes both ISO 14001-certified companies and non-certified companies. Consideration is given to energy improvement efforts in the companies before the adoption of ISO 14001. The analysis has been carried out using statistical methods for two different industrial energy parameters: electricity and fossil fuel consumption. The results indicate that ISO 14001 adoption and certification has increased energy efficiency regarding the use of fossil fuel. In contrast, no effect of the management systems has been found concerning the use of electricity. The mixed results of this study are only partly in line with the results of previous studies based on perceptions of company representatives.
A hybrid approach for efficient anomaly detection using metaheuristic methods
Directory of Open Access Journals (Sweden)
Tamer F. Ghanem
2015-07-01
Full Text Available Network intrusion detection based on anomaly detection techniques has a significant role in protecting networks and systems against harmful activities. Different metaheuristic techniques have been used for anomaly detector generation. Yet, reported literature has not studied the use of the multi-start metaheuristic method for detector generation. This paper proposes a hybrid approach for anomaly detection in large scale datasets using detectors generated based on multi-start metaheuristic method and genetic algorithms. The proposed approach has taken some inspiration of negative selection-based detector generation. The evaluation of this approach is performed using NSL-KDD dataset which is a modified version of the widely used KDD CUP 99 dataset. The results show its effectiveness in generating a suitable number of detectors with an accuracy of 96.1% compared to other competitors of machine learning algorithms.
Design of efficient and safe neural stimulators a multidisciplinary approach
van Dongen, Marijn
2016-01-01
This book discusses the design of neural stimulator systems which are used for the treatment of a wide variety of brain disorders such as Parkinson’s, depression and tinnitus. Whereas many existing books treating neural stimulation focus on one particular design aspect, such as the electrical design of the stimulator, this book uses a multidisciplinary approach: by combining the fields of neuroscience, electrophysiology and electrical engineering a thorough understanding of the complete neural stimulation chain is created (from the stimulation IC down to the neural cell). This multidisciplinary approach enables readers to gain new insights into stimulator design, while context is provided by presenting innovative design examples. Provides a single-source, multidisciplinary reference to the field of neural stimulation, bridging an important knowledge gap among the fields of bioelectricity, neuroscience, neuroengineering and microelectronics;Uses a top-down approach to understanding the neural activation proc...
Gaining Efficiency of Computational Experiments in Modeling the Flight Vehicle Movement
Directory of Open Access Journals (Sweden)
I. K. Romanova
2017-01-01
Full Text Available The paper considers one of the important aspects to gain efficiency of conducted computational experiments, namely to provide grid optimization. The problem solution will ultimately create a more perfect system, because just a multivariate simulation is a basis to apply optimization methods by the specified criteria and to identify problems in functioning of technical systems.The paper discusses a class of the moving objects, representing a body of revolution, which, for one reason or another, endures deformation of casing. Analyses using the author's techniques have shown that there are the following complex functional dependencies of aerodynamic characteristics of the studied class of deformed objects.Presents a literature review on new ways for organizing the calculations, data storage and transfer. Provides analysing the methods of forming grids, including those used in initial calculations and visualization of information. In addition to the regular grids, are offered unstructured grids, including those for dynamic spatial-temporal information. Attention is drawn to the problem of an efficient retrieval of information. The paper shows a relevant capability to run with large data volumes, including an OLAP technology, multidimensional cubes (Data Cube, and finally, an integrated Date Mining approach.Despite the huge number of successful modern approaches to the solution of problems of formation, storage and processing of multidimensional data, it should be noted that computationally these tools are quite expensive. Expenditure for using the special tools often exceeds the cost of directly conducted computational experiments as such. In this regard, it was recognized that it is unnecessary to abandon the use of traditional tools and focus on a direct increase of their efficiency. Within the framework of the applied problem under consideration such a tool was to form the optimal grids.The optimal grid was understood to be a grid in the N
Computational Diagnostic: A Novel Approach to View Medical Data.
Energy Technology Data Exchange (ETDEWEB)
Mane, K. K. (Ketan Kirtiraj); Börner, K. (Katy)
2007-01-01
A transition from traditional paper-based medical records to electronic health record is largely underway. The use of electronic records offers tremendous potential to personalize patient diagnosis and treatment. In this paper, we discuss a computational diagnostic tool that uses digital medical records to help doctors gain better insight about a patient's medical condition. The paper details different interactive features of the tool which offer potential to practice evidence-based medicine and advance patient diagnosis practices. The healthcare industry is a constantly evolving domain. Research from this domain is often translated into better understanding of different medical conditions. This new knowledge often contributes towards improved diagnosis and treatment solutions for patients. But the healthcare industry lags behind to seek immediate benefits of the new knowledge as it still adheres to the traditional paper-based approach to keep track of medical records. However recently we notice a drive that promotes a transition towards electronic health record (EHR). An EHR stores patient medical records in digital format and offers potential to replace the paper health records. Earlier attempts of an EHR replicated the paper layout on the screen, representation of medical history of a patient in a graphical time-series format, interactive visualization with 2D/3D generated images from an imaging device. But an EHR can be much more than just an 'electronic view' of the paper record or a collection of images from an imaging device. In this paper, we present an EHR called 'Computational Diagnostic Tool', that provides a novel computational approach to look at patient medical data. The developed EHR system is knowledge driven and acts as clinical decision support tool. The EHR tool provides two visual views of the medical data. Dynamic interaction with data is supported to help doctors practice evidence-based decisions and make judicious
Solvent effect on indocyanine dyes: A computational approach
International Nuclear Information System (INIS)
Bertolino, Chiara A.; Ferrari, Anna M.; Barolo, Claudia; Viscardi, Guido; Caputo, Giuseppe; Coluccia, Salvatore
2006-01-01
The solvatochromic behaviour of a series of indocyanine dyes (Dyes I-VIII) was investigated by quantum chemical calculations. The effect of the polymethine chain length and of the indolenine structure has been satisfactorily reproduced by semiempirical Pariser-Parr-Pople (PPP) calculations. The solvatochromism of 3,3,3',3'-tetramethyl-N,N'-diethylindocarbocyanine iodide (Dye I) has been deeply investigated within the ab initio time-dependent density functional theory (TD-DFT) approach. Dye I undergoes non-polar solvation and a linear correlation has been individuated between absorption shifts and refractive index. Computed absorption λ max and oscillator strengths obtained by TD-DFT are in good agreement with the experimental data
Systems approaches to computational modeling of the oral microbiome
Directory of Open Access Journals (Sweden)
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
A computational approach to mechanistic and predictive toxicology of pesticides
DEFF Research Database (Denmark)
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......, and procymidone exerted their effects mainly via interference with steroidogenesis and nuclear receptors. Prochloraz was associated to a large number of human diseases, and together with tebuconazole showed several significant associations to Testicular Dysgenesis Syndrome. Mancozeb showed a differential mode...
Vehicular traffic noise prediction using soft computing approach.
Singh, Daljeet; Nigam, S P; Agrawal, V P; Kumar, Maneek
2016-12-01
A new approach for the development of vehicular traffic noise prediction models is presented. Four different soft computing methods, namely, Generalized Linear Model, Decision Trees, Random Forests and Neural Networks, have been used to develop models to predict the hourly equivalent continuous sound pressure level, Leq, at different locations in the Patiala city in India. The input variables include the traffic volume per hour, percentage of heavy vehicles and average speed of vehicles. The performance of the four models is compared on the basis of performance criteria of coefficient of determination, mean square error and accuracy. 10-fold cross validation is done to check the stability of the Random Forest model, which gave the best results. A t-test is performed to check the fit of the model with the field data. Copyright © 2016 Elsevier Ltd. All rights reserved.
Computer-aided modeling framework for efficient model development, analysis and identification
DEFF Research Database (Denmark)
Heitzig, Martina; Sin, Gürkan; Sales Cruz, Mauricio
2011-01-01
Model-based computer aided product-process engineering has attained increased importance in a number of industries, including pharmaceuticals, petrochemicals, fine chemicals, polymers, biotechnology, food, energy, and water. This trend is set to continue due to the substantial benefits computer-aided...... methods introduce. The key prerequisite of computer-aided product-process engineering is however the availability of models of different types, forms, and application modes. The development of the models required for the systems under investigation tends to be a challenging and time-consuming task....... The methodology has been implemented into a computer-aided modeling framework, which combines expert skills, tools, and database connections that are required for the different steps of the model development work-flow with the goal to increase the efficiency of the modeling process. The framework has two main...
Dias, Weeratilake
1998-01-01
Efficient operation of agricultural credit markets is very important both for the producer as well as for the policy makers. DEA approach is used to calculate productivity analysis which allows decomposition of sources of productivity changes into efficiency and technical change. Measured efficiencies are comparable to most recent parametric studies.
Matrix approach to consistency of the additive efficient normalization of semivalues
Xu, G.; Driessen, Theo; Sun, H.; Sun, H.
2007-01-01
In fact the Shapley value is the unique efficient semivalue. This motivated Ruiz et al. to do additive efficient normalization for semivalues. In this paper, by matrix approach we derive the relationship between the additive efficient normalization of semivalues and the Shapley value. Based on the
An Organic Computing Approach to Self-organising Robot Ensembles
Directory of Open Access Journals (Sweden)
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.
Liu, Chen; Han, Runze; Zhou, Zheng; Huang, Peng; Liu, Lifeng; Liu, Xiaoyan; Kang, Jinfeng
2018-04-01
In this work we present a novel convolution computing architecture based on metal oxide resistive random access memory (RRAM) to process the image data stored in the RRAM arrays. The proposed image storage architecture shows performances of better speed-device consumption efficiency compared with the previous kernel storage architecture. Further we improve the architecture for a high accuracy and low power computing by utilizing the binary storage and the series resistor. For a 28 × 28 image and 10 kernels with a size of 3 × 3, compared with the previous kernel storage approach, the newly proposed architecture shows excellent performances including: 1) almost 100% accuracy within 20% LRS variation and 90% HRS variation; 2) more than 67 times speed boost; 3) 71.4% energy saving.
A computational approach to climate science education with CLIMLAB
Rose, B. E. J.
2017-12-01
CLIMLAB is a Python-based software toolkit for interactive, process-oriented climate modeling for use in education and research. It is motivated by the need for simpler tools and more reproducible workflows with which to "fill in the gaps" between blackboard-level theory and the results of comprehensive climate models. With CLIMLAB you can interactively mix and match physical model components, or combine simpler process models together into a more comprehensive model. I use CLIMLAB in the classroom to put models in the hands of students (undergraduate and graduate), and emphasize a hierarchical, process-oriented approach to understanding the key emergent properties of the climate system. CLIMLAB is equally a tool for climate research, where the same needs exist for more robust, process-based understanding and reproducible computational results. I will give an overview of CLIMLAB and an update on recent developments, including: a full-featured, well-documented, interactive implementation of a widely-used radiation model (RRTM) packaging with conda-forge for compiler-free (and hassle-free!) installation on Mac, Windows and Linux interfacing with xarray for i/o and graphics with gridded model data a rich and growing collection of examples and self-computing lecture notes in Jupyter notebook format
Heidari, A. A.; Moayedi, A.; Abbaspour, R. Ali
2017-09-01
Automated fare collection (AFC) systems are regarded as valuable resources for public transport planners. In this paper, the AFC data are utilized to analysis and extract mobility patterns in a public transportation system. For this purpose, the smart card data are inserted into a proposed metaheuristic-based aggregation model and then converted to O-D matrix between stops, since the size of O-D matrices makes it difficult to reproduce the measured passenger flows precisely. The proposed strategy is applied to a case study from Haaglanden, Netherlands. In this research, moth-flame optimizer (MFO) is utilized and evaluated for the first time as a new metaheuristic algorithm (MA) in estimating transit origin-destination matrices. The MFO is a novel, efficient swarm-based MA inspired from the celestial navigation of moth insects in nature. To investigate the capabilities of the proposed MFO-based approach, it is compared to methods that utilize the K-means algorithm, gray wolf optimization algorithm (GWO) and genetic algorithm (GA). The sum of the intra-cluster distances and computational time of operations are considered as the evaluation criteria to assess the efficacy of the optimizers. The optimality of solutions of different algorithms is measured in detail. The traveler's behavior is analyzed to achieve to a smooth and optimized transport system. The results reveal that the proposed MFO-based aggregation strategy can outperform other evaluated approaches in terms of convergence tendency and optimality of the results. The results show that it can be utilized as an efficient approach to estimating the transit O-D matrices.
Directory of Open Access Journals (Sweden)
A. A. Heidari
2017-09-01
Full Text Available Automated fare collection (AFC systems are regarded as valuable resources for public transport planners. In this paper, the AFC data are utilized to analysis and extract mobility patterns in a public transportation system. For this purpose, the smart card data are inserted into a proposed metaheuristic-based aggregation model and then converted to O-D matrix between stops, since the size of O-D matrices makes it difficult to reproduce the measured passenger flows precisely. The proposed strategy is applied to a case study from Haaglanden, Netherlands. In this research, moth-flame optimizer (MFO is utilized and evaluated for the first time as a new metaheuristic algorithm (MA in estimating transit origin-destination matrices. The MFO is a novel, efficient swarm-based MA inspired from the celestial navigation of moth insects in nature. To investigate the capabilities of the proposed MFO-based approach, it is compared to methods that utilize the K-means algorithm, gray wolf optimization algorithm (GWO and genetic algorithm (GA. The sum of the intra-cluster distances and computational time of operations are considered as the evaluation criteria to assess the efficacy of the optimizers. The optimality of solutions of different algorithms is measured in detail. The traveler's behavior is analyzed to achieve to a smooth and optimized transport system. The results reveal that the proposed MFO-based aggregation strategy can outperform other evaluated approaches in terms of convergence tendency and optimality of the results. The results show that it can be utilized as an efficient approach to estimating the transit O-D matrices.
AN EFFICIENT WEB PERSONALIZATION APPROACH TO DISCOVER USER INTERESTED DIRECTORIES
Directory of Open Access Journals (Sweden)
M. Robinson Joel
2014-04-01
Full Text Available Web Usage Mining is the application of data mining technique used to retrieve the web usage from web proxy log file. Web Usage Mining consists of three major stages: preprocessing, clustering and pattern analysis. This paper explains each of these stages in detail. In this proposed approach, the web directories are discovered based on the user’s interestingness. The web proxy log file undergoes a preprocessing phase to improve the quality of data. Fuzzy Clustering Algorithm is used to cluster the user and session into disjoint clusters. In this paper, an effective approach is presented for Web personalization based on an Advanced Apriori algorithm. It is used to select the user interested web directories. The proposed method is compared with the existing web personalization methods like Objective Probabilistic Directory Miner (OPDM, Objective Community Directory Miner (OCDM and Objective Clustering and Probabilistic Directory Miner (OCPDM. The result shows that the proposed approach provides better results than the aforementioned existing approaches. At last, an application is developed with the user interested directories and web usage details.
Energy Efficiency of ORM Approaches: an Empirical Evaluation
Procaccianti, G.; Lago, P.; Diesveld, W.
2016-01-01
Context. Object-Relational Mapping (ORM) frameworks are widely used in business software applications to interact with database systems. Even if ORMs introduce several benefits when compared to a plain SQL approach, these techniques have known disadvantages. Goal. In this paper, we present an
Li, X Y; Yang, G W; Zheng, D S; Guo, W S; Hung, W N N
2015-04-28
Genetic regulatory networks are the key to understanding biochemical systems. One condition of the genetic regulatory network under different living environments can be modeled as a synchronous Boolean network. The attractors of these Boolean networks will help biologists to identify determinant and stable factors. Existing methods identify attractors based on a random initial state or the entire state simultaneously. They cannot identify the fixed length attractors directly. The complexity of including time increases exponentially with respect to the attractor number and length of attractors. This study used the bounded model checking to quickly locate fixed length attractors. Based on the SAT solver, we propose a new algorithm for efficiently computing the fixed length attractors, which is more suitable for large Boolean networks and numerous attractors' networks. After comparison using the tool BooleNet, empirical experiments involving biochemical systems demonstrated the feasibility and efficiency of our approach.
A zero-dimensional approach to compute real radicals
Directory of Open Access Journals (Sweden)
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.
Efficient scatter model for simulation of ultrasound images from computed tomography data
D'Amato, J. P.; Lo Vercio, L.; Rubi, P.; Fernandez Vera, E.; Barbuzza, R.; Del Fresno, M.; Larrabide, I.
2015-12-01
Background and motivation: Real-time ultrasound simulation refers to the process of computationally creating fully synthetic ultrasound images instantly. Due to the high value of specialized low cost training for healthcare professionals, there is a growing interest in the use of this technology and the development of high fidelity systems that simulate the acquisitions of echographic images. The objective is to create an efficient and reproducible simulator that can run either on notebooks or desktops using low cost devices. Materials and methods: We present an interactive ultrasound simulator based on CT data. This simulator is based on ray-casting and provides real-time interaction capabilities. The simulation of scattering that is coherent with the transducer position in real time is also introduced. Such noise is produced using a simplified model of multiplicative noise and convolution with point spread functions (PSF) tailored for this purpose. Results: The computational efficiency of scattering maps generation was revised with an improved performance. This allowed a more efficient simulation of coherent scattering in the synthetic echographic images while providing highly realistic result. We describe some quality and performance metrics to validate these results, where a performance of up to 55fps was achieved. Conclusion: The proposed technique for real-time scattering modeling provides realistic yet computationally efficient scatter distributions. The error between the original image and the simulated scattering image was compared for the proposed method and the state-of-the-art, showing negligible differences in its distribution.
Tailor-made Design of Chemical Blends using Decomposition-based Computer-aided Approach
DEFF Research Database (Denmark)
Yunus, Nor Alafiza; Manan, Zainuddin Abd.; Gernaey, Krist
(properties). In this way, first the systematic computer-aided technique establishes the search space, and then narrows it down in subsequent steps until a small number of feasible and promising candidates remain and then experimental work may be conducted to verify if any or all the candidates satisfy......Computer aided technique is an efficient approach to solve chemical product design problems such as design of blended liquid products (chemical blending). In chemical blending, one tries to find the best candidate, which satisfies the product targets defined in terms of desired product attributes...... is decomposed into two stages. The first stage investigates the mixture stability where all unstable mixtures are eliminated and the stable blend candidates are retained for further testing. In the second stage, the blend candidates have to satisfy a set of target properties that are ranked according...
An approach to efficient mobility management in intelligent networks
Murthy, K. M. S.
1995-01-01
Providing personal communication systems supporting full mobility require intelligent networks for tracking mobile users and facilitating outgoing and incoming calls over different physical and network environments. In realizing the intelligent network functionalities, databases play a major role. Currently proposed network architectures envision using the SS7-based signaling network for linking these DB's and also for interconnecting DB's with switches. If the network has to support ubiquitous, seamless mobile services, then it has to support additionally mobile application parts, viz., mobile origination calls, mobile destination calls, mobile location updates and inter-switch handovers. These functions will generate significant amount of data and require them to be transferred between databases (HLR, VLR) and switches (MSC's) very efficiently. In the future, the users (fixed or mobile) may use and communicate with sophisticated CPE's (e.g. multimedia, multipoint and multisession calls) which may require complex signaling functions. This will generate volumness service handling data and require efficient transfer of these message between databases and switches. Consequently, the network providers would be able to add new services and capabilities to their networks incrementally, quickly and cost-effectively.
Buildings Energy Efficiency: Interventions Analysis under a Smart Cities Approach
Directory of Open Access Journals (Sweden)
Gabriele Battista
2014-07-01
Full Text Available Most of the world’s population lives in urban areas and in inefficient buildings under the energy point of view. Starting from these assumptions, there is the need to identify methodologies and innovations able to improve social development and the quality of life of people living in cities. Smart cities can be a viable solution. The methodology traditionally adopted to evaluate building energy efficiency starts from the structure’s energy demands analysis and the demands reduction evaluation. Consequently, the energy savings is assessed through a cascade of interventions. Regarding the building envelope, the first intervention is usually related to the reduction of the thermal transmittance value, but there is also the need to emphasize the building energy savings through other parameters, such as the solar gain factor and dye solar absorbance coefficients. In this contribution, a standard building has been modeled by means of the well-known dynamic software, TRNSYS. This study shows a parametrical analysis through which it is possible to evaluate the effect of each single intervention and, consequently, its influence on the building energy demand. Through this analysis, an intervention chart has been carried out, aiming to assess the intervention efficiency starting from the percentage variation of energy demands.
Computer-Aided Approaches for Targeting HIVgp41
Directory of Open Access Journals (Sweden)
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.
Computed tomography of the lung. A pattern approach. 2. ed.
International Nuclear Information System (INIS)
Verschakelen, Johny A.; Wever, Walter de
2018-01-01
Computed Tomography of the Lung: A Pattern Approach aims to enable the reader to recognize and understand the CT signs of lung diseases and diseases with pulmonary involvement as a sound basis for diagnosis. After an introductory chapter, basic anatomy and its relevance to the interpretation of CT appearances is discussed. Advice is then provided on how to approach a CT scan of the lungs, and the different distribution and appearance patterns of disease are described. Subsequent chapters focus on the nature of these patterns, identify which diseases give rise to them, and explain how to differentiate between the diseases. The concluding chapter presents a large number of typical and less typical cases that will help the reader to practice application of the knowledge gained from the earlier chapters. Since the first edition, the book has been adapted and updated, with the inclusion of many new figures and case studies. It will be an invaluable asset both for radiologists and pulmonologists in training and for more experienced specialists wishing to update their knowledge.
Optical computing - an alternate approach to trigger processing
International Nuclear Information System (INIS)
Cleland, W.E.
1981-01-01
The enormous rate reduction factors required by most ISABELLE experiments suggest that we should examine every conceivable approach to trigger processing. One approach that has not received much attention by high energy physicists is optical data processing. The past few years have seen rapid advances in optoelectronic technology, stimulated mainly by the military and the communications industry. An intriguing question is whether one can utilize this technology together with the optical computing techniques that have been developed over the past two decades to develop a rapid trigger processor for high energy physics experiments. Optical data processing is a method for performing a few very specialized operations on data which is inherently two dimensional. Typical operations are the formation of convolution or correlation integrals between the input data and information stored in the processor in the form of an optical filter. Optical processors are classed as coherent or incoherent, according to the spatial coherence of the input wavefront. Typically, in a coherent processor a laser beam is modulated with a photographic transparency which represents the input data. In an incoherent processor, the input may be an incoherently illuminated transparency, but self-luminous objects, such as an oscilloscope trace, have also been used. We consider here an incoherent processor in which the input data is converted into an optical wavefront through the excitation of an array of point sources - either light emitting diodes or injection lasers
COMPUTER APPROACHES TO WHEAT HIGH-THROUGHPUT PHENOTYPING
Directory of Open Access Journals (Sweden)
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.
TOBACCO SMOKING AND LUNG DISEASES: EFFICIENCY OF TREATMENT APPROACHES
Directory of Open Access Journals (Sweden)
V. A. Nikitin
2016-01-01
Full Text Available The review presents data on the significant increase of tobacco smoking prevalence and its harmful effect on the development and course of chronic respiratory diseases: tuberculosis, pneumonia, lung cancer, chronic obstructive pulmonary disease and asthma. Negative consequences of tobacco smoking are caused by chronic intoxication of the host by the components of tobacco smoke providing impact on various organs and cells of the host, thus causing a big variety of diseases. Both active and passive smoking deteriorates their course and increase the risk of exacerbation, hinders taking control over the disease and interferes with adequate response to drugs.Current approaches to treatment of tobacco addiction have been presented. There are several ways to overcome nicotine addiction – drug therapy and the other forms of therapy. Integrated approach to tobacco smoking management allows achieving success in 30% of cases within short period of time with continuous and quality remissions.
Robust fault detection of linear systems using a computationally efficient set-membership method
DEFF Research Database (Denmark)
Tabatabaeipour, Mojtaba; Bak, Thomas
2014-01-01
In this paper, a computationally efficient set-membership method for robust fault detection of linear systems is proposed. The method computes an interval outer-approximation of the output of the system that is consistent with the model, the bounds on noise and disturbance, and the past measureme...... is trivially parallelizable. The method is demonstrated for fault detection of a hydraulic pitch actuator of a wind turbine. We show the effectiveness of the proposed method by comparing our results with two zonotope-based set-membership methods....
A New Method of Histogram Computation for Efficient Implementation of the HOG Algorithm
Directory of Open Access Journals (Sweden)
Mariana-Eugenia Ilas
2018-03-01
Full Text Available In this paper we introduce a new histogram computation method to be used within the histogram of oriented gradients (HOG algorithm. The new method replaces the arctangent with the slope computation and the classical magnitude allocation based on interpolation with a simpler algorithm. The new method allows a more efficient implementation of HOG in general, and particularly in field-programmable gate arrays (FPGAs, by considerably reducing the area (thus increasing the level of parallelism, while maintaining very close classification accuracy compared to the original algorithm. Thus, the new method is attractive for many applications, including car detection and classification.
An efficient approach to BAC based assembly of complex genomes.
Visendi, Paul; Berkman, Paul J; Hayashi, Satomi; Golicz, Agnieszka A; Bayer, Philipp E; Ruperao, Pradeep; Hurgobin, Bhavna; Montenegro, Juan; Chan, Chon-Kit Kenneth; Staňková, Helena; Batley, Jacqueline; Šimková, Hana; Doležel, Jaroslav; Edwards, David
2016-01-01
There has been an exponential growth in the number of genome sequencing projects since the introduction of next generation DNA sequencing technologies. Genome projects have increasingly involved assembly of whole genome data which produces inferior assemblies compared to traditional Sanger sequencing of genomic fragments cloned into bacterial artificial chromosomes (BACs). While whole genome shotgun sequencing using next generation sequencing (NGS) is relatively fast and inexpensive, this method is extremely challenging for highly complex genomes, where polyploidy or high repeat content confounds accurate assembly, or where a highly accurate 'gold' reference is required. Several attempts have been made to improve genome sequencing approaches by incorporating NGS methods, to variable success. We present the application of a novel BAC sequencing approach which combines indexed pools of BACs, Illumina paired read sequencing, a sequence assembler specifically designed for complex BAC assembly, and a custom bioinformatics pipeline. We demonstrate this method by sequencing and assembling BAC cloned fragments from bread wheat and sugarcane genomes. We demonstrate that our assembly approach is accurate, robust, cost effective and scalable, with applications for complete genome sequencing in large and complex genomes.
Directory of Open Access Journals (Sweden)
Jinping Sun
2017-01-01
Full Text Available The multiple hypothesis tracker (MHT is currently the preferred method for addressing data association problem in multitarget tracking (MTT application. MHT seeks the most likely global hypothesis by enumerating all possible associations over time, which is equal to calculating maximum a posteriori (MAP estimate over the report data. Despite being a well-studied method, MHT remains challenging mostly because of the computational complexity of data association. In this paper, we describe an efficient method for solving the data association problem using graphical model approaches. The proposed method uses the graph representation to model the global hypothesis formation and subsequently applies an efficient message passing algorithm to obtain the MAP solution. Specifically, the graph representation of data association problem is formulated as a maximum weight independent set problem (MWISP, which translates the best global hypothesis formation into finding the maximum weight independent set on the graph. Then, a max-product belief propagation (MPBP inference algorithm is applied to seek the most likely global hypotheses with the purpose of avoiding a brute force hypothesis enumeration procedure. The simulation results show that the proposed MPBP-MHT method can achieve better tracking performance than other algorithms in challenging tracking situations.
A Game-Theoretical Approach for Spectrum Efficiency Improvement in Cloud-RAN
Directory of Open Access Journals (Sweden)
Zhuofu Zhou
2016-01-01
Full Text Available As tremendous mobile devices access to the Internet in the future, the cells which can provide high data rate and more capacity are expected to be deployed. Specifically, in the next generation of mobile communication 5G, cloud computing is supposed to be applied to radio access network. In cloud radio access network (Cloud-RAN, the traditional base station is divided into two parts, that is, remote radio heads (RRHs and base band units (BBUs. RRHs are geographically distributed and densely deployed, so as to achieve high data rate and low latency. However, the ultradense deployment inevitably deteriorates spectrum efficiency due to the severer intercell interference among RRHs. In this paper, the downlink spectrum efficiency can be improved through the cooperative transmission based on forming the coalitions of RRHs. We formulate the problem as a coalition formation game in partition form. In the process of coalition formation, each RRH can join or leave one coalition to maximize its own individual utility while taking into account the coalition utility at the same time. Moreover, the convergence and stability of the resulting coalition structure are studied. The numeric simulation result demonstrates that the proposed approach based on coalition formation game is superior to the noncooperative method in terms of the aggregate coalition utility.
An Efficient Similarity Digests Database Lookup - A Logarithmic Divide & Conquer Approach
Directory of Open Access Journals (Sweden)
Frank Breitinger
2014-09-01
Full Text Available Investigating seized devices within digital forensics represents a challenging task due to the increasing amount of data. Common procedures utilize automated file identification, which reduces the amount of data an investigator has to examine manually. In the past years the research field of approximate matching arises to detect similar data. However, if n denotes the number of similarity digests in a database, then the lookup for a single similarity digest is of complexity of O(n. This paper presents a concept to extend existing approximate matching algorithms, which reduces the lookup complexity from O(n to O(log(n. Our proposed approach is based on the well-known divide and conquer paradigm and builds a Bloom filter-based tree data structure in order to enable an efficient lookup of similarity digests. Further, it is demonstrated that the presented technique is highly scalable operating a trade-off between storage requirements and computational efficiency. We perform a theoretical assessment based on recently published results and reasonable magnitudes of input data, and show that the complexity reduction achieved by the proposed technique yields a 220-fold acceleration of look-up costs.
a Novel Approach of Indexing and Retrieving Spatial Polygons for Efficient Spatial Region Queries
Zhao, J. H.; Wang, X. Z.; Wang, F. Y.; Shen, Z. H.; Zhou, Y. C.; Wang, Y. L.
2017-10-01
Spatial region queries are more and more widely used in web-based applications. Mechanisms to provide efficient query processing over geospatial data are essential. However, due to the massive geospatial data volume, heavy geometric computation, and high access concurrency, it is difficult to get response in real time. Spatial indexes are usually used in this situation. In this paper, based on k-d tree, we introduce a distributed KD-Tree (DKD-Tree) suitbable for polygon data, and a two-step query algorithm. The spatial index construction is recursive and iterative, and the query is an in memory process. Both the index and query methods can be processed in parallel, and are implemented based on HDFS, Spark and Redis. Experiments on a large volume of Remote Sensing images metadata have been carried out, and the advantages of our method are investigated by comparing with spatial region queries executed on PostgreSQL and PostGIS. Results show that our approach not only greatly improves the efficiency of spatial region query, but also has good scalability, Moreover, the two-step spatial range query algorithm can also save cluster resources to support a large number of concurrent queries. Therefore, this method is very useful when building large geographic information systems.
A NOVEL APPROACH OF INDEXING AND RETRIEVING SPATIAL POLYGONS FOR EFFICIENT SPATIAL REGION QUERIES
Directory of Open Access Journals (Sweden)
J. H. Zhao
2017-10-01
Full Text Available Spatial region queries are more and more widely used in web-based applications. Mechanisms to provide efficient query processing over geospatial data are essential. However, due to the massive geospatial data volume, heavy geometric computation, and high access concurrency, it is difficult to get response in real time. Spatial indexes are usually used in this situation. In this paper, based on k-d tree, we introduce a distributed KD-Tree (DKD-Tree suitbable for polygon data, and a two-step query algorithm. The spatial index construction is recursive and iterative, and the query is an in memory process. Both the index and query methods can be processed in parallel, and are implemented based on HDFS, Spark and Redis. Experiments on a large volume of Remote Sensing images metadata have been carried out, and the advantages of our method are investigated by comparing with spatial region queries executed on PostgreSQL and PostGIS. Results show that our approach not only greatly improves the efficiency of spatial region query, but also has good scalability, Moreover, the two-step spatial range query algorithm can also save cluster resources to support a large number of concurrent queries. Therefore, this method is very useful when building large geographic information systems.
An evolutionary computation approach to examine functional brain plasticity
Directory of Open Access Journals (Sweden)
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
A new approach to a high efficiency inductive store
International Nuclear Information System (INIS)
Zowarka, R.C. Jr.; Kajs, J.P.; Price, J.H.; Weldon, W.F.
1991-01-01
In the Spring of 1989, Parker Kinetic Design, Inc. (PKD) and the Center for Electromechanics at The University of Texas at Austin (CEM-UT) conducted a study to examine the basic technologies to be used in the construction and operation of a feasible and reliable electromagnetic (EM) gun system. This work was performed for Brown and Root Vickers, Ltd. (BRV) in response to a feasibility analysis requirement of the Royal Armament and Development Establishment (RARDE), Ministry of Defence (MD) of the United Kingdom. This paper summarizes that this study focused on the analysis and evaluation of the suitability and applicability of various pulsed power supply options for the performance goals of the RARDE EM gun program. The existing technologies considered included batteries, compulsators, capacitors, and homopolar generators (HPGs). Primary performance specifications for the electrical energy radius system were that it be capable of providing 12 MJ of muzzle energy; velocities between 2.0 and 3.5 km/s; and a repetitive shot rate of up to 10 shots per day, with no more than a 30-min interval between shots. In addition, the recommended system needed to be reliable, easily maintainable, and capable of routinely firing large numbers of shots. Strict adherence to the goal of designing a system based only on demonstrated technology results in power supplies that are prohibitively expensive and large. As a consequence, candidate system designs represent a modest extrapolation from demonstrated technology well within an acceptable design envelope. A new topology has been developed for a highly efficient inductive store suitable for pulsed-power applications. The new design features high L/R ratios without having to cryogenically cool the conductors. This allows for high efficiency charging of the inductor from low impedance dc sources such as batteries of HPGs
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 assessment of FFR. Average execution time went down from 196.3 ± 78.5 s for the CFD model to ∼2.4 ± 0.44 s for the machine-learning model on a workstation with 3.4-GHz Intel i7 8-core processor. Copyright © 2016 the American Physiological Society.
A Representation-Theoretic Approach to Reversible Computation with Applications
DEFF Research Database (Denmark)
Maniotis, Andreas Milton
Reversible computing is a sub-discipline of computer science that helps to understand the foundations of the interplay between physics, algebra, and logic in the context of computation. Its subjects of study are computational devices and abstract models of computation that satisfy the constraint ......, there is still no uniform and consistent theory that is general in the sense of giving a model-independent account to the field....... of information conservation. Such machine models, which are known as reversible models of computation, have been examined both from a theoretical perspective and from an engineering perspective. While a bundle of many isolated successful findings and applications concerning reversible computing exists...
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...
System supplier approach to projects and operations efficiency
Energy Technology Data Exchange (ETDEWEB)
Moe, P O [Siemens Offshore A/S (Norway)
1994-12-31
The conference paper outlines the most important elements for a new approach to project realisation that enable a cost reduction of 30-50% compared to conventional methods. The achievements are based on studies and evaluations to the Norwegian Vigdis development project. The system elements covered are the electrical and automation systems including safety and process control and all traditional phases of a project from concept design to the operational phase. The concept involves new principles for project execution where traditional borderlines and interfaces between the various participants have been redefined. Management attention has been verified as an important prerequisite for a successful implementation of this strategy. 2 figs.
Evaluation of the efficiency of computer-aided spectra search systems based on information theory
International Nuclear Information System (INIS)
Schaarschmidt, K.
1979-01-01
Application of information theory allows objective evaluation of the efficiency of computer-aided spectra search systems. For this purpose, a significant number of search processes must be analyzed. The amount of information gained by computer application is considered as the difference between the entropy of the data bank and a conditional entropy depending on the proportion of unsuccessful search processes and ballast. The influence of the following factors can be estimated: volume, structure, and quality of the spectra collection stored, efficiency of the encoding instruction and the comparing algorithm, and subjective errors involved in the encoding of spectra. The relations derived are applied to two published storage and retrieval systems for infared spectra. (Auth.)
A Power Efficient Exaflop Computer Design for Global Cloud System Resolving Climate Models.
Wehner, M. F.; Oliker, L.; Shalf, J.
2008-12-01
Exascale computers would allow routine ensemble modeling of the global climate system at the cloud system resolving scale. Power and cost requirements of traditional architecture systems are likely to delay such capability for many years. We present an alternative route to the exascale using embedded processor technology to design a system optimized for ultra high resolution climate modeling. These power efficient processors, used in consumer electronic devices such as mobile phones, portable music players, cameras, etc., can be tailored to the specific needs of scientific computing. We project that a system capable of integrating a kilometer scale climate model a thousand times faster than real time could be designed and built in a five year time scale for US$75M with a power consumption of 3MW. This is cheaper, more power efficient and sooner than any other existing technology.
An Intelligent Alternative Approach to the efficient Network Management
Directory of Open Access Journals (Sweden)
MARTÍN, A.
2012-12-01
Full Text Available Due to the increasing complexity and heterogeneity of networks and services, many efforts have been made to develop intelligent techniques for management. Network intelligent management is a key technology for operating large heterogeneous data transmission networks. This paper presents a proposal for an architecture that integrates management object specifications and the knowledge of expert systems. We present a new approach named Integrated Expert Management, for learning objects based on expert management rules and describe the design and implementation of an integrated intelligent management platform based on OSI and Internet management models. The main contributions of our approach is the integration of both expert system and managed models, so we can make use of them to construct more flexible intelligent management network. The prototype SONAP (Software for Network Assistant and Performance is accuracy-aware since it can control and manage a network. We have tested our system on real data to the fault diagnostic in a telecommunication system of a power utility. The results validate the model and show a significant improvement with respect to the number of rules and the error rate in others systems.
Analyzing the Approaches to the Interpretation of Efficiency of Activity of Enterprises
Directory of Open Access Journals (Sweden)
Gerasymov Oleksandr K.
2017-10-01
Full Text Available The article is aimed at studying, systematizing and analyzing scientific approaches to the definition of the category of «efficiency», evolution of the formation and development of scientific schools, defining of the basic and the general theories of efficiency: economic, dynamic, statistical, adaptive, and synergistic. The results of the study show that there is no uniform approach to understanding the concept of «efficiency» in the current circumstances. Efficiency presents itself as an indicator of the development of actor (phenomenon and works as an incentive for implementing entrepreneurial activity. Efficiency is the target guideline of managerial activities for leaders of enterprises who direct their activities towards substantiation, necessity, justification, and sufficiency. Prospect for further research in this area is the development of an organizational-economic mechanism for the marketing provision of enterprise, as well as a methodical approach to assessing the efficiency of the enterprise performance along with its marketing subsystem.
I/O-Efficient Computation of Water Flow Across a Terrain
DEFF Research Database (Denmark)
Arge, Lars Allan; Revsbæk, Morten; Zeh, Norbert
2010-01-01
). We present an I/O-efficient algorithm that solves this problem using O(sort(X) log (X/M) + sort(N)) I/Os, where N is the number of terrain vertices, X is the number of pits of the terrain, sort(N) is the cost of sorting N data items, and M is the size of the computer's main memory. Our algorithm...
An accurate and computationally efficient small-scale nonlinear FEA of flexible risers
Rahmati, MT; Bahai, H; Alfano, G
2016-01-01
This paper presents a highly efficient small-scale, detailed finite-element modelling method for flexible risers which can be effectively implemented in a fully-nested (FE2) multiscale analysis based on computational homogenisation. By exploiting cyclic symmetry and applying periodic boundary conditions, only a small fraction of a flexible pipe is used for a detailed nonlinear finite-element analysis at the small scale. In this model, using three-dimensional elements, all layer components are...
A comparison of efficient methods for the computation of Born gluon amplitudes
International Nuclear Information System (INIS)
Dinsdale, Michael; Ternick, Marko; Weinzierl, Stefan
2006-01-01
We compare four different methods for the numerical computation of the pure gluonic amplitudes in the Born approximation. We are in particular interested in the efficiency of the various methods as the number n of the external particles increases. In addition we investigate the numerical accuracy in critical phase space regions. The methods considered are based on (i) Berends-Giele recurrence relations, (ii) scalar diagrams, (iii) MHV vertices and (iv) BCF recursion relations
Energy Technology Data Exchange (ETDEWEB)
Mitchell, Scott A. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Ebeida, Mohamed Salah [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Romero, Vicente J. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Swiler, Laura Painton [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Rushdi, Ahmad A. [Univ. of Texas, Austin, TX (United States); Abdelkader, Ahmad [Univ. of Maryland, College Park, MD (United States)
2015-09-01
This SAND report summarizes our work on the Sandia National Laboratory LDRD project titled "Efficient Probability of Failure Calculations for QMU using Computational Geometry" which was project #165617 and proposal #13-0144. This report merely summarizes our work. Those interested in the technical details are encouraged to read the full published results, and contact the report authors for the status of the software and follow-on projects.
New III-V cell design approaches for very high efficiency
Energy Technology Data Exchange (ETDEWEB)
Lundstrom, M.S.; Melloch, M.R.; Lush, G.B.; Patkar, M.P.; Young, M.P. (Purdue Univ., Lafayette, IN (United States))
1993-04-01
This report describes to examine new solar cell desip approaches for achieving very high conversion efficiencies. The program consists of two elements. The first centers on exploring new thin-film approaches specifically designed for M-III semiconductors. Substantial efficiency gains may be possible by employing light trapping techniques to confine the incident photons, as well as the photons emitted by radiative recombination. The thin-film approach is a promising route for achieving substantial performance improvements in the already high-efficiency, single-junction, III-V cell. The second element of the research involves exploring desip approaches for achieving high conversion efficiencies without requiring extremely high-quality material. This work has applications to multiple-junction cells, for which the selection of a component cell often involves a compromise between optimum band pp and optimum material quality. It could also be a benefit manufacturing environment by making the cell's efficiency less dependent on materialquality.
Design of tailor-made chemical blend using a decomposition-based computer-aided approach
DEFF Research Database (Denmark)
Yunus, Nor Alafiza; Gernaey, Krist; Manan, Z.A.
2011-01-01
Computer aided techniques form an efficient approach to solve chemical product design problems such as the design of blended liquid products (chemical blending). In chemical blending, one tries to find the best candidate, which satisfies the product targets defined in terms of desired product...... methodology for blended liquid products that identifies a set of feasible chemical blends. The blend design problem is formulated as a Mixed Integer Nonlinear Programming (MINLP) model where the objective is to find the optimal blended gasoline or diesel product subject to types of chemicals...... and their compositions and a set of desired target properties of the blended product as design constraints. This blend design problem is solved using a decomposition approach, which eliminates infeasible and/or redundant candidates gradually through a hierarchy of (property) model based constraints. This decomposition...
Polymer density functional approach to efficient evaluation of path integrals
DEFF Research Database (Denmark)
Brukhno, Andrey; Vorontsov-Velyaminov, Pavel N.; Bohr, Henrik
2005-01-01
A polymer density functional theory (P-DFT) has been extended to the case of quantum statistics within the framework of Feynman path integrals. We start with the exact P-DFT formalism for an ideal open chain and adapt its efficient numerical solution to the case of a ring. We show that, similarly......, the path integral problem can, in principle, be solved exactly by making use of the two-particle pair correlation function (2p-PCF) for the ends of an open polymer, half of the original. This way the exact data for one-dimensional quantum harmonic oscillator are reproduced in a wide range of temperatures....... The exact solution is not, though, reachable in three dimensions (3D) because of a vast amount of storage required for 2p-PCF. In order to treat closed paths in 3D, we introduce a so-called "open ring" approximation which proves to be rather accurate in the limit of long chains. We also employ a simple self...
Efficient computational methods for electromagnetic imaging with applications to 3D magnetotellurics
Kordy, Michal Adam
The motivation for this work is the forward and inverse problem for magnetotellurics, a frequency domain electromagnetic remote-sensing geophysical method used in mineral, geothermal, and groundwater exploration. The dissertation consists of four papers. In the first paper, we prove the existence and uniqueness of a representation of any vector field in H(curl) by a vector lying in H(curl) and H(div). It allows us to represent electric or magnetic fields by another vector field, for which nodal finite element approximation may be used in the case of non-constant electromagnetic properties. With this approach, the system matrix does not become ill-posed for low-frequency. In the second paper, we consider hexahedral finite element approximation of an electric field for the magnetotelluric forward problem. The near-null space of the system matrix for low frequencies makes the numerical solution unstable in the air. We show that the proper solution may obtained by applying a correction on the null space of the curl. It is done by solving a Poisson equation using discrete Helmholtz decomposition. We parallelize the forward code on multicore workstation with large RAM. In the next paper, we use the forward code in the inversion. Regularization of the inversion is done by using the second norm of the logarithm of conductivity. The data space Gauss-Newton approach allows for significant savings in memory and computational time. We show the efficiency of the method by considering a number of synthetic inversions and we apply it to real data collected in Cascade Mountains. The last paper considers a cross-frequency interpolation of the forward response as well as the Jacobian. We consider Pade approximation through model order reduction and rational Krylov subspace. The interpolating frequencies are chosen adaptively in order to minimize the maximum error of interpolation. Two error indicator functions are compared. We prove a theorem of almost always lucky failure in the
US residential energy demand and energy efficiency: A stochastic demand frontier approach
International Nuclear Information System (INIS)
Filippini, Massimo; Hunt, Lester C.
2012-01-01
This paper estimates a US frontier residential aggregate energy demand function using panel data for 48 ‘states’ over the period 1995 to 2007 using stochastic frontier analysis (SFA). Utilizing an econometric energy demand model, the (in)efficiency of each state is modeled and it is argued that this represents a measure of the inefficient use of residential energy in each state (i.e. ‘waste energy’). This underlying efficiency for the US is therefore observed for each state as well as the relative efficiency across the states. Moreover, the analysis suggests that energy intensity is not necessarily a good indicator of energy efficiency, whereas by controlling for a range of economic and other factors, the measure of energy efficiency obtained via this approach is. This is a novel approach to model residential energy demand and efficiency and it is arguably particularly relevant given current US energy policy discussions related to energy efficiency.
Dendritic nonlinearities are tuned for efficient spike-based computations in cortical circuits.
Ujfalussy, Balázs B; Makara, Judit K; Branco, Tiago; Lengyel, Máté
2015-12-24
Cortical neurons integrate thousands of synaptic inputs in their dendrites in highly nonlinear ways. It is unknown how these dendritic nonlinearities in individual cells contribute to computations at the level of neural circuits. Here, we show that dendritic nonlinearities are critical for the efficient integration of synaptic inputs in circuits performing analog computations with spiking neurons. We developed a theory that formalizes how a neuron's dendritic nonlinearity that is optimal for integrating synaptic inputs depends on the statistics of its presynaptic activity patterns. Based on their in vivo preynaptic population statistics (firing rates, membrane potential fluctuations, and correlations due to ensemble dynamics), our theory accurately predicted the responses of two different types of cortical pyramidal cells to patterned stimulation by two-photon glutamate uncaging. These results reveal a new computational principle underlying dendritic integration in cortical neurons by suggesting a functional link between cellular and systems--level properties of cortical circuits.
Zimoń, Małgorzata; Sawko, Robert; Emerson, David; Thompson, Christopher
2017-11-01
Uncertainty quantification (UQ) is increasingly becoming an indispensable tool for assessing the reliability of computational modelling. Efficient handling of stochastic inputs, such as boundary conditions, physical properties or geometry, increases the utility of model results significantly. We discuss the application of non-intrusive generalised polynomial chaos techniques in the context of fluid engineering simulations. Deterministic and Monte Carlo integration rules are applied to a set of problems, including ordinary differential equations and the computation of aerodynamic parameters subject to random perturbations. In particular, we analyse acoustic wave propagation in a heterogeneous medium to study the effects of mesh resolution, transients, number and variability of stochastic inputs. We consider variants of multi-level Monte Carlo and perform a novel comparison of the methods with respect to numerical and parametric errors, as well as computational cost. The results provide a comprehensive view of the necessary steps in UQ analysis and demonstrate some key features of stochastic fluid flow systems.
DEFF Research Database (Denmark)
Brodal, Gerth Stølting; Fagerberg, Rolf; Mailund, Thomas
2013-01-01
), respectively, and counting how often the induced topologies in the two input trees are different. In this paper we present efficient algorithms for computing these distances. We show how to compute the triplet distance in time O(n log n) and the quartet distance in time O(d n log n), where d is the maximal......The triplet and quartet distances are distance measures to compare two rooted and two unrooted trees, respectively. The leaves of the two trees should have the same set of n labels. The distances are defined by enumerating all subsets of three labels (triplets) and four labels (quartets...... degree of any node in the two trees. Within the same time bounds, our framework also allows us to compute the parameterized triplet and quartet distances, where a parameter is introduced to weight resolved (binary) topologies against unresolved (non-binary) topologies. The previous best algorithm...
Efficient Backprojection-Based Synthetic Aperture Radar Computation with Many-Core Processors
Directory of Open Access Journals (Sweden)
Jongsoo Park
2013-01-01
Full Text Available Tackling computationally challenging problems with high efficiency often requires the combination of algorithmic innovation, advanced architecture, and thorough exploitation of parallelism. We demonstrate this synergy through synthetic aperture radar (SAR via backprojection, an image reconstruction method that can require hundreds of TFLOPS. Computation cost is significantly reduced by our new algorithm of approximate strength reduction; data movement cost is economized by software locality optimizations facilitated by advanced architecture support; parallelism is fully harnessed in various patterns and granularities. We deliver over 35 billion backprojections per second throughput per compute node on an Intel® Xeon® processor E5-2670-based cluster, equipped with Intel® Xeon Phi™ coprocessors. This corresponds to processing a 3K×3K image within a second using a single node. Our study can be extended to other settings: backprojection is applicable elsewhere including medical imaging, approximate strength reduction is a general code transformation technique, and many-core processors are emerging as a solution to energy-efficient computing.
Efficient computation of the joint sample frequency spectra for multiple populations.
Kamm, John A; Terhorst, Jonathan; Song, Yun S
2017-01-01
A wide range of studies in population genetics have employed the sample frequency spectrum (SFS), a summary statistic which describes the distribution of mutant alleles at a polymorphic site in a sample of DNA sequences and provides a highly efficient dimensional reduction of large-scale population genomic variation data. Recently, there has been much interest in analyzing the joint SFS data from multiple populations to infer parameters of complex demographic histories, including variable population sizes, population split times, migration rates, admixture proportions, and so on. SFS-based inference methods require accurate computation of the expected SFS under a given demographic model. Although much methodological progress has been made, existing methods suffer from numerical instability and high computational complexity when multiple populations are involved and the sample size is large. In this paper, we present new analytic formulas and algorithms that enable accurate, efficient computation of the expected joint SFS for thousands of individuals sampled from hundreds of populations related by a complex demographic model with arbitrary population size histories (including piecewise-exponential growth). Our results are implemented in a new software package called momi (MOran Models for Inference). Through an empirical study we demonstrate our improvements to numerical stability and computational complexity.
Energy Technology Data Exchange (ETDEWEB)
Park, Won Young; Phadke, Amol; Shah, Nihar [Environmental Energy Technologies Division, Lawrence Berkeley National Laboratory, Berkeley, CA (United States)
2013-08-15
Displays account for a significant portion of electricity consumed in personal computer (PC) use, and global PC monitor shipments are expected to continue to increase. We assess the market trends in the energy efficiency of PC monitors that are likely to occur without any additional policy intervention and estimate that PC monitor efficiency will likely improve by over 40 % by 2015 with saving potential of 4.5 TWh per year in 2015, compared to today's technology. We discuss various energy-efficiency improvement options and evaluate the cost-effectiveness of three of them, at least one of which improves efficiency by at least 20 % cost effectively beyond the ongoing market trends. We assess the potential for further improving efficiency taking into account the recent development of universal serial bus-powered liquid crystal display monitors and find that the current technology available and deployed in them has the potential to deeply and cost effectively reduce energy consumption by as much as 50 %. We provide insights for policies and programs that can be used to accelerate the adoption of efficient technologies to further capture global energy saving potential from PC monitors which we estimate to be 9.2 TWh per year in 2015.
Lashkin, S. V.; Kozelkov, A. S.; Yalozo, A. V.; Gerasimov, V. Yu.; Zelensky, D. K.
2017-12-01
This paper describes the details of the parallel implementation of the SIMPLE algorithm for numerical solution of the Navier-Stokes system of equations on arbitrary unstructured grids. The iteration schemes for the serial and parallel versions of the SIMPLE algorithm are implemented. In the description of the parallel implementation, special attention is paid to computational data exchange among processors under the condition of the grid model decomposition using fictitious cells. We discuss the specific features for the storage of distributed matrices and implementation of vector-matrix operations in parallel mode. It is shown that the proposed way of matrix storage reduces the number of interprocessor exchanges. A series of numerical experiments illustrates the effect of the multigrid SLAE solver tuning on the general efficiency of the algorithm; the tuning involves the types of the cycles used (V, W, and F), the number of iterations of a smoothing operator, and the number of cells for coarsening. Two ways (direct and indirect) of efficiency evaluation for parallelization of the numerical algorithm are demonstrated. The paper presents the results of solving some internal and external flow problems with the evaluation of parallelization efficiency by two algorithms. It is shown that the proposed parallel implementation enables efficient computations for the problems on a thousand processors. Based on the results obtained, some general recommendations are made for the optimal tuning of the multigrid solver, as well as for selecting the optimal number of cells per processor.
Ligand efficiency based approach for efficient virtual screening of compound libraries.
Ke, Yi-Yu; Coumar, Mohane Selvaraj; Shiao, Hui-Yi; Wang, Wen-Chieh; Chen, Chieh-Wen; Song, Jen-Shin; Chen, Chun-Hwa; Lin, Wen-Hsing; Wu, Szu-Huei; Hsu, John T A; Chang, Chung-Ming; Hsieh, Hsing-Pang
2014-08-18
Here we report for the first time the use of fit quality (FQ), a ligand efficiency (LE) based measure for virtual screening (VS) of compound libraries. The LE based VS protocol was used to screen an in-house database of 125,000 compounds to identify aurora kinase A inhibitors. First, 20 known aurora kinase inhibitors were docked to aurora kinase A crystal structure (PDB ID: 2W1C); and the conformations of docked ligand were used to create a pharmacophore (PH) model. The PH model was used to screen the database compounds, and rank (PH rank) them based on the predicted IC50 values. Next, LE_Scale, a weight-dependant LE function, was derived from 294 known aurora kinase inhibitors. Using the fit quality (FQ = LE/LE_Scale) score derived from the LE_Scale function, the database compounds were reranked (PH_FQ rank) and the top 151 (0.12% of database) compounds were assessed for aurora kinase A inhibition biochemically. This VS protocol led to the identification of 7 novel hits, with compound 5 showing aurora kinase A IC50 = 1.29 μM. Furthermore, testing of 5 against a panel of 31 kinase reveals that it is selective toward aurora kinase A & B, with <50% inhibition for other kinases at 10 μM concentrations and is a suitable candidate for further development. Incorporation of FQ score in the VS protocol not only helped identify a novel aurora kinase inhibitor, 5, but also increased the hit rate of the VS protocol by improving the enrichment factor (EF) for FQ based screening (EF = 828), compared to PH based screening (EF = 237) alone. The LE based VS protocol disclosed here could be applied to other targets for hit identification in an efficient manner. Copyright © 2014 Elsevier Masson SAS. All rights reserved.