A Linear Time Algorithm for the <em>k> Maximal Sums Problem
DEFF Research Database (Denmark)
Brodal, Gerth Stølting; Jørgensen, Allan Grønlund
2007-01-01
k maximal sums problem. We use this algorithm to obtain algorithms solving the two-dimensional k maximal sums problem in O(m 2·n + k) time, where the input is an m ×n matrix with m ≤ n. We generalize this algorithm to solve the d-dimensional problem in O(n 2d − 1 + k) time. The space usage of all......Finding the sub-vector with the largest sum in a sequence of n numbers is known as the maximum sum problem. Finding the k sub-vectors with the largest sums is a natural extension of this, and is known as the k maximal sums problem. In this paper we design an optimal O(n + k) time algorithm for the...... the algorithms can be reduced to O(n d − 1 + k). This leads to the first algorithm for the k maximal sums problem in one dimension using O(n + k) time and O(k) space....
International Nuclear Information System (INIS)
Kim, Dae Won
2005-01-01
Ultrasonic inspection methods are widely used for detecting flaws in materials. The signal analysis step plays a crucial part in the data interpretation process. A number of signal processing methods have been proposed to classify ultrasonic flaw signals. One of the more popular methods involves the extraction of an appropriate set of features followed by the use of a neural network for the classification of the signals in the feature spare. This paper describes an alternative approach which uses the least mean square (LMS) method and exportation maximization (EM) algorithm with the model based deconvolution which is employed for classifying nondestructive evaluation (NDE) signals from steam generator tubes in a nuclear power plant. The signals due to cracks and deposits are not significantly different. These signals must be discriminated to prevent from happening a huge disaster such as contamination of water or explosion. A model based deconvolution has been described to facilitate comparison of classification results. The method uses the space alternating generalized expectation maximiBation (SAGE) algorithm ill conjunction with the Newton-Raphson method which uses the Hessian parameter resulting in fast convergence to estimate the time of flight and the distance between the tube wall and the ultrasonic sensor. Results using these schemes for the classification of ultrasonic signals from cracks and deposits within steam generator tubes are presented and showed a reasonable performances
Energy Technology Data Exchange (ETDEWEB)
Kagie, Matthew J. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Lanterman, Aaron D. [Georgia Inst. of Technology, Atlanta, GA (United States)
2017-12-01
This paper addresses parameter estimation for an optical transient signal when the received data has been right-censored. We develop an expectation-maximization (EM) algorithm to estimate the amplitude of a Poisson intensity with a known shape in the presence of additive background counts, where the measurements are subject to saturation effects. We compare the results of our algorithm with those of an EM algorithm that is unaware of the censoring.
A New Augmentation Based Algorithm for Extracting Maximal Chordal Subgraphs.
Bhowmick, Sanjukta; Chen, Tzu-Yi; Halappanavar, Mahantesh
2015-02-01
A graph is chordal if every cycle of length greater than three contains an edge between non-adjacent vertices. Chordal graphs are of interest both theoretically, since they admit polynomial time solutions to a range of NP-hard graph problems, and practically, since they arise in many applications including sparse linear algebra, computer vision, and computational biology. A maximal chordal subgraph is a chordal subgraph that is not a proper subgraph of any other chordal subgraph. Existing algorithms for computing maximal chordal subgraphs depend on dynamically ordering the vertices, which is an inherently sequential process and therefore limits the algorithms' parallelizability. In this paper we explore techniques to develop a scalable parallel algorithm for extracting a maximal chordal subgraph. We demonstrate that an earlier attempt at developing a parallel algorithm may induce a non-optimal vertex ordering and is therefore not guaranteed to terminate with a maximal chordal subgraph. We then give a new algorithm that first computes and then repeatedly augments a spanning chordal subgraph. After proving that the algorithm terminates with a maximal chordal subgraph, we then demonstrate that this algorithm is more amenable to parallelization and that the parallel version also terminates with a maximal chordal subgraph. That said, the complexity of the new algorithm is higher than that of the previous parallel algorithm, although the earlier algorithm computes a chordal subgraph which is not guaranteed to be maximal. We experimented with our augmentation-based algorithm on both synthetic and real-world graphs. We provide scalability results and also explore the effect of different choices for the initial spanning chordal subgraph on both the running time and on the number of edges in the maximal chordal subgraph.
An application of the maximal independent set algorithm to course ...
African Journals Online (AJOL)
In this paper, we demonstrated one of the many applications of the Maximal Independent Set Algorithm in the area of course allocation. A program was developed in Pascal and used in implementing a modified version of the algorithm to assign teaching courses to available lecturers in any academic environment and it ...
Research on Adaptive Optics Image Restoration Algorithm by Improved Expectation Maximization Method
Zhang, Lijuan; Li, Dongming; Su, Wei; Yang, Jinhua; Jiang, Yutong
2014-01-01
To improve the effect of adaptive optics images’ restoration, we put forward a deconvolution algorithm improved by the EM algorithm which joints multiframe adaptive optics images based on expectation-maximization theory. Firstly, we need to make a mathematical model for the degenerate multiframe adaptive optics images. The function model is deduced for the points that spread with time based on phase error. The AO images are denoised using the image power spectral density and support constrain...
Improved Algorithms OF CELF and CELF++ for Influence Maximization
Directory of Open Access Journals (Sweden)
Jiaguo Lv
2014-06-01
Full Text Available Motivated by the wide application in some fields, such as viral marketing, sales promotion etc, influence maximization has been the most important and extensively studied problem in social network. However, the most classical KK-Greedy algorithm for influence maximization is inefficient. Two major sources of the algorithm’s inefficiency were analyzed in this paper. With the analysis of algorithms CELF and CELF++, all nodes in the influenced set of u would never bring any marginal gain when a new seed u was produced. Through this optimization strategy, a lot of redundant nodes will be removed from the candidate nodes. Basing on the strategy, two improved algorithms of Lv_CELF and Lv_CELF++ were proposed in this study. To evaluate the two algorithms, the two algorithms with their benchmark algorithms of CELF and CELF++ were conducted on some real world datasets. To estimate the algorithms, influence degree and running time were employed to measure the performance and efficiency respectively. Experimental results showed that, compared with benchmark algorithms of CELF and CELF++, matching effects and higher efficiency were achieved by the new algorithms Lv_CELF and Lv_CELF++. Solutions with the proposed optimization strategy can be useful for the decisionmaking problems under the scenarios related to the influence maximization problem.
International Nuclear Information System (INIS)
Zhang Jin; Shi Daxin; Anastasio, Mark A; Sillanpaa, Jussi; Chang Jenghwa
2005-01-01
We propose and investigate weighted expectation maximization (EM) algorithms for image reconstruction in x-ray tomography. The development of the algorithms is motivated by the respiratory-gated megavoltage tomography problem, in which the acquired asymmetric cone-beam projections are limited in number and unevenly sampled over view angle. In these cases, images reconstructed by use of the conventional EM algorithm can contain ring- and streak-like artefacts that are attributable to a combination of data inconsistencies and truncation of the projection data. By use of computer-simulated and clinical gated fan-beam megavoltage projection data, we demonstrate that the proposed weighted EM algorithms effectively mitigate such image artefacts. (note)
Hui, Z.; Cheng, P.; Ziggah, Y. Y.; Nie, Y.
2018-04-01
Filtering is a key step for most applications of airborne LiDAR point clouds. Although lots of filtering algorithms have been put forward in recent years, most of them suffer from parameters setting or thresholds adjusting, which will be time-consuming and reduce the degree of automation of the algorithm. To overcome this problem, this paper proposed a threshold-free filtering algorithm based on expectation-maximization. The proposed algorithm is developed based on an assumption that point clouds are seen as a mixture of Gaussian models. The separation of ground points and non-ground points from point clouds can be replaced as a separation of a mixed Gaussian model. Expectation-maximization (EM) is applied for realizing the separation. EM is used to calculate maximum likelihood estimates of the mixture parameters. Using the estimated parameters, the likelihoods of each point belonging to ground or object can be computed. After several iterations, point clouds can be labelled as the component with a larger likelihood. Furthermore, intensity information was also utilized to optimize the filtering results acquired using the EM method. The proposed algorithm was tested using two different datasets used in practice. Experimental results showed that the proposed method can filter non-ground points effectively. To quantitatively evaluate the proposed method, this paper adopted the dataset provided by the ISPRS for the test. The proposed algorithm can obtain a 4.48 % total error which is much lower than most of the eight classical filtering algorithms reported by the ISPRS.
An efficient community detection algorithm using greedy surprise maximization
International Nuclear Information System (INIS)
Jiang, Yawen; Jia, Caiyan; Yu, Jian
2014-01-01
Community detection is an important and crucial problem in complex network analysis. Although classical modularity function optimization approaches are widely used for identifying communities, the modularity function (Q) suffers from its resolution limit. Recently, the surprise function (S) was experimentally proved to be better than the Q function. However, up until now, there has been no algorithm available to perform searches to directly determine the maximal surprise values. In this paper, considering the superiority of the S function over the Q function, we propose an efficient community detection algorithm called AGSO (algorithm based on greedy surprise optimization) and its improved version FAGSO (fast-AGSO), which are based on greedy surprise optimization and do not suffer from the resolution limit. In addition, (F)AGSO does not need the number of communities K to be specified in advance. Tests on experimental networks show that (F)AGSO is able to detect optimal partitions in both simple and even more complex networks. Moreover, algorithms based on surprise maximization perform better than those algorithms based on modularity maximization, including Blondel–Guillaume–Lambiotte–Lefebvre (BGLL), Clauset–Newman–Moore (CNM) and the other state-of-the-art algorithms such as Infomap, order statistics local optimization method (OSLOM) and label propagation algorithm (LPA). (paper)
Development of regularized expectation maximization algorithms for fan-beam SPECT data
International Nuclear Information System (INIS)
Kim, Soo Mee; Lee, Jae Sung; Lee, Dong Soo; Lee, Soo Jin; Kim, Kyeong Min
2005-01-01
SPECT using a fan-beam collimator improves spatial resolution and sensitivity. For the reconstruction from fan-beam projections, it is necessary to implement direct fan-beam reconstruction methods without transforming the data into the parallel geometry. In this study, various fan-beam reconstruction algorithms were implemented and their performances were compared. The projector for fan-beam SPECT was implemented using a ray-tracing method. The direct reconstruction algorithms implemented for fan-beam projection data were FBP (filtered backprojection), EM (expectation maximization), OS-EM (ordered subsets EM) and MAP-EM OSL (maximum a posteriori EM using the one-step late method) with membrane and thin-plate models as priors. For comparison, the fan-beam projection data were also rebinned into the parallel data using various interpolation methods, such as the nearest neighbor, bilinear and bicubic interpolations, and reconstructed using the conventional EM algorithm for parallel data. Noiseless and noisy projection data from the digital Hoffman brain and Shepp/Logan phantoms were reconstructed using the above algorithms. The reconstructed images were compared in terms of a percent error metric. For the fan-beam data with Poisson noise, the MAP-EM OSL algorithm with the thin-plate prior showed the best result in both percent error and stability. Bilinear interpolation was the most effective method for rebinning from the fan-beam to parallel geometry when the accuracy and computation load were considered. Direct fan-beam EM reconstructions were more accurate than the standard EM reconstructions obtained from rebinned parallel data. Direct fan-beam reconstruction algorithms were implemented, which provided significantly improved reconstructions
Clustering performance comparison using K-means and expectation maximization algorithms.
Jung, Yong Gyu; Kang, Min Soo; Heo, Jun
2014-11-14
Clustering is an important means of data mining based on separating data categories by similar features. Unlike the classification algorithm, clustering belongs to the unsupervised type of algorithms. Two representatives of the clustering algorithms are the K -means and the expectation maximization (EM) algorithm. Linear regression analysis was extended to the category-type dependent variable, while logistic regression was achieved using a linear combination of independent variables. To predict the possibility of occurrence of an event, a statistical approach is used. However, the classification of all data by means of logistic regression analysis cannot guarantee the accuracy of the results. In this paper, the logistic regression analysis is applied to EM clusters and the K -means clustering method for quality assessment of red wine, and a method is proposed for ensuring the accuracy of the classification results.
Applications of expectation maximization algorithm for coherent optical communication
DEFF Research Database (Denmark)
Carvalho, L.; Oliveira, J.; Zibar, Darko
2014-01-01
In this invited paper, we present powerful statistical signal processing methods, used by machine learning community, and link them to current problems in optical communication. In particular, we will look into iterative maximum likelihood parameter estimation based on expectation maximization...... algorithm and its application in coherent optical communication systems for linear and nonlinear impairment mitigation. Furthermore, the estimated parameters are used to build the probabilistic model of the system for the synthetic impairment generation....
Zeng, Nianyin; Wang, Zidong; Li, Yurong; Du, Min; Cao, Jie; Liu, Xiaohui
2013-12-01
In this paper, the expectation maximization (EM) algorithm is applied to the modeling of the nano-gold immunochromatographic assay (nano-GICA) via available time series of the measured signal intensities of the test and control lines. The model for the nano-GICA is developed as the stochastic dynamic model that consists of a first-order autoregressive stochastic dynamic process and a noisy measurement. By using the EM algorithm, the model parameters, the actual signal intensities of the test and control lines, as well as the noise intensity can be identified simultaneously. Three different time series data sets concerning the target concentrations are employed to demonstrate the effectiveness of the introduced algorithm. Several indices are also proposed to evaluate the inferred models. It is shown that the model fits the data very well.
Energy-driven scheduling algorithm for nanosatellite energy harvesting maximization
Slongo, L. K.; Martínez, S. V.; Eiterer, B. V. B.; Pereira, T. G.; Bezerra, E. A.; Paiva, K. V.
2018-06-01
The number of tasks that a satellite may execute in orbit is strongly related to the amount of energy its Electrical Power System (EPS) is able to harvest and to store. The manner the stored energy is distributed within the satellite has also a great impact on the CubeSat's overall efficiency. Most CubeSat's EPS do not prioritize energy constraints in their formulation. Unlike that, this work proposes an innovative energy-driven scheduling algorithm based on energy harvesting maximization policy. The energy harvesting circuit is mathematically modeled and the solar panel I-V curves are presented for different temperature and irradiance levels. Considering the models and simulations, the scheduling algorithm is designed to keep solar panels working close to their maximum power point by triggering tasks in the appropriate form. Tasks execution affects battery voltage, which is coupled to the solar panels through a protection circuit. A software based Perturb and Observe strategy allows defining the tasks to be triggered. The scheduling algorithm is tested in FloripaSat, which is an 1U CubeSat. A test apparatus is proposed to emulate solar irradiance variation, considering the satellite movement around the Earth. Tests have been conducted to show that the scheduling algorithm improves the CubeSat energy harvesting capability by 4.48% in a three orbit experiment and up to 8.46% in a single orbit cycle in comparison with the CubeSat operating without the scheduling algorithm.
Weissman, Alexander
2013-01-01
Convergence of the expectation-maximization (EM) algorithm to a global optimum of the marginal log likelihood function for unconstrained latent variable models with categorical indicators is presented. The sufficient conditions under which global convergence of the EM algorithm is attainable are provided in an information-theoretic context by…
Research on Adaptive Optics Image Restoration Algorithm by Improved Expectation Maximization Method
Directory of Open Access Journals (Sweden)
Lijuan Zhang
2014-01-01
Full Text Available To improve the effect of adaptive optics images’ restoration, we put forward a deconvolution algorithm improved by the EM algorithm which joints multiframe adaptive optics images based on expectation-maximization theory. Firstly, we need to make a mathematical model for the degenerate multiframe adaptive optics images. The function model is deduced for the points that spread with time based on phase error. The AO images are denoised using the image power spectral density and support constraint. Secondly, the EM algorithm is improved by combining the AO imaging system parameters and regularization technique. A cost function for the joint-deconvolution multiframe AO images is given, and the optimization model for their parameter estimations is built. Lastly, the image-restoration experiments on both analog images and the real AO are performed to verify the recovery effect of our algorithm. The experimental results show that comparing with the Wiener-IBD or RL-IBD algorithm, our iterations decrease 14.3% and well improve the estimation accuracy. The model distinguishes the PSF of the AO images and recovers the observed target images clearly.
Application of the EM algorithm to radiographic images.
Brailean, J C; Little, D; Giger, M L; Chen, C T; Sullivan, B J
1992-01-01
The expectation maximization (EM) algorithm has received considerable attention in the area of positron emitted tomography (PET) as a restoration and reconstruction technique. In this paper, the restoration capabilities of the EM algorithm when applied to radiographic images is investigated. This application does not involve reconstruction. The performance of the EM algorithm is quantitatively evaluated using a "perceived" signal-to-noise ratio (SNR) as the image quality metric. This perceived SNR is based on statistical decision theory and includes both the observer's visual response function and a noise component internal to the eye-brain system. For a variety of processing parameters, the relative SNR (ratio of the processed SNR to the original SNR) is calculated and used as a metric to compare quantitatively the effects of the EM algorithm with two other image enhancement techniques: global contrast enhancement (windowing) and unsharp mask filtering. The results suggest that the EM algorithm's performance is superior when compared to unsharp mask filtering and global contrast enhancement for radiographic images which contain objects smaller than 4 mm.
Energy Technology Data Exchange (ETDEWEB)
Lee, Youngrok [Iowa State Univ., Ames, IA (United States)
2013-05-15
Heterogeneity exists on a data set when samples from di erent classes are merged into the data set. Finite mixture models can be used to represent a survival time distribution on heterogeneous patient group by the proportions of each class and by the survival time distribution within each class as well. The heterogeneous data set cannot be explicitly decomposed to homogeneous subgroups unless all the samples are precisely labeled by their origin classes; such impossibility of decomposition is a barrier to overcome for estimating nite mixture models. The expectation-maximization (EM) algorithm has been used to obtain maximum likelihood estimates of nite mixture models by soft-decomposition of heterogeneous samples without labels for a subset or the entire set of data. In medical surveillance databases we can find partially labeled data, that is, while not completely unlabeled there is only imprecise information about class values. In this study we propose new EM algorithms that take advantages of using such partial labels, and thus incorporate more information than traditional EM algorithms. We particularly propose four variants of the EM algorithm named EM-OCML, EM-PCML, EM-HCML and EM-CPCML, each of which assumes a specific mechanism of missing class values. We conducted a simulation study on exponential survival trees with five classes and showed that the advantages of incorporating substantial amount of partially labeled data can be highly signi cant. We also showed model selection based on AIC values fairly works to select the best proposed algorithm on each specific data set. A case study on a real-world data set of gastric cancer provided by Surveillance, Epidemiology and End Results (SEER) program showed a superiority of EM-CPCML to not only the other proposed EM algorithms but also conventional supervised, unsupervised and semi-supervised learning algorithms.
Performance evaluation of the EM algorithm applied to radiographic images
International Nuclear Information System (INIS)
Brailean, J.C.; Giger, M.L.; Chen, C.T.; Sullivan, B.J.
1990-01-01
In this paper the authors evaluate the expectation maximization (EM) algorithm, both qualitatively and quantitatively, as a technique for enhancing radiographic images. Previous studies have qualitatively shown the usefulness of the EM algorithm but have failed to quantify and compare its performance with those of other image processing techniques. Recent studies by Loo et al, Ishida et al, and Giger et al, have explained improvements in image quality quantitatively in terms of a signal-to-noise ratio (SNR) derived from signal detection theory. In this study, we take a similar approach in quantifying the effect of the EM algorithm on detection of simulated low-contrast square objects superimposed on radiographic mottle. The SNRs of the original and processed images are calculated taking into account both the human visual system response and the screen-film transfer function as well as a noise component internal to the eye-brain system. The EM algorithm was also implemented on digital screen-film images of test patterns and clinical mammograms
Regier, Michael D; Moodie, Erica E M
2016-05-01
We propose an extension of the EM algorithm that exploits the common assumption of unique parameterization, corrects for biases due to missing data and measurement error, converges for the specified model when standard implementation of the EM algorithm has a low probability of convergence, and reduces a potentially complex algorithm into a sequence of smaller, simpler, self-contained EM algorithms. We use the theory surrounding the EM algorithm to derive the theoretical results of our proposal, showing that an optimal solution over the parameter space is obtained. A simulation study is used to explore the finite sample properties of the proposed extension when there is missing data and measurement error. We observe that partitioning the EM algorithm into simpler steps may provide better bias reduction in the estimation of model parameters. The ability to breakdown a complicated problem in to a series of simpler, more accessible problems will permit a broader implementation of the EM algorithm, permit the use of software packages that now implement and/or automate the EM algorithm, and make the EM algorithm more accessible to a wider and more general audience.
EM algorithm for one-shot device testing with competing risks under exponential distribution
International Nuclear Information System (INIS)
Balakrishnan, N.; So, H.Y.; Ling, M.H.
2015-01-01
This paper provides an extension of the work of Balakrishnan and Ling [1] by introducing a competing risks model into a one-shot device testing analysis under an accelerated life test setting. An Expectation Maximization (EM) algorithm is then developed for the estimation of the model parameters. An extensive Monte Carlo simulation study is carried out to assess the performance of the EM algorithm and then compare the obtained results with the initial estimates obtained by the Inequality Constrained Least Squares (ICLS) method of estimation. Finally, we apply the EM algorithm to a clinical data, ED01, to illustrate the method of inference developed here. - Highlights: • ALT data analysis for one-shot devices with competing risks is considered. • EM algorithm is developed for the determination of the MLEs. • The estimations of lifetime under normal operating conditions are presented. • The EM algorithm improves the convergence rate
A quantitative performance evaluation of the EM algorithm applied to radiographic images
International Nuclear Information System (INIS)
Brailean, J.C.; Sullivan, B.J.; Giger, M.L.; Chen, C.T.
1991-01-01
In this paper, the authors quantitatively evaluate the performance of the Expectation Maximization (EM) algorithm as a restoration technique for radiographic images. The perceived signal-to-noise ratio (SNR), of simple radiographic patterns processed by the EM algorithm are calculated on the basis of a statistical decision theory model that includes both the observer's visual response function and a noise component internal to the eye-brain system. The relative SNR (ratio of the processed SNR to the original SNR) is calculated and used as a metric to quantitatively compare the effects of the EM algorithm to two popular image enhancement techniques: contrast enhancement (windowing) and unsharp mask filtering
On the use of successive data in the ML-EM algorithm in Positron Emission Tomography
Energy Technology Data Exchange (ETDEWEB)
Desmedt, P; Lemahieu, I [University of Ghent, ELIS Department, SInt-Pietersnieuwstraat 41, B-9000 Gent, (Belgium)
1994-12-31
The Maximum Likelihood-Expectation Maximization (ML-EM) algorithm is the most popular statistical reconstruction technique for Positron Emission Tomography (PET). The ML-EM algorithm is however also renowned for its long reconstruction times. An acceleration technique for this algorithm is studied in this paper. The proposed technique starts the ML-EM algorithm before the measurement process is completed. Since the reconstruction is initiated during the scan of the patient, the time elapsed before a reconstruction becomes available is reduced. Experiments with software phantoms indicate that the quality of the reconstructed image using successive data is comparable to the quality of the reconstruction with the normal ML-EM algorithm. (authors). 7 refs, 3 figs.
A Local Scalable Distributed Expectation Maximization Algorithm for Large Peer-to-Peer Networks
National Aeronautics and Space Administration — This paper describes a local and distributed expectation maximization algorithm for learning parameters of Gaussian mixture models (GMM) in large peer-to-peer (P2P)...
DEFF Research Database (Denmark)
Hobolth, Asger
2008-01-01
-dimensional integrals required in the EM algorithm are estimated using MCMC sampling. The MCMC sampler requires simulation of sample paths from a continuous time Markov process, conditional on the beginning and ending states and the paths of the neighboring sites. An exact path sampling algorithm is developed......The evolution of DNA sequences can be described by discrete state continuous time Markov processes on a phylogenetic tree. We consider neighbor-dependent evolutionary models where the instantaneous rate of substitution at a site depends on the states of the neighboring sites. Neighbor......-dependent substitution models are analytically intractable and must be analyzed using either approximate or simulation-based methods. We describe statistical inference of neighbor-dependent models using a Markov chain Monte Carlo expectation maximization (MCMC-EM) algorithm. In the MCMC-EM algorithm, the high...
Ning, Jing; Chen, Yong; Piao, Jin
2017-07-01
Publication bias occurs when the published research results are systematically unrepresentative of the population of studies that have been conducted, and is a potential threat to meaningful meta-analysis. The Copas selection model provides a flexible framework for correcting estimates and offers considerable insight into the publication bias. However, maximizing the observed likelihood under the Copas selection model is challenging because the observed data contain very little information on the latent variable. In this article, we study a Copas-like selection model and propose an expectation-maximization (EM) algorithm for estimation based on the full likelihood. Empirical simulation studies show that the EM algorithm and its associated inferential procedure performs well and avoids the non-convergence problem when maximizing the observed likelihood. © The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
International Nuclear Information System (INIS)
Viana, R.S.; Yoriyaz, H.; Santos, A.
2011-01-01
The Expectation-Maximization (E-M) algorithm is an iterative computational method for maximum likelihood (M-L) estimates, useful in a variety of incomplete-data problems. Due to its stochastic nature, one of the most relevant applications of E-M algorithm is the reconstruction of emission tomography images. In this paper, the statistical formulation of the E-M algorithm was applied to the in vivo spectrographic imaging of stable isotopes called Neutron Stimulated Emission Computed Tomography (NSECT). In the process of E-M algorithm iteration, the conditional probability distribution plays a very important role to achieve high quality image. This present work proposes an alternative methodology for the generation of the conditional probability distribution associated to the E-M reconstruction algorithm, using the Monte Carlo code MCNP5 and with the application of the reciprocity theorem. (author)
Energy Technology Data Exchange (ETDEWEB)
Viana, R.S.; Yoriyaz, H.; Santos, A., E-mail: rodrigossviana@gmail.com, E-mail: hyoriyaz@ipen.br, E-mail: asantos@ipen.br [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil)
2011-07-01
The Expectation-Maximization (E-M) algorithm is an iterative computational method for maximum likelihood (M-L) estimates, useful in a variety of incomplete-data problems. Due to its stochastic nature, one of the most relevant applications of E-M algorithm is the reconstruction of emission tomography images. In this paper, the statistical formulation of the E-M algorithm was applied to the in vivo spectrographic imaging of stable isotopes called Neutron Stimulated Emission Computed Tomography (NSECT). In the process of E-M algorithm iteration, the conditional probability distribution plays a very important role to achieve high quality image. This present work proposes an alternative methodology for the generation of the conditional probability distribution associated to the E-M reconstruction algorithm, using the Monte Carlo code MCNP5 and with the application of the reciprocity theorem. (author)
Wei, Chengying; Xiong, Cuilian; Liu, Huanlin
2017-12-01
Maximal multicast stream algorithm based on network coding (NC) can improve the network's throughput for wavelength-division multiplexing (WDM) networks, which however is far less than the network's maximal throughput in terms of theory. And the existing multicast stream algorithms do not give the information distribution pattern and routing in the meantime. In the paper, an improved genetic algorithm is brought forward to maximize the optical multicast throughput by NC and to determine the multicast stream distribution by hybrid chromosomes construction for multicast with single source and multiple destinations. The proposed hybrid chromosomes are constructed by the binary chromosomes and integer chromosomes, while the binary chromosomes represent optical multicast routing and the integer chromosomes indicate the multicast stream distribution. A fitness function is designed to guarantee that each destination can receive the maximum number of decoding multicast streams. The simulation results showed that the proposed method is far superior over the typical maximal multicast stream algorithms based on NC in terms of network throughput in WDM networks.
An O(n²) maximal planarization algorithm based on PQ-trees
Kant, G.
1992-01-01
In this paper we investigate the problem how to delete a number of edges from a nonplanar graph G such that the resulting graph G’ is maximal planar, i.e., such that we cannot add an edge e E G – G’ to G’ without destroying planarity. Actually, our algorithm is a corrected and more generalized
An Expectation Maximization Algorithm to Model Failure Times by Continuous-Time Markov Chains
Directory of Open Access Journals (Sweden)
Qihong Duan
2010-01-01
Full Text Available In many applications, the failure rate function may present a bathtub shape curve. In this paper, an expectation maximization algorithm is proposed to construct a suitable continuous-time Markov chain which models the failure time data by the first time reaching the absorbing state. Assume that a system is described by methods of supplementary variables, the device of stage, and so on. Given a data set, the maximum likelihood estimators of the initial distribution and the infinitesimal transition rates of the Markov chain can be obtained by our novel algorithm. Suppose that there are m transient states in the system and that there are n failure time data. The devised algorithm only needs to compute the exponential of m×m upper triangular matrices for O(nm2 times in each iteration. Finally, the algorithm is applied to two real data sets, which indicates the practicality and efficiency of our algorithm.
Improved Expectation Maximization Algorithm for Gaussian Mixed Model Using the Kernel Method
Directory of Open Access Journals (Sweden)
Mohd Izhan Mohd Yusoff
2013-01-01
Full Text Available Fraud activities have contributed to heavy losses suffered by telecommunication companies. In this paper, we attempt to use Gaussian mixed model, which is a probabilistic model normally used in speech recognition to identify fraud calls in the telecommunication industry. We look at several issues encountered when calculating the maximum likelihood estimates of the Gaussian mixed model using an Expectation Maximization algorithm. Firstly, we look at a mechanism for the determination of the initial number of Gaussian components and the choice of the initial values of the algorithm using the kernel method. We show via simulation that the technique improves the performance of the algorithm. Secondly, we developed a procedure for determining the order of the Gaussian mixed model using the log-likelihood function and the Akaike information criteria. Finally, for illustration, we apply the improved algorithm to real telecommunication data. The modified method will pave the way to introduce a comprehensive method for detecting fraud calls in future work.
A Trust Region Aggressive Space Mapping Algorithm for EM
DEFF Research Database (Denmark)
Bakr., M.; Bandler, J. W.; Biernacki, R.
1998-01-01
A robust new algorithm for electromagnetic (EM) optimization of microwave circuits is presented. The algorithm (TRASM) integrates a trust region methodology with the aggressive space mapping (ASM). The trust region ensures that each iteration results in improved alignment between the coarse....... This suggested step exploits all the available EM simulations for improving the uniqueness of parameter extraction. The new algorithm was successfully used to design a number of microwave circuits. Examples include the EM optimization of a double-folded stub filter and of a high-temperature superconducting (HTS...
Douglas, Julie A.; Sandefur, Conner I.
2008-01-01
In family-based genetic studies, it is often useful to identify a subset of unrelated individuals. When such studies are conducted in population isolates, however, most if not all individuals are often detectably related to each other. To identify a set of maximally unrelated (or equivalently, minimally related) individuals, we have implemented simulated annealing, a general-purpose algorithm for solving difficult combinatorial optimization problems. We illustrate our method on data from a ge...
Continuous Analog of Accelerated OS-EM Algorithm for Computed Tomography
Directory of Open Access Journals (Sweden)
Kiyoko Tateishi
2017-01-01
Full Text Available The maximum-likelihood expectation-maximization (ML-EM algorithm is used for an iterative image reconstruction (IIR method and performs well with respect to the inverse problem as cross-entropy minimization in computed tomography. For accelerating the convergence rate of the ML-EM, the ordered-subsets expectation-maximization (OS-EM with a power factor is effective. In this paper, we propose a continuous analog to the power-based accelerated OS-EM algorithm. The continuous-time image reconstruction (CIR system is described by nonlinear differential equations with piecewise smooth vector fields by a cyclic switching process. A numerical discretization of the differential equation by using the geometric multiplicative first-order expansion of the nonlinear vector field leads to an exact equivalent iterative formula of the power-based OS-EM. The convergence of nonnegatively constrained solutions to a globally stable equilibrium is guaranteed by the Lyapunov theorem for consistent inverse problems. We illustrate through numerical experiments that the convergence characteristics of the continuous system have the highest quality compared with that of discretization methods. We clarify how important the discretization method approximates the solution of the CIR to design a better IIR method.
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Taghipour, Sharareh; Banjevic, Dragan
2011-01-01
Trend analysis is a common statistical method used to investigate the operation and changes of a repairable system over time. This method takes historical failure data of a system or a group of similar systems and determines whether the recurrent failures exhibit an increasing or decreasing trend. Most trend analysis methods proposed in the literature assume that the failure times are known, so the failure data is statistically complete; however, in many situations, such as hidden failures, failure times are subject to censoring. In this paper we assume that the failure process of a group of similar independent repairable units follows a non-homogenous Poisson process with a power law intensity function. Moreover, the failure data are subject to left, interval and right censoring. The paper proposes using the likelihood ratio test to check for trends in the failure data. It uses the Expectation-Maximization (EM) algorithm to find the parameters, which maximize the data likelihood in the case of null and alternative hypotheses. A recursive procedure is used to solve the main technical problem of calculating the expected values in the Expectation step. The proposed method is applied to a hospital's maintenance data for trend analysis of the components of a general infusion pump.
Goldengorin, B.; Ghosh, D.
Maximization of submodular functions on a ground set is a NP-hard combinatorial optimization problem. Data correcting algorithms are among the several algorithms suggested for solving this problem exactly and approximately. From the point of view of Hasse diagrams data correcting algorithms use
An Efficient Algorithm for Maximizing Range Sum Queries in a Road Network
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Tien-Khoi Phan
2014-01-01
Full Text Available Given a set of positive-weighted points and a query rectangle r (specified by a client of given extents, the goal of a maximizing range sum (MaxRS query is to find the optimal location of r such that the total weights of all the points covered by r are maximized. All existing methods for processing MaxRS queries assume the Euclidean distance metric. In many location-based applications, however, the motion of a client may be constrained by an underlying (spatial road network; that is, the client cannot move freely in space. This paper addresses the problem of processing MaxRS queries in a road network. We propose the external-memory algorithm that is suited for a large road network database. In addition, in contrast to the existing methods, which retrieve only one optimal location, our proposed algorithm retrieves all the possible optimal locations. Through simulations, we evaluate the performance of the proposed algorithm.
Jafari, Hamed; Salmasi, Nasser
2015-09-01
The nurse scheduling problem (NSP) has received a great amount of attention in recent years. In the NSP, the goal is to assign shifts to the nurses in order to satisfy the hospital's demand during the planning horizon by considering different objective functions. In this research, we focus on maximizing the nurses' preferences for working shifts and weekends off by considering several important factors such as hospital's policies, labor laws, governmental regulations, and the status of nurses at the end of the previous planning horizon in one of the largest hospitals in Iran i.e., Milad Hospital. Due to the shortage of available nurses, at first, the minimum total number of required nurses is determined. Then, a mathematical programming model is proposed to solve the problem optimally. Since the proposed research problem is NP-hard, a meta-heuristic algorithm based on simulated annealing (SA) is applied to heuristically solve the problem in a reasonable time. An initial feasible solution generator and several novel neighborhood structures are applied to enhance performance of the SA algorithm. Inspired from our observations in Milad hospital, random test problems are generated to evaluate the performance of the SA algorithm. The results of computational experiments indicate that the applied SA algorithm provides solutions with average percentage gap of 5.49 % compared to the upper bounds obtained from the mathematical model. Moreover, the applied SA algorithm provides significantly better solutions in a reasonable time than the schedules provided by the head nurses.
Obulesu, O.; Rama Mohan Reddy, A., Dr; Mahendra, M.
2017-08-01
Detecting regular and efficient cyclic models is the demanding activity for data analysts due to unstructured, vigorous and enormous raw information produced from web. Many existing approaches generate large candidate patterns in the occurrence of huge and complex databases. In this work, two novel algorithms are proposed and a comparative examination is performed by considering scalability and performance parameters. The first algorithm is, EFPMA (Extended Regular Model Detection Algorithm) used to find frequent sequential patterns from the spatiotemporal dataset and the second one is, ETMA (Enhanced Tree-based Mining Algorithm) for detecting effective cyclic models with symbolic database representation. EFPMA is an algorithm grows models from both ends (prefixes and suffixes) of detected patterns, which results in faster pattern growth because of less levels of database projection compared to existing approaches such as Prefixspan and SPADE. ETMA uses distinct notions to store and manage transactions data horizontally such as segment, sequence and individual symbols. ETMA exploits a partition-and-conquer method to find maximal patterns by using symbolic notations. Using this algorithm, we can mine cyclic models in full-series sequential patterns including subsection series also. ETMA reduces the memory consumption and makes use of the efficient symbolic operation. Furthermore, ETMA only records time-series instances dynamically, in terms of character, series and section approaches respectively. The extent of the pattern and proving efficiency of the reducing and retrieval techniques from synthetic and actual datasets is a really open & challenging mining problem. These techniques are useful in data streams, traffic risk analysis, medical diagnosis, DNA sequence Mining, Earthquake prediction applications. Extensive investigational outcomes illustrates that the algorithms outperforms well towards efficiency and scalability than ECLAT, STNR and MAFIA approaches.
Mousavi, Seyed Hosein; Nazemi, Ali; Hafezalkotob, Ashkan
2015-03-01
With the formation of the competitive electricity markets in the world, optimization of bidding strategies has become one of the main discussions in studies related to market designing. Market design is challenged by multiple objectives that need to be satisfied. The solution of those multi-objective problems is searched often over the combined strategy space, and thus requires the simultaneous optimization of multiple parameters. The problem is formulated analytically using the Nash equilibrium concept for games composed of large numbers of players having discrete and large strategy spaces. The solution methodology is based on a characterization of Nash equilibrium in terms of minima of a function and relies on a metaheuristic optimization approach to find these minima. This paper presents some metaheuristic algorithms to simulate how generators bid in the spot electricity market viewpoint of their profit maximization according to the other generators' strategies, such as genetic algorithm (GA), simulated annealing (SA) and hybrid simulated annealing genetic algorithm (HSAGA) and compares their results. As both GA and SA are generic search methods, HSAGA is also a generic search method. The model based on the actual data is implemented in a peak hour of Tehran's wholesale spot market in 2012. The results of the simulations show that GA outperforms SA and HSAGA on computing time, number of function evaluation and computing stability, as well as the results of calculated Nash equilibriums by GA are less various and different from each other than the other algorithms.
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Mahdi M. M. El-Arini
2013-01-01
Full Text Available In recent years, the solar energy has become one of the most important alternative sources of electric energy, so it is important to operate photovoltaic (PV panel at the optimal point to obtain the possible maximum efficiency. This paper presents a new optimization approach to maximize the electrical power of a PV panel. The technique which is based on objective function represents the output power of the PV panel and constraints, equality and inequality. First the dummy variables that have effect on the output power are classified into two categories: dependent and independent. The proposed approach is a multistage one as the genetic algorithm, GA, is used to obtain the best initial population at optimal solution and this initial population is fed to Lagrange multiplier algorithm (LM, then a comparison between the two algorithms, GA and LM, is performed. The proposed technique is applied to solar radiation measured at Helwan city at latitude 29.87°, Egypt. The results showed that the proposed technique is applicable.
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Rongxiao Wang
2017-09-01
Full Text Available The accurate prediction of air contaminant dispersion is essential to air quality monitoring and the emergency management of contaminant gas leakage incidents in chemical industry parks. Conventional atmospheric dispersion models can seldom give accurate predictions due to inaccurate input parameters. In order to improve the prediction accuracy of dispersion models, two data assimilation methods (i.e., the typical particle filter & the combination of a particle filter and expectation-maximization algorithm are proposed to assimilate the virtual Unmanned Aerial Vehicle (UAV observations with measurement error into the atmospheric dispersion model. Two emission cases with different dimensions of state parameters are considered. To test the performances of the proposed methods, two numerical experiments corresponding to the two emission cases are designed and implemented. The results show that the particle filter can effectively estimate the model parameters and improve the accuracy of model predictions when the dimension of state parameters is relatively low. In contrast, when the dimension of state parameters becomes higher, the method of particle filter combining the expectation-maximization algorithm performs better in terms of the parameter estimation accuracy. Therefore, the proposed data assimilation methods are able to effectively support air quality monitoring and emergency management in chemical industry parks.
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Conceição António, Carlos A.; Monteiro, João Brasileiro; Afonso, Clito Félix
2014-01-01
An approach based on the optimal placement of buildings that favors the use of solar energy is proposed. By maximizing the area of exposure to incident solar irradiation on roofs and facades of buildings, improvements on the energy performance of the urban matrix are reached, contributing decisively to reduce dependence on other less environmentally friendly energy options. A mathematical model is proposed to optimize the annual solar irradiation availability where the placement of the buildings in urban environment favors the use of solar energy resource. Improvements on the solar energy potential of the urban grid are reached by maximizing the exposure of incident solar irradiation on roofs and facades of buildings. The proposed model considers predominant, the amount of direct solar radiation, omitting the components of the solar irradiation diffused and reflected. The dynamic interaction of buildings on exposure to sunlight is simulated aiming to evaluate the shadowing zones. The incident solar irradiation simulation and the dynamic shading model were integrated in an optimization approach implemented numerically. The search for optimal topological solutions for urban grid is based on a Genetic Algorithm. The objective is to generate optimal scenarios for the placement of buildings into the urban grid in the pre-design phase, which enhances the use of solar irradiation. - Highlights: • A mathematical model is proposed to optimize annual solar irradiation availability. • Maximization of incident solar irradiation on roofs and facades of buildings. • Dynamic interaction of buildings is simulated aiming to evaluate shadowing zones. • Search for optimal topological solutions for urban grid based on genetic algorithm. • Solutions are compared with the conventional configurations for urban grid
Energy Technology Data Exchange (ETDEWEB)
Han, H; Xing, L [Stanford University, Palo Alto, CA (United States); Liang, Z [Stony Brook University, Stony Brook, NY (United States); Li, L [City University of New York College of Staten Island, Staten Island, NY (United States)
2016-06-15
Purpose: To investigate the feasibility of estimating the tissue mixture perfusions and quantifying cerebral blood flow change in arterial spin labeled (ASL) perfusion MR images. Methods: The proposed perfusion MR image analysis framework consists of 5 steps: (1) Inhomogeneity correction was performed on the T1- and T2-weighted images, which are available for each studied perfusion MR dataset. (2) We used the publicly available FSL toolbox to strip off the non-brain structures from the T1- and T2-weighted MR images. (3) We applied a multi-spectral tissue-mixture segmentation algorithm on both T1- and T2-structural MR images to roughly estimate the fraction of each tissue type - white matter, grey matter and cerebral spinal fluid inside each image voxel. (4) The distributions of the three tissue types or tissue mixture across the structural image array are down-sampled and mapped onto the ASL voxel array via a co-registration operation. (5) The presented 4-dimensional expectation-maximization (4D-EM) algorithm takes the down-sampled three tissue type distributions on perfusion image data to generate the perfusion mean, variance and percentage images for each tissue type of interest. Results: Experimental results on three volunteer datasets demonstrated that the multi-spectral tissue-mixture segmentation algorithm was effective to initialize tissue mixtures from T1- and T2-weighted MR images. Compared with the conventional ASL image processing toolbox, the proposed 4D-EM algorithm not only generated comparable perfusion mean images, but also produced perfusion variance and percentage images, which the ASL toolbox cannot obtain. It is observed that the perfusion contribution percentages may not be the same as the corresponding tissue mixture volume fractions estimated in the structural images. Conclusion: A specific application to brain ASL images showed that the presented perfusion image analysis method is promising for detecting subtle changes in tissue perfusions
International Nuclear Information System (INIS)
Han, H; Xing, L; Liang, Z; Li, L
2016-01-01
Purpose: To investigate the feasibility of estimating the tissue mixture perfusions and quantifying cerebral blood flow change in arterial spin labeled (ASL) perfusion MR images. Methods: The proposed perfusion MR image analysis framework consists of 5 steps: (1) Inhomogeneity correction was performed on the T1- and T2-weighted images, which are available for each studied perfusion MR dataset. (2) We used the publicly available FSL toolbox to strip off the non-brain structures from the T1- and T2-weighted MR images. (3) We applied a multi-spectral tissue-mixture segmentation algorithm on both T1- and T2-structural MR images to roughly estimate the fraction of each tissue type - white matter, grey matter and cerebral spinal fluid inside each image voxel. (4) The distributions of the three tissue types or tissue mixture across the structural image array are down-sampled and mapped onto the ASL voxel array via a co-registration operation. (5) The presented 4-dimensional expectation-maximization (4D-EM) algorithm takes the down-sampled three tissue type distributions on perfusion image data to generate the perfusion mean, variance and percentage images for each tissue type of interest. Results: Experimental results on three volunteer datasets demonstrated that the multi-spectral tissue-mixture segmentation algorithm was effective to initialize tissue mixtures from T1- and T2-weighted MR images. Compared with the conventional ASL image processing toolbox, the proposed 4D-EM algorithm not only generated comparable perfusion mean images, but also produced perfusion variance and percentage images, which the ASL toolbox cannot obtain. It is observed that the perfusion contribution percentages may not be the same as the corresponding tissue mixture volume fractions estimated in the structural images. Conclusion: A specific application to brain ASL images showed that the presented perfusion image analysis method is promising for detecting subtle changes in tissue perfusions
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Stadler Peter F
2010-06-01
Full Text Available Abstract Background The Maximal Pairing Problem (MPP is the prototype of a class of combinatorial optimization problems that are of considerable interest in bioinformatics: Given an arbitrary phylogenetic tree T and weights ωxy for the paths between any two pairs of leaves (x, y, what is the collection of edge-disjoint paths between pairs of leaves that maximizes the total weight? Special cases of the MPP for binary trees and equal weights have been described previously; algorithms to solve the general MPP are still missing, however. Results We describe a relatively simple dynamic programming algorithm for the special case of binary trees. We then show that the general case of multifurcating trees can be treated by interleaving solutions to certain auxiliary Maximum Weighted Matching problems with an extension of this dynamic programming approach, resulting in an overall polynomial-time solution of complexity (n4 log n w.r.t. the number n of leaves. The source code of a C implementation can be obtained under the GNU Public License from http://www.bioinf.uni-leipzig.de/Software/Targeting. For binary trees, we furthermore discuss several constrained variants of the MPP as well as a partition function approach to the probabilistic version of the MPP. Conclusions The algorithms introduced here make it possible to solve the MPP also for large trees with high-degree vertices. This has practical relevance in the field of comparative phylogenetics and, for example, in the context of phylogenetic targeting, i.e., data collection with resource limitations.
Mean field theory of EM algorithm for Bayesian grey scale image restoration
International Nuclear Information System (INIS)
Inoue, Jun-ichi; Tanaka, Kazuyuki
2003-01-01
The EM algorithm for the Bayesian grey scale image restoration is investigated in the framework of the mean field theory. Our model system is identical to the infinite range random field Q-Ising model. The maximum marginal likelihood method is applied to the determination of hyper-parameters. We calculate both the data-averaged mean square error between the original image and its maximizer of posterior marginal estimate, and the data-averaged marginal likelihood function exactly. After evaluating the hyper-parameter dependence of the data-averaged marginal likelihood function, we derive the EM algorithm which updates the hyper-parameters to obtain the maximum likelihood estimate analytically. The time evolutions of the hyper-parameters and so-called Q function are obtained. The relation between the speed of convergence of the hyper-parameters and the shape of the Q function is explained from the viewpoint of dynamics
Automatic Derivation of Statistical Algorithms: The EM Family and Beyond
Gray, Alexander G.; Fischer, Bernd; Schumann, Johann; Buntine, Wray
2003-01-01
Machine learning has reached a point where many probabilistic methods can be understood as variations, extensions and combinations of a much smaller set of abstract themes, e.g., as different instances of the EM algorithm. This enables the systematic derivation of algorithms customized for different models. Here, we describe the AUTOBAYES system which takes a high-level statistical model specification, uses powerful symbolic techniques based on schema-based program synthesis and computer alge...
Statistical trajectory of an approximate EM algorithm for probabilistic image processing
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Tanaka, Kazuyuki; Titterington, D M
2007-01-01
We calculate analytically a statistical average of trajectories of an approximate expectation-maximization (EM) algorithm with generalized belief propagation (GBP) and a Gaussian graphical model for the estimation of hyperparameters from observable data in probabilistic image processing. A statistical average with respect to observed data corresponds to a configuration average for the random-field Ising model in spin glass theory. In the present paper, hyperparameters which correspond to interactions and external fields of spin systems are estimated by an approximate EM algorithm. A practical algorithm is described for gray-level image restoration based on a Gaussian graphical model and GBP. The GBP approach corresponds to the cluster variation method in statistical mechanics. Our main result in the present paper is to obtain the statistical average of the trajectory in the approximate EM algorithm by using loopy belief propagation and GBP with respect to degraded images generated from a probability density function with true values of hyperparameters. The statistical average of the trajectory can be expressed in terms of recursion formulas derived from some analytical calculations
Dragonfly: an implementation of the expand-maximize-compress algorithm for single-particle imaging.
Ayyer, Kartik; Lan, Ti-Yen; Elser, Veit; Loh, N Duane
2016-08-01
Single-particle imaging (SPI) with X-ray free-electron lasers has the potential to change fundamentally how biomacromolecules are imaged. The structure would be derived from millions of diffraction patterns, each from a different copy of the macromolecule before it is torn apart by radiation damage. The challenges posed by the resultant data stream are staggering: millions of incomplete, noisy and un-oriented patterns have to be computationally assembled into a three-dimensional intensity map and then phase reconstructed. In this paper, the Dragonfly software package is described, based on a parallel implementation of the expand-maximize-compress reconstruction algorithm that is well suited for this task. Auxiliary modules to simulate SPI data streams are also included to assess the feasibility of proposed SPI experiments at the Linac Coherent Light Source, Stanford, California, USA.
Application and performance of an ML-EM algorithm in NEXT
Simón, A.; Lerche, C.; Monrabal, F.; Gómez-Cadenas, J. J.; Álvarez, V.; Azevedo, C. D. R.; Benlloch-Rodríguez, J. M.; Borges, F. I. G. M.; Botas, A.; Cárcel, S.; Carrión, J. V.; Cebrián, S.; Conde, C. A. N.; Díaz, J.; Diesburg, M.; Escada, J.; Esteve, R.; Felkai, R.; Fernandes, L. M. P.; Ferrario, P.; Ferreira, A. L.; Freitas, E. D. C.; Goldschmidt, A.; González-Díaz, D.; Gutiérrez, R. M.; Hauptman, J.; Henriques, C. A. O.; Hernandez, A. I.; Hernando Morata, J. A.; Herrero, V.; Jones, B. J. P.; Labarga, L.; Laing, A.; Lebrun, P.; Liubarsky, I.; López-March, N.; Losada, M.; Martín-Albo, J.; Martínez-Lema, G.; Martínez, A.; McDonald, A. D.; Monteiro, C. M. B.; Mora, F. J.; Moutinho, L. M.; Muñoz Vidal, J.; Musti, M.; Nebot-Guinot, M.; Novella, P.; Nygren, D. R.; Palmeiro, B.; Para, A.; Pérez, J.; Querol, M.; Renner, J.; Ripoll, L.; Rodríguez, J.; Rogers, L.; Santos, F. P.; dos Santos, J. M. F.; Sofka, C.; Sorel, M.; Stiegler, T.; Toledo, J. F.; Torrent, J.; Tsamalaidze, Z.; Veloso, J. F. C. A.; Webb, R.; White, J. T.; Yahlali, N.
2017-08-01
The goal of the NEXT experiment is the observation of neutrinoless double beta decay in 136Xe using a gaseous xenon TPC with electroluminescent amplification and specialized photodetector arrays for calorimetry and tracking. The NEXT Collaboration is exploring a number of reconstruction algorithms to exploit the full potential of the detector. This paper describes one of them: the Maximum Likelihood Expectation Maximization (ML-EM) method, a generic iterative algorithm to find maximum-likelihood estimates of parameters that has been applied to solve many different types of complex inverse problems. In particular, we discuss a bi-dimensional version of the method in which the photosensor signals integrated over time are used to reconstruct a transverse projection of the event. First results show that, when applied to detector simulation data, the algorithm achieves nearly optimal energy resolution (better than 0.5% FWHM at the Q value of 136Xe) for events distributed over the full active volume of the TPC.
International Nuclear Information System (INIS)
Chen, C.M.; Lee, S.Y.
1995-01-01
The EM algorithm promises an estimated image with the maximal likelihood for 3D PET image reconstruction. However, due to its long computation time, the EM algorithm has not been widely used in practice. While several parallel implementations of the EM algorithm have been developed to make the EM algorithm feasible, they do not guarantee an optimal parallelization efficiency. In this paper, the authors propose a new parallel EM algorithm which maximizes the performance by optimizing data replication on a mesh-connected message-passing multiprocessor. To optimize data replication, the authors have formally derived the optimal allocation of shared data, group sizes, integration and broadcasting of replicated data as well as the scheduling of shared data accesses. The proposed parallel EM algorithm has been implemented on an iPSC/860 with 16 PEs. The experimental and theoretical results, which are consistent with each other, have shown that the proposed parallel EM algorithm could improve performance substantially over those using unoptimized data replication
Liu, Haiguang; Spence, John C H
2014-11-01
Crystallographic auto-indexing algorithms provide crystal orientations and unit-cell parameters and assign Miller indices based on the geometric relations between the Bragg peaks observed in diffraction patterns. However, if the Bravais symmetry is higher than the space-group symmetry, there will be multiple indexing options that are geometrically equivalent, and hence many ways to merge diffraction intensities from protein nanocrystals. Structure factor magnitudes from full reflections are required to resolve this ambiguity but only partial reflections are available from each XFEL shot, which must be merged to obtain full reflections from these 'stills'. To resolve this chicken-and-egg problem, an expectation maximization algorithm is described that iteratively constructs a model from the intensities recorded in the diffraction patterns as the indexing ambiguity is being resolved. The reconstructed model is then used to guide the resolution of the indexing ambiguity as feedback for the next iteration. Using both simulated and experimental data collected at an X-ray laser for photosystem I in the P63 space group (which supports a merohedral twinning indexing ambiguity), the method is validated.
Energy Technology Data Exchange (ETDEWEB)
Tumuluru, Jaya
2013-01-10
Aims: The present case study is on maximizing the aqua feed properties using response surface methodology and genetic algorithm. Study Design: Effect of extrusion process variables like screw speed, L/D ratio, barrel temperature, and feed moisture content were analyzed to maximize the aqua feed properties like water stability, true density, and expansion ratio. Place and Duration of Study: This study was carried out in the Department of Agricultural and Food Engineering, Indian Institute of Technology, Kharagpur, India. Methodology: A variable length single screw extruder was used in the study. The process variables selected were screw speed (rpm), length-to-diameter (L/D) ratio, barrel temperature (degrees C), and feed moisture content (%). The pelletized aqua feed was analyzed for physical properties like water stability (WS), true density (TD), and expansion ratio (ER). Extrusion experimental data was collected by based on central composite design. The experimental data was further analyzed using response surface methodology (RSM) and genetic algorithm (GA) for maximizing feed properties. Results: Regression equations developed for the experimental data has adequately described the effect of process variables on the physical properties with coefficient of determination values (R2) of > 0.95. RSM analysis indicated WS, ER, and TD were maximized at L/D ratio of 12-13, screw speed of 60-80 rpm, feed moisture content of 30-40%, and barrel temperature of = 80 degrees C for ER and TD and > 90 degrees C for WS. Based on GA analysis, a maxium WS of 98.10% was predicted at a screw speed of 96.71 rpm, L/D radio of 13.67, barrel temperature of 96.26 degrees C, and feed moisture content of 33.55%. Maximum ER and TD of 0.99 and 1346.9 kg/m3 was also predicted at screw speed of 60.37 and 90.24 rpm, L/D ratio of 12.18 and 13.52, barrel temperature of 68.50 and 64.88 degrees C, and medium feed moisture content of 33.61 and 38.36%. Conclusion: The present data analysis indicated
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Aida Tayebiyan
2016-06-01
Full Text Available Background: Several reservoir systems have been constructed for hydropower generation around the world. Hydropower offers an economical source of electricity with reduce carbon emissions. Therefore, it is such a clean and renewable source of energy. Reservoirs that generate hydropower are typically operated with the goal of maximizing energy revenue. Yet, reservoir systems are inefficiently operated and manage according to policies determined at the construction time. It is worth noting that with little enhancement in operation of reservoir system, there could be an increase in efficiency of the scheme for many consumers. Methods: This research develops simulation-optimization models that reflect discrete hedging policy (DHP to manage and operate hydropower reservoir system and analyse it in both single and multireservoir system. Accordingly, three operational models (2 single reservoir systems and 1 multi-reservoir system were constructed and optimized by genetic algorithm (GA. Maximizing the total power generation in horizontal time is chosen as an objective function in order to improve the functional efficiency in hydropower production with consideration to operational and physical limitations. The constructed models, which is a cascade hydropower reservoirs system have been tested and evaluated in the Cameron Highland and Batang Padang in Malaysia. Results: According to the given results, usage of DHP for hydropower reservoir system operation could increase the power generation output to nearly 13% in the studied reservoir system compared to present operating policy (TNB operation. This substantial increase in power production will enhance economic development. Moreover, the given results of single and multi-reservoir systems affirmed that hedging policy could manage the single system much better than operation of the multi-reservoir system. Conclusion: It can be summarized that DHP is an efficient and feasible policy, which could be used
International Nuclear Information System (INIS)
Hufnagel, Heike; Pennec, Xavier; Ayache, Nicholas; Ehrhardt, Jan; Handels, Heinz
2008-01-01
Identification of point correspondences between shapes is required for statistical analysis of organ shapes differences. Since manual identification of landmarks is not a feasible option in 3D, several methods were developed to automatically find one-to-one correspondences on shape surfaces. For unstructured point sets, however, one-to-one correspondences do not exist but correspondence probabilities can be determined. A method was developed to compute a statistical shape model based on shapes which are represented by unstructured point sets with arbitrary point numbers. A fundamental problem when computing statistical shape models is the determination of correspondences between the points of the shape observations of the training data set. In the absence of landmarks, exact correspondences can only be determined between continuous surfaces, not between unstructured point sets. To overcome this problem, we introduce correspondence probabilities instead of exact correspondences. The correspondence probabilities are found by aligning the observation shapes with the affine expectation maximization-iterative closest points (EM-ICP) registration algorithm. In a second step, the correspondence probabilities are used as input to compute a mean shape (represented once again by an unstructured point set). Both steps are unified in a single optimization criterion which depe nds on the two parameters 'registration transformation' and 'mean shape'. In a last step, a variability model which best represents the variability in the training data set is computed. Experiments on synthetic data sets and in vivo brain structure data sets (MRI) are then designed to evaluate the performance of our algorithm. The new method was applied to brain MRI data sets, and the estimated point correspondences were compared to a statistical shape model built on exact correspondences. Based on established measures of ''generalization ability'' and ''specificity'', the estimates were very satisfactory
Bayer, Christian
2016-02-20
© 2016 Taylor & Francis Group, LLC. ABSTRACT: In this work, we present an extension of the forward–reverse representation introduced by Bayer and Schoenmakers (Annals of Applied Probability, 24(5):1994–2032, 2014) to the context of stochastic reaction networks (SRNs). We apply this stochastic representation to the computation of efficient approximations of expected values of functionals of SRN bridges, that is, SRNs conditional on their values in the extremes of given time intervals. We then employ this SRN bridge-generation technique to the statistical inference problem of approximating reaction propensities based on discretely observed data. To this end, we introduce a two-phase iterative inference method in which, during phase I, we solve a set of deterministic optimization problems where the SRNs are replaced by their reaction-rate ordinary differential equations approximation; then, during phase II, we apply the Monte Carlo version of the expectation-maximization algorithm to the phase I output. By selecting a set of overdispersed seeds as initial points in phase I, the output of parallel runs from our two-phase method is a cluster of approximate maximum likelihood estimates. Our results are supported by numerical examples.
Vilanova, Pedro
2016-01-07
In this work, we present an extension of the forward-reverse representation introduced in Simulation of forward-reverse stochastic representations for conditional diffusions , a 2014 paper by Bayer and Schoenmakers to the context of stochastic reaction networks (SRNs). We apply this stochastic representation to the computation of efficient approximations of expected values of functionals of SRN bridges, i.e., SRNs conditional on their values in the extremes of given time-intervals. We then employ this SRN bridge-generation technique to the statistical inference problem of approximating reaction propensities based on discretely observed data. To this end, we introduce a two-phase iterative inference method in which, during phase I, we solve a set of deterministic optimization problems where the SRNs are replaced by their reaction-rate ordinary differential equations approximation; then, during phase II, we apply the Monte Carlo version of the Expectation-Maximization algorithm to the phase I output. By selecting a set of over-dispersed seeds as initial points in phase I, the output of parallel runs from our two-phase method is a cluster of approximate maximum likelihood estimates. Our results are supported by numerical examples.
Noise properties of the EM algorithm. Pt. 1
International Nuclear Information System (INIS)
Barrett, H.H.; Wilson, D.W.; Tsui, B.M.W.
1994-01-01
The expectation-maximisation (EM) algorithm is an important tool for maximum-likelihood (ML) estimation and image reconstruction, especially in medical imaging. It is a non-linear iterative algorithm that attempts to find the ML estimate of the object that produced a data set. The convergence of the algorithm and other deterministic properties are well established, but relatively little is known about how noise in the data influences noise in the final reconstructed image. In this paper we present a detailed treatment of these statistical properties. The specific application we have in mind is image reconstruction in emission tomography, but the results are valid for any application of the EM algorithm in which the data set can be described by Poisson statistics. We show that the probability density function for the grey level at a pixel in the image is well approximated by a log-normal law. An expression is derived for the variance of the grey level and for pixel-to-pixel covariance. The variance increases rapidly with iteration number at first, but eventually saturates as the ML estimate is approached. Moreover, the variance at any iteration number has a factor proportional to the square of the mean image (though other factors may also depend on the mean image), so a map of the standard deviation resembles the object itself. Thus low-intensity regions of the image tend to have low noise. (author)
Energy Technology Data Exchange (ETDEWEB)
Ha, Woo Seok; Kim, Soo Mee; Park, Min Jae; Lee, Dong Soo; Lee, Jae Sung [Seoul National University, Seoul (Korea, Republic of)
2009-10-15
The maximum likelihood-expectation maximization (ML-EM) is the statistical reconstruction algorithm derived from probabilistic model of the emission and detection processes. Although the ML-EM has many advantages in accuracy and utility, the use of the ML-EM is limited due to the computational burden of iterating processing on a CPU (central processing unit). In this study, we developed a parallel computing technique on GPU (graphic processing unit) for ML-EM algorithm. Using Geforce 9800 GTX+ graphic card and CUDA (compute unified device architecture) the projection and backprojection in ML-EM algorithm were parallelized by NVIDIA's technology. The time delay on computations for projection, errors between measured and estimated data and backprojection in an iteration were measured. Total time included the latency in data transmission between RAM and GPU memory. The total computation time of the CPU- and GPU-based ML-EM with 32 iterations were 3.83 and 0.26 sec, respectively. In this case, the computing speed was improved about 15 times on GPU. When the number of iterations increased into 1024, the CPU- and GPU-based computing took totally 18 min and 8 sec, respectively. The improvement was about 135 times and was caused by delay on CPU-based computing after certain iterations. On the other hand, the GPU-based computation provided very small variation on time delay per iteration due to use of shared memory. The GPU-based parallel computation for ML-EM improved significantly the computing speed and stability. The developed GPU-based ML-EM algorithm could be easily modified for some other imaging geometries
International Nuclear Information System (INIS)
Ha, Woo Seok; Kim, Soo Mee; Park, Min Jae; Lee, Dong Soo; Lee, Jae Sung
2009-01-01
The maximum likelihood-expectation maximization (ML-EM) is the statistical reconstruction algorithm derived from probabilistic model of the emission and detection processes. Although the ML-EM has many advantages in accuracy and utility, the use of the ML-EM is limited due to the computational burden of iterating processing on a CPU (central processing unit). In this study, we developed a parallel computing technique on GPU (graphic processing unit) for ML-EM algorithm. Using Geforce 9800 GTX+ graphic card and CUDA (compute unified device architecture) the projection and backprojection in ML-EM algorithm were parallelized by NVIDIA's technology. The time delay on computations for projection, errors between measured and estimated data and backprojection in an iteration were measured. Total time included the latency in data transmission between RAM and GPU memory. The total computation time of the CPU- and GPU-based ML-EM with 32 iterations were 3.83 and 0.26 sec, respectively. In this case, the computing speed was improved about 15 times on GPU. When the number of iterations increased into 1024, the CPU- and GPU-based computing took totally 18 min and 8 sec, respectively. The improvement was about 135 times and was caused by delay on CPU-based computing after certain iterations. On the other hand, the GPU-based computation provided very small variation on time delay per iteration due to use of shared memory. The GPU-based parallel computation for ML-EM improved significantly the computing speed and stability. The developed GPU-based ML-EM algorithm could be easily modified for some other imaging geometries
Pal, Suvra; Balakrishnan, Narayanaswamy
2018-05-01
In this paper, we develop likelihood inference based on the expectation maximization algorithm for the Box-Cox transformation cure rate model assuming the lifetimes to follow a Weibull distribution. A simulation study is carried out to demonstrate the performance of the proposed estimation method. Through Monte Carlo simulations, we also study the effect of model misspecification on the estimate of cure rate. Finally, we analyze a well-known data on melanoma with the model and the inferential method developed here.
Directory of Open Access Journals (Sweden)
Kim Jae H
2005-01-01
Full Text Available In this paper, we consider the issue of blind detection of Alamouti-type differential space-time (ST modulation in static Rayleigh fading channels. We focus our attention on a -shifted BPSK constellation, introducing a novel transformation to the received signal such that this binary ST modulation, which has a second-order transmit diversity, is equivalent to QPSK modulation with second-order receive diversity. This equivalent representation allows us to apply a low-complexity detection technique specifically designed for receive diversity, namely, scalar multiple-symbol differential detection (MSDD. To further increase receiver performance, we apply an iterative expectation-maximization (EM algorithm which performs joint channel estimation and sequence detection. This algorithm uses minimum mean square estimation to obtain channel estimates and the maximum-likelihood principle to detect the transmitted sequence, followed by differential decoding. With receiver complexity proportional to the observation window length, our receiver can achieve the performance of a coherent maximal ratio combining receiver (with differential decoding in as few as a single EM receiver iteration, provided that the window size of the initial MSDD is sufficiently long. To further demonstrate that the MSDD is a vital part of this receiver setup, we show that an initial ST conventional differential detector would lead to strange convergence behavior in the EM algorithm.
International Nuclear Information System (INIS)
Matsumoto, Keiichi; Ohnishi, Hideo; Niida, Hideharu; Nishimura, Yoshihiro; Wada, Yasuhiro; Kida, Tetsuo
2003-01-01
The maximum likelihood expectation maximization (ML-EM) algorithm has become available as an alternative to filtered back projection in SPECT. The actual physical performance may be different depending on the manufacturer and model, because of differences in computational details. The purpose of this study was to investigate the characteristics of seven different types of ML-EM algorithms using simple simulation data. Seven ML-EM algorithm programs were used: Genie (GE), esoft (Siemens), HARP-III (Hitachi), GMS-5500UI (Toshiba), Pegasys (ADAC), ODYSSEY-FX (Marconi), and Windows-PC (original software). Projection data of a 2-pixel-wide line source in the center of the field of view were simulated without attenuation or scatter. Images were reconstructed with ML-EM by changing the number of iterations from 1 to 45 for each algorithm. Image quality was evaluated after a reconstruction using full width at half maximum (FWHM), full width at tenth maximum (FWTM), and the total counts of the reconstructed images. In the maximum number of iterations, the difference in the FWHM value was up to 1.5 pixels, and that of FWTM, no less than 2.0 pixels. The total counts of the reconstructed images in the initial few iterations were larger or smaller than the converged value depending on the initial values. Our results for the simplest simulation data suggest that each ML-EM algorithm itself provides a simulation image. We should keep in mind which algorithm is being used and its computational details, when physical and clinical usefulness are compared. (author)
Foronda, Augusto; Ohta, Chikara; Tamaki, Hisashi
Dirty paper coding (DPC) is a strategy to achieve the region capacity of multiple input multiple output (MIMO) downlink channels and a DPC scheduler is throughput optimal if users are selected according to their queue states and current rates. However, DPC is difficult to implement in practical systems. One solution, zero-forcing beamforming (ZFBF) strategy has been proposed to achieve the same asymptotic sum rate capacity as that of DPC with an exhaustive search over the entire user set. Some suboptimal user group selection schedulers with reduced complexity based on ZFBF strategy (ZFBF-SUS) and proportional fair (PF) scheduling algorithm (PF-ZFBF) have also been proposed to enhance the throughput and fairness among the users, respectively. However, they are not throughput optimal, fairness and throughput decrease if each user queue length is different due to different users channel quality. Therefore, we propose two different scheduling algorithms: a throughput optimal scheduling algorithm (ZFBF-TO) and a reduced complexity scheduling algorithm (ZFBF-RC). Both are based on ZFBF strategy and, at every time slot, the scheduling algorithms have to select some users based on user channel quality, user queue length and orthogonality among users. Moreover, the proposed algorithms have to produce the rate allocation and power allocation for the selected users based on a modified water filling method. We analyze the schedulers complexity and numerical results show that ZFBF-RC provides throughput and fairness improvements compared to the ZFBF-SUS and PF-ZFBF scheduling algorithms.
Efficient Rectangular Maximal-Volume Algorithm for Rating Elicitation in Collaborative Filtering
Fonarev, Alexander; Mikhalev, Alexander; Serdyukov, Pavel; Gusev, Gleb; Oseledets, Ivan
2017-01-01
preference information for making good recommendations. One of the most successful approaches, called Representative Based Matrix Factorization, is based on Maxvol algorithm. Unfortunately, this approach has one important limitation - a seed set of a
Tracking of Multiple Moving Sources Using Recursive EM Algorithm
Directory of Open Access Journals (Sweden)
Böhme Johann F
2005-01-01
Full Text Available We deal with recursive direction-of-arrival (DOA estimation of multiple moving sources. Based on the recursive EM algorithm, we develop two recursive procedures to estimate the time-varying DOA parameter for narrowband signals. The first procedure requires no prior knowledge about the source movement. The second procedure assumes that the motion of moving sources is described by a linear polynomial model. The proposed recursion updates the polynomial coefficients when a new data arrives. The suggested approaches have two major advantages: simple implementation and easy extension to wideband signals. Numerical experiments show that both procedures provide excellent results in a slowly changing environment. When the DOA parameter changes fast or two source directions cross with each other, the procedure designed for a linear polynomial model has a better performance than the general procedure. Compared to the beamforming technique based on the same parameterization, our approach is computationally favorable and has a wider range of applications.
Linear array implementation of the EM algorithm for PET image reconstruction
International Nuclear Information System (INIS)
Rajan, K.; Patnaik, L.M.; Ramakrishna, J.
1995-01-01
The PET image reconstruction based on the EM algorithm has several attractive advantages over the conventional convolution back projection algorithms. However, the PET image reconstruction based on the EM algorithm is computationally burdensome for today's single processor systems. In addition, a large memory is required for the storage of the image, projection data, and the probability matrix. Since the computations are easily divided into tasks executable in parallel, multiprocessor configurations are the ideal choice for fast execution of the EM algorithms. In tis study, the authors attempt to overcome these two problems by parallelizing the EM algorithm on a multiprocessor systems. The parallel EM algorithm on a linear array topology using the commercially available fast floating point digital signal processor (DSP) chips as the processing elements (PE's) has been implemented. The performance of the EM algorithm on a 386/387 machine, IBM 6000 RISC workstation, and on the linear array system is discussed and compared. The results show that the computational speed performance of a linear array using 8 DSP chips as PE's executing the EM image reconstruction algorithm is about 15.5 times better than that of the IBM 6000 RISC workstation. The novelty of the scheme is its simplicity. The linear array topology is expandable with a larger number of PE's. The architecture is not dependant on the DSP chip chosen, and the substitution of the latest DSP chip is straightforward and could yield better speed performance
DEFF Research Database (Denmark)
Zibar, Darko; Winther, Ole; Franceschi, Niccolo
2012-01-01
In this paper, we show numerically and experimentally that expectation maximization (EM) algorithm is a powerful tool in combating system impairments such as fibre nonlinearities, inphase and quadrature (I/Q) modulator imperfections and laser linewidth. The EM algorithm is an iterative algorithm ...
Efficient Rectangular Maximal-Volume Algorithm for Rating Elicitation in Collaborative Filtering
Fonarev, Alexander
2017-02-07
Cold start problem in Collaborative Filtering can be solved by asking new users to rate a small seed set of representative items or by asking representative users to rate a new item. The question is how to build a seed set that can give enough preference information for making good recommendations. One of the most successful approaches, called Representative Based Matrix Factorization, is based on Maxvol algorithm. Unfortunately, this approach has one important limitation - a seed set of a particular size requires a rating matrix factorization of fixed rank that should coincide with that size. This is not necessarily optimal in the general case. In the current paper, we introduce a fast algorithm for an analytical generalization of this approach that we call Rectangular Maxvol. It allows the rank of factorization to be lower than the required size of the seed set. Moreover, the paper includes the theoretical analysis of the method\\'s error, the complexity analysis of the existing methods and the comparison to the state-of-the-art approaches.
A Local Scalable Distributed EM Algorithm for Large P2P Networks
National Aeronautics and Space Administration — his paper describes a local and distributed expectation maximization algorithm for learning parameters of Gaussian mixture models (GMM) in large peer-to-peer (P2P)...
International Nuclear Information System (INIS)
Singh, Sonveer; Agrawal, Sanjay
2016-01-01
Highlights: • Thermal modeling of novel dual channel semitransparent photovoltaic thermal hybrid module. • Efficiency maximization and performance evaluation of dual channel photovoltaic thermal module. • Annual performance has been evaluated for Srinagar, Jodhpur, Bangalore and New Delhi (India). • There are improvements in results for optimized system as compared to un-optimized system. - Abstract: The work has been carried out in two steps; firstly the parameters of hybrid dual channel semitransparent photovoltaic thermal module has been optimized using a fuzzyfied genetic algorithm. During the course of optimization, overall exergy efficiency is considered as an objective function and different design parameters of the proposed module have been optimized. Fuzzy controller is used to improve the performance of genetic algorithms and the approach is called as a fuzzyfied genetic algorithm. In the second step, the performance of the module has been analyzed for four cities of India such as Srinagar, Bangalore, Jodhpur and New Delhi. The performance of the module has been evaluated for daytime 08:00 AM to 05:00 PM and annually from January to December. It is to be noted that, an average improvement occurs in electrical efficiency of the optimized module, simultaneously there is also a reduction in solar cell temperature as compared to un-optimized module.
International Nuclear Information System (INIS)
Samatova, N F; Schmidt, M C; Hendrix, W; Breimyer, P; Thomas, K; Park, B-H
2008-01-01
Data-driven construction of predictive models for biological systems faces challenges from data intensity, uncertainty, and computational complexity. Data-driven model inference is often considered a combinatorial graph problem where an enumeration of all feasible models is sought. The data-intensive and the NP-hard nature of such problems, however, challenges existing methods to meet the required scale of data size and uncertainty, even on modern supercomputers. Maximal clique enumeration (MCE) in a graph derived from such biological data is often a rate-limiting step in detecting protein complexes in protein interaction data, finding clusters of co-expressed genes in microarray data, or identifying clusters of orthologous genes in protein sequence data. We report two key advances that address this challenge. We designed and implemented the first (to the best of our knowledge) parallel MCE algorithm that scales linearly on thousands of processors running MCE on real-world biological networks with thousands and hundreds of thousands of vertices. In addition, we proposed and developed the Graph Perturbation Theory (GPT) that establishes a foundation for efficiently solving the MCE problem in perturbed graphs, which model the uncertainty in the data. GPT formulates necessary and sufficient conditions for detecting the differences between the sets of maximal cliques in the original and perturbed graphs and reduces the enumeration time by more than 80% compared to complete recomputation
High-speed computation of the EM algorithm for PET image reconstruction
International Nuclear Information System (INIS)
Rajan, K.; Patnaik, L.M.; Ramakrishna, J.
1994-01-01
The PET image reconstruction based on the EM algorithm has several attractive advantages over the conventional convolution backprojection algorithms. However, two major drawbacks have impeded the routine use of the EM algorithm, namely, the long computational time due to slow convergence and the large memory required for the storage of the image, projection data and the probability matrix. In this study, the authors attempts to solve these two problems by parallelizing the EM algorithm on a multiprocessor system. The authors have implemented an extended hypercube (EH) architecture for the high-speed computation of the EM algorithm using the commercially available fast floating point digital signal processor (DSP) chips as the processing elements (PEs). The authors discuss and compare the performance of the EM algorithm on a 386/387 machine, CD 4360 mainframe, and on the EH system. The results show that the computational speed performance of an EH using DSP chips as PEs executing the EM image reconstruction algorithm is about 130 times better than that of the CD 4360 mainframe. The EH topology is expandable with more number of PEs
Directory of Open Access Journals (Sweden)
Yasui Yutaka
2011-01-01
Full Text Available Abstract Background Autism spectrum disorders (ASD are associated with complications of pregnancy that implicate fetal hypoxia (FH; the excess of ASD in male gender is poorly understood. We tested the hypothesis that risk of ASD is related to fetal hypoxia and investigated whether this effect is greater among males. Methods Provincial delivery records (PDR identified the cohort of all 218,890 singleton live births in the province of Alberta, Canada, between 01-01-98 and 12-31-04. These were followed-up for ASD via ICD-9 diagnostic codes assigned by physician billing until 03-31-08. Maternal and obstetric risk factors, including FH determined from blood tests of acidity (pH, were extracted from PDR. The binary FH status was missing in approximately half of subjects. Assuming that characteristics of mothers and pregnancies would be correlated with FH, we used an Estimation-Maximization algorithm to estimate HF-ASD association, allowing for both missing-at-random (MAR and specific not-missing-at-random (NMAR mechanisms. Results Data indicated that there was excess risk of ASD among males who were hypoxic at birth, not materially affected by adjustment for potential confounding due to birth year and socio-economic status: OR 1.13, 95%CI: 0.96, 1.33 (MAR assumption. Limiting analysis to full-term males, the adjusted OR under specific NMAR assumptions spanned 95%CI of 1.0 to 1.6. Conclusion Our results are consistent with a weak effect of fetal hypoxia on risk of ASD among males. E-M algorithm is an efficient and flexible tool for modeling missing data in the studied setting.
Touw, D J; Vinks, A A; Neef, C
1997-06-01
The availability of personal computer programs for individualizing drug dosage regimens has stimulated the interest in modelling population pharmacokinetics. Data from 82 adolescent and adult patients with cystic fibrosis (CF) who were treated with intravenous tobramycin because of an exacerbation of their pulmonary infection were analysed with a non-parametric expectation maximization (NPEM) algorithm. This algorithm estimates the entire discrete joint probability density of the pharmacokinetic parameters. It also provides traditional parametric statistics such as the means, standard deviation, median, covariances and correlations among the various parameters. It also provides graphic-2- and 3-dimensional representations of the marginal densities of the parameters investigated. Several models for intravenous tobramycin in adolescent and adult patients with CF were compared. Covariates were total body weight (for the volume of distribution) and creatinine clearance (for the total body clearance and elimination rate). Because of lack of data on patients with poor renal function, restricted models with non-renal clearance and the non-renal elimination rate constant fixed at literature values of 0.15 L/h and 0.01 h-1 were also included. In this population, intravenous tobramycin could be best described by median (+/-dispersion factor) volume of distribution per unit of total body weight of 0.28 +/- 0.05 L/kg, elimination rate constant of 0.25 +/- 0.10 h-1 and elimination rate constant per unit of creatinine clearance of 0.0008 +/- 0.0009 h-1/(ml/min/1.73 m2). Analysis of populations of increasing size showed that using a restricted model with a non-renal elimination rate constant fixed at 0.01 h-1, a model based on a population of only 10 to 20 patients, contained parameter values similar to those of the entire population and, using the full model, a larger population (at least 40 patients) was needed.
International Nuclear Information System (INIS)
Zeng, G.L.; Gullberg, G.T.
1990-01-01
Reconstruction artifacts in cone beam tomography are studied for filtered backprojection (Feldkamp) and iterative EM algorithms. The filtered backprojection algorithm uses a voxel-driven, interpolated backprojection to reconstruct the cone beam data; whereas, the iterative EM algorithm performs ray-driven projection and backprojection operations for each iteration. Two weight in schemes for the projection and backprojection operations in the EM algorithm are studied. One weights each voxel by the length of the ray through the voxel and the other equates the value of a voxel to the functional value of the midpoint of the line intersecting the voxel, which is obtained by interpolating between eight neighboring voxels. Cone beam reconstruction artifacts such as rings, bright vertical extremities, and slice-to slice cross talk are not found with parallel beam and fan beam geometries
Yang, Liu; Lu, Yinzhi; Zhong, Yuanchang; Wu, Xuegang; Yang, Simon X
2015-12-26
Energy resource limitation is a severe problem in traditional wireless sensor networks (WSNs) because it restricts the lifetime of network. Recently, the emergence of energy harvesting techniques has brought with them the expectation to overcome this problem. In particular, it is possible for a sensor node with energy harvesting abilities to work perpetually in an Energy Neutral state. In this paper, a Multi-hop Energy Neutral Clustering (MENC) algorithm is proposed to construct the optimal multi-hop clustering architecture in energy harvesting WSNs, with the goal of achieving perpetual network operation. All cluster heads (CHs) in the network act as routers to transmit data to base station (BS) cooperatively by a multi-hop communication method. In addition, by analyzing the energy consumption of intra- and inter-cluster data transmission, we give the energy neutrality constraints. Under these constraints, every sensor node can work in an energy neutral state, which in turn provides perpetual network operation. Furthermore, the minimum network data transmission cycle is mathematically derived using convex optimization techniques while the network information gathering is maximal. Simulation results show that our protocol can achieve perpetual network operation, so that the consistent data delivery is guaranteed. In addition, substantial improvements on the performance of network throughput are also achieved as compared to the famous traditional clustering protocol LEACH and recent energy harvesting aware clustering protocols.
Directory of Open Access Journals (Sweden)
Chia-Feng Lu
Full Text Available Automatic identification of various perfusion compartments from dynamic susceptibility contrast magnetic resonance brain images can assist in clinical diagnosis and treatment of cerebrovascular diseases. The principle of segmentation methods was based on the clustering of bolus transit-time profiles to discern areas of different tissues. However, the cerebrovascular diseases may result in a delayed and dispersed local perfusion and therefore alter the hemodynamic signal profiles. Assessing the accuracy of the segmentation technique under delayed/dispersed circumstance is critical to accurately evaluate the severity of the vascular disease. In this study, we improved the segmentation method of expectation-maximization algorithm by using the results of hierarchical clustering on whitened perfusion data as initial parameters for a mixture of multivariate Gaussians model. In addition, Monte Carlo simulations were conducted to evaluate the performance of proposed method under different levels of delay, dispersion, and noise of signal profiles in tissue segmentation. The proposed method was used to classify brain tissue types using perfusion data from five normal participants, a patient with unilateral stenosis of the internal carotid artery, and a patient with moyamoya disease. Our results showed that the normal, delayed or dispersed hemodynamics can be well differentiated for patients, and therefore the local arterial input function for impaired tissues can be recognized to minimize the error when estimating the cerebral blood flow. Furthermore, the tissue in the risk of infarct and the tissue with or without the complementary blood supply from the communicating arteries can be identified.
Directory of Open Access Journals (Sweden)
Liu Yang
2015-12-01
Full Text Available Energy resource limitation is a severe problem in traditional wireless sensor networks (WSNs because it restricts the lifetime of network. Recently, the emergence of energy harvesting techniques has brought with them the expectation to overcome this problem. In particular, it is possible for a sensor node with energy harvesting abilities to work perpetually in an Energy Neutral state. In this paper, a Multi-hop Energy Neutral Clustering (MENC algorithm is proposed to construct the optimal multi-hop clustering architecture in energy harvesting WSNs, with the goal of achieving perpetual network operation. All cluster heads (CHs in the network act as routers to transmit data to base station (BS cooperatively by a multi-hop communication method. In addition, by analyzing the energy consumption of intra- and inter-cluster data transmission, we give the energy neutrality constraints. Under these constraints, every sensor node can work in an energy neutral state, which in turn provides perpetual network operation. Furthermore, the minimum network data transmission cycle is mathematically derived using convex optimization techniques while the network information gathering is maximal. Simulation results show that our protocol can achieve perpetual network operation, so that the consistent data delivery is guaranteed. In addition, substantial improvements on the performance of network throughput are also achieved as compared to the famous traditional clustering protocol LEACH and recent energy harvesting aware clustering protocols.
Unsupervised Cryo-EM Data Clustering through Adaptively Constrained K-Means Algorithm.
Xu, Yaofang; Wu, Jiayi; Yin, Chang-Cheng; Mao, Youdong
2016-01-01
In single-particle cryo-electron microscopy (cryo-EM), K-means clustering algorithm is widely used in unsupervised 2D classification of projection images of biological macromolecules. 3D ab initio reconstruction requires accurate unsupervised classification in order to separate molecular projections of distinct orientations. Due to background noise in single-particle images and uncertainty of molecular orientations, traditional K-means clustering algorithm may classify images into wrong classes and produce classes with a large variation in membership. Overcoming these limitations requires further development on clustering algorithms for cryo-EM data analysis. We propose a novel unsupervised data clustering method building upon the traditional K-means algorithm. By introducing an adaptive constraint term in the objective function, our algorithm not only avoids a large variation in class sizes but also produces more accurate data clustering. Applications of this approach to both simulated and experimental cryo-EM data demonstrate that our algorithm is a significantly improved alterative to the traditional K-means algorithm in single-particle cryo-EM analysis.
International Nuclear Information System (INIS)
Lalush, D.S.; Tsui, B.M.W.; Karimi, S.S.
1996-01-01
We evaluate fast reconstruction algorithms including ordered subsets-EM (OS-EM) and Rescaled Block Iterative EM (RBI-EM) in fully 3D SPECT applications on the basis of their convergence and resolution recovery properties as iterations proceed. Using a 3D computer-simulated phantom consisting of 3D Gaussian objects, we simulated projection data that includes only the effects of sampling and detector response of a parallel-hole collimator. Reconstructions were performed using each of the three algorithms (ML-EM, OS-EM, and RBI-EM) modeling the 3D detector response in the projection function. Resolution recovery was evaluated by fitting Gaussians to each of the four objects in the iterated image estimates at selected intervals. Results show that OS-EM and RBI-EM behave identically in this case; their resolution recovery results are virtually indistinguishable. Their resolution behavior appears to be very similar to that of ML-EM, but accelerated by a factor of twenty. For all three algorithms, smaller objects take more iterations to converge. Next, we consider the effect noise has on convergence. For both noise-free and noisy data, we evaluate the log likelihood function at each subiteration of OS-EM and RBI-EM, and at each iteration of ML-EM. With noisy data, both OS-EM and RBI-EM give results for which the log-likelihood function oscillates. Especially for 180-degree acquisitions, RBI-EM oscillates less than OS-EM. Both OS-EM and RBI-EM appear to converge to solutions, but not to the ML solution. We conclude that both OS-EM and RBI-EM can be effective algorithms for fully 3D SPECT reconstruction. Both recover resolution similarly to ML-EM, only more quickly
Directory of Open Access Journals (Sweden)
Jurgen A. Doornik
2017-11-01
Full Text Available This paper provides some test cases, called circuits, for the evaluation of Gaussian likelihood maximization algorithms of the cointegrated vector autoregressive model. Both I(1 and I(2 models are considered. The performance of algorithms is compared first in terms of effectiveness, defined as the ability to find the overall maximum. The next step is to compare their efficiency and reliability across experiments. The aim of the paper is to commence a collective learning project by the profession on the actual properties of algorithms for cointegrated vector autoregressive model estimation, in order to improve their quality and, as a consequence, also the reliability of empirical research.
Energy Technology Data Exchange (ETDEWEB)
Machado-Neto, L. V. B.; Cabral, C. V. T.; Diniz, A. S. A. C.; Cortizo, P. C.; Oliveira-Filho, D.
2004-07-01
The maximization of the efficiency in the energy conversion is essential into the developing of technical and economic sustainability of photovoltaic solar energy systems. In this paper is realized the study of a power maximization technique for photovoltaic generators. The power maximization technique explored in this paper is the Maximum Power Point Tracking (MPPT). There are different strategies being studied currently; this work consists of the development of an electronic converter prototype for MPPT, including the developing of the tracking algorithm implemented in a microcontroller. It is also realized a simulation of the system and a prototype was assembled and the first results are presented here. (Author)
Al-Jabr, Ahmad Ali; Alsunaidi, Mohammad A.; Ng, Tien Khee; Ooi, Boon S.
2013-01-01
In this paper, an finite-difference time-domain (FDTD) algorithm for simulating propagation of EM waves in anisotropic material is presented. The algorithm is based on the auxiliary differential equation and the general polarization formulation. In anisotropic materials, electric fields are coupled and elements in the permittivity tensor are, in general, multiterm dispersive. The presented algorithm resolves the field coupling using a formulation based on electric polarizations. It also offers a simple procedure for the treatment of multiterm dispersion in the FDTD scheme. The algorithm is tested by simulating wave propagation in 1-D magnetized plasma showing excellent agreement with analytical solutions. Extension of the algorithm to multidimensional structures is straightforward. The presented algorithm is efficient and simple compared to other algorithms found in the literature. © 2012 IEEE.
Al-Jabr, Ahmad Ali
2013-03-01
In this paper, an finite-difference time-domain (FDTD) algorithm for simulating propagation of EM waves in anisotropic material is presented. The algorithm is based on the auxiliary differential equation and the general polarization formulation. In anisotropic materials, electric fields are coupled and elements in the permittivity tensor are, in general, multiterm dispersive. The presented algorithm resolves the field coupling using a formulation based on electric polarizations. It also offers a simple procedure for the treatment of multiterm dispersion in the FDTD scheme. The algorithm is tested by simulating wave propagation in 1-D magnetized plasma showing excellent agreement with analytical solutions. Extension of the algorithm to multidimensional structures is straightforward. The presented algorithm is efficient and simple compared to other algorithms found in the literature. © 2012 IEEE.
Papaconstadopoulos, P; Levesque, I R; Maglieri, R; Seuntjens, J
2016-02-07
Direct determination of the source intensity distribution of clinical linear accelerators is still a challenging problem for small field beam modeling. Current techniques most often involve special equipment and are difficult to implement in the clinic. In this work we present a maximum-likelihood expectation-maximization (MLEM) approach to the source reconstruction problem utilizing small fields and a simple experimental set-up. The MLEM algorithm iteratively ray-traces photons from the source plane to the exit plane and extracts corrections based on photon fluence profile measurements. The photon fluence profiles were determined by dose profile film measurements in air using a high density thin foil as build-up material and an appropriate point spread function (PSF). The effect of other beam parameters and scatter sources was minimized by using the smallest field size ([Formula: see text] cm(2)). The source occlusion effect was reproduced by estimating the position of the collimating jaws during this process. The method was first benchmarked against simulations for a range of typical accelerator source sizes. The sources were reconstructed with an accuracy better than 0.12 mm in the full width at half maximum (FWHM) to the respective electron sources incident on the target. The estimated jaw positions agreed within 0.2 mm with the expected values. The reconstruction technique was also tested against measurements on a Varian Novalis Tx linear accelerator and compared to a previously commissioned Monte Carlo model. The reconstructed FWHM of the source agreed within 0.03 mm and 0.11 mm to the commissioned electron source in the crossplane and inplane orientations respectively. The impact of the jaw positioning, experimental and PSF uncertainties on the reconstructed source distribution was evaluated with the former presenting the dominant effect.
Use of the AIC with the EM algorithm: A demonstration of a probability model selection technique
Energy Technology Data Exchange (ETDEWEB)
Glosup, J.G.; Axelrod M.C. [Lawrence Livermore National Lab., CA (United States)
1994-11-15
The problem of discriminating between two potential probability models, a Gaussian distribution and a mixture of Gaussian distributions, is considered. The focus of our interest is a case where the models are potentially non-nested and the parameters of the mixture model are estimated through the EM algorithm. The AIC, which is frequently used as a criterion for discriminating between non-nested models, is modified to work with the EM algorithm and is shown to provide a model selection tool for this situation. A particular problem involving an infinite mixture distribution known as Middleton`s Class A model is used to demonstrate the effectiveness and limitations of this method.
High-dimensional cluster analysis with the Masked EM Algorithm
Kadir, Shabnam N.; Goodman, Dan F. M.; Harris, Kenneth D.
2014-01-01
Cluster analysis faces two problems in high dimensions: first, the “curse of dimensionality” that can lead to overfitting and poor generalization performance; and second, the sheer time taken for conventional algorithms to process large amounts of high-dimensional data. We describe a solution to these problems, designed for the application of “spike sorting” for next-generation high channel-count neural probes. In this problem, only a small subset of features provide information about the cluster member-ship of any one data vector, but this informative feature subset is not the same for all data points, rendering classical feature selection ineffective. We introduce a “Masked EM” algorithm that allows accurate and time-efficient clustering of up to millions of points in thousands of dimensions. We demonstrate its applicability to synthetic data, and to real-world high-channel-count spike sorting data. PMID:25149694
Adachi, Kohei
2013-01-01
Rubin and Thayer ("Psychometrika," 47:69-76, 1982) proposed the EM algorithm for exploratory and confirmatory maximum likelihood factor analysis. In this paper, we prove the following fact: the EM algorithm always gives a proper solution with positive unique variances and factor correlations with absolute values that do not exceed one,…
An Efficient Forward-Reverse EM Algorithm for Statistical Inference in Stochastic Reaction Networks
Bayer, Christian
2016-01-06
In this work [1], we present an extension of the forward-reverse algorithm by Bayer and Schoenmakers [2] to the context of stochastic reaction networks (SRNs). We then apply this bridge-generation technique to the statistical inference problem of approximating the reaction coefficients based on discretely observed data. To this end, we introduce an efficient two-phase algorithm in which the first phase is deterministic and it is intended to provide a starting point for the second phase which is the Monte Carlo EM Algorithm.
Simulating Evolution of <em>Drosophila melanogaster Ebonyem> Mutants Using a Genetic Algorithm
DEFF Research Database (Denmark)
Helles, Glennie
2009-01-01
Genetic algorithms are generally quite easy to understand and work with, and they are a popular choice in many cases. One area in which genetic algorithms are widely and successfully used is artificial life where they are used to simulate evolution of artificial creatures. However, despite...... their suggestive name, simplicity and popularity in artificial life, they do not seem to have gained a footing within the field of population genetics to simulate evolution of real organisms --- possibly because genetic algorithms are based on a rather crude simplification of the evolutionary mechanisms known...
Singh, Ranjan Kumar; Rinawa, Moti Lal
2018-04-01
The residual stresses arising in fiber-reinforced laminates during their curing in closed molds lead to changes in the composites after their removal from the molds and cooling. One of these dimensional changes of angle sections is called springback. The parameters such as lay-up, stacking sequence, material system, cure temperature, thickness etc play important role in it. In present work, it is attempted to optimize lay-up and stacking sequence for maximization of flexural stiffness and minimization of springback angle. The search algorithms are employed to obtain best sequence through repair strategy such as swap. A new search algorithm, termed as lay-up search algorithm (LSA) is also proposed, which is an extension of permutation search algorithm (PSA). The efficacy of PSA and LSA is tested on the laminates with a range of lay-ups. A computer code is developed on MATLAB implementing the above schemes. Also, the strategies for multi objective optimization using search algorithms are suggested and tested.
Directory of Open Access Journals (Sweden)
Rabha W. Ibrahim
2018-01-01
Full Text Available The maximum min utility function (MMUF problem is an important representative of a large class of cloud computing systems (CCS. Having numerous applications in practice, especially in economy and industry. This paper introduces an effective solution-based search (SBS algorithm for solving the problem MMUF. First, we suggest a new formula of the utility function in term of the capacity of the cloud. We formulate the capacity in CCS, by using a fractional diffeo-integral equation. This equation usually describes the flow of CCS. The new formula of the utility function is modified recent active utility functions. The suggested technique first creates a high-quality initial solution by eliminating the less promising components, and then develops the quality of the achieved solution by the summation search solution (SSS. This method is considered by the Mittag-Leffler sum as hash functions to determine the position of the agent. Experimental results commonly utilized in the literature demonstrate that the proposed algorithm competes approvingly with the state-of-the-art algorithms both in terms of solution quality and computational efficiency.
Directory of Open Access Journals (Sweden)
Tiansong Cui
2016-01-01
Full Text Available Dynamic energy pricing provides a promising solution for the utility companies to incentivize energy users to perform demand side management in order to minimize their electric bills. Moreover, the emerging decentralized smart grid, which is a likely infrastructure scenario for future electrical power networks, allows energy consumers to select their energy provider from among multiple utility companies in any billing period. This paper thus starts by considering an oligopolistic energy market with multiple non-cooperative (competitive utility companies, and addresses the problem of determining dynamic energy prices for every utility company in this market based on a modified Bertrand Competition Model of user behaviors. Two methods of dynamic energy pricing are proposed for a utility company to maximize its total profit. The first method finds the greatest lower bound on the total profit that can be achieved by the utility company, whereas the second method finds the best response of a utility company to dynamic pricing policies that the other companies have adopted in previous billing periods. To exploit the advantages of each method while compensating their shortcomings, an adaptive dynamic pricing policy is proposed based on a machine learning technique, which finds a good balance between invocations of the two aforesaid methods. Experimental results show that the adaptive policy results in consistently high profit for the utility company no matter what policies are employed by the other companies.
Finite sample performance of the E-M algorithm for ranks data modelling
Directory of Open Access Journals (Sweden)
Angela D'Elia
2007-10-01
Full Text Available We check the finite sample performance of the maximum likelihood estimators of the parameters of a mixture distribution recently introduced for modelling ranks/preference data. The estimates are derived by the E-M algorithm and the performance is evaluated both from an univariate and bivariate points of view. While the results are generally acceptable as far as it concerns the bias, the Monte Carlo experiment shows a different behaviour of the estimators efficiency for the two parameters of the mixture, mainly depending upon their location in the admissible parametric space. Some operative suggestions conclude the paer.
International Nuclear Information System (INIS)
Jones, W.F.; Byars, L.G.; Casey, M.E.
1988-01-01
A digital electronic architecture for parallel processing of the expectation maximization (EM) algorithm for Positron Emission tomography (PET) image reconstruction is proposed. Rapid (0.2 second) EM iterations on high resolution (256 x 256) images are supported. Arrays of two very large scale integration (VLSI) chips perform forward and back projection calculations. A description of the architecture is given, including data flow and partitioning relevant to EM and parallel processing. EM images shown are produced with software simulating the proposed hardware reconstruction algorithm. Projected cost of the system is estimated to be small in comparison to the cost of current PET scanners
Chow, Sy-Miin; Lu, Zhaohua; Sherwood, Andrew; Zhu, Hongtu
2016-03-01
The past decade has evidenced the increased prevalence of irregularly spaced longitudinal data in social sciences. Clearly lacking, however, are modeling tools that allow researchers to fit dynamic models to irregularly spaced data, particularly data that show nonlinearity and heterogeneity in dynamical structures. We consider the issue of fitting multivariate nonlinear differential equation models with random effects and unknown initial conditions to irregularly spaced data. A stochastic approximation expectation-maximization algorithm is proposed and its performance is evaluated using a benchmark nonlinear dynamical systems model, namely, the Van der Pol oscillator equations. The empirical utility of the proposed technique is illustrated using a set of 24-h ambulatory cardiovascular data from 168 men and women. Pertinent methodological challenges and unresolved issues are discussed.
Mino, H
2007-01-01
To estimate the parameters, the impulse response (IR) functions of some linear time-invariant systems generating intensity processes, in Shot-Noise-Driven Doubly Stochastic Poisson Process (SND-DSPP) in which multivariate presynaptic spike trains and postsynaptic spike trains can be assumed to be modeled by the SND-DSPPs. An explicit formula for estimating the IR functions from observations of multivariate input processes of the linear systems and the corresponding counting process (output process) is derived utilizing the expectation maximization (EM) algorithm. The validity of the estimation formula was verified through Monte Carlo simulations in which two presynaptic spike trains and one postsynaptic spike train were assumed to be observable. The IR functions estimated on the basis of the proposed identification method were close to the true IR functions. The proposed method will play an important role in identifying the input-output relationship of pre- and postsynaptic neural spike trains in practical situations.
DEFF Research Database (Denmark)
Christensen, Lars P.B.; Larsen, Jan
2006-01-01
A general Variational Bayesian framework for iterative data and parameter estimation for coherent detection is introduced as a generalization of the EM-algorithm. Explicit solutions are given for MIMO channel estimation with Gaussian prior and noise covariance estimation with inverse-Wishart prior....... Simulation of a GSM-like system provides empirical proof that the VBEM-algorithm is able to provide better performance than the EM-algorithm. However, if the posterior distribution is highly peaked, the VBEM-algorithm approaches the EM-algorithm and the gain disappears. The potential gain is therefore...
A structural dynamic factor model for the effects of monetary policy estimated by the EM algorithm
DEFF Research Database (Denmark)
Bork, Lasse
This paper applies the maximum likelihood based EM algorithm to a large-dimensional factor analysis of US monetary policy. Specifically, economy-wide effects of shocks to the US federal funds rate are estimated in a structural dynamic factor model in which 100+ US macroeconomic and financial time...... series are driven by the joint dynamics of the federal funds rate and a few correlated dynamic factors. This paper contains a number of methodological contributions to the existing literature on data-rich monetary policy analysis. Firstly, the identification scheme allows for correlated factor dynamics...... as opposed to the orthogonal factors resulting from the popular principal component approach to structural factor models. Correlated factors are economically more sensible and important for a richer monetary policy transmission mechanism. Secondly, I consider both static factor loadings as well as dynamic...
Indian Academy of Sciences (India)
polynomial) division have been found in Vedic Mathematics which are dated much before Euclid's algorithm. A programming language Is used to describe an algorithm for execution on a computer. An algorithm expressed using a programming.
A fast EM algorithm for BayesA-like prediction of genomic breeding values.
Directory of Open Access Journals (Sweden)
Xiaochen Sun
Full Text Available Prediction accuracies of estimated breeding values for economically important traits are expected to benefit from genomic information. Single nucleotide polymorphism (SNP panels used in genomic prediction are increasing in density, but the Markov Chain Monte Carlo (MCMC estimation of SNP effects can be quite time consuming or slow to converge when a large number of SNPs are fitted simultaneously in a linear mixed model. Here we present an EM algorithm (termed "fastBayesA" without MCMC. This fastBayesA approach treats the variances of SNP effects as missing data and uses a joint posterior mode of effects compared to the commonly used BayesA which bases predictions on posterior means of effects. In each EM iteration, SNP effects are predicted as a linear combination of best linear unbiased predictions of breeding values from a mixed linear animal model that incorporates a weighted marker-based realized relationship matrix. Method fastBayesA converges after a few iterations to a joint posterior mode of SNP effects under the BayesA model. When applied to simulated quantitative traits with a range of genetic architectures, fastBayesA is shown to predict GEBV as accurately as BayesA but with less computing effort per SNP than BayesA. Method fastBayesA can be used as a computationally efficient substitute for BayesA, especially when an increasing number of markers bring unreasonable computational burden or slow convergence to MCMC approaches.
Indian Academy of Sciences (India)
Abstract. It is shown that (i) every probability density is the unique maximizer of relative entropy in an appropriate class and (ii) in the class of all pdf f that satisfy. ∫ fhi dμ = λi for i = 1, 2,...,...k the maximizer of entropy is an f0 that is pro- portional to exp(. ∑ ci hi ) for some choice of ci . An extension of this to a continuum of.
Indian Academy of Sciences (India)
It is shown that (i) every probability density is the unique maximizer of relative entropy in an appropriate class and (ii) in the class of all pdf that satisfy ∫ f h i d = i for i = 1 , 2 , … , … k the maximizer of entropy is an f 0 that is proportional to exp ( ∑ c i h i ) for some choice of c i . An extension of this to a continuum of ...
Moslemi, Vahid; Ashoor, Mansour
2017-10-01
One of the major problems associated with parallel hole collimators (PCs) is the trade-off between their resolution and sensitivity. To solve this problem, a novel PC - namely, extended parallel hole collimator (EPC) - was proposed, in which particular trapezoidal denticles were increased upon septa on the side of the detector. In this study, an EPC was designed and its performance was compared with that of two PCs, PC35 and PC41, with a hole size of 1.5 mm and hole lengths of 35 and 41 mm, respectively. The Monte Carlo method was used to calculate the important parameters such as resolution, sensitivity, scattering, and penetration ratio. A Jaszczak phantom was also simulated to evaluate the resolution and contrast of tomographic images, which were produced by the EPC6, PC35, and PC41 using the Monte Carlo N-particle version 5 code, and tomographic images were reconstructed by using maximum likelihood expectation maximization algorithm. Sensitivity of the EPC6 was increased by 20.3% in comparison with that of the PC41 at the identical spatial resolution and full-width at tenth of maximum here. Moreover, the penetration and scattering ratio of the EPC6 was 1.2% less than that of the PC41. The simulated phantom images show that the EPC6 increases contrast-resolution and contrast-to-noise ratio compared with those of PC41 and PC35. When compared with PC41 and PC35, EPC6 improved trade-off between resolution and sensitivity, reduced penetrating and scattering ratios, and produced images with higher quality. EPC6 can be used to increase detectability of more details in nuclear medicine images.
Indian Academy of Sciences (India)
to as 'divide-and-conquer'. Although there has been a large effort in realizing efficient algorithms, there are not many universally accepted algorithm design paradigms. In this article, we illustrate algorithm design techniques such as balancing, greedy strategy, dynamic programming strategy, and backtracking or traversal of ...
Finding Maximal Quasiperiodicities in Strings
DEFF Research Database (Denmark)
Brodal, Gerth Stølting; Pedersen, Christian N. S.
2000-01-01
of length n in time O(n log n) and space O(n). Our algorithm uses the suffix tree as the fundamental data structure combined with efficient methods for merging and performing multiple searches in search trees. Besides finding all maximal quasiperiodic substrings, our algorithm also marks the nodes......Apostolico and Ehrenfeucht defined the notion of a maximal quasiperiodic substring and gave an algorithm that finds all maximal quasiperiodic substrings in a string of length n in time O(n log2 n). In this paper we give an algorithm that finds all maximal quasiperiodic substrings in a string...... in the suffix tree that have a superprimitive path-label....
Indian Academy of Sciences (India)
ticians but also forms the foundation of computer science. Two ... with methods of developing algorithms for solving a variety of problems but ... applications of computers in science and engineer- ... numerical calculus are as important. We will ...
Energy Technology Data Exchange (ETDEWEB)
Razali, Azhani Mohd, E-mail: azhani@nuclearmalaysia.gov.my; Abdullah, Jaafar, E-mail: jaafar@nuclearmalaysia.gov.my [Plant Assessment Technology (PAT) Group, Industrial Technology Division, Malaysian Nuclear Agency, Bangi, 43000 Kajang (Malaysia)
2015-04-29
Single Photon Emission Computed Tomography (SPECT) is a well-known imaging technique used in medical application, and it is part of medical imaging modalities that made the diagnosis and treatment of disease possible. However, SPECT technique is not only limited to the medical sector. Many works are carried out to adapt the same concept by using high-energy photon emission to diagnose process malfunctions in critical industrial systems such as in chemical reaction engineering research laboratories, as well as in oil and gas, petrochemical and petrochemical refining industries. Motivated by vast applications of SPECT technique, this work attempts to study the application of SPECT on a Pebble Bed Reactor (PBR) using numerical phantom of pebbles inside the PBR core. From the cross-sectional images obtained from SPECT, the behavior of pebbles inside the core can be analyzed for further improvement of the PBR design. As the quality of the reconstructed image is largely dependent on the algorithm used, this work aims to compare two image reconstruction algorithms for SPECT, namely the Expectation Maximization Algorithm and the Exact Inversion Formula. The results obtained from the Exact Inversion Formula showed better image contrast and sharpness, and shorter computational time compared to the Expectation Maximization Algorithm.
International Nuclear Information System (INIS)
Razali, Azhani Mohd; Abdullah, Jaafar
2015-01-01
Single Photon Emission Computed Tomography (SPECT) is a well-known imaging technique used in medical application, and it is part of medical imaging modalities that made the diagnosis and treatment of disease possible. However, SPECT technique is not only limited to the medical sector. Many works are carried out to adapt the same concept by using high-energy photon emission to diagnose process malfunctions in critical industrial systems such as in chemical reaction engineering research laboratories, as well as in oil and gas, petrochemical and petrochemical refining industries. Motivated by vast applications of SPECT technique, this work attempts to study the application of SPECT on a Pebble Bed Reactor (PBR) using numerical phantom of pebbles inside the PBR core. From the cross-sectional images obtained from SPECT, the behavior of pebbles inside the core can be analyzed for further improvement of the PBR design. As the quality of the reconstructed image is largely dependent on the algorithm used, this work aims to compare two image reconstruction algorithms for SPECT, namely the Expectation Maximization Algorithm and the Exact Inversion Formula. The results obtained from the Exact Inversion Formula showed better image contrast and sharpness, and shorter computational time compared to the Expectation Maximization Algorithm
Razali, Azhani Mohd; Abdullah, Jaafar
2015-04-01
Single Photon Emission Computed Tomography (SPECT) is a well-known imaging technique used in medical application, and it is part of medical imaging modalities that made the diagnosis and treatment of disease possible. However, SPECT technique is not only limited to the medical sector. Many works are carried out to adapt the same concept by using high-energy photon emission to diagnose process malfunctions in critical industrial systems such as in chemical reaction engineering research laboratories, as well as in oil and gas, petrochemical and petrochemical refining industries. Motivated by vast applications of SPECT technique, this work attempts to study the application of SPECT on a Pebble Bed Reactor (PBR) using numerical phantom of pebbles inside the PBR core. From the cross-sectional images obtained from SPECT, the behavior of pebbles inside the core can be analyzed for further improvement of the PBR design. As the quality of the reconstructed image is largely dependent on the algorithm used, this work aims to compare two image reconstruction algorithms for SPECT, namely the Expectation Maximization Algorithm and the Exact Inversion Formula. The results obtained from the Exact Inversion Formula showed better image contrast and sharpness, and shorter computational time compared to the Expectation Maximization Algorithm.
A system for the 3D reconstruction of retracted-septa PET data using the EM algorithm
International Nuclear Information System (INIS)
Johnson, C.A.; Yan, Y.; Carson, R.E.; Martino, R.L.; Daube-Witherspoon, M.E.
1995-01-01
The authors have implemented the EM reconstruction algorithm for volume acquisition from current generation retracted-septa PET scanners. Although the software was designed for a GE Advance scanner, it is easily adaptable to other 3D scanners. The reconstruction software was written for an Intel iPSC/860 parallel computer with 128 compute nodes. Running on 32 processors, the algorithm requires approximately 55 minutes per iteration to reconstruct a 128 x 128 x 35 image. No projection data compression schemes or other approximations were used in the implementation. Extensive use of EM system matrix (C ij ) symmetries (including the 8-fold in-plane symmetries, 2-fold axial symmetries, and axial parallel line redundancies) reduces the storage cost by a factor of 188. The parallel algorithm operates on distributed projection data which are decomposed by base-symmetry angles. Symmetry operators copy and index the C ij chord to the form required for the particular symmetry. The use of asynchronous reads, lookup tables, and optimized image indexing improves computational performance
Indian Academy of Sciences (India)
algorithm design technique called 'divide-and-conquer'. One of ... Turtle graphics, September. 1996. 5. ... whole list named 'PO' is a pointer to the first element of the list; ..... Program for computing matrices X and Y and placing the result in C *).
Indian Academy of Sciences (India)
algorithm that it is implicitly understood that we know how to generate the next natural ..... Explicit comparisons are made in line (1) where maximum and minimum is ... It can be shown that the function T(n) = 3/2n -2 is the solution to the above ...
Indian Academy of Sciences (India)
will become clear in the next article when we discuss a simple logo like programming language. ... Rod B may be used as an auxiliary store. The problem is to find an algorithm which performs this task. ... No disks are moved from A to Busing C as auxiliary rod. • move _disk (A, C);. (No + l)th disk is moved from A to C directly ...
An Efficient Forward-Reverse EM Algorithm for Statistical Inference in Stochastic Reaction Networks
Bayer, Christian; Moraes, Alvaro; Tempone, Raul; Vilanova, Pedro
2016-01-01
In this work [1], we present an extension of the forward-reverse algorithm by Bayer and Schoenmakers [2] to the context of stochastic reaction networks (SRNs). We then apply this bridge-generation technique to the statistical inference problem
Maximal Conflict Set Enumeration Algorithm Based on Locality of Petri Nets%基于Pe tri网局部性的极大冲突集枚举算法
Institute of Scientific and Technical Information of China (English)
潘理; 郑红; 刘显明; 杨勃
2016-01-01
冲突是Petri网研究的重要主题。目前Petri网冲突研究主要集中于冲突建模和冲突消解策略，而对冲突问题本身的计算复杂性却很少关注。提出Petri网的冲突集问题，并证明冲突集问题是NP（Non-deterministic Polyno-mial）完全的。提出极大冲突集动态枚举算法，该算法基于当前标识的所有极大冲突集，利用Petri网实施局部性，仅计算下一标识中受局部性影响的极大冲突集，从而避免重新枚举所有极大冲突集。该算法时间复杂度为O（m2 n），m是当前标识的极大冲突集数目，n是变迁数。最后证明自由选择网、非对称选择网的极大冲突集枚举算法复杂度可降至O（n2）。极大冲突集枚举算法研究将为Petri网冲突问题的算法求解提供理论参考。%Conflict is an essential concept in Petri net theory.The existing research focuses on the modelling and resolu-tion strategies of conflict problems,but less on the computational complexity of the problems theirselves.In this paper,we pro-pose the conflict set problem for Petri nets,and prove that the conflict set problem is NP-complete.Furthermore,we present a dynamic algorithm for the maximal conflict set enumeration.Our algorithm only computes those conflict sets that are affected by local firing,which avoids enumerating all maximal conflict sets at each marking.The algorithm needs time O(m2n)where m is the number of maximal conflict sets at the current marking and n is the number of transitions.Finally,we show that the maximal conflict set enumeration problem can be solved in O(n2)for free-choice nets and asymmetric choice nets.The results on complexity of thel conflict set problem provide a theoretical reference for solving conflict problems of Petri nets.
Sensor Data Quality and Angular Rate Down-Selection Algorithms on SLS EM-1
Park, Thomas; Smith, Austin; Oliver, T. Emerson
2018-01-01
The NASA Space Launch System Block 1 launch vehicle is equipped with an Inertial Navigation System (INS) and multiple Rate Gyro Assemblies (RGA) that are used in the Guidance, Navigation, and Control (GN&C) algorithms. The INS provides the inertial position, velocity, and attitude of the vehicle along with both angular rate and specific force measurements. Additionally, multiple sets of co-located rate gyros supply angular rate data. The collection of angular rate data, taken along the launch vehicle, is used to separate out vehicle motion from flexible body dynamics. Since the system architecture uses redundant sensors, the capability was developed to evaluate the health (or validity) of the independent measurements. A suite of Sensor Data Quality (SDQ) algorithms is responsible for assessing the angular rate data from the redundant sensors. When failures are detected, SDQ will take the appropriate action and disqualify or remove faulted sensors from forward processing. Additionally, the SDQ algorithms contain logic for down-selecting the angular rate data used by the GNC software from the set of healthy measurements. This paper explores the trades and analyses that were performed in selecting a set of robust fault-detection algorithms included in the GN&C flight software. These trades included both an assessment of hardware-provided health and status data as well as an evaluation of different algorithms based on time-to-detection, type of failures detected, and probability of detecting false positives. We then provide an overview of the algorithms used for both fault-detection and measurement down selection. We next discuss the role of trajectory design, flexible-body models, and vehicle response to off-nominal conditions in setting the detection thresholds. Lastly, we present lessons learned from software integration and hardware-in-the-loop testing.
A Study of Wind Turbine Comprehensive Operational Assessment Model Based on EM-PCA Algorithm
Zhou, Minqiang; Xu, Bin; Zhan, Yangyan; Ren, Danyuan; Liu, Dexing
2018-01-01
To assess wind turbine performance accurately and provide theoretical basis for wind farm management, a hybrid assessment model based on Entropy Method and Principle Component Analysis (EM-PCA) was established, which took most factors of operational performance into consideration and reach to a comprehensive result. To verify the model, six wind turbines were chosen as the research objects, the ranking obtained by the method proposed in the paper were 4#>6#>1#>5#>2#>3#, which are completely in conformity with the theoretical ranking, which indicates that the reliability and effectiveness of the EM-PCA method are high. The method could give guidance for processing unit state comparison among different units and launching wind farm operational assessment.
Directory of Open Access Journals (Sweden)
Enrique Calderín-Ojeda
2017-11-01
Full Text Available Generalized linear models might not be appropriate when the probability of extreme events is higher than that implied by the normal distribution. Extending the method for estimating the parameters of a double Pareto lognormal distribution (DPLN in Reed and Jorgensen (2004, we develop an EM algorithm for the heavy-tailed Double-Pareto-lognormal generalized linear model. The DPLN distribution is obtained as a mixture of a lognormal distribution with a double Pareto distribution. In this paper the associated generalized linear model has the location parameter equal to a linear predictor which is used to model insurance claim amounts for various data sets. The performance is compared with those of the generalized beta (of the second kind and lognorma distributions.
AUC-Maximizing Ensembles through Metalearning.
LeDell, Erin; van der Laan, Mark J; Petersen, Maya
2016-05-01
Area Under the ROC Curve (AUC) is often used to measure the performance of an estimator in binary classification problems. An AUC-maximizing classifier can have significant advantages in cases where ranking correctness is valued or if the outcome is rare. In a Super Learner ensemble, maximization of the AUC can be achieved by the use of an AUC-maximining metalearning algorithm. We discuss an implementation of an AUC-maximization technique that is formulated as a nonlinear optimization problem. We also evaluate the effectiveness of a large number of different nonlinear optimization algorithms to maximize the cross-validated AUC of the ensemble fit. The results provide evidence that AUC-maximizing metalearners can, and often do, out-perform non-AUC-maximizing metalearning methods, with respect to ensemble AUC. The results also demonstrate that as the level of imbalance in the training data increases, the Super Learner ensemble outperforms the top base algorithm by a larger degree.
Institute of Scientific and Technical Information of China (English)
赵星; 王逊; 黄树成
2018-01-01
Through the improvement of the missing value filling algorithm based on K-means clustering,a filling algorithm based on distance maximization and missing data clustering is proposed in this paper.First of all,the original filling algorithm needs to enter the number of clusters in advance.To solve this problem,an improved K-means clustering algorithm is designed.It determines the cluster centers by the maximum distance between the data.It will automatically generate the number of clusters,and improve the efficiency of clustering.Secondly,the clustering distance function is improved.The improved algorithm can be used to cluster the missing value records,thus simplifying the steps of the original filling algorithm.Through experiments on STUDENT ALCOHOL CONSUMPTION data set,experimental results show that the proposed algorithm can improve efficiency and effectively fill the missing data at the same time.%通过对基于K-means聚类的缺失值填充算法的改进,文中提出了基于距离最大化和缺失数据聚类的填充算法.首先,针对原填充算法需要提前输入聚类个数这一缺点,设计了改进的K-means聚类算法:使用数据间的最大距离确定聚类中心,自动产生聚类个数,提高聚类效果;其次,对聚类的距离函数进行改进,采用部分距离度量方式,改进后的算法可以对含有缺失值的记录进行聚类,简化原填充算法步骤.通过对STUDENT ALCOHOL CONSUMPTION数据集的实验,结果证明了该算法能够在提高效率的同时,有效地填充缺失数据.
EMHP: an accurate automated hole masking algorithm for single-particle cryo-EM image processing.
Berndsen, Zachary; Bowman, Charles; Jang, Haerin; Ward, Andrew B
2017-12-01
The Electron Microscopy Hole Punch (EMHP) is a streamlined suite of tools for quick assessment, sorting and hole masking of electron micrographs. With recent advances in single-particle electron cryo-microscopy (cryo-EM) data processing allowing for the rapid determination of protein structures using a smaller computational footprint, we saw the need for a fast and simple tool for data pre-processing that could run independent of existing high-performance computing (HPC) infrastructures. EMHP provides a data preprocessing platform in a small package that requires minimal python dependencies to function. https://www.bitbucket.org/chazbot/emhp Apache 2.0 License. bowman@scripps.edu. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.
Suppression of EM Fields using Active Control Algorithms and MIMO Antenna System
Directory of Open Access Journals (Sweden)
A. Mohammed
2004-09-01
Full Text Available Active methods for attenuating acoustic pressure fields have beensuccessfully used in many applications. In this paper we investigatesome of these active control methods in combination with a MIMO antennasystem in order to assess their validity and performance when appliedto electromagnetic fields. The application that we evaluated in thispaper is a model of a mobile phone equipped with one ordinarytransmitting antenna and two actuator-antennas which purpose is toreduce the electromagnetic field at a specific area in space (e.g. atthe human head. Simulation results show the promise of using theadaptive active control algorithms and MIMO system to attenuate theelectromagnetic field power density.
Models and Algorithms for Tracking Target with Coordinated Turn Motion
Directory of Open Access Journals (Sweden)
Xianghui Yuan
2014-01-01
Full Text Available Tracking target with coordinated turn (CT motion is highly dependent on the models and algorithms. First, the widely used models are compared in this paper—coordinated turn (CT model with known turn rate, augmented coordinated turn (ACT model with Cartesian velocity, ACT model with polar velocity, CT model using a kinematic constraint, and maneuver centered circular motion model. Then, in the single model tracking framework, the tracking algorithms for the last four models are compared and the suggestions on the choice of models for different practical target tracking problems are given. Finally, in the multiple models (MM framework, the algorithm based on expectation maximization (EM algorithm is derived, including both the batch form and the recursive form. Compared with the widely used interacting multiple model (IMM algorithm, the EM algorithm shows its effectiveness.
Profit maximization mitigates competition
DEFF Research Database (Denmark)
Dierker, Egbert; Grodal, Birgit
1996-01-01
We consider oligopolistic markets in which the notion of shareholders' utility is well-defined and compare the Bertrand-Nash equilibria in case of utility maximization with those under the usual profit maximization hypothesis. Our main result states that profit maximization leads to less price...... competition than utility maximization. Since profit maximization tends to raise prices, it may be regarded as beneficial for the owners as a whole. Moreover, if profit maximization is a good proxy for utility maximization, then there is no need for a general equilibrium analysis that takes the distribution...... of profits among consumers fully into account and partial equilibrium analysis suffices...
Maximizing Entropy over Markov Processes
DEFF Research Database (Denmark)
Biondi, Fabrizio; Legay, Axel; Nielsen, Bo Friis
2013-01-01
The channel capacity of a deterministic system with confidential data is an upper bound on the amount of bits of data an attacker can learn from the system. We encode all possible attacks to a system using a probabilistic specification, an Interval Markov Chain. Then the channel capacity...... as a reward function, a polynomial algorithm to verify the existence of an system maximizing entropy among those respecting a specification, a procedure for the maximization of reward functions over Interval Markov Chains and its application to synthesize an implementation maximizing entropy. We show how...... to use Interval Markov Chains to model abstractions of deterministic systems with confidential data, and use the above results to compute their channel capacity. These results are a foundation for ongoing work on computing channel capacity for abstractions of programs derived from code....
Maximizing entropy over Markov processes
DEFF Research Database (Denmark)
Biondi, Fabrizio; Legay, Axel; Nielsen, Bo Friis
2014-01-01
The channel capacity of a deterministic system with confidential data is an upper bound on the amount of bits of data an attacker can learn from the system. We encode all possible attacks to a system using a probabilistic specification, an Interval Markov Chain. Then the channel capacity...... as a reward function, a polynomial algorithm to verify the existence of a system maximizing entropy among those respecting a specification, a procedure for the maximization of reward functions over Interval Markov Chains and its application to synthesize an implementation maximizing entropy. We show how...... to use Interval Markov Chains to model abstractions of deterministic systems with confidential data, and use the above results to compute their channel capacity. These results are a foundation for ongoing work on computing channel capacity for abstractions of programs derived from code. © 2014 Elsevier...
Maximal lattice free bodies, test sets and the Frobenius problem
DEFF Research Database (Denmark)
Jensen, Anders Nedergaard; Lauritzen, Niels; Roune, Bjarke Hammersholt
Maximal lattice free bodies are maximal polytopes without interior integral points. Scarf initiated the study of maximal lattice free bodies relative to the facet normals in a fixed matrix. In this paper we give an efficient algorithm for computing the maximal lattice free bodies of an integral m...... method is inspired by the novel algorithm by Einstein, Lichtblau, Strzebonski and Wagon and the Groebner basis approach by Roune....
von Davier, Matthias
2016-01-01
This report presents results on a parallel implementation of the expectation-maximization (EM) algorithm for multidimensional latent variable models. The developments presented here are based on code that parallelizes both the E step and the M step of the parallel-E parallel-M algorithm. Examples presented in this report include item response…
Maximally incompatible quantum observables
Energy Technology Data Exchange (ETDEWEB)
Heinosaari, Teiko, E-mail: teiko.heinosaari@utu.fi [Turku Centre for Quantum Physics, Department of Physics and Astronomy, University of Turku, FI-20014 Turku (Finland); Schultz, Jussi, E-mail: jussi.schultz@gmail.com [Dipartimento di Matematica, Politecnico di Milano, Piazza Leonardo da Vinci 32, I-20133 Milano (Italy); Toigo, Alessandro, E-mail: alessandro.toigo@polimi.it [Dipartimento di Matematica, Politecnico di Milano, Piazza Leonardo da Vinci 32, I-20133 Milano (Italy); Istituto Nazionale di Fisica Nucleare, Sezione di Milano, Via Celoria 16, I-20133 Milano (Italy); Ziman, Mario, E-mail: ziman@savba.sk [RCQI, Institute of Physics, Slovak Academy of Sciences, Dúbravská cesta 9, 84511 Bratislava (Slovakia); Faculty of Informatics, Masaryk University, Botanická 68a, 60200 Brno (Czech Republic)
2014-05-01
The existence of maximally incompatible quantum observables in the sense of a minimal joint measurability region is investigated. Employing the universal quantum cloning device it is argued that only infinite dimensional quantum systems can accommodate maximal incompatibility. It is then shown that two of the most common pairs of complementary observables (position and momentum; number and phase) are maximally incompatible.
Maximally incompatible quantum observables
International Nuclear Information System (INIS)
Heinosaari, Teiko; Schultz, Jussi; Toigo, Alessandro; Ziman, Mario
2014-01-01
The existence of maximally incompatible quantum observables in the sense of a minimal joint measurability region is investigated. Employing the universal quantum cloning device it is argued that only infinite dimensional quantum systems can accommodate maximal incompatibility. It is then shown that two of the most common pairs of complementary observables (position and momentum; number and phase) are maximally incompatible.
Directory of Open Access Journals (Sweden)
Raquel Aparecida Pizolato
2007-09-01
Full Text Available Parafunctional habits, such as bruxism, are contributory factors for temporomandibular disorders (TMD. The aim of this study was to evaluate the maximal bite force (MBF in the presence of TMD and bruxism (TMDB in young adults. Twelve women (mean age 21.5 years and 7 men (mean age 22.4 years, composed the TMDB group. Ten healthy women and 9 men (mean age 21.4 and 22.4 years, respectively formed the control group. TMD symptoms were evaluated by a structured questionnaire and clinical signs/symptoms were evaluated during clinical examination. A visual analogical scale (VAS was applied for stress assessment. MBF was measured with a gnatodynamometer. The subjects were asked to bite 2 times with maximal effort, during 5 seconds, with a rest interval of about one minute. The highest values were considered. The data were analyzed with Shapiro-Wilks W-test, descriptive statistics, paired or unpaired t tests or Mann-Whitney tests when indicated, and Fisher's exact test (p Hábitos parafuncionais, como o bruxismo, podem contribuir para a disfunção temporomandibular (DTM. O objetivo deste trabalho foi avaliar a força de mordida máxima (FMM na presença de DTM e bruxismo (DTMB em adultos jovens. Doze mulheres (idade média de 21,5 anos e sete homens (idade média 22,4 anos compuseram o grupo DTMB. O grupo controle foi formado por 10 mulheres e 9 homens saudáveis, com idades médias de 21,4 e 22,4 anos, respectivamente. Os sintomas de DTM foram avaliados com um questionário estruturado, e os sinais/sintomas clínicos foram avaliados no exame clínico. Para avaliar estresse, utilizou-se a escala analógica visual (VAS. A FMM foi mensurada com gnatodinamômetro, e o participante foi orientado a morder com o máximo esforço durante 5 segundos, duas vezes, com intervalo de aproximadamente 1 minuto, considerando-se os valores máximos. Os dados foram analisados pelo teste de Shapiro-Wilks, estatística descritiva, teste t pareado e independente, Mann
Directory of Open Access Journals (Sweden)
Raqueli Biscayno Viecili
2011-12-01
Full Text Available OBJETIVO: Identificar o papel do broncodilatador no tempo de apneia voluntária máxima em pacientes com distúrbios ventilatórios obstrutivos (DVOs. MÉTODOS: Estudo caso-controle incluindo pacientes com DVOs e grupo controle. Foram realizadas espirometrias antes e após o uso de broncodilatador, assim como testes de apneia respiratória, utilizando-se um microprocessador eletrônico e um pneumotacógrafo como transdutor de fluxo. As curvas de fluxo respiratório foram exibidas em tempo real em um computador portátil, e os tempos de apneia voluntária inspiratória e expiratória máximos (TAVIM e TAVEM, respectivamente foram determinados a partir do sinal adquirido. RESULTADOS: Um total de 35 pacientes com DVOs e 16 controles foram incluídos no estudo. O TAVIM sem o uso de broncodilatador foi significativamente menor no grupo DVO que no grupo controle (22,27 ± 11,81 s vs. 31,45 ± 15,73; p = 0,025, mas essa diferença não foi significativa após o uso de broncodilatador (24,94 ± 12,89 s vs. 31,67 ± 17,53 s. Os valores de TAVEM foram significativamente menores no grupo DVO que no grupo controle antes (16,88 ± 6,58 s vs. 22,09 ± 7,95 s; p = 0,017 e após o uso de broncodilatador (21,22 ± 9,37 s vs. 28,53 ± 12,46 s; p = 0,024. CONCLUSÕES: Estes resultados fornecem uma evidência adicional da utilidade clínica do teste de apneia na avaliação da função pulmonar e do papel do broncodilatador nesse teste.OBJECTIVE: To identify the role of bronchodilators in the maximal breath-hold time in patients with obstructive lung disease (OLD. METHODS: We conducted a case-control study including patients with OLD and a control group. Spirometric tests were performed prior to and after the use of a bronchodilator, as were breath-hold tests, using an electronic microprocessor and a pneumotachograph as a flow transducer. Respiratory flow curves were displayed in real time on a portable computer. The maximal breath-hold times at end
Energy Technology Data Exchange (ETDEWEB)
Siqueira, Newton Norat
2006-12-15
This work shows a new approach to solve availability maximization problems in electromechanical systems, under periodic preventive scheduled tests. This approach uses a new Optimization tool called PSO developed by Kennedy and Eberhart (2001), Particle Swarm Optimization, integrated with probabilistic safety analysis model. Two maintenance optimization problems are solved by the proposed technique, the first one is a hypothetical electromechanical configuration and the second one is a real case from a nuclear power plant (Emergency Diesel Generators). For both problem PSO is compared to a genetic algorithm (GA). In the experiments made, PSO was able to obtain results comparable or even slightly better than those obtained b GA. Therefore, the PSO algorithm is simpler and its convergence is faster, indicating that PSO is a good alternative for solving such kind of problems. (author)
Andrew M. Parker; Wandi Bruine de Bruin; Baruch Fischhoff
2007-01-01
Our previous research suggests that people reporting a stronger desire to maximize obtain worse life outcomes (Bruine de Bruin et al., 2007). Here, we examine whether this finding may be explained by the decision-making styles of self-reported maximizers. Expanding on Schwartz et al. (2002), we find that self-reported maximizers are more likely to show problematic decision-making styles, as evidenced by self-reports of less behavioral coping, greater dependence on others when making decisions...
Maximal combustion temperature estimation
International Nuclear Information System (INIS)
Golodova, E; Shchepakina, E
2006-01-01
This work is concerned with the phenomenon of delayed loss of stability and the estimation of the maximal temperature of safe combustion. Using the qualitative theory of singular perturbations and canard techniques we determine the maximal temperature on the trajectories located in the transition region between the slow combustion regime and the explosive one. This approach is used to estimate the maximal temperature of safe combustion in multi-phase combustion models
Preconditioned alternating projection algorithms for maximum a posteriori ECT reconstruction
International Nuclear Information System (INIS)
Krol, Andrzej; Li, Si; Shen, Lixin; Xu, Yuesheng
2012-01-01
We propose a preconditioned alternating projection algorithm (PAPA) for solving the maximum a posteriori (MAP) emission computed tomography (ECT) reconstruction problem. Specifically, we formulate the reconstruction problem as a constrained convex optimization problem with the total variation (TV) regularization. We then characterize the solution of the constrained convex optimization problem and show that it satisfies a system of fixed-point equations defined in terms of two proximity operators raised from the convex functions that define the TV-norm and the constraint involved in the problem. The characterization (of the solution) via the proximity operators that define two projection operators naturally leads to an alternating projection algorithm for finding the solution. For efficient numerical computation, we introduce to the alternating projection algorithm a preconditioning matrix (the EM-preconditioner) for the dense system matrix involved in the optimization problem. We prove theoretically convergence of the PAPA. In numerical experiments, performance of our algorithms, with an appropriately selected preconditioning matrix, is compared with performance of the conventional MAP expectation-maximization (MAP-EM) algorithm with TV regularizer (EM-TV) and that of the recently developed nested EM-TV algorithm for ECT reconstruction. Based on the numerical experiments performed in this work, we observe that the alternating projection algorithm with the EM-preconditioner outperforms significantly the EM-TV in all aspects including the convergence speed, the noise in the reconstructed images and the image quality. It also outperforms the nested EM-TV in the convergence speed while providing comparable image quality. (paper)
Energy Technology Data Exchange (ETDEWEB)
Pereira, Claudio M.N.A. [Instituto de Engenharia Nuclear (IEN), Rio de Janeiro, RJ (Brazil); Schirru, Roberto; Martinez, Aquilino S. [Universidade Federal, Rio de Janeiro, RJ (Brazil). Coordenacao dos Programas de Pos-graduacao de Engenharia
1997-12-01
This work presents a prototype of a system for nuclear reactor core design optimization based on genetic algorithms and artificial neural networks. A neural network is modeled and trained in order to predict the flux and the neutron multiplication factor values based in the enrichment, network pitch and cladding thickness, with average error less than 2%. The values predicted by the neural network are used by a genetic algorithm in this heuristic search, guided by an objective function that rewards the high flux values and penalizes multiplication factors far from the required value. Associating the quick prediction - that may substitute the reactor physics calculation code - with the global optimization capacity of the genetic algorithm, it was obtained a quick and effective system for nuclear reactor core design optimization. (author). 11 refs., 8 figs., 3 tabs.
Maximally multipartite entangled states
Facchi, Paolo; Florio, Giuseppe; Parisi, Giorgio; Pascazio, Saverio
2008-06-01
We introduce the notion of maximally multipartite entangled states of n qubits as a generalization of the bipartite case. These pure states have a bipartite entanglement that does not depend on the bipartition and is maximal for all possible bipartitions. They are solutions of a minimization problem. Examples for small n are investigated, both analytically and numerically.
Directory of Open Access Journals (Sweden)
Andrew M. Parker
2007-12-01
Full Text Available Our previous research suggests that people reporting a stronger desire to maximize obtain worse life outcomes (Bruine de Bruin et al., 2007. Here, we examine whether this finding may be explained by the decision-making styles of self-reported maximizers. Expanding on Schwartz et al. (2002, we find that self-reported maximizers are more likely to show problematic decision-making styles, as evidenced by self-reports of less behavioral coping, greater dependence on others when making decisions, more avoidance of decision making, and greater tendency to experience regret. Contrary to predictions, self-reported maximizers were more likely to report spontaneous decision making. However, the relationship between self-reported maximizing and worse life outcomes is largely unaffected by controls for measures of other decision-making styles, decision-making competence, and demographic variables.
International Nuclear Information System (INIS)
Gronau, M.
1984-01-01
Two ambiguities are noted in the definition of the concept of maximal CP violation. The phase convention ambiguity is overcome by introducing a CP violating phase in the quark mixing matrix U which is invariant under rephasing transformations. The second ambiguity, related to the parametrization of U, is resolved by finding a single empirically viable definition of maximal CP violation when assuming that U does not single out one generation. Considerable improvement in the calculation of nonleptonic weak amplitudes is required to test the conjecture of maximal CP violation. 21 references
Similarity-regulation of OS-EM for accelerated SPECT reconstruction
Vaissier, P. E. B.; Beekman, F. J.; Goorden, M. C.
2016-06-01
Ordered subsets expectation maximization (OS-EM) is widely used to accelerate image reconstruction in single photon emission computed tomography (SPECT). Speedup of OS-EM over maximum likelihood expectation maximization (ML-EM) is close to the number of subsets used. Although a high number of subsets can shorten reconstruction times significantly, it can also cause severe image artifacts such as improper erasure of reconstructed activity if projections contain few counts. We recently showed that such artifacts can be prevented by using a count-regulated OS-EM (CR-OS-EM) algorithm which automatically adapts the number of subsets for each voxel based on the estimated number of counts that the voxel contributed to the projections. While CR-OS-EM reached high speed-up over ML-EM in high-activity regions of images, speed in low-activity regions could still be very slow. In this work we propose similarity-regulated OS-EM (SR-OS-EM) as a much faster alternative to CR-OS-EM. SR-OS-EM also automatically and locally adapts the number of subsets, but it uses a different criterion for subset regulation: the number of subsets that is used for updating an individual voxel depends on how similar the reconstruction algorithm would update the estimated activity in that voxel with different subsets. Reconstructions of an image quality phantom and in vivo scans show that SR-OS-EM retains all of the favorable properties of CR-OS-EM, while reconstruction speed can be up to an order of magnitude higher in low-activity regions. Moreover our results suggest that SR-OS-EM can be operated with identical reconstruction parameters (including the number of iterations) for a wide range of count levels, which can be an additional advantage from a user perspective since users would only have to post-filter an image to present it at an appropriate noise level.
<em>Maximizing policy learning in international committeesem>
DEFF Research Database (Denmark)
Nedergaard, Peter
2007-01-01
In the voluminous literature on the European Union's open method of coordination (OMC), no one has hitherto analysed on the basis of scholarly examination the question of what contributes to the learning processes in the OMC committees. On the basis of a questionnaire sent to all participants, th......-qualified and engaged participants, and a neutral presidency should be present in order to act as an authoritative persuader....
Directory of Open Access Journals (Sweden)
Kaori Kodama
2009-06-01
Full Text Available O artigo "O tráfico dos negros considerado como a causa da febre amarela", de Mathieu François Maxime Audouard (1776-1856, foi publicado em 1850 no jornal O Philantropo, periódico de propaganda contra o tráfico que circulou no Rio de Janeiro entre 1849 e 1852, e contava com diversos médicos entre seus membros. O texto, traduzido do original do médico francês e publicado no contexto da epidemia de febre amarela na cidade, oferece elementos para refletir sobre a atuação dos médicos brasileiros na questão da escravidão, no momento em que era promulgada a cessação do tráfico no país.The article "O tráfico de negros considerado como a causa da febre amarela" [The Negro slave trade considered as the cause of yellow fever] , by French physician Mathieu François Maxime Audouard (1776-1856, was published in 1850 in the newspaper O Philantropo, an organ of anti-slave trade propaganda that circulated in Rio de Janeiro from 1849 to 1852, with a number of physicians as members. Translated from the original and published during the yellow fever epidemic that hit Rio de Janeiro, the text affords an opportunity to reflect on the positions about slavery that were held by Brazilian physicians at the time the law against the slave trade was promulgated in Brazil.
Al-Jabr, Ahmad Ali; Alsunaidi, Mohammad A.; Ooi, Boon S.
2013-01-01
This paper presents methods of simulating gain media in the finite difference time-domain (FDTD) algorithm utilizing a generalized polarization formulation. The gain can be static or dynamic. For static gain, Lorentzian and non-Lorentzian models are presented and tested. For the dynamic gain, rate equations for two-level and four-level models are incorporated in the FDTD scheme. The simulation results conform with the expected behavior of wave amplification and dynamic population inversion.
DEFF Research Database (Denmark)
Andersen, Klaus Ejner
1985-01-01
Guinea pig maximization tests (GPMT) with chlorocresol were performed to ascertain whether the sensitization rate was affected by minor changes in the Freund's complete adjuvant (FCA) emulsion used. Three types of emulsion were evaluated: the oil phase was mixed with propylene glycol, saline...
Quantitation of PET data with the EM reconstruction technique
International Nuclear Information System (INIS)
Rosenqvist, G.; Dahlbom, M.; Erikson, L.; Bohm, C.; Blomqvist, G.
1989-01-01
The expectation maximization (EM) algorithm offers high spatial resolution and excellent noise reduction with low statistics PET data, since it incorporates the Poisson nature of the data. The main difficulties are long computation times, difficulties to find appropriate criteria to terminate the reconstruction and to quantify the resulting image data. In the present work a modified EM algorithm has been implements on a VAX 11/780. Its capability to quantify image data has been tested in phantom studies and in two clinical cases, cerebral blood flow studies and dopamine D2-receptor studies. Data from phantom studies indicate the superiority of images reconstructed with the EM technique compared to images reconstructed with the conventional filtered back-projection (FB) technique in areas with low statistics. At higher statistics the noise characteristics of the two techniques coincide. Clinical data support these findings
Tri-maximal vs. bi-maximal neutrino mixing
International Nuclear Information System (INIS)
Scott, W.G
2000-01-01
It is argued that data from atmospheric and solar neutrino experiments point strongly to tri-maximal or bi-maximal lepton mixing. While ('optimised') bi-maximal mixing gives an excellent a posteriori fit to the data, tri-maximal mixing is an a priori hypothesis, which is not excluded, taking account of terrestrial matter effects
Distributed-Memory Fast Maximal Independent Set
Energy Technology Data Exchange (ETDEWEB)
Kanewala Appuhamilage, Thejaka Amila J.; Zalewski, Marcin J.; Lumsdaine, Andrew
2017-09-13
The Maximal Independent Set (MIS) graph problem arises in many applications such as computer vision, information theory, molecular biology, and process scheduling. The growing scale of MIS problems suggests the use of distributed-memory hardware as a cost-effective approach to providing necessary compute and memory resources. Luby proposed four randomized algorithms to solve the MIS problem. All those algorithms are designed focusing on shared-memory machines and are analyzed using the PRAM model. These algorithms do not have direct efficient distributed-memory implementations. In this paper, we extend two of Luby’s seminal MIS algorithms, “Luby(A)” and “Luby(B),” to distributed-memory execution, and we evaluate their performance. We compare our results with the “Filtered MIS” implementation in the Combinatorial BLAS library for two types of synthetic graph inputs.
DEFF Research Database (Denmark)
Lisonek, Petr
1996-01-01
A two-distance set in E^d is a point set X inthe d-dimensional Euclidean spacesuch that the distances between distinct points in Xassume only two different non-zero values. Based on results from classical distance geometry, we developan algorithm to classify, for a given dimension, all maximal...... (largest possible)two-distance sets in E^d.Using this algorithm we have completed the full classificationfor all dimensions less than or equal to 7, andwe have found one set in E^8 whosemaximality follows from Blokhuis' upper bound on sizes of s-distance sets.While in the dimensions less than or equal to 6...
Directory of Open Access Journals (Sweden)
Katia Abbas
2008-12-01
Full Text Available Junto com o crescimento do setor de serviços tem-se o princípio da escassez, ou seja, é necessário fazer opções, não apenas relacionadas ao que fazer, mas também sobre o que não fazer, incluindo a prioridade hierárquica dos objetivos a serem atingidos. Uma das formas como os recursos podem ser utilizados deve levar em consideração a maximização da qualidade dos serviços oferecidos aos clientes. Esta alocação de recursos deve reconhecer o valor dos ativos intangíveis no resultado percebido pelos clientes do serviço. Nesse sentido, o objetivo deste artigo é propor uma sistemática para alocação de recursos nos ativos intangíveis, os quais maximizem a percepção da qualidade pelos clientes de serviços. Para tanto, os ativos intangíveis serão relacionados aos atributos dos serviços percebidos obtendo-se assim o papel dos ativos intangíveis na formação dos atributos dos serviços, percebidos como prioritários. Para reforçar esta constatação, será utilizado o diagrama de enlace causal para obter a influência dos ativos intangíveis, seu comportamento, a interação entre eles e como um pode influenciar o outro. A partir do conhecimento dos ativos intangíveis, a alocação de recursos nestes ativos intangíveis possibilitará melhorias em outros ativos intangíveis, visto que há uma inter-relação entre eles, e entre os atributos considerados prioritários nos serviços mais relevantes.Together with the growth of the services sector is the principle of the scarcity, i.e. it is necessary to make options including the hierarchy of the objectives to be reached. When making use of the resources, the maximization of the quality of the services offered to consumers should be taken into take consideration. The allocation of resources must acknowledge the value of intangible assets as it is perceived by the customers. The objective of this article is to consider a system for allocating resources in intangible assets that
Algorithmic detectability threshold of the stochastic block model
Kawamoto, Tatsuro
2018-03-01
The assumption that the values of model parameters are known or correctly learned, i.e., the Nishimori condition, is one of the requirements for the detectability analysis of the stochastic block model in statistical inference. In practice, however, there is no example demonstrating that we can know the model parameters beforehand, and there is no guarantee that the model parameters can be learned accurately. In this study, we consider the expectation-maximization (EM) algorithm with belief propagation (BP) and derive its algorithmic detectability threshold. Our analysis is not restricted to the community structure but includes general modular structures. Because the algorithm cannot always learn the planted model parameters correctly, the algorithmic detectability threshold is qualitatively different from the one with the Nishimori condition.
Directory of Open Access Journals (Sweden)
Tarcisio Abreu Saurin
2012-04-01
Full Text Available Este trabalho tem como objetivo principal desenvolver melhorias em um método de classificação de tipos de erros humanos de operadores de linha de frente. Tais melhorias foram desenvolvidas com base no teste do método em canteiros de obras, um ambiente no qual ele ainda não havia sido aplicado. Assim, foram investigados 19 acidentes de trabalho ocorridos em uma construtora de pequeno porte, sendo classificados os tipos de erros dos trabalhadores lesionados e de colegas de equipe que se encontravam no cenário do acidente. Os resultados indicaram que não houve nenhum erro em 70,5% das 34 vezes em que o método foi aplicado, evidenciando que as causas dos acidentes estavam fortemente associadas a fatores organizacionais. O estudo apresenta ainda recomendações para a interpretação das perguntas que constituem o método, bem como modificações em algumas dessas perguntas em comparação às versões anteriores.The objective of this study is to propose improvements in the algorithm for classifying error types of front-line workers. The improvements have been identified on the basis of testing the algorithm in construction sites, an environment where it had not been implemented it. To this end, 19 occupational accidents which occurred in a small construction company were investigated, and the error types of both injured workers and team members were classified. The results indicated that there was no error in 70.5% of the 34 times the algorithm was applied, providing evidence that the causes were strongly linked to organizational factors. Moreover, the study presents not only recommendations to facilitate the interpretation of the questions that constitute the algorithm, but also changes in some questions in comparison to the previous versions of the tool.
PEG Enhancement for EM1 and EM2+ Missions
Von der Porten, Paul; Ahmad, Naeem; Hawkins, Matt
2018-01-01
NASA is currently building the Space Launch System (SLS) Block-1 launch vehicle for the Exploration Mission 1 (EM-1) test flight. The next evolution of SLS, the Block-1B Exploration Mission 2 (EM-2), is currently being designed. The Block-1 and Block-1B vehicles will use the Powered Explicit Guidance (PEG) algorithm. Due to the relatively low thrust-to-weight ratio of the Exploration Upper Stage (EUS), certain enhancements to the Block-1 PEG algorithm are needed to perform Block-1B missions. In order to accommodate mission design for EM-2 and beyond, PEG has been significantly improved since its use on the Space Shuttle program. The current version of PEG has the ability to switch to different targets during Core Stage (CS) or EUS flight, and can automatically reconfigure for a single Engine Out (EO) scenario, loss of communication with the Launch Abort System (LAS), and Inertial Navigation System (INS) failure. The Thrust Factor (TF) algorithm uses measured state information in addition to a priori parameters, providing PEG with an improved estimate of propulsion information. This provides robustness against unknown or undetected engine failures. A loft parameter input allows LAS jettison while maximizing payload mass. The current PEG algorithm is now able to handle various classes of missions with burn arcs much longer than were seen in the shuttle program. These missions include targeting a circular LEO orbit with a low-thrust, long-burn-duration upper stage, targeting a highly eccentric Trans-Lunar Injection (TLI) orbit, targeting a disposal orbit using the low-thrust Reaction Control System (RCS), and targeting a hyperbolic orbit. This paper will describe the design and implementation of the TF algorithm, the strategy to handle EO in various flight regimes, algorithms to cover off-nominal conditions, and other enhancements to the Block-1 PEG algorithm. This paper illustrates challenges posed by the Block-1B vehicle, and results show that the improved PEG
Gendreau, Keith; Cash, Webster; Gorenstein, Paul; Windt, David; Kaaret, Phil; Reynolds, Chris
2004-01-01
The Beyond Einstein Program in NASA's Office of Space Science Structure and Evolution of the Universe theme spells out the top level scientific requirements for a Black Hole Imager in its strategic plan. The MAXIM mission will provide better than one tenth of a microarcsecond imaging in the X-ray band in order to satisfy these requirements. We will overview the driving requirements to achieve these goals and ultimately resolve the event horizon of a supermassive black hole. We will present the current status of this effort that includes a study of a baseline design as well as two alternative approaches.
Social group utility maximization
Gong, Xiaowen; Yang, Lei; Zhang, Junshan
2014-01-01
This SpringerBrief explains how to leverage mobile users' social relationships to improve the interactions of mobile devices in mobile networks. It develops a social group utility maximization (SGUM) framework that captures diverse social ties of mobile users and diverse physical coupling of mobile devices. Key topics include random access control, power control, spectrum access, and location privacy.This brief also investigates SGUM-based power control game and random access control game, for which it establishes the socially-aware Nash equilibrium (SNE). It then examines the critical SGUM-b
Directory of Open Access Journals (Sweden)
Claudio Gil Soares de Araújo
2005-07-01
Full Text Available OBJETIVO: Comparar, retrospectivamente, os valores de freqüência cardíaca máxima (FCM e o descenso da freqüência cardíaca no primeiro minuto da recuperação (dFC, obtidos em teste de exercício (TE realizados em dois ergômetros e momentos distintos. MÉTODOS: Sessenta indivíduos (29 a 80 anos de idade, submetidos a TE cardiopulmonar em ciclo de membros inferiores (CMI em nosso laboratório e que possuíam TE prévio (até 36 meses em esteira (EST em outros laboratórios, nas condições idênticas de medicações de ação cronotrópica negativa. RESULTADOS: FCM foi semelhante no CMI: 156±3 e EST: 154±2 bpm (p=0,125, enquanto o dFC foi maior em CMI: 33±2, EST: 26±3 bpm (média ± erro padrão da média (pOBJECTIVE: To compare, retrospectively, the values of maximum heart rate (MHR and the decrease of the heart rate at the first minute of recovery, which were obtained in an exercise test (ET performed in two different ergometers and at different moments. METHODS: Sixty individuals (from 29 to 80 years old, submitted to cardiopulmonary ET in a cycle of lower limbs (CLL in our laboratory and who had previous ET (up to 36 months in a treadmill (TRM in other laboratories, under identical conditions of medications of negative chronotropic action. RESULTS: MHR was similar in CLL: 156±3 and TRM: 154±2 bpm (p=0.125, whereas dHR was higher in CLL: 33±2, EST: 26±3 bpm (mean ± standard error of the mean (p<0.001. In hemodynamic variables studied, the systolic blood pressure and the double product were higher in the ET-CLL (p<0.001. The electrocardiogram (ECG was similar in both ETs, except due to more frequent supraventricular arrhythmias in CLL. CONCLUSION: a With some diligence from the examiner and previous knowledge of MHR in a previous ET it is possible to obtain high levels of MHR in an ET-CLL; b interrupting the MHR-based ET forecast through equations tends to lead to sub-maximum efforts; c dHR differs in active and passive
The Large Margin Mechanism for Differentially Private Maximization
Chaudhuri, Kamalika; Hsu, Daniel; Song, Shuang
2014-01-01
A basic problem in the design of privacy-preserving algorithms is the private maximization problem: the goal is to pick an item from a universe that (approximately) maximizes a data-dependent function, all under the constraint of differential privacy. This problem has been used as a sub-routine in many privacy-preserving algorithms for statistics and machine-learning. Previous algorithms for this problem are either range-dependent---i.e., their utility diminishes with the size of the universe...
Directory of Open Access Journals (Sweden)
Ricardo Augusto Cassel
2006-08-01
Full Text Available O presente artigo parte do problema do cálculo de custos em indústrias de produção conjunta. Observa-se que a abordagem tradicional adotada para tratar o tema, o método do custo conjunto, apresenta limitações no que tange ao modelo adotado e aos resultados obtidos em termos da análise da lucratividade dos diferentes produtos finais. Como forma de tratar o problema apresenta-se uma abordagem alternativa baseada na Teoria das Restrições suportada por técnicas de Pesquisa Operacional. Visando mostrar as diferenças dos resultados na utilização dos dois métodos, é realizado um estudo de caso em uma unidade de abate e industrialização de aves. Os resultados obtidos, em termos da lucratividade global da operação, apresentam diferenças significativas. A abordagem da Teoria das Restrições aplicada com base na utilização de técnicas de Pesquisa Operacional demonstra-se mais eficaz do prisma da tomada de decisão.This paper discusses the problem related to the costing in joint product industries. Traditional approaches to this subject present limitations regarding the analysis of the individual profitability of each final product. This problem is discussed and an alternative approach based on the Theory of Constraints, and supported by the Operational Research, is proposed. To demonstrate the differences between this new approach and the traditional one, a case study in a poultry company is presented, and the results are discussed.
Quantum speedup in solving the maximal-clique problem
Chang, Weng-Long; Yu, Qi; Li, Zhaokai; Chen, Jiahui; Peng, Xinhua; Feng, Mang
2018-03-01
The maximal-clique problem, to find the maximally sized clique in a given graph, is classically an NP-complete computational problem, which has potential applications ranging from electrical engineering, computational chemistry, and bioinformatics to social networks. Here we develop a quantum algorithm to solve the maximal-clique problem for any graph G with n vertices with quadratic speedup over its classical counterparts, where the time and spatial complexities are reduced to, respectively, O (√{2n}) and O (n2) . With respect to oracle-related quantum algorithms for the NP-complete problems, we identify our algorithm as optimal. To justify the feasibility of the proposed quantum algorithm, we successfully solve a typical clique problem for a graph G with two vertices and one edge by carrying out a nuclear magnetic resonance experiment involving four qubits.
Algorithms over partially ordered sets
DEFF Research Database (Denmark)
Baer, Robert M.; Østerby, Ole
1969-01-01
in partially ordered sets, answer the combinatorial question of how many maximal chains might exist in a partially ordered set withn elements, and we give an algorithm for enumerating all maximal chains. We give (in § 3) algorithms which decide whether a partially ordered set is a (lower or upper) semi......-lattice, and whether a lattice has distributive, modular, and Boolean properties. Finally (in § 4) we give Algol realizations of the various algorithms....
Blood detection in wireless capsule endoscopy using expectation maximization clustering
Hwang, Sae; Oh, JungHwan; Cox, Jay; Tang, Shou Jiang; Tibbals, Harry F.
2006-03-01
Wireless Capsule Endoscopy (WCE) is a relatively new technology (FDA approved in 2002) allowing doctors to view most of the small intestine. Other endoscopies such as colonoscopy, upper gastrointestinal endoscopy, push enteroscopy, and intraoperative enteroscopy could be used to visualize up to the stomach, duodenum, colon, and terminal ileum, but there existed no method to view most of the small intestine without surgery. With the miniaturization of wireless and camera technologies came the ability to view the entire gestational track with little effort. A tiny disposable video capsule is swallowed, transmitting two images per second to a small data receiver worn by the patient on a belt. During an approximately 8-hour course, over 55,000 images are recorded to a worn device and then downloaded to a computer for later examination. Typically, a medical clinician spends more than two hours to analyze a WCE video. Research has been attempted to automatically find abnormal regions (especially bleeding) to reduce the time needed to analyze the videos. The manufacturers also provide the software tool to detect the bleeding called Suspected Blood Indicator (SBI), but its accuracy is not high enough to replace human examination. It was reported that the sensitivity and the specificity of SBI were about 72% and 85%, respectively. To address this problem, we propose a technique to detect the bleeding regions automatically utilizing the Expectation Maximization (EM) clustering algorithm. Our experimental results indicate that the proposed bleeding detection method achieves 92% and 98% of sensitivity and specificity, respectively.
Kim, Ye-seul; Park, Hye-suk; Lee, Haeng-Hwa; Choi, Young-Wook; Choi, Jae-Gu; Kim, Hak Hee; Kim, Hee-Joung
2016-02-01
Digital breast tomosynthesis (DBT) is a recently developed system for three-dimensional imaging that offers the potential to reduce the false positives of mammography by preventing tissue overlap. Many qualitative evaluations of digital breast tomosynthesis were previously performed by using a phantom with an unrealistic model and with heterogeneous background and noise, which is not representative of real breasts. The purpose of the present work was to compare reconstruction algorithms for DBT by using various breast phantoms; validation was also performed by using patient images. DBT was performed by using a prototype unit that was optimized for very low exposures and rapid readout. Three algorithms were compared: a back-projection (BP) algorithm, a filtered BP (FBP) algorithm, and an iterative expectation maximization (EM) algorithm. To compare the algorithms, three types of breast phantoms (homogeneous background phantom, heterogeneous background phantom, and anthropomorphic breast phantom) were evaluated, and clinical images were also reconstructed by using the different reconstruction algorithms. The in-plane image quality was evaluated based on the line profile and the contrast-to-noise ratio (CNR), and out-of-plane artifacts were evaluated by means of the artifact spread function (ASF). Parenchymal texture features of contrast and homogeneity were computed based on reconstructed images of an anthropomorphic breast phantom. The clinical images were studied to validate the effect of reconstruction algorithms. The results showed that the CNRs of masses reconstructed by using the EM algorithm were slightly higher than those obtained by using the BP algorithm, whereas the FBP algorithm yielded much lower CNR due to its high fluctuations of background noise. The FBP algorithm provides the best conspicuity for larger calcifications by enhancing their contrast and sharpness more than the other algorithms; however, in the case of small-size and low
International Nuclear Information System (INIS)
Choi, Joonsung; Kim, Dongchan; Oh, Changhyun; Han, Yeji; Park, HyunWook
2013-01-01
In MRI (magnetic resonance imaging), signal sampling along a radial k-space trajectory is preferred in certain applications due to its distinct advantages such as robustness to motion, and the radial sampling can be beneficial for reconstruction algorithms such as parallel MRI (pMRI) due to the incoherency. For radial MRI, the image is usually reconstructed from projection data using analytic methods such as filtered back-projection or Fourier reconstruction after gridding. However, the quality of the reconstructed image from these analytic methods can be degraded when the number of acquired projection views is insufficient. In this paper, we propose a novel reconstruction method based on the expectation maximization (EM) method, where the EM algorithm is remodeled for MRI so that complex images can be reconstructed. Then, to optimize the proposed method for radial pMRI, a reconstruction method that uses coil sensitivity information of multichannel RF coils is formulated. Experiment results from synthetic and in vivo data show that the proposed method introduces better reconstructed images than the analytic methods, even from highly subsampled data, and provides monotonic convergence properties compared to the conjugate gradient based reconstruction method. (paper)
Maximal Bell's inequality violation for non-maximal entanglement
International Nuclear Information System (INIS)
Kobayashi, M.; Khanna, F.; Mann, A.; Revzen, M.; Santana, A.
2004-01-01
Bell's inequality violation (BIQV) for correlations of polarization is studied for a product state of two two-mode squeezed vacuum (TMSV) states. The violation allowed is shown to attain its maximal limit for all values of the squeezing parameter, ζ. We show via an explicit example that a state whose entanglement is not maximal allow maximal BIQV. The Wigner function of the state is non-negative and the average value of either polarization is nil
Real-time topic-aware influence maximization using preprocessing.
Chen, Wei; Lin, Tian; Yang, Cheng
2016-01-01
Influence maximization is the task of finding a set of seed nodes in a social network such that the influence spread of these seed nodes based on certain influence diffusion model is maximized. Topic-aware influence diffusion models have been recently proposed to address the issue that influence between a pair of users are often topic-dependent and information, ideas, innovations etc. being propagated in networks are typically mixtures of topics. In this paper, we focus on the topic-aware influence maximization task. In particular, we study preprocessing methods to avoid redoing influence maximization for each mixture from scratch. We explore two preprocessing algorithms with theoretical justifications. Our empirical results on data obtained in a couple of existing studies demonstrate that one of our algorithms stands out as a strong candidate providing microsecond online response time and competitive influence spread, with reasonable preprocessing effort.
Maximally Symmetric Composite Higgs Models.
Csáki, Csaba; Ma, Teng; Shu, Jing
2017-09-29
Maximal symmetry is a novel tool for composite pseudo Goldstone boson Higgs models: it is a remnant of an enhanced global symmetry of the composite fermion sector involving a twisting with the Higgs field. Maximal symmetry has far-reaching consequences: it ensures that the Higgs potential is finite and fully calculable, and also minimizes the tuning. We present a detailed analysis of the maximally symmetric SO(5)/SO(4) model and comment on its observational consequences.
Principles of maximally classical and maximally realistic quantum ...
Indian Academy of Sciences (India)
Principles of maximally classical and maximally realistic quantum mechanics. S M ROY. Tata Institute of Fundamental Research, Homi Bhabha Road, Mumbai 400 005, India. Abstract. Recently Auberson, Mahoux, Roy and Singh have proved a long standing conjecture of Roy and Singh: In 2N-dimensional phase space, ...
Maximizing and customer loyalty: Are maximizers less loyal?
Directory of Open Access Journals (Sweden)
Linda Lai
2011-06-01
Full Text Available Despite their efforts to choose the best of all available solutions, maximizers seem to be more inclined than satisficers to regret their choices and to experience post-decisional dissonance. Maximizers may therefore be expected to change their decisions more frequently and hence exhibit lower customer loyalty to providers of products and services compared to satisficers. Findings from the study reported here (N = 1978 support this prediction. Maximizers reported significantly higher intentions to switch to another service provider (television provider than satisficers. Maximizers' intentions to switch appear to be intensified and mediated by higher proneness to regret, increased desire to discuss relevant choices with others, higher levels of perceived knowledge of alternatives, and higher ego involvement in the end product, compared to satisficers. Opportunities for future research are suggested.
Implications of maximal Jarlskog invariant and maximal CP violation
International Nuclear Information System (INIS)
Rodriguez-Jauregui, E.; Universidad Nacional Autonoma de Mexico
2001-04-01
We argue here why CP violating phase Φ in the quark mixing matrix is maximal, that is, Φ=90 . In the Standard Model CP violation is related to the Jarlskog invariant J, which can be obtained from non commuting Hermitian mass matrices. In this article we derive the conditions to have Hermitian mass matrices which give maximal Jarlskog invariant J and maximal CP violating phase Φ. We find that all squared moduli of the quark mixing elements have a singular point when the CP violation phase Φ takes the value Φ=90 . This special feature of the Jarlskog invariant J and the quark mixing matrix is a clear and precise indication that CP violating Phase Φ is maximal in order to let nature treat democratically all of the quark mixing matrix moduli. (orig.)
Phenomenology of maximal and near-maximal lepton mixing
International Nuclear Information System (INIS)
Gonzalez-Garcia, M. C.; Pena-Garay, Carlos; Nir, Yosef; Smirnov, Alexei Yu.
2001-01-01
The possible existence of maximal or near-maximal lepton mixing constitutes an intriguing challenge for fundamental theories of flavor. We study the phenomenological consequences of maximal and near-maximal mixing of the electron neutrino with other (x=tau and/or muon) neutrinos. We describe the deviations from maximal mixing in terms of a parameter ε(equivalent to)1-2sin 2 θ ex and quantify the present experimental status for |ε| e mixing comes from solar neutrino experiments. We find that the global analysis of solar neutrino data allows maximal mixing with confidence level better than 99% for 10 -8 eV 2 ∼ 2 ∼ -7 eV 2 . In the mass ranges Δm 2 ∼>1.5x10 -5 eV 2 and 4x10 -10 eV 2 ∼ 2 ∼ -7 eV 2 the full interval |ε| e mixing in atmospheric neutrinos, supernova neutrinos, and neutrinoless double beta decay
Maximal quantum Fisher information matrix
International Nuclear Information System (INIS)
Chen, Yu; Yuan, Haidong
2017-01-01
We study the existence of the maximal quantum Fisher information matrix in the multi-parameter quantum estimation, which bounds the ultimate precision limit. We show that when the maximal quantum Fisher information matrix exists, it can be directly obtained from the underlying dynamics. Examples are then provided to demonstrate the usefulness of the maximal quantum Fisher information matrix by deriving various trade-off relations in multi-parameter quantum estimation and obtaining the bounds for the scalings of the precision limit. (paper)
Directory of Open Access Journals (Sweden)
Leandro Ricardo Altimari
2006-06-01
Full Text Available Este estudo investigou o efeito de um longo período de suplementação com creatina monoidratada (Cr m sobre o trabalho total relativo (TTR em esforços intermitentes máximos no cicloergômetro de homens treinados. Vinte seis indivíduos foram divididos aleatoriamente em grupo creatina (CR, n=13 e grupo placebo (PL, n=13. Os sujeitos receberam em sistema duplo-cego, doses de Cr m ou placebo-maltodextrina (20 g.d-1 por 5 dias e 3 g.d-1 durante 51 dias subseqüentes. Os grupos tiveram seus hábitos alimentares e sua condição física previamente controlados. Para determinação do TTR os sujeitos foram submetidos a protocolo de exercício em cicloergômetro composto de três Testes de Wingate de 30s separados por dois minutos recuperação, antes e após o período de suplementação. ANOVA, seguido pelo teste post hoc de Tukey, quando pThis study investigated the effect of long-term supplementation with creatine monohydrate (Cr m on relative total work (RTW in intermittent maximal efforts in the cycle ergometer of trained men. Twenty six individuals were randomly divided in creatine group (CR, n=13 and placebo group (PL, n=13. The subjects received in a double-blind manner, doses of Cr m or placebo-maltodextrin (20 g.d-1 for 5 days and 3 g.d-1 for 51 subsequent days. The groups had their alimentary habits and physical fitness controlled previously. For determination of the RTW the subjects were submitted to exercise protocol in cycle ergometer comprised three 30s Anaerobic Wingate Test interspersed with two minutes recovery, before and after the supplementation period. ANOVA, followed by the Tukey post hoc test, when p<0.05, were used for data treatment. There was a significant time effect for RTW (F1,24=8.00; p<0.05, with the CR group demonstrating significant greater (3% on the RTW production compared to PL group after the supplementation period (690.54 ± 46.83 vs 655.71 ± 74.34 J.kg-1 respectively; p<0.05. The results of the present study
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Adriana Rahal
2009-01-01
Full Text Available OBJETIVO: Analisar a diferença entre os lados na atividade eletromiográfica do masseter em indivíduos adultos com oclusão dentária normal. MÉTODOS: Foram avaliados 30 indivíduos saudáveis entre 21 e 30 anos e realizou-se eletromiografia de superfície nos músculos masseteres direito e esquerdo, durante apertamento em máxima intercuspidação e mastigação habitual com uva passa. Foram computados os valores médios dos três apertamentos dentários e dos 15 segundos da mastigação habitual para cada indivíduo. Foram considerados para a análise: o lado de maior valor e o de menor valor eletromiográfico. RESULTADOS: Durante o apertamento dentário, a diferença média entre os dois lados foi de 20,0 microvolts (μV com intervalo de confiança (95% entre 14,0 e 26,0 μV e durante a mastigação habitual, a diferença média entre os dois lados foi de 10,3 μV com intervalo de confiança (95% entre 6,7 e 13,8 μV. CONCLUSÃO: Houve diferença estatisticamente significante entre os lados, com relação entre eles de 24% para o apertamento dentário e de 27% para a mastigação habitual, em indiv duos adultos saudáveis.PURPOSE: To analyze the difference between both sides of the face during the electromyographic activity of the masseter muscle in adults with normal occlusion. METHODS: Thirty healthy individuals with ages ranging from 21 to 30 years old were selected. Surface electromyography was performed on right and left masseter muscles during maximal voluntary clenching and habitual chewing with raisins. The mean values of three teeth clenching and fifteen seconds of habitual chewing were calculated for each subject. The analysis considered the sides with higher and lower electromyographic activity. RESULTS: During maximal voluntary clenching, the mean difference between sides was 20.0 microvolts (μV, with confidence interval (95% between 14.0 and 26.0 μV. During habitual chewing, the mean difference between sides was 10.3
Lange, L. H.
1974-01-01
Five different methods for determining the maximizing condition for x(a - x) are presented. Included is the ancient Greek version and a method attributed to Fermat. None of the proofs use calculus. (LS)
Maximization of submodular functions : Theory and enumeration algorithms
Goldengorin, B.
2009-01-01
Submodular functions are powerful tools to model and solve either to optimality or approximately many operational research problems including problems defined on graphs. After reviewing some long-standing theoretical results about the structure of local and global maxima of submodular functions,
Influence Maximization in Social Networks with Genetic Algorithms
Bucur, Doina; Iacca, Giovanni; Squillero, Giovanni; Burelli, Paolo
We live in a world of social networks. Our everyday choices are often influenced by social interactions. Word of mouth, meme diffusion on the Internet, and viral marketing are all examples of how social networks can affect our behaviour. In many practical applications, it is of great interest to
Two Expectation-Maximization Algorithms for Boolean Factor Analysis
Czech Academy of Sciences Publication Activity Database
Frolov, A. A.; Húsek, Dušan; Polyakov, P.Y.
2014-01-01
Roč. 130, 23 April (2014), s. 83-97 ISSN 0925-2312 R&D Projects: GA ČR GAP202/10/0262 Grant - others:GA MŠk(CZ) ED1.1.00/02.0070; GA MŠk(CZ) EE.2.3.20.0073 Program:ED Institutional research plan: CEZ:AV0Z10300504 Keywords : Boolean Factor analysis * Binary Matrix factorization * Neural networks * Binary data model * Dimension reduction * Bars problem Subject RIV: IN - Informatics, Computer Science Impact factor: 2.083, year: 2014
An Expectation-Maximization Method for Calibrating Synchronous Machine Models
Energy Technology Data Exchange (ETDEWEB)
Meng, Da; Zhou, Ning; Lu, Shuai; Lin, Guang
2013-07-21
The accuracy of a power system dynamic model is essential to its secure and efficient operation. Lower confidence in model accuracy usually leads to conservative operation and lowers asset usage. To improve model accuracy, this paper proposes an expectation-maximization (EM) method to calibrate the synchronous machine model using phasor measurement unit (PMU) data. First, an extended Kalman filter (EKF) is applied to estimate the dynamic states using measurement data. Then, the parameters are calculated based on the estimated states using maximum likelihood estimation (MLE) method. The EM method iterates over the preceding two steps to improve estimation accuracy. The proposed EM method’s performance is evaluated using a single-machine infinite bus system and compared with a method where both state and parameters are estimated using an EKF method. Sensitivity studies of the parameter calibration using EM method are also presented to show the robustness of the proposed method for different levels of measurement noise and initial parameter uncertainty.
Salvio, Alberto; Strumia, Alessandro; Urbano, Alfredo
2016-01-01
Motivated by the 750 GeV diphoton excess found at LHC, we compute the maximal width into $\\gamma\\gamma$ that a neutral scalar can acquire through a loop of charged fermions or scalars as function of the maximal scale at which the theory holds, taking into account vacuum (meta)stability bounds. We show how an extra gauge symmetry can qualitatively weaken such bounds, and explore collider probes and connections with Dark Matter.
Directory of Open Access Journals (Sweden)
Ana Paula Iannoni
2006-04-01
Full Text Available O modelo hipercubo, conhecido na literatura de problemas de localização de sistemas servidor para cliente, é um modelo baseado em teoria de filas espacialmente distribuídas e aproximações Markovianas. O modelo pode ser modificado para analisar os sistemas de atendimentos emergenciais (SAEs em rodovias, considerando as particularidades da política de despacho destes sistemas. Neste estudo, combinou-se o modelo hipercubo com um algoritmo genético para otimizar a configuração e operação de SAEs em rodovias. A abordagem é efetiva para apoiar decisões relacionadas ao planejamento e operação destes sistemas, por exemplo, em determinar o tamanho ideal para as áreas de cobertura de cada ambulância, de forma a minimizar o tempo médio de resposta aos usuários e o desbalanceamento das cargas de trabalho das ambulâncias. Os resultados computacionais desta abordagem foram analisados utilizando dados reais do sistema Anjos do Asfalto (rodovia Presidente Dutra.The hypercube model, well-known in the literature on problems of server-to-customer localization systems, is based on the spatially distributed queuing theory and Markovian analysis approximations. The model can be modified to analyze Emergency Medical Systems (EMSs on highways, considering the particularities of these systems' dispatching policies. In this study, we combine the hypercube model with a genetic algorithm to optimize the configuration and operation of EMSs on highways. This approach is effective to support planning and operation decisions, such as determining the ideal size of the area each ambulance should cover to minimize not only the average time of response to the user but also ambulance workload imbalances, as well as generating a Pareto efficient boundary between these measures. The computational results of this approach were analyzed using real data Anjos do Asfalto EMS (which covers the Presidente Dutra highway.
Directory of Open Access Journals (Sweden)
Fúlvia de Barros Manchado
2006-10-01
Full Text Available A máxima fase estável de lactato (MFEL é considerada padrão-ouro para a determinação da intensidade de transição metabólica aeróbia-anaeróbia em exercício contínuo, porém a resposta lactacidêmica nessa intensidade é, em humanos, dependente do ergômetro utilizado na avaliação. Uma ferramenta importante para estudos em fisiologia e áreas correlatas é a aplicação de modelos experimentais utilizando animais. Entretanto, ainda são restritas as pesquisas destinadas a investigar protocolos de avaliação em ratos. O objetivo do estudo foi verificar se a MFEL é dependente do ergômetro utilizado para a avaliação aeróbia de ratos. Para isso, 40 ratos Wistar adultos foram avaliados em dois diferentes exercícios: natação e corrida em esteira. Em ambos, a MFEL foi verificada após aplicação de quatro testes contínuos, em diferentes intensidades, com duração de 25 minutos, separados por intervalo de 48 horas. Em todos os testes houve coleta sanguínea da cauda dos animais a cada cinco minutos de exercício para análise do lactato sanguíneo. Os testes de natação ocorreram em tanque cilíndrico profundo, com a temperatura da água a 31 ± 1°C. As cargas adotadas para os testes foram de 4,5; 5,0; 5,5; 6,0% do peso corporal, atadas ao dorso dos animais. Para a determinação da MFEL em corrida, houve seleção dos ratos corredores e as velocidades dos testes foram de 15, 20, 25, 30m.min¹. A MFEL foi interpretada como a mais alta intensidade de exercício na qual o aumento da lactacidemia foi igual ou inferior a 1mM, do 10º ao 25º minuto. Anova one-way identificou diferenças entre as concentrações de lactato sanguíneo nos diversos tempos de exercício e ergômetros. A MFEL na natação ocorreu a 5,0% do peso corporal (pc, em concentração de lactato de 5,20 ± 0,22mM. Para o exercício em esteira rolante, observou-se MFEL a 20m.min¹, em concentração 3,87 ± 0,33mM. Dessa forma, é possível concluir que a MFEL
Dong, Jian; Hayakawa, Yoshihiko; Kannenberg, Sven; Kober, Cornelia
2013-02-01
The objective of this study was to reduce metal-induced streak artifact on oral and maxillofacial x-ray computed tomography (CT) images by developing the fast statistical image reconstruction system using iterative reconstruction algorithms. Adjacent CT images often depict similar anatomical structures in thin slices. So, first, images were reconstructed using the same projection data of an artifact-free image. Second, images were processed by the successive iterative restoration method where projection data were generated from reconstructed image in sequence. Besides the maximum likelihood-expectation maximization algorithm, the ordered subset-expectation maximization algorithm (OS-EM) was examined. Also, small region of interest (ROI) setting and reverse processing were applied for improving performance. Both algorithms reduced artifacts instead of slightly decreasing gray levels. The OS-EM and small ROI reduced the processing duration without apparent detriments. Sequential and reverse processing did not show apparent effects. Two alternatives in iterative reconstruction methods were effective for artifact reduction. The OS-EM algorithm and small ROI setting improved the performance. Copyright © 2012 Elsevier Inc. All rights reserved.
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A. Garmroodi Asil
2017-09-01
To further reduce the sulfur dioxide emission of the entire refining process, two scenarios of acid gas or air preheats are investigated when either of them is used simultaneously with the third enrichment scheme. The maximum overall sulfur recovery efficiency and highest combustion chamber temperature is slightly higher for acid gas preheats but air preheat is more favorable because it is more benign. To the best of our knowledge, optimization of the entire GTU + enrichment section and SRU processes has not been addressed previously.
PENDUGAAN DATA HILANG DENGAN METODE YATES DAN ALGORITMA EM PADA RANCANGAN LATTICE SEIMBANG
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MADE SUSILAWATI
2015-06-01
Full Text Available Missing data often occur in agriculture and animal husbandry experiment. The missing data in experimental design makes the information that we get less complete. In this research, the missing data was estimated with Yates method and Expectation Maximization (EM algorithm. The basic concept of the Yates method is to minimize sum square error (JKG, meanwhile the basic concept of the EM algorithm is to maximize the likelihood function. This research applied Balanced Lattice Design with 9 treatments, 4 replications and 3 group of each repetition. Missing data estimation results showed that the Yates method was better used for two of missing data in the position on a treatment, a column and random, meanwhile the EM algorithm was better used to estimate one of missing data and two of missing data in the position of a group and a replication. The comparison of the result JKG of ANOVA showed that JKG of incomplete data larger than JKG of incomplete data that has been added with estimator of data. This suggest thatwe need to estimate the missing data.
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Ricardo Vinicius Ledesma Contarteze
2007-06-01
Full Text Available INTRODUÇÃO: O estresse alcançado durante exercício agudo/crônico é relevante, pois altos índices de estresse podem prejudicar o bem-estar dos animais. As concentrações dos hormônios adrenocorticotrófico (ACTH e corticosterona, bem como as concentrações de ácido ascórbico e colesterol das glândulas adrenais são importantes biomarcadores de estresse. OBJETIVO: Analisar a sensibilidade de diferentes biomarcadores de estresse em ratos durante exercício agudo de natação em diferentes intensidades. MÉTODO: Ratos (18 adaptados à natação foram submetidos a três testes de 25 minutos suportando cargas 5,0; 5,5 e 6,0% do peso corporal (PC, para obtenção da máxima fase estável de lactato (MFEL. Em seguida, os animais foram divididos em dois grupos: M (n = 9, sacrificado após 25 minutos de exercício na intensidade de MFEL e S (n = 9, sacrificado após exercício exaustivo, em intensidade 25% superior a MFEL. Para comparações, um grupo controle C (n = 10 foi sacrificado em repouso. RESULTADOS: As concentrações séricas de ACTH e corticosterona foram superiores após exercício em ambas as intensidades comparadas com o grupo controle (P INTRODUCTION: The level of stress during acute/chronic exercise is important, since higher levels of stress may impair animal welfare. The adrenocorticotrophic (ACTH and corticosterone hormone concentrations, as well as cholesterol and ascorbic acid concentrations in adrenal gland, are considered an important stress biomarker. PURPOSE: To analyze the sensitivity of the different biomarkers during acute swimming exercise in different intensities performed by rats. METHODS: Male Wistar adult rats (n = 18 previously adapted to swimming were submitted to three 25 min. swimming tests with loads of 5.0; 5.5 and 6.0% of their body weight (BW, for maximum lactate steady state (MLSS determination. After MLSS attainment, the animals were divided into two groups: M (n = 9 sacrificed shortly after a 25
Chamaebatiaria millefolium (Torr.) Maxim.: fernbush
Nancy L. Shaw; Emerenciana G. Hurd
2008-01-01
Fernbush - Chamaebatiaria millefolium (Torr.) Maxim. - the only species in its genus, is endemic to the Great Basin, Colorado Plateau, and adjacent areas of the western United States. It is an upright, generally multistemmed, sweetly aromatic shrub 0.3 to 2 m tall. Bark of young branches is brown and becomes smooth and gray with age. Leaves are leathery, alternate,...
Gap processing for adaptive maximal poisson-disk sampling
Yan, Dongming
2013-10-17
In this article, we study the generation of maximal Poisson-disk sets with varying radii. First, we present a geometric analysis of gaps in such disk sets. This analysis is the basis for maximal and adaptive sampling in Euclidean space and on manifolds. Second, we propose efficient algorithms and data structures to detect gaps and update gaps when disks are inserted, deleted, moved, or when their radii are changed.We build on the concepts of regular triangulations and the power diagram. Third, we show how our analysis contributes to the state-of-the-art in surface remeshing. © 2013 ACM.
Gap processing for adaptive maximal poisson-disk sampling
Yan, Dongming; Wonka, Peter
2013-01-01
In this article, we study the generation of maximal Poisson-disk sets with varying radii. First, we present a geometric analysis of gaps in such disk sets. This analysis is the basis for maximal and adaptive sampling in Euclidean space and on manifolds. Second, we propose efficient algorithms and data structures to detect gaps and update gaps when disks are inserted, deleted, moved, or when their radii are changed.We build on the concepts of regular triangulations and the power diagram. Third, we show how our analysis contributes to the state-of-the-art in surface remeshing. © 2013 ACM.
Enumerating all maximal frequent subtrees in collections of phylogenetic trees.
Deepak, Akshay; Fernández-Baca, David
2014-01-01
A common problem in phylogenetic analysis is to identify frequent patterns in a collection of phylogenetic trees. The goal is, roughly, to find a subset of the species (taxa) on which all or some significant subset of the trees agree. One popular method to do so is through maximum agreement subtrees (MASTs). MASTs are also used, among other things, as a metric for comparing phylogenetic trees, computing congruence indices and to identify horizontal gene transfer events. We give algorithms and experimental results for two approaches to identify common patterns in a collection of phylogenetic trees, one based on agreement subtrees, called maximal agreement subtrees, the other on frequent subtrees, called maximal frequent subtrees. These approaches can return subtrees on larger sets of taxa than MASTs, and can reveal new common phylogenetic relationships not present in either MASTs or the majority rule tree (a popular consensus method). Our current implementation is available on the web at https://code.google.com/p/mfst-miner/. Our computational results confirm that maximal agreement subtrees and all maximal frequent subtrees can reveal a more complete phylogenetic picture of the common patterns in collections of phylogenetic trees than maximum agreement subtrees; they are also often more resolved than the majority rule tree. Further, our experiments show that enumerating maximal frequent subtrees is considerably more practical than enumerating ordinary (not necessarily maximal) frequent subtrees.
Enumerating all maximal frequent subtrees in collections of phylogenetic trees
2014-01-01
Background A common problem in phylogenetic analysis is to identify frequent patterns in a collection of phylogenetic trees. The goal is, roughly, to find a subset of the species (taxa) on which all or some significant subset of the trees agree. One popular method to do so is through maximum agreement subtrees (MASTs). MASTs are also used, among other things, as a metric for comparing phylogenetic trees, computing congruence indices and to identify horizontal gene transfer events. Results We give algorithms and experimental results for two approaches to identify common patterns in a collection of phylogenetic trees, one based on agreement subtrees, called maximal agreement subtrees, the other on frequent subtrees, called maximal frequent subtrees. These approaches can return subtrees on larger sets of taxa than MASTs, and can reveal new common phylogenetic relationships not present in either MASTs or the majority rule tree (a popular consensus method). Our current implementation is available on the web at https://code.google.com/p/mfst-miner/. Conclusions Our computational results confirm that maximal agreement subtrees and all maximal frequent subtrees can reveal a more complete phylogenetic picture of the common patterns in collections of phylogenetic trees than maximum agreement subtrees; they are also often more resolved than the majority rule tree. Further, our experiments show that enumerating maximal frequent subtrees is considerably more practical than enumerating ordinary (not necessarily maximal) frequent subtrees. PMID:25061474
Nonlinear Impairment Compensation Using Expectation Maximization for PDM 16-QAM Systems
DEFF Research Database (Denmark)
Zibar, Darko; Winther, Ole; Franceschi, Niccolo
2012-01-01
We show experimentally that by using non-linear signal processing based algorithm, expectation maximization, nonlinear system tolerance can be increased by 2 dB. Expectation maximization is also effective in combating I/Q modulator nonlinearities and laser linewidth....
IMNN: Information Maximizing Neural Networks
Charnock, Tom; Lavaux, Guilhem; Wandelt, Benjamin D.
2018-04-01
This software trains artificial neural networks to find non-linear functionals of data that maximize Fisher information: information maximizing neural networks (IMNNs). As compressing large data sets vastly simplifies both frequentist and Bayesian inference, important information may be inadvertently missed. Likelihood-free inference based on automatically derived IMNN summaries produces summaries that are good approximations to sufficient statistics. IMNNs are robustly capable of automatically finding optimal, non-linear summaries of the data even in cases where linear compression fails: inferring the variance of Gaussian signal in the presence of noise, inferring cosmological parameters from mock simulations of the Lyman-α forest in quasar spectra, and inferring frequency-domain parameters from LISA-like detections of gravitational waveforms. In this final case, the IMNN summary outperforms linear data compression by avoiding the introduction of spurious likelihood maxima.
International Nuclear Information System (INIS)
Ferrandis, Javier
2005-01-01
The current experimental determination of the absolute values of the CKM elements indicates that 2 vertical bar V ub /V cb V us vertical bar =(1-z), with z given by z=0.19+/-0.14. This fact implies that irrespective of the form of the quark Yukawa matrices, the measured value of the SM CP phase β is approximately the maximum allowed by the measured absolute values of the CKM elements. This is β=(π/6-z/3) for γ=(π/3+z/3), which implies α=π/2. Alternatively, assuming that β is exactly maximal and using the experimental measurement sin(2β)=0.726+/-0.037, the phase γ is predicted to be γ=(π/2-β)=66.3 o +/-1.7 o . The maximality of β, if confirmed by near-future experiments, may give us some clues as to the origin of CP violation
Strategy to maximize maintenance operation
Espinoza, Michael
2005-01-01
This project presents a strategic analysis to maximize maintenance operations in Alcan Kitimat Works in British Columbia. The project studies the role of maintenance in improving its overall maintenance performance. It provides strategic alternatives and specific recommendations addressing Kitimat Works key strategic issues and problems. A comprehensive industry and competitive analysis identifies the industry structure and its competitive forces. In the mature aluminium industry, the bargain...
Scalable Nonlinear AUC Maximization Methods
Khalid, Majdi; Ray, Indrakshi; Chitsaz, Hamidreza
2017-01-01
The area under the ROC curve (AUC) is a measure of interest in various machine learning and data mining applications. It has been widely used to evaluate classification performance on heavily imbalanced data. The kernelized AUC maximization machines have established a superior generalization ability compared to linear AUC machines because of their capability in modeling the complex nonlinear structure underlying most real world-data. However, the high training complexity renders the kernelize...
FLOUTING MAXIMS IN INDONESIA LAWAK KLUB CONVERSATION
Directory of Open Access Journals (Sweden)
Rahmawati Sukmaningrum
2017-04-01
Full Text Available This study aims to identify the types of maxims flouted in the conversation in famous comedy show, Indonesia Lawak Club. Likewise, it also tries to reveal the speakers‘ intention of flouting the maxim in the conversation during the show. The writers use descriptive qualitative method in conducting this research. The data is taken from the dialogue of Indonesia Lawak club and then analyzed based on Grice‘s cooperative principles. The researchers read the dialogue‘s transcripts, identify the maxims, and interpret the data to find the speakers‘ intention for flouting the maxims in the communication. The results show that there are four types of maxims flouted in the dialogue. Those are maxim of quality (23%, maxim of quantity (11%, maxim of manner (31%, and maxim of relevance (35. Flouting the maxims in the conversations is intended to make the speakers feel uncomfortable with the conversation, show arrogances, show disagreement or agreement, and ridicule other speakers.
Energy Technology Data Exchange (ETDEWEB)
Leite, Vinicius Freitas
2012-07-01
This work analyzes, through the study of the interaction of electromagnetic radiation with matter, two schemes of heterogeneous phantoms schematised to simulate real cases of planning with different electronic densities through the Pencil Beam, Collapsed Cone and Analytical Anisotropic Algorithm algorithms and compare with measurements Of relative absorbed dose in an IBA CC13 ionization chamber and Gafchromic® EBT2 radiochromic film. Epichlorohydrin rubber and its compatibility in comparison with human bone has also been evaluated. The assembly of the heterogeneous phantoms was feasible and the results regarding the density and attenuation of the rubber presented consistent values. However, the study of PDPs in constructed phantoms showed a considerable percentage discrepancy between measurements and planning.
Energy Technology Data Exchange (ETDEWEB)
Souza, Claudio Eduardo Scriptori de
1996-02-01
In the Operating Center of Electrical Energy System has been every time more and more important the understanding of the difficulties related to the electrical power behavior. In order to have adequate operation of the system the state estimation process is very important. However before performing the system state estimation owe needs to know if the system is observable otherwise the estimation will no be possible. This work has a main objective, to develop a software that allows one to visualize the whole network in case that network is observable or the observable island of the entire network. As theoretical background the theories and algorithm using the triangular factorization of gain matrix as well as the concepts contained on factorization path developed by Bretas et alli were used. The algorithm developed by him was adapted to the Windows graphical form so that the numerical results of the network observability are shown in the computer screen in graphical form. This algorithm is essentially instead of numerical as the one based on the factorization of gain matrix only. To implement the algorithm previously referred it was used the Borland C++ compiler for windows version 4.0 due to the facilities for sources generation it presents. The results of the tests in the network with 6, 14 and 30 bus leads to: (1) the simplification of observability analysis, using sparse vectors and triangular factorization of the gain matrix; (2) the behavior similarity of the three testes systems with effective clues that the routine developed works well for any systems mainly for systems with bigger quantities of bus and lines; (3) the alternative way of presenting numerical results using the program developed here in graphical forms. (author)
Directory of Open Access Journals (Sweden)
Danilo Marcelo Leite do Prado
2010-04-01
Full Text Available FUNDAMENTO: Pouco se sabe sobre a resposta cardiorrespiratória e metabólica em crianças saudáveis durante teste de esforço progressivo máximo. OBJETIVO: Testar a hipótese de que as crianças apresentam respostas diferentes nos parâmetros cardiorrespiratórios e metabólicos durante teste de esforço progressivo máximo em comparação aos adultos. MÉTODOS: Vinte e cinco crianças saudáveis (sexo, 15M/10F; idade, 10,2 ± 0,2 e 20 adultos saudáveis (sexo, 11M/9F; idade, 27,5 ± 0,4 foram submetidos a um teste cardiopulmonar progressivo em esteira ergométrica até a exaustão para determinar a capacidade aeróbia máxima e limiar anaeróbio ventilatório (LAV. RESULTADOS: A carga de pico (5,9 ± 0,1 vs 5,6 ± 0,1 mph, respectivamente; p > 0,05, tempo de exercício (9,8 ± 0,4 vs 10,2 ± 0,4 min, respectivamente, p > 0,05, e aptidão cardiorrespiratória (VO2pico, 39,4 ± 2,1 vs 39,1 ± 2,0 ml.kg-1.min-1, respectivamente, p > 0,05 foram semelhantes em crianças e adultos. No limiar anaeróbio ventilatório, a frequência cardíaca, VO2 ml.kg-1.min-1, a frequência respiratória (FR, o espaço morto funcional estimado (VD/VT, o equivalente ventilatório de oxigênio (VE/VO2 e a pressão expiratória final do oxigênio (PETO2 foram maiores nas crianças, enquanto o volume corrente (VC, pulso de O2 e a pressão expiratória final do dióxido de carbono (PETCO2 foram menores. No pico do exercício, as crianças apresentaram FR e VD/VT superiores. No entanto, o pulso de O2, o VC, a ventilação pulmonar, o PETCO2 e a razão de troca respiratória foram menores nas crianças do que em adultos. CONCLUSÃO: Respostas cardiorrespiratórias e metabólicas durante o teste de esforço progressivo são diferentes em crianças em comparação aos adultos. Especificamente, essas diferenças sugerem que as crianças têm menor eficiência cardiovascular e respiratória. No entanto, as crianças apresentaram maior eficiência metabólica durante o teste
DEFF Research Database (Denmark)
Mahnke, Martina; Uprichard, Emma
2014-01-01
Imagine sailing across the ocean. The sun is shining, vastness all around you. And suddenly [BOOM] you’ve hit an invisible wall. Welcome to the Truman Show! Ever since Eli Pariser published his thoughts on a potential filter bubble, this movie scenario seems to have become reality, just with slight...... changes: it’s not the ocean, it’s the internet we’re talking about, and it’s not a TV show producer, but algorithms that constitute a sort of invisible wall. Building on this assumption, most research is trying to ‘tame the algorithmic tiger’. While this is a valuable and often inspiring approach, we...
Directory of Open Access Journals (Sweden)
Vinicius Minatel
2012-10-01
Full Text Available CONTEXTUALIZAÇÃO: A medida de pressão expiratória máxima (PEmáx possui algumas contraindicações, pois acredita-se que as respostas obtidas nessa medida são similares às respostas encontradas na manobra de Valsalva (MV. OBJETIVOS: O objetivo principal é avaliar a resposta da frequência cardíaca (FC durante a medida da PEmáx e da MV em jovens saudáveis, em diferentes posturas, para identificar se e em qual condição a PEmáx reproduz as respostas obtidas na MV e, adicionalmente, estimar o trabalho realizado nas manobras. MÉTODO: Doze jovens saudáveis foram avaliados, orientados e familiarizados com as manobras. A MV foi composta por um esforço expiratório (40 mmHg durante 15 segundos contra um manômetro. A PEmáx foi executada segundo a American Thoracic Society. Ambas as medidas foram realizadas nas posturas supino e sentado. Para a análise da variação da frequência cardíaca (∆FC, índice de Valsalva (IV, índice da PEmáx (IPEmáx e o trabalho estimado das manobras (Wtotal, Wisotime, Wtotal/∆FCtotal e Wisotime/∆FCisotime , utilizou-se ANOVA two-way com post-hoc de Holm-Sidak (pBACKGROUND: The measure of the maximal expiratory pressure (MEP has some contraindications, as it is believed that the responses obtained in this measure are similar to the Valsalva maneuver (VM. OBJECTIVE: The main purpose of this study was to evaluate the heart rate responses (HR during the MEP and the VM measures in healthy young men into different postures aiming to identify whether and in which situation the MEP reproduces the responses obtained in the VM. Additionally we aim to estimate the workload realized during the maneuvers. METHOD: Twelve healthy young men were evaluated, instructed and familiarized with the maneuvers. The VM was characterized by an expiratory effort (40 mmHg against a manometer for 15 seconds. The MEP measure has been performed according to the American Thoracic Society. Both measures were performed at sitting
Algorithms for Reinforcement Learning
Szepesvari, Csaba
2010-01-01
Reinforcement learning is a learning paradigm concerned with learning to control a system so as to maximize a numerical performance measure that expresses a long-term objective. What distinguishes reinforcement learning from supervised learning is that only partial feedback is given to the learner about the learner's predictions. Further, the predictions may have long term effects through influencing the future state of the controlled system. Thus, time plays a special role. The goal in reinforcement learning is to develop efficient learning algorithms, as well as to understand the algorithms'
Disk Density Tuning of a Maximal Random Packing.
Ebeida, Mohamed S; Rushdi, Ahmad A; Awad, Muhammad A; Mahmoud, Ahmed H; Yan, Dong-Ming; English, Shawn A; Owens, John D; Bajaj, Chandrajit L; Mitchell, Scott A
2016-08-01
We introduce an algorithmic framework for tuning the spatial density of disks in a maximal random packing, without changing the sizing function or radii of disks. Starting from any maximal random packing such as a Maximal Poisson-disk Sampling (MPS), we iteratively relocate, inject (add), or eject (remove) disks, using a set of three successively more-aggressive local operations. We may achieve a user-defined density, either more dense or more sparse, almost up to the theoretical structured limits. The tuned samples are conflict-free, retain coverage maximality, and, except in the extremes, retain the blue noise randomness properties of the input. We change the density of the packing one disk at a time, maintaining the minimum disk separation distance and the maximum domain coverage distance required of any maximal packing. These properties are local, and we can handle spatially-varying sizing functions. Using fewer points to satisfy a sizing function improves the efficiency of some applications. We apply the framework to improve the quality of meshes, removing non-obtuse angles; and to more accurately model fiber reinforced polymers for elastic and failure simulations.
Lawther, R
2018-01-01
In this work the author lets \\Phi be an irreducible root system, with Coxeter group W. He considers subsets of \\Phi which are abelian, meaning that no two roots in the set have sum in \\Phi \\cup \\{ 0 \\}. He classifies all maximal abelian sets (i.e., abelian sets properly contained in no other) up to the action of W: for each W-orbit of maximal abelian sets we provide an explicit representative X, identify the (setwise) stabilizer W_X of X in W, and decompose X into W_X-orbits. Abelian sets of roots are closely related to abelian unipotent subgroups of simple algebraic groups, and thus to abelian p-subgroups of finite groups of Lie type over fields of characteristic p. Parts of the work presented here have been used to confirm the p-rank of E_8(p^n), and (somewhat unexpectedly) to obtain for the first time the 2-ranks of the Monster and Baby Monster sporadic groups, together with the double cover of the latter. Root systems of classical type are dealt with quickly here; the vast majority of the present work con...
Directory of Open Access Journals (Sweden)
Kaarina Matilainen
Full Text Available Estimation of variance components by Monte Carlo (MC expectation maximization (EM restricted maximum likelihood (REML is computationally efficient for large data sets and complex linear mixed effects models. However, efficiency may be lost due to the need for a large number of iterations of the EM algorithm. To decrease the computing time we explored the use of faster converging Newton-type algorithms within MC REML implementations. The implemented algorithms were: MC Newton-Raphson (NR, where the information matrix was generated via sampling; MC average information(AI, where the information was computed as an average of observed and expected information; and MC Broyden's method, where the zero of the gradient was searched using a quasi-Newton-type algorithm. Performance of these algorithms was evaluated using simulated data. The final estimates were in good agreement with corresponding analytical ones. MC NR REML and MC AI REML enhanced convergence compared to MC EM REML and gave standard errors for the estimates as a by-product. MC NR REML required a larger number of MC samples, while each MC AI REML iteration demanded extra solving of mixed model equations by the number of parameters to be estimated. MC Broyden's method required the largest number of MC samples with our small data and did not give standard errors for the parameters directly. We studied the performance of three different convergence criteria for the MC AI REML algorithm. Our results indicate the importance of defining a suitable convergence criterion and critical value in order to obtain an efficient Newton-type method utilizing a MC algorithm. Overall, use of a MC algorithm with Newton-type methods proved feasible and the results encourage testing of these methods with different kinds of large-scale problem settings.
Energy Technology Data Exchange (ETDEWEB)
Almeida, Adino Americo Heimlich
2009-07-01
Graphics Processing Units (GPU) are high performance co-processors intended, originally, to improve the use and quality of computer graphics applications. Since researchers and practitioners realized the potential of using GPU for general purpose, their application has been extended to other fields out of computer graphics scope. The main objective of this work is to evaluate the impact of using GPU in two typical problems of Nuclear area. The neutron transport simulation using Monte Carlo method and solve heat equation in a bi-dimensional domain by finite differences method. To achieve this, we develop parallel algorithms for GPU and CPU in the two problems described above. The comparison showed that the GPU-based approach is faster than the CPU in a computer with two quad core processors, without precision loss. (author)
Maximizing benefits from resource development
International Nuclear Information System (INIS)
Skjelbred, B.
2002-01-01
The main objectives of Norwegian petroleum policy are to maximize the value creation for the country, develop a national oil and gas industry, and to be at the environmental forefront of long term resource management and coexistence with other industries. The paper presents a graph depicting production and net export of crude oil for countries around the world for 2002. Norway produced 3.41 mill b/d and exported 3.22 mill b/d. Norwegian petroleum policy measures include effective regulation and government ownership, research and technology development, and internationalisation. Research and development has been in five priority areas, including enhanced recovery, environmental protection, deep water recovery, small fields, and the gas value chain. The benefits of internationalisation includes capitalizing on Norwegian competency, exploiting emerging markets and the assurance of long-term value creation and employment. 5 figs
Maximizing synchronizability of duplex networks
Wei, Xiang; Emenheiser, Jeffrey; Wu, Xiaoqun; Lu, Jun-an; D'Souza, Raissa M.
2018-01-01
We study the synchronizability of duplex networks formed by two randomly generated network layers with different patterns of interlayer node connections. According to the master stability function, we use the smallest nonzero eigenvalue and the eigenratio between the largest and the second smallest eigenvalues of supra-Laplacian matrices to characterize synchronizability on various duplexes. We find that the interlayer linking weight and linking fraction have a profound impact on synchronizability of duplex networks. The increasingly large inter-layer coupling weight is found to cause either decreasing or constant synchronizability for different classes of network dynamics. In addition, negative node degree correlation across interlayer links outperforms positive degree correlation when most interlayer links are present. The reverse is true when a few interlayer links are present. The numerical results and understanding based on these representative duplex networks are illustrative and instructive for building insights into maximizing synchronizability of more realistic multiplex networks.
Energy Technology Data Exchange (ETDEWEB)
Barbosa, Diego R.; Silva, Alessandro L. da; Luciano, Edson Jose Rezende; Nepomuceno, Leonardo [Universidade Estadual Paulista (UNESP), Bauru, SP (Brazil). Dept. de Engenharia Eletrica], Emails: diego_eng.eletricista@hotmail.com, alessandrolopessilva@uol.com.br, edson.joserl@uol.com.br, leo@feb.unesp.br
2009-07-01
Problems of DC Optimal Power Flow (OPF) have been solved by various conventional optimization methods. When the modeling of DC OPF involves discontinuous functions or not differentiable, the use of solution methods based on conventional optimization is often not possible because of the difficulty in calculating the gradient vectors at points of discontinuity/non-differentiability of these functions. This paper proposes a method for solving the DC OPF based on Genetic Algorithms (GA) with real coding. The proposed GA has specific genetic operators to improve the quality and viability of the solution. The results are analyzed for an IEEE test system, and its solutions are compared, when possible, with those obtained by a method of interior point primal-dual logarithmic barrier. The results highlight the robustness of the method and feasibility of obtaining the solution to real systems.
Directory of Open Access Journals (Sweden)
Bruno Honorato da Silveira
2012-03-01
Full Text Available O objetivo do estudo foi comparar o ponto de deflexão da freqüência cardíaca (PDFC visual e método DMAX com a máxima fase estável de lactato (MFEL. Treze corredores executaram teste incremental Vameval e testes de cargas retangulares (TCR. A velocidade do PDFC visual (14,3 ± 1,13km.h-1 foi significantemente maior que o DMAX (13,2 ± 1,35km.h-1 além de apresentarem correlação não significante. Entretanto, nenhuma dessas velocidades foram diferentes da MFEL (13,8 ± 0,90km.h-1 embora somente o PDFC visual tenha apresentado correlação significante com a MFEL (r = 0,75. A concentração de lactato sanguíneo não apresentou estabilidade em oito sujeitos no TCR na intensidade do PDFC visual o qual nos leva a concluir que este não é um índice confiável para estimativa da MFEL. No entanto, este índice pode ser usado como um indicador de capacidade aeróbia.The aim of study was to compare heart rate deflection point (HRDP determined by visual and DMAX methods to Maximal lactate steady state (MLSS. Thirteen runners carried out incremental test Vameval and constant load tests (CLT. Velocity of HRDP (14,3 ± 1,13km.h-1 was significantly higher compared to DMAX (13,2 ± 1,35km.h-1 but they were not significantly correlated. However, both velocities, HRDP and DMAX, were not different from MLSS (13,8 ± 0,90km.h-1 while only HRDP has been significant correlated with MLSS (r = 0,75. On eight runners during CLT the blood lactate concentration did not show stability at HRDP velocity which to let us to conclude that HRPD is not appropriated to estimate MLSS. However, it may be used as aerobic capacity index.
VIOLATION OF CONVERSATION MAXIM ON TV ADVERTISEMENTS
Directory of Open Access Journals (Sweden)
Desak Putu Eka Pratiwi
2015-07-01
Full Text Available Maxim is a principle that must be obeyed by all participants textually and interpersonally in order to have a smooth communication process. Conversation maxim is divided into four namely maxim of quality, maxim of quantity, maxim of relevance, and maxim of manner of speaking. Violation of the maxim may occur in a conversation in which the information the speaker has is not delivered well to his speaking partner. Violation of the maxim in a conversation will result in an awkward impression. The example of violation is the given information that is redundant, untrue, irrelevant, or convoluted. Advertisers often deliberately violate the maxim to create unique and controversial advertisements. This study aims to examine the violation of maxims in conversations of TV ads. The source of data in this research is food advertisements aired on TV media. Documentation and observation methods are applied to obtain qualitative data. The theory used in this study is a maxim theory proposed by Grice (1975. The results of the data analysis are presented with informal method. The results of this study show an interesting fact that the violation of maxim in a conversation found in the advertisement exactly makes the advertisements very attractive and have a high value.
De Götzen , Amalia; Mion , Luca; Tache , Olivier
2007-01-01
International audience; We call sound algorithms the categories of algorithms that deal with digital sound signal. Sound algorithms appeared in the very infancy of computer. Sound algorithms present strong specificities that are the consequence of two dual considerations: the properties of the digital sound signal itself and its uses, and the properties of auditory perception.
Wang, Lui; Bayer, Steven E.
1991-01-01
Genetic algorithms are mathematical, highly parallel, adaptive search procedures (i.e., problem solving methods) based loosely on the processes of natural genetics and Darwinian survival of the fittest. Basic genetic algorithms concepts are introduced, genetic algorithm applications are introduced, and results are presented from a project to develop a software tool that will enable the widespread use of genetic algorithm technology.
Polarity related influence maximization in signed social networks.
Directory of Open Access Journals (Sweden)
Dong Li
Full Text Available Influence maximization in social networks has been widely studied motivated by applications like spread of ideas or innovations in a network and viral marketing of products. Current studies focus almost exclusively on unsigned social networks containing only positive relationships (e.g. friend or trust between users. Influence maximization in signed social networks containing both positive relationships and negative relationships (e.g. foe or distrust between users is still a challenging problem that has not been studied. Thus, in this paper, we propose the polarity-related influence maximization (PRIM problem which aims to find the seed node set with maximum positive influence or maximum negative influence in signed social networks. To address the PRIM problem, we first extend the standard Independent Cascade (IC model to the signed social networks and propose a Polarity-related Independent Cascade (named IC-P diffusion model. We prove that the influence function of the PRIM problem under the IC-P model is monotonic and submodular Thus, a greedy algorithm can be used to achieve an approximation ratio of 1-1/e for solving the PRIM problem in signed social networks. Experimental results on two signed social network datasets, Epinions and Slashdot, validate that our approximation algorithm for solving the PRIM problem outperforms state-of-the-art methods.
Maximizing ROI (return on information)
Energy Technology Data Exchange (ETDEWEB)
McDonald, B.
2000-05-01
The role and importance of managing information are discussed, underscoring the importance by quoting from the report of the International Data Corporation, according to which Fortune 500 companies lost $ 12 billion in 1999 due to inefficiencies resulting from intellectual re-work, substandard performance , and inability to find knowledge resources. The report predicts that this figure will rise to $ 31.5 billion by 2003. Key impediments to implementing knowledge management systems are identified as : the cost and human resources requirement of deployment; inflexibility of historical systems to adapt to change; and the difficulty of achieving corporate acceptance of inflexible software products that require changes in 'normal' ways of doing business. The author recommends the use of model, document and rule-independent systems with a document centered interface (DCI), employing rapid application development (RAD) and object technologies and visual model development, which eliminate these problems, making it possible for companies to maximize their return on information (ROI), and achieve substantial savings in implementation costs.
Maximizing the optical network capacity.
Bayvel, Polina; Maher, Robert; Xu, Tianhua; Liga, Gabriele; Shevchenko, Nikita A; Lavery, Domaniç; Alvarado, Alex; Killey, Robert I
2016-03-06
Most of the digital data transmitted are carried by optical fibres, forming the great part of the national and international communication infrastructure. The information-carrying capacity of these networks has increased vastly over the past decades through the introduction of wavelength division multiplexing, advanced modulation formats, digital signal processing and improved optical fibre and amplifier technology. These developments sparked the communication revolution and the growth of the Internet, and have created an illusion of infinite capacity being available. But as the volume of data continues to increase, is there a limit to the capacity of an optical fibre communication channel? The optical fibre channel is nonlinear, and the intensity-dependent Kerr nonlinearity limit has been suggested as a fundamental limit to optical fibre capacity. Current research is focused on whether this is the case, and on linear and nonlinear techniques, both optical and electronic, to understand, unlock and maximize the capacity of optical communications in the nonlinear regime. This paper describes some of them and discusses future prospects for success in the quest for capacity. © 2016 The Authors.
Memetic algorithms for de novo motif-finding in biomedical sequences.
Bi, Chengpeng
2012-09-01
The objectives of this study are to design and implement a new memetic algorithm for de novo motif discovery, which is then applied to detect important signals hidden in various biomedical molecular sequences. In this paper, memetic algorithms are developed and tested in de novo motif-finding problems. Several strategies in the algorithm design are employed that are to not only efficiently explore the multiple sequence local alignment space, but also effectively uncover the molecular signals. As a result, there are a number of key features in the implementation of the memetic motif-finding algorithm (MaMotif), including a chromosome replacement operator, a chromosome alteration-aware local search operator, a truncated local search strategy, and a stochastic operation of local search imposed on individual learning. To test the new algorithm, we compare MaMotif with a few of other similar algorithms using simulated and experimental data including genomic DNA, primary microRNA sequences (let-7 family), and transmembrane protein sequences. The new memetic motif-finding algorithm is successfully implemented in C++, and exhaustively tested with various simulated and real biological sequences. In the simulation, it shows that MaMotif is the most time-efficient algorithm compared with others, that is, it runs 2 times faster than the expectation maximization (EM) method and 16 times faster than the genetic algorithm-based EM hybrid. In both simulated and experimental testing, results show that the new algorithm is compared favorably or superior to other algorithms. Notably, MaMotif is able to successfully discover the transcription factors' binding sites in the chromatin immunoprecipitation followed by massively parallel sequencing (ChIP-Seq) data, correctly uncover the RNA splicing signals in gene expression, and precisely find the highly conserved helix motif in the transmembrane protein sequences, as well as rightly detect the palindromic segments in the primary micro
Joux, Antoine
2009-01-01
Illustrating the power of algorithms, Algorithmic Cryptanalysis describes algorithmic methods with cryptographically relevant examples. Focusing on both private- and public-key cryptographic algorithms, it presents each algorithm either as a textual description, in pseudo-code, or in a C code program.Divided into three parts, the book begins with a short introduction to cryptography and a background chapter on elementary number theory and algebra. It then moves on to algorithms, with each chapter in this section dedicated to a single topic and often illustrated with simple cryptographic applic
Accelerated EM-based clustering of large data sets
Verbeek, J.J.; Nunnink, J.R.J.; Vlassis, N.
2006-01-01
Motivated by the poor performance (linear complexity) of the EM algorithm in clustering large data sets, and inspired by the successful accelerated versions of related algorithms like k-means, we derive an accelerated variant of the EM algorithm for Gaussian mixtures that: (1) offers speedups that
On Maximizing the Throughput of Packet Transmission under Energy Constraints.
Wu, Weiwei; Dai, Guangli; Li, Yan; Shan, Feng
2018-06-23
More and more Internet of Things (IoT) wireless devices have been providing ubiquitous services over the recent years. Since most of these devices are powered by batteries, a fundamental trade-off to be addressed is the depleted energy and the achieved data throughput in wireless data transmission. By exploiting the rate-adaptive capacities of wireless devices, most existing works on energy-efficient data transmission try to design rate-adaptive transmission policies to maximize the amount of transmitted data bits under the energy constraints of devices. Such solutions, however, cannot apply to scenarios where data packets have respective deadlines and only integrally transmitted data packets contribute. Thus, this paper introduces a notion of weighted throughput, which measures how much total value of data packets are successfully and integrally transmitted before their own deadlines. By designing efficient rate-adaptive transmission policies, this paper aims to make the best use of the energy and maximize the weighted throughput. What is more challenging but with practical significance, we consider the fading effect of wireless channels in both offline and online scenarios. In the offline scenario, we develop an optimal algorithm that computes the optimal solution in pseudo-polynomial time, which is the best possible solution as the problem undertaken is NP-hard. In the online scenario, we propose an efficient heuristic algorithm based on optimal properties derived for the optimal offline solution. Simulation results validate the efficiency of the proposed algorithm.
Hougardy, Stefan
2016-01-01
Algorithms play an increasingly important role in nearly all fields of mathematics. This book allows readers to develop basic mathematical abilities, in particular those concerning the design and analysis of algorithms as well as their implementation. It presents not only fundamental algorithms like the sieve of Eratosthenes, the Euclidean algorithm, sorting algorithms, algorithms on graphs, and Gaussian elimination, but also discusses elementary data structures, basic graph theory, and numerical questions. In addition, it provides an introduction to programming and demonstrates in detail how to implement algorithms in C++. This textbook is suitable for students who are new to the subject and covers a basic mathematical lecture course, complementing traditional courses on analysis and linear algebra. Both authors have given this "Algorithmic Mathematics" course at the University of Bonn several times in recent years.
Does mental exertion alter maximal muscle activation?
Directory of Open Access Journals (Sweden)
Vianney eRozand
2014-09-01
Full Text Available Mental exertion is known to impair endurance performance, but its effects on neuromuscular function remain unclear. The purpose of this study was to test the hypothesis that mental exertion reduces torque and muscle activation during intermittent maximal voluntary contractions of the knee extensors. Ten subjects performed in a randomized order three separate mental exertion conditions lasting 27 minutes each: i high mental exertion (incongruent Stroop task, ii moderate mental exertion (congruent Stroop task, iii low mental exertion (watching a movie. In each condition, mental exertion was combined with ten intermittent maximal voluntary contractions of the knee extensor muscles (one maximal voluntary contraction every 3 minutes. Neuromuscular function was assessed using electrical nerve stimulation. Maximal voluntary torque, maximal muscle activation and other neuromuscular parameters were similar across mental exertion conditions and did not change over time. These findings suggest that mental exertion does not affect neuromuscular function during intermittent maximal voluntary contractions of the knee extensors.
On maximal massive 3D supergravity
Bergshoeff , Eric A; Hohm , Olaf; Rosseel , Jan; Townsend , Paul K
2010-01-01
ABSTRACT We construct, at the linearized level, the three-dimensional (3D) N = 4 supersymmetric " general massive supergravity " and the maximally supersymmetric N = 8 " new massive supergravity ". We also construct the maximally supersymmetric linearized N = 7 topologically massive supergravity, although we expect N = 6 to be maximal at the non-linear level. (Bergshoeff, Eric A) (Hohm, Olaf) (Rosseel, Jan) P.K.Townsend@da...
Inclusive Fitness Maximization:An Axiomatic Approach
Okasha, Samir; Weymark, John; Bossert, Walter
2014-01-01
Kin selection theorists argue that evolution in social contexts will lead organisms to behave as if maximizing their inclusive, as opposed to personal, fitness. The inclusive fitness concept allows biologists to treat organisms as akin to rational agents seeking to maximize a utility function. Here we develop this idea and place it on a firm footing by employing a standard decision-theoretic methodology. We show how the principle of inclusive fitness maximization and a related principle of qu...
Tel, G.
We define the notion of total algorithms for networks of processes. A total algorithm enforces that a "decision" is taken by a subset of the processes, and that participation of all processes is required to reach this decision. Total algorithms are an important building block in the design of
Activity versus outcome maximization in time management.
Malkoc, Selin A; Tonietto, Gabriela N
2018-04-30
Feeling time-pressed has become ubiquitous. Time management strategies have emerged to help individuals fit in more of their desired and necessary activities. We provide a review of these strategies. In doing so, we distinguish between two, often competing, motives people have in managing their time: activity maximization and outcome maximization. The emerging literature points to an important dilemma: a given strategy that maximizes the number of activities might be detrimental to outcome maximization. We discuss such factors that might hinder performance in work tasks and enjoyment in leisure tasks. Finally, we provide theoretically grounded recommendations that can help balance these two important goals in time management. Published by Elsevier Ltd.
On the maximal superalgebras of supersymmetric backgrounds
International Nuclear Information System (INIS)
Figueroa-O'Farrill, Jose; Hackett-Jones, Emily; Moutsopoulos, George; Simon, Joan
2009-01-01
In this paper we give a precise definition of the notion of a maximal superalgebra of certain types of supersymmetric supergravity backgrounds, including the Freund-Rubin backgrounds, and propose a geometric construction extending the well-known construction of its Killing superalgebra. We determine the structure of maximal Lie superalgebras and show that there is a finite number of isomorphism classes, all related via contractions from an orthosymplectic Lie superalgebra. We use the structure theory to show that maximally supersymmetric waves do not possess such a maximal superalgebra, but that the maximally supersymmetric Freund-Rubin backgrounds do. We perform the explicit geometric construction of the maximal superalgebra of AdS 4 X S 7 and find that it is isomorphic to osp(1|32). We propose an algebraic construction of the maximal superalgebra of any background asymptotic to AdS 4 X S 7 and we test this proposal by computing the maximal superalgebra of the M2-brane in its two maximally supersymmetric limits, finding agreement.
Task-oriented maximally entangled states
International Nuclear Information System (INIS)
Agrawal, Pankaj; Pradhan, B
2010-01-01
We introduce the notion of a task-oriented maximally entangled state (TMES). This notion depends on the task for which a quantum state is used as the resource. TMESs are the states that can be used to carry out the task maximally. This concept may be more useful than that of a general maximally entangled state in the case of a multipartite system. We illustrate this idea by giving an operational definition of maximally entangled states on the basis of communication tasks of teleportation and superdense coding. We also give examples and a procedure to obtain such TMESs for n-qubit systems.
Sum Rate Maximization using Linear Precoding and Decoding in the Multiuser MIMO Downlink
Tenenbaum, Adam J.; Adve, Raviraj S.
2008-01-01
We propose an algorithm to maximize the instantaneous sum data rate transmitted by a base station in the downlink of a multiuser multiple-input, multiple-output system. The transmitter and the receivers may each be equipped with multiple antennas and each user may receive more than one data stream. We show that maximizing the sum rate is closely linked to minimizing the product of mean squared errors (PMSE). The algorithm employs an uplink/downlink duality to iteratively design transmit-recei...
Wobbling and LSF-based maximum likelihood expectation maximization reconstruction for wobbling PET
International Nuclear Information System (INIS)
Kim, Hang-Keun; Son, Young-Don; Kwon, Dae-Hyuk; Joo, Yohan; Cho, Zang-Hee
2016-01-01
Positron emission tomography (PET) is a widely used imaging modality; however, the PET spatial resolution is not yet satisfactory for precise anatomical localization of molecular activities. Detector size is the most important factor because it determines the intrinsic resolution, which is approximately half of the detector size and determines the ultimate PET resolution. Detector size, however, cannot be made too small because both the decreased detection efficiency and the increased septal penetration effect degrade the image quality. A wobbling and line spread function (LSF)-based maximum likelihood expectation maximization (WL-MLEM) algorithm, which combined the MLEM iterative reconstruction algorithm with wobbled sampling and LSF-based deconvolution using the system matrix, was proposed for improving the spatial resolution of PET without reducing the scintillator or detector size. The new algorithm was evaluated using a simulation, and its performance was compared with that of the existing algorithms, such as conventional MLEM and LSF-based MLEM. Simulations demonstrated that the WL-MLEM algorithm yielded higher spatial resolution and image quality than the existing algorithms. The WL-MLEM algorithm with wobbling PET yielded substantially improved resolution compared with conventional algorithms with stationary PET. The algorithm can be easily extended to other iterative reconstruction algorithms, such as maximum a priori (MAP) and ordered subset expectation maximization (OSEM). The WL-MLEM algorithm with wobbling PET may offer improvements in both sensitivity and resolution, the two most sought-after features in PET design. - Highlights: • This paper proposed WL-MLEM algorithm for PET and demonstrated its performance. • WL-MLEM algorithm effectively combined wobbling and line spread function based MLEM. • WL-MLEM provided improvements in the spatial resolution and the PET image quality. • WL-MLEM can be easily extended to the other iterative
Maximally Entangled Multipartite States: A Brief Survey
International Nuclear Information System (INIS)
Enríquez, M; Wintrowicz, I; Życzkowski, K
2016-01-01
The problem of identifying maximally entangled quantum states of a composite quantum systems is analyzed. We review some states of multipartite systems distinguished with respect to certain measures of quantum entanglement. Numerical results obtained for 4-qubit pure states illustrate the fact that the notion of maximally entangled state depends on the measure used. (paper)
Utility maximization and mode of payment
Koning, R.H.; Ridder, G.; Heijmans, R.D.H.; Pollock, D.S.G.; Satorra, A.
2000-01-01
The implications of stochastic utility maximization in a model of choice of payment are examined. Three types of compatibility with utility maximization are distinguished: global compatibility, local compatibility on an interval, and local compatibility on a finite set of points. Keywords:
Corporate Social Responsibility and Profit Maximizing Behaviour
Becchetti, Leonardo; Giallonardo, Luisa; Tessitore, Maria Elisabetta
2005-01-01
We examine the behavior of a profit maximizing monopolist in a horizontal differentiation model in which consumers differ in their degree of social responsibility (SR) and consumers SR is dynamically influenced by habit persistence. The model outlines parametric conditions under which (consumer driven) corporate social responsibility is an optimal choice compatible with profit maximizing behavior.
Inclusive fitness maximization: An axiomatic approach.
Okasha, Samir; Weymark, John A; Bossert, Walter
2014-06-07
Kin selection theorists argue that evolution in social contexts will lead organisms to behave as if maximizing their inclusive, as opposed to personal, fitness. The inclusive fitness concept allows biologists to treat organisms as akin to rational agents seeking to maximize a utility function. Here we develop this idea and place it on a firm footing by employing a standard decision-theoretic methodology. We show how the principle of inclusive fitness maximization and a related principle of quasi-inclusive fitness maximization can be derived from axioms on an individual׳s 'as if preferences' (binary choices) for the case in which phenotypic effects are additive. Our results help integrate evolutionary theory and rational choice theory, help draw out the behavioural implications of inclusive fitness maximization, and point to a possible way in which evolution could lead organisms to implement it. Copyright © 2014 Elsevier Ltd. All rights reserved.
Maximal Entanglement in High Energy Physics
Directory of Open Access Journals (Sweden)
Alba Cervera-Lierta, José I. Latorre, Juan Rojo, Luca Rottoli
2017-11-01
Full Text Available We analyze how maximal entanglement is generated at the fundamental level in QED by studying correlations between helicity states in tree-level scattering processes at high energy. We demonstrate that two mechanisms for the generation of maximal entanglement are at work: i $s$-channel processes where the virtual photon carries equal overlaps of the helicities of the final state particles, and ii the indistinguishable superposition between $t$- and $u$-channels. We then study whether requiring maximal entanglement constrains the coupling structure of QED and the weak interactions. In the case of photon-electron interactions unconstrained by gauge symmetry, we show how this requirement allows reproducing QED. For $Z$-mediated weak scattering, the maximal entanglement principle leads to non-trivial predictions for the value of the weak mixing angle $\\theta_W$. Our results are a first step towards understanding the connections between maximal entanglement and the fundamental symmetries of high-energy physics.
Efficient Maximum Likelihood Estimation for Pedigree Data with the Sum-Product Algorithm.
Engelhardt, Alexander; Rieger, Anna; Tresch, Achim; Mansmann, Ulrich
2016-01-01
We analyze data sets consisting of pedigrees with age at onset of colorectal cancer (CRC) as phenotype. The occurrence of familial clusters of CRC suggests the existence of a latent, inheritable risk factor. We aimed to compute the probability of a family possessing this risk factor as well as the hazard rate increase for these risk factor carriers. Due to the inheritability of this risk factor, the estimation necessitates a costly marginalization of the likelihood. We propose an improved EM algorithm by applying factor graphs and the sum-product algorithm in the E-step. This reduces the computational complexity from exponential to linear in the number of family members. Our algorithm is as precise as a direct likelihood maximization in a simulation study and a real family study on CRC risk. For 250 simulated families of size 19 and 21, the runtime of our algorithm is faster by a factor of 4 and 29, respectively. On the largest family (23 members) in the real data, our algorithm is 6 times faster. We introduce a flexible and runtime-efficient tool for statistical inference in biomedical event data with latent variables that opens the door for advanced analyses of pedigree data. © 2017 S. Karger AG, Basel.
Change detection algorithms for surveillance in visual iot: a comparative study
International Nuclear Information System (INIS)
Akram, B.A.; Zafar, A.; Akbar, A.H.; Chaudhry, A.
2018-01-01
The VIoT (Visual Internet of Things) connects virtual information world with real world objects using sensors and pervasive computing. For video surveillance in VIoT, ChD (Change Detection) is a critical component. ChD algorithms identify regions of change in multiple images of the same scene recorded at different time intervals for video surveillance. This paper presents performance comparison of histogram thresholding and classification ChD algorithms using quantitative measures for video surveillance in VIoT based on salient features of datasets. The thresholding algorithms Otsu, Kapur, Rosin and classification methods k-means, EM (Expectation Maximization) were simulated in MATLAB using diverse datasets. For performance evaluation, the quantitative measures used include OSR (Overall Success Rate), YC (Yule’s Coefficient) and JC (Jaccard’s Coefficient), execution time and memory consumption. Experimental results showed that Kapur’s algorithm performed better for both indoor and outdoor environments with illumination changes, shadowing and medium to fast moving objects. However, it reflected degraded performance for small object size with minor changes. Otsu algorithm showed better results for indoor environments with slow to medium changes and nomadic object mobility. k-means showed good results in indoor environment with small object size producing slow change, no shadowing and scarce illumination changes. (author)
Acceleration of the direct reconstruction of linear parametric images using nested algorithms
International Nuclear Information System (INIS)
Wang Guobao; Qi Jinyi
2010-01-01
Parametric imaging using dynamic positron emission tomography (PET) provides important information for biological research and clinical diagnosis. Indirect and direct methods have been developed for reconstructing linear parametric images from dynamic PET data. Indirect methods are relatively simple and easy to implement because the image reconstruction and kinetic modeling are performed in two separate steps. Direct methods estimate parametric images directly from raw PET data and are statistically more efficient. However, the convergence rate of direct algorithms can be slow due to the coupling between the reconstruction and kinetic modeling. Here we present two fast gradient-type algorithms for direct reconstruction of linear parametric images. The new algorithms decouple the reconstruction and linear parametric modeling at each iteration by employing the principle of optimization transfer. Convergence speed is accelerated by running more sub-iterations of linear parametric estimation because the computation cost of the linear parametric modeling is much less than that of the image reconstruction. Computer simulation studies demonstrated that the new algorithms converge much faster than the traditional expectation maximization (EM) and the preconditioned conjugate gradient algorithms for dynamic PET.
Change Detection Algorithms for Surveillance in Visual IoT: A Comparative Study
Akram, Beenish Ayesha; Zafar, Amna; Akbar, Ali Hammad; Wajid, Bilal; Chaudhry, Shafique Ahmad
2018-01-01
The VIoT (Visual Internet of Things) connects virtual information world with real world objects using sensors and pervasive computing. For video surveillance in VIoT, ChD (Change Detection) is a critical component. ChD algorithms identify regions of change in multiple images of the same scene recorded at different time intervals for video surveillance. This paper presents performance comparison of histogram thresholding and classification ChD algorithms using quantitative measures for video surveillance in VIoT based on salient features of datasets. The thresholding algorithms Otsu, Kapur, Rosin and classification methods k-means, EM (Expectation Maximization) were simulated in MATLAB using diverse datasets. For performance evaluation, the quantitative measures used include OSR (Overall Success Rate), YC (Yule's Coefficient) and JC (Jaccard's Coefficient), execution time and memory consumption. Experimental results showed that Kapur's algorithm performed better for both indoor and outdoor environments with illumination changes, shadowing and medium to fast moving objects. However, it reflected degraded performance for small object size with minor changes. Otsu algorithm showed better results for indoor environments with slow to medium changes and nomadic object mobility. k-means showed good results in indoor environment with small object size producing slow change, no shadowing and scarce illumination changes.
International Nuclear Information System (INIS)
Roche-Lima, Abiel; Thulasiram, Ruppa K
2012-01-01
Finite automata, in which each transition is augmented with an output label in addition to the familiar input label, are considered finite-state transducers. Transducers have been used to analyze some fundamental issues in bioinformatics. Weighted finite-state transducers have been proposed to pairwise alignments of DNA and protein sequences; as well as to develop kernels for computational biology. Machine learning algorithms for conditional transducers have been implemented and used for DNA sequence analysis. Transducer learning algorithms are based on conditional probability computation. It is calculated by using techniques, such as pair-database creation, normalization (with Maximum-Likelihood normalization) and parameters optimization (with Expectation-Maximization - EM). These techniques are intrinsically costly for computation, even worse when are applied to bioinformatics, because the databases sizes are large. In this work, we describe a parallel implementation of an algorithm to learn conditional transducers using these techniques. The algorithm is oriented to bioinformatics applications, such as alignments, phylogenetic trees, and other genome evolution studies. Indeed, several experiences were developed using the parallel and sequential algorithm on Westgrid (specifically, on the Breeze cluster). As results, we obtain that our parallel algorithm is scalable, because execution times are reduced considerably when the data size parameter is increased. Another experience is developed by changing precision parameter. In this case, we obtain smaller execution times using the parallel algorithm. Finally, number of threads used to execute the parallel algorithm on the Breezy cluster is changed. In this last experience, we obtain as result that speedup is considerably increased when more threads are used; however there is a convergence for number of threads equal to or greater than 16.
Bipartite Bell Inequality and Maximal Violation
International Nuclear Information System (INIS)
Li Ming; Fei Shaoming; Li-Jost Xian-Qing
2011-01-01
We present new bell inequalities for arbitrary dimensional bipartite quantum systems. The maximal violation of the inequalities is computed. The Bell inequality is capable of detecting quantum entanglement of both pure and mixed quantum states more effectively. (general)
HEALTH INSURANCE: CONTRIBUTIONS AND REIMBURSEMENT MAXIMAL
HR Division
2000-01-01
Affected by both the salary adjustment index on 1.1.2000 and the evolution of the staff members and fellows population, the average reference salary, which is used as an index for fixed contributions and reimbursement maximal, has changed significantly. An adjustment of the amounts of the reimbursement maximal and the fixed contributions is therefore necessary, as from 1 January 2000.Reimbursement maximalThe revised reimbursement maximal will appear on the leaflet summarising the benefits for the year 2000, which will soon be available from the divisional secretariats and from the AUSTRIA office at CERN.Fixed contributionsThe fixed contributions, applicable to some categories of voluntarily insured persons, are set as follows (amounts in CHF for monthly contributions):voluntarily insured member of the personnel, with complete coverage:815,- (was 803,- in 1999)voluntarily insured member of the personnel, with reduced coverage:407,- (was 402,- in 1999)voluntarily insured no longer dependent child:326,- (was 321...
Maximal Inequalities for Dependent Random Variables
DEFF Research Database (Denmark)
Hoffmann-Jorgensen, Jorgen
2016-01-01
Maximal inequalities play a crucial role in many probabilistic limit theorem; for instance, the law of large numbers, the law of the iterated logarithm, the martingale limit theorem and the central limit theorem. Let X-1, X-2,... be random variables with partial sums S-k = X-1 + ... + X-k. Then a......Maximal inequalities play a crucial role in many probabilistic limit theorem; for instance, the law of large numbers, the law of the iterated logarithm, the martingale limit theorem and the central limit theorem. Let X-1, X-2,... be random variables with partial sums S-k = X-1 + ... + X......-k. Then a maximal inequality gives conditions ensuring that the maximal partial sum M-n = max(1) (...
Maximizing Function through Intelligent Robot Actuator Control
National Aeronautics and Space Administration — Maximizing Function through Intelligent Robot Actuator Control Successful missions to Mars and beyond will only be possible with the support of high-performance...
An ethical justification of profit maximization
DEFF Research Database (Denmark)
Koch, Carsten Allan
2010-01-01
In much of the literature on business ethics and corporate social responsibility, it is more or less taken for granted that attempts to maximize profits are inherently unethical. The purpose of this paper is to investigate whether an ethical argument can be given in support of profit maximizing...... behaviour. It is argued that some form of consequential ethics must be applied, and that both profit seeking and profit maximization can be defended from a rule-consequential point of view. It is noted, however, that the result does not apply unconditionally, but requires that certain form of profit (and...... utility) maximizing actions are ruled out, e.g., by behavioural norms or formal institutions....
A definition of maximal CP-violation
International Nuclear Information System (INIS)
Roos, M.
1985-01-01
The unitary matrix of quark flavour mixing is parametrized in a general way, permitting a mathematically natural definition of maximal CP violation. Present data turn out to violate this definition by 2-3 standard deviations. (orig.)
A cosmological problem for maximally symmetric supergravity
International Nuclear Information System (INIS)
German, G.; Ross, G.G.
1986-01-01
Under very general considerations it is shown that inflationary models of the universe based on maximally symmetric supergravity with flat potentials are unable to resolve the cosmological energy density (Polonyi) problem. (orig.)
Insulin resistance and maximal oxygen uptake
DEFF Research Database (Denmark)
Seibaek, Marie; Vestergaard, Henrik; Burchardt, Hans
2003-01-01
BACKGROUND: Type 2 diabetes, coronary atherosclerosis, and physical fitness all correlate with insulin resistance, but the relative importance of each component is unknown. HYPOTHESIS: This study was undertaken to determine the relationship between insulin resistance, maximal oxygen uptake......, and the presence of either diabetes or ischemic heart disease. METHODS: The study population comprised 33 patients with and without diabetes and ischemic heart disease. Insulin resistance was measured by a hyperinsulinemic euglycemic clamp; maximal oxygen uptake was measured during a bicycle exercise test. RESULTS......: There was a strong correlation between maximal oxygen uptake and insulin-stimulated glucose uptake (r = 0.7, p = 0.001), and maximal oxygen uptake was the only factor of importance for determining insulin sensitivity in a model, which also included the presence of diabetes and ischemic heart disease. CONCLUSION...
Maximal supergravities and the E10 model
International Nuclear Information System (INIS)
Kleinschmidt, Axel; Nicolai, Hermann
2006-01-01
The maximal rank hyperbolic Kac-Moody algebra e 10 has been conjectured to play a prominent role in the unification of duality symmetries in string and M theory. We review some recent developments supporting this conjecture
DEFF Research Database (Denmark)
Cherchi, Elisabetta; Guevara, Cristian
2012-01-01
with cross-sectional or with panel data, and (d) EM systematically attained more efficient estimators than the MSL method. The results imply that if the purpose of the estimation is only to determine the ratios of the model parameters (e.g., the value of time), the EM method should be preferred. For all......The random coefficients logit model allows a more realistic representation of agents' behavior. However, the estimation of that model may involve simulation, which may become impractical with many random coefficients because of the curse of dimensionality. In this paper, the traditional maximum...... simulated likelihood (MSL) method is compared with the alternative expectation- maximization (EM) method, which does not require simulation. Previous literature had shown that for cross-sectional data, MSL outperforms the EM method in the ability to recover the true parameters and estimation time...
Gaussian maximally multipartite-entangled states
Facchi, Paolo; Florio, Giuseppe; Lupo, Cosmo; Mancini, Stefano; Pascazio, Saverio
2009-12-01
We study maximally multipartite-entangled states in the context of Gaussian continuous variable quantum systems. By considering multimode Gaussian states with constrained energy, we show that perfect maximally multipartite-entangled states, which exhibit the maximum amount of bipartite entanglement for all bipartitions, only exist for systems containing n=2 or 3 modes. We further numerically investigate the structure of these states and their frustration for n≤7 .
Gaussian maximally multipartite-entangled states
International Nuclear Information System (INIS)
Facchi, Paolo; Florio, Giuseppe; Pascazio, Saverio; Lupo, Cosmo; Mancini, Stefano
2009-01-01
We study maximally multipartite-entangled states in the context of Gaussian continuous variable quantum systems. By considering multimode Gaussian states with constrained energy, we show that perfect maximally multipartite-entangled states, which exhibit the maximum amount of bipartite entanglement for all bipartitions, only exist for systems containing n=2 or 3 modes. We further numerically investigate the structure of these states and their frustration for n≤7.
Neutrino mass textures with maximal CP violation
International Nuclear Information System (INIS)
Aizawa, Ichiro; Kitabayashi, Teruyuki; Yasue, Masaki
2005-01-01
We show three types of neutrino mass textures, which give maximal CP violation as well as maximal atmospheric neutrino mixing. These textures are described by six real mass parameters: one specified by two complex flavor neutrino masses and two constrained ones and the others specified by three complex flavor neutrino masses. In each texture, we calculate mixing angles and masses, which are consistent with observed data, as well as Majorana CP phases
Why firms should not always maximize profits
Kolstad, Ivar
2006-01-01
Though corporate social responsibility (CSR) is on the agenda of most major corporations, corporate executives still largely support the view that corporations should maximize the returns to their owners. There are two lines of defence for this position. One is the Friedmanian view that maximizing owner returns is the corporate social responsibility of corporations. The other is a position voiced by many executives, that CSR and profits go together. This paper argues that the first position i...
Maximally Informative Observables and Categorical Perception
Tsiang, Elaine
2012-01-01
We formulate the problem of perception in the framework of information theory, and prove that categorical perception is equivalent to the existence of an observable that has the maximum possible information on the target of perception. We call such an observable maximally informative. Regardless whether categorical perception is real, maximally informative observables can form the basis of a theory of perception. We conclude with the implications of such a theory for the problem of speech per...
Consumer-driven profit maximization in broiler production and processing
Directory of Open Access Journals (Sweden)
Ecio de Farias Costa
2004-01-01
Full Text Available Increased emphasis on consumer markets in broiler profit-maximizing modeling generates results that differ from those by traditional profit-maximization models. This approach reveals that the adoption of step pricing and consideration of marketing options (examples of responsiveness to consumers affect the optimal feed formulation levels and types of broiler production to generate maximum profitability. The adoption of step pricing attests that higher profits can be obtained for targeted weights only if premium prices for broiler products are contracted.Um aumento na ênfase dada ao mercado de consumidores de carne de frango e modelos de maximização de lucros na produção de frangos de corte geram resultados que diferem daqueles obtidos em modelos tradicionais de maximização de lucros. Esta metodologia revela que a adoção de step-pricing e considerando opções de mercado (exemplos de resposta às preferências de consumidores afetam os níveis ótimos de formulação de rações e os tipos de produção de frangos de corte que geram uma lucratividade máxima. A adoção de step-pricing atesta que maiores lucros podem ser obtidos para pesos-alvo somente se preços-prêmio para produtos processados de carne de frango forem contratados.
Shareholder, stakeholder-owner or broad stakeholder maximization
Mygind, Niels
2004-01-01
With reference to the discussion about shareholder versus stakeholder maximization it is argued that the normal type of maximization is in fact stakeholder-owner maxi-mization. This means maximization of the sum of the value of the shares and stake-holder benefits belonging to the dominating stakeholder-owner. Maximization of shareholder value is a special case of owner-maximization, and only under quite re-strictive assumptions shareholder maximization is larger or equal to stakeholder-owner...
Automatic control algorithm effects on energy production
Mcnerney, G. M.
1981-01-01
A computer model was developed using actual wind time series and turbine performance data to simulate the power produced by the Sandia 17-m VAWT operating in automatic control. The model was used to investigate the influence of starting algorithms on annual energy production. The results indicate that, depending on turbine and local wind characteristics, a bad choice of a control algorithm can significantly reduce overall energy production. The model can be used to select control algorithms and threshold parameters that maximize long term energy production. The results from local site and turbine characteristics were generalized to obtain general guidelines for control algorithm design.
Alignment of cryo-EM movies of individual particles by optimization of image translations.
Rubinstein, John L; Brubaker, Marcus A
2015-11-01
Direct detector device (DDD) cameras have revolutionized single particle electron cryomicroscopy (cryo-EM). In addition to an improved camera detective quantum efficiency, acquisition of DDD movies allows for correction of movement of the specimen, due to both instabilities in the microscope specimen stage and electron beam-induced movement. Unlike specimen stage drift, beam-induced movement is not always homogeneous within an image. Local correlation in the trajectories of nearby particles suggests that beam-induced motion is due to deformation of the ice layer. Algorithms have already been described that can correct movement for large regions of frames and for >1 MDa protein particles. Another algorithm allows individual images to be aligned without frame averaging or linear trajectories. The algorithm maximizes the overall correlation of the shifted frames with the sum of the shifted frames. The optimum in this single objective function is found efficiently by making use of analytically calculated derivatives of the function. To smooth estimates of particle trajectories, rapid changes in particle positions between frames are penalized in the objective function and weighted averaging of nearby trajectories ensures local correlation in trajectories. This individual particle motion correction, in combination with weighting of Fourier components to account for increasing radiation damage in later frames, can be used to improve 3-D maps from single particle cryo-EM. Copyright © 2015 Elsevier Inc. All rights reserved.
Vacua of maximal gauged D=3 supergravities
International Nuclear Information System (INIS)
Fischbacher, T; Nicolai, H; Samtleben, H
2002-01-01
We analyse the scalar potentials of maximal gauged three-dimensional supergravities which reveal a surprisingly rich structure. In contrast to maximal supergravities in dimensions D≥4, all these theories possess a maximally supersymmetric (N=16) ground state with negative cosmological constant Λ 2 gauged theory, whose maximally supersymmetric groundstate has Λ = 0. We compute the mass spectra of bosonic and fermionic fluctuations around these vacua and identify the unitary irreducible representations of the relevant background (super)isometry groups to which they belong. In addition, we find several stationary points which are not maximally supersymmetric, and determine their complete mass spectra as well. In particular, we show that there are analogues of all stationary points found in higher dimensions, among them are de Sitter (dS) vacua in the theories with noncompact gauge groups SO(5, 3) 2 and SO(4, 4) 2 , as well as anti-de Sitter (AdS) vacua in the compact gauged theory preserving 1/4 and 1/8 of the supersymmetries. All the dS vacua have tachyonic instabilities, whereas there do exist nonsupersymmetric AdS vacua which are stable, again in contrast to the D≥4 theories
International Nuclear Information System (INIS)
Aman, M.M.; Jasmon, G.B.; Bakar, A.H.A.; Mokhlis, H.
2013-01-01
Highlights: • A new algorithm is proposed for optimum DG placement and sizing.• I 2 R losses minimization and voltage stability maximization is considered in fitness function.• Bus voltage stability and line stability is considered in voltage stability maximization.• Multi-objective PSO is used to solve the problem.• Proposed method is compared with analytical and grid search algorithm. - Abstract: Distributed Generation (DG) placement on the basis of minimization of losses and maximization of system voltage stability are two different approaches, discussed in research. In the new proposed algorithm, a multi-objective approach is used to combine the both approaches together. Minimization of power losses and maximization of voltage stability due to finding weakest voltage bus as well as due to weakest link in the system are considered in the fitness function. Particle Swarm Optimization (PSO) algorithm is used in this paper to solve the multi-objective problem. This paper will also compare the propose method with existing DG placement methods. From results, the proposed method is found more advantageous than the previous work in terms of voltage profile improvement, maximization of system loadability, reduction in power system losses and maximization of bus and line voltage stability. The results are validated on 12-bus, 30-bus, 33-bus and 69-bus radial distribution networks and also discussed in detailed
A very fast implementation of 2D iterative reconstruction algorithms
DEFF Research Database (Denmark)
Toft, Peter Aundal; Jensen, Peter James
1996-01-01
that iterative reconstruction algorithms can be implemented and run almost as fast as direct reconstruction algorithms. The method has been implemented in a software package that is available for free, providing reconstruction algorithms using ART, EM, and the Least Squares Conjugate Gradient Method...
A comparison of algorithms for inference and learning in probabilistic graphical models.
Frey, Brendan J; Jojic, Nebojsa
2005-09-01
Research into methods for reasoning under uncertainty is currently one of the most exciting areas of artificial intelligence, largely because it has recently become possible to record, store, and process large amounts of data. While impressive achievements have been made in pattern classification problems such as handwritten character recognition, face detection, speaker identification, and prediction of gene function, it is even more exciting that researchers are on the verge of introducing systems that can perform large-scale combinatorial analyses of data, decomposing the data into interacting components. For example, computational methods for automatic scene analysis are now emerging in the computer vision community. These methods decompose an input image into its constituent objects, lighting conditions, motion patterns, etc. Two of the main challenges are finding effective representations and models in specific applications and finding efficient algorithms for inference and learning in these models. In this paper, we advocate the use of graph-based probability models and their associated inference and learning algorithms. We review exact techniques and various approximate, computationally efficient techniques, including iterated conditional modes, the expectation maximization (EM) algorithm, Gibbs sampling, the mean field method, variational techniques, structured variational techniques and the sum-product algorithm ("loopy" belief propagation). We describe how each technique can be applied in a vision model of multiple, occluding objects and contrast the behaviors and performances of the techniques using a unifying cost function, free energy.
An information maximization model of eye movements
Renninger, Laura Walker; Coughlan, James; Verghese, Preeti; Malik, Jitendra
2005-01-01
We propose a sequential information maximization model as a general strategy for programming eye movements. The model reconstructs high-resolution visual information from a sequence of fixations, taking into account the fall-off in resolution from the fovea to the periphery. From this framework we get a simple rule for predicting fixation sequences: after each fixation, fixate next at the location that minimizes uncertainty (maximizes information) about the stimulus. By comparing our model performance to human eye movement data and to predictions from a saliency and random model, we demonstrate that our model is best at predicting fixation locations. Modeling additional biological constraints will improve the prediction of fixation sequences. Our results suggest that information maximization is a useful principle for programming eye movements.
Utility Maximization in Nonconvex Wireless Systems
Brehmer, Johannes
2012-01-01
This monograph formulates a framework for modeling and solving utility maximization problems in nonconvex wireless systems. First, a model for utility optimization in wireless systems is defined. The model is general enough to encompass a wide array of system configurations and performance objectives. Based on the general model, a set of methods for solving utility maximization problems is developed. The development is based on a careful examination of the properties that are required for the application of each method. The focus is on problems whose initial formulation does not allow for a solution by standard convex methods. Solution approaches that take into account the nonconvexities inherent to wireless systems are discussed in detail. The monograph concludes with two case studies that demonstrate the application of the proposed framework to utility maximization in multi-antenna broadcast channels.
Maximizing band gaps in plate structures
DEFF Research Database (Denmark)
Halkjær, Søren; Sigmund, Ole; Jensen, Jakob Søndergaard
2006-01-01
periodic plate using Bloch theory, which conveniently reduces the maximization problem to that of a single base cell. Secondly, we construct a finite periodic plate using a number of the optimized base cells in a postprocessed version. The dynamic properties of the finite plate are investigated......Band gaps, i.e., frequency ranges in which waves cannot propagate, can be found in elastic structures for which there is a certain periodic modulation of the material properties or structure. In this paper, we maximize the band gap size for bending waves in a Mindlin plate. We analyze an infinite...... theoretically and experimentally and the issue of finite size effects is addressed....
Singularity Structure of Maximally Supersymmetric Scattering Amplitudes
DEFF Research Database (Denmark)
Arkani-Hamed, Nima; Bourjaily, Jacob L.; Cachazo, Freddy
2014-01-01
We present evidence that loop amplitudes in maximally supersymmetric (N=4) Yang-Mills theory (SYM) beyond the planar limit share some of the remarkable structures of the planar theory. In particular, we show that through two loops, the four-particle amplitude in full N=4 SYM has only logarithmic ...... singularities and is free of any poles at infinity—properties closely related to uniform transcendentality and the UV finiteness of the theory. We also briefly comment on implications for maximal (N=8) supergravity theory (SUGRA)....
Learning curves for mutual information maximization
International Nuclear Information System (INIS)
Urbanczik, R.
2003-01-01
An unsupervised learning procedure based on maximizing the mutual information between the outputs of two networks receiving different but statistically dependent inputs is analyzed [S. Becker and G. Hinton, Nature (London) 355, 161 (1992)]. For a generic data model, I show that in the large sample limit the structure in the data is recognized by mutual information maximization. For a more restricted model, where the networks are similar to perceptrons, I calculate the learning curves for zero-temperature Gibbs learning. These show that convergence can be rather slow, and a way of regularizing the procedure is considered
Finding Maximal Pairs with Bounded Gap
DEFF Research Database (Denmark)
Brodal, Gerth Stølting; Lyngsø, Rune B.; Pedersen, Christian N. S.
1999-01-01
. In this paper we present methods for finding all maximal pairs under various constraints on the gap. In a string of length n we can find all maximal pairs with gap in an upper and lower bounded interval in time O(n log n+z) where z is the number of reported pairs. If the upper bound is removed the time reduces...... to O(n+z). Since a tandem repeat is a pair where the gap is zero, our methods can be seen as a generalization of finding tandem repeats. The running time of our methods equals the running time of well known methods for finding tandem repeats....
Directory of Open Access Journals (Sweden)
Kujawińska Agnieszka
2016-06-01
Full Text Available The article presents a study of applying the proposed method of cluster analysis to support purchasing decisions in the welding industry. The authors analyze the usefulness of the non-hierarchical method, Expectation Maximization (EM, in the selection of material (212 combinations of flux and wire melt for the SAW (Submerged Arc Welding method process. The proposed approach to cluster analysis is proved as useful in supporting purchase decisions.
Techniques to maximize software reliability in radiation fields
International Nuclear Information System (INIS)
Eichhorn, G.; Piercey, R.B.
1986-01-01
Microprocessor system failures due to memory corruption by single event upsets (SEUs) and/or latch-up in RAM or ROM memory are common in environments where there is high radiation flux. Traditional methods to harden microcomputer systems against SEUs and memory latch-up have usually involved expensive large scale hardware redundancy. Such systems offer higher reliability, but they tend to be more complex and non-standard. At the Space Astronomy Laboratory the authors have developed general programming techniques for producing software which is resistant to such memory failures. These techniques, which may be applied to standard off-the-shelf hardware, as well as custom designs, include an implementation of Maximally Redundant Software (MRS) model, error detection algorithms and memory verification and management
Maximal network reliability for a stochastic power transmission network
International Nuclear Information System (INIS)
Lin, Yi-Kuei; Yeh, Cheng-Ta
2011-01-01
Many studies regarded a power transmission network as a binary-state network and constructed it with several arcs and vertices to evaluate network reliability. In practice, the power transmission network should be stochastic because each arc (transmission line) combined with several physical lines is multistate. Network reliability is the probability that the network can transmit d units of electric power from a power plant (source) to a high voltage substation at a specific area (sink). This study focuses on searching for the optimal transmission line assignment to the power transmission network such that network reliability is maximized. A genetic algorithm based method integrating the minimal paths and the Recursive Sum of Disjoint Products is developed to solve this assignment problem. A real power transmission network is adopted to demonstrate the computational efficiency of the proposed method while comparing with the random solution generation approach.
Designing lattice structures with maximal nearest-neighbor entanglement
Energy Technology Data Exchange (ETDEWEB)
Navarro-Munoz, J C; Lopez-Sandoval, R [Instituto Potosino de Investigacion CientIfica y Tecnologica, Camino a la presa San Jose 2055, 78216 San Luis Potosi (Mexico); Garcia, M E [Theoretische Physik, FB 18, Universitaet Kassel and Center for Interdisciplinary Nanostructure Science and Technology (CINSaT), Heinrich-Plett-Str.40, 34132 Kassel (Germany)
2009-08-07
In this paper, we study the numerical optimization of nearest-neighbor concurrence of bipartite one- and two-dimensional lattices, as well as non-bipartite two-dimensional lattices. These systems are described in the framework of a tight-binding Hamiltonian while the optimization of concurrence was performed using genetic algorithms. Our results show that the concurrence of the optimized lattice structures is considerably higher than that of non-optimized systems. In the case of one-dimensional chains, the concurrence increases dramatically when the system begins to dimerize, i.e., it undergoes a structural phase transition (Peierls distortion). This result is consistent with the idea that entanglement is maximal or shows a singularity near quantum phase transitions. Moreover, the optimization of concurrence in two-dimensional bipartite and non-bipartite lattices is achieved when the structures break into smaller subsystems, which are arranged in geometrically distinguishable configurations.
On Maximal Hard-Core Thinnings of Stationary Particle Processes
Hirsch, Christian; Last, Günter
2018-02-01
The present paper studies existence and distributional uniqueness of subclasses of stationary hard-core particle systems arising as thinnings of stationary particle processes. These subclasses are defined by natural maximality criteria. We investigate two specific criteria, one related to the intensity of the hard-core particle process, the other one being a local optimality criterion on the level of realizations. In fact, the criteria are equivalent under suitable moment conditions. We show that stationary hard-core thinnings satisfying such criteria exist and are frequently distributionally unique. More precisely, distributional uniqueness holds in subcritical and barely supercritical regimes of continuum percolation. Additionally, based on the analysis of a specific example, we argue that fluctuations in grain sizes can play an important role for establishing distributional uniqueness at high intensities. Finally, we provide a family of algorithmically constructible approximations whose volume fractions are arbitrarily close to the maximum.
Pareto optimization of an industrial ecosystem: sustainability maximization
Directory of Open Access Journals (Sweden)
J. G. M.-S. Monteiro
2010-09-01
Full Text Available This work investigates a procedure to design an Industrial Ecosystem for sequestrating CO2 and consuming glycerol in a Chemical Complex with 15 integrated processes. The Complex is responsible for the production of methanol, ethylene oxide, ammonia, urea, dimethyl carbonate, ethylene glycol, glycerol carbonate, β-carotene, 1,2-propanediol and olefins, and is simulated using UNISIM Design (Honeywell. The process environmental impact (EI is calculated using the Waste Reduction Algorithm, while Profit (P is estimated using classic cost correlations. MATLAB (The Mathworks Inc is connected to UNISIM to enable optimization. The objective is granting maximum process sustainability, which involves finding a compromise between high profitability and low environmental impact. Sustainability maximization is therefore understood as a multi-criteria optimization problem, addressed by means of the Pareto optimization methodology for trading off P vs. EI.
Dopaminergic balance between reward maximization and policy complexity
Directory of Open Access Journals (Sweden)
Naama eParush
2011-05-01
Full Text Available Previous reinforcement-learning models of the basal ganglia network have highlighted the role of dopamine in encoding the mismatch between prediction and reality. Far less attention has been paid to the computational goals and algorithms of the main-axis (actor. Here, we construct a top-down model of the basal ganglia with emphasis on the role of dopamine as both a reinforcement learning signal and as a pseudo-temperature signal controlling the general level of basal ganglia excitability and motor vigilance of the acting agent. We argue that the basal ganglia endow the thalamic-cortical networks with the optimal dynamic tradeoff between two constraints: minimizing the policy complexity (cost and maximizing the expected future reward (gain. We show that this multi-dimensional optimization processes results in an experience-modulated version of the softmax behavioral policy. Thus, as in classical softmax behavioral policies, probability of actions are selected according to their estimated values and the pseudo-temperature, but in addition also vary according to the frequency of previous choices of these actions. We conclude that the computational goal of the basal ganglia is not to maximize cumulative (positive and negative reward. Rather, the basal ganglia aim at optimization of independent gain and cost functions. Unlike previously suggested single-variable maximization processes, this multi-dimensional optimization process leads naturally to a softmax-like behavioral policy. We suggest that beyond its role in the modulation of the efficacy of the cortico-striatal synapses, dopamine directly affects striatal excitability and thus provides a pseudo-temperature signal that modulates the trade-off between gain and cost. The resulting experience and dopamine modulated softmax policy can then serve as a theoretical framework to account for the broad range of behaviors and clinical states governed by the basal ganglia and dopamine systems.
A new simple iterative reconstruction algorithm for SPECT transmission measurement
International Nuclear Information System (INIS)
Hwang, D.S.; Zeng, G.L.
2005-01-01
This paper proposes a new iterative reconstruction algorithm for transmission tomography and compares this algorithm with several other methods. The new algorithm is simple and resembles the emission ML-EM algorithm in form. Due to its simplicity, it is easy to implement and fast to compute a new update at each iteration. The algorithm also always guarantees non-negative solutions. Evaluations are performed using simulation studies and real phantom data. Comparisons with other algorithms such as convex, gradient, and logMLEM show that the proposed algorithm is as good as others and performs better in some cases
International Nuclear Information System (INIS)
Creutz, M.
1987-11-01
A large variety of Monte Carlo algorithms are being used for lattice gauge simulations. For purely bosonic theories, present approaches are generally adequate; nevertheless, overrelaxation techniques promise savings by a factor of about three in computer time. For fermionic fields the situation is more difficult and less clear. Algorithms which involve an extrapolation to a vanishing step size are all quite closely related. Methods which do not require such an approximation tend to require computer time which grows as the square of the volume of the system. Recent developments combining global accept/reject stages with Langevin or microcanonical updatings promise to reduce this growth to V/sup 4/3/
Hu, T C
2002-01-01
Newly enlarged, updated second edition of a valuable text presents algorithms for shortest paths, maximum flows, dynamic programming and backtracking. Also discusses binary trees, heuristic and near optimums, matrix multiplication, and NP-complete problems. 153 black-and-white illus. 23 tables.Newly enlarged, updated second edition of a valuable, widely used text presents algorithms for shortest paths, maximum flows, dynamic programming and backtracking. Also discussed are binary trees, heuristic and near optimums, matrix multiplication, and NP-complete problems. New to this edition: Chapter 9
Simulated annealing algorithm for optimal capital growth
Luo, Yong; Zhu, Bo; Tang, Yong
2014-08-01
We investigate the problem of dynamic optimal capital growth of a portfolio. A general framework that one strives to maximize the expected logarithm utility of long term growth rate was developed. Exact optimization algorithms run into difficulties in this framework and this motivates the investigation of applying simulated annealing optimized algorithm to optimize the capital growth of a given portfolio. Empirical results with real financial data indicate that the approach is inspiring for capital growth portfolio.
Evaluation of 3D reconstruction algorithms for a small animal PET camera
International Nuclear Information System (INIS)
Johnson, C.A.; Gandler, W.R.; Seidel, J.
1996-01-01
The use of paired, opposing position-sensitive phototube scintillation cameras (SCs) operating in coincidence for small animal imaging with positron emitters is currently under study. Because of the low sensitivity of the system even in 3D mode and the need to produce images with high resolution, it was postulated that a 3D expectation maximization (EM) reconstruction algorithm might be well suited for this application. We investigated four reconstruction algorithms for the 3D SC PET camera: 2D filtered back-projection (FBP), 2D ordered subset EM (OSEM), 3D reprojection (3DRP), and 3D OSEM. Noise was assessed for all slices by the coefficient of variation in a simulated uniform cylinder. Resolution was assessed from a simulation of 15 point sources in the warm background of the uniform cylinder. At comparable noise levels, the resolution achieved with OSEM (0.9-mm to 1.2-mm) is significantly better than that obtained with FBP or 3DRP (1.5-mm to 2.0-mm.) Images of a rat skull labeled with 18 F-fluoride suggest that 3D OSEM can improve image quality of a small animal PET camera
Maximizing the Range of a Projectile.
Brown, Ronald A.
1992-01-01
Discusses solutions to the problem of maximizing the range of a projectile. Presents three references that solve the problem with and without the use of calculus. Offers a fourth solution suitable for introductory physics courses that relies more on trigonometry and the geometry of the problem. (MDH)
Robust Utility Maximization Under Convex Portfolio Constraints
International Nuclear Information System (INIS)
Matoussi, Anis; Mezghani, Hanen; Mnif, Mohamed
2015-01-01
We study a robust maximization problem from terminal wealth and consumption under a convex constraints on the portfolio. We state the existence and the uniqueness of the consumption–investment strategy by studying the associated quadratic backward stochastic differential equation. We characterize the optimal control by using the duality method and deriving a dynamic maximum principle
Ehrenfest's Lottery--Time and Entropy Maximization
Ashbaugh, Henry S.
2010-01-01
Successful teaching of the Second Law of Thermodynamics suffers from limited simple examples linking equilibrium to entropy maximization. I describe a thought experiment connecting entropy to a lottery that mixes marbles amongst a collection of urns. This mixing obeys diffusion-like dynamics. Equilibrium is achieved when the marble distribution is…
Reserve design to maximize species persistence
Robert G. Haight; Laurel E. Travis
2008-01-01
We develop a reserve design strategy to maximize the probability of species persistence predicted by a stochastic, individual-based, metapopulation model. Because the population model does not fit exact optimization procedures, our strategy involves deriving promising solutions from theory, obtaining promising solutions from a simulation optimization heuristic, and...
Maximal indecomposable past sets and event horizons
International Nuclear Information System (INIS)
Krolak, A.
1984-01-01
The existence of maximal indecomposable past sets MIPs is demonstrated using the Kuratowski-Zorn lemma. A criterion for the existence of an absolute event horizon in space-time is given in terms of MIPs and a relation to black hole event horizon is shown. (author)
Maximization of eigenvalues using topology optimization
DEFF Research Database (Denmark)
Pedersen, Niels Leergaard
2000-01-01
to localized modes in low density areas. The topology optimization problem is formulated using the SIMP method. Special attention is paid to a numerical method for removing localized eigenmodes in low density areas. The method is applied to numerical examples of maximizing the first eigenfrequency, One example...
Maximizing Resource Utilization in Video Streaming Systems
Alsmirat, Mohammad Abdullah
2013-01-01
Video streaming has recently grown dramatically in popularity over the Internet, Cable TV, and wire-less networks. Because of the resource demanding nature of video streaming applications, maximizing resource utilization in any video streaming system is a key factor to increase the scalability and decrease the cost of the system. Resources to…
A THEORY OF MAXIMIZING SENSORY INFORMATION
Hateren, J.H. van
1992-01-01
A theory is developed on the assumption that early sensory processing aims at maximizing the information rate in the channels connecting the sensory system to more central parts of the brain, where it is assumed that these channels are noisy and have a limited dynamic range. Given a stimulus power
Maximizing scientific knowledge from randomized clinical trials
DEFF Research Database (Denmark)
Gustafsson, Finn; Atar, Dan; Pitt, Bertram
2010-01-01
Trialists have an ethical and financial responsibility to plan and conduct clinical trials in a manner that will maximize the scientific knowledge gained from the trial. However, the amount of scientific information generated by randomized clinical trials in cardiovascular medicine is highly vari...
A Model of College Tuition Maximization
Bosshardt, Donald I.; Lichtenstein, Larry; Zaporowski, Mark P.
2009-01-01
This paper develops a series of models for optimal tuition pricing for private colleges and universities. The university is assumed to be a profit maximizing, price discriminating monopolist. The enrollment decision of student's is stochastic in nature. The university offers an effective tuition rate, comprised of stipulated tuition less financial…
Logit Analysis for Profit Maximizing Loan Classification
Watt, David L.; Mortensen, Timothy L.; Leistritz, F. Larry
1988-01-01
Lending criteria and loan classification methods are developed. Rating system breaking points are analyzed to present a method to maximize loan revenues. Financial characteristics of farmers are used as determinants of delinquency in a multivariate logistic model. Results indicate that debt-to-asset and operating ration are most indicative of default.
Developing maximal neuromuscular power: Part 1--biological basis of maximal power production.
Cormie, Prue; McGuigan, Michael R; Newton, Robert U
2011-01-01
This series of reviews focuses on the most important neuromuscular function in many sport performances, the ability to generate maximal muscular power. Part 1 focuses on the factors that affect maximal power production, while part 2, which will follow in a forthcoming edition of Sports Medicine, explores the practical application of these findings by reviewing the scientific literature relevant to the development of training programmes that most effectively enhance maximal power production. The ability of the neuromuscular system to generate maximal power is affected by a range of interrelated factors. Maximal muscular power is defined and limited by the force-velocity relationship and affected by the length-tension relationship. The ability to generate maximal power is influenced by the type of muscle action involved and, in particular, the time available to develop force, storage and utilization of elastic energy, interactions of contractile and elastic elements, potentiation of contractile and elastic filaments as well as stretch reflexes. Furthermore, maximal power production is influenced by morphological factors including fibre type contribution to whole muscle area, muscle architectural features and tendon properties as well as neural factors including motor unit recruitment, firing frequency, synchronization and inter-muscular coordination. In addition, acute changes in the muscle environment (i.e. alterations resulting from fatigue, changes in hormone milieu and muscle temperature) impact the ability to generate maximal power. Resistance training has been shown to impact each of these neuromuscular factors in quite specific ways. Therefore, an understanding of the biological basis of maximal power production is essential for developing training programmes that effectively enhance maximal power production in the human.
Understanding Violations of Gricean Maxims in Preschoolers and Adults
Directory of Open Access Journals (Sweden)
Mako eOkanda
2015-07-01
Full Text Available This study used a revised Conversational Violations Test to examine Gricean maxim violations in 4- to 6-year-old Japanese children and adults. Participants’ understanding of the following maxims was assessed: be informative (first maxim of quantity, avoid redundancy (second maxim of quantity, be truthful (maxim of quality, be relevant (maxim of relation, avoid ambiguity (second maxim of manner, and be polite (maxim of politeness. Sensitivity to violations of Gricean maxims increased with age: 4-year-olds’ understanding of maxims was near chance, 5-year-olds understood some maxims (first maxim of quantity and maxims of quality, relation, and manner, and 6-year-olds and adults understood all maxims. Preschoolers acquired the maxim of relation first and had the greatest difficulty understanding the second maxim of quantity. Children and adults differed in their comprehension of the maxim of politeness. The development of the pragmatic understanding of Gricean maxims and implications for the construction of developmental tasks from early childhood to adulthood are discussed.
Land-cover classification with an expert classification algorithm using digital aerial photographs
Directory of Open Access Journals (Sweden)
José L. de la Cruz
2010-05-01
Full Text Available The purpose of this study was to evaluate the usefulness of the spectral information of digital aerial sensors in determining land-cover classification using new digital techniques. The land covers that have been evaluated are the following, (1 bare soil, (2 cereals, including maize (<em>Zea maysem> L., oats (<em>Avena sativaem> L., rye (<em>Secale cereale em>L., wheat (<em>Triticum aestivum em>L. and barley (<em>Hordeun vulgareem> L., (3 high protein crops, such as peas (<em>Pisum sativumem> L. and beans (<em>Vicia fabaem> L., (4 alfalfa (<em>Medicago sativaem> L., (5 woodlands and scrublands, including holly oak (<em>Quercus ilexem> L. and common retama (<em>Retama sphaerocarpaem> L., (6 urban soil, (7 olive groves (<em>Olea europaeaem> L. and (8 burnt crop stubble. The best result was obtained using an expert classification algorithm, achieving a reliability rate of 95%. This result showed that the images of digital airborne sensors hold considerable promise for the future in the field of digital classifications because these images contain valuable information that takes advantage of the geometric viewpoint. Moreover, new classification techniques reduce problems encountered using high-resolution images; while reliabilities are achieved that are better than those achieved with traditional methods.
Robust EM Continual Reassessment Method in Oncology Dose Finding
Yuan, Ying; Yin, Guosheng
2012-01-01
The continual reassessment method (CRM) is a commonly used dose-finding design for phase I clinical trials. Practical applications of this method have been restricted by two limitations: (1) the requirement that the toxicity outcome needs to be observed shortly after the initiation of the treatment; and (2) the potential sensitivity to the prespecified toxicity probability at each dose. To overcome these limitations, we naturally treat the unobserved toxicity outcomes as missing data, and use the expectation-maximization (EM) algorithm to estimate the dose toxicity probabilities based on the incomplete data to direct dose assignment. To enhance the robustness of the design, we propose prespecifying multiple sets of toxicity probabilities, each set corresponding to an individual CRM model. We carry out these multiple CRMs in parallel, across which model selection and model averaging procedures are used to make more robust inference. We evaluate the operating characteristics of the proposed robust EM-CRM designs through simulation studies and show that the proposed methods satisfactorily resolve both limitations of the CRM. Besides improving the MTD selection percentage, the new designs dramatically shorten the duration of the trial, and are robust to the prespecification of the toxicity probabilities. PMID:22375092
Power maximization of a point absorber wave energy converter using improved model predictive control
Milani, Farideh; Moghaddam, Reihaneh Kardehi
2017-08-01
This paper considers controlling and maximizing the absorbed power of wave energy converters for irregular waves. With respect to physical constraints of the system, a model predictive control is applied. Irregular waves' behavior is predicted by Kalman filter method. Owing to the great influence of controller parameters on the absorbed power, these parameters are optimized by imperialist competitive algorithm. The results illustrate the method's efficiency in maximizing the extracted power in the presence of unknown excitation force which should be predicted by Kalman filter.
Directory of Open Access Journals (Sweden)
Anna Bourmistrova
2011-02-01
Full Text Available The autodriver algorithm is an intelligent method to eliminate the need of steering by a driver on a well-defined road. The proposed method performs best on a four-wheel steering (4WS vehicle, though it is also applicable to two-wheel-steering (TWS vehicles. The algorithm is based on coinciding the actual vehicle center of rotation and road center of curvature, by adjusting the kinematic center of rotation. The road center of curvature is assumed prior information for a given road, while the dynamic center of rotation is the output of dynamic equations of motion of the vehicle using steering angle and velocity measurements as inputs. We use kinematic condition of steering to set the steering angles in such a way that the kinematic center of rotation of the vehicle sits at a desired point. At low speeds the ideal and actual paths of the vehicle are very close. With increase of forward speed the road and tire characteristics, along with the motion dynamics of the vehicle cause the vehicle to turn about time-varying points. By adjusting the steering angles, our algorithm controls the dynamic turning center of the vehicle so that it coincides with the road curvature center, hence keeping the vehicle on a given road autonomously. The position and orientation errors are used as feedback signals in a closed loop control to adjust the steering angles. The application of the presented autodriver algorithm demonstrates reliable performance under different driving conditions.
Determination of Pavement Rehabilitation Activities through a Permutation Algorithm
Directory of Open Access Journals (Sweden)
Sangyum Lee
2013-01-01
Full Text Available This paper presents a mathematical programming model for optimal pavement rehabilitation planning. The model maximized the rehabilitation area through a newly developed permutation algorithm, based on the procedures outlined in the harmony search (HS algorithm. Additionally, the proposed algorithm was based on an optimal solution method for the problem of multilocation rehabilitation activities on pavement structure, using empirical deterioration and rehabilitation effectiveness models, according to a limited maintenance budget. Thus, nonlinear pavement performance and rehabilitation activity decision models were used to maximize the objective functions of the rehabilitation area within a limited budget, through the permutation algorithm. Our results showed that the heuristic permutation algorithm provided a good optimum in terms of maximizing the rehabilitation area, compared with a method of the worst-first maintenance currently used in Seoul.
Algorithmic test design using classical item parameters
van der Linden, Willem J.; Adema, Jos J.
Two optimalization models for the construction of tests with a maximal value of coefficient alpha are given. Both models have a linear form and can be solved by using a branch-and-bound algorithm. The first model assumes an item bank calibrated under the Rasch model and can be used, for instance,
Refined reservoir description to maximize oil recovery
International Nuclear Information System (INIS)
Flewitt, W.E.
1975-01-01
To assure maximized oil recovery from older pools, reservoir description has been advanced by fully integrating original open-hole logs and the recently introduced interpretive techniques made available through cased-hole wireline saturation logs. A refined reservoir description utilizing normalized original wireline porosity logs has been completed in the Judy Creek Beaverhill Lake ''A'' Pool, a reefal carbonate pool with current potential productivity of 100,000 BOPD and 188 active wells. Continuous porosity was documented within a reef rim and cap while discontinuous porous lenses characterized an interior lagoon. With the use of pulsed neutron logs and production data a separate water front and pressure response was recognized within discrete environmental units. The refined reservoir description aided in reservoir simulation model studies and quantifying pool performance. A pattern water flood has now replaced the original peripheral bottom water drive to maximize oil recovery
Maximal frustration as an immunological principle.
de Abreu, F Vistulo; Mostardinha, P
2009-03-06
A fundamental problem in immunology is that of understanding how the immune system selects promptly which cells to kill without harming the body. This problem poses an apparent paradox. Strong reactivity against pathogens seems incompatible with perfect tolerance towards self. We propose a different view on cellular reactivity to overcome this paradox: effector functions should be seen as the outcome of cellular decisions which can be in conflict with other cells' decisions. We argue that if cellular systems are frustrated, then extensive cross-reactivity among the elements in the system can decrease the reactivity of the system as a whole and induce perfect tolerance. Using numerical and mathematical analyses, we discuss two simple models that perform optimal pathogenic detection with no autoimmunity if cells are maximally frustrated. This study strongly suggests that a principle of maximal frustration could be used to build artificial immune systems. It would be interesting to test this principle in the real adaptive immune system.
DEFF Research Database (Denmark)
Markham, Annette
This paper takes an actor network theory approach to explore some of the ways that algorithms co-construct identity and relational meaning in contemporary use of social media. Based on intensive interviews with participants as well as activity logging and data tracking, the author presents a richly...... layered set of accounts to help build our understanding of how individuals relate to their devices, search systems, and social network sites. This work extends critical analyses of the power of algorithms in implicating the social self by offering narrative accounts from multiple perspectives. It also...... contributes an innovative method for blending actor network theory with symbolic interaction to grapple with the complexity of everyday sensemaking practices within networked global information flows....
Derivative pricing based on local utility maximization
Jan Kallsen
2002-01-01
This paper discusses a new approach to contingent claim valuation in general incomplete market models. We determine the neutral derivative price which occurs if investors maximize their local utility and if derivative demand and supply are balanced. We also introduce the sensitivity process of a contingent claim. This process quantifies the reliability of the neutral derivative price and it can be used to construct price bounds. Moreover, it allows to calibrate market models in order to be co...
Control of Shareholders’ Wealth Maximization in Nigeria
A. O. Oladipupo; C. O. Okafor
2014-01-01
This research focuses on who controls shareholder’s wealth maximization and how does this affect firm’s performance in publicly quoted non-financial companies in Nigeria. The shareholder fund was the dependent while explanatory variables were firm size (proxied by log of turnover), retained earning (representing management control) and dividend payment (representing measure of shareholders control). The data used for this study were obtained from the Nigerian Stock Exchange [NSE] fact book an...
Definable maximal discrete sets in forcing extensions
DEFF Research Database (Denmark)
Törnquist, Asger Dag; Schrittesser, David
2018-01-01
Let be a Σ11 binary relation, and recall that a set A is -discrete if no two elements of A are related by . We show that in the Sacks and Miller forcing extensions of L there is a Δ12 maximal -discrete set. We use this to answer in the negative the main question posed in [5] by showing...
Dynamic Convex Duality in Constrained Utility Maximization
Li, Yusong; Zheng, Harry
2016-01-01
In this paper, we study a constrained utility maximization problem following the convex duality approach. After formulating the primal and dual problems, we construct the necessary and sufficient conditions for both the primal and dual problems in terms of FBSDEs plus additional conditions. Such formulation then allows us to explicitly characterize the primal optimal control as a function of the adjoint process coming from the dual FBSDEs in a dynamic fashion and vice versa. Moreover, we also...
Rabideau, Gregg R.; Chien, Steve A.
2010-01-01
AVA v2 software selects goals for execution from a set of goals that oversubscribe shared resources. The term goal refers to a science or engineering request to execute a possibly complex command sequence, such as image targets or ground-station downlinks. Developed as an extension to the Virtual Machine Language (VML) execution system, the software enables onboard and remote goal triggering through the use of an embedded, dynamic goal set that can oversubscribe resources. From the set of conflicting goals, a subset must be chosen that maximizes a given quality metric, which in this case is strict priority selection. A goal can never be pre-empted by a lower priority goal, and high-level goals can be added, removed, or updated at any time, and the "best" goals will be selected for execution. The software addresses the issue of re-planning that must be performed in a short time frame by the embedded system where computational resources are constrained. In particular, the algorithm addresses problems with well-defined goal requests without temporal flexibility that oversubscribes available resources. By using a fast, incremental algorithm, goal selection can be postponed in a "just-in-time" fashion allowing requests to be changed or added at the last minute. Thereby enabling shorter response times and greater autonomy for the system under control.
Single maximal versus combination punch kinematics.
Piorkowski, Barry A; Lees, Adrian; Barton, Gabor J
2011-03-01
The aim of this study was to determine the influence of punch type (Jab, Cross, Lead Hook and Reverse Hook) and punch modality (Single maximal, 'In-synch' and 'Out of synch' combination) on punch speed and delivery time. Ten competition-standard volunteers performed punches with markers placed on their anatomical landmarks for 3D motion capture with an eight-camera optoelectronic system. Speed and duration between key moments were computed. There were significant differences in contact speed between punch types (F(2,18,84.87) = 105.76, p = 0.001) with Lead and Reverse Hooks developing greater speed than Jab and Cross. There were significant differences in contact speed between punch modalities (F(2,64,102.87) = 23.52, p = 0.001) with the Single maximal (M+/- SD: 9.26 +/- 2.09 m/s) higher than 'Out of synch' (7.49 +/- 2.32 m/s), 'In-synch' left (8.01 +/- 2.35 m/s) or right lead (7.97 +/- 2.53 m/s). Delivery times were significantly lower for Jab and Cross than Hook. Times were significantly lower 'In-synch' than a Single maximal or 'Out of synch' combination mode. It is concluded that a defender may have more evasion-time than previously reported. This research could be of use to performers and coaches when considering training preparations.
Formation Control for the MAXIM Mission
Luquette, Richard J.; Leitner, Jesse; Gendreau, Keith; Sanner, Robert M.
2004-01-01
Over the next twenty years, a wave of change is occurring in the space-based scientific remote sensing community. While the fundamental limits in the spatial and angular resolution achievable in spacecraft have been reached, based on today s technology, an expansive new technology base has appeared over the past decade in the area of Distributed Space Systems (DSS). A key subset of the DSS technology area is that which covers precision formation flying of space vehicles. Through precision formation flying, the baselines, previously defined by the largest monolithic structure which could fit in the largest launch vehicle fairing, are now virtually unlimited. Several missions including the Micro-Arcsecond X-ray Imaging Mission (MAXIM), and the Stellar Imager will drive the formation flying challenges to achieve unprecedented baselines for high resolution, extended-scene, interferometry in the ultraviolet and X-ray regimes. This paper focuses on establishing the feasibility for the formation control of the MAXIM mission. MAXIM formation flying requirements are on the order of microns, while Stellar Imager mission requirements are on the order of nanometers. This paper specifically addresses: (1) high-level science requirements for these missions and how they evolve into engineering requirements; and (2) the development of linearized equations of relative motion for a formation operating in an n-body gravitational field. Linearized equations of motion provide the ground work for linear formation control designs.
Gradient Dynamics and Entropy Production Maximization
Janečka, Adam; Pavelka, Michal
2018-01-01
We compare two methods for modeling dissipative processes, namely gradient dynamics and entropy production maximization. Both methods require similar physical inputs-how energy (or entropy) is stored and how it is dissipated. Gradient dynamics describes irreversible evolution by means of dissipation potential and entropy, it automatically satisfies Onsager reciprocal relations as well as their nonlinear generalization (Maxwell-Onsager relations), and it has statistical interpretation. Entropy production maximization is based on knowledge of free energy (or another thermodynamic potential) and entropy production. It also leads to the linear Onsager reciprocal relations and it has proven successful in thermodynamics of complex materials. Both methods are thermodynamically sound as they ensure approach to equilibrium, and we compare them and discuss their advantages and shortcomings. In particular, conditions under which the two approaches coincide and are capable of providing the same constitutive relations are identified. Besides, a commonly used but not often mentioned step in the entropy production maximization is pinpointed and the condition of incompressibility is incorporated into gradient dynamics.
Energy Technology Data Exchange (ETDEWEB)
Albino, Lucas D.; Santos, Gabriela R.; Ribeiro, Victor A.B.; Rodrigues, Laura N., E-mail: lucasdelbem1@gmail.com [Universidade de Sao Paulo (USP), Sao Paulo, SP (Brazil). Faculdade de Medicina. Instituto de Radiologia; Weltman, Eduardo; Braga, Henrique F. [Instituto do Cancer do Estado de Sao Paulo, Sao Paulo, SP (Brazil). Servico de Radioterapia
2013-12-15
The dose accuracy calculated by a treatment planning system is directly related to the chosen algorithm. Nowadays, several calculation doses algorithms are commercially available and they differ in calculation time and accuracy, especially when individual tissue densities are taken into account. The aim of this study was to compare two different calculation algorithms from iPlan®, BrainLAB, in the treatment of pituitary gland tumor with intensity-modulated radiation therapy (IMRT). These tumors are located in a region with variable electronic density tissues. The deviations from the plan with no heterogeneity correction were evaluated. To initial validation of the data inserted into the planning system, an IMRT plan was simulated in a anthropomorphic phantom and the dose distribution was measured with a radiochromic film. The gamma analysis was performed in the film, comparing it with dose distributions calculated with X-ray Voxel Monte Carlo (XVMC) algorithm and pencil beam convolution (PBC). Next, 33 patients plans, initially calculated by PBC algorithm, were recalculated with XVMC algorithm. The treatment volumes and organs-at-risk dose-volume histograms were compared. No relevant differences were found in dose-volume histograms between XVMC and PBC. However, differences were obtained when comparing each plan with the plan without heterogeneity correction. (author)
Primal Decomposition-Based Method for Weighted Sum-Rate Maximization in Downlink OFDMA Systems
Directory of Open Access Journals (Sweden)
Weeraddana Chathuranga
2010-01-01
Full Text Available We consider the weighted sum-rate maximization problem in downlink Orthogonal Frequency Division Multiple Access (OFDMA systems. Motivated by the increasing popularity of OFDMA in future wireless technologies, a low complexity suboptimal resource allocation algorithm is obtained for joint optimization of multiuser subcarrier assignment and power allocation. The algorithm is based on an approximated primal decomposition-based method, which is inspired from exact primal decomposition techniques. The original nonconvex optimization problem is divided into two subproblems which can be solved independently. Numerical results are provided to compare the performance of the proposed algorithm to Lagrange relaxation based suboptimal methods as well as to optimal exhaustive search-based method. Despite its reduced computational complexity, the proposed algorithm provides close-to-optimal performance.
Cardiorespiratory Coordination in Repeated Maximal Exercise
Directory of Open Access Journals (Sweden)
Sergi Garcia-Retortillo
2017-06-01
Full Text Available Increases in cardiorespiratory coordination (CRC after training with no differences in performance and physiological variables have recently been reported using a principal component analysis approach. However, no research has yet evaluated the short-term effects of exercise on CRC. The aim of this study was to delineate the behavior of CRC under different physiological initial conditions produced by repeated maximal exercises. Fifteen participants performed 2 consecutive graded and maximal cycling tests. Test 1 was performed without any previous exercise, and Test 2 6 min after Test 1. Both tests started at 0 W and the workload was increased by 25 W/min in males and 20 W/min in females, until they were not able to maintain the prescribed cycling frequency of 70 rpm for more than 5 consecutive seconds. A principal component (PC analysis of selected cardiovascular and cardiorespiratory variables (expired fraction of O2, expired fraction of CO2, ventilation, systolic blood pressure, diastolic blood pressure, and heart rate was performed to evaluate the CRC defined by the number of PCs in both tests. In order to quantify the degree of coordination, the information entropy was calculated and the eigenvalues of the first PC (PC1 were compared between tests. Although no significant differences were found between the tests with respect to the performed maximal workload (Wmax, maximal oxygen consumption (VO2 max, or ventilatory threshold (VT, an increase in the number of PCs and/or a decrease of eigenvalues of PC1 (t = 2.95; p = 0.01; d = 1.08 was found in Test 2 compared to Test 1. Moreover, entropy was significantly higher (Z = 2.33; p = 0.02; d = 1.43 in the last test. In conclusion, despite the fact that no significant differences were observed in the conventionally explored maximal performance and physiological variables (Wmax, VO2 max, and VT between tests, a reduction of CRC was observed in Test 2. These results emphasize the interest of CRC
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.
Generation of Referring Expressions: Assessing the Incremental Algorithm
van Deemter, Kees; Gatt, Albert; van der Sluis, Ielka; Power, Richard
2012-01-01
A substantial amount of recent work in natural language generation has focused on the generation of "one-shot" referring expressions whose only aim is to identify a target referent. Dale and Reiter's Incremental Algorithm (IA) is often thought to be the best algorithm for maximizing the similarity to referring expressions produced by people. We…
Development of an image reconstruction algorithm for a few number of projection data
International Nuclear Information System (INIS)
Vieira, Wilson S.; Brandao, Luiz E.; Braz, Delson
2007-01-01
An image reconstruction algorithm was developed for specific cases of radiotracer applications in industry (rotating cylindrical mixers), involving a very few number of projection data. The algorithm was planned for imaging radioactive isotope distributions around the center of circular planes. The method consists of adapting the original expectation maximization algorithm (EM) to solve the ill-posed emission tomography inverse problem in order to reconstruct transversal 2D images of an object with only four projections. To achieve this aim, counts of photons emitted by selected radioactive sources in the plane, after they had been simulated using the commercial software MICROSHIELD 5.05, constitutes the projections and a computational code (SPECTEM) was developed to generate activity vectors or images related to those sources. SPECTEM is flexible to support simultaneous changes of the detectors's geometry, the medium under investigation and the properties of the gamma radiation. As a consequence of the code had been followed correctly the proposed method, good results were obtained and they encouraged us to continue the next step of the research: the validation of SPECTEM utilizing experimental data to check its real performance. We aim this code will improve considerably radiotracer methodology, making easier the diagnosis of fails in industrial processes. (author)
Development of an image reconstruction algorithm for a few number of projection data
Energy Technology Data Exchange (ETDEWEB)
Vieira, Wilson S.; Brandao, Luiz E. [Instituto de Engenharia Nuclear (IEN-CNEN/RJ), Rio de Janeiro , RJ (Brazil)]. E-mails: wilson@ien.gov.br; brandao@ien.gov.br; Braz, Delson [Universidade Federal do Rio de Janeiro (UFRJ), RJ (Brazil). Coordenacao dos Programa de Pos-graduacao de Engenharia (COPPE). Lab. de Instrumentacao Nuclear]. E-mail: delson@mailhost.lin.ufrj.br
2007-07-01
An image reconstruction algorithm was developed for specific cases of radiotracer applications in industry (rotating cylindrical mixers), involving a very few number of projection data. The algorithm was planned for imaging radioactive isotope distributions around the center of circular planes. The method consists of adapting the original expectation maximization algorithm (EM) to solve the ill-posed emission tomography inverse problem in order to reconstruct transversal 2D images of an object with only four projections. To achieve this aim, counts of photons emitted by selected radioactive sources in the plane, after they had been simulated using the commercial software MICROSHIELD 5.05, constitutes the projections and a computational code (SPECTEM) was developed to generate activity vectors or images related to those sources. SPECTEM is flexible to support simultaneous changes of the detectors's geometry, the medium under investigation and the properties of the gamma radiation. As a consequence of the code had been followed correctly the proposed method, good results were obtained and they encouraged us to continue the next step of the research: the validation of SPECTEM utilizing experimental data to check its real performance. We aim this code will improve considerably radiotracer methodology, making easier the diagnosis of fails in industrial processes. (author)
A Joint Land Cover Mapping and Image Registration Algorithm Based on a Markov Random Field Model
Directory of Open Access Journals (Sweden)
Apisit Eiumnoh
2013-10-01
Full Text Available Traditionally, image registration of multi-modal and multi-temporal images is performed satisfactorily before land cover mapping. However, since multi-modal and multi-temporal images are likely to be obtained from different satellite platforms and/or acquired at different times, perfect alignment is very difficult to achieve. As a result, a proper land cover mapping algorithm must be able to correct registration errors as well as perform an accurate classification. In this paper, we propose a joint classification and registration technique based on a Markov random field (MRF model to simultaneously align two or more images and obtain a land cover map (LCM of the scene. The expectation maximization (EM algorithm is employed to solve the joint image classification and registration problem by iteratively estimating the map parameters and approximate posterior probabilities. Then, the maximum a posteriori (MAP criterion is used to produce an optimum land cover map. We conducted experiments on a set of four simulated images and one pair of remotely sensed images to investigate the effectiveness and robustness of the proposed algorithm. Our results show that, with proper selection of a critical MRF parameter, the resulting LCMs derived from an unregistered image pair can achieve an accuracy that is as high as when images are perfectly aligned. Furthermore, the registration error can be greatly reduced.
Directory of Open Access Journals (Sweden)
K KUDRNA
2004-07-01
Full Text Available On the basis of analysis of yield time series from a ten-year period, isolines of maximal yields of crops (isocarps have been constructed, homogenized yield zones have been determined, and inner structures of the agricultural system have been calculated. The algorithm of a normal and an optimal structure calculation have been used, and differences in the structure of the agricultural system have been determined for every defi ned zone.
SU(2) gauge theory in the maximally Abelian gauge without monopoles
International Nuclear Information System (INIS)
Shmakov, S.Yu.; Zadorozhnyj, A.M.
1995-01-01
We present an algorithm for simulation of SU(2) lattice gauge theory under the maximally Abelian (MA) gauge and first numerical results for the theory without Abelian monopoles. The results support the idea that nonperturbative interaction arises between monopoles and residual Abelian field and the other interactions are perturbative. It is shown that the Gribov region for the theory with the MA gauge fixed is non-connected. 12 refs., 1 tab
First results with two light flavours of quarks with maximally twisted mass
International Nuclear Information System (INIS)
Jansen, K.; Urbach, C.
2006-10-01
We report on first results of an ongoing effort to simulate lattice QCD with two degenerate flavours of quarks by means of the twisted mass formulation tuned to maximal twist. By utilising recent improvements of the HMC algorithm, pseudo-scalar masses well below 300 MeV are simulated on volumes L 3 .T with T=2L and L>2 fm and at values of the lattice spacing a f =2+1+1 flavours are discussed. (orig.)
Wang, Huiya; Feng, Jun; Wang, Hongyu
2017-07-20
Detection of clustered microcalcification (MC) from mammograms plays essential roles in computer-aided diagnosis for early stage breast cancer. To tackle problems associated with the diversity of data structures of MC lesions and the variability of normal breast tissues, multi-pattern sample space learning is required. In this paper, a novel grouped fuzzy Support Vector Machine (SVM) algorithm with sample space partition based on Expectation-Maximization (EM) (called G-FSVM) is proposed for clustered MC detection. The diversified pattern of training data is partitioned into several groups based on EM algorithm. Then a series of fuzzy SVM are integrated for classification with each group of samples from the MC lesions and normal breast tissues. From DDSM database, a total of 1,064 suspicious regions are selected from 239 mammography, and the measurement of Accuracy, True Positive Rate (TPR), False Positive Rate (FPR) and EVL = TPR* 1-FPR are 0.82, 0.78, 0.14 and 0.72, respectively. The proposed method incorporates the merits of fuzzy SVM and multi-pattern sample space learning, decomposing the MC detection problem into serial simple two-class classification. Experimental results from synthetic data and DDSM database demonstrate that our integrated classification framework reduces the false positive rate significantly while maintaining the true positive rate.
Casanova, Henri; Robert, Yves
2008-01-01
""…The authors of the present book, who have extensive credentials in both research and instruction in the area of parallelism, present a sound, principled treatment of parallel algorithms. … This book is very well written and extremely well designed from an instructional point of view. … The authors have created an instructive and fascinating text. The book will serve researchers as well as instructors who need a solid, readable text for a course on parallelism in computing. Indeed, for anyone who wants an understandable text from which to acquire a current, rigorous, and broad vi
DEFF Research Database (Denmark)
Gustavson, Fred G.; Reid, John K.; Wasniewski, Jerzy
2007-01-01
We present subroutines for the Cholesky factorization of a positive-definite symmetric matrix and for solving corresponding sets of linear equations. They exploit cache memory by using the block hybrid format proposed by the authors in a companion article. The matrix is packed into n(n + 1)/2 real...... variables, and the speed is usually better than that of the LAPACK algorithm that uses full storage (n2 variables). Included are subroutines for rearranging a matrix whose upper or lower-triangular part is packed by columns to this format and for the inverse rearrangement. Also included is a kernel...
Postactivation potentiation biases maximal isometric strength assessment.
Lima, Leonardo Coelho Rabello; Oliveira, Felipe Bruno Dias; Oliveira, Thiago Pires; Assumpção, Claudio de Oliveira; Greco, Camila Coelho; Cardozo, Adalgiso Croscato; Denadai, Benedito Sérgio
2014-01-01
Postactivation potentiation (PAP) is known to enhance force production. Maximal isometric strength assessment protocols usually consist of two or more maximal voluntary isometric contractions (MVCs). The objective of this study was to determine if PAP would influence isometric strength assessment. Healthy male volunteers (n = 23) performed two five-second MVCs separated by a 180-seconds interval. Changes in isometric peak torque (IPT), time to achieve it (tPTI), contractile impulse (CI), root mean square of the electromyographic signal during PTI (RMS), and rate of torque development (RTD), in different intervals, were measured. Significant increases in IPT (240.6 ± 55.7 N·m versus 248.9 ± 55.1 N·m), RTD (746 ± 152 N·m·s(-1) versus 727 ± 158 N·m·s(-1)), and RMS (59.1 ± 12.2% RMSMAX versus 54.8 ± 9.4% RMSMAX) were found on the second MVC. tPTI decreased significantly on the second MVC (2373 ± 1200 ms versus 2784 ± 1226 ms). We conclude that a first MVC leads to PAP that elicits significant enhancements in strength-related variables of a second MVC performed 180 seconds later. If disconsidered, this phenomenon might bias maximal isometric strength assessment, overestimating some of these variables.
Gain maximization in a probabilistic entanglement protocol
di Lorenzo, Antonio; Esteves de Queiroz, Johnny Hebert
Entanglement is a resource. We can therefore define gain as a monotonic function of entanglement G (E) . If a pair with entanglement E is produced with probability P, the net gain is N = PG (E) - (1 - P) C , where C is the cost of a failed attempt. We study a protocol where a pair of quantum systems is produced in a maximally entangled state ρm with probability Pm, while it is produced in a partially entangled state ρp with the complementary probability 1 -Pm . We mix a fraction w of the partially entangled pairs with the maximally entangled ones, i.e. we take the state to be ρ = (ρm + wUlocρpUloc+) / (1 + w) , where Uloc is an appropriate unitary local operation designed to maximize the entanglement of ρ. This procedure on one hand reduces the entanglement E, and hence the gain, but on the other hand it increases the probability of success to P =Pm + w (1 -Pm) , therefore the net gain N may increase. There may be hence, a priori, an optimal value for w, the fraction of failed attempts that we mix in. We show that, in the hypothesis of a linear gain G (E) = E , even assuming a vanishing cost C -> 0 , the net gain N is increasing with w, therefore the best strategy is to always mix the partially entangled states. Work supported by CNPq, Conselho Nacional de Desenvolvimento Científico e Tecnológico, proc. 311288/2014-6, and by FAPEMIG, Fundação de Amparo à Pesquisa de Minas Gerais, proc. IC-FAPEMIG2016-0269 and PPM-00607-16.
Maximizing percentage depletion in solid minerals
International Nuclear Information System (INIS)
Tripp, J.; Grove, H.D.; McGrath, M.
1982-01-01
This article develops a strategy for maximizing percentage depletion deductions when extracting uranium or other solid minerals. The goal is to avoid losing percentage depletion deductions by staying below the 50% limitation on taxable income from the property. The article is divided into two major sections. The first section is comprised of depletion calculations that illustrate the problem and corresponding solutions. The last section deals with the feasibility of applying the strategy and complying with the Internal Revenue Code and appropriate regulations. Three separate strategies or appropriate situations are developed and illustrated. 13 references, 3 figures, 7 tables
What currency do bumble bees maximize?
Directory of Open Access Journals (Sweden)
Nicholas L Charlton
2010-08-01
Full Text Available In modelling bumble bee foraging, net rate of energetic intake has been suggested as the appropriate currency. The foraging behaviour of honey bees is better predicted by using efficiency, the ratio of energetic gain to expenditure, as the currency. We re-analyse several studies of bumble bee foraging and show that efficiency is as good a currency as net rate in terms of predicting behaviour. We suggest that future studies of the foraging of bumble bees should be designed to distinguish between net rate and efficiency maximizing behaviour in an attempt to discover which is the more appropriate currency.
Maximizing policy learning in international committees
DEFF Research Database (Denmark)
Nedergaard, Peter
2007-01-01
, this article demonstrates that valuable lessons can be learned about policy learning, in practice and theoretically, by analysing the cooperation in the OMC committees. Using the Advocacy Coalition Framework as the starting point of analysis, 15 hypotheses on policy learning are tested. Among other things......, it is concluded that in order to maximize policy learning in international committees, empirical data should be made available to committees and provided by sources close to the participants (i.e. the Commission). In addition, the work in the committees should be made prestigious in order to attract well...
Pouliot type duality via a-maximization
International Nuclear Information System (INIS)
Kawano, Teruhiko; Ookouchi, Yutaka; Tachikawa, Yuji; Yagi, Futoshi
2006-01-01
We study four-dimensional N=1Spin(10) gauge theory with a single spinor and N Q vectors at the superconformal fixed point via the electric-magnetic duality and a-maximization. When gauge invariant chiral primary operators hit the unitarity bounds, we find that the theory with no superpotential is identical to the one with some superpotential at the infrared fixed point. The auxiliary field method in the electric theory offers a satisfying description of the infrared fixed point, which is consistent with the better picture in the magnetic theory. In particular, it gives a clear description of the emergence of new massless degrees of freedom in the electric theory
Cormie, Prue; McGuigan, Michael R; Newton, Robert U
2011-02-01
This series of reviews focuses on the most important neuromuscular function in many sport performances: the ability to generate maximal muscular power. Part 1, published in an earlier issue of Sports Medicine, focused on the factors that affect maximal power production while part 2 explores the practical application of these findings by reviewing the scientific literature relevant to the development of training programmes that most effectively enhance maximal power production. The ability to generate maximal power during complex motor skills is of paramount importance to successful athletic performance across many sports. A crucial issue faced by scientists and coaches is the development of effective and efficient training programmes that improve maximal power production in dynamic, multi-joint movements. Such training is referred to as 'power training' for the purposes of this review. Although further research is required in order to gain a deeper understanding of the optimal training techniques for maximizing power in complex, sports-specific movements and the precise mechanisms underlying adaptation, several key conclusions can be drawn from this review. First, a fundamental relationship exists between strength and power, which dictates that an individual cannot possess a high level of power without first being relatively strong. Thus, enhancing and maintaining maximal strength is essential when considering the long-term development of power. Second, consideration of movement pattern, load and velocity specificity is essential when designing power training programmes. Ballistic, plyometric and weightlifting exercises can be used effectively as primary exercises within a power training programme that enhances maximal power. The loads applied to these exercises will depend on the specific requirements of each particular sport and the type of movement being trained. The use of ballistic exercises with loads ranging from 0% to 50% of one-repetition maximum (1RM) and
Analysing Music with Point-Set Compression Algorithms
DEFF Research Database (Denmark)
Meredith, David
2016-01-01
Several point-set pattern-discovery and compression algorithms designed for analysing music are reviewed and evaluated. Each algorithm takes as input a point-set representation of a score in which each note is represented as a point in pitch-time space. Each algorithm computes the maximal...... and sections in pieces of classical music. On the first task, the best-performing algorithms achieved success rates of around 84%. In the second task, the best algorithms achieved mean F1 scores of around 0.49, with scores for individual pieces rising as high as 0.71....
Maximization techniques for oilfield development profits
International Nuclear Information System (INIS)
Lerche, I.
1999-01-01
In 1981 Nind provided a quantitative procedure for estimating the optimum number of development wells to emplace on an oilfield to maximize profit. Nind's treatment assumed that there was a steady selling price, that all wells were placed in production simultaneously, and that each well's production profile was identical and a simple exponential decline with time. This paper lifts these restrictions to allow for price fluctuations, variable with time emplacement of wells, and production rates that are more in line with actual production records than is a simple exponential decline curve. As a consequence, it is possible to design production rate strategies, correlated with price fluctuations, so as to maximize the present-day worth of a field. For price fluctuations that occur on a time-scale rapid compared to inflation rates it is appropriate to have production rates correlate directly with such price fluctuations. The same strategy does not apply for price fluctuations occurring on a time-scale long compared to inflation rates where, for small amplitudes in the price fluctuations, it is best to sell as much product as early as possible to overcome inflation factors, while for large amplitude fluctuations the best strategy is to sell product as early as possible but to do so mainly on price upswings. Examples are provided to show how these generalizations of Nind's (1981) formula change the complexion of oilfield development optimization. (author)
SU-C-207B-02: Maximal Noise Reduction Filter with Anatomical Structures Preservation
Energy Technology Data Exchange (ETDEWEB)
Maitree, R; Guzman, G; Chundury, A; Roach, M; Yang, D [Washington University School of Medicine, St Louis, MO (United States)
2016-06-15
Purpose: All medical images contain noise, which can result in an undesirable appearance and can reduce the visibility of anatomical details. There are varieties of techniques utilized to reduce noise such as increasing the image acquisition time and using post-processing noise reduction algorithms. However, these techniques are increasing the imaging time and cost or reducing tissue contrast and effective spatial resolution which are useful diagnosis information. The three main focuses in this study are: 1) to develop a novel approach that can adaptively and maximally reduce noise while preserving valuable details of anatomical structures, 2) to evaluate the effectiveness of available noise reduction algorithms in comparison to the proposed algorithm, and 3) to demonstrate that the proposed noise reduction approach can be used clinically. Methods: To achieve a maximal noise reduction without destroying the anatomical details, the proposed approach automatically estimated the local image noise strength levels and detected the anatomical structures, i.e. tissue boundaries. Such information was used to adaptively adjust strength of the noise reduction filter. The proposed algorithm was tested on 34 repeating swine head datasets and 54 patients MRI and CT images. The performance was quantitatively evaluated by image quality metrics and manually validated for clinical usages by two radiation oncologists and one radiologist. Results: Qualitative measurements on repeated swine head images demonstrated that the proposed algorithm efficiently removed noise while preserving the structures and tissues boundaries. In comparisons, the proposed algorithm obtained competitive noise reduction performance and outperformed other filters in preserving anatomical structures. Assessments from the manual validation indicate that the proposed noise reduction algorithm is quite adequate for some clinical usages. Conclusion: According to both clinical evaluation (human expert ranking) and
SU-C-207B-02: Maximal Noise Reduction Filter with Anatomical Structures Preservation
International Nuclear Information System (INIS)
Maitree, R; Guzman, G; Chundury, A; Roach, M; Yang, D
2016-01-01
Purpose: All medical images contain noise, which can result in an undesirable appearance and can reduce the visibility of anatomical details. There are varieties of techniques utilized to reduce noise such as increasing the image acquisition time and using post-processing noise reduction algorithms. However, these techniques are increasing the imaging time and cost or reducing tissue contrast and effective spatial resolution which are useful diagnosis information. The three main focuses in this study are: 1) to develop a novel approach that can adaptively and maximally reduce noise while preserving valuable details of anatomical structures, 2) to evaluate the effectiveness of available noise reduction algorithms in comparison to the proposed algorithm, and 3) to demonstrate that the proposed noise reduction approach can be used clinically. Methods: To achieve a maximal noise reduction without destroying the anatomical details, the proposed approach automatically estimated the local image noise strength levels and detected the anatomical structures, i.e. tissue boundaries. Such information was used to adaptively adjust strength of the noise reduction filter. The proposed algorithm was tested on 34 repeating swine head datasets and 54 patients MRI and CT images. The performance was quantitatively evaluated by image quality metrics and manually validated for clinical usages by two radiation oncologists and one radiologist. Results: Qualitative measurements on repeated swine head images demonstrated that the proposed algorithm efficiently removed noise while preserving the structures and tissues boundaries. In comparisons, the proposed algorithm obtained competitive noise reduction performance and outperformed other filters in preserving anatomical structures. Assessments from the manual validation indicate that the proposed noise reduction algorithm is quite adequate for some clinical usages. Conclusion: According to both clinical evaluation (human expert ranking) and
2D evaluation of spectral LIBS data derived from heterogeneous materials using cluster algorithm
Gottlieb, C.; Millar, S.; Grothe, S.; Wilsch, G.
2017-08-01
Laser-induced Breakdown Spectroscopy (LIBS) is capable of providing spatially resolved element maps in regard to the chemical composition of the sample. The evaluation of heterogeneous materials is often a challenging task, especially in the case of phase boundaries. In order to determine information about a certain phase of a material, the need for a method that offers an objective evaluation is necessary. This paper will introduce a cluster algorithm in the case of heterogeneous building materials (concrete) to separate the spectral information of non-relevant aggregates and cement matrix. In civil engineering, the information about the quantitative ingress of harmful species like Cl-, Na+ and SO42- is of great interest in the evaluation of the remaining lifetime of structures (Millar et al., 2015; Wilsch et al., 2005). These species trigger different damage processes such as the alkali-silica reaction (ASR) or the chloride-induced corrosion of the reinforcement. Therefore, a discrimination between the different phases, mainly cement matrix and aggregates, is highly important (Weritz et al., 2006). For the 2D evaluation, the expectation-maximization-algorithm (EM algorithm; Ester and Sander, 2000) has been tested for the application presented in this work. The method has been introduced and different figures of merit have been presented according to recommendations given in Haddad et al. (2014). Advantages of this method will be highlighted. After phase separation, non-relevant information can be excluded and only the wanted phase displayed. Using a set of samples with known and unknown composition, the EM-clustering method has been validated regarding to Gustavo González and Ángeles Herrador (2007).
Combinatorial optimization theory and algorithms
Korte, Bernhard
2018-01-01
This comprehensive textbook on combinatorial optimization places special emphasis on theoretical results and algorithms with provably good performance, in contrast to heuristics. It is based on numerous courses on combinatorial optimization and specialized topics, mostly at graduate level. This book reviews the fundamentals, covers the classical topics (paths, flows, matching, matroids, NP-completeness, approximation algorithms) in detail, and proceeds to advanced and recent topics, some of which have not appeared in a textbook before. Throughout, it contains complete but concise proofs, and also provides numerous exercises and references. This sixth edition has again been updated, revised, and significantly extended. Among other additions, there are new sections on shallow-light trees, submodular function maximization, smoothed analysis of the knapsack problem, the (ln 4+ɛ)-approximation for Steiner trees, and the VPN theorem. Thus, this book continues to represent the state of the art of combinatorial opti...
Expectation-Maximization Tensor Factorization for Practical Location Privacy Attacks
Directory of Open Access Journals (Sweden)
Murakami Takao
2017-10-01
Full Text Available Location privacy attacks based on a Markov chain model have been widely studied to de-anonymize or de-obfuscate mobility traces. An adversary can perform various kinds of location privacy attacks using a personalized transition matrix, which is trained for each target user. However, the amount of training data available to the adversary can be very small, since many users do not disclose much location information in their daily lives. In addition, many locations can be missing from the training traces, since many users do not disclose their locations continuously but rather sporadically. In this paper, we show that the Markov chain model can be a threat even in this realistic situation. Specifically, we focus on a training phase (i.e. mobility profile building phase and propose Expectation-Maximization Tensor Factorization (EMTF, which alternates between computing a distribution of missing locations (E-step and computing personalized transition matrices via tensor factorization (M-step. Since the time complexity of EMTF is exponential in the number of missing locations, we propose two approximate learning methods, one of which uses the Viterbi algorithm while the other uses the Forward Filtering Backward Sampling (FFBS algorithm. We apply our learning methods to a de-anonymization attack and a localization attack, and evaluate them using three real datasets. The results show that our learning methods significantly outperform a random guess, even when there is only one training trace composed of 10 locations per user, and each location is missing with probability 80% (i.e. even when users hardly disclose two temporally-continuous locations.
Engblom, Henrik; Tufvesson, Jane; Jablonowski, Robert; Carlsson, Marcus; Aletras, Anthony H; Hoffmann, Pavel; Jacquier, Alexis; Kober, Frank; Metzler, Bernhard; Erlinge, David; Atar, Dan; Arheden, Håkan; Heiberg, Einar
2016-05-04
Late gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR) using magnitude inversion recovery (IR) or phase sensitive inversion recovery (PSIR) has become clinical standard for assessment of myocardial infarction (MI). However, there is no clinical standard for quantification of MI even though multiple methods have been proposed. Simple thresholds have yielded varying results and advanced algorithms have only been validated in single center studies. Therefore, the aim of this study was to develop an automatic algorithm for MI quantification in IR and PSIR LGE images and to validate the new algorithm experimentally and compare it to expert delineations in multi-center, multi-vendor patient data. The new automatic algorithm, EWA (Expectation Maximization, weighted intensity, a priori information), was implemented using an intensity threshold by Expectation Maximization (EM) and a weighted summation to account for partial volume effects. The EWA algorithm was validated in-vivo against triphenyltetrazolium-chloride (TTC) staining (n = 7 pigs with paired IR and PSIR images) and against ex-vivo high resolution T1-weighted images (n = 23 IR and n = 13 PSIR images). The EWA algorithm was also compared to expert delineation in 124 patients from multi-center, multi-vendor clinical trials 2-6 days following first time ST-elevation myocardial infarction (STEMI) treated with percutaneous coronary intervention (PCI) (n = 124 IR and n = 49 PSIR images). Infarct size by the EWA algorithm in vivo in pigs showed a bias to ex-vivo TTC of -1 ± 4%LVM (R = 0.84) in IR and -2 ± 3%LVM (R = 0.92) in PSIR images and a bias to ex-vivo T1-weighted images of 0 ± 4%LVM (R = 0.94) in IR and 0 ± 5%LVM (R = 0.79) in PSIR images. In multi-center patient studies, infarct size by the EWA algorithm showed a bias to expert delineation of -2 ± 6 %LVM (R = 0.81) in IR images (n = 124) and 0 ± 5%LVM (R = 0.89) in
Shareholder, stakeholder-owner or broad stakeholder maximization
DEFF Research Database (Denmark)
Mygind, Niels
2004-01-01
With reference to the discussion about shareholder versus stakeholder maximization it is argued that the normal type of maximization is in fact stakeholder-owner maxi-mization. This means maximization of the sum of the value of the shares and stake-holder benefits belonging to the dominating...... including the shareholders of a company. Although it may be the ultimate goal for Corporate Social Responsibility to achieve this kind of maximization, broad stakeholder maximization is quite difficult to give a precise definition. There is no one-dimensional measure to add different stakeholder benefits...... not traded on the mar-ket, and therefore there is no possibility for practical application. Broad stakeholder maximization instead in practical applications becomes satisfying certain stakeholder demands, so that the practical application will be stakeholder-owner maximization un-der constraints defined...
Maximizing Lumen Gain With Directional Atherectomy.
Stanley, Gregory A; Winscott, John G
2016-08-01
To describe the use of a low-pressure balloon inflation (LPBI) technique to delineate intraluminal plaque and guide directional atherectomy in order to maximize lumen gain and achieve procedure success. The technique is illustrated in a 77-year-old man with claudication who underwent superficial femoral artery revascularization using a HawkOne directional atherectomy catheter. A standard angioplasty balloon was inflated to 1 to 2 atm during live fluoroscopy to create a 3-dimensional "lumenogram" of the target lesion. Directional atherectomy was performed only where plaque impinged on the balloon at a specific fluoroscopic orientation. The results of the LPBI technique were corroborated with multimodality diagnostic imaging, including digital subtraction angiography, intravascular ultrasound, and intra-arterial pressure measurements. With the LPBI technique, directional atherectomy can routinely achieve <10% residual stenosis, as illustrated in this case, thereby broadly supporting a no-stent approach to lower extremity endovascular revascularization. © The Author(s) 2016.
Primordial two-component maximally symmetric inflation
Enqvist, K.; Nanopoulos, D. V.; Quirós, M.; Kounnas, C.
1985-12-01
We propose a two-component inflation model, based on maximally symmetric supergravity, where the scales of reheating and the inflation potential at the origin are decoupled. This is possible because of the second-order phase transition from SU(5) to SU(3)×SU(2)×U(1) that takes place when φ≅φcinflation at the global minimum, and leads to a reheating temperature TR≅(1015-1016) GeV. This makes it possible to generate baryon asymmetry in the conventional way without any conflict with experimental data on proton lifetime. The mass of the gravitinos is m3/2≅1012 GeV, thus avoiding the gravitino problem. Monopoles are diluted by residual inflation in the broken phase below the cosmological bounds if φcUSA.
Quench dynamics of topological maximally entangled states.
Chung, Ming-Chiang; Jhu, Yi-Hao; Chen, Pochung; Mou, Chung-Yu
2013-07-17
We investigate the quench dynamics of the one-particle entanglement spectra (OPES) for systems with topologically nontrivial phases. By using dimerized chains as an example, it is demonstrated that the evolution of OPES for the quenched bipartite systems is governed by an effective Hamiltonian which is characterized by a pseudospin in a time-dependent pseudomagnetic field S(k,t). The existence and evolution of the topological maximally entangled states (tMESs) are determined by the winding number of S(k,t) in the k-space. In particular, the tMESs survive only if nontrivial Berry phases are induced by the winding of S(k,t). In the infinite-time limit the equilibrium OPES can be determined by an effective time-independent pseudomagnetic field Seff(k). Furthermore, when tMESs are unstable, they are destroyed by quasiparticles within a characteristic timescale in proportion to the system size.
Maximizing policy learning in international committees
DEFF Research Database (Denmark)
Nedergaard, Peter
2007-01-01
, this article demonstrates that valuable lessons can be learned about policy learning, in practice and theoretically, by analysing the cooperation in the OMC committees. Using the Advocacy Coalition Framework as the starting point of analysis, 15 hypotheses on policy learning are tested. Among other things......In the voluminous literature on the European Union's open method of coordination (OMC), no one has hitherto analysed on the basis of scholarly examination the question of what contributes to the learning processes in the OMC committees. On the basis of a questionnaire sent to all participants......, it is concluded that in order to maximize policy learning in international committees, empirical data should be made available to committees and provided by sources close to the participants (i.e. the Commission). In addition, the work in the committees should be made prestigious in order to attract well...
Lovelock black holes with maximally symmetric horizons
Energy Technology Data Exchange (ETDEWEB)
Maeda, Hideki; Willison, Steven; Ray, Sourya, E-mail: hideki@cecs.cl, E-mail: willison@cecs.cl, E-mail: ray@cecs.cl [Centro de Estudios CientIficos (CECs), Casilla 1469, Valdivia (Chile)
2011-08-21
We investigate some properties of n( {>=} 4)-dimensional spacetimes having symmetries corresponding to the isometries of an (n - 2)-dimensional maximally symmetric space in Lovelock gravity under the null or dominant energy condition. The well-posedness of the generalized Misner-Sharp quasi-local mass proposed in the past study is shown. Using this quasi-local mass, we clarify the basic properties of the dynamical black holes defined by a future outer trapping horizon under certain assumptions on the Lovelock coupling constants. The C{sup 2} vacuum solutions are classified into four types: (i) Schwarzschild-Tangherlini-type solution; (ii) Nariai-type solution; (iii) special degenerate vacuum solution; and (iv) exceptional vacuum solution. The conditions for the realization of the last two solutions are clarified. The Schwarzschild-Tangherlini-type solution is studied in detail. We prove the first law of black-hole thermodynamics and present the expressions for the heat capacity and the free energy.
MAXIMIZING THE BENEFITS OF ERP SYSTEMS
Directory of Open Access Journals (Sweden)
Paulo André da Conceição Menezes
2010-04-01
Full Text Available The ERP (Enterprise Resource Planning systems have been consolidated in companies with different sizes and sectors, allowing their real benefits to be definitively evaluated. In this study, several interactions have been studied in different phases, such as the strategic priorities and strategic planning defined as ERP Strategy; business processes review and the ERP selection in the pre-implementation phase, the project management and ERP adaptation in the implementation phase, as well as the ERP revision and integration efforts in the post-implementation phase. Through rigorous use of case study methodology, this research led to developing and to testing a framework for maximizing the benefits of the ERP systems, and seeks to contribute for the generation of ERP initiatives to optimize their performance.
Maximal energy extraction under discrete diffusive exchange
Energy Technology Data Exchange (ETDEWEB)
Hay, M. J., E-mail: hay@princeton.edu [Department of Astrophysical Sciences, Princeton University, Princeton, New Jersey 08544 (United States); Schiff, J. [Department of Mathematics, Bar-Ilan University, Ramat Gan 52900 (Israel); Fisch, N. J. [Department of Astrophysical Sciences, Princeton University, Princeton, New Jersey 08544 (United States); Princeton Plasma Physics Laboratory, Princeton, New Jersey 08543 (United States)
2015-10-15
Waves propagating through a bounded plasma can rearrange the densities of states in the six-dimensional velocity-configuration phase space. Depending on the rearrangement, the wave energy can either increase or decrease, with the difference taken up by the total plasma energy. In the case where the rearrangement is diffusive, only certain plasma states can be reached. It turns out that the set of reachable states through such diffusive rearrangements has been described in very different contexts. Building upon those descriptions, and making use of the fact that the plasma energy is a linear functional of the state densities, the maximal extractable energy under diffusive rearrangement can then be addressed through linear programming.
Maximizing profitability in a hospital outpatient pharmacy.
Jorgenson, J A; Kilarski, J W; Malatestinic, W N; Rudy, T A
1989-07-01
This paper describes the strategies employed to increase the profitability of an existing ambulatory pharmacy operated by the hospital. Methods to generate new revenue including implementation of a home parenteral therapy program, a home enteral therapy program, a durable medical equipment service, and home care disposable sales are described. Programs to maximize existing revenue sources such as increasing the capture rate on discharge prescriptions, increasing "walk-in" prescription traffic and increasing HMO prescription volumes are discussed. A method utilized to reduce drug expenditures is also presented. By minimizing expenses and increasing the revenues for the ambulatory pharmacy operation, net profit increased from +26,000 to over +140,000 in one year.
Maximizing the benefits of a dewatering system
International Nuclear Information System (INIS)
Matthews, P.; Iverson, T.S.
1999-01-01
The use of dewatering systems in the mining, industrial sludge and sewage waste treatment industries is discussed, also describing some of the problems that have been encountered while using drilling fluid dewatering technology. The technology is an acceptable drilling waste handling alternative but it has had problems associated with recycled fluid incompatibility, high chemical costs and system inefficiencies. This paper discussed the following five action areas that can maximize the benefits and help reduce costs of a dewatering project: (1) co-ordinate all services, (2) choose equipment that fits the drilling program, (3) match the chemical treatment with the drilling fluid types, (4) determine recycled fluid compatibility requirements, and (5) determine the disposal requirements before project start-up. 2 refs., 5 figs
Mixtures of maximally entangled pure states
Energy Technology Data Exchange (ETDEWEB)
Flores, M.M., E-mail: mflores@nip.up.edu.ph; Galapon, E.A., E-mail: eric.galapon@gmail.com
2016-09-15
We study the conditions when mixtures of maximally entangled pure states remain entangled. We found that the resulting mixed state remains entangled when the number of entangled pure states to be mixed is less than or equal to the dimension of the pure states. For the latter case of mixing a number of pure states equal to their dimension, we found that the mixed state is entangled provided that the entangled pure states to be mixed are not equally weighted. We also found that one can restrict the set of pure states that one can mix from in order to ensure that the resulting mixed state is genuinely entangled. Also, we demonstrate how these results could be applied as a way to detect entanglement in mixtures of the entangled pure states with noise.
Maximally reliable Markov chains under energy constraints.
Escola, Sean; Eisele, Michael; Miller, Kenneth; Paninski, Liam
2009-07-01
Signal-to-noise ratios in physical systems can be significantly degraded if the outputs of the systems are highly variable. Biological processes for which highly stereotyped signal generations are necessary features appear to have reduced their signal variabilities by employing multiple processing steps. To better understand why this multistep cascade structure might be desirable, we prove that the reliability of a signal generated by a multistate system with no memory (i.e., a Markov chain) is maximal if and only if the system topology is such that the process steps irreversibly through each state, with transition rates chosen such that an equal fraction of the total signal is generated in each state. Furthermore, our result indicates that by increasing the number of states, it is possible to arbitrarily increase the reliability of the system. In a physical system, however, an energy cost is associated with maintaining irreversible transitions, and this cost increases with the number of such transitions (i.e., the number of states). Thus, an infinite-length chain, which would be perfectly reliable, is infeasible. To model the effects of energy demands on the maximally reliable solution, we numerically optimize the topology under two distinct energy functions that penalize either irreversible transitions or incommunicability between states, respectively. In both cases, the solutions are essentially irreversible linear chains, but with upper bounds on the number of states set by the amount of available energy. We therefore conclude that a physical system for which signal reliability is important should employ a linear architecture, with the number of states (and thus the reliability) determined by the intrinsic energy constraints of the system.
A Criterion to Identify Maximally Entangled Four-Qubit State
International Nuclear Information System (INIS)
Zha Xinwei; Song Haiyang; Feng Feng
2011-01-01
Paolo Facchi, et al. [Phys. Rev. A 77 (2008) 060304(R)] presented a maximally multipartite entangled state (MMES). Here, we give a criterion for the identification of maximally entangled four-qubit states. Using this criterion, we not only identify some existing maximally entangled four-qubit states in the literature, but also find several new maximally entangled four-qubit states as well. (general)
Directory of Open Access Journals (Sweden)
Xuefeng Zhang
2012-05-01
Full Text Available Fluorescence<em> em>>in situ em>hybridization (FISH assay is considered the “gold standard” in evaluating <em>HER2/neu (HER2em> gene status. However, FISH detection is costly and time consuming. Thus, we established nuclei microarray with extracted intact nuclei from paraffin embedded breast cancer tissues for FISH detection. The nuclei microarray FISH (NMFISH technology serves as a useful platform for analyzing <em>HER2em> gene/chromosome 17 centromere ratio. We examined <em>HER2em> gene status in 152 cases of invasive ductal carcinomas of the breast that were resected surgically with FISH and NMFISH. <em>HER2em> gene amplification status was classified according to the guidelines of the American Society of Clinical Oncology and College of American Pathologists (ASCO/CAP. Comparison of the cut-off values for <em>HER2em>/chromosome 17 centromere copy number ratio obtained by NMFISH and FISH showed that there was almost perfect agreement between the two methods (κ coefficient 0.920. The results of the two methods were almost consistent for the evaluation of <em>HER2em> gene counts. The present study proved that NMFISH is comparable with FISH for evaluating <em>HER2em> gene status. The use of nuclei microarray technology is highly efficient, time and reagent conserving and inexpensive.
Statistical complexity is maximized in a small-world brain.
Directory of Open Access Journals (Sweden)
Teck Liang Tan
Full Text Available In this paper, we study a network of Izhikevich neurons to explore what it means for a brain to be at the edge of chaos. To do so, we first constructed the phase diagram of a single Izhikevich excitatory neuron, and identified a small region of the parameter space where we find a large number of phase boundaries to serve as our edge of chaos. We then couple the outputs of these neurons directly to the parameters of other neurons, so that the neuron dynamics can drive transitions from one phase to another on an artificial energy landscape. Finally, we measure the statistical complexity of the parameter time series, while the network is tuned from a regular network to a random network using the Watts-Strogatz rewiring algorithm. We find that the statistical complexity of the parameter dynamics is maximized when the neuron network is most small-world-like. Our results suggest that the small-world architecture of neuron connections in brains is not accidental, but may be related to the information processing that they do.
Managing the innovation supply chain to maximize personalized medicine.
Waldman, S A; Terzic, A
2014-02-01
Personalized medicine epitomizes an evolving model of care tailored to the individual patient. This emerging paradigm harnesses radical technological advances to define each patient's molecular characteristics and decipher his or her unique pathophysiological processes. Translated into individualized algorithms, personalized medicine aims to predict, prevent, and cure disease without producing therapeutic adverse events. Although the transformative power of personalized medicine is generally recognized by physicians, patients, and payers, the complexity of translating discoveries into new modalities that transform health care is less appreciated. We often consider the flow of innovation and technology along a continuum of discovery, development, regulation, and application bridging the bench with the bedside. However, this process also can be viewed through a complementary prism, as a necessary supply chain of services and providers, each making essential contributions to the development of the final product to maximize value to consumers. Considering personalized medicine in this context of supply chain management highlights essential points of vulnerability and/or scalability that can ultimately constrain translation of the biological revolution or potentiate it into individualized diagnostics and therapeutics for optimized value creation and delivery.
Directory of Open Access Journals (Sweden)
Paulo de Tarso Guerrero Müller
2012-10-01
Full Text Available OBJETIVO: Comparar o comportamento de oxygen uptake efficiency slope (OUES, inclinação da eficiência do consumo de oxigênio com o do consumo de oxigênio no pico do exercício (VO2pico. MÉTODOS: Estudo prospectivo transversal envolvendo 21 pacientes (15 homens com DPOC leve/moderada que foram submetidos a espirometria, dinamometria de preensão palmar (DIN, teste cardiopulmonar de exercício e medida de lactato no pico do exercício (LACpico. RESULTADOS: A média de peso foi 66,7 ± 13,6 kg, e a de idade foi 60,7 ± 7,8 anos. Com exceção de VEF1 e relação VEF1/CVF (75,8 ± 18,6 do previsto e 56,6 ± 8,8, respectivamente, as demais variáveis espirométricas foram normais, assim como DIN. As médias, em % do previsto, para VO2pico (93,1 ± 15,4, FC máxima (92,5 ± 10,4 e OUES (99,4 ± 24,4, assim como a da taxa de troca respiratória (1,2 ± 0,1, indicaram estresse metabólico e hemodinâmico importante. A correlação entre o VO2pico e a OUES foi elevada (r = 0,747; p OBJECTIVE: To compare the behavior of the oxygen uptake efficiency slope (OUES with that of oxygen uptake at peak exertion (VO2peak. METHODS: This was a prospective cross-sectional study involving 21 patients (15 men with mild-to-moderate COPD undergoing spirometry, handgrip strength (HGS testing, cardiopulmonary exercise testing, and determination of lactate at peak exertion (LACpeak. RESULTS: Mean weight was 66.7 ± 13.6 kg, and mean age was 60.7 ± 7.8 years. With the exception of FEV1 and FEV1/FVC ratio (75.8 ± 18.6 of predicted and 56.6 ± 8.8, respectively, all spirometric variables were normal, as was HGS. The patients exhibited significant metabolic and hemodynamic stress, as evidenced by the means (% of predicted for VO2peak (93.1 ± 15.4, maximum HR (92.5 ± 10.4, and OUES (99.4 ± 24.4, as well as for the gas exchange rate (1.2 ± 0.1. The correlation between VO2peak and OUES was significant (r = 0.747; p < 0.0001. The correlation between HGS and VO2peak (r
Directory of Open Access Journals (Sweden)
Stefan Braren Damato
2015-04-01
Full Text Available O mercado de confinamento demonstra alto grau de complexidade quanto às variáveis que o influenciam, gerando dificuldade no estabelecimento de diretrizes estratégicas para a atividade. A necessidade de gerar milhares de simulações de resultados para que se tornasse possível uma visão ampla de negócios levou à criação de uma ferramenta que cruzasse a maior quantidade possível de dados técnicos e mercadológicos, concatenasse as informações disponíveis e retornasse cenários de forma direta ao gestor, possibilitando a este, a determinação de objetivos e estratégias que aumentariam a competitividade da empresa. Para tanto, foi estudado um confinamento no estado de Goiás, em que foram obtidas informações reais de produção e resultados financeiros no ano de 2012. Foram comparados cenários reais e simulados, com a finalidade de se comparar o EBITDA, além de ser apresentada uma breve explanação sobre os fatores que tem direta influência sobre os cálculos realizados. Os estudos demonstram que a utilização de um plano estratégico pode contribuir positivamente para a lucratividade ao responder o melhor momento de confinar, o perfil dos animais, e o período ideal de manutenção no regime de engorda. Por questão de confidencialidade empresarial, não foi autorizada a divulgação da fonte dos dados. = The containment market shows a high degree of complexity for the variables that influence it, hindering the establishment of strategic guidelines for the activity. The need to generate thousands of simulating results to obtain a broad vision of the business has led to the creation of a tool that crossed the largest possible amount of market and technical data, concatenating information available and developing scenarios directly to the manager, providing tools to determine objectives and strategies to increase company’s competitiveness. For that purpose, a feedlot in the state of Goiás (Brazil was studied, where actual
Optimization of Second Fault Detection Thresholds to Maximize Mission POS
Anzalone, Evan
2018-01-01
both magnitude and time. As such, the Navigation team is taking advantage of the INS's capability to schedule and change fault detection thresholds in flight. These values are optimized along a nominal trajectory in order to maximize probability of mission success, and reducing the probability of false positives (defined as when the INS would report a second fault condition resulting in loss of mission, but the vehicle would still meet insertion requirements within system-level margins). This paper will describe an optimization approach using Genetic Algorithms to tune the threshold parameters to maximize vehicle resilience to second fault events as a function of potential fault magnitude and time of fault over an ascent mission profile. The analysis approach, and performance assessment of the results will be presented to demonstrate the applicability of this process to second fault detection to maximize mission probability of success.
Energy Technology Data Exchange (ETDEWEB)
Gewehr, Diego N.; Vargas, Ricardo B.; Melo, Eduardo D. de; Paschoareli Junior, Dionizio [Universidade Estadual Paulista (DEE/UNESP), Ilha Solteira, SP (Brazil). Dept. de Engenharia Eletrica. Grupo de Pesquisa em Fontes Alternativas e Aproveitamento de Energia
2008-07-01
This paper presents a methodology for electric power sources location in isolated direct current micro grids, using genetic algorithm. In this work, photovoltaic panels are considered, although the methodology can be extended for any kind of DC sources. A computational tool is developed using the Matlab simulator, to obtain the best dc system configuration for reduction of panels quantity and costs, and to improve the system performance. (author)
Allenby, Mark C; Misener, Ruth; Panoskaltsis, Nicki; Mantalaris, Athanasios
2017-02-01
Three-dimensional (3D) imaging techniques provide spatial insight into environmental and cellular interactions and are implemented in various fields, including tissue engineering, but have been restricted by limited quantification tools that misrepresent or underutilize the cellular phenomena captured. This study develops image postprocessing algorithms pairing complex Euclidean metrics with Monte Carlo simulations to quantitatively assess cell and microenvironment spatial distributions while utilizing, for the first time, the entire 3D image captured. Although current methods only analyze a central fraction of presented confocal microscopy images, the proposed algorithms can utilize 210% more cells to calculate 3D spatial distributions that can span a 23-fold longer distance. These algorithms seek to leverage the high sample cost of 3D tissue imaging techniques by extracting maximal quantitative data throughout the captured image.
A New Natural Lactone from <em>Dimocarpus> <em>longan> Lour. Seeds
Directory of Open Access Journals (Sweden)
Zhongjun Li
2012-08-01
Full Text Available A new natural product named longanlactone was isolated from <em>Dimocarpus> <em>longan> Lour. seeds. Its structure was determined as 3-(2-acetyl-1<em>H>-pyrrol-1-yl-5-(prop-2-yn-1-yldihydrofuran-2(3H-one by spectroscopic methods and HRESIMS.
Energy Technology Data Exchange (ETDEWEB)
Fontana, W.
1990-12-13
In this paper complex adaptive systems are defined by a self- referential loop in which objects encode functions that act back on these objects. A model for this loop is presented. It uses a simple recursive formal language, derived from the lambda-calculus, to provide a semantics that maps character strings into functions that manipulate symbols on strings. The interaction between two functions, or algorithms, is defined naturally within the language through function composition, and results in the production of a new function. An iterated map acting on sets of functions and a corresponding graph representation are defined. Their properties are useful to discuss the behavior of a fixed size ensemble of randomly interacting functions. This function gas'', or Turning gas'', is studied under various conditions, and evolves cooperative interaction patterns of considerable intricacy. These patterns adapt under the influence of perturbations consisting in the addition of new random functions to the system. Different organizations emerge depending on the availability of self-replicators.
Sum Rate Maximization of D2D Communications in Cognitive Radio Network Using Cheating Strategy
Directory of Open Access Journals (Sweden)
Yanjing Sun
2018-01-01
Full Text Available This paper focuses on the cheating algorithm for device-to-device (D2D pairs that reuse the uplink channels of cellular users. We are concerned about the way how D2D pairs are matched with cellular users (CUs to maximize their sum rate. In contrast with Munkres’ algorithm which gives the optimal matching in terms of the maximum throughput, Gale-Shapley algorithm ensures the stability of the system on the same time and achieves a men-optimal stable matching. In our system, D2D pairs play the role of “men,” so that each D2D pair could be matched to the CU that ranks as high as possible in the D2D pair’s preference list. It is found by previous studies that, by unilaterally falsifying preference lists in a particular way, some men can get better partners, while no men get worse off. We utilize this theory to exploit the best cheating strategy for D2D pairs. We find out that to acquire such a cheating strategy, we need to seek as many and as large cabals as possible. To this end, we develop a cabal finding algorithm named RHSTLC, and also we prove that it reaches the Pareto optimality. In comparison with other algorithms proposed by related works, the results show that our algorithm can considerably improve the sum rate of D2D pairs.
Directory of Open Access Journals (Sweden)
Zhong Wan
2013-01-01
Full Text Available In accord with the practical engineering design conditions, a nonlinear programming model is constructed for maximizing the fatigue life of V-belt drive in which some polymorphic uncertainties are incorporated. For a given satisfaction level and a confidence level, an equivalent formulation of this uncertain optimization model is obtained where only interval parameters are involved. Based on the concepts of maximal and minimal range inequalities for describing interval inequality, the interval parameter model is decomposed into two standard nonlinear programming problems, and an algorithm, called two-step based sampling algorithm, is developed to find an interval optimal solution for the original problem. Case study is employed to demonstrate the validity and practicability of the constructed model and the algorithm.
Reference Gene Selection in the Desert Plant <em>Eremosparton songoricuem>m>
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Dao-Yuan Zhang
2012-06-01
Full Text Available <em>Eremosparton songoricum em>(Litv. Vass. (<em>E. songoricumem> is a rare and extremely drought-tolerant desert plant that holds promise as a model organism for the identification of genes associated with water deficit stress. Here, we cloned and evaluated the expression of eight candidate reference genes using quantitative real-time reverse transcriptase polymerase chain reactions. The expression of these candidate reference genes was analyzed in a diverse set of 20 samples including various <em>E. songoricumem> plant tissues exposed to multiple environmental stresses. GeNorm analysis indicated that expression stability varied between the reference genes in the different experimental conditions, but the two most stable reference genes were sufficient for normalization in most conditions.<em> EsEFem> and <em>Esα-TUB> were sufficient for various stress conditions, <em>EsEF> and <em>EsACT> were suitable for samples of differing germination stages, and <em>EsGAPDH>and <em>Es>UBQ em>were most stable across multiple adult tissue samples. The <em>Es18Sem> gene was unsuitable as a reference gene in our analysis. In addition, the expression level of the drought-stress related transcription factor <em>EsDREB2em>> em>verified the utility of<em> E. songoricumem> reference genes and indicated that no single gene was adequate for normalization on its own. This is the first systematic report on the selection of reference genes in <em>E. songoricumem>, and these data will facilitate future work on gene expression in this species.
On maximal surfaces in asymptotically flat space-times
International Nuclear Information System (INIS)
Bartnik, R.; Chrusciel, P.T.; O Murchadha, N.
1990-01-01
Existence of maximal and 'almost maximal' hypersurfaces in asymptotically flat space-times is established under boundary conditions weaker than those considered previously. We show in particular that every vacuum evolution of asymptotically flat data for Einstein equations can be foliated by slices maximal outside a spatially compact set and that every (strictly) stationary asymptotically flat space-time can be foliated by maximal hypersurfaces. Amongst other uniqueness results, we show that maximal hypersurface can be used to 'partially fix' an asymptotic Poincare group. (orig.)
Vilanova, Pedro
2016-01-01
reaction networks (SRNs). We apply this stochastic representation to the computation of efficient approximations of expected values of functionals of SRN bridges, i.e., SRNs conditional on their values in the extremes of given time-intervals. We then employ
Bayer, Christian; Moraes, Alvaro; Tempone, Raul; Vilanova, Pedro
2016-01-01
then employ this SRN bridge-generation technique to the statistical inference problem of approximating reaction propensities based on discretely observed data. To this end, we introduce a two-phase iterative inference method in which, during phase I, we solve
J. Byrka (Jaroslaw); K.T. Huber; S.M. Kelk (Steven); P. Gawrychowski
2009-01-01
htmlabstractThe study of phylogenetic networks is of great interest to computational evolutionary biology and numerous different types of such structures are known. This article addresses the following question concerning rooted versions of phylogenetic networks. What is the maximum value of pset
Power backup Density based Clustering Algorithm for Maximizing Lifetime of Wireless Sensor Networks
DEFF Research Database (Denmark)
Wagh, Sanjeev; Prasad, Ramjee
2014-01-01
WSNs consists several nodes spread over experimental fields for specific application temporarily. The spatially distributed sensor nodes sense and gather the information for intended parameters like temperature, sound, vibrations, etc for the particular application. In this paper, we evaluate the...
A Multilevel Search Algorithm for the Maximization of Submodular Functions
Goldengorin, Boris; Ghosh, Diptesh
2004-01-01
We consider the objective function of a simple recourse problem with fixed technology matrix and integer second-stage variables. Separability due to the simple recourse structure allows to study a one-dimensional version instead. Based on an explicit formula for the objective function, we derive a
Energy Technology Data Exchange (ETDEWEB)
Vieira, Jose Wilson; Leal Neto, Viriato; Lima Filho, Jose de Melo, E-mail: jose.wilson59@uol.com.br [Instituto Federal de Educacao Ciencia e Tecnologia de Pernambuco (IFPE), Recife, PE (Brazil); Lima, Fernando Roberto de Andrade [Centro Regional de Ciencias Nucleares do Nordeste (CRCN-NE/CNEN-PE), Recife, PE (Brazil)
2013-07-01
This paper presents as algorithm of a planar and isotropic radioactive source and by rotating the probability density function (PDF) Gaussian standard subjected to a translatory method which displaces its maximum throughout its field changes its intensity and makes the dispersion around the mean right asymmetric. The algorithm was used to generate samples of photons emerging from a plane and reach a semicircle involving a phantom voxels. The PDF describing this problem is already known, but the generating function of random numbers (FRN) associated with it can not be deduced by direct MC techniques. This is a significant problem because it can be adjusted to simulations involving natural terrestrial radiation or accidents in medical establishments or industries where the radioactive material spreads in a plane. Some attempts to obtain a FRN for the PDF of the problem have already been implemented by the Research Group in Numerical Dosimetry (GND) from Recife-PE, Brazil, always using the technique rejection sampling MC. This article followed methodology of previous work, except on one point: The problem of the PDF was replaced by a normal PDF transferred. To perform dosimetric comparisons, we used two MCES: the MSTA (Mash standing, composed by the adult male voxel phantom in orthostatic position, MASH (male mesh), available from the Department of Nuclear Energy (DEN) of the Federal University of Pernambuco (UFPE), coupled to MC EGSnrc code and the GND planar source based on the rejection technique) and MSTA{sub N}T. The two MCES are similar in all but FRN used in planar source. The results presented and discussed in this paper establish the new algorithm for a planar source to be used by GND.
Energy Technology Data Exchange (ETDEWEB)
Lapa, Celso M. Franklin; Pereira, Claudio M.N.A.; Mol, Antonio C. de Abreu [Instituto de Engenharia Nuclear (IEN), Rio de Janeiro, RJ (Brazil)
1999-07-01
This paper presents a solution based on genetic algorithm and probabilistic safety analysis that can be applied in the optimization of the preventive maintenance politic of nuclear power plant safety systems. The goal of this approach is to improve the average availability of the system through the optimization of the preventive maintenance scheduling politic. The auxiliary feed water system of a two loops pressurized water reactor is used as a sample case, in order to demonstrate the effectiveness of the proposed method. The results, when compared to those obtained by some standard maintenance politics, reveal quantitative gains and operational safety levels. (author)
A Lyapunov based approach to energy maximization in renewable energy technologies
Iyasere, Erhun
This dissertation describes the design and implementation of Lyapunov-based control strategies for the maximization of the power captured by renewable energy harnessing technologies such as (i) a variable speed, variable pitch wind turbine, (ii) a variable speed wind turbine coupled to a doubly fed induction generator, and (iii) a solar power generating system charging a constant voltage battery. First, a torque control strategy is presented to maximize wind energy captured in variable speed, variable pitch wind turbines at low to medium wind speeds. The proposed strategy applies control torque to the wind turbine pitch and rotor subsystems to simultaneously control the blade pitch and tip speed ratio, via the rotor angular speed, to an optimum point at which the capture efficiency is maximum. The control method allows for aerodynamic rotor power maximization without exact knowledge of the wind turbine model. A series of numerical results show that the wind turbine can be controlled to achieve maximum energy capture. Next, a control strategy is proposed to maximize the wind energy captured in a variable speed wind turbine, with an internal induction generator, at low to medium wind speeds. The proposed strategy controls the tip speed ratio, via the rotor angular speed, to an optimum point at which the efficiency constant (or power coefficient) is maximal for a particular blade pitch angle and wind speed by using the generator rotor voltage as a control input. This control method allows for aerodynamic rotor power maximization without exact wind turbine model knowledge. Representative numerical results demonstrate that the wind turbine can be controlled to achieve near maximum energy capture. Finally, a power system consisting of a photovoltaic (PV) array panel, dc-to-dc switching converter, charging a battery is considered wherein the environmental conditions are time-varying. A backstepping PWM controller is developed to maximize the power of the solar generating
A Note of Caution on Maximizing Entropy
Directory of Open Access Journals (Sweden)
Richard E. Neapolitan
2014-07-01
Full Text Available The Principle of Maximum Entropy is often used to update probabilities due to evidence instead of performing Bayesian updating using Bayes’ Theorem, and its use often has efficacious results. However, in some circumstances the results seem unacceptable and unintuitive. This paper discusses some of these cases, and discusses how to identify some of the situations in which this principle should not be used. The paper starts by reviewing three approaches to probability, namely the classical approach, the limiting frequency approach, and the Bayesian approach. It then introduces maximum entropy and shows its relationship to the three approaches. Next, through examples, it shows that maximizing entropy sometimes can stand in direct opposition to Bayesian updating based on reasonable prior beliefs. The paper concludes that if we take the Bayesian approach that probability is about reasonable belief based on all available information, then we can resolve the conflict between the maximum entropy approach and the Bayesian approach that is demonstrated in the examples.
Optimal topologies for maximizing network transmission capacity
Chen, Zhenhao; Wu, Jiajing; Rong, Zhihai; Tse, Chi K.
2018-04-01
It has been widely demonstrated that the structure of a network is a major factor that affects its traffic dynamics. In this work, we try to identify the optimal topologies for maximizing the network transmission capacity, as well as to build a clear relationship between structural features of a network and the transmission performance in terms of traffic delivery. We propose an approach for designing optimal network topologies against traffic congestion by link rewiring and apply them on the Barabási-Albert scale-free, static scale-free and Internet Autonomous System-level networks. Furthermore, we analyze the optimized networks using complex network parameters that characterize the structure of networks, and our simulation results suggest that an optimal network for traffic transmission is more likely to have a core-periphery structure. However, assortative mixing and the rich-club phenomenon may have negative impacts on network performance. Based on the observations of the optimized networks, we propose an efficient method to improve the transmission capacity of large-scale networks.
New features of the maximal abelian projection
International Nuclear Information System (INIS)
Bornyakov, V.G.; Polikarpov, M.I.; Syritsyn, S.N.; Schierholz, G.; Suzuki, T.
2005-12-01
After fixing the Maximal Abelian gauge in SU(2) lattice gauge theory we decompose the nonabelian gauge field into the so called monopole field and the modified nonabelian field with monopoles removed. We then calculate respective static potentials and find that the potential due to the modified nonabelian field is nonconfining while, as is well known, the monopole field potential is linear. Furthermore, we show that the sum of these potentials approximates the nonabelian static potential with 5% or higher precision at all distances considered. We conclude that at large distances the monopole field potential describes the classical energy of the hadronic string while the modified nonabelian field potential describes the string fluctuations. Similar decomposition was observed to work for the adjoint static potential. A check was also made of the center projection in the direct center gauge. Two static potentials, determined by projected Z 2 and by modified nonabelian field without Z 2 component were calculated. It was found that their sum is a substantially worse approximation of the SU(2) static potential than that found in the monopole case. It is further demonstrated that similar decomposition can be made for the flux tube action/energy density. (orig.)
The geometry of entanglement and Grover's algorithm
International Nuclear Information System (INIS)
Iwai, Toshihiro; Hayashi, Naoki; Mizobe, Kimitake
2008-01-01
A measure of entanglement with respect to a bipartite partition of n-qubit has been defined and studied from the viewpoint of Riemannian geometry (Iwai 2007 J. Phys. A: Math. Theor. 40 12161). This paper has two aims. One is to study further the geometry of entanglement, and the other is to investigate Grover's search algorithms, both the original and the fixed-point ones, in reference with entanglement. As the distance between the maximally entangled states and the separable states is known already in the previous paper, this paper determines the set of maximally entangled states nearest to a typical separable state which is used as an initial state in Grover's search algorithms, and to find geodesic segments which realize the above-mentioned distance. As for Grover's algorithms, it is already known that while the initial and the target states are separable, the algorithms generate sequences of entangled states. This fact is confirmed also in the entanglement measure proposed in the previous paper, and then a split Grover algorithm is proposed which generates sequences of separable states only with respect to the bipartite partition
Worst-Case Energy Efficiency Maximization in a 5G Massive MIMO-NOMA System
Directory of Open Access Journals (Sweden)
Sunil Chinnadurai
2017-09-01
Full Text Available In this paper, we examine the robust beamforming design to tackle the energy efficiency (EE maximization problem in a 5G massive multiple-input multiple-output (MIMO-non-orthogonal multiple access (NOMA downlink system with imperfect channel state information (CSI at the base station. A novel joint user pairing and dynamic power allocation (JUPDPA algorithm is proposed to minimize the inter user interference and also to enhance the fairness between the users. This work assumes imperfect CSI by adding uncertainties to channel matrices with worst-case model, i.e., ellipsoidal uncertainty model (EUM. A fractional non-convex optimization problem is formulated to maximize the EE subject to the transmit power constraints and the minimum rate requirement for the cell edge user. The designed problem is difficult to solve due to its nonlinear fractional objective function. We firstly employ the properties of fractional programming to transform the non-convex problem into its equivalent parametric form. Then, an efficient iterative algorithm is proposed established on the constrained concave-convex procedure (CCCP that solves and achieves convergence to a stationary point of the above problem. Finally, Dinkelbach’s algorithm is employed to determine the maximum energy efficiency. Comprehensive numerical results illustrate that the proposed scheme attains higher worst-case energy efficiency as compared with the existing NOMA schemes and the conventional orthogonal multiple access (OMA scheme.
Maximization of Energy Efficiency in Wireless ad hoc and Sensor Networks With SERENA
Directory of Open Access Journals (Sweden)
Saoucene Mahfoudh
2009-01-01
Full Text Available In wireless ad hoc and sensor networks, an analysis of the node energy consumption distribution shows that the largest part is due to the time spent in the idle state. This result is at the origin of SERENA, an algorithm to SchEdule RoutEr Nodes Activity. SERENA allows router nodes to sleep, while ensuring end-to-end communication in the wireless network. It is a localized and decentralized algorithm assigning time slots to nodes. Any node stays awake only during its slot and the slots assigned to its neighbors, it sleeps the remaining time. Simulation results show that SERENA enables us to maximize network lifetime while increasing the number of user messages delivered. SERENA is based on a two-hop coloring algorithm, whose complexity in terms of colors and rounds is evaluated. We then quantify the slot reuse. Finally, we show how SERENA improves the node energy consumption distribution and maximizes the energy efficiency of wireless ad hoc and sensor networks. We compare SERENA with classical TDMA and optimized variants such as USAP in wireless ad hoc and sensor networks.
Worst-Case Energy Efficiency Maximization in a 5G Massive MIMO-NOMA System.
Chinnadurai, Sunil; Selvaprabhu, Poongundran; Jeong, Yongchae; Jiang, Xueqin; Lee, Moon Ho
2017-09-18
In this paper, we examine the robust beamforming design to tackle the energy efficiency (EE) maximization problem in a 5G massive multiple-input multiple-output (MIMO)-non-orthogonal multiple access (NOMA) downlink system with imperfect channel state information (CSI) at the base station. A novel joint user pairing and dynamic power allocation (JUPDPA) algorithm is proposed to minimize the inter user interference and also to enhance the fairness between the users. This work assumes imperfect CSI by adding uncertainties to channel matrices with worst-case model, i.e., ellipsoidal uncertainty model (EUM). A fractional non-convex optimization problem is formulated to maximize the EE subject to the transmit power constraints and the minimum rate requirement for the cell edge user. The designed problem is difficult to solve due to its nonlinear fractional objective function. We firstly employ the properties of fractional programming to transform the non-convex problem into its equivalent parametric form. Then, an efficient iterative algorithm is proposed established on the constrained concave-convex procedure (CCCP) that solves and achieves convergence to a stationary point of the above problem. Finally, Dinkelbach's algorithm is employed to determine the maximum energy efficiency. Comprehensive numerical results illustrate that the proposed scheme attains higher worst-case energy efficiency as compared with the existing NOMA schemes and the conventional orthogonal multiple access (OMA) scheme.
Value maximizing maintenance policies under general repair
International Nuclear Information System (INIS)
Marais, Karen B.
2013-01-01
One class of maintenance optimization problems considers the notion of general repair maintenance policies where systems are repaired or replaced on failure. In each case the optimality is based on minimizing the total maintenance cost of the system. These cost-centric optimizations ignore the value dimension of maintenance and can lead to maintenance strategies that do not maximize system value. This paper applies these ideas to the general repair optimization problem using a semi-Markov decision process, discounted cash flow techniques, and dynamic programming to identify the value-optimal actions for any given time and system condition. The impact of several parameters on maintenance strategy, such as operating cost and revenue, system failure characteristics, repair and replacement costs, and the planning time horizon, is explored. This approach provides a quantitative basis on which to base maintenance strategy decisions that contribute to system value. These decisions are different from those suggested by traditional cost-based approaches. The results show (1) how the optimal action for a given time and condition changes as replacement and repair costs change, and identifies the point at which these costs become too high for profitable system operation; (2) that for shorter planning horizons it is better to repair, since there is no time to reap the benefits of increased operating profit and reliability; (3) how the value-optimal maintenance policy is affected by the system's failure characteristics, and hence whether it is worthwhile to invest in higher reliability; and (4) the impact of the repair level on the optimal maintenance policy. -- Highlights: •Provides a quantitative basis for maintenance strategy decisions that contribute to system value. •Shows how the optimal action for a given condition changes as replacement and repair costs change. •Shows how the optimal policy is affected by the system's failure characteristics. •Shows when it is
PEM-PCA: A Parallel Expectation-Maximization PCA Face Recognition Architecture
Directory of Open Access Journals (Sweden)
Kanokmon Rujirakul
2014-01-01
Full Text Available Principal component analysis or PCA has been traditionally used as one of the feature extraction techniques in face recognition systems yielding high accuracy when requiring a small number of features. However, the covariance matrix and eigenvalue decomposition stages cause high computational complexity, especially for a large database. Thus, this research presents an alternative approach utilizing an Expectation-Maximization algorithm to reduce the determinant matrix manipulation resulting in the reduction of the stages’ complexity. To improve the computational time, a novel parallel architecture was employed to utilize the benefits of parallelization of matrix computation during feature extraction and classification stages including parallel preprocessing, and their combinations, so-called a Parallel Expectation-Maximization PCA architecture. Comparing to a traditional PCA and its derivatives, the results indicate lower complexity with an insignificant difference in recognition precision leading to high speed face recognition systems, that is, the speed-up over nine and three times over PCA and Parallel PCA.
PEM-PCA: a parallel expectation-maximization PCA face recognition architecture.
Rujirakul, Kanokmon; So-In, Chakchai; Arnonkijpanich, Banchar
2014-01-01
Principal component analysis or PCA has been traditionally used as one of the feature extraction techniques in face recognition systems yielding high accuracy when requiring a small number of features. However, the covariance matrix and eigenvalue decomposition stages cause high computational complexity, especially for a large database. Thus, this research presents an alternative approach utilizing an Expectation-Maximization algorithm to reduce the determinant matrix manipulation resulting in the reduction of the stages' complexity. To improve the computational time, a novel parallel architecture was employed to utilize the benefits of parallelization of matrix computation during feature extraction and classification stages including parallel preprocessing, and their combinations, so-called a Parallel Expectation-Maximization PCA architecture. Comparing to a traditional PCA and its derivatives, the results indicate lower complexity with an insignificant difference in recognition precision leading to high speed face recognition systems, that is, the speed-up over nine and three times over PCA and Parallel PCA.
A Simulated Annealing method to solve a generalized maximal covering location problem
Directory of Open Access Journals (Sweden)
M. Saeed Jabalameli
2011-04-01
Full Text Available The maximal covering location problem (MCLP seeks to locate a predefined number of facilities in order to maximize the number of covered demand points. In a classical sense, MCLP has three main implicit assumptions: all or nothing coverage, individual coverage, and fixed coverage radius. By relaxing these assumptions, three classes of modelling formulations are extended: the gradual cover models, the cooperative cover models, and the variable radius models. In this paper, we develop a special form of MCLP which combines the characteristics of gradual cover models, cooperative cover models, and variable radius models. The proposed problem has many applications such as locating cell phone towers. The model is formulated as a mixed integer non-linear programming (MINLP. In addition, a simulated annealing algorithm is used to solve the resulted problem and the performance of the proposed method is evaluated with a set of randomly generated problems.
MAXIMIZING HYDROPOWER PRODUCTION FROM RESERVOIRS:THE CASE STUDY OF MARKABA
International Nuclear Information System (INIS)
Jaafar, H.
2014-01-01
Hydropower is a form of renewable energy that is clean and cheap. Under uncertain climatic conditions, maximization of hydropower production becomes a challenging task.Stochastic Dynamic programming (SDP) is a promising optimization algorithm that is usedfor complex non-linear reservoir operational policies and strategies.In this research, a combined simulation-SDPoptimization model isdeveloped andverified for maximizing large-scale hydropower production in a monthly time step. The model isdeveloped to generate optimal operational policies for the Qarawn reservoir in Lebanon and test these policies in real time conditions. The model isused to derive operational regimes for the Qarawn reservoirunder varying flows using transitional probability matrices. Simulating the derived rules and the generated operational policies proved effective in maximizingthe hydropower production from the Markaba power plant. The model could be successfully applied to other hydropower dams in the region. (author)
Directory of Open Access Journals (Sweden)
Xishi Tai
2012-09-01
Full Text Available A new trinuclear Cd (II complex [Cd_{3}(L_{6}(2,2-bipyridine_{3}] [L =<em> Nem>-phenylsulfonyl-L>-leucinato] has been synthesized and characterized by elemental analysis, IR and X-ray single crystal diffraction analysis. The results show that the complex belongs to the orthorhombic, space group<em> Pem>2_{1}2_{1}2_{1} with<em> aem> = 16.877(3 Å, <em>b> em>= 22.875(5 Å, <em>c em>= 29.495(6 Å, <em>α> em>= <em>β em>= <em>γ em>= 90°, <em>V> em>= 11387(4 Å^{3}, <em>Z> em>= 4, <em>D_{c}>= 1.416 μg·m^{−3}, <em>μ em>= 0.737 mm^{−1}, <em>F> em>(000 = 4992, and final <em>R>_{1} = 0.0390, <em>ωR>_{2} = 0.0989. The complex comprises two seven-coordinated Cd (II atoms, with a N_{2}O_{5} distorted pengonal bipyramidal coordination environment and a six-coordinated Cd (II atom, with a N_{2}O_{4} distorted octahedral coordination environment. The molecules form one dimensional chain structure by the interaction of bridged carboxylato groups, hydrogen bonds and p-p interaction of 2,2-bipyridine. The luminescent properties of the Cd (II complex and <em>N-Benzenesulphonyl-L>-leucine in solid and in CH_{3}OH solution also have been investigated.
Pseudo-deterministic Algorithms
Goldwasser , Shafi
2012-01-01
International audience; In this talk we describe a new type of probabilistic algorithm which we call Bellagio Algorithms: a randomized algorithm which is guaranteed to run in expected polynomial time, and to produce a correct and unique solution with high probability. These algorithms are pseudo-deterministic: they can not be distinguished from deterministic algorithms in polynomial time by a probabilistic polynomial time observer with black box access to the algorithm. We show a necessary an...
Todor, Nicolae; Todor, Irina; Săplăcan, Gavril
2014-01-01
The linear combination of variables is an attractive method in many medical analyses targeting a score to classify patients. In the case of ROC curves the most popular problem is to identify the linear combination which maximizes area under curve (AUC). This problem is complete closed when normality assumptions are met. With no assumption of normality search algorithm are avoided because it is accepted that we have to evaluate AUC n(d) times where n is the number of distinct observation and d is the number of variables. For d = 2, using particularities of AUC formula, we described an algorithm which lowered the number of evaluations of AUC from n(2) to n(n-1) + 1. For d > 2 our proposed solution is an approximate method by considering equidistant points on the unit sphere in R(d) where we evaluate AUC. The algorithms were applied to data from our lab to predict response of treatment by a set of molecular markers in cervical cancers patients. In order to evaluate the strength of our algorithms a simulation was added. In the case of no normality presented algorithms are feasible. For many variables computation time could be increased but acceptable.
POLITENESS MAXIM OF MAIN CHARACTER IN SECRET FORGIVEN
Directory of Open Access Journals (Sweden)
Sang Ayu Isnu Maharani
2017-06-01
Full Text Available Maxim of Politeness is an interesting subject to be discussed, since politeness has been criticized from our childhood. We are obliques to be polite to anyone either in speaking or in acting. Somehow we are manage to show politeness in our spoken expression though our intention might be not so polite. For example we must appriciate others opinion although we feel objection toward the opinion. In this article the analysis of politeness is based on maxim proposes by Leech. He proposed six types of politeness maxim. The discussion shows that the main character (Kristen and Kami use all types of maxim in their conversation. The most commonly used are approbation maxim and agreement maxim
Maximizing gain in high-throughput screening using conformal prediction.
Svensson, Fredrik; Afzal, Avid M; Norinder, Ulf; Bender, Andreas
2018-02-21
Iterative screening has emerged as a promising approach to increase the efficiency of screening campaigns compared to traditional high throughput approaches. By learning from a subset of the compound library, inferences on what compounds to screen next can be made by predictive models, resulting in more efficient screening. One way to evaluate screening is to consider the cost of screening compared to the gain associated with finding an active compound. In this work, we introduce a conformal predictor coupled with a gain-cost function with the aim to maximise gain in iterative screening. Using this setup we were able to show that by evaluating the predictions on the training data, very accurate predictions on what settings will produce the highest gain on the test data can be made. We evaluate the approach on 12 bioactivity datasets from PubChem training the models using 20% of the data. Depending on the settings of the gain-cost function, the settings generating the maximum gain were accurately identified in 8-10 out of the 12 datasets. Broadly, our approach can predict what strategy generates the highest gain based on the results of the cost-gain evaluation: to screen the compounds predicted to be active, to screen all the remaining data, or not to screen any additional compounds. When the algorithm indicates that the predicted active compounds should be screened, our approach also indicates what confidence level to apply in order to maximize gain. Hence, our approach facilitates decision-making and allocation of the resources where they deliver the most value by indicating in advance the likely outcome of a screening campaign.
Fast algorithm of adaptive Fourier series
Gao, You; Ku, Min; Qian, Tao
2018-05-01
Adaptive Fourier decomposition (AFD, precisely 1-D AFD or Core-AFD) was originated for the goal of positive frequency representations of signals. It achieved the goal and at the same time offered fast decompositions of signals. There then arose several types of AFDs. AFD merged with the greedy algorithm idea, and in particular, motivated the so-called pre-orthogonal greedy algorithm (Pre-OGA) that was proven to be the most efficient greedy algorithm. The cost of the advantages of the AFD type decompositions is, however, the high computational complexity due to the involvement of maximal selections of the dictionary parameters. The present paper offers one formulation of the 1-D AFD algorithm by building the FFT algorithm into it. Accordingly, the algorithm complexity is reduced, from the original $\\mathcal{O}(M N^2)$ to $\\mathcal{O}(M N\\log_2 N)$, where $N$ denotes the number of the discretization points on the unit circle and $M$ denotes the number of points in $[0,1)$. This greatly enhances the applicability of AFD. Experiments are carried out to show the high efficiency of the proposed algorithm.
Maximizers versus satisficers: Decision-making styles, competence, and outcomes
Andrew M. Parker; Wändi Bruine de Bruin; Baruch Fischhoff
2007-01-01
Our previous research suggests that people reporting a stronger desire to maximize obtain worse life outcomes (Bruine de Bruin et al., 2007). Here, we examine whether this finding may be explained by the decision-making styles of self-reported maximizers. Expanding on Schwartz et al.\\ (2002), we find that self-reported maximizers are more likely to show problematic decision-making styles, as evidenced by self-reports of less behavioral coping, greater dependence on others when making decision...
Elsheikh, A. H.; Wheeler, M. F.; Hoteit, Ibrahim
2013-01-01
Calibration of subsurface flow models is an essential step for managing ground water aquifers, designing of contaminant remediation plans, and maximizing recovery from hydrocarbon reservoirs. We investigate an efficient sampling algorithm known
International Nuclear Information System (INIS)
Wetterich, C.
1999-01-01
The naturalness of maximal mixing between myon- and tau-neutrinos is investigated. A spontaneously broken nonabelian generation symmetry can explain a small parameter which governs the deviation from maximal mixing. In many cases all three neutrino masses are almost degenerate. Maximal ν μ -ν τ -mixing suggests that the leading contribution to the light neutrino masses arises from the expectation value of a heavy weak triplet rather than from the seesaw mechanism. In this scenario the deviation from maximal mixing is predicted to be less than about 1%. (Copyright (c) 1999 Elsevier Science B.V., Amsterdam. All rights reserved.)
On the way towards a generalized entropy maximization procedure
International Nuclear Information System (INIS)
Bagci, G. Baris; Tirnakli, Ugur
2009-01-01
We propose a generalized entropy maximization procedure, which takes into account the generalized averaging procedures and information gain definitions underlying the generalized entropies. This novel generalized procedure is then applied to Renyi and Tsallis entropies. The generalized entropy maximization procedure for Renyi entropies results in the exponential stationary distribution asymptotically for q element of (0,1] in contrast to the stationary distribution of the inverse power law obtained through the ordinary entropy maximization procedure. Another result of the generalized entropy maximization procedure is that one can naturally obtain all the possible stationary distributions associated with the Tsallis entropies by employing either ordinary or q-generalized Fourier transforms in the averaging procedure.
Violating Bell inequalities maximally for two d-dimensional systems
International Nuclear Information System (INIS)
Chen Jingling; Wu Chunfeng; Oh, C. H.; Kwek, L. C.; Ge Molin
2006-01-01
We show the maximal violation of Bell inequalities for two d-dimensional systems by using the method of the Bell operator. The maximal violation corresponds to the maximal eigenvalue of the Bell operator matrix. The eigenvectors corresponding to these eigenvalues are described by asymmetric entangled states. We estimate the maximum value of the eigenvalue for large dimension. A family of elegant entangled states |Ψ> app that violate Bell inequality more strongly than the maximally entangled state but are somewhat close to these eigenvectors is presented. These approximate states can potentially be useful for quantum cryptography as well as many other important fields of quantum information
Evaluation of anti-hyperglycemic effect of Actinidia kolomikta (Maxim. etRur.) Maxim. root extract.
Hu, Xuansheng; Cheng, Delin; Wang, Linbo; Li, Shuhong; Wang, Yuepeng; Li, Kejuan; Yang, Yingnan; Zhang, Zhenya
2015-05-01
This study aimed to evaluate the anti-hyperglycemic effect of ethanol extract from Actinidia kolomikta (Maxim. etRur.) Maxim. root (AKE).An in vitro evaluation was performed by using rat intestinal α-glucosidase (maltase and sucrase), the key enzymes linked with type 2 diabetes. And an in vivo evaluation was also performed by loading maltose, sucrose, glucose to normal rats. As a result, AKE showed concentration-dependent inhibition effects on rat intestinal maltase and rat intestinal sucrase with IC(50) values of 1.83 and 1.03mg/mL, respectively. In normal rats, after loaded with maltose, sucrose and glucose, administration of AKE significantly reduced postprandial hyperglycemia, which is similar to acarbose used as an anti-diabetic drug. High contents of total phenolics (80.49 ± 0.05mg GAE/g extract) and total flavonoids (430.69 ± 0.91mg RE/g extract) were detected in AKE. In conclusion, AKE possessed anti-hyperglycemic effects and the possible mechanisms were associated with its inhibition on α-glucosidase and the improvement on insulin release and/or insulin sensitivity as well. The anti-hyperglycemic activity possessed by AKE maybe attributable to its high contents of phenolic and flavonoid compounds.
Alternative approaches to maximally supersymmetric field theories
International Nuclear Information System (INIS)
Broedel, Johannes
2010-01-01
The central objective of this work is the exploration and application of alternative possibilities to describe maximally supersymmetric field theories in four dimensions: N=4 super Yang-Mills theory and N=8 supergravity. While twistor string theory has been proven very useful in the context of N=4 SYM, no analogous formulation for N=8 supergravity is available. In addition to the part describing N=4 SYM theory, twistor string theory contains vertex operators corresponding to the states of N=4 conformal supergravity. Those vertex operators have to be altered in order to describe (non-conformal) Einstein supergravity. A modified version of the known open twistor string theory, including a term which breaks the conformal symmetry for the gravitational vertex operators, has been proposed recently. In a first part of the thesis structural aspects and consistency of the modified theory are discussed. Unfortunately, the majority of amplitudes can not be constructed, which can be traced back to the fact that the dimension of the moduli space of algebraic curves in twistor space is reduced in an inconsistent manner. The issue of a possible finiteness of N=8 supergravity is closely related to the question of the existence of valid counterterms in the perturbation expansion of the theory. In particular, the coefficient in front of the so-called R 4 counterterm candidate has been shown to vanish by explicit calculation. This behavior points into the direction of a symmetry not taken into account, for which the hidden on-shell E 7(7) symmetry is the prime candidate. The validity of the so-called double-soft scalar limit relation is a necessary condition for a theory exhibiting E 7(7) symmetry. By calculating the double-soft scalar limit for amplitudes derived from an N=8 supergravity action modified by an additional R 4 counterterm, one can test for possible constraints originating in the E 7(7) symmetry. In a second part of the thesis, the appropriate amplitudes are calculated
Comparison of turbulence mitigation algorithms
Kozacik, Stephen T.; Paolini, Aaron; Sherman, Ariel; Bonnett, James; Kelmelis, Eric
2017-07-01
When capturing imagery over long distances, atmospheric turbulence often degrades the data, especially when observation paths are close to the ground or in hot environments. These issues manifest as time-varying scintillation and warping effects that decrease the effective resolution of the sensor and reduce actionable intelligence. In recent years, several image processing approaches to turbulence mitigation have shown promise. Each of these algorithms has different computational requirements, usability demands, and degrees of independence from camera sensors. They also produce different degrees of enhancement when applied to turbulent imagery. Additionally, some of these algorithms are applicable to real-time operational scenarios while others may only be suitable for postprocessing workflows. EM Photonics has been developing image-processing-based turbulence mitigation technology since 2005. We will compare techniques from the literature with our commercially available, real-time, GPU-accelerated turbulence mitigation software. These comparisons will be made using real (not synthetic), experimentally obtained data for a variety of conditions, including varying optical hardware, imaging range, subjects, and turbulence conditions. Comparison metrics will include image quality, video latency, computational complexity, and potential for real-time operation. Additionally, we will present a technique for quantitatively comparing turbulence mitigation algorithms using real images of radial resolution targets.
Hamiltonian Algorithm Sound Synthesis
大矢, 健一
2013-01-01
Hamiltonian Algorithm (HA) is an algorithm for searching solutions is optimization problems. This paper introduces a sound synthesis technique using Hamiltonian Algorithm and shows a simple example. "Hamiltonian Algorithm Sound Synthesis" uses phase transition effect in HA. Because of this transition effect, totally new waveforms are produced.
Progressive geometric algorithms
Alewijnse, S.P.A.; Bagautdinov, T.M.; de Berg, M.T.; Bouts, Q.W.; ten Brink, Alex P.; Buchin, K.A.; Westenberg, M.A.
2015-01-01
Progressive algorithms are algorithms that, on the way to computing a complete solution to the problem at hand, output intermediate solutions that approximate the complete solution increasingly well. We present a framework for analyzing such algorithms, and develop efficient progressive algorithms
Progressive geometric algorithms
Alewijnse, S.P.A.; Bagautdinov, T.M.; Berg, de M.T.; Bouts, Q.W.; Brink, ten A.P.; Buchin, K.; Westenberg, M.A.
2014-01-01
Progressive algorithms are algorithms that, on the way to computing a complete solution to the problem at hand, output intermediate solutions that approximate the complete solution increasingly well. We present a framework for analyzing such algorithms, and develop efficient progressive algorithms
COMPARISON OF DIFFERENT SEGMENTATION ALGORITHMS FOR DERMOSCOPIC IMAGES
Directory of Open Access Journals (Sweden)
A.A. Haseena Thasneem
2015-05-01
Full Text Available This paper compares different algorithms for the segmentation of skin lesions in dermoscopic images. The basic segmentation algorithms compared are Thresholding techniques (Global and Adaptive, Region based techniques (K-means, Fuzzy C means, Expectation Maximization and Statistical Region Merging, Contour models (Active Contour Model and Chan - Vese Model and Spectral Clustering. Accuracy, sensitivity, specificity, Border error, Hammoude distance, Hausdorff distance, MSE, PSNR and elapsed time metrices were used to evaluate various segmentation techniques.
Algorithm comparison for schedule optimization in MR fingerprinting.
Cohen, Ouri; Rosen, Matthew S
2017-09-01
In MR Fingerprinting, the flip angles and repetition times are chosen according to a pseudorandom schedule. In previous work, we have shown that maximizing the discrimination between different tissue types by optimizing the acquisition schedule allows reductions in the number of measurements required. The ideal optimization algorithm for this application remains unknown, however. In this work we examine several different optimization algorithms to determine the one best suited for optimizing MR Fingerprinting acquisition schedules. Copyright © 2017 Elsevier Inc. All rights reserved.
A Comparison of Heuristics with Modularity Maximization Objective using Biological Data Sets
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Pirim Harun
2016-01-01
Full Text Available Finding groups of objects exhibiting similar patterns is an important data analytics task. Many disciplines have their own terminologies such as cluster, group, clique, community etc. defining the similar objects in a set. Adopting the term community, many exact and heuristic algorithms are developed to find the communities of interest in available data sets. Here, three heuristic algorithms to find communities are compared using five gene expression data sets. The heuristics have a common objective function of maximizing the modularity that is a quality measure of a partition and a reflection of objects’ relevance in communities. Partitions generated by the heuristics are compared with the real ones using the adjusted rand index, one of the most commonly used external validation measures. The paper discusses the results of the partitions on the mentioned biological data sets.
DEFF Research Database (Denmark)
Bucher, Taina
2017-01-01
the notion of the algorithmic imaginary. It is argued that the algorithmic imaginary – ways of thinking about what algorithms are, what they should be and how they function – is not just productive of different moods and sensations but plays a generative role in moulding the Facebook algorithm itself...... of algorithms affect people's use of these platforms, if at all? To help answer these questions, this article examines people's personal stories about the Facebook algorithm through tweets and interviews with 25 ordinary users. To understand the spaces where people and algorithms meet, this article develops...
Energy Technology Data Exchange (ETDEWEB)
Geist, G.A. [Oak Ridge National Lab., TN (United States). Computer Science and Mathematics Div.; Howell, G.W. [Florida Inst. of Tech., Melbourne, FL (United States). Dept. of Applied Mathematics; Watkins, D.S. [Washington State Univ., Pullman, WA (United States). Dept. of Pure and Applied Mathematics
1997-11-01
The BR algorithm, a new method for calculating the eigenvalues of an upper Hessenberg matrix, is introduced. It is a bulge-chasing algorithm like the QR algorithm, but, unlike the QR algorithm, it is well adapted to computing the eigenvalues of the narrowband, nearly tridiagonal matrices generated by the look-ahead Lanczos process. This paper describes the BR algorithm and gives numerical evidence that it works well in conjunction with the Lanczos process. On the biggest problems run so far, the BR algorithm beats the QR algorithm by a factor of 30--60 in computing time and a factor of over 100 in matrix storage space.
A new hybrid metaheuristic algorithm for wind farm micrositing
International Nuclear Information System (INIS)
Massan, S.U.R.; Wagan, A.I.; Shaikh, M.M.
2017-01-01
This work focuses on proposing a new algorithm, referred as HMA (Hybrid Metaheuristic Algorithm) for the solution of the WTO (Wind Turbine Optimization) problem. It is well documented that turbines located behind one another face a power loss due to the obstruction of the wind due to wake loss. It is required to reduce this wake loss by the effective placement of turbines using a new HMA. This HMA is derived from the two basic algorithms i.e. DEA (Differential Evolution Algorithm) and the FA (Firefly Algorithm). The function of optimization is undertaken on the N.O. Jensen model. The blending of DEA and FA into HMA are discussed and the new algorithm HMA is implemented maximize power and minimize the cost in a WTO problem. The results by HMA have been compared with GA (Genetic Algorithm) used in some previous studies. The successfully calculated total power produced and cost per unit turbine for a wind farm by using HMA and its comparison with past approaches using single algorithms have shown that there is a significant advantage of using the HMA as compared to the use of single algorithms. The first time implementation of a new algorithm by blending two single algorithms is a significant step towards learning the behavior of algorithms and their added advantages by using them together. (author)
A New Hybrid Metaheuristic Algorithm for Wind Farm Micrositing
Directory of Open Access Journals (Sweden)
SHAFIQ-UR-REHMAN MASSAN
2017-07-01
Full Text Available This work focuses on proposing a new algorithm, referred as HMA (Hybrid Metaheuristic Algorithm for the solution of the WTO (Wind Turbine Optimization problem. It is well documented that turbines located behind one another face a power loss due to the obstruction of the wind due to wake loss. It is required to reduce this wake loss by the effective placement of turbines using a new HMA. This HMA is derived from the two basic algorithms i.e. DEA (Differential Evolution Algorithm and the FA (Firefly Algorithm. The function of optimization is undertaken on the N.O. Jensen model. The blending of DEA and FA into HMA are discussed and the new algorithm HMA is implemented maximize power and minimize the cost in a WTO problem. The results by HMA have been compared with GA (Genetic Algorithm used in some previous studies. The successfully calculated total power produced and cost per unit turbine for a wind farm by using HMA and its comparison with past approaches using single algorithms have shown that there is a significant advantage of using the HMA as compared to the use of single algorithms. The first time implementation of a new algorithm by blending two single algorithms is a significant step towards learning the behavior of algorithms and their added advantages by using them together.
Kinetic theory in maximal-acceleration invariant phase space
International Nuclear Information System (INIS)
Brandt, H.E.
1989-01-01
A vanishing directional derivative of a scalar field along particle trajectories in maximal acceleration invariant phase space is identical in form to the ordinary covariant Vlasov equation in curved spacetime in the presence of both gravitational and nongravitational forces. A natural foundation is thereby provided for a covariant kinetic theory of particles in maximal-acceleration invariant phase space. (orig.)
IIB solutions with N>28 Killing spinors are maximally supersymmetric
International Nuclear Information System (INIS)
Gran, U.; Gutowski, J.; Papadopoulos, G.; Roest, D.
2007-01-01
We show that all IIB supergravity backgrounds which admit more than 28 Killing spinors are maximally supersymmetric. In particular, we find that for all N>28 backgrounds the supercovariant curvature vanishes, and that the quotients of maximally supersymmetric backgrounds either preserve all 32 or N<29 supersymmetries
Muscle mitochondrial capacity exceeds maximal oxygen delivery in humans
DEFF Research Database (Denmark)
Boushel, Robert Christopher; Gnaiger, Erich; Calbet, Jose A L
2011-01-01
Across a wide range of species and body mass a close matching exists between maximal conductive oxygen delivery and mitochondrial respiratory rate. In this study we investigated in humans how closely in-vivo maximal oxygen consumption (VO(2) max) is matched to state 3 muscle mitochondrial respira...
Pace's Maxims for Homegrown Library Projects. Coming Full Circle
Pace, Andrew K.
2005-01-01
This article discusses six maxims by which to run library automation. The following maxims are discussed: (1) Solve only known problems; (2) Avoid changing data to fix display problems; (3) Aut viam inveniam aut faciam; (4) If you cannot make it yourself, buy something; (5) Kill the alligator closest to the boat; and (6) Just because yours is…
Algorithm for Controlling a Centrifugal Compressor
Benedict, Scott M.
2004-01-01
An algorithm has been developed for controlling a centrifugal compressor that serves as the prime mover in a heatpump system. Experimental studies have shown that the operating conditions for maximum compressor efficiency are close to the boundary beyond which surge occurs. Compressor surge is a destructive condition in which there are instantaneous reversals of flow associated with a high outlet-to-inlet pressure differential. For a given cooling load, the algorithm sets the compressor speed at the lowest possible value while adjusting the inlet guide vane angle and diffuser vane angle to maximize efficiency, subject to an overriding requirement to prevent surge. The onset of surge is detected via the onset of oscillations of the electric current supplied to the compressor motor, associated with surge-induced oscillations of the torque exerted by and on the compressor rotor. The algorithm can be implemented in any of several computer languages.
Algorithmically specialized parallel computers
Snyder, Lawrence; Gannon, Dennis B
1985-01-01
Algorithmically Specialized Parallel Computers focuses on the concept and characteristics of an algorithmically specialized computer.This book discusses the algorithmically specialized computers, algorithmic specialization using VLSI, and innovative architectures. The architectures and algorithms for digital signal, speech, and image processing and specialized architectures for numerical computations are also elaborated. Other topics include the model for analyzing generalized inter-processor, pipelined architecture for search tree maintenance, and specialized computer organization for raster
Teaching learning based optimization algorithm and its engineering applications
Rao, R Venkata
2016-01-01
Describing a new optimization algorithm, the “Teaching-Learning-Based Optimization (TLBO),” in a clear and lucid style, this book maximizes reader insights into how the TLBO algorithm can be used to solve continuous and discrete optimization problems involving single or multiple objectives. As the algorithm operates on the principle of teaching and learning, where teachers influence the quality of learners’ results, the elitist version of TLBO algorithm (ETLBO) is described along with applications of the TLBO algorithm in the fields of electrical engineering, mechanical design, thermal engineering, manufacturing engineering, civil engineering, structural engineering, computer engineering, electronics engineering, physics and biotechnology. The book offers a valuable resource for scientists, engineers and practitioners involved in the development and usage of advanced optimization algorithms.
Xi, Songnan; Zoltowski, Michael D.
2008-04-01
Multiuser multiple-input multiple-output (MIMO) systems are considered in this paper. We continue our research on uplink transmit beamforming design for multiple users under the assumption that the full multiuser channel state information, which is the collection of the channel state information between each of the users and the base station, is known not only to the receiver but also to all the transmitters. We propose an algorithm for designing optimal beamforming weights in terms of maximizing the signal-to-interference-plus-noise ratio (SINR). Through statistical modeling, we decouple the original mathematically intractable optimization problem and achieved a closed-form solution. As in our previous work, the minimum mean-squared error (MMSE) receiver with successive interference cancellation (SIC) is adopted for multiuser detection. The proposed scheme is compared with an existing jointly optimized transceiver design, referred to as the joint transceiver in this paper, and our previously proposed eigen-beamforming algorithm. Simulation results demonstrate that our algorithm, with much less computational burden, accomplishes almost the same performance as the joint transceiver for spatially independent MIMO channel and even better performance for spatially correlated MIMO channels. And it always works better than our previously proposed eigen beamforming algorithm.
Blind Multiuser Detection by Kurtosis Maximization for Asynchronous Multirate DS/CDMA Systems
Directory of Open Access Journals (Sweden)
Peng Chun-Hsien
2006-01-01
Full Text Available Chi et al. proposed a fast kurtosis maximization algorithm (FKMA for blind equalization/deconvolution of multiple-input multiple-output (MIMO linear time-invariant systems. This algorithm has been applied to blind multiuser detection of single-rate direct-sequence/code-division multiple-access (DS/CDMA systems and blind source separation (or independent component analysis. In this paper, the FKMA is further applied to blind multiuser detection for multirate DS/CDMA systems. The ideas are to properly formulate discrete-time MIMO signal models by converting real multirate users into single-rate virtual users, followed by the use of FKMA for extraction of virtual users' data sequences associated with the desired user, and recovery of the data sequence of the desired user from estimated virtual users' data sequences. Assuming that all the users' spreading sequences are given a priori, two multirate blind multiuser detection algorithms (with either a single receive antenna or multiple antennas, which also enjoy the merits of superexponential convergence rate and guaranteed convergence of the FKMA, are proposed in the paper, one based on a convolutional MIMO signal model and the other based on an instantaneous MIMO signal model. Some simulation results are then presented to demonstrate their effectiveness and to provide a performance comparison with some existing algorithms.
Coverage maximization under resource constraints using a nonuniform proliferating random walk.
Saha, Sudipta; Ganguly, Niloy
2013-02-01
Information management services on networks, such as search and dissemination, play a key role in any large-scale distributed system. One of the most desirable features of these services is the maximization of the coverage, i.e., the number of distinctly visited nodes under constraints of network resources as well as time. However, redundant visits of nodes by different message packets (modeled, e.g., as walkers) initiated by the underlying algorithms for these services cause wastage of network resources. In this work, using results from analytical studies done in the past on a K-random-walk-based algorithm, we identify that redundancy quickly increases with an increase in the density of the walkers. Based on this postulate, we design a very simple distributed algorithm which dynamically estimates the density of the walkers and thereby carefully proliferates walkers in sparse regions. We use extensive computer simulations to test our algorithm in various kinds of network topologies whereby we find it to be performing particularly well in networks that are highly clustered as well as sparse.
Survival associated pathway identification with group Lp penalized global AUC maximization
Directory of Open Access Journals (Sweden)
Liu Zhenqiu
2010-08-01
Full Text Available Abstract It has been demonstrated that genes in a cell do not act independently. They interact with one another to complete certain biological processes or to implement certain molecular functions. How to incorporate biological pathways or functional groups into the model and identify survival associated gene pathways is still a challenging problem. In this paper, we propose a novel iterative gradient based method for survival analysis with group Lp penalized global AUC summary maximization. Unlike LASSO, Lp (p 1. We first extend Lp for individual gene identification to group Lp penalty for pathway selection, and then develop a novel iterative gradient algorithm for penalized global AUC summary maximization (IGGAUCS. This method incorporates the genetic pathways into global AUC summary maximization and identifies survival associated pathways instead of individual genes. The tuning parameters are determined using 10-fold cross validation with training data only. The prediction performance is evaluated using test data. We apply the proposed method to survival outcome analysis with gene expression profile and identify multiple pathways simultaneously. Experimental results with simulation and gene expression data demonstrate that the proposed procedures can be used for identifying important biological pathways that are related to survival phenotype and for building a parsimonious model for predicting the survival times.
Directory of Open Access Journals (Sweden)
Yuhang Wu
2016-01-01
Full Text Available This paper focuses on the attention allocation problem (AAP in modeling multioperator multi-UAV (MOMU, with the operator model and task properties taken into consideration. The model of MOMU operator AAP based on maximizing the global reward is established and used to allocate tasks to all operators as well as set work time and rest time to each task simultaneously for operators. The proposed model is validated in Matlab simulation environment, using the immune algorithm and dynamic programming algorithm to evaluate the performance of the model in terms of the reward value with regard to the work time, rest time, and task allocation. The result shows that the total reward of the proposed model is larger than the one obtained from previously published methods using local maximization and the total reward of our method has an exponent-like relation with the task arrival rate. The proposed model can improve the operators’ task processing efficiency in the MOMU command and control scenarios.
Constructing Optimal Coarse-Grained Sites of Huge Biomolecules by Fluctuation Maximization.
Li, Min; Zhang, John Zenghui; Xia, Fei
2016-04-12
Coarse-grained (CG) models are valuable tools for the study of functions of large biomolecules on large length and time scales. The definition of CG representations for huge biomolecules is always a formidable challenge. In this work, we propose a new method called fluctuation maximization coarse-graining (FM-CG) to construct the CG sites of biomolecules. The defined residual in FM-CG converges to a maximal value as the number of CG sites increases, allowing an optimal CG model to be rigorously defined on the basis of the maximum. More importantly, we developed a robust algorithm called stepwise local iterative optimization (SLIO) to accelerate the process of coarse-graining large biomolecules. By means of the efficient SLIO algorithm, the computational cost of coarse-graining large biomolecules is reduced to within the time scale of seconds, which is far lower than that of conventional simulated annealing. The coarse-graining of two huge systems, chaperonin GroEL and lengsin, indicates that our new methods can coarse-grain huge biomolecular systems with up to 10,000 residues within the time scale of minutes. The further parametrization of CG sites derived from FM-CG allows us to construct the corresponding CG models for studies of the functions of huge biomolecular systems.
AC-600 reactor reloading pattern optimization by using genetic algorithms
International Nuclear Information System (INIS)
Wu Hongchun; Xie Zhongsheng; Yao Dong; Li Dongsheng; Zhang Zongyao
2000-01-01
The use of genetic algorithms to optimize reloading pattern of the nuclear power plant reactor is proposed. And a new encoding and translating method is given. Optimization results of minimizing core power peak and maximizing cycle length for both low-leakage and out-in loading pattern of AC-600 reactor are obtained
Clustering algorithms for Stokes space modulation format recognition
DEFF Research Database (Denmark)
Boada, Ricard; Borkowski, Robert; Tafur Monroy, Idelfonso
2015-01-01
influences the performance of the detection process, particularly at low signal-to-noise ratios. This paper reports on an extensive study of six different clustering algorithms: k-means, expectation maximization, density-based DBSCAN and OPTICS, spectral clustering and maximum likelihood clustering, used...
Inquiry in bibliography some of the bustan`s maxim
Directory of Open Access Journals (Sweden)
sajjad rahmatian
2016-12-01
Full Text Available Sa`di is on of those poets who`s has placed a special position to preaching and guiding the people and among his works, allocated throughout the text of bustan to advice and maxim on legal and ethical various subjects. Surely, sa`di on the way of to compose this work and expression of its moral point, direct or indirect have been affected by some previous sources and possibly using their content. The main purpose of this article is that the pay review of basis and sources of bustan`s maxims and show that sa`di when expression the maxims of this work has been affected by which of the texts and works. For this purpose is tried to with search and research on the resources that have been allocated more or less to the aphorisms, to discover and extract traces of influence sa`di from their moral and didactic content. From the most important the finding of this study can be mentioned that indirect effect of some pahlavi books of maxim (like maxims of azarbad marespandan and bozorgmehr book of maxim and also noted sa`di directly influenced of moral and ethical works of poets and writers before him, and of this, sa`di`s influence from abo- shakur balkhi maxims, ferdowsi and keikavus is remarkable and noteworthy.
Can monkeys make investments based on maximized pay-off?
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Sophie Steelandt
2011-03-01
Full Text Available Animals can maximize benefits but it is not known if they adjust their investment according to expected pay-offs. We investigated whether monkeys can use different investment strategies in an exchange task. We tested eight capuchin monkeys (Cebus apella and thirteen macaques (Macaca fascicularis, Macaca tonkeana in an experiment where they could adapt their investment to the food amounts proposed by two different experimenters. One, the doubling partner, returned a reward that was twice the amount given by the subject, whereas the other, the fixed partner, always returned a constant amount regardless of the amount given. To maximize pay-offs, subjects should invest a maximal amount with the first partner and a minimal amount with the second. When tested with the fixed partner only, one third of monkeys learned to remove a maximal amount of food for immediate consumption before investing a minimal one. With both partners, most subjects failed to maximize pay-offs by using different decision rules with each partner' quality. A single Tonkean macaque succeeded in investing a maximal amount to one experimenter and a minimal amount to the other. The fact that only one of over 21 subjects learned to maximize benefits in adapting investment according to experimenters' quality indicates that such a task is difficult for monkeys, albeit not impossible.
Quantum Computation and Algorithms
International Nuclear Information System (INIS)
Biham, O.; Biron, D.; Biham, E.; Grassi, M.; Lidar, D.A.
1999-01-01
It is now firmly established that quantum algorithms provide a substantial speedup over classical algorithms for a variety of problems, including the factorization of large numbers and the search for a marked element in an unsorted database. In this talk I will review the principles of quantum algorithms, the basic quantum gates and their operation. The combination of superposition and interference, that makes these algorithms efficient, will be discussed. In particular, Grover's search algorithm will be presented as an example. I will show that the time evolution of the amplitudes in Grover's algorithm can be found exactly using recursion equations, for any initial amplitude distribution
Directory of Open Access Journals (Sweden)
Chad H. Stahl
2012-05-01
Full Text Available Satellite cell activity is necessary for postnatal skeletal muscle growth. Severe phosphate (PO_{4} deficiency can alter satellite cell activity, however the role of neonatal PO_{4} nutrition on satellite cell biology remains obscure. Twenty-one piglets (1 day of age, 1.8 ± 0.2 kg BW were pair-fed liquid diets that were either PO_{4} adequate (0.9% total P, supra-adequate (1.2% total P in PO_{4} requirement or deficient (0.7% total P in PO_{4} content for 12 days. Body weight was recorded daily and blood samples collected every 6 days. At day 12, pigs were orally dosed with BrdU and 12 h later, satellite cells were isolated. Satellite cells were also cultured <em>in vitroem> for 7 days to determine if PO_{4} nutrition alters their ability to proceed through their myogenic lineage. Dietary PO_{4} deficiency resulted in reduced (<em>P> < 0.05 sera PO_{4} and parathyroid hormone (PTH concentrations, while supra-adequate dietary PO_{4} improved (<em>P> < 0.05 feed conversion efficiency as compared to the PO_{4} adequate group. <em>In vivoem> satellite cell proliferation was reduced (<em>P> < 0.05 among the PO_{4} deficient pigs, and these cells had altered <em>in vitroem> expression of markers of myogenic progression. Further work to better understand early nutritional programming of satellite cells and the potential benefits of emphasizing early PO_{4} nutrition for future lean growth potential is warranted.
Goharian, E.; Gailey, R.; Maples, S.; Azizipour, M.; Sandoval Solis, S.; Fogg, G. E.
2017-12-01
The drought incidents and growing water scarcity in California have a profound effect on human, agricultural, and environmental water needs. California experienced multi-year droughts, which have caused groundwater overdraft and dropping groundwater levels, and dwindling of major reservoirs. These concerns call for a stringent evaluation of future water resources sustainability and security in the state. To answer to this call, Sustainable Groundwater Management Act (SGMA) was passed in 2014 to promise a sustainable groundwater management in California by 2042. SGMA refers to managed aquifer recharge (MAR) as a key management option, especially in areas with high variation in water availability intra- and inter-annually, to secure the refill of underground water storage and return of groundwater quality to a desirable condition. The hybrid optimization of an integrated water resources system provides an opportunity to adapt surface reservoir operations for enhancement in groundwater recharge. Here, to re-operate Folsom Reservoir, objectives are maximizing the storage in the whole American-Cosumnes watershed and maximizing hydropower generation from Folsom Reservoir. While a linear programing (LP) module tends to maximize the total groundwater recharge by distributing and spreading water over suitable lands in basin, a genetic based algorithm, Non-dominated Sorting Genetic Algorithm II (NSGA-II), layer above it controls releases from the reservoir to secure the hydropower generation, carry-over storage in reservoir, available water for replenishment, and downstream water requirements. The preliminary results show additional releases from the reservoir for groundwater recharge during high flow seasons. Moreover, tradeoffs between the objectives describe that new operation performs satisfactorily to increase the storage in the basin, with nonsignificant effects on other objectives.
Profit maximization with customer satisfaction control for electric vehicle charging in smart grids
Directory of Open Access Journals (Sweden)
Edwin Collado
2017-05-01
Full Text Available As the market of electric vehicles is gaining popularity, large-scale commercialized or privately-operated charging stations are expected to play a key role as a technology enabler. In this paper, we study the problem of charging electric vehicles at stations with limited charging machines and power resources. The purpose of this study is to develop a novel profit maximization framework for station operation in both offline and online charging scenarios, under certain customer satisfaction constraints. The main goal is to maximize the profit obtained by the station owner and provide a satisfactory charging service to the customers. The framework includes not only the vehicle scheduling and charging power control, but also the managing of user satisfaction factors, which are defined as the percentages of finished charging targets. The profit maximization problem is proved to be NPcomplete in both scenarios (NP refers to “nondeterministic polynomial time”, for which two-stage charging strategies are proposed to obtain efficient suboptimal solutions. Competitive analysis is also provided to analyze the performance of the proposed online two-stage charging algorithm against the offline counterpart under non-congested and congested charging scenarios. Finally, the simulation results show that the proposed two-stage charging strategies achieve performance close to that with exhaustive search. Also, the proposed algorithms provide remarkable performance gains compared to the other conventional charging strategies with respect to not only the unified profit, but also other practical interests, such as the computational time, the user satisfaction factor, the power consumption, and the competitive ratio.
Gravitational collapse of charged dust shell and maximal slicing condition
International Nuclear Information System (INIS)
Maeda, Keiichi
1980-01-01
The maximal slicing condition is a good time coordinate condition qualitatively when pursuing the gravitational collapse by the numerical calculation. The analytic solution of the gravitational collapse under the maximal slicing condition is given in the case of a spherical charged dust shell and the behavior of time slices with this coordinate condition is investigated. It is concluded that under the maximal slicing condition we can pursue the gravitational collapse until the radius of the shell decreases to about 0.7 x (the radius of the event horizon). (author)
Optimal quantum error correcting codes from absolutely maximally entangled states
Raissi, Zahra; Gogolin, Christian; Riera, Arnau; Acín, Antonio
2018-02-01
Absolutely maximally entangled (AME) states are pure multi-partite generalizations of the bipartite maximally entangled states with the property that all reduced states of at most half the system size are in the maximally mixed state. AME states are of interest for multipartite teleportation and quantum secret sharing and have recently found new applications in the context of high-energy physics in toy models realizing the AdS/CFT-correspondence. We work out in detail the connection between AME states of minimal support and classical maximum distance separable (MDS) error correcting codes and, in particular, provide explicit closed form expressions for AME states of n parties with local dimension \
Breakdown of maximality conjecture in continuous phase transitions
International Nuclear Information System (INIS)
Mukamel, D.; Jaric, M.V.
1983-04-01
A Landau-Ginzburg-Wilson model associated with a single irreducible representation which exhibits an ordered phase whose symmetry group is not a maximal isotropy subgroup of the symmetry group of the disordered phase is constructed. This example disproves the maximality conjecture suggested in numerous previous studies. Below the (continuous) transition, the order parameter points along a direction which varies with the temperature and with the other parameters which define the model. An extension of the maximality conjecture to reducible representations was postulated in the context of Higgs symmetry breaking mechanism. Our model can also be extended to provide a counter example in these cases. (author)
Constituents from <em>Vigna em>vexillata> and Their Anti-Inflammatory Activity
Directory of Open Access Journals (Sweden)
Guo-Feng Chen
2012-08-01
Full Text Available The seeds of <em>Vigna em>genus are important food resources and there have already been many reports regarding their bioactivities. In our preliminary bioassay, the chloroform layer of methanol extracts of<em> V. vexillata em>demonstrated significant anti-inflammatory bioactivity. Therefore, the present research is aimed to purify and identify the anti-inflammatory principles of <em>V. vexillataem>. One new sterol (1 and two new isoflavones (2,3 were reported from the natural sources for the first time and their chemical structures were determined by the spectroscopic and mass spectrometric analyses. In addition, 37 known compounds were identified by comparison of their physical and spectroscopic data with those reported in the literature. Among the isolates, daidzein (23, abscisic acid (25, and quercetin (40 displayed the most significant inhibition of superoxide anion generation and elastase release.
International Nuclear Information System (INIS)
Chandrasekharan, Shailesh
2000-01-01
Cluster algorithms have been recently used to eliminate sign problems that plague Monte-Carlo methods in a variety of systems. In particular such algorithms can also be used to solve sign problems associated with the permutation of fermion world lines. This solution leads to the possibility of designing fermion cluster algorithms in certain cases. Using the example of free non-relativistic fermions we discuss the ideas underlying the algorithm
Autonomous Star Tracker Algorithms
DEFF Research Database (Denmark)
Betto, Maurizio; Jørgensen, John Leif; Kilsgaard, Søren
1998-01-01
Proposal, in response to an ESA R.f.P., to design algorithms for autonomous star tracker operations.The proposal also included the development of a star tracker breadboard to test the algorithms performances.......Proposal, in response to an ESA R.f.P., to design algorithms for autonomous star tracker operations.The proposal also included the development of a star tracker breadboard to test the algorithms performances....
Directory of Open Access Journals (Sweden)
Hugo Andrés Ruiz
2012-06-01
Full Text Available En este artículo se presenta un método para resolver el problema de estimación de estado en sistemas eléctricos usando optimización combinatoria. Su objetivo es el estudio de mediciones con errores de difícil detección, que afectan el desempeño y calidad de los resultados cuando se emplea un estimador de estado clásico. Dada su complejidad matemática, se deducen indicadores de sensibilidad de la teoría de puntos de apalancamiento que se usan en el algoritmo de optimización de Chu-Beasley, con el fin de disminuir el esfuerzo computacional y mejorar la calidad de los resultados. El método propuesto se valida en un sistema IEEE de 30 nodos.Neste artigo apresenta-se um método para resolver o problema de estimativa de estado em sistemas elétricos usando otimização combinatória. Seu objetivo é o estudo de medidas com erros de difícil detecção, que afetam o desempenho e qualidade dos resultados quando se emprega um estimador de estado clássico. Dada sua complexidade matemática, deduzem-se indicadores de sensibilidade da teoria de pontos de alavancagem que se usam no algoritmo de otimização de Chu-Beasley, com o fim de diminuir o esforço computacional e melhorar a qualidade dos resultados. O método proposto se valida em um sistema IEEE de 30 nós.In this paper a method to solve the state estimation problem in electric systems applying combinatorial optimization is presented. Its objective is the study of measures with difficult detection errors, which affect the performance and quality of the results when a classic state estimator is used. Due to the mathematical complexity, sensibility indicators are deduced from the theory of leverage points used in the Chu-Beasley optimization algorithm with the purpose of reducing the computational effort and enhance the quality of the results. The proposed method is validated in a 30-node IEEE system.
Reference Values for Maximal Inspiratory Pressure: A Systematic Review
Directory of Open Access Journals (Sweden)
Isabela MB Sclauser Pessoa
2014-01-01
Full Text Available BACKGROUND: Maximal inspiratory pressure (MIP is the most commonly used measure to evaluate inspiratory muscle strength. Normative values for MIP vary significantly among studies, which may reflect differences in participant demographics and technique of MIP measurement.
Classification of conformal representations induced from the maximal cuspidal parabolic
Energy Technology Data Exchange (ETDEWEB)
Dobrev, V. K., E-mail: dobrev@inrne.bas.bg [Scuola Internazionale Superiore di Studi Avanzati (Italy)
2017-03-15
In the present paper we continue the project of systematic construction of invariant differential operators on the example of representations of the conformal algebra induced from the maximal cuspidal parabolic.
Maximizing Your Investment in Building Automation System Technology.
Darnell, Charles
2001-01-01
Discusses how organizational issues and system standardization can be important factors that determine an institution's ability to fully exploit contemporary building automation systems (BAS). Further presented is management strategy for maximizing BAS investments. (GR)
Eccentric exercise decreases maximal insulin action in humans
DEFF Research Database (Denmark)
Asp, Svend; Daugaard, J R; Kristiansen, S
1996-01-01
subjects participated in two euglycaemic clamps, performed in random order. One clamp was preceded 2 days earlier by one-legged eccentric exercise (post-eccentric exercise clamp (PEC)) and one was without the prior exercise (control clamp (CC)). 2. During PEC the maximal insulin-stimulated glucose uptake...... for all three clamp steps used (P maximal activity of glycogen synthase was identical in the two thighs for all clamp steps. 3. The glucose infusion rate (GIR......) necessary to maintain euglycaemia during maximal insulin stimulation was lower during PEC compared with CC (15.7%, 81.3 +/- 3.2 vs. 96.4 +/- 8.8 mumol kg-1 min-1, P maximal...
Maximal slicing of D-dimensional spherically symmetric vacuum spacetime
International Nuclear Information System (INIS)
Nakao, Ken-ichi; Abe, Hiroyuki; Yoshino, Hirotaka; Shibata, Masaru
2009-01-01
We study the foliation of a D-dimensional spherically symmetric black-hole spacetime with D≥5 by two kinds of one-parameter families of maximal hypersurfaces: a reflection-symmetric foliation with respect to the wormhole slot and a stationary foliation that has an infinitely long trumpetlike shape. As in the four-dimensional case, the foliations by the maximal hypersurfaces avoid the singularity irrespective of the dimensionality. This indicates that the maximal slicing condition will be useful for simulating higher-dimensional black-hole spacetimes in numerical relativity. For the case of D=5, we present analytic solutions of the intrinsic metric, the extrinsic curvature, the lapse function, and the shift vector for the foliation by the stationary maximal hypersurfaces. These data will be useful for checking five-dimensional numerical-relativity codes based on the moving puncture approach.
ICTs and Urban Micro Enterprises : Maximizing Opportunities for ...
International Development Research Centre (IDRC) Digital Library (Canada)
ICTs and Urban Micro Enterprises : Maximizing Opportunities for Economic Development ... the use of ICTs in micro enterprises and their role in reducing poverty. ... in its approach to technological connectivity but bottom-up in relation to.
Multiuser TOA Estimation Algorithm in DS-CDMA Sparse Channel for Radiolocation
Kim, Sunwoo
This letter considers multiuser time delay estimation in a sparse channel environment for radiolocation. The generalized successive interference cancellation (GSIC) algorithm is used to eliminate the multiple access interference (MAI). To adapt GSIC to sparse channels the alternating maximization (AM) algorithm is considered, and the continuous time delay of each path is estimated without requiring a priori known data sequences.
A polynomial time algorithm for checking regularity of totally normed process algebra
Yang, F.; Huang, H.
2015-01-01
A polynomial algorithm for the regularity problem of weak and branching bisimilarity on totally normed process algebra (PA) processes is given. Its time complexity is O(n 3 +mn) O(n3+mn), where n is the number of transition rules and m is the maximal length of the rules. The algorithm works for
Quantitative validation of a new coregistration algorithm
International Nuclear Information System (INIS)
Pickar, R.D.; Esser, P.D.; Pozniakoff, T.A.; Van Heertum, R.L.; Stoddart, H.A. Jr.
1995-01-01
A new coregistration software package, Neuro9OO Image Coregistration software, has been developed specifically for nuclear medicine. With this algorithm, the correlation coefficient is maximized between volumes generated from sets of transaxial slices. No localization markers or segmented surfaces are needed. The coregistration program was evaluated for translational and rotational registration accuracy. A Tc-99m HM-PAO split-dose study (0.53 mCi low dose, L, and 1.01 mCi high dose, H) was simulated with a Hoffman Brain Phantom with five fiducial markers. Translation error was determined by a shift in image centroid, and rotation error was determined by a simplified two-axis approach. Changes in registration accuracy were measured with respect to: (1) slice spacing, using the four different combinations LL, LH, HL, HH, (2) translational and rotational misalignment before coregistration, (3) changes in the step size of the iterative parameters. In all the cases the algorithm converged with only small difference in translation offset, 0 and 0. At 6 nun slice spacing, translational efforts ranged from 0.9 to 2.8 mm (system resolution at 100 mm, 6.8 mm). The converged parameters showed little sensitivity to count density. In addition the correlation coefficient increased with decreasing iterative step size, as expected. From these experiments, the authors found that this algorithm based on the maximization of the correlation coefficient between studies was an accurate way to coregister SPECT brain images
Divasón, Jose; Joosten, Sebastiaan; Thiemann, René; Yamada, Akihisa
2018-01-01
The Lenstra-Lenstra-Lovász basis reduction algorithm, also known as LLL algorithm, is an algorithm to find a basis with short, nearly orthogonal vectors of an integer lattice. Thereby, it can also be seen as an approximation to solve the shortest vector problem (SVP), which is an NP-hard problem,
Nonadditive entropy maximization is inconsistent with Bayesian updating
Pressé, Steve
2014-11-01
The maximum entropy method—used to infer probabilistic models from data—is a special case of Bayes's model inference prescription which, in turn, is grounded in basic propositional logic. By contrast to the maximum entropy method, the compatibility of nonadditive entropy maximization with Bayes's model inference prescription has never been established. Here we demonstrate that nonadditive entropy maximization is incompatible with Bayesian updating and discuss the immediate implications of this finding. We focus our attention on special cases as illustrations.
Sex differences in autonomic function following maximal exercise.
Kappus, Rebecca M; Ranadive, Sushant M; Yan, Huimin; Lane-Cordova, Abbi D; Cook, Marc D; Sun, Peng; Harvey, I Shevon; Wilund, Kenneth R; Woods, Jeffrey A; Fernhall, Bo
2015-01-01
Heart rate variability (HRV), blood pressure variability, (BPV) and heart rate recovery (HRR) are measures that provide insight regarding autonomic function. Maximal exercise can affect autonomic function, and it is unknown if there are sex differences in autonomic recovery following exercise. Therefore, the purpose of this study was to determine sex differences in several measures of autonomic function and the response following maximal exercise. Seventy-one (31 males and 40 females) healthy, nonsmoking, sedentary normotensive subjects between the ages of 18 and 35 underwent measurements of HRV and BPV at rest and following a maximal exercise bout. HRR was measured at minute one and two following maximal exercise. Males have significantly greater HRR following maximal exercise at both minute one and two; however, the significance between sexes was eliminated when controlling for VO2 peak. Males had significantly higher resting BPV-low-frequency (LF) values compared to females and did not significantly change following exercise, whereas females had significantly increased BPV-LF values following acute maximal exercise. Although males and females exhibited a significant decrease in both HRV-LF and HRV-high frequency (HF) with exercise, females had significantly higher HRV-HF values following exercise. Males had a significantly higher HRV-LF/HF ratio at rest; however, both males and females significantly increased their HRV-LF/HF ratio following exercise. Pre-menopausal females exhibit a cardioprotective autonomic profile compared to age-matched males due to lower resting sympathetic activity and faster vagal reactivation following maximal exercise. Acute maximal exercise is a sufficient autonomic stressor to demonstrate sex differences in the critical post-exercise recovery period.
Power Converters Maximize Outputs Of Solar Cell Strings
Frederick, Martin E.; Jermakian, Joel B.
1993-01-01
Microprocessor-controlled dc-to-dc power converters devised to maximize power transferred from solar photovoltaic strings to storage batteries and other electrical loads. Converters help in utilizing large solar photovoltaic arrays most effectively with respect to cost, size, and weight. Main points of invention are: single controller used to control and optimize any number of "dumb" tracker units and strings independently; power maximized out of converters; and controller in system is microprocessor.
Maximally flat radiation patterns of a circular aperture
Minkovich, B. M.; Mints, M. Ia.
1989-08-01
The paper presents an explicit solution to the problems of maximizing the area utilization coefficient and of obtaining the best approximation (on the average) of a sectorial Pi-shaped radiation pattern of an antenna with a circular aperture when Butterworth conditions are imposed on the approximating pattern with the aim of flattening it. Constraints on the choice of admissible minimum and maximum antenna dimensions are determined which make possible the synthesis of maximally flat patterns with small sidelobes.
Design of optimal linear antennas with maximally flat radiation patterns
Minkovich, B. M.; Mints, M. Ia.
1990-02-01
The paper presents an explicit solution to the problem of maximizing the aperture area utilization coefficient and obtaining the best approximation in the mean of the sectorial U-shaped radiation pattern of a linear antenna, when Butterworth flattening constraints are imposed on the approximating pattern. Constraints are established on the choice of the smallest and large antenna dimensions that make it possible to obtain maximally flat patterns, having a low sidelobe level and free from pulsations within the main lobe.
No Mikheyev-Smirnov-Wolfenstein Effect in Maximal Mixing
Harrison, P. F.; Perkins, D. H.; Scott, W. G.
1996-01-01
We investigate the possible influence of the MSW effect on the expectations for the solar neutrino experiments in the maximal mixing scenario suggested by the atmospheric neutrino data. A direct numerical calculation of matter induced effects in the Sun shows that the naive vacuum predictions are left completely undisturbed in the particular case of maximal mixing, so that the MSW effect turns out to be unobservable. We give a qualitative explanation of this result.
A fractional optimal control problem for maximizing advertising efficiency
Igor Bykadorov; Andrea Ellero; Stefania Funari; Elena Moretti
2007-01-01
We propose an optimal control problem to model the dynamics of the communication activity of a firm with the aim of maximizing its efficiency. We assume that the advertising effort undertaken by the firm contributes to increase the firm's goodwill and that the goodwill affects the firm's sales. The aim is to find the advertising policies in order to maximize the firm's efficiency index which is computed as the ratio between "outputs" and "inputs" properly weighted; the outputs are represented...
On Maximally Dissipative Shock Waves in Nonlinear Elasticity
Knowles, James K.
2010-01-01
Shock waves in nonlinearly elastic solids are, in general, dissipative. We study the following question: among all plane shock waves that can propagate with a given speed in a given one-dimensional nonlinearly elastic bar, which one—if any—maximizes the rate of dissipation? We find that the answer to this question depends strongly on the qualitative nature of the stress-strain relation characteristic of the given material. When maximally dissipative shocks do occur, they propagate according t...
Maximal near-field radiative heat transfer between two plates
Nefzaoui, Elyes; Ezzahri, Younès; Drevillon, Jérémie; Joulain, Karl
2013-01-01
International audience; Near-field radiative transfer is a promising way to significantly and simultaneously enhance both thermo-photovoltaic (TPV) devices power densities and efficiencies. A parametric study of Drude and Lorentz models performances in maximizing near-field radiative heat transfer between two semi-infinite planes separated by nanometric distances at room temperature is presented in this paper. Optimal parameters of these models that provide optical properties maximizing the r...
Energy Efficiency Maximization for WSNs with Simultaneous Wireless Information and Power Transfer.
Yu, Hongyan; Zhang, Yongqiang; Guo, Songtao; Yang, Yuanyuan; Ji, Luyue
2017-08-18
Recently, the simultaneous wireless information and power transfer (SWIPT) technique has been regarded as a promising approach to enhance performance of wireless sensor networks with limited energy supply. However, from a green communication perspective, energy efficiency optimization for SWIPT system design has not been investigated in Wireless Rechargeable Sensor Networks (WRSNs). In this paper, we consider the tradeoffs between energy efficiency and three factors including spectral efficiency, the transmit power and outage target rate for two different modes, i.e., power splitting (PS) and time switching modes (TS), at the receiver. Moreover, we formulate the energy efficiency maximization problem subject to the constraints of minimum Quality of Service (QoS), minimum harvested energy and maximum transmission power as non-convex optimization problem. In particular, we focus on optimizing power control and power allocation policy in PS and TS modes to maximize energy efficiency of data transmission. For PS and TS modes, we propose the corresponding algorithm to characterize a non-convex optimization problem that takes into account the circuit power consumption and the harvested energy. By exploiting nonlinear fractional programming and Lagrangian dual decomposition, we propose suboptimal iterative algorithms to obtain the solutions of non-convex optimization problems. Furthermore, we derive the outage probability and effective throughput from the scenarios that the transmitter does not or partially know the channel state information (CSI) of the receiver. Simulation results illustrate that the proposed optimal iterative algorithm can achieve optimal solutions within a small number of iterations and various tradeoffs between energy efficiency and spectral efficiency, transmit power and outage target rate, respectively.
Energy Efficiency Maximization for WSNs with Simultaneous Wireless Information and Power Transfer
Yu, Hongyan; Zhang, Yongqiang; Yang, Yuanyuan; Ji, Luyue
2017-01-01
Recently, the simultaneous wireless information and power transfer (SWIPT) technique has been regarded as a promising approach to enhance performance of wireless sensor networks with limited energy supply. However, from a green communication perspective, energy efficiency optimization for SWIPT system design has not been investigated in Wireless Rechargeable Sensor Networks (WRSNs). In this paper, we consider the tradeoffs between energy efficiency and three factors including spectral efficiency, the transmit power and outage target rate for two different modes, i.e., power splitting (PS) and time switching modes (TS), at the receiver. Moreover, we formulate the energy efficiency maximization problem subject to the constraints of minimum Quality of Service (QoS), minimum harvested energy and maximum transmission power as non-convex optimization problem. In particular, we focus on optimizing power control and power allocation policy in PS and TS modes to maximize energy efficiency of data transmission. For PS and TS modes, we propose the corresponding algorithm to characterize a non-convex optimization problem that takes into account the circuit power consumption and the harvested energy. By exploiting nonlinear fractional programming and Lagrangian dual decomposition, we propose suboptimal iterative algorithms to obtain the solutions of non-convex optimization problems. Furthermore, we derive the outage probability and effective throughput from the scenarios that the transmitter does not or partially know the channel state information (CSI) of the receiver. Simulation results illustrate that the proposed optimal iterative algorithm can achieve optimal solutions within a small number of iterations and various tradeoffs between energy efficiency and spectral efficiency, transmit power and outage target rate, respectively. PMID:28820496
Directory of Open Access Journals (Sweden)
Marcelo Mollinari
2008-04-01
Full Text Available O objetivo deste trabalho foi avaliar a eficiência, na construção de mapas genéticos, dos algoritmos seriação e delineação rápida em cadeia, além dos critérios para avaliação de ordens: produto mínimo das frações de recombinação adjacentes, soma mínima das frações de recombinação adjacentes e soma máxima dos LOD Scores adjacentes, quando usados com o algoritmo de verificação de erros " ripple" . Foi simulado um mapa com 24 marcadores, posicionados aleatoriamente a distâncias variadas, com média 10 cM. Por meio do método Monte Carlo, foram obtidas 1.000 populações de retrocruzamento e 1.000 populações F2, com 200 indivíduos cada, e diferentes combinações de marcadores dominantes e co-dominantes (100% co-dominantes, 100% dominantes e mistura com 50% co-dominantes e 50% dominantes. Foi, também, simulada a perda de 25, 50 e 75% dos dados. Observou-se que os dois algoritmos avaliados tiveram desempenho semelhante e foram sensíveis à presença de dados perdidos e à presença de marcadores dominantes; esta última dificultou a obtenção de estimativas com boa acurácia, tanto da ordem quanto da distância. Além disso, observou-se que o algoritmo " ripple" geralmente aumenta o número de ordens corretas e pode ser combinado com os critérios soma mínima das frações de recombinação adjacentes e produto mínimo das frações de recombinação adjacentes.The objective of this work was to evaluate the efficiency for the construction of genetic linkage maps of the algorithms seriation and rapid chain delineation, as well as the criteria: product of adjacent recombination fractions, sum of adjacent recombination fractions, and sum of adjacent LOD Scores, used with the ripple algorithm. A genetic linkage map was simulated containing 24 markers with random distances between them, with an average of 10 cM. Using the Monte Carlo method, 1,000 backcross populations and 1,000 F2 populations were simulated. The
Softly Broken Lepton Numbers: an Approach to Maximal Neutrino Mixing
International Nuclear Information System (INIS)
Grimus, W.; Lavoura, L.
2001-01-01
We discuss models where the U(1) symmetries of lepton numbers are responsible for maximal neutrino mixing. We pay particular attention to an extension of the Standard Model (SM) with three right-handed neutrino singlets in which we require that the three lepton numbers L e , L μ , and L τ be separately conserved in the Yukawa couplings, but assume that they are softly broken by the Majorana mass matrix M R of the neutrino singlets. In this framework, where lepton-number breaking occurs at a scale much higher than the electroweak scale, deviations from family lepton number conservation are calculable, i.e., finite, and lepton mixing stems exclusively from M R . We show that in this framework either maximal atmospheric neutrino mixing or maximal solar neutrino mixing or both can be imposed by invoking symmetries. In this way those maximal mixings are stable against radiative corrections. The model which achieves maximal (or nearly maximal) solar neutrino mixing assumes that there are two different scales in M R and that the lepton number (dash)L=L e -L μ -L τ 1 is conserved in between them. We work out the difference between this model and the conventional scenario where (approximate) (dash)L invariance is imposed directly on the mass matrix of the light neutrinos. (author)
Momentos em freios e em embraiagens
Mimoso, Rui Miguel Pereira
2011-01-01
Dissertação para obtenção do Grau de Mestre em Mestrado Integrado em Engenharia Mecânica Nesta dissertação reúnem-se os modelos de cálculo utilizados na determinação dos momentos em freios e em embraiagens. Neste trabalho consideram-se os casos de freios e embraiagens de atrito seco e atrito viscoso. Nos freios de atrito viscoso são considerados casos em que as características dos fluidos não são induzidas, e outros em que são induzidas modificações a essas mesmas características. São a...
Nature-inspired optimization algorithms
Yang, Xin-She
2014-01-01
Nature-Inspired Optimization Algorithms provides a systematic introduction to all major nature-inspired algorithms for optimization. The book's unified approach, balancing algorithm introduction, theoretical background and practical implementation, complements extensive literature with well-chosen case studies to illustrate how these algorithms work. Topics include particle swarm optimization, ant and bee algorithms, simulated annealing, cuckoo search, firefly algorithm, bat algorithm, flower algorithm, harmony search, algorithm analysis, constraint handling, hybrid methods, parameter tuning
VISUALIZATION OF PAGERANK ALGORITHM
Perhaj, Ervin
2013-01-01
The goal of the thesis is to develop a web application that help users understand the functioning of the PageRank algorithm. The thesis consists of two parts. First we develop an algorithm to calculate PageRank values of web pages. The input of algorithm is a list of web pages and links between them. The user enters the list through the web interface. From the data the algorithm calculates PageRank value for each page. The algorithm repeats the process, until the difference of PageRank va...
Akl, Selim G
1985-01-01
Parallel Sorting Algorithms explains how to use parallel algorithms to sort a sequence of items on a variety of parallel computers. The book reviews the sorting problem, the parallel models of computation, parallel algorithms, and the lower bounds on the parallel sorting problems. The text also presents twenty different algorithms, such as linear arrays, mesh-connected computers, cube-connected computers. Another example where algorithm can be applied is on the shared-memory SIMD (single instruction stream multiple data stream) computers in which the whole sequence to be sorted can fit in the
Use of Genetic Algorithms for Contrast and Entropy Optimization in ISAR Autofocusing
Directory of Open Access Journals (Sweden)
Martorella Marco
2006-01-01
Full Text Available Image contrast maximization and entropy minimization are two commonly used techniques for ISAR image autofocusing. When the signal phase history due to the target radial motion has to be approximated with high order polynomial models, classic optimization techniques fail when attempting to either maximize the image contrast or minimize the image entropy. In this paper a solution of this problem is proposed by using genetic algorithms. The performances of the new algorithms that make use of genetic algorithms overcome the problem with previous implementations based on deterministic approaches. Tests on real data of airplanes and ships confirm the insight.
Energy Technology Data Exchange (ETDEWEB)
Li, Si; Xu, Yuesheng, E-mail: yxu06@syr.edu [Guangdong Provincial Key Laboratory of Computational Science, School of Mathematics and Computational Sciences, Sun Yat-sen University, Guangzhou 510275 (China); Zhang, Jiahan; Lipson, Edward [Department of Physics, Syracuse University, Syracuse, New York 13244 (United States); Krol, Andrzej; Feiglin, David [Department of Radiology, SUNY Upstate Medical University, Syracuse, New York 13210 (United States); Schmidtlein, C. Ross [Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York 10065 (United States); Vogelsang, Levon [Carestream Health, Rochester, New York 14608 (United States); Shen, Lixin [Guangdong Provincial Key Laboratory of Computational Science, School of Mathematics and Computational Sciences, Sun Yat-sen University, Guangzhou 510275, China and Department of Mathematics, Syracuse University, Syracuse, New York 13244 (United States)
2015-08-15
Purpose: The authors have recently developed a preconditioned alternating projection algorithm (PAPA) with total variation (TV) regularizer for solving the penalized-likelihood optimization model for single-photon emission computed tomography (SPECT) reconstruction. This algorithm belongs to a novel class of fixed-point proximity methods. The goal of this work is to investigate how PAPA performs while dealing with realistic noisy SPECT data, to compare its performance with more conventional methods, and to address issues with TV artifacts by proposing a novel form of the algorithm invoking high-order TV regularization, denoted as HOTV-PAPA, which has been explored and studied extensively in the present work. Methods: Using Monte Carlo methods, the authors simulate noisy SPECT data from two water cylinders; one contains lumpy “warm” background and “hot” lesions of various sizes with Gaussian activity distribution, and the other is a reference cylinder without hot lesions. The authors study the performance of HOTV-PAPA and compare it with PAPA using first-order TV regularization (TV-PAPA), the Panin–Zeng–Gullberg one-step-late method with TV regularization (TV-OSL), and an expectation–maximization algorithm with Gaussian postfilter (GPF-EM). The authors select penalty-weights (hyperparameters) by qualitatively balancing the trade-off between resolution and image noise separately for TV-PAPA and TV-OSL. However, the authors arrived at the same penalty-weight value for both of them. The authors set the first penalty-weight in HOTV-PAPA equal to the optimal penalty-weight found for TV-PAPA. The second penalty-weight needed for HOTV-PAPA is tuned by balancing resolution and the severity of staircase artifacts. The authors adjust the Gaussian postfilter to approximately match the local point spread function of GPF-EM and HOTV-PAPA. The authors examine hot lesion detectability, study local spatial resolution, analyze background noise properties, estimate mean
International Nuclear Information System (INIS)
Li, Si; Xu, Yuesheng; Zhang, Jiahan; Lipson, Edward; Krol, Andrzej; Feiglin, David; Schmidtlein, C. Ross; Vogelsang, Levon; Shen, Lixin
2015-01-01
Purpose: The authors have recently developed a preconditioned alternating projection algorithm (PAPA) with total variation (TV) regularizer for solving the penalized-likelihood optimization model for single-photon emission computed tomography (SPECT) reconstruction. This algorithm belongs to a novel class of fixed-point proximity methods. The goal of this work is to investigate how PAPA performs while dealing with realistic noisy SPECT data, to compare its performance with more conventional methods, and to address issues with TV artifacts by proposing a novel form of the algorithm invoking high-order TV regularization, denoted as HOTV-PAPA, which has been explored and studied extensively in the present work. Methods: Using Monte Carlo methods, the authors simulate noisy SPECT data from two water cylinders; one contains lumpy “warm” background and “hot” lesions of various sizes with Gaussian activity distribution, and the other is a reference cylinder without hot lesions. The authors study the performance of HOTV-PAPA and compare it with PAPA using first-order TV regularization (TV-PAPA), the Panin–Zeng–Gullberg one-step-late method with TV regularization (TV-OSL), and an expectation–maximization algorithm with Gaussian postfilter (GPF-EM). The authors select penalty-weights (hyperparameters) by qualitatively balancing the trade-off between resolution and image noise separately for TV-PAPA and TV-OSL. However, the authors arrived at the same penalty-weight value for both of them. The authors set the first penalty-weight in HOTV-PAPA equal to the optimal penalty-weight found for TV-PAPA. The second penalty-weight needed for HOTV-PAPA is tuned by balancing resolution and the severity of staircase artifacts. The authors adjust the Gaussian postfilter to approximately match the local point spread function of GPF-EM and HOTV-PAPA. The authors examine hot lesion detectability, study local spatial resolution, analyze background noise properties, estimate mean
International Nuclear Information System (INIS)
Huang Zhenghai; Gu Weizhe
2008-01-01
In this paper, we construct an augmented system of the standard monotone linear complementarity problem (LCP), and establish the relations between the augmented system and the LCP. We present a smoothing-type algorithm for solving the augmented system. The algorithm is shown to be globally convergent without assuming any prior knowledge of feasibility/infeasibility of the problem. In particular, if the LCP has a solution, then the algorithm either generates a maximal complementary solution of the LCP or detects correctly solvability of the LCP, and in the latter case, an existing smoothing-type algorithm can be directly applied to solve the LCP without any additional assumption and it generates a maximal complementary solution of the LCP; and that if the LCP is infeasible, then the algorithm detect correctly infeasibility of the LCP. To the best of our knowledge, such properties have not appeared in the existing literature for smoothing-type algorithms
Modified Clipped LMS Algorithm
Directory of Open Access Journals (Sweden)
Lotfizad Mojtaba
2005-01-01
Full Text Available Abstract A new algorithm is proposed for updating the weights of an adaptive filter. The proposed algorithm is a modification of an existing method, namely, the clipped LMS, and uses a three-level quantization ( scheme that involves the threshold clipping of the input signals in the filter weight update formula. Mathematical analysis shows the convergence of the filter weights to the optimum Wiener filter weights. Also, it can be proved that the proposed modified clipped LMS (MCLMS algorithm has better tracking than the LMS algorithm. In addition, this algorithm has reduced computational complexity relative to the unmodified one. By using a suitable threshold, it is possible to increase the tracking capability of the MCLMS algorithm compared to the LMS algorithm, but this causes slower convergence. Computer simulations confirm the mathematical analysis presented.
Optimizing fluorescently tethered Hsp90 inhibitor dose for maximal specific uptake by breast tumors
Crouch, Brian T.; Duer, Joy; Wang, Roujia; Gallagher, Jennifer; Hall, Allison; Soo, Mary Scott; Hughes, Philip; Haystead, Timothy A. J.; Ramanujam, Nirmala
2018-03-01
Despite improvements in surgical resection, 20-40% of patients undergoing breast conserving surgery require at least one additional re-excision. Leveraging the unique surface expression of heat shock protein 90 (Hsp90), a chaperone protein involved in several key hallmarks of cancer, in breast cancer provides an exciting opportunity to identify residual disease during surgery. We developed a completely non-destructive strategy using HS-27, a fluorescently-tethered Hsp90 inhibitor, to assay surface Hsp90 expression on intact tissue specimens using a fluorescence microendoscope with a field of view of 750 μm and subcellular resolution of 4 μm. HS-27 consists of an FDA approved Hsp90 inhibitor tethered to fluorescein isothiocyanate (EX 488nm, EM 525nm). Here, we optimized ex vivo HS-27 administration in pre-clinical breast cancer models and validated our approach on 21 patients undergoing standard of care ultrasound guided core needle biopsy. HS-27 administration time was fixed at 1- minute to minimize imaging impact on clinical workflow. HS-27 and HS-217 (non-specific control) doses were modulated from 1 μM up to 100 μM to identify the dose maximizing the ratio of specific uptake (HS-27 fluorescence) to non-specific uptake (HS-217 fluorescence). The specificity ratio was maximized at 100 μM and was significantly greater than all other doses (pcancer makes this technology attractive for assessing tumor margins, as one agent can be used for all subtypes.
Holst, Glendon
2016-12-01
Serial section electron microscopy (SSEM) image stacks generated using high throughput microscopy techniques are an integral tool for investigating brain connectivity and cell morphology. FIB or 3View scanning electron microscopes easily generate gigabytes of data. In order to produce analyzable 3D dataset from the imaged volumes, efficient and reliable image segmentation is crucial. Classical manual approaches to segmentation are time consuming and labour intensive. Semiautomatic seeded watershed segmentation algorithms, such as those implemented by ilastik image processing software, are a very powerful alternative, substantially speeding up segmentation times. We have used ilastik effectively for small EM stacks – on a laptop, no less; however, ilastik was unable to carve the large EM stacks we needed to segment because its memory requirements grew too large – even for the biggest workstations we had available. For this reason, we refactored the carving module of ilastik to scale it up to large EM stacks on large workstations, and tested its efficiency. We modified the carving module, building on existing blockwise processing functionality to process data in manageable chunks that can fit within RAM (main memory). We review this refactoring work, highlighting the software architecture, design choices, modifications, and issues encountered.
A novel clustering algorithm based on quantum games
International Nuclear Information System (INIS)
Li Qiang; He Yan; Jiang Jingping
2009-01-01
Enormous successes have been made by quantum algorithms during the last decade. In this paper, we combine the quantum game with the problem of data clustering, and then develop a quantum-game-based clustering algorithm, in which data points in a dataset are considered as players who can make decisions and implement quantum strategies in quantum games. After each round of a quantum game, each player's expected payoff is calculated. Later, he uses a link-removing-and-rewiring (LRR) function to change his neighbors and adjust the strength of links connecting to them in order to maximize his payoff. Further, algorithms are discussed and analyzed in two cases of strategies, two payoff matrixes and two LRR functions. Consequently, the simulation results have demonstrated that data points in datasets are clustered reasonably and efficiently, and the clustering algorithms have fast rates of convergence. Moreover, the comparison with other algorithms also provides an indication of the effectiveness of the proposed approach.
Iterative Mixture Component Pruning Algorithm for Gaussian Mixture PHD Filter
Directory of Open Access Journals (Sweden)
Xiaoxi Yan
2014-01-01
Full Text Available As far as the increasing number of mixture components in the Gaussian mixture PHD filter is concerned, an iterative mixture component pruning algorithm is proposed. The pruning algorithm is based on maximizing the posterior probability density of the mixture weights. The entropy distribution of the mixture weights is adopted as the prior distribution of mixture component parameters. The iterative update formulations of the mixture weights are derived by Lagrange multiplier and Lambert W function. Mixture components, whose weights become negative during iterative procedure, are pruned by setting corresponding mixture weights to zeros. In addition, multiple mixture components with similar parameters describing the same PHD peak can be merged into one mixture component in the algorithm. Simulation results show that the proposed iterative mixture component pruning algorithm is superior to the typical pruning algorithm based on thresholds.
Directory of Open Access Journals (Sweden)
Adriana Garófolo
2010-10-01
industrializada reduziu o deficit nutricional, principalmente em desnutridos leves. Os resultados sugerem que a suplemento industrializado por sonda favoreceu a recuperação nutricional, principalmente com o uso mais prolongado.Objective This study aimed to describe the algorithm and the global results after its implementation. Methods This was a randomized clinical trial done with malnourished cancer patients. Follow-up followed an algorithm and patients with mild malnutrition were randomized to receive store-bought or homemade oral supplementation. The patients were reassessed after three, eight and twelve weeks. Depending on how the group supplemented with store-bought supplements responded, the supplementation was either continued orally, by tube-feeding or discontinued. The group receiving homemade supplementation either continued on it if the response was positive or received store-bought oral supplementation if the response was negative. The severely malnourished patients either received store-bought supplementation by feeding tube or orally, or it was discontinued if an adequate nutritional status was reached. The patients' responses to supplementation were determined by weight-for-height Z-scores, body mass indices, triceps skinfold thicknesses and circumferences. Results One hundred and seventeen out of 141 patients completed the first three weeks; 58 were severely malnourished and 59 were mildly malnourished. The nutritional status of 41% of the severely malnourished patients and 97% of the mildly malnourished patients receiving store-bought supplement orally improved. The nutritional status of 77% of the mildly malnourished patients receiving homemade supplement orally also improved. Of the 117 patients, 42 had to be tube-fed; of these, 23 accepted and 19 refused tube feeding and continued taking store-bought supplement orally. Consumption of store-bought supplement was higher in tube-fed patients than in orally-fed patients. Consumption also increased as orally
Zhang, Yu; Li, Fei; Zhang, Shengkai; Zhu, Tingting
2017-04-01
Synthetic Aperture Radar (SAR) is significantly important for polar remote sensing since it can provide continuous observations in all days and all weather. SAR can be used for extracting the surface roughness information characterized by the variance of dielectric properties and different polarization channels, which make it possible to observe different ice types and surface structure for deformation analysis. In November, 2016, Chinese National Antarctic Research Expedition (CHINARE) 33rd cruise has set sails in sea ice zone in Antarctic. Accurate leads spatial distribution in sea ice zone for routine planning of ship navigation is essential. In this study, the semantic relationship between leads and sea ice categories has been described by the Conditional Random Fields (CRF) model, and leads characteristics have been modeled by statistical distributions in SAR imagery. In the proposed algorithm, a mixture statistical distribution based CRF is developed by considering the contexture information and the statistical characteristics of sea ice for improving leads detection in Sentinel-1A dual polarization SAR imagery. The unary potential and pairwise potential in CRF model is constructed by integrating the posteriori probability estimated from statistical distributions. For mixture statistical distribution parameter estimation, Method of Logarithmic Cumulants (MoLC) is exploited for single statistical distribution parameters estimation. The iteration based Expectation Maximal (EM) algorithm is investigated to calculate the parameters in mixture statistical distribution based CRF model. In the posteriori probability inference, graph-cut energy minimization method is adopted in the initial leads detection. The post-processing procedures including aspect ratio constrain and spatial smoothing approaches are utilized to improve the visual result. The proposed method is validated on Sentinel-1A SAR C-band Extra Wide Swath (EW) Ground Range Detected (GRD) imagery with a
Link adaptation algorithm for distributed coded transmissions in cooperative OFDMA systems
DEFF Research Database (Denmark)
Varga, Mihaly; Badiu, Mihai Alin; Bota, Vasile
2015-01-01
This paper proposes a link adaptation algorithm for cooperative transmissions in the down-link connection of an OFDMA-based wireless system. The algorithm aims at maximizing the spectral efficiency of a relay-aided communication link, while satisfying the block error rate constraints at both...... adaptation algorithm has linear complexity with the number of available resource blocks, while still provides a very good performance, as shown by simulation results....
Dermatoses em renais cronicos em terapia dialitica
Directory of Open Access Journals (Sweden)
Luis Alberto Batista Peres
2014-03-01
Full Text Available Objetivo: As desordens cutâneas e das mucosas são comuns em pacientes em hemodiálise a longo prazo. A diálise prolonga a expectativa de vida, dando tempo para a manifestação destas anormalidades. Os objetivos deste estudo foram avaliar a prevalência de problemas dermatológicos em pacientes com doença renal crônica (DRC em hemodiálise. Métodos: Cento e quarenta e cinco pacientes com doença renal crônica em hemodiálise foram estudados. Todos os pacientes foram completamente analisados para as alterações cutâneas, de cabelos, mucosas e unhas por um único examinador e foram coletados dados de exames laboratoriais. Os dados foram armazenados em um banco de dados do Microsolft Excel e analisados por estatística descritiva. As variáveis contínuas foram comparadas pelo teste t de Student e as variáveis categóricas utilizando o teste do qui-quadrado ou o teste Exato de Fischer, conforme adequado. Resultados: O estudo incluiu 145 pacientes, com idade média de 53,6 ± 14,7 anos, predominantemente do sexo masculino (64,1% e caucasianos (90,0%. O tempo médio de diálise foi de 43,3 ± 42,3 meses. As principais doenças subjacentes foram: hipertensão arterial em 33,8%, diabetes mellitus em 29,6% e glomerulonefrite crônica em 13,1%. As principais manifestações dermatológicas observadas foram: xerose em 109 (75,2%, equimose em 87 (60,0%, prurido em 78 (53,8% e lentigo em 33 (22,8% pacientes. Conclusão: O nosso estudo mostrou a presença de mais do que uma dermatose por paciente. As alterações cutâneas são frequentes em pacientes em diálise. Mais estudos são necessários para melhor caracterização e manejo destas dermatoses.
Qiu, Sihang; Chen, Bin; Wang, Rongxiao; Zhu, Zhengqiu; Wang, Yuan; Qiu, Xiaogang
2018-04-01
Hazardous gas leak accident has posed a potential threat to human beings. Predicting atmospheric dispersion and estimating its source become increasingly important in emergency management. Current dispersion prediction and source estimation models cannot satisfy the requirement of emergency management because they are not equipped with high efficiency and accuracy at the same time. In this paper, we develop a fast and accurate dispersion prediction and source estimation method based on artificial neural network (ANN), particle swarm optimization (PSO) and expectation maximization (EM). The novel method uses a large amount of pre-determined scenarios to train the ANN for dispersion prediction, so that the ANN can predict concentration distribution accurately and efficiently. PSO and EM are applied for estimating the source parameters, which can effectively accelerate the process of convergence. The method is verified by the Indianapolis field study with a SF6 release source. The results demonstrate the effectiveness of the method.
A maximum-likelihood reconstruction algorithm for tomographic gamma-ray nondestructive assay
International Nuclear Information System (INIS)
Prettyman, T.H.; Estep, R.J.; Cole, R.A.; Sheppard, G.A.
1994-01-01
A new tomographic reconstruction algorithm for nondestructive assay with high resolution gamma-ray spectroscopy (HRGS) is presented. The reconstruction problem is formulated using a maximum-likelihood approach in which the statistical structure of both the gross and continuum measurements used to determine the full-energy response in HRGS is precisely modeled. An accelerated expectation-maximization algorithm is used to determine the optimal solution. The algorithm is applied to safeguards and environmental assays of large samples (for example, 55-gal. drums) in which high continuum levels caused by Compton scattering are routinely encountered. Details of the implementation of the algorithm and a comparative study of the algorithm's performance are presented
Semioptimal practicable algorithmic cooling
International Nuclear Information System (INIS)
Elias, Yuval; Mor, Tal; Weinstein, Yossi
2011-01-01
Algorithmic cooling (AC) of spins applies entropy manipulation algorithms in open spin systems in order to cool spins far beyond Shannon's entropy bound. Algorithmic cooling of nuclear spins was demonstrated experimentally and may contribute to nuclear magnetic resonance spectroscopy. Several cooling algorithms were suggested in recent years, including practicable algorithmic cooling (PAC) and exhaustive AC. Practicable algorithms have simple implementations, yet their level of cooling is far from optimal; exhaustive algorithms, on the other hand, cool much better, and some even reach (asymptotically) an optimal level of cooling, but they are not practicable. We introduce here semioptimal practicable AC (SOPAC), wherein a few cycles (typically two to six) are performed at each recursive level. Two classes of SOPAC algorithms are proposed and analyzed. Both attain cooling levels significantly better than PAC and are much more efficient than the exhaustive algorithms. These algorithms are shown to bridge the gap between PAC and exhaustive AC. In addition, we calculated the number of spins required by SOPAC in order to purify qubits for quantum computation. As few as 12 and 7 spins are required (in an ideal scenario) to yield a mildly pure spin (60% polarized) from initial polarizations of 1% and 10%, respectively. In the latter case, about five more spins are sufficient to produce a highly pure spin (99.99% polarized), which could be relevant for fault-tolerant quantum computing.
Analysis and enumeration algorithms for biological graphs
Marino, Andrea
2015-01-01
In this work we plan to revise the main techniques for enumeration algorithms and to show four examples of enumeration algorithms that can be applied to efficiently deal with some biological problems modelled by using biological networks: enumerating central and peripheral nodes of a network, enumerating stories, enumerating paths or cycles, and enumerating bubbles. Notice that the corresponding computational problems we define are of more general interest and our results hold in the case of arbitrary graphs. Enumerating all the most and less central vertices in a network according to their eccentricity is an example of an enumeration problem whose solutions are polynomial and can be listed in polynomial time, very often in linear or almost linear time in practice. Enumerating stories, i.e. all maximal directed acyclic subgraphs of a graph G whose sources and targets belong to a predefined subset of the vertices, is on the other hand an example of an enumeration problem with an exponential number of solutions...
Online EM with weight-based forgetting
Celaya, Enric; Agostini, Alejandro
2015-01-01
In the on-line version of the EM algorithm introduced by Sato and Ishii (2000), a time-dependent discount factor is introduced for forgetting the effect of the old posterior values obtained with an earlier, inaccurate estimator. In their approach, forgetting is uniformly applied to the estimators of each mixture component depending exclusively on time, irrespective of the weight attributed to each unit for the observed sample. This causes an excessive forgetting in the less frequently sampled...
Kurnianingsih, Yoanna A; Sim, Sam K Y; Chee, Michael W L; Mullette-Gillman, O'Dhaniel A
2015-01-01
We investigated how adult aging specifically alters economic decision-making, focusing on examining alterations in uncertainty preferences (willingness to gamble) and choice strategies (what gamble information influences choices) within both the gains and losses domains. Within each domain, participants chose between certain monetary outcomes and gambles with uncertain outcomes. We examined preferences by quantifying how uncertainty modulates choice behavior as if altering the subjective valuation of gambles. We explored age-related preferences for two types of uncertainty, risk, and ambiguity. Additionally, we explored how aging may alter what information participants utilize to make their choices by comparing the relative utilization of maximizing and satisficing information types through a choice strategy metric. Maximizing information was the ratio of the expected value of the two options, while satisficing information was the probability of winning. We found age-related alterations of economic preferences within the losses domain, but no alterations within the gains domain. Older adults (OA; 61-80 years old) were significantly more uncertainty averse for both risky and ambiguous choices. OA also exhibited choice strategies with decreased use of maximizing information. Within OA, we found a significant correlation between risk preferences and choice strategy. This linkage between preferences and strategy appears to derive from a convergence to risk neutrality driven by greater use of the effortful maximizing strategy. As utility maximization and value maximization intersect at risk neutrality, this result suggests that OA are exhibiting a relationship between enhanced rationality and enhanced value maximization. While there was variability in economic decision-making measures within OA, these individual differences were unrelated to variability within examined measures of cognitive ability. Our results demonstrate that aging alters economic decision-making for
Directory of Open Access Journals (Sweden)
Yoanna Arlina Kurnianingsih
2015-05-01
Full Text Available We investigated how adult aging specifically alters economic decision-making, focusing on examining alterations in uncertainty preferences (willingness to gamble and choice strategies (what gamble information influences choices within both the gains and losses domains. Within each domain, participants chose between certain monetary outcomes and gambles with uncertain outcomes. We examined preferences by quantifying how uncertainty modulates choice behavior as if altering the subjective valuation of gambles. We explored age-related preferences for two types of uncertainty, risk and ambiguity. Additionally, we explored how aging may alter what information participants utilize to make their choices by comparing the relative utilization of maximizing and satisficing information types through a choice strategy metric. Maximizing information was the ratio of the expected value of the two options, while satisficing information was the probability of winning.We found age-related alterations of economic preferences within the losses domain, but no alterations within the gains domain. Older adults (OA; 61 to 80 years old were significantly more uncertainty averse for both risky and ambiguous choices. OA also exhibited choice strategies with decreased use of maximizing information. Within OA, we found a significant correlation between risk preferences and choice strategy. This linkage between preferences and strategy appears to derive from a convergence to risk neutrality driven by greater use of the effortful maximizing strategy. As utility maximization and value maximization intersect at risk neutrality, this result suggests that OA are exhibiting a relationship between enhanced rationality and enhanced value maximization. While there was variability in economic decision-making measures within OA, these individual differences were unrelated to variability within examined measures of cognitive ability. Our results demonstrate that aging alters economic
Estimating Hull Coating Thickness Distributions Using the EM Algorithm
National Research Council Canada - National Science Library
Corriere, Michael
2000-01-01
The underwater hull coating system on surface ships is comprised anti-corrosive (AC) and anti-fouling (AF) paint The AF layers are designed to wear away, continuously leaching cuprous oxide to inhibit marine growth...
Motion based segmentation for robot vision using adapted EM algorithm
Zhao, Wei; Roos, Nico
2016-01-01
Robots operate in a dynamic world in which objects are often moving. The movement of objects may help the robot to segment the objects from the background. The result of the segmentation can subsequently be used to identify the objects. This paper investigates the possibility of segmenting objects
A Generalized Partial Credit Model: Application of an EM Algorithm.
Muraki, Eiji
1992-01-01
The partial credit model with a varying slope parameter is developed and called the generalized partial credit model (GPCM). Analysis results for simulated data by this and other polytomous item-response models demonstrate that the rating formulation of the GPCM is adaptable to the analysis of polytomous item responses. (SLD)
Quantization with maximally degenerate Poisson brackets: the harmonic oscillator!
International Nuclear Information System (INIS)
Nutku, Yavuz
2003-01-01
Nambu's construction of multi-linear brackets for super-integrable systems can be thought of as degenerate Poisson brackets with a maximal set of Casimirs in their kernel. By introducing privileged coordinates in phase space these degenerate Poisson brackets are brought to the form of Heisenberg's equations. We propose a definition for constructing quantum operators for classical functions, which enables us to turn the maximally degenerate Poisson brackets into operators. They pose a set of eigenvalue problems for a new state vector. The requirement of the single-valuedness of this eigenfunction leads to quantization. The example of the harmonic oscillator is used to illustrate this general procedure for quantizing a class of maximally super-integrable systems
Cycle length maximization in PWRs using empirical core models
International Nuclear Information System (INIS)
Okafor, K.C.; Aldemir, T.
1987-01-01
The problem of maximizing cycle length in nuclear reactors through optimal fuel and poison management has been addressed by many investigators. An often-used neutronic modeling technique is to find correlations between the state and control variables to describe the response of the core to changes in the control variables. In this study, a set of linear correlations, generated by two-dimensional diffusion-depletion calculations, is used to find the enrichment distribution that maximizes cycle length for the initial core of a pressurized water reactor (PWR). These correlations (a) incorporate the effect of composition changes in all the control zones on a given fuel assembly and (b) are valid for a given range of control variables. The advantage of using such correlations is that the cycle length maximization problem can be reduced to a linear programming problem
Maximization of regional probabilities using Optimal Surface Graphs
DEFF Research Database (Denmark)
Arias Lorza, Andres M.; Van Engelen, Arna; Petersen, Jens
2018-01-01
Purpose: We present a segmentation method that maximizes regional probabilities enclosed by coupled surfaces using an Optimal Surface Graph (OSG) cut approach. This OSG cut determines the globally optimal solution given a graph constructed around an initial surface. While most methods for vessel...... wall segmentation only use edge information, we show that maximizing regional probabilities using an OSG improves the segmentation results. We applied this to automatically segment the vessel wall of the carotid artery in magnetic resonance images. Methods: First, voxel-wise regional probability maps...... were obtained using a Support Vector Machine classifier trained on local image features. Then, the OSG segments the regions which maximizes the regional probabilities considering smoothness and topological constraints. Results: The method was evaluated on 49 carotid arteries from 30 subjects...
El culto de Maximón en Guatemala
Pédron‑Colombani, Sylvie
2009-01-01
Este artículo se enfoca en la figura de Maximón, deidad sincrética de Guatemala, en un contexto de desplazamiento de la religión católica popular por parte de las iglesias protestantes. Esta divinidad híbrida a la cual se agregan santos católicos como Judas Iscariote o el dios maya Mam, permite la apropiación de Maximón por segmentos diferenciados de la población (tanto indígena como mestiza). Permite igualmente ser símbolo de protestas sociales enmascaradas cuando se asocia Maximón con figur...
Maximal Electric Dipole Moments of Nuclei with Enhanced Schiff Moments
Ellis, John; Pilaftsis, Apostolos
2011-01-01
The electric dipole moments (EDMs) of heavy nuclei, such as 199Hg, 225Ra and 211Rn, can be enhanced by the Schiff moments induced by the presence of nearby parity-doublet states. Working within the framework of the maximally CP-violating and minimally flavour-violating (MCPMFV) version of the MSSM, we discuss the maximal values that such EDMs might attain, given the existing experimental constraints on the Thallium, neutron and Mercury EDMs. The maximal EDM values of the heavy nuclei are obtained with the help of a differential-geometrical approach proposed recently that enables the maxima of new CP-violating observables to be calculated exactly in the linear approximation. In the case of 225Ra, we find that its EDM may be as large as 6 to 50 x 10^{-27} e.cm.
Introduction to Evolutionary Algorithms
Yu, Xinjie
2010-01-01
Evolutionary algorithms (EAs) are becoming increasingly attractive for researchers from various disciplines, such as operations research, computer science, industrial engineering, electrical engineering, social science, economics, etc. This book presents an insightful, comprehensive, and up-to-date treatment of EAs, such as genetic algorithms, differential evolution, evolution strategy, constraint optimization, multimodal optimization, multiobjective optimization, combinatorial optimization, evolvable hardware, estimation of distribution algorithms, ant colony optimization, particle swarm opti