The selection and implementation of hidden line algorithms
International Nuclear Information System (INIS)
Schneider, A.
1983-06-01
One of the most challenging problems in the field of computer graphics is the elimination of hidden lines in images of nontransparent bodies. In the real world the nontransparent material hinders the light ray coming from hidden regions to the observer. In the computer based image formation process there is no automatic visibility regulation of this kind. So many lines are created which result in a poor quality of the spacial representation. Therefore a three-dimensional representation on the screen is only meaningfull if the hidden lines are eliminated. For this process many algorithms have been developed in the past. A common feature of these codes is the large amount of computer time needed. In the first generation of algorithms, which are commonly used today, the bodies are modeled by plane polygons. More recently, however, also algorithms are in use, which are able to treat curved surfaces without discretisation by plane surfaces. In this paper the first group of algorithms is reviewed, and the most important codes are described. The experience obtained during the implementation of two algorithms is presented. (orig.) [de
Genetic Algorithms Principles Towards Hidden Markov Model
Directory of Open Access Journals (Sweden)
Nabil M. Hewahi
2011-10-01
Full Text Available In this paper we propose a general approach based on Genetic Algorithms (GAs to evolve Hidden Markov Models (HMM. The problem appears when experts assign probability values for HMM, they use only some limited inputs. The assigned probability values might not be accurate to serve in other cases related to the same domain. We introduce an approach based on GAs to find
out the suitable probability values for the HMM to be mostly correct in more cases than what have been used to assign the probability values.
Search algorithms, hidden labour and information control
Directory of Open Access Journals (Sweden)
Paško Bilić
2016-06-01
Full Text Available The paper examines some of the processes of the closely knit relationship between Google’s ideologies of neutrality and objectivity and global market dominance. Neutrality construction comprises an important element sustaining the company’s economic position and is reflected in constant updates, estimates and changes to utility and relevance of search results. Providing a purely technical solution to these issues proves to be increasingly difficult without a human hand in steering algorithmic solutions. Search relevance fluctuates and shifts through continuous tinkering and tweaking of the search algorithm. The company also uses third parties to hire human raters for performing quality assessments of algorithmic updates and adaptations in linguistically and culturally diverse global markets. The adaptation process contradicts the technical foundations of the company and calculations based on the initial Page Rank algorithm. Annual market reports, Google’s Search Quality Rating Guidelines, and reports from media specialising in search engine optimisation business are analysed. The Search Quality Rating Guidelines document provides a rare glimpse into the internal architecture of search algorithms and the notions of utility and relevance which are presented and structured as neutral and objective. Intertwined layers of ideology, hidden labour of human raters, advertising revenues, market dominance and control are discussed throughout the paper.
Optimisation of Hidden Markov Model using Baum–Welch algorithm
Indian Academy of Sciences (India)
Home; Journals; Journal of Earth System Science; Volume 126; Issue 1. Optimisation of Hidden Markov Model using Baum–Welch algorithm for prediction of maximum and minimum temperature over Indian Himalaya. J C Joshi Tankeshwar Kumar Sunita Srivastava Divya Sachdeva. Volume 126 Issue 1 February 2017 ...
Engineering of Algorithms for Hidden Markov models and Tree Distances
DEFF Research Database (Denmark)
Sand, Andreas
Bioinformatics is an interdisciplinary scientific field that combines biology with mathematics, statistics and computer science in an effort to develop computational methods for handling, analyzing and learning from biological data. In the recent decades, the amount of available biological data has...... speed up all the classical algorithms for analyses and training of hidden Markov models. And I show how two particularly important algorithms, the forward algorithm and the Viterbi algorithm, can be accelerated through a reformulation of the algorithms and a somewhat more complicated parallelization...... contribution to the theoretically fastest set of algorithms presently available to compute two closely related measures of tree distance, the triplet distance and the quartet distance. And I further demonstrate that they are also the fastest algorithms in almost all cases when tested in practice....
Algorithms for a parallel implementation of Hidden Markov Models with a small state space
DEFF Research Database (Denmark)
Nielsen, Jesper; Sand, Andreas
2011-01-01
Two of the most important algorithms for Hidden Markov Models are the forward and the Viterbi algorithms. We show how formulating these using linear algebra naturally lends itself to parallelization. Although the obtained algorithms are slow for Hidden Markov Models with large state spaces...
Optimisation of Hidden Markov Model using Baum–Welch algorithm ...
Indian Academy of Sciences (India)
The present work is a part of development of Hidden Markov Model. (HMM) based ... the Himalaya. In this work, HMMs have been developed for forecasting of maximum and minimum ..... data collection teams of Snow and Avalanche Study.
Streaming Algorithms for Line Simplification
DEFF Research Database (Denmark)
Abam, Mohammad; de Berg, Mark; Hachenberger, Peter
2010-01-01
this problem in a streaming setting, where we only have a limited amount of storage, so that we cannot store all the points. We analyze the competitive ratio of our algorithms, allowing resource augmentation: we let our algorithm maintain a simplification with 2k (internal) points and compare the error of our...... simplification to the error of the optimal simplification with k points. We obtain the algorithms with O(1) competitive ratio for three cases: convex paths, where the error is measured using the Hausdorff distance (or Fréchet distance), xy-monotone paths, where the error is measured using the Hausdorff distance...... (or Fréchet distance), and general paths, where the error is measured using the Fréchet distance. In the first case the algorithm needs O(k) additional storage, and in the latter two cases the algorithm needs O(k 2) additional storage....
Directory of Open Access Journals (Sweden)
Zhongbo Hu
2014-01-01
Full Text Available Many improved differential Evolution (DE algorithms have emerged as a very competitive class of evolutionary computation more than a decade ago. However, few improved DE algorithms guarantee global convergence in theory. This paper developed a convergent DE algorithm in theory, which employs a self-adaptation scheme for the parameters and two operators, that is, uniform mutation and hidden adaptation selection (haS operators. The parameter self-adaptation and uniform mutation operator enhance the diversity of populations and guarantee ergodicity. The haS can automatically remove some inferior individuals in the process of the enhancing population diversity. The haS controls the proposed algorithm to break the loop of current generation with a small probability. The breaking probability is a hidden adaptation and proportional to the changes of the number of inferior individuals. The proposed algorithm is tested on ten engineering optimization problems taken from IEEE CEC2011.
Belief Bisimulation for Hidden Markov Models Logical Characterisation and Decision Algorithm
DEFF Research Database (Denmark)
Jansen, David N.; Nielson, Flemming; Zhang, Lijun
2012-01-01
This paper establishes connections between logical equivalences and bisimulation relations for hidden Markov models (HMM). Both standard and belief state bisimulations are considered. We also present decision algorithms for the bisimilarities. For standard bisimilarity, an extension of the usual...... partition refinement algorithm is enough. Belief bisimilarity, being a relation on the continuous space of belief states, cannot be described directly. Instead, we show how to generate a linear equation system in time cubic in the number of states....
Identification of chaotic systems with hidden variables (modified Bock's algorithm)
International Nuclear Information System (INIS)
Bezruchko, Boris P.; Smirnov, Dmitry A.; Sysoev, Ilya V.
2006-01-01
We address the problem of estimating parameters of chaotic dynamical systems from a time series in a situation when some of state variables are not observed and/or the data are very noisy. Using specially developed quantitative criteria, we compare performance of the original multiple shooting approach (Bock's algorithm) and its modified version. The latter is shown to be significantly superior for long chaotic time series. In particular, it allows to obtain accurate estimates for much worse starting guesses for the estimated parameters
Enhanced Map-Matching Algorithm with a Hidden Markov Model for Mobile Phone Positioning
Directory of Open Access Journals (Sweden)
An Luo
2017-10-01
Full Text Available Numerous map-matching techniques have been developed to improve positioning, using Global Positioning System (GPS data and other sensors. However, most existing map-matching algorithms process GPS data with high sampling rates, to achieve a higher correct rate and strong universality. This paper introduces a novel map-matching algorithm based on a hidden Markov model (HMM for GPS positioning and mobile phone positioning with a low sampling rate. The HMM is a statistical model well known for providing solutions to temporal recognition applications such as text and speech recognition. In this work, the hidden Markov chain model was built to establish a map-matching process, using the geometric data, the topologies matrix of road links in road network and refined quad-tree data structure. HMM-based map-matching exploits the Viterbi algorithm to find the optimized road link sequence. The sequence consists of hidden states in the HMM model. The HMM-based map-matching algorithm is validated on a vehicle trajectory using GPS and mobile phone data. The results show a significant improvement in mobile phone positioning and high and low sampling of GPS data.
Hidden Broad Line Seyfert 2 Galaxies in the CfA and 12micron Samples
Tran, Hien D.
2001-01-01
We report the results of a spectropolarimetric survey of the CfA and 12micron samples of Seyfert 2 galaxies (S2s). Polarized (hidden) broad line regions (HBLRs) are confirmed in a number of galaxies, and several new cases (F02581-1136, MCG -3-58-7, NGC 5995, NGC 6552, NGC 7682) are reported. The 12micron S2 sample shows a significantly higher incidence of HBLR (50%) than its CfA counterpart (30%), suggesting that the latter may be incomplete in hidden AGNs. Compared to the non-HBLR S2s, the H...
Two Methods for Antialiased Wireframe Drawing with Hidden Line Removal
DEFF Research Database (Denmark)
Bærentzen, Jakob Andreas; Munk-Lund, Steen; Gjøl, Mikkel
2008-01-01
Two novel and robust techniques for wireframe drawing are proposed. Neither suffer from the well-known artifacts associated with the standard two pass, offset based techniques for wireframe drawing. Both methods draw prefiltered lines and produce high-quality antialiased results without super...
ALFA: an automated line fitting algorithm
Wesson, R.
2016-03-01
I present the automated line fitting algorithm, ALFA, a new code which can fit emission line spectra of arbitrary wavelength coverage and resolution, fully automatically. In contrast to traditional emission line fitting methods which require the identification of spectral features suspected to be emission lines, ALFA instead uses a list of lines which are expected to be present to construct a synthetic spectrum. The parameters used to construct the synthetic spectrum are optimized by means of a genetic algorithm. Uncertainties are estimated using the noise structure of the residuals. An emission line spectrum containing several hundred lines can be fitted in a few seconds using a single processor of a typical contemporary desktop or laptop PC. I show that the results are in excellent agreement with those measured manually for a number of spectra. Where discrepancies exist, the manually measured fluxes are found to be less accurate than those returned by ALFA. Together with the code NEAT, ALFA provides a powerful way to rapidly extract physical information from observations, an increasingly vital function in the era of highly multiplexed spectroscopy. The two codes can deliver a reliable and comprehensive analysis of very large data sets in a few hours with little or no user interaction.
Hidden Broad-line Regions in Seyfert 2 Galaxies: From the Spectropolarimetric Perspective
International Nuclear Information System (INIS)
Du, Pu; Wang, Jian-Min; Zhang, Zhi-Xiang
2017-01-01
The hidden broad-line regions (BLRs) in Seyfert 2 galaxies, which display broad emission lines (BELs) in their polarized spectra, are a key piece of evidence in support of the unified model for active galactic nuclei (AGNs). However, the detailed kinematics and geometry of hidden BLRs are still not fully understood. The virial factor obtained from reverberation mapping of type 1 AGNs may be a useful diagnostic of the nature of hidden BLRs in type 2 objects. In order to understand the hidden BLRs, we compile six type 2 objects from the literature with polarized BELs and dynamical measurements of black hole masses. All of them contain pseudobulges. We estimate their virial factors, and find the average value is 0.60 and the standard deviation is 0.69, which agree well with the value of type 1 AGNs with pseudobulges. This study demonstrates that (1) the geometry and kinematics of BLR are similar in type 1 and type 2 AGNs of the same bulge type (pseudobulges), and (2) the small values of virial factors in Seyfert 2 galaxies suggest that, similar to type 1 AGNs, BLRs tend to be very thick disks in type 2 objects.
Energy Technology Data Exchange (ETDEWEB)
Ichikawa, Kohei; Ueda, Yoshihiro [Department of Astronomy, Kyoto University, Kitashirakawa-Oiwake-cho, Sakyo-ku, Kyoto 606-8502 (Japan); Packham, Christopher; Lopez-Rodriguez, Enrique; Alsip, Crystal D. [Department of Physics and Astronomy, University of Texas at San Antonio, One UTSA Circle, San Antonio, TX 78249 (United States); Almeida, Cristina Ramos; Ramos, Andrés Asensio; González-Martín, Omaira [Instituto de Astrofísica de Canarias, C/Vía Láctea, s/n, E-38205 La Laguna, Tenerife (Spain); Alonso-Herrero, Almudena [Instituto de Física de Cantabria, CSIC-Universidad de Cantabria, E-39005 Santander (Spain); Díaz-Santos, Tanio [Spitzer Science Center, California Institute of Technology, MS 220-6, Pasadena, CA 91125 (United States); Elitzur, Moshe [Department of Physics and Astronomy, University of Kentucky, Lexington, KY 40506-0055 (United States); Hönig, Sebastian F. [School of Physics and Astronomy, University of Southampton, Southampton SO17 1BJ (United Kingdom); Imanishi, Masatoshi [Subaru Telescope, 650 North A’ohoku Place, Hilo, HI 96720 (United States); Levenson, Nancy A. [Gemini Observatory, Southern Operations Center, c/o AURA, Casilla 603, La Serena (Chile); Mason, Rachel E. [Gemini Observatory, Northern Operations Center, 670 N. A’ohoku Place, Hilo, HI 96720 (United States); Perlman, Eric S., E-mail: ichikawa@kusastro.kyoto-u.ac.jp [Department of Physics and Space Sciences, 150 W. University Blvd., Florida Institute of Technology, Melbourne, FL 32901 (United States)
2015-04-20
We present results from the fitting of infrared (IR) spectral energy distributions of 21 active galactic nuclei (AGNs) with clumpy torus models. We compiled high spatial resolution (∼0.3–0.7 arcsec) mid-IR (MIR) N-band spectroscopy, Q-band imaging, and nuclear near- and MIR photometry from the literature. Combining these nuclear near- and MIR observations, far-IR photometry, and clumpy torus models enables us to put constraints on the torus properties and geometry. We divide the sample into three types according to the broad line region (BLR) properties: type-1s, type-2s with scattered or hidden broad line region (HBLR) previously observed, and type-2s without any published HBLR signature (NHBLR). Comparing the torus model parameters gives us the first quantitative torus geometrical view for each subgroup. We find that NHBLR AGNs have smaller torus opening angles and larger covering factors than HBLR AGNs. This suggests that the chance to observe scattered (polarized) flux from the BLR in NHBLR could be reduced by the dual effects of (a) less scattering medium due to the reduced scattering volume given the small torus opening angle and (b) the increased torus obscuration between the observer and the scattering region. These effects give a reasonable explanation for the lack of observed HBLR in some type-2 AGNs.
Time series segmentation: a new approach based on Genetic Algorithm and Hidden Markov Model
Toreti, A.; Kuglitsch, F. G.; Xoplaki, E.; Luterbacher, J.
2009-04-01
The subdivision of a time series into homogeneous segments has been performed using various methods applied to different disciplines. In climatology, for example, it is accompanied by the well-known homogenization problem and the detection of artificial change points. In this context, we present a new method (GAMM) based on Hidden Markov Model (HMM) and Genetic Algorithm (GA), applicable to series of independent observations (and easily adaptable to autoregressive processes). A left-to-right hidden Markov model, estimating the parameters and the best-state sequence, respectively, with the Baum-Welch and Viterbi algorithms, was applied. In order to avoid the well-known dependence of the Baum-Welch algorithm on the initial condition, a Genetic Algorithm was developed. This algorithm is characterized by mutation, elitism and a crossover procedure implemented with some restrictive rules. Moreover the function to be minimized was derived following the approach of Kehagias (2004), i.e. it is the so-called complete log-likelihood. The number of states was determined applying a two-fold cross-validation procedure (Celeux and Durand, 2008). Being aware that the last issue is complex, and it influences all the analysis, a Multi Response Permutation Procedure (MRPP; Mielke et al., 1981) was inserted. It tests the model with K+1 states (where K is the state number of the best model) if its likelihood is close to K-state model. Finally, an evaluation of the GAMM performances, applied as a break detection method in the field of climate time series homogenization, is shown. 1. G. Celeux and J.B. Durand, Comput Stat 2008. 2. A. Kehagias, Stoch Envir Res 2004. 3. P.W. Mielke, K.J. Berry, G.W. Brier, Monthly Wea Rev 1981.
Intense gamma-ray lines from hidden vector dark matter decay
Energy Technology Data Exchange (ETDEWEB)
Arina, Chiara; Hambye, Thomas [Universite Libre de Bruxelles (Belgium). Service de Physique Theorique; Ibarra, Alejandro [Technische Univ. Muenchen, Garching (Germany). Physik-Department; Weniger, Christoph [Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany)
2009-12-15
Scenarios with hidden, spontaneously broken, non-abelian gauge groups contain a natural dark matter candidate, the hidden vector, whose longevity is due to an accidental custodial symmetry in the renormalizable Lagrangian. Nevertheless, non-renormalizable dimension six operators break the custodial symmetry and induce the decay of the dark matter particle at cosmological times. We discuss in this paper the cosmic ray signatures of this scenario and we show that the decay of hidden vector dark matter particles generically produce an intense gamma ray line which could be observed by the Fermi-LAT experiment, if the scale of custodial symmetry breaking is close to the Grand Unification scale. This gamma line proceeds directly from a tree level dark matter 2-body decay in association with a Higgs boson. Within this model we also perform a determination of the relic density constraints taking into account the dark matter annihilation processes with one dark matter particle in the final state. The corresponding direct detection rates can be easily of order the current experimental sensitivities. (orig.)
Intense gamma-ray lines from hidden vector dark matter decay
International Nuclear Information System (INIS)
Arina, Chiara; Hambye, Thomas
2009-12-01
Scenarios with hidden, spontaneously broken, non-abelian gauge groups contain a natural dark matter candidate, the hidden vector, whose longevity is due to an accidental custodial symmetry in the renormalizable Lagrangian. Nevertheless, non-renormalizable dimension six operators break the custodial symmetry and induce the decay of the dark matter particle at cosmological times. We discuss in this paper the cosmic ray signatures of this scenario and we show that the decay of hidden vector dark matter particles generically produce an intense gamma ray line which could be observed by the Fermi-LAT experiment, if the scale of custodial symmetry breaking is close to the Grand Unification scale. This gamma line proceeds directly from a tree level dark matter 2-body decay in association with a Higgs boson. Within this model we also perform a determination of the relic density constraints taking into account the dark matter annihilation processes with one dark matter particle in the final state. The corresponding direct detection rates can be easily of order the current experimental sensitivities. (orig.)
Intense gamma-ray lines from hidden vector dark matter decay
International Nuclear Information System (INIS)
Arina, Chiara; Hambye, Thomas; Ibarra, Alejandro; Weniger, Christoph
2010-01-01
Scenarios with hidden, spontaneously broken, non-abelian gauge groups contain a natural dark matter candidate, the hidden vector, whose longevity is due to an accidental custodial symmetry in the renormalizable Lagrangian. Nevertheless, non-renormalizable dimension six operators break the custodial symmetry and induce the decay of the dark matter particle at cosmological times. We discuss in this paper the cosmic ray signatures of this scenario and we show that the decay of hidden vector dark matter particles generically produce an intense gamma ray line which could be observed by the Fermi-LAT experiment, if the scale of custodial symmetry breaking is close to the Grand Unification scale. This gamma line proceeds directly from a tree level dark matter 2-body decay in association with a Higgs boson. Within this model we also perform a determination of the relic density constraints taking into account the dark matter annihilation processes with one dark matter particle in the final state. The corresponding direct detection rates can be easily of order the current experimental sensitivities
Line-breaking algorithm enhancement in inverse typesetting paradigma
Directory of Open Access Journals (Sweden)
Jan Přichystal
2007-01-01
Full Text Available High quality text preparing using computer desktop publishing systems usually uses line-breaking algorithm which cannot make provision for line heights and typeset paragraph accurately when composition width, page break, line index or other object appears. This article deals with enhancing of line-breaking algorithm based on optimum-fit algorithm. This algorithm is enhanced with calculation of immediate typesetting width and thus solves problem of forced change. Line-breaking algorithm enhancement causes expansion potentialities of high-quality typesetting in cases that have not been yet covered with present typesetting systems.
An Efficient Algorithm for Modelling Duration in Hidden Markov Models, with a Dramatic Application
DEFF Research Database (Denmark)
Hauberg, Søren; Sloth, Jakob
2008-01-01
For many years, the hidden Markov model (HMM) has been one of the most popular tools for analysing sequential data. One frequently used special case is the left-right model, in which the order of the hidden states is known. If knowledge of the duration of a state is available it is not possible...... to represent it explicitly with an HMM. Methods for modelling duration with HMM's do exist (Rabiner in Proc. IEEE 77(2):257---286, [1989]), but they come at the price of increased computational complexity. Here we present an efficient and robust algorithm for modelling duration in HMM's, and this algorithm...
On-Line Algorithms and Reverse Mathematics
Harris, Seth
In this thesis, we classify the reverse-mathematical strength of sequential problems. If we are given a problem P of the form ∀X(alpha(X) → ∃Zbeta(X,Z)) then the corresponding sequential problem, SeqP, asserts the existence of infinitely many solutions to P: ∀X(∀nalpha(Xn) → ∃Z∀nbeta(X n,Zn)). P is typically provable in RCA0 if all objects involved are finite. SeqP, however, is only guaranteed to be provable in ACA0. In this thesis we exactly characterize which sequential problems are equivalent to RCA0, WKL0, or ACA0.. We say that a problem P is solvable by an on-line algorithm if P can be solved according to a two-player game, played by Alice and Bob, in which Bob has a winning strategy. Bob wins the game if Alice's sequence of plays 〈a0, ..., ak〉 and Bob's sequence of responses 〈 b0, ..., bk〉 constitute a solution to P. Formally, an on-line algorithm A is a function that inputs an admissible sequence of plays 〈a 0, b0, ..., aj〉 and outputs a new play bj for Bob. (This differs from the typical definition of "algorithm", though quite often a concrete set of instructions can be easily deduced from A.). We show that SeqP is provable in RCA0 precisely when P is solvable by an on-line algorithm. Schmerl proved this result specifically for the graph coloring problem; we generalize Schmerl's result to any problem that is on-line solvable. To prove our separation, we introduce a principle called Predictk(r) that is equivalent to -WKL0 for standard k, r.. We show that WKL0 is sufficient to prove SeqP precisely when P has a solvable closed kernel. This means that a solution exists, and each initial segment of this solution is a solution to the corresponding initial segment of the problem. (Certain bounding conditions are necessary as well.) If no such solution exists, then SeqP is equivalent to ACA0 over RCA 0 + ISigma02; RCA0 alone suffices if only sequences of standard length are considered. We use different techniques from Schmerl to prove
The Hidden Flow Structure and Metric Space of Network Embedding Algorithms Based on Random Walks.
Gu, Weiwei; Gong, Li; Lou, Xiaodan; Zhang, Jiang
2017-10-13
Network embedding which encodes all vertices in a network as a set of numerical vectors in accordance with it's local and global structures, has drawn widespread attention. Network embedding not only learns significant features of a network, such as the clustering and linking prediction but also learns the latent vector representation of the nodes which provides theoretical support for a variety of applications, such as visualization, link prediction, node classification, and recommendation. As the latest progress of the research, several algorithms based on random walks have been devised. Although those algorithms have drawn much attention for their high scores in learning efficiency and accuracy, there is still a lack of theoretical explanation, and the transparency of those algorithms has been doubted. Here, we propose an approach based on the open-flow network model to reveal the underlying flow structure and its hidden metric space of different random walk strategies on networks. We show that the essence of embedding based on random walks is the latent metric structure defined on the open-flow network. This not only deepens our understanding of random- walk-based embedding algorithms but also helps in finding new potential applications in network embedding.
The Different Nature in Seyfert 2 Galaxies With and Without Hidden Broad-Line Regions
Wu, Yu-Zhong; Zhang, En-Peng; Liang, Yan-Chun; Zhang, Cheng-Min; Zhao, Yong-Heng
2011-01-01
We compile a large sample of 120 Seyfert 2 galaxies (Sy2s) which contains 49 hidden broad-line region (HBLR) Sy2s and 71 non-HBLR Sy2s. From the difference in the power sources between two groups, we test if HBLR Sy2s are dominated by active galactic nuclei (AGNs), and if non-HBLR Sy2s are dominated by starbursts. We show that: (1) HBLR Sy2s have larger accretion rates than non-HBLR Sy2s; (2) HBLR Sy2s have larger \\Nev $\\lambda 14.32$/\\Neii $\\lambda 12.81$ and \\oiv $\\lambda 25.89$/\\Neii $\\lam...
A novel line segment detection algorithm based on graph search
Zhao, Hong-dan; Liu, Guo-ying; Song, Xu
2018-02-01
To overcome the problem of extracting line segment from an image, a method of line segment detection was proposed based on the graph search algorithm. After obtaining the edge detection result of the image, the candidate straight line segments are obtained in four directions. For the candidate straight line segments, their adjacency relationships are depicted by a graph model, based on which the depth-first search algorithm is employed to determine how many adjacent line segments need to be merged. Finally we use the least squares method to fit the detected straight lines. The comparative experimental results verify that the proposed algorithm has achieved better results than the line segment detector (LSD).
An efficient algorithm for the detection of exposed and hidden wormhole attack
International Nuclear Information System (INIS)
Khan, Z.A.; Rehman, S.U.; Islam, M.H.
2016-01-01
MANETs (Mobile Ad Hoc Networks) are slowly integrating into our everyday lives, their most prominent uses are visible in the disaster and war struck areas where physical infrastructure is almost impossible or very hard to build. MANETs like other networks are facing the threat of malicious users and their activities. A number of attacks have been identified but the most severe of them is the wormhole attack which has the ability to succeed even in case of encrypted traffic and secure networks. Once wormhole is launched successfully, the severity increases by the fact that attackers can launch other attacks too. This paper presents a comprehensive algorithm for the detection of exposed as well as hidden wormhole attack while keeping the detection rate to maximum and at the same reducing false alarms. The algorithm does not require any extra hardware, time synchronization or any special type of nodes. The architecture consists of the combination of Routing Table, RTT (Round Trip Time) and RSSI (Received Signal Strength Indicator) for comprehensive detection of wormhole attack. The proposed technique is robust, light weight, has low resource requirements and provides real-time detection against the wormhole attack. Simulation results show that the algorithm is able to provide a higher detection rate, packet delivery ratio, negligible false alarms and is also better in terms of Ease of Implementation, Detection Accuracy/ Speed and processing overhead. (author)
Using hidden Markov models to deal with availability bias on line transect surveys.
Borchers, D L; Zucchini, W; Heide-Jørgensen, M P; Cañadas, A; Langrock, R
2013-09-01
We develop estimators for line transect surveys of animals that are stochastically unavailable for detection while within detection range. The detection process is formulated as a hidden Markov model with a binary state-dependent observation model that depends on both perpendicular and forward distances. This provides a parametric method of dealing with availability bias when estimates of availability process parameters are available even if series of availability events themselves are not. We apply the estimators to an aerial and a shipboard survey of whales, and investigate their properties by simulation. They are shown to be more general and more flexible than existing estimators based on parametric models of the availability process. We also find that methods using availability correction factors can be very biased when surveys are not close to being instantaneous, as can estimators that assume temporal independence in availability when there is temporal dependence. © 2013, The International Biometric Society.
An algorithm for on-line price discrimination
D.D.B. van Bragt; D.J.A. Somefun (Koye); E. Kutschinski; J.A. La Poutré (Han)
2002-01-01
textabstractThe combination of on-line dynamic pricing with price discrimination can be very beneficial for firms operating on the Internet. We therefore develop an on-line dynamic pricing algorithm that can adjust the price schedule for a good or service on behalf of a firm. This algorithm (a
Directory of Open Access Journals (Sweden)
Jesse Robert Zaneveld
2014-08-01
Full Text Available Complex symbioses between animal or plant hosts and their associated microbiotas can involve thousands of species and millions of genes. Because of the number of interacting partners, it is often impractical to study all organisms or genes in these host-microbe symbioses individually. Yet new phylogenetic predictive methods can use the wealth of accumulated data on diverse model organisms to make inferences into the properties of less well-studied species and gene families. Predictive functional profiling methods use evolutionary models based on the properties of studied relatives to put bounds on the likely characteristics of an organism or gene that has not yet been studied in detail. These techniques have been applied to predict diverse features of host-associated microbial communities ranging from the enzymatic function of uncharacterized genes to the gene content of uncultured microorganisms. We consider these phylogenetically-informed predictive techniques from disparate fields as examples of a general class of algorithms for Hidden State Prediction (HSP, and argue that HSP methods have broad value in predicting organismal traits in a variety of contexts, including the study of complex host-microbe symbioses.
Zaneveld, Jesse R R; Thurber, Rebecca L V
2014-01-01
Complex symbioses between animal or plant hosts and their associated microbiotas can involve thousands of species and millions of genes. Because of the number of interacting partners, it is often impractical to study all organisms or genes in these host-microbe symbioses individually. Yet new phylogenetic predictive methods can use the wealth of accumulated data on diverse model organisms to make inferences into the properties of less well-studied species and gene families. Predictive functional profiling methods use evolutionary models based on the properties of studied relatives to put bounds on the likely characteristics of an organism or gene that has not yet been studied in detail. These techniques have been applied to predict diverse features of host-associated microbial communities ranging from the enzymatic function of uncharacterized genes to the gene content of uncultured microorganisms. We consider these phylogenetically informed predictive techniques from disparate fields as examples of a general class of algorithms for Hidden State Prediction (HSP), and argue that HSP methods have broad value in predicting organismal traits in a variety of contexts, including the study of complex host-microbe symbioses.
Reliable Line Matching Algorithm for Stereo Images with Topological Relationship
Directory of Open Access Journals (Sweden)
WANG Jingxue
2017-11-01
Full Text Available Because of the lack of relationships between matching line and adjacent lines in the process of individual line matching, and the weak reliability of the individual line descriptor facing on discontinue texture, this paper presents a reliable line matching algorithm for stereo images with topological relationship. The algorithm firstly generates grouped line pairs from lines extracted from the reference image and searching image according to the basic topological relationships such as distance and angle between the lines. Then it takes the grouped line pairs as matching primitives, and matches these grouped line pairs by using epipolar constraint, homography constraint, quadrant constraint and gray correlation constraint of irregular triangle in order. And finally, it resolves the corresponding line pairs into two pairs of corresponding individual lines, and obtains one to one matching results after the post-processing of integrating, fitting, and checking. This paper adopts digital aerial images and close-range images with typical texture features to deal with the parameter analysis and line matching, and the experiment results demonstrate that the proposed algorithm in this paper can obtain reliable line matching results.
Phase Grouping Line Extraction Algorithm Using Overlapped Partition
Directory of Open Access Journals (Sweden)
WANG Jingxue
2015-07-01
Full Text Available Aiming at solving the problem of fracture at the discontinuities area and the challenges of line fitting in each partition, an innovative line extraction algorithm is proposed based on phase grouping using overlapped partition. The proposed algorithm adopted dual partition steps, which will generate overlapped eight partitions. Between the two steps, the middle axis in the first step coincides with the border lines in the other step. Firstly, the connected edge points that share the same phase gradients are merged into the line candidates, and fitted into line segments. Then to remedy the break lines at the border areas, the break segments in the second partition steps are refitted. The proposed algorithm is robust and does not need any parameter tuning. Experiments with various datasets have confirmed that the method is not only capable of handling the linear features, but also powerful enough in handling the curve features.
A Novel Entropy-Based Decoding Algorithm for a Generalized High-Order Discrete Hidden Markov Model
Directory of Open Access Journals (Sweden)
Jason Chin-Tiong Chan
2018-01-01
Full Text Available The optimal state sequence of a generalized High-Order Hidden Markov Model (HHMM is tracked from a given observational sequence using the classical Viterbi algorithm. This classical algorithm is based on maximum likelihood criterion. We introduce an entropy-based Viterbi algorithm for tracking the optimal state sequence of a HHMM. The entropy of a state sequence is a useful quantity, providing a measure of the uncertainty of a HHMM. There will be no uncertainty if there is only one possible optimal state sequence for HHMM. This entropy-based decoding algorithm can be formulated in an extended or a reduction approach. We extend the entropy-based algorithm for computing the optimal state sequence that was developed from a first-order to a generalized HHMM with a single observational sequence. This extended algorithm performs the computation exponentially with respect to the order of HMM. The computational complexity of this extended algorithm is due to the growth of the model parameters. We introduce an efficient entropy-based decoding algorithm that used reduction approach, namely, entropy-based order-transformation forward algorithm (EOTFA to compute the optimal state sequence of any generalized HHMM. This EOTFA algorithm involves a transformation of a generalized high-order HMM into an equivalent first-order HMM and an entropy-based decoding algorithm is developed based on the equivalent first-order HMM. This algorithm performs the computation based on the observational sequence and it requires OTN~2 calculations, where N~ is the number of states in an equivalent first-order model and T is the length of observational sequence.
A Novel Assembly Line Balancing Method Based on PSO Algorithm
Directory of Open Access Journals (Sweden)
Xiaomei Hu
2014-01-01
Full Text Available Assembly line is widely used in manufacturing system. Assembly line balancing problem is a crucial question during design and management of assembly lines since it directly affects the productivity of the whole manufacturing system. The model of assembly line balancing problem is put forward and a general optimization method is proposed. The key data on assembly line balancing problem is confirmed, and the precedence relations diagram is described. A double objective optimization model based on takt time and smoothness index is built, and balance optimization scheme based on PSO algorithm is proposed. Through the simulation experiments of examples, the feasibility and validity of the assembly line balancing method based on PSO algorithm is proved.
An ultrafast line-by-line algorithm for calculating spectral transmittance and radiance
International Nuclear Information System (INIS)
Tan, X.
2013-01-01
An ultrafast line-by-line algorithm for calculating spectral transmittance and radiance of gases is presented. The algorithm is based on fast convolution of the Voigt line profile using Fourier transform and a binning technique. The algorithm breaks a radiative transfer calculation into two steps: a one-time pre-computation step in which a set of pressure independent coefficients are computed using the spectral line information; a normal calculation step in which the Fourier transform coefficients of the optical depth are calculated using the line of sight information and the coefficients pre-computed in the first step, the optical depth is then calculated using an inverse Fourier transform and the spectral transmittance and radiance are calculated. The algorithm is significantly faster than line-by-line algorithms that do not employ special speedup techniques by a factor of 10 3 –10 6 . A case study of the 2.7 μm band of H 2 O vapor is presented. -- Highlights: •An ultrafast line-by-line model based on FFT and a binning technique is presented. •Computationally expensive calculations are factored out into a pre-computation step. •It is 10 3 –10 8 times faster than LBL algorithms that do not employ speedup techniques. •Good agreement with experimental data for the 2.7 μm band of H 2 O
Noise propagation in iterative reconstruction algorithms with line searches
International Nuclear Information System (INIS)
Qi, Jinyi
2003-01-01
In this paper we analyze the propagation of noise in iterative image reconstruction algorithms. We derive theoretical expressions for the general form of preconditioned gradient algorithms with line searches. The results are applicable to a wide range of iterative reconstruction problems, such as emission tomography, transmission tomography, and image restoration. A unique contribution of this paper comparing to our previous work [1] is that the line search is explicitly modeled and we do not use the approximation that the gradient of the objective function is zero. As a result, the error in the estimate of noise at early iterations is significantly reduced
Document localization algorithms based on feature points and straight lines
Skoryukina, Natalya; Shemiakina, Julia; Arlazarov, Vladimir L.; Faradjev, Igor
2018-04-01
The important part of the system of a planar rectangular object analysis is the localization: the estimation of projective transform from template image of an object to its photograph. The system also includes such subsystems as the selection and recognition of text fields, the usage of contexts etc. In this paper three localization algorithms are described. All algorithms use feature points and two of them also analyze near-horizontal and near- vertical lines on the photograph. The algorithms and their combinations are tested on a dataset of real document photographs. Also the method of localization quality estimation is proposed that allows configuring the localization subsystem independently of the other subsystems quality.
Lining seam elimination algorithm and surface crack detection in concrete tunnel lining
Qu, Zhong; Bai, Ling; An, Shi-Quan; Ju, Fang-Rong; Liu, Ling
2016-11-01
Due to the particularity of the surface of concrete tunnel lining and the diversity of detection environments such as uneven illumination, smudges, localized rock falls, water leakage, and the inherent seams of the lining structure, existing crack detection algorithms cannot detect real cracks accurately. This paper proposed an algorithm that combines lining seam elimination with the improved percolation detection algorithm based on grid cell analysis for surface crack detection in concrete tunnel lining. First, check the characteristics of pixels within the overlapping grid to remove the background noise and generate the percolation seed map (PSM). Second, cracks are detected based on the PSM by the accelerated percolation algorithm so that the fracture unit areas can be scanned and connected. Finally, the real surface cracks in concrete tunnel lining can be obtained by removing the lining seam and performing percolation denoising. Experimental results show that the proposed algorithm can accurately, quickly, and effectively detect the real surface cracks. Furthermore, it can fill the gap in the existing concrete tunnel lining surface crack detection by removing the lining seam.
An optimal algorithm for preemptive on-line scheduling
Chen, B.; Vliet, van A.; Woeginger, G.J.
1995-01-01
We investigate the problem of on-line scheduling jobs on m identical parallel machines where preemption is allowed. The goal is to minimize the makespan. We derive an approximation algorithm with worst-case guarantee mm/(mm - (m - 1)m) for every m 2, which increasingly tends to e/(e - 1) ˜ 1.58 as m
Padilla-Frausto, Imelda D; Wallace, Steven P
2015-08-01
More than three-quarters of a million (772,000) older Californians are among the "hidden poor"--older adults with incomes above the federal poverty line (FPL) but below a minimally decent standard of living as determined by the Elder Economic Security Standard™ Index (Elder Index) in 2011. This policy brief uses the most recent Elder Index calculations to document the wide discrepancy that exists between the FPL and the Elder Index. This study finds that the FPL significantly underestimates the number of economically insecure older adults who are unable to make ends meet. Yet, because many public assistance programs are aligned with the FPL, potentially hundreds of thousands of economically insecure older Californians are denied aid. The highest rates of the hidden poor among older adults are found among renters, Latinos, women, those who are raising grandchildren, and people in the oldest age groups. Raising the income and asset eligibility requirement thresholds for social support programs such as Supplemental Security Income (SSI), housing, health care, and food assistance would help California's older hidden poor make ends meet.
Generalization of some hidden subgroup algorithms for input sets of arbitrary size
Poslu, Damla; Say, A. C. Cem
2006-05-01
We consider the problem of generalizing some quantum algorithms so that they will work on input domains whose cardinalities are not necessarily powers of two. When analyzing the algorithms we assume that generating superpositions of arbitrary subsets of basis states whose cardinalities are not necessarily powers of two perfectly is possible. We have taken Ballhysa's model as a template and have extended it to Chi, Kim and Lee's generalizations of the Deutsch-Jozsa algorithm and to Simon's algorithm. With perfectly equal superpositions of input sets of arbitrary size, Chi, Kim and Lee's generalized Deutsch-Jozsa algorithms, both for evenly-distributed and evenly-balanced functions, worked with one-sided error property. For Simon's algorithm the success probability of the generalized algorithm is the same as that of the original for input sets of arbitrary cardinalities with equiprobable superpositions, since the property that the measured strings are all those which have dot product zero with the string we search, for the case where the function is 2-to-1, is not lost.
Using a Quadtree Algorithm To Assess Line of Sight
Gonzalez, Joseph; Chamberlain, Robert; Tailor, Eric; Gutt, Gary
2006-01-01
A matched pair of computer algorithms determines whether line of sight (LOS) is obstructed by terrain. These algorithms were originally designed for use in conjunction with combat-simulation software in military training exercises, but could also be used for such commercial purposes as evaluating lines of sight for antennas or determining what can be seen from a "room with a view." The quadtree preparation algorithm operates on an array of digital elevation data and only needs to be run once for a terrain region, which can be quite large. Relatively little computation time is needed, as each elevation value is considered only one and one-third times. The LOS assessment algorithm uses that quadtree to answer LOS queries. To determine whether LOS is obstructed, a piecewise-planar (or higher-order) terrain skin is computationally draped over the digital elevation data. Adjustments are made to compensate for curvature of the Earth and for refraction of the LOS by the atmosphere. Average computing time appears to be proportional to the number of queries times the logarithm of the number of elevation data points. Accuracy is as high as is possible for the available elevation data, and symmetric results are assured. In the simulation, the LOS query program runs as a separate process, thereby making more random-access memory available for other computations.
A Two-Channel Training Algorithm for Hidden Markov Model and Its Application to Lip Reading
Directory of Open Access Journals (Sweden)
Foo Say Wei
2005-01-01
Full Text Available Hidden Markov model (HMM has been a popular mathematical approach for sequence classification such as speech recognition since 1980s. In this paper, a novel two-channel training strategy is proposed for discriminative training of HMM. For the proposed training strategy, a novel separable-distance function that measures the difference between a pair of training samples is adopted as the criterion function. The symbol emission matrix of an HMM is split into two channels: a static channel to maintain the validity of the HMM and a dynamic channel that is modified to maximize the separable distance. The parameters of the two-channel HMM are estimated by iterative application of expectation-maximization (EM operations. As an example of the application of the novel approach, a hierarchical speaker-dependent visual speech recognition system is trained using the two-channel HMMs. Results of experiments on identifying a group of confusable visemes indicate that the proposed approach is able to increase the recognition accuracy by an average of 20% compared with the conventional HMMs that are trained with the Baum-Welch estimation.
Directory of Open Access Journals (Sweden)
Trong-Ngoc Le
2016-01-01
Full Text Available Objective. Our objective is to develop a computerized scheme for liver tumor segmentation in MR images. Materials and Methods. Our proposed scheme consists of four main stages. Firstly, the region of interest (ROI image which contains the liver tumor region in the T1-weighted MR image series was extracted by using seed points. The noise in this ROI image was reduced and the boundaries were enhanced. A 3D fast marching algorithm was applied to generate the initial labeled regions which are considered as teacher regions. A single hidden layer feedforward neural network (SLFN, which was trained by a noniterative algorithm, was employed to classify the unlabeled voxels. Finally, the postprocessing stage was applied to extract and refine the liver tumor boundaries. The liver tumors determined by our scheme were compared with those manually traced by a radiologist, used as the “ground truth.” Results. The study was evaluated on two datasets of 25 tumors from 16 patients. The proposed scheme obtained the mean volumetric overlap error of 27.43% and the mean percentage volume error of 15.73%. The mean of the average surface distance, the root mean square surface distance, and the maximal surface distance were 0.58 mm, 1.20 mm, and 6.29 mm, respectively.
Eliminating harmonics in line to line voltage using genetic algorithm using multilevel inverter
Energy Technology Data Exchange (ETDEWEB)
Gunasekaran, R. [Excel College of Engineering and Technology, Komarapalayam (India). Electrical and Electronics Engineering; Karthikeyan, C. [K.S. Rangasamy College of Engineering, Tamil Nadu (India). Electrical and Electronics Engineering
2017-04-15
In this project the total harmonic distortion (THD) minimization of the multilevel inverters output voltage is discussed. The approach in reducing harmonics contents in inverters output voltage is THD elimination. The switching angles are varied with the fundamental frequency so the output THD is minimized. In three phase applications, the line voltage harmonics are of the main concern from the load point of view. Using a genetic algorithm, a THD minimization process is directly applied to the line to line voltage of the inverter. Genetic (GA) algorithm allows the determination of the optimized parameters and consequently an optimal operating point of the circuit and a wide pass band with a unity gain is obtained.
Simoncini, Valeria
2016-01-01
Focusing on special matrices and matrices which are in some sense "near" to structured matrices, this volume covers a broad range of topics of current interest in numerical linear algebra. Exploitation of these less obvious structural properties can be of great importance in the design of efficient numerical methods, for example algorithms for matrices with low-rank block structure, matrices with decay, and structured tensor computations. Applications range from quantum chemistry to queuing theory. Structured matrices arise frequently in applications. Examples include banded and sparse matrices, Toeplitz-type matrices, and matrices with semi-separable or quasi-separable structure, as well as Hamiltonian and symplectic matrices. The associated literature is enormous, and many efficient algorithms have been developed for solving problems involving such matrices. The text arose from a C.I.M.E. course held in Cetraro (Italy) in June 2015 which aimed to present this fast growing field to young researchers, exploit...
Parallel field line and stream line tracing algorithms for space physics applications
Toth, G.; de Zeeuw, D.; Monostori, G.
2004-05-01
Field line and stream line tracing is required in various space physics applications, such as the coupling of the global magnetosphere and inner magnetosphere models, the coupling of the solar energetic particle and heliosphere models, or the modeling of comets, where the multispecies chemical equations are solved along stream lines of a steady state solution obtained with single fluid MHD model. Tracing a vector field is an inherently serial process, which is difficult to parallelize. This is especially true when the data corresponding to the vector field is distributed over a large number of processors. We designed algorithms for the various applications, which scale well to a large number of processors. In the first algorithm the computational domain is divided into blocks. Each block is on a single processor. The algorithm folows the vector field inside the blocks, and calculates a mapping of the block surfaces. The blocks communicate the values at the coinciding surfaces, and the results are interpolated. Finally all block surfaces are defined and values inside the blocks are obtained. In the second algorithm all processors start integrating along the vector field inside the accessible volume. When the field line leaves the local subdomain, the position and other information is stored in a buffer. Periodically the processors exchange the buffers, and continue integration of the field lines until they reach a boundary. At that point the results are sent back to the originating processor. Efficiency is achieved by a careful phasing of computation and communication. In the third algorithm the results of a steady state simulation are stored on a hard drive. The vector field is contained in blocks. All processors read in all the grid and vector field data and the stream lines are integrated in parallel. If a stream line enters a block, which has already been integrated, the results can be interpolated. By a clever ordering of the blocks the execution speed can be
A New Algorithm for Identifying Cis-Regulatory Modules Based on Hidden Markov Model
Directory of Open Access Journals (Sweden)
Haitao Guo
2017-01-01
Full Text Available The discovery of cis-regulatory modules (CRMs is the key to understanding mechanisms of transcription regulation. Since CRMs have specific regulatory structures that are the basis for the regulation of gene expression, how to model the regulatory structure of CRMs has a considerable impact on the performance of CRM identification. The paper proposes a CRM discovery algorithm called ComSPS. ComSPS builds a regulatory structure model of CRMs based on HMM by exploring the rules of CRM transcriptional grammar that governs the internal motif site arrangement of CRMs. We test ComSPS on three benchmark datasets and compare it with five existing methods. Experimental results show that ComSPS performs better than them.
A New Algorithm for Identifying Cis-Regulatory Modules Based on Hidden Markov Model
2017-01-01
The discovery of cis-regulatory modules (CRMs) is the key to understanding mechanisms of transcription regulation. Since CRMs have specific regulatory structures that are the basis for the regulation of gene expression, how to model the regulatory structure of CRMs has a considerable impact on the performance of CRM identification. The paper proposes a CRM discovery algorithm called ComSPS. ComSPS builds a regulatory structure model of CRMs based on HMM by exploring the rules of CRM transcriptional grammar that governs the internal motif site arrangement of CRMs. We test ComSPS on three benchmark datasets and compare it with five existing methods. Experimental results show that ComSPS performs better than them. PMID:28497059
A novel seizure detection algorithm informed by hidden Markov model event states
Baldassano, Steven; Wulsin, Drausin; Ung, Hoameng; Blevins, Tyler; Brown, Mesha-Gay; Fox, Emily; Litt, Brian
2016-06-01
Objective. Recently the FDA approved the first responsive, closed-loop intracranial device to treat epilepsy. Because these devices must respond within seconds of seizure onset and not miss events, they are tuned to have high sensitivity, leading to frequent false positive stimulations and decreased battery life. In this work, we propose a more robust seizure detection model. Approach. We use a Bayesian nonparametric Markov switching process to parse intracranial EEG (iEEG) data into distinct dynamic event states. Each event state is then modeled as a multidimensional Gaussian distribution to allow for predictive state assignment. By detecting event states highly specific for seizure onset zones, the method can identify precise regions of iEEG data associated with the transition to seizure activity, reducing false positive detections associated with interictal bursts. The seizure detection algorithm was translated to a real-time application and validated in a small pilot study using 391 days of continuous iEEG data from two dogs with naturally occurring, multifocal epilepsy. A feature-based seizure detector modeled after the NeuroPace RNS System was developed as a control. Main results. Our novel seizure detection method demonstrated an improvement in false negative rate (0/55 seizures missed versus 2/55 seizures missed) as well as a significantly reduced false positive rate (0.0012 h versus 0.058 h-1). All seizures were detected an average of 12.1 ± 6.9 s before the onset of unequivocal epileptic activity (unequivocal epileptic onset (UEO)). Significance. This algorithm represents a computationally inexpensive, individualized, real-time detection method suitable for implantable antiepileptic devices that may considerably reduce false positive rate relative to current industry standards.
International Nuclear Information System (INIS)
Chi, Dong Pyo; Kim, Jeong San; Lee, Soojoon
2006-01-01
We consider the hidden subgroup problem on the semi-direct product of cyclic groups Z N -bar Z p , where p is a prime that does not divide p j -1 for any of the prime factors p j of N, and show that the hidden subgroup problem can be reduced to other ones for which solutions are already known
On-line Certification for All: The PINVOX Algorithm
Directory of Open Access Journals (Sweden)
E Canessa
2012-09-01
Full Text Available A protoype algorithm: PINVOX (“Personal Identification Number by Voice" for on-line certification is introduced to guarantee that scholars have followed, i.e., listened and watched, a complete recorded lecture with the option of earning a certificate or diploma of completion after remotely attending courses. It is based on the injection of unique, randomly selected and pre-recorded integer numbers (or single letters or words within the audio trace of a video stream at places where silence is automatically detected. The certificate of completion or “virtual attendance” is generated on-the-fly after the successful identification of the embedded PINVOX code by a video viewer student.
An Improved Seeding Algorithm of Magnetic Flux Lines Based on Data in 3D Space
Directory of Open Access Journals (Sweden)
Jia Zhong
2015-05-01
Full Text Available This paper will propose an approach to increase the accuracy and efficiency of seeding algorithms of magnetic flux lines in magnetic field visualization. To obtain accurate and reliable visualization results, the density of the magnetic flux lines should map the magnetic induction intensity, and seed points should determine the density of the magnetic flux lines. However, the traditional seeding algorithm, which is a statistical algorithm based on data, will produce errors when computing magnetic flux through subdivision of the plane. To achieve higher accuracy, more subdivisions should be made, which will reduce efficiency. This paper analyzes the errors made when the traditional seeding algorithm is used and gives an improved algorithm. It then validates the accuracy and efficiency of the improved algorithm by comparing the results of the two algorithms with results from the equivalent magnetic flux algorithm.
Kizilkaya, Elif A.; Gupta, Surendra M.
2005-11-01
In this paper, we compare the impact of different disassembly line balancing (DLB) algorithms on the performance of our recently introduced Dynamic Kanban System for Disassembly Line (DKSDL) to accommodate the vagaries of uncertainties associated with disassembly and remanufacturing processing. We consider a case study to illustrate the impact of various DLB algorithms on the DKSDL. The approach to the solution, scenario settings, results and the discussions of the results are included.
Catheter Calibration Using Template Matching Line Interpolation Algorithm
National Research Council Canada - National Science Library
Nagy, L
2001-01-01
..., such as: image resolution, type of the calibration, algorithm used for contour detection, size of the FOV, other parameters of the image The studied calibration method is the one using catheter size...
A parallel line sieve for the GNFS Algorithm
Sameh Daoud; Ibrahim Gad
2014-01-01
RSA is one of the most important public key cryptosystems for information security. The security of RSA depends on Integer factorization problem, it relies on the difficulty of factoring large integers. Much research has gone into problem of factoring a large number. Due to advances in factoring algorithms and advances in computing hardware the size of the number that can be factorized increases exponentially year by year. The General Number Field Sieve algorithm (GNFS) is currently the best ...
Algorithms for the on-line travelling salesman
Ausiello, G.; Feuerstein, E.; Leonardi, S.; Stougie, L.; Talamo, M.
1999-01-01
In this paper the problem of efficiently serving a sequence of requests presented in an on-line fashion located at points of a metric space is considered. We call this problem the On-Line Travelling Salesman Problem (OLTSP). It has a variety of relevant applications in logistics and robotics. We
An Algorithm to Compress Line-transition Data for Radiative-transfer Calculations
Cubillos, Patricio E.
2017-11-01
Molecular line-transition lists are an essential ingredient for radiative-transfer calculations. With recent databases now surpassing the billion-line mark, handling them has become computationally prohibitive, due to both the required processing power and memory. Here I present a temperature-dependent algorithm to separate strong from weak line transitions, reformatting the large majority of the weaker lines into a cross-section data file, and retaining the detailed line-by-line information of the fewer strong lines. For any given molecule over the 0.3-30 μm range, this algorithm reduces the number of lines to a few million, enabling faster radiative-transfer computations without a significant loss of information. The final compression rate depends on how densely populated the spectrum is. I validate this algorithm by comparing Exomol’s HCN extinction-coefficient spectra between the complete (65 million line transitions) and compressed (7.7 million) line lists. Over the 0.6-33 μm range, the average difference between extinction-coefficient values is less than 1%. A Python/C implementation of this algorithm is open-source and available at https://github.com/pcubillos/repack. So far, this code handles the Exomol and HITRAN line-transition format.
Ecodriver. D23.2: Simulation and analysis document for on-line vehicle algorithms
Seewald, P.; Orfila, O.; Saintpierre, G.
2014-01-01
This deliverable reports on the simulations and analysis of the on-line vehicle algorithms as well as the ecoDriver Android application. The simulation and field test results give an impression of how the algorithms will perform in the real world trials in SP3. Thus, it is possible to apply
Solving radiative transfer with line overlaps using Gauss-Seidel algorithms
Daniel, F.; Cernicharo, J.
2008-09-01
Context: The improvement in observational facilities requires refining the modelling of the geometrical structures of astrophysical objects. Nevertheless, for complex problems such as line overlap in molecules showing hyperfine structure, a detailed analysis still requires a large amount of computing time and thus, misinterpretation cannot be dismissed due to an undersampling of the whole space of parameters. Aims: We extend the discussion of the implementation of the Gauss-Seidel algorithm in spherical geometry and include the case of hyperfine line overlap. Methods: We first review the basics of the short characteristics method that is used to solve the radiative transfer equations. Details are given on the determination of the Lambda operator in spherical geometry. The Gauss-Seidel algorithm is then described and, by analogy to the plan-parallel case, we see how to introduce it in spherical geometry. Doing so requires some approximations in order to keep the algorithm competitive. Finally, line overlap effects are included. Results: The convergence speed of the algorithm is compared to the usual Jacobi iterative schemes. The gain in the number of iterations is typically factors of 2 and 4 for the two implementations made of the Gauss-Seidel algorithm. This is obtained despite the introduction of approximations in the algorithm. A comparison of results obtained with and without line overlaps for N2H^+, HCN, and HNC shows that the J=3-2 line intensities are significantly underestimated in models where line overlap is neglected.
Directory of Open Access Journals (Sweden)
Diamantidis A. C.
2004-01-01
Full Text Available In this study, the buffer allocation problem (BAP in homogeneous, asymptotically reliable serial production lines is considered. A known aggregation method, given by Lim, Meerkov, and Top (1990, for the performance evaluation (i.e., estimation of throughput of this type of production lines when the buffer allocation is known, is used as an evaluative method in conjunction with a newly developed dynamic programming (DP algorithm for the BAP. The proposed algorithm is applied to production lines where the number of machines is varying from four up to a hundred machines. The proposed algorithm is fast because it reduces the volume of computations by rejecting allocations that do not lead to maximization of the line's throughput. Numerical results are also given for large production lines.
Cebiroglu, Gökhan; Horst, Ulrich
2012-01-01
We cross-sectionally analyze the presence of aggregated hidden depth and trade volume in the S&P 500 and identify its key determinants. We find that the spread is the main predictor for a stock’s hidden dimension, both in terms of traded and posted liquidity. Our findings moreover suggest that large hidden orders are associated with larger transaction costs, higher price impact and increased volatility. In particular, as large hidden orders fail to attract (latent) liquidity to the market, hi...
Localization of hidden Chua's attractors
International Nuclear Information System (INIS)
Leonov, G.A.; Kuznetsov, N.V.; Vagaitsev, V.I.
2011-01-01
The classical attractors of Lorenz, Rossler, Chua, Chen, and other widely-known attractors are those excited from unstable equilibria. From computational point of view this allows one to use numerical method, in which after transient process a trajectory, started from a point of unstable manifold in the neighborhood of equilibrium, reaches an attractor and identifies it. However there are attractors of another type: hidden attractors, a basin of attraction of which does not contain neighborhoods of equilibria. In the present Letter for localization of hidden attractors of Chua's circuit it is suggested to use a special analytical-numerical algorithm. -- Highlights: → There are hidden attractors: basin doesn't contain neighborhoods of equilibria. → Hidden attractors cannot be reached by trajectory from neighborhoods of equilibria. → We suggested special procedure for localization of hidden attractors. → We discovered hidden attractor in Chua's system, L. Chua in his work didn't expect this.
Verification test for on-line diagnosis algorithm based on noise analysis
International Nuclear Information System (INIS)
Tamaoki, T.; Naito, N.; Tsunoda, T.; Sato, M.; Kameda, A.
1980-01-01
An on-line diagnosis algorithm was developed and its verification test was performed using a minicomputer. This algorithm identifies the plant state by analyzing various system noise patterns, such as power spectral densities, coherence functions etc., in three procedure steps. Each obtained noise pattern is examined by using the distances from its reference patterns prepared for various plant states. Then, the plant state is identified by synthesizing each result with an evaluation weight. This weight is determined automatically from the reference noise patterns prior to on-line diagnosis. The test was performed with 50 MW (th) Steam Generator noise data recorded under various controller parameter values. The algorithm performance was evaluated based on a newly devised index. The results obtained with one kind of weight showed the algorithm efficiency under the proper selection of noise patterns. Results for another kind of weight showed the robustness of the algorithm to this selection. (orig.)
Microscope self-calibration based on micro laser line imaging and soft computing algorithms
Apolinar Muñoz Rodríguez, J.
2018-06-01
A technique to perform microscope self-calibration via micro laser line and soft computing algorithms is presented. In this technique, the microscope vision parameters are computed by means of soft computing algorithms based on laser line projection. To implement the self-calibration, a microscope vision system is constructed by means of a CCD camera and a 38 μm laser line. From this arrangement, the microscope vision parameters are represented via Bezier approximation networks, which are accomplished through the laser line position. In this procedure, a genetic algorithm determines the microscope vision parameters by means of laser line imaging. Also, the approximation networks compute the three-dimensional vision by means of the laser line position. Additionally, the soft computing algorithms re-calibrate the vision parameters when the microscope vision system is modified during the vision task. The proposed self-calibration improves accuracy of the traditional microscope calibration, which is accomplished via external references to the microscope system. The capability of the self-calibration based on soft computing algorithms is determined by means of the calibration accuracy and the micro-scale measurement error. This contribution is corroborated by an evaluation based on the accuracy of the traditional microscope calibration.
Efficient algorithm for generating spectra using line-by-line methods
International Nuclear Information System (INIS)
Sonnad, V.; Iglesias, C.A.
2011-01-01
A method is presented for efficient generation of spectra using line-by-line approaches. The only approximation is replacing the line shape function with an interpolation procedure, which makes the method independent of the line profile functional form. The resulting computational savings for large number of lines is proportional to the number of frequency points in the spectral range. Therefore, for large-scale problems the method can provide speedups of two orders of magnitude or more. A method was presented to generate line-by-line spectra efficiently. The first step was to replace the explicit calculation of the profile by the Newton divided-differences interpolating polynomial. The second step is to accumulate the lines effectively reducing their number to the number of frequency points. The final step is recognizing the resulting expression as a convolution and amenable to FFT methods. The reduction in computational effort for a configuration-to-configuration transition array with large number of lines is proportional to the number of frequency points. The method involves no approximations except for replacing the explicit profile evaluation by interpolation. Specifically, the line accumulation and convolution are exact given the interpolation procedure. Furthermore, the interpolation makes the method independent of the line profile functional form contrary to other schemes using FFT methods to generate line-by-line spectra but relying on the analytic form of the profile Fourier transform. Finally, the method relies on a uniform frequency mesh. For non-uniform frequency meshes, however, the method can be applied by using a suitable temporary uniform mesh and the results interpolated onto the final mesh with little additional cost.
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 ...
A Novel Assembly Line Scheduling Algorithm Based on CE-PSO
Directory of Open Access Journals (Sweden)
Xiaomei Hu
2015-01-01
Full Text Available With the widespread application of assembly line in enterprises, assembly line scheduling is an important problem in the production since it directly affects the productivity of the whole manufacturing system. The mathematical model of assembly line scheduling problem is put forward and key data are confirmed. A double objective optimization model based on equipment utilization and delivery time loss is built, and optimization solution strategy is described. Based on the idea of solution strategy, assembly line scheduling algorithm based on CE-PSO is proposed to overcome the shortcomings of the standard PSO. Through the simulation experiments of two examples, the validity of the assembly line scheduling algorithm based on CE-PSO is proved.
Directory of Open Access Journals (Sweden)
Zoran N. Milivojevic
2011-09-01
Full Text Available The paper introduces a testing framework for the evaluation and validation of text line segmentation algorithms. Text line segmentation represents the key action for correct optical character recognition. Many of the tests for the evaluation of text line segmentation algorithms deal with text databases as reference templates. Because of the mismatch, the reliable testing framework is required. Hence, a new approach to a comprehensive experimental framework for the evaluation of text line segmentation algorithms is proposed. It consists of synthetic multi-like text samples and real handwritten text as well. Although the tests are mutually independent, the results are cross-linked. The proposed method can be used for different types of scripts and languages. Furthermore, two different procedures for the evaluation of algorithm efficiency based on the obtained error type classification are proposed. The first is based on the segmentation line error description, while the second one incorporates well-known signal detection theory. Each of them has different capabilities and convenience, but they can be used as supplements to make the evaluation process efficient. Overall the proposed procedure based on the segmentation line error description has some advantages, characterized by five measures that describe measurement procedures.
International Nuclear Information System (INIS)
Ghoudjehbaklou, H.; Danai, B.
2001-01-01
Reactive power dispatch for voltage profile modification has been of interest to power utilities. Usually local bus voltages can be altered by changing generator voltages, reactive shunts, ULTC transformers and SVCs. Determination of optimum values for control parameters, however, is not simple for modern power system networks. Heuristic and rather intelligent algorithms have to be sought. In this paper a new algorithm is proposed that is based on a variant of a genetic algorithm combined with simulated annealing updates. In this algorithm a fuzzy multi-objective a approach is used for the fitness function of the genetic algorithm. This fuzzy multi-objective function can efficiently modify the voltage profile in order to minimize transmission lines losses, thus reducing the operating costs. The reason for such a combination is to utilize the best characteristics of each method and overcome their deficiencies. The proposed algorithm is much faster than the classical genetic algorithm and cna be easily integrated into existing power utilities software. The proposed algorithm is tested on an actual system model of 1284 buses, 799 lines, 1175 fixed and ULTC transformers, 86 generators, 181 controllable shunts and 425 loads
Hybrid phase retrieval algorithm for solving the twin image problem in in-line digital holography
Zhao, Jie; Wang, Dayong; Zhang, Fucai; Wang, Yunxin
2010-10-01
For the reconstruction in the in-line digital holography, there are three terms overlapping with each other on the image plane, named the zero order term, the real image and the twin image respectively. The unwanted twin image degrades the real image seriously. A hybrid phase retrieval algorithm is presented to address this problem, which combines the advantages of two popular phase retrieval algorithms. One is the improved version of the universal iterative algorithm (UIA), called the phase flipping-based UIA (PFB-UIA). The key point of this algorithm is to flip the phase of the object iteratively. It is proved that the PFB-UIA is able to find the support of the complicated object. Another one is the Fienup algorithm, which is a kind of well-developed algorithm and uses the support of the object as the constraint among the iteration procedure. Thus, by following the Fienup algorithm immediately after the PFB-UIA, it is possible to produce the amplitude and the phase distributions of the object with high fidelity. The primary simulated results showed that the proposed algorithm is powerful for solving the twin image problem in the in-line digital holography.
An on-line modified least-mean-square algorithm for training neurofuzzy controllers.
Tan, Woei Wan
2007-04-01
The problem hindering the use of data-driven modelling methods for training controllers on-line is the lack of control over the amount by which the plant is excited. As the operating schedule determines the information available on-line, the knowledge of the process may degrade if the setpoint remains constant for an extended period. This paper proposes an identification algorithm that alleviates "learning interference" by incorporating fuzzy theory into the normalized least-mean-square update rule. The ability of the proposed methodology to achieve faster learning is examined by employing the algorithm to train a neurofuzzy feedforward controller for controlling a liquid level process. Since the proposed identification strategy has similarities with the normalized least-mean-square update rule and the recursive least-square estimator, the on-line learning rates of these algorithms are also compared.
Implementations of PI-line based FBP and BPF algorithms on GPGPU
Energy Technology Data Exchange (ETDEWEB)
Shen, Le [Tsinghua Univ., Beijing (China). Dept. of Engineering Physics; Xing, Yuxiang [Tsinghua Univ., Beijing (China). Dept. of Engineering Physics; Ministry of Education, Beijing (China). Key Lab. of Particle and Radiation Imaging
2011-07-01
Exact reconstruction is under the spotlight in cone beam CT. Katsevich put forward the first exact inversion formula for helical cone beam CT, which belongs to FBP type. Also, Pan Xiaochuan's group proposed another PI-line based exact reconstruction algorithm of BPF type. These two exact reconstruction algorithms and their derivative forms have been widely studied. In this paper, we present a different way of selecting PI-line segments appropriate for both Katsevich's FBP and Pan Xiaochuan's BPF algorithms. As 3D reconstruction contributes to massive computations and takes long time, people have made efforts to speed up the algorithms with the help of multi-core CPUs and GPGPU (General Purpose Graphics Processing Unit). In this paper, we also presents implementations for these two algorithms on GPGPU using an innovative way of selecting PI-line segments. Acceleration techniques and implementations are addressed in detail. The methods are tested on the Shepp-Logan phantom. Compared with our CPU's implementations, the accelerated algorithms on GPGPU are tens to hundreds times faster. (orig.)
On-line reconstruction algorithms for the CBM and ALICE experiments
International Nuclear Information System (INIS)
Gorbunov, Sergey
2013-01-01
This thesis presents various algorithms which have been developed for on-line event reconstruction in the CBM experiment at GSI, Darmstadt and the ALICE experiment at CERN, Geneve. Despite the fact that the experiments are different - CBM is a fixed target experiment with forward geometry, while ALICE has a typical collider geometry - they share common aspects when reconstruction is concerned. The thesis describes: - general modifications to the Kalman filter method, which allows one to accelerate, to improve, and to simplify existing fit algorithms; - developed algorithms for track fit in CBM and ALICE experiment, including a new method for track extrapolation in non-homogeneous magnetic field. - developed algorithms for primary and secondary vertex fit in the both experiments. In particular, a new method of reconstruction of decayed particles is presented. - developed parallel algorithm for the on-line tracking in the CBM experiment. - developed parallel algorithm for the on-line tracking in High Level Trigger of the ALICE experiment. - the realisation of the track finders on modern hardware, such as SIMD CPU registers and GPU accelerators. All the presented methods have been developed by or with the direct participation of the author.
A Line Search Multilevel Truncated Newton Algorithm for Computing the Optical Flow
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Lluís Garrido
2015-06-01
Full Text Available We describe the implementation details and give the experimental results of three optimization algorithms for dense optical flow computation. In particular, using a line search strategy, we evaluate the performance of the unilevel truncated Newton method (LSTN, a multiresolution truncated Newton (MR/LSTN and a full multigrid truncated Newton (FMG/LSTN. We use three image sequences and four models of optical flow for performance evaluation. The FMG/LSTN algorithm is shown to lead to better optical flow estimation with less computational work than both the LSTN and MR/LSTN algorithms.
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Djoni Haryadi Setiabudi
2001-01-01
Full Text Available Hidden surface removal is an algorithm used to hide part of the object which is blocked by the object in front of it. If there are two plane crossed each other displayed without Hidden surface removal algorithm, the crossing section is invisible, because one object will block another object without crossing. The crossing sections can be displayed using Hidden surface removal algorithm. Z buffer algorithm implements Hidden Surface Removal by entering color and depth of the visible plane into the buffer, then displays the result on the screen. Scan Line algorithm will scanning the screen row by row of each object surface in three dimension and then displays on the screen after each row scanning. Both of the algorithms will be compared based on the memory usage dan time needed to execute. The experiment shows that Scanline algorithm uses less memory compared with Z-Buffer algoritm. Furthermore, based on the speed, the Scanline is better than the Z-Buffer if the object is collected on the y row, but the Z-Buffer is better than the Scanline if the object scattered and used all rows on the drawing plane and has more surface do displayed. Abstract in Bahasa Indonesia : Hidden surface removal adalah suatu algoritma yang digunakan untuk menghilangkan penampilan bagian yang tertutup oleh objek yang didepannya. Apabila ada dua bidang yang berpotongan, apabila ditampilkan biasa tanpa menggunakan algoritma Hidden surface removal maka bagian yang berpotongan itu akan tidak kelihatan, oleh karena bidang yang satu ditutupi oleh bagian yang lain tanpa memotong. Oleh karena itu untuk menampilkan bidang perpotongan, diperlukan Algoritma Hidden surface removal. Algoritma Z buffer melaksanakan proses Hidden Surface Removal dengan memasukkan warna dan kedalaman bidang permukaan yang tampak ke dalam buffer, dan kemudian setelah selesai hasilnya ditampilkan ke layar. Algoritma Scan Line melakukan scanning untuk setiap baris dari layar bidang gambar untuk setiap
A Fast Inspection of Tool Electrode and Drilling Depth in EDM Drilling by Detection Line Algorithm.
Huang, Kuo-Yi
2008-08-21
The purpose of this study was to develop a novel measurement method using a machine vision system. Besides using image processing techniques, the proposed system employs a detection line algorithm that detects the tool electrode length and drilling depth of a workpiece accurately and effectively. Different boundaries of areas on the tool electrode are defined: a baseline between base and normal areas, a ND-line between normal and drilling areas (accumulating carbon area), and a DD-line between drilling area and dielectric fluid droplet on the electrode tip. Accordingly, image processing techniques are employed to extract a tool electrode image, and the centroid, eigenvector, and principle axis of the tool electrode are determined. The developed detection line algorithm (DLA) is then used to detect the baseline, ND-line, and DD-line along the direction of the principle axis. Finally, the tool electrode length and drilling depth of the workpiece are estimated via detected baseline, ND-line, and DD-line. Experimental results show good accuracy and efficiency in estimation of the tool electrode length and drilling depth under different conditions. Hence, this research may provide a reference for industrial application in EDM drilling measurement.
Line Balancing Using Largest Candidate Rule Algorithm In A Garment Industry: A Case Study
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V. P.Jaganathan
2014-12-01
Full Text Available The emergence of fast changes in fashion has given rise to the need to shorten production cycle times in the garment industry. As effective usage of resources has a significant effect on the productivity and efficiency of production operations, garment manufacturers are urged to utilize their resources effectively in order to meet dynamic customer demand. This paper focuses specifically on line balancing and layout modification. The aim of assembly line balance in sewing lines is to assign tasks to the workstations, so that the machines of the workstation can perform the assigned tasks with a balanced loading. Largest Candidate Rule Algorithm (LCR has been deployed in this paper.
Motion Vector Estimation Using Line-Square Search Block Matching Algorithm for Video Sequences
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Guo Bao-long
2004-09-01
Full Text Available Motion estimation and compensation techniques are widely used for video coding applications but the real-time motion estimation is not easily achieved due to its enormous computations. In this paper, a new fast motion estimation algorithm based on line search is presented, in which computation complexity is greatly reduced by using the line search strategy and a parallel search pattern. Moreover, the accurate search is achieved because the small square search pattern is used. It has a best-case scenario of only 9 search points, which is 4 search points less than the diamond search algorithm. Simulation results show that, compared with the previous techniques, the LSPS algorithm significantly reduces the computational requirements for finding motion vectors, and also produces close performance in terms of motion compensation errors.
Distinguishing Hidden Markov Chains
Kiefer, Stefan; Sistla, A. Prasad
2015-01-01
Hidden Markov Chains (HMCs) are commonly used mathematical models of probabilistic systems. They are employed in various fields such as speech recognition, signal processing, and biological sequence analysis. We consider the problem of distinguishing two given HMCs based on an observation sequence that one of the HMCs generates. More precisely, given two HMCs and an observation sequence, a distinguishing algorithm is expected to identify the HMC that generates the observation sequence. Two HM...
A fast, robust algorithm for power line interference cancellation in neural recording
Keshtkaran, Mohammad Reza; Yang, Zhi
2014-04-01
Objective. Power line interference may severely corrupt neural recordings at 50/60 Hz and harmonic frequencies. The interference is usually non-stationary and can vary in frequency, amplitude and phase. To retrieve the gamma-band oscillations at the contaminated frequencies, it is desired to remove the interference without compromising the actual neural signals at the interference frequency bands. In this paper, we present a robust and computationally efficient algorithm for removing power line interference from neural recordings. Approach. The algorithm includes four steps. First, an adaptive notch filter is used to estimate the fundamental frequency of the interference. Subsequently, based on the estimated frequency, harmonics are generated by using discrete-time oscillators, and then the amplitude and phase of each harmonic are estimated by using a modified recursive least squares algorithm. Finally, the estimated interference is subtracted from the recorded data. Main results. The algorithm does not require any reference signal, and can track the frequency, phase and amplitude of each harmonic. When benchmarked with other popular approaches, our algorithm performs better in terms of noise immunity, convergence speed and output signal-to-noise ratio (SNR). While minimally affecting the signal bands of interest, the algorithm consistently yields fast convergence (30 dB) in different conditions of interference strengths (input SNR from -30 to 30 dB), power line frequencies (45-65 Hz) and phase and amplitude drifts. In addition, the algorithm features a straightforward parameter adjustment since the parameters are independent of the input SNR, input signal power and the sampling rate. A hardware prototype was fabricated in a 65 nm CMOS process and tested. Software implementation of the algorithm has been made available for open access at https://github.com/mrezak/removePLI. Significance. The proposed algorithm features a highly robust operation, fast adaptation to
Cellular Genetic Algorithm with Communicating Grids for Assembly Line Balancing Problems
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BRUDARU, O.
2010-05-01
Full Text Available This paper presents a new approach with cellular multigrid genetic algorithms for the "I"-shaped and "U"-shaped assembly line balancing problems, including parallel workstations and compatibility constraints. First, a cellular hybrid genetic algorithm that uses a single grid is described. Appropriate operators for mutation, hypermutation, and crossover and two devoration techniques are proposed for creating and maintaining groups based on similarity. This monogrid algorithm is extended for handling many populations placed on different grids. In the multigrid version, the population of each grid is organized in clusters using the positional information of the chromosomes. A similarity preserving communication protocol between the clusters placed on different grids is introduced. The experimental evaluation shows that the multigrid cellular genetic algorithm with communicating grids is better than the hybrid genetic algorithm used for building it, whereas it dominates the monogrid version in all cases. Absolute performance is evaluated using classical benchmarks. The role of certain components of the cellular algorithm is explained and the effect of some parameters is evaluated.
Determination of edge plasma parameters by a genetic algorithm analysis of spectral line shapes
International Nuclear Information System (INIS)
Marandet, Y.; Genesio, P.; Godbert-Mouret, L.; Koubiti, M.; Stamm, R.; Capes, H.; Guirlet, R.
2003-01-01
Comparing an experimental and a theoretical line shape can be achieved by a genetic algorithm (GA) based on an analogy to the mechanisms of natural selection. Such an algorithm is able to deal with complex non-linear models, and can avoid local minima. We have used this optimization tool in the context of edge plasma spectroscopy, for a determination of the temperatures and fractions of the various populations of neutral deuterium emitting the D α line in 2 configurations of Tore-Supra: ergodic divertor and toroidal pumped limiter. Using the GA fit, the neutral emitters are separated into up to 4 populations which can be identified as resulting from molecular dissociation reactions, charge exchange, or reflection. In all the edge plasmas studied, a significant fraction of neutrals emit in the line wings, leading to neutrals with a temperature up to a few hundreds eV if a Gaussian line shape is assumed. This conclusion could be modified if the line wing exhibits a non Gaussian behavior
Determination of edge plasma parameters by a genetic algorithm analysis of spectral line shapes
Energy Technology Data Exchange (ETDEWEB)
Marandet, Y.; Genesio, P.; Godbert-Mouret, L.; Koubiti, M.; Stamm, R. [Universite de Provence (PIIM), Centre de Saint-Jerome, 13 - Marseille (France); Capes, H.; Guirlet, R. [Association Euratom-CEA Cadarache, 13 - Saint-Paul-lez-Durance (France). Dept. de Recherches sur la Fusion Controlee
2003-07-01
Comparing an experimental and a theoretical line shape can be achieved by a genetic algorithm (GA) based on an analogy to the mechanisms of natural selection. Such an algorithm is able to deal with complex non-linear models, and can avoid local minima. We have used this optimization tool in the context of edge plasma spectroscopy, for a determination of the temperatures and fractions of the various populations of neutral deuterium emitting the D{sub {alpha}} line in 2 configurations of Tore-Supra: ergodic divertor and toroidal pumped limiter. Using the GA fit, the neutral emitters are separated into up to 4 populations which can be identified as resulting from molecular dissociation reactions, charge exchange, or reflection. In all the edge plasmas studied, a significant fraction of neutrals emit in the line wings, leading to neutrals with a temperature up to a few hundreds eV if a Gaussian line shape is assumed. This conclusion could be modified if the line wing exhibits a non Gaussian behavior.
Improving the Power Quality in Tehran Metro Line-Two Using the Ant Colony Algorithm
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H. Ehteshami
2017-12-01
Full Text Available This research aims to survey the improvement of power quality in Tehran metro line 2 using the ant colony algorithm and to investigate all the factors affecting the achievement of this goal. In order to put Tehran on the road of sustainable development, finding a solution for dealing with air pollution is essential. The use of public transportation, especially metro, is one of the ways to achieve this goal. Since the highest share of pollutants in Tehran belongs to cars and mobile sources, relative statistical indicators are estimated through assuming the effect of metro lines development and subsequently reduction of traffic on power quality index.
A Weighing Algorithm for Checking Missing Components in a Pharmaceutical Line
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Alessandro Silvestri
2014-11-01
image. The goal of the present work is the development of an algorithm able to optimize the production line of a pharmaceutical firm. In particular, the proposed weighing procedure allows both checking missing components in packaging and minimizing false rejects of packages by dynamic scales. The main problem is the presence at the same time, in the same package, of different components with different variable weights. The consequence is uncertainty in recognizing the absence of one or more components.
Directory of Open Access Journals (Sweden)
Chae Young Lee
Full Text Available The purposes of this study were to optimize a proton computed tomography system (pCT for proton range verification and to confirm the pCT image reconstruction algorithm based on projection images generated with optimized parameters. For this purpose, we developed a new pCT scanner using the Geometry and Tracking (GEANT 4.9.6 simulation toolkit. GEANT4 simulations were performed to optimize the geometric parameters representing the detector thickness and the distance between the detectors for pCT. The system consisted of four silicon strip detectors for particle tracking and a calorimeter to measure the residual energies of the individual protons. The optimized pCT system design was then adjusted to ensure that the solution to a CS-based convex optimization problem would converge to yield the desired pCT images after a reasonable number of iterative corrections. In particular, we used a total variation-based formulation that has been useful in exploiting prior knowledge about the minimal variations of proton attenuation characteristics in the human body. Examinations performed using our CS algorithm showed that high-quality pCT images could be reconstructed using sets of 72 projections within 20 iterations and without any streaks or noise, which can be caused by under-sampling and proton starvation. Moreover, the images yielded by this CS algorithm were found to be of higher quality than those obtained using other reconstruction algorithms. The optimized pCT scanner system demonstrated the potential to perform high-quality pCT during on-line image-guided proton therapy, without increasing the imaging dose, by applying our CS based proton CT reconstruction algorithm. Further, we make our optimized detector system and CS-based proton CT reconstruction algorithm potentially useful in on-line proton therapy.
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Abhijeet Ravankar
2016-05-01
Full Text Available Line detection is an important problem in computer vision, graphics and autonomous robot navigation. Lines detected using a laser range sensor (LRS mounted on a robot can be used as features to build a map of the environment, and later to localize the robot in the map, in a process known as Simultaneous Localization and Mapping (SLAM. We propose an efficient algorithm for line detection from LRS data using a novel hopping-points Singular Value Decomposition (SVD and Hough transform-based algorithm, in which SVD is applied to intermittent LRS points to accelerate the algorithm. A reverse-hop mechanism ensures that the end points of the line segments are accurately extracted. Line segments extracted from the proposed algorithm are used to form a map and, subsequently, LRS data points are matched with the line segments to localize the robot. The proposed algorithm eliminates the drawbacks of point-based matching algorithms like the Iterative Closest Points (ICP algorithm, the performance of which degrades with an increasing number of points. We tested the proposed algorithm for mapping and localization in both simulated and real environments, and found it to detect lines accurately and build maps with good self-localization.
Improved Seam-Line Searching Algorithm for UAV Image Mosaic with Optical Flow.
Zhang, Weilong; Guo, Bingxuan; Li, Ming; Liao, Xuan; Li, Wenzhuo
2018-04-16
Ghosting and seams are two major challenges in creating unmanned aerial vehicle (UAV) image mosaic. In response to these problems, this paper proposes an improved method for UAV image seam-line searching. First, an image matching algorithm is used to extract and match the features of adjacent images, so that they can be transformed into the same coordinate system. Then, the gray scale difference, the gradient minimum, and the optical flow value of pixels in adjacent image overlapped area in a neighborhood are calculated, which can be applied to creating an energy function for seam-line searching. Based on that, an improved dynamic programming algorithm is proposed to search the optimal seam-lines to complete the UAV image mosaic. This algorithm adopts a more adaptive energy aggregation and traversal strategy, which can find a more ideal splicing path for adjacent UAV images and avoid the ground objects better. The experimental results show that the proposed method can effectively solve the problems of ghosting and seams in the panoramic UAV images.
A Line-Based Adaptive-Weight Matching Algorithm Using Loopy Belief Propagation
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Hui Li
2015-01-01
Full Text Available In traditional adaptive-weight stereo matching, the rectangular shaped support region requires excess memory consumption and time. We propose a novel line-based stereo matching algorithm for obtaining a more accurate disparity map with low computation complexity. This algorithm can be divided into two steps: disparity map initialization and disparity map refinement. In the initialization step, a new adaptive-weight model based on the linear support region is put forward for cost aggregation. In this model, the neural network is used to evaluate the spatial proximity, and the mean-shift segmentation method is used to improve the accuracy of color similarity; the Birchfield pixel dissimilarity function and the census transform are adopted to establish the dissimilarity measurement function. Then the initial disparity map is obtained by loopy belief propagation. In the refinement step, the disparity map is optimized by iterative left-right consistency checking method and segmentation voting method. The parameter values involved in this algorithm are determined with many simulation experiments to further improve the matching effect. Simulation results indicate that this new matching method performs well on standard stereo benchmarks and running time of our algorithm is remarkably lower than that of algorithm with rectangle-shaped support region.
Discrete PSO algorithm based optimization of transmission lines loading in TNEP problem
International Nuclear Information System (INIS)
Shayeghi, H.; Mahdavi, M.; Bagheri, A.
2010-01-01
Transmission network expansion planning (TNEP) is a basic part of power system planning that determines where, when and how many new transmission lines should be added to the network. Up till now, various methods have been presented to solve the static transmission network expansion planning (STNEP) problem. But in all of these methods, lines adequacy rate has not been considered at the end of planning horizon, i.e. expanded network misses adequacy after some times and needs to be expanded again. In this paper, expansion planning has been implemented by merging lines loading parameter in the STNEP and inserting investment cost into the fitness function constraints using discrete particle swarm optimization (DPSO) algorithm. Expanded network will possess a maximum adequacy to provide load demand and also the transmission lines overloaded later. The proposed idea has been tested on the Garvers network and an actual transmission network of the Azerbaijan regional electric company, Iran, and the results are compared with the decimal codification genetic algorithm (DCGA) technique. The results evaluation shows that the network will possess maximum efficiency economically. Also, it is shown that precision and convergence speed of the proposed DPSO based method for the solution of the STNEP problem is superior to DCGA approach.
International Nuclear Information System (INIS)
Shayeghi, H.; Mahdavi, M.; Bagheri, A.
2010-01-01
Static transmission network expansion planning (STNEP) problem acquires a principal role in power system planning and should be evaluated carefully. Up till now, various methods have been presented to solve the STNEP problem. But only in one of them, lines adequacy rate has been considered at the end of planning horizon and the problem has been optimized by discrete particle swarm optimization (DPSO). DPSO is a new population-based intelligence algorithm and exhibits good performance on solution of the large-scale, discrete and non-linear optimization problems like STNEP. However, during the running of the algorithm, the particles become more and more similar, and cluster into the best particle in the swarm, which make the swarm premature convergence around the local solution. In order to overcome these drawbacks and considering lines adequacy rate, in this paper, expansion planning has been implemented by merging lines loading parameter in the STNEP and inserting investment cost into the fitness function constraints using an improved DPSO algorithm. The proposed improved DPSO is a new conception, collectivity, which is based on similarity between the particle and the current global best particle in the swarm that can prevent the premature convergence of DPSO around the local solution. The proposed method has been tested on the Garver's network and a real transmission network in Iran, and compared with the DPSO based method for solution of the TNEP problem. The results show that the proposed improved DPSO based method by preventing the premature convergence is caused that with almost the same expansion costs, the network adequacy is increased considerably. Also, regarding the convergence curves of both methods, it can be seen that precision of the proposed algorithm for the solution of the STNEP problem is more than DPSO approach.
The design of the public transport lines with the use of the fast genetic algorithm
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Aleksander Król
2015-09-01
Full Text Available Background: The growing role of public transport and the pressure of economic criteria requires the new optimization tools for process of public transport planning. These problems are computationally very complex, thus it is preferable to use various approximate methods, leading to a good solution within an acceptable time. Methods: One of such method is the genetic algorithm mimicking the processes of evolution and natural selection in the nature. In this paper, the different variants of the public transport lines layout are subjected to the artificial selection. The essence of the proposed approach is a simplified method of calculating the value of the fit function for a single individual, which brings relatively short computation time even for large jobs. Results: It was shown that despite the introduced simplifications the quality of the results is not worsened. Using the data obtained from KZK GOP (Communications Municipal Association of Upper Silesian Industrial Region the described algorithm was used to optimize the layout of the network of bus lines located within the borders of Katowice. Conclusion: The proposed algorithm was applied to a real, very complex network of public transportation and a possibility of a significant improvement of its efficiency was indicated. The obtained results give hope that the presented model, after some improvements can be the basis of the scientific method, and in a consequence of a further development to find practical application.
Quantitative comparison of direct phase retrieval algorithms in in-line phase tomography
International Nuclear Information System (INIS)
Langer, Max; Cloetens, Peter; Guigay, Jean-Pierre; Peyrin, Francoise
2008-01-01
A well-known problem in x-ray microcomputed tomography is low sensitivity. Phase contrast imaging offers an increase of sensitivity of up to a factor of 10 3 in the hard x-ray region, which makes it possible to image soft tissue and small density variations. If a sufficiently coherent x-ray beam, such as that obtained from a third generation synchrotron, is used, phase contrast can be obtained by simply moving the detector downstream of the imaged object. This setup is known as in-line or propagation based phase contrast imaging. A quantitative relationship exists between the phase shift induced by the object and the recorded intensity and inversion of this relationship is called phase retrieval. Since the phase shift is proportional to projections through the three-dimensional refractive index distribution in the object, once the phase is retrieved, the refractive index can be reconstructed by using the phase as input to a tomographic reconstruction algorithm. A comparison between four phase retrieval algorithms is presented. The algorithms are based on the transport of intensity equation (TIE), transport of intensity equation for weak absorption, the contrast transfer function (CTF), and a mixed approach between the CTF and TIE, respectively. The compared methods all rely on linearization of the relationship between phase shift and recorded intensity to yield fast phase retrieval algorithms. The phase retrieval algorithms are compared using both simulated and experimental data, acquired at the European Synchrotron Radiation Facility third generation synchrotron light source. The algorithms are evaluated in terms of two different reconstruction error metrics. While being slightly less computationally effective, the mixed approach shows the best performance in terms of the chosen criteria.
Diagnostic performance of line-immunoassay based algorithms for incident HIV-1 infection
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Schüpbach Jörg
2012-04-01
Full Text Available Abstract Background Serologic testing algorithms for recent HIV seroconversion (STARHS provide important information for HIV surveillance. We have previously demonstrated that a patient's antibody reaction pattern in a confirmatory line immunoassay (INNO-LIA™ HIV I/II Score provides information on the duration of infection, which is unaffected by clinical, immunological and viral variables. In this report we have set out to determine the diagnostic performance of Inno-Lia algorithms for identifying incident infections in patients with known duration of infection and evaluated the algorithms in annual cohorts of HIV notifications. Methods Diagnostic sensitivity was determined in 527 treatment-naive patients infected for up to 12 months. Specificity was determined in 740 patients infected for longer than 12 months. Plasma was tested by Inno-Lia and classified as either incident ( Results The 10 best algorithms had a mean raw sensitivity of 59.4% and a mean specificity of 95.1%. Adjustment for overrepresentation of patients in the first quarter year of infection further reduced the sensitivity. In the preferred model, the mean adjusted sensitivity was 37.4%. Application of the 10 best algorithms to four annual cohorts of HIV-1 notifications totalling 2'595 patients yielded a mean IIR of 0.35 in 2005/6 (baseline and of 0.45, 0.42 and 0.35 in 2008, 2009 and 2010, respectively. The increase between baseline and 2008 and the ensuing decreases were highly significant. Other adjustment models yielded different absolute IIR, although the relative changes between the cohorts were identical for all models. Conclusions The method can be used for comparing IIR in annual cohorts of HIV notifications. The use of several different algorithms in combination, each with its own sensitivity and specificity to detect incident infection, is advisable as this reduces the impact of individual imperfections stemming primarily from relatively low sensitivities and
Fast intersection detection algorithm for PC-based robot off-line programming
Fedrowitz, Christian H.
1994-11-01
This paper presents a method for fast and reliable collision detection in complex production cells. The algorithm is part of the PC-based robot off-line programming system of the University of Siegen (Ropsus). The method is based on a solid model which is managed by a simplified constructive solid geometry model (CSG-model). The collision detection problem is divided in two steps. In the first step the complexity of the problem is reduced in linear time. In the second step the remaining solids are tested for intersection. For this the Simplex algorithm, which is known from linear optimization, is used. It computes a point which is common to two convex polyhedra. The polyhedra intersect, if such a point exists. Regarding the simplified geometrical model of Ropsus the algorithm runs also in linear time. In conjunction with the first step a resultant collision detection algorithm is found which requires linear time in all. Moreover it computes the resultant intersection polyhedron using the dual transformation.
Barney, D; Kokkas, P; Manthos, N; Sidiropoulos, G; Reynaud, S; Vichoudis, P
2007-01-01
The CMS Endcap Preshower (ES) sub-detector comprises 4288 silicon sensors, each containing 32 strips. The data are transferred from the detector to the counting room via 1208 optical fibres running at 800Mbps. Each fibre carries data from two, three or four sensors. For the readout of the Preshower, a VME-based system, the Endcap Preshower Data Concentrator Card (ES-DCC), is currently under development. The main objective of each readout board is to acquire on-detector data from up to 36 optical links, perform on-line data reduction via zero suppression and pass the concentrated data to the CMS event builder. This document presents the conceptual design of the Reduction Algorithms as well as their implementation in the ES-DCC FPGAs. These algorithms, as implemented in the ES-DCC, result in a data-reduction factor of 20.
Barney, David; Kokkas, Panagiotis; Manthos, Nikolaos; Reynaud, Serge; Sidiropoulos, Georgios; Vichoudis, Paschalis
2006-01-01
The CMS Endcap Preshower (ES) sub-detector comprises 4288 silicon sensors, each containing 32 strips. The data are transferred from the detector to the counting room via 1208 optical fibres running at 800Mbps. Each fibre carries data from 2, 3 or 4 sensors. For the readout of the Preshower, a VME-based system - the Endcap Preshower Data Concentrator Card (ES-DCC) is currently under development. The main objective of each readout board is to acquire on-detector data from up to 36 optical links, perform on-line data reduction (zero suppression) and pass the concentrated data to the CMS event builder. This document presents the conceptual design of the Reduction Algorithms as well as their implementation into the ES-DCC FPGAs. The algorithms implemented into the ES-DCC resulted in a reduction factor of ~20.
Regalia, Giulia; Coelli, Stefania; Biffi, Emilia; Ferrigno, Giancarlo; Pedrocchi, Alessandra
2016-01-01
Neuronal spike sorting algorithms are designed to retrieve neuronal network activity on a single-cell level from extracellular multiunit recordings with Microelectrode Arrays (MEAs). In typical analysis of MEA data, one spike sorting algorithm is applied indiscriminately to all electrode signals. However, this approach neglects the dependency of algorithms' performances on the neuronal signals properties at each channel, which require data-centric methods. Moreover, sorting is commonly performed off-line, which is time and memory consuming and prevents researchers from having an immediate glance at ongoing experiments. The aim of this work is to provide a versatile framework to support the evaluation and comparison of different spike classification algorithms suitable for both off-line and on-line analysis. We incorporated different spike sorting "building blocks" into a Matlab-based software, including 4 feature extraction methods, 3 feature clustering methods, and 1 template matching classifier. The framework was validated by applying different algorithms on simulated and real signals from neuronal cultures coupled to MEAs. Moreover, the system has been proven effective in running on-line analysis on a standard desktop computer, after the selection of the most suitable sorting methods. This work provides a useful and versatile instrument for a supported comparison of different options for spike sorting towards more accurate off-line and on-line MEA data analysis.
Practical algorithms for simulation and reconstruction of digital in-line holograms.
Latychevskaia, Tatiana; Fink, Hans-Werner
2015-03-20
Here we present practical methods for simulation and reconstruction of in-line digital holograms recorded with plane and spherical waves. The algorithms described here are applicable to holographic imaging of an object exhibiting absorption as well as phase-shifting properties. Optimal parameters, related to distances, sampling rate, and other factors for successful simulation and reconstruction of holograms are evaluated and criteria for the achievable resolution are worked out. Moreover, we show that the numerical procedures for the reconstruction of holograms recorded with plane and spherical waves are identical under certain conditions. Experimental examples of holograms and their reconstructions are also discussed.
A Nonmonotone Line Search Filter Algorithm for the System of Nonlinear Equations
Directory of Open Access Journals (Sweden)
Zhong Jin
2012-01-01
Full Text Available We present a new iterative method based on the line search filter method with the nonmonotone strategy to solve the system of nonlinear equations. The equations are divided into two groups; some equations are treated as constraints and the others act as the objective function, and the two groups are just updated at the iterations where it is needed indeed. We employ the nonmonotone idea to the sufficient reduction conditions and filter technique which leads to a flexibility and acceptance behavior comparable to monotone methods. The new algorithm is shown to be globally convergent and numerical experiments demonstrate its effectiveness.
Ecodriver. D23.1: Report on test scenarios for val-idation of on-line vehicle algorithms
Seewald, P.; Ivens, T.W.T.; Spronkmans, S.
2014-01-01
This deliverable provides a description of test scenarios that will be used for validation of WP22’s on-line vehicle algorithms. These algorithms consist of the two modules VE³ (Vehicle Energy and Environment Estimator) and RSG (Reference Signal Genera-tor) and will be tested using the
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.
Directory of Open Access Journals (Sweden)
Masoud Rabbani
2016-12-01
Full Text Available This paper deals with mixed model assembly line (MMAL balancing problem of type-I. In MMALs several products are made on an assembly line while the similarity of these products is so high. As a result, it is possible to assemble several types of products simultaneously without any additional setup times. The problem has some particular features such as parallel workstations and precedence constraints in dynamic periods in which each period also effects on its next period. The research intends to reduce the number of workstations and maximize the workload smoothness between workstations. Dynamic periods are used to determine all variables in different periods to achieve efficient solutions. A non-dominated sorting genetic algorithm (NSGA-II and multi-objective particle swarm optimization (MOPSO are used to solve the problem. The proposed model is validated with GAMS software for small size problem and the performance of the foregoing algorithms is compared with each other based on some comparison metrics. The NSGA-II outperforms MOPSO with respect to some comparison metrics used in this paper, but in other metrics MOPSO is better than NSGA-II. Finally, conclusion and future research is provided.
Wideband Impulse Modulation and Receiver Algorithms for Multiuser Power Line Communications
Directory of Open Access Journals (Sweden)
Andrea M. Tonello
2007-01-01
Full Text Available We consider a bit-interleaved coded wideband impulse-modulated system for power line communications. Impulse modulation is combined with direct-sequence code-division multiple access (DS-CDMA to obtain a form of orthogonal modulation and to multiplex the users. We focus on the receiver signal processing algorithms and derive a maximum likelihood frequency-domain detector that takes into account the presence of impulse noise as well as the intercode interference (ICI and the multiple-access interference (MAI that are generated by the frequency-selective power line channel. To reduce complexity, we propose several simplified frequency-domain receiver algorithms with different complexity and performance. We address the problem of the practical estimation of the channel frequency response as well as the estimation of the correlation of the ICI-MAI-plus-noise that is needed in the detection metric. To improve the estimators performance, a simple hard feedback from the channel decoder is also used. Simulation results show that the scheme provides robust performance as a result of spreading the symbol energy both in frequency (through the wideband pulse and in time (through the spreading code and the bit-interleaved convolutional code.
Fast algorithm for spectral processing with application to on-line welding quality assurance
Mirapeix, J.; Cobo, A.; Jaúregui, C.; López-Higuera, J. M.
2006-10-01
A new technique is presented in this paper for the analysis of welding process emission spectra to accurately estimate in real-time the plasma electronic temperature. The estimation of the electronic temperature of the plasma, through the analysis of the emission lines from multiple atomic species, may be used to monitor possible perturbations during the welding process. Unlike traditional techniques, which usually involve peak fitting to Voigt functions using the Levenberg-Marquardt recursive method, sub-pixel algorithms are used to more accurately estimate the central wavelength of the peaks. Three different sub-pixel algorithms will be analysed and compared, and it will be shown that the LPO (linear phase operator) sub-pixel algorithm is a better solution within the proposed system. Experimental tests during TIG-welding using a fibre optic to capture the arc light, together with a low cost CCD-based spectrometer, show that some typical defects associated with perturbations in the electron temperature can be easily detected and identified with this technique. A typical processing time for multiple peak analysis is less than 20 ms running on a conventional PC.
DEFF Research Database (Denmark)
Kieffer-Kristensen, Rikke; Johansen, Karen Lise Gaardsvig
2013-01-01
to participate. RESULTS: All children were affected by their parents' ABI and the altered family situation. The children's expressions led the authors to identify six themes, including fear of losing the parent, distress and estrangement, chores and responsibilities, hidden loss, coping and support. The main......PRIMARY OBJECTIVE: The purpose of this study was to listen to and learn from children showing high levels of post-traumatic stress symptoms after parental acquired brain injury (ABI), in order to achieve an in-depth understanding of the difficulties the children face in their everyday lives...... finding indicates that the children experienced numerous losses, many of which were often suppressed or neglected by the children to protect the ill parents. CONCLUSIONS: The findings indicated that the children seemed to make a special effort to hide their feelings of loss and grief in order to protect...
Barrett, Steven R. H.; Britter, Rex E.
Predicting long-term mean pollutant concentrations in the vicinity of airports, roads and other industrial sources are frequently of concern in regulatory and public health contexts. Many emissions are represented geometrically as ground-level line or area sources. Well developed modelling tools such as AERMOD and ADMS are able to model dispersion from finite (i.e. non-point) sources with considerable accuracy, drawing upon an up-to-date understanding of boundary layer behaviour. Due to mathematical difficulties associated with line and area sources, computationally expensive numerical integration schemes have been developed. For example, some models decompose area sources into a large number of line sources orthogonal to the mean wind direction, for which an analytical (Gaussian) solution exists. Models also employ a time-series approach, which involves computing mean pollutant concentrations for every hour over one or more years of meteorological data. This can give rise to computer runtimes of several days for assessment of a site. While this may be acceptable for assessment of a single industrial complex, airport, etc., this level of computational cost precludes national or international policy assessments at the level of detail available with dispersion modelling. In this paper, we extend previous work [S.R.H. Barrett, R.E. Britter, 2008. Development of algorithms and approximations for rapid operational air quality modelling. Atmospheric Environment 42 (2008) 8105-8111] to line and area sources. We introduce approximations which allow for the development of new analytical solutions for long-term mean dispersion from line and area sources, based on hypergeometric functions. We describe how these solutions can be parameterized from a single point source run from an existing advanced dispersion model, thereby accounting for all processes modelled in the more costly algorithms. The parameterization method combined with the analytical solutions for long-term mean
Combined mixed approach algorithm for in-line phase-contrast x-ray imaging
International Nuclear Information System (INIS)
De Caro, Liberato; Scattarella, Francesco; Giannini, Cinzia; Tangaro, Sabina; Rigon, Luigi; Longo, Renata; Bellotti, Roberto
2010-01-01
Purpose: In the past decade, phase-contrast imaging (PCI) has been applied to study different kinds of tissues and human body parts, with an increased improvement of the image quality with respect to simple absorption radiography. A technique closely related to PCI is phase-retrieval imaging (PRI). Indeed, PCI is an imaging modality thought to enhance the total contrast of the images through the phase shift introduced by the object (human body part); PRI is a mathematical technique to extract the quantitative phase-shift map from PCI. A new phase-retrieval algorithm for the in-line phase-contrast x-ray imaging is here proposed. Methods: The proposed algorithm is based on a mixed transfer-function and transport-of-intensity approach (MA) and it requires, at most, an initial approximate estimate of the average phase shift introduced by the object as prior knowledge. The accuracy in the initial estimate determines the convergence speed of the algorithm. The proposed algorithm retrieves both the object phase and its complex conjugate in a combined MA (CMA). Results: Although slightly less computationally effective with respect to other mixed-approach algorithms, as two phases have to be retrieved, the results obtained by the CMA on simulated data have shown that the obtained reconstructed phase maps are characterized by particularly low normalized mean square errors. The authors have also tested the CMA on noisy experimental phase-contrast data obtained by a suitable weakly absorbing sample consisting of a grid of submillimetric nylon fibers as well as on a strongly absorbing object made of a 0.03 mm thick lead x-ray resolution star pattern. The CMA has shown a good efficiency in recovering phase information, also in presence of noisy data, characterized by peak-to-peak signal-to-noise ratios down to a few dBs, showing the possibility to enhance with phase radiography the signal-to-noise ratio for features in the submillimetric scale with respect to the attenuation
Sriwana, I. K.; Marie, I. A.; Mangala, D.
2017-12-01
Kencana Gemilang, Co. is one electronics industry engaging in the manufacture sector. This company manufactures and assembles household electronic products, such as rice cooker, fan, iron, blender, etc. The company deals with an issue of underachievement of an established production target on MCM products line 1. This study aimed to calculate line efficiencies, delay times, and initial line smoothness indexes. The research was carried out by means of depicting a precedence diagram and gathering time data of each work element followed by examination and calculation of standard time as well as line balancing using methods of Moodie Young and Generics Algorithm. Based on results of calculation, better line balancing than the existing initial conditions, i.e. improvement in the line efficiency by 18.39%, deterioration in balanced delay by 28.39%, and deterioration of a smoothness index by 23.85% was obtained.
An inertia-free filter line-search algorithm for large-scale nonlinear programming
Energy Technology Data Exchange (ETDEWEB)
Chiang, Nai-Yuan; Zavala, Victor M.
2016-02-15
We present a filter line-search algorithm that does not require inertia information of the linear system. This feature enables the use of a wide range of linear algebra strategies and libraries, which is essential to tackle large-scale problems on modern computing architectures. The proposed approach performs curvature tests along the search step to detect negative curvature and to trigger convexification. We prove that the approach is globally convergent and we implement the approach within a parallel interior-point framework to solve large-scale and highly nonlinear problems. Our numerical tests demonstrate that the inertia-free approach is as efficient as inertia detection via symmetric indefinite factorizations. We also demonstrate that the inertia-free approach can lead to reductions in solution time because it reduces the amount of convexification needed.
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 ...
Optimal Rotor Design of Line Start Permanent Magnet Synchronous Motor by Genetic Algorithm
Directory of Open Access Journals (Sweden)
Bui Minh Dinh
2017-07-01
Full Text Available Line start permanent magnet synchronous motor (LSPMSM is one of the highest efficiency motors due to no rotor copper loss at synchronous speed and self-starting. LSPMSM has torque characteristics of both induction motor IM and Permanent Magnet Synchronous Motor-PMSM. Using Genetic Algorithm (GA for balancing magnetic cost and for copper loss minimization, the magnetic sizes and geometry parameter of stator and rotor are found and manufactured for industrial evaluation. This article is also taking account practical manufacturing factors to minimize mass production cost. In order to maximize efficiency, an optimal design method of cage-bars and magnet shape has to be considered. The geometry parameters of stator and rotor can be obtained by an analytical model method and validated by FEM simulation. This paper presents the optimal rotor design of a three-phase line-start permanent magnet motor (LSPM considering the starting torque and efficiency. To consider nonlinear characteristics, the design process is comprised of the FEM and analytical method. During this study, permanent-magnets and cage bars were designed using the magnetic equivalent circuit method and the barriers that control all magnetic flux were designed using the FEM, and the tradeoff of starting torque and efficiency is controlled by weight function in Taguchi method simulation. Finally, some practical results have been obtained and analyzed based on a LSPMSM test bench.
A Novel Method for Decoding Any High-Order Hidden Markov Model
Directory of Open Access Journals (Sweden)
Fei Ye
2014-01-01
Full Text Available This paper proposes a novel method for decoding any high-order hidden Markov model. First, the high-order hidden Markov model is transformed into an equivalent first-order hidden Markov model by Hadar’s transformation. Next, the optimal state sequence of the equivalent first-order hidden Markov model is recognized by the existing Viterbi algorithm of the first-order hidden Markov model. Finally, the optimal state sequence of the high-order hidden Markov model is inferred from the optimal state sequence of the equivalent first-order hidden Markov model. This method provides a unified algorithm framework for decoding hidden Markov models including the first-order hidden Markov model and any high-order hidden Markov model.
Yang, Chun-Chieh; Kim, Moon S.; Chuang, Yung-Kun; Lee, Hoyoung
2013-05-01
This paper reports the development of a multispectral algorithm, using the line-scan hyperspectral imaging system, to detect fecal contamination on leafy greens. Fresh bovine feces were applied to the surfaces of washed loose baby spinach leaves. A hyperspectral line-scan imaging system was used to acquire hyperspectral fluorescence images of the contaminated leaves. Hyperspectral image analysis resulted in the selection of the 666 nm and 688 nm wavebands for a multispectral algorithm to rapidly detect feces on leafy greens, by use of the ratio of fluorescence intensities measured at those two wavebands (666 nm over 688 nm). The algorithm successfully distinguished most of the lowly diluted fecal spots (0.05 g feces/ml water and 0.025 g feces/ml water) and some of the highly diluted spots (0.0125 g feces/ml water and 0.00625 g feces/ml water) from the clean spinach leaves. The results showed the potential of the multispectral algorithm with line-scan imaging system for application to automated food processing lines for food safety inspection of leafy green vegetables.
Alpay, D.; Dijksma, A.; Langer, H.
2004-01-01
We prove that a 2 × 2 matrix polynomial which is J-unitary on the real line can be written as a product of normalized elementary J-unitary factors and a J-unitary constant. In the second part we give an algorithm for this factorization using an analog of the Schur transformation.
Arkin, Ethem; Tekinerdogan, Bedir
2016-01-01
Mapping parallel algorithms to parallel computing platforms requires several activities such as the analysis of the parallel algorithm, the definition of the logical configuration of the platform, the mapping of the algorithm to the logical configuration platform and the implementation of the
Knypiński, Łukasz
2017-12-01
In this paper an algorithm for the optimization of excitation system of line-start permanent magnet synchronous motors will be presented. For the basis of this algorithm, software was developed in the Borland Delphi environment. The software consists of two independent modules: an optimization solver, and a module including the mathematical model of a synchronous motor with a self-start ability. The optimization module contains the bat algorithm procedure. The mathematical model of the motor has been developed in an Ansys Maxwell environment. In order to determine the functional parameters of the motor, additional scripts in Visual Basic language were developed. Selected results of the optimization calculation are presented and compared with results for the particle swarm optimization algorithm.
Peng, Jiangtao; Peng, Silong; Xie, Qiong; Wei, Jiping
2011-04-01
In order to eliminate the lower order polynomial interferences, a new quantitative calibration algorithm "Baseline Correction Combined Partial Least Squares (BCC-PLS)", which combines baseline correction and conventional PLS, is proposed. By embedding baseline correction constraints into PLS weights selection, the proposed calibration algorithm overcomes the uncertainty in baseline correction and can meet the requirement of on-line attenuated total reflectance Fourier transform infrared (ATR-FTIR) quantitative analysis. The effectiveness of the algorithm is evaluated by the analysis of glucose and marzipan ATR-FTIR spectra. BCC-PLS algorithm shows improved prediction performance over PLS. The root mean square error of cross-validation (RMSECV) on marzipan spectra for the prediction of the moisture is found to be 0.53%, w/w (range 7-19%). The sugar content is predicted with a RMSECV of 2.04%, w/w (range 33-68%). Copyright © 2011 Elsevier B.V. All rights reserved.
A General Event Location Algorithm with Applications to Eclipse and Station Line-of-Sight
Parker, Joel J. K.; Hughes, Steven P.
2011-01-01
A general-purpose algorithm for the detection and location of orbital events is developed. The proposed algorithm reduces the problem to a global root-finding problem by mapping events of interest (such as eclipses, station access events, etc.) to continuous, differentiable event functions. A stepping algorithm and a bracketing algorithm are used to detect and locate the roots. Examples of event functions and the stepping/bracketing algorithms are discussed, along with results indicating performance and accuracy in comparison to commercial tools across a variety of trajectories.
A General Event Location Algorithm with Applications to Eclispe and Station Line-of-Sight
Parker, Joel J. K.; Hughes, Steven P.
2011-01-01
A general-purpose algorithm for the detection and location of orbital events is developed. The proposed algorithm reduces the problem to a global root-finding problem by mapping events of interest (such as eclipses, station access events, etc.) to continuous, differentiable event functions. A stepping algorithm and a bracketing algorithm are used to detect and locate the roots. Examples of event functions and the stepping/bracketing algorithms are discussed, along with results indicating performance and accuracy in comparison to commercial tools across a variety of trajectories.
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 ...
Sociology of Hidden Curriculum
Directory of Open Access Journals (Sweden)
Alireza Moradi
2017-06-01
Full Text Available This paper reviews the concept of hidden curriculum in the sociological theories and wants to explain sociological aspects of formation of hidden curriculum. The main question concentrates on the theoretical approaches in which hidden curriculum is explained sociologically.For this purpose it was applied qualitative research methodology. The relevant data include various sociological concepts and theories of hidden curriculum collected by the documentary method. The study showed a set of rules, procedures, relationships and social structure of education have decisive role in the formation of hidden curriculum. A hidden curriculum reinforces by existed inequalities among learners (based on their social classes or statues. There is, in fact, a balance between the learner's "knowledge receptions" with their "inequality proportion".The hidden curriculum studies from different major sociological theories such as Functionalism, Marxism and critical theory, Symbolic internationalism and Feminism. According to the functionalist perspective a hidden curriculum has a social function because it transmits social values. Marxists and critical thinkers correlate between hidden curriculum and the totality of social structure. They depicts that curriculum prepares learners for the exploitation in the work markets. Symbolic internationalism rejects absolute hegemony of hidden curriculum on education and looks to the socialization as a result of interaction between learner and instructor. Feminism theory also considers hidden curriculum as a vehicle which legitimates gender stereotypes.
Directory of Open Access Journals (Sweden)
Ada Che
2008-01-01
Full Text Available Modern automated production lines usually use one or multiple computer-controlled robots or hoists for material handling between workstations. A typical application of such lines is an automated electroplating line for processing printed circuit boards (PCBs. In these systems, cyclic production policy is widely used due to large lot size and simplicity of implementation. This paper addresses cyclic scheduling of a multihoist electroplating line with constant processing times. The objective is to minimize the cycle time, or equivalently to maximize the production throughput, for a given number of hoists. We propose a mathematical model and a polynomial algorithm for this scheduling problem. Computational results on randomly generated instances are reported.
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)
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 ...
Li, Xiangyu; Cai, Hao; Wang, Xianlong; Ao, Lu; Guo, You; He, Jun; Gu, Yunyan; Qi, Lishuang; Guan, Qingzhou; Lin, Xu; Guo, Zheng
2017-10-13
To detect differentially expressed genes (DEGs) in small-scale cell line experiments, usually with only two or three technical replicates for each state, the commonly used statistical methods such as significance analysis of microarrays (SAM), limma and RankProd (RP) lack statistical power, while the fold change method lacks any statistical control. In this study, we demonstrated that the within-sample relative expression orderings (REOs) of gene pairs were highly stable among technical replicates of a cell line but often widely disrupted after certain treatments such like gene knockdown, gene transfection and drug treatment. Based on this finding, we customized the RankComp algorithm, previously designed for individualized differential expression analysis through REO comparison, to identify DEGs with certain statistical control for small-scale cell line data. In both simulated and real data, the new algorithm, named CellComp, exhibited high precision with much higher sensitivity than the original RankComp, SAM, limma and RP methods. Therefore, CellComp provides an efficient tool for analyzing small-scale cell line data. © The Author 2017. Published by Oxford University Press.
Control and monitoring of On-line Trigger Algorithms using gaucho
Van Herwijnen, Eric
2005-01-01
In the LHCb experiment, the trigger decisions are computed by Gaudi (the LHCb software framework) algorithms running on an event filter farm of around 2000 PCs. The control and monitoring of these algorithms has to be integrated in the overall experiment control system (ECS). To enable and facilitate this integration Gaucho, the GAUdi Component Helping Online, was developed. Gaucho consists of three parts: a C++ package integrated with Gaudi, the communications package DIM, and a set of PVSS panels and libraries. PVSS is a commercial SCADA system chosen as toolkit and framework for the LHCb controls system. The C++ package implements monitor service interface (IMonitorSvc) following the Gaudi specifications, with methods to declare variables and histograms for monitoring. Algorithms writers use them to indicate which quantities should be monitored. Since the interface resides in the GaudiKernel the code does not need changing if the monitoring services are not present. The Gaudi main job implements a state ma...
International Nuclear Information System (INIS)
Stairs, Allen
2007-01-01
Recent results by Paul Busch and Adan Cabello claim to show that by appealing to POVMs, non-contextual hidden variables can be ruled out in two dimensions. While the results of Busch and Cabello are mathematically correct, interpretive problems render them problematic as no hidden variable proofs
Partially Hidden Markov Models
DEFF Research Database (Denmark)
Forchhammer, Søren Otto; Rissanen, Jorma
1996-01-01
Partially Hidden Markov Models (PHMM) are introduced. They differ from the ordinary HMM's in that both the transition probabilities of the hidden states and the output probabilities are conditioned on past observations. As an illustration they are applied to black and white image compression where...
Vijayakumar, Ganesh; Sprague, Michael
2017-11-01
Demonstrating expected convergence rates with spatial- and temporal-grid refinement is the ``gold standard'' of code and algorithm verification. However, the lack of analytical solutions and generating manufactured solutions presents challenges for verifying codes for complex systems. The application of the method of manufactured solutions (MMS) for verification for coupled multi-physics phenomena like fluid-structure interaction (FSI) has only seen recent investigation. While many FSI algorithms for aeroelastic phenomena have focused on boundary-resolved CFD simulations, the actuator-line representation of the structure is widely used for FSI simulations in wind-energy research. In this work, we demonstrate the verification of an FSI algorithm using MMS for actuator-line CFD simulations with a simplified structural model. We use a manufactured solution for the fluid velocity field and the displacement of the SMD system. We demonstrate the convergence of both the fluid and structural solver to second-order accuracy with grid and time-step refinement. This work was funded by the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Wind Energy Technologies Office, under Contract No. DE-AC36-08-GO28308 with the National Renewable Energy Laboratory.
Directory of Open Access Journals (Sweden)
Eyad K Almaita
2017-03-01
Keywords: Energy efficiency, Power quality, Radial basis function, neural networks, adaptive, harmonic. Article History: Received Dec 15, 2016; Received in revised form Feb 2nd 2017; Accepted 13rd 2017; Available online How to Cite This Article: Almaita, E.K and Shawawreh J.Al (2017 Improving Stability and Convergence for Adaptive Radial Basis Function Neural Networks Algorithm (On-Line Harmonics Estimation Application. International Journal of Renewable Energy Develeopment, 6(1, 9-17. http://dx.doi.org/10.14710/ijred.6.1.9-17
Modelling and control algorithms of the cross conveyors line with multiengine variable speed drives
Cheremushkina, M. S.; Baburin, S. V.
2017-02-01
The paper deals with the actual problem of developing the control algorithm that meets the technical requirements of the mine belt conveyors, and enables energy and resource savings taking into account a random sort of traffic. The most effective method of solution of these tasks is the construction of control systems with the use of variable speed drives for asynchronous motors. The authors designed the mathematical model of the system ‘variable speed multiengine drive - conveyor - control system of conveyors’ that takes into account the dynamic processes occurring in the elements of the transport system, provides an assessment of the energy efficiency of application the developed algorithms, which allows one to reduce the dynamic overload in the belt to 15-20%.
Directory of Open Access Journals (Sweden)
Mohamed Dine
2012-01-01
Full Text Available This paper presents a new approach to fault location on power transmission lines. This approach uses two-end unsynchronised measurements of the line and benefits from the advantages of digital technology and numerical relaying, which are available today and can easily be applied for off-line analysis. The approach is to modify the apparent impedance method using a very simple first-order formula. The new method is independent of fault resistance, source impedances and pre-fault currents. In addition, the data volume communicated between relays is sufficiently small enough to be transmitted easily using a digital protection channel. The proposed approach is tested via digital simulation using MATLand the applied test results corroborate the superior performance of the proposed approach.
Morillot, Olivier; Likforman-Sulem, Laurence; Grosicki, Emmanuèle
2013-04-01
Many preprocessing techniques have been proposed for isolated word recognition. However, recently, recognition systems have dealt with text blocks and their compound text lines. In this paper, we propose a new preprocessing approach to efficiently correct baseline skew and fluctuations. Our approach is based on a sliding window within which the vertical position of the baseline is estimated. Segmentation of text lines into subparts is, thus, avoided. Experiments conducted on a large publicly available database (Rimes), with a BLSTM (bidirectional long short-term memory) recurrent neural network recognition system, show that our baseline correction approach highly improves performance.
International Nuclear Information System (INIS)
O'Raifeartaigh, L.
1979-01-01
This review describes the principles of hidden gauge symmetry and of its application to the fundamental interactions. The emphasis is on the structure of the theory rather than on the technical details and, in order to emphasise the structure, gauge symmetry and hidden symmetry are first treated as independent phenomena before being combined into a single (hidden gauge symmetric) theory. The main application of the theory is to the weak and electromagnetic interactions of the elementary particles, and although models are used for comparison with experiment and for illustration, emphasis is placed on those features of the application which are model-independent. (author)
Exploratory Analysis of an On-line Evolutionary Algorithm in Simulated Robots
Haasdijk, E.W.; Smit, S.K.; Eiben, A.E.
2012-01-01
In traditional evolutionary robotics, robot controllers are evolved in a separate design phase preceding actual deployment; we call this off-line evolution. Alternatively, robot controllers can evolve while the robots perform their proper tasks, during the actual operational phase; we call this
A FAST LEXICALLY CONSTRAINED VITERBI ALGORITHM FOR ON LINE HANDWRITING RECOGNITIO
Lifchitz, A.; Maire, F.
2004-01-01
Most online cursive handwriting recognition systems use a lexical constraint to help improve the recognition performance. Traditionally, the vocabulary lexicon is stored in a trie (automaton whose underlying graph is a tree). In this paper, we propose a solution based on a more compact data
International Nuclear Information System (INIS)
Comelli, M.; Benes, M.; Bampo, A.; Villalta, R.
2006-01-01
The Regional Environment Protection Agency of Friuli Venezia Giulia (A.R.P.A. F.V.G., Italy) has performed an analysis on existing software designed to calculate magnetic induction field generated by power lines. As far as the agency requirements are concerned the tested programs display some difficulties in the immediate processing of electrical and geometrical data supplied by plant owners, and in certain cases turn out to be inadequate in representing complex configurations of power lines. Furthermore, none of them is preset for cyclic calculus to determine the time evolution of induction in a certain exposure area. Finally, the output data are not immediately importable by ArcView, the G.I.S. used by A.R.P.A. F.V.G., and it is not always possible to implement the territory orography to determine the field at specified heights above the ground. P.h.i.d.e.l., an innovative software, tackles and works out al l the above mentioned problems. The power line wires interested in its implementation are represented by poly lines, and the field is analytically calculated, with no further approximation, not even when more power lines are concerned. Therefore, the obtained results, when compared with those of other programs, are the closest to experimental measurements. The output data can be employed both in G.I.S. and Excel environments, allowing the immediate overlaying of digital cartography and the determining of the 3 and 10 μT bands, in compliance with the Italian Decree of the President of the Council of Ministers of 8 July 2003. (authors)
Energy Technology Data Exchange (ETDEWEB)
Sadeh, Javad; Afradi, Hamid [Electrical Engineering Department, Faculty of Engineering, Ferdowsi University of Mashhad, P.O. Box: 91775-1111, Mashhad (Iran)
2009-11-15
This paper presents a new and accurate algorithm for locating faults in a combined overhead transmission line with underground power cable using Adaptive Network-Based Fuzzy Inference System (ANFIS). The proposed method uses 10 ANFIS networks and consists of 3 stages, including fault type classification, faulty section detection and exact fault location. In the first part, an ANFIS is used to determine the fault type, applying four inputs, i.e., fundamental component of three phase currents and zero sequence current. Another ANFIS network is used to detect the faulty section, whether the fault is on the overhead line or on the underground cable. Other eight ANFIS networks are utilized to pinpoint the faults (two for each fault type). Four inputs, i.e., the dc component of the current, fundamental frequency of the voltage and current and the angle between them, are used to train the neuro-fuzzy inference systems in order to accurately locate the faults on each part of the combined line. The proposed method is evaluated under different fault conditions such as different fault locations, different fault inception angles and different fault resistances. Simulation results confirm that the proposed method can be used as an efficient means for accurate fault location on the combined transmission lines. (author)
Utilization of genetic algorithm in on-line tuning of fluid power servos
Energy Technology Data Exchange (ETDEWEB)
Halme, J.
1997-12-31
This study describes a robust and plausible method based on genetic algorithms suitable for tuning a regulator. The main advantages of the method presented is its robustness and easy-to-use feature. In this thesis the method is demonstrated by searching for appropriate control parameters of a state-feedback controller in a fluid power environment. To corroborate the robustness of the tuning method, two earlier studies are also presented in the appendix, where the presented tuning method is used in different kinds of regulator tuning situations. (orig.) 33 refs.
Utilization of genetic algorithm in on-line tuning of fluid power servos
Energy Technology Data Exchange (ETDEWEB)
Halme, J
1998-12-31
This study describes a robust and plausible method based on genetic algorithms suitable for tuning a regulator. The main advantages of the method presented is its robustness and easy-to-use feature. In this thesis the method is demonstrated by searching for appropriate control parameters of a state-feedback controller in a fluid power environment. To corroborate the robustness of the tuning method, two earlier studies are also presented in the appendix, where the presented tuning method is used in different kinds of regulator tuning situations. (orig.) 33 refs.
Gadsby, Naomi J; Helgason, Kristjan O; Dickson, Elizabeth M; Mills, Jonathan M; Lindsay, Diane S J; Edwards, Giles F; Hanson, Mary F; Templeton, Kate E
2016-02-01
Urinary antigen testing for Legionella pneumophila serogroup 1 is the leading rapid diagnostic test for Legionnaires' Disease (LD); however other Legionella species and serogroups can also cause LD. The aim was to determine the utility of front-line L. pneumophila and Legionella species PCR in a severe respiratory infection algorithm. L. pneumophila and Legionella species duplex real-time PCR was carried out on 1944 specimens from hospitalised patients over a 4 year period in Edinburgh, UK. L. pneumophila was detected by PCR in 49 (2.7%) specimens from 36 patients. During a LD outbreak, combined L. pneumophila respiratory PCR and urinary antigen testing had optimal sensitivity and specificity (92.6% and 98.3% respectively) for the detection of confirmed cases. Legionella species was detected by PCR in 16 (0.9%) specimens from 10 patients. The 5 confirmed and 1 probable cases of Legionella longbeachae LD were both PCR and antibody positive. Front-line L. pneumophila and Legionella species PCR is a valuable addition to urinary antigen testing as part of a well-defined algorithm. Cases of LD due to L. longbeachae might be considered laboratory-confirmed when there is a positive Legionella species PCR result and detection of L. longbeachae specific antibody response. Copyright © 2015 The British Infection Association. Published by Elsevier Ltd. All rights reserved.
International Nuclear Information System (INIS)
Disney, M.
1985-01-01
Astronomer Disney has followed a somewhat different tack than that of most popular books on cosmology by concentrating on the notion of hidden (as in not directly observable by its own radiation) matter in the universe
National Research Council Canada - National Science Library
Oeverlier, Lasse; Syverson, Paul F
2006-01-01
.... Announced properties include server resistance to distributed DoS. Both the EFF and Reporters Without Borders have issued guides that describe using hidden services via Tor to protect the safety of dissidents as well as to resist censorship...
Viau, C. R.
2012-06-01
The use of the intensity change and line-of-sight (LOS) change concepts have previously been documented in the open-literature as techniques used by non-imaging infrared (IR) seekers to reject expendable IR countermeasures (IRCM). The purpose of this project was to implement IR counter-countermeasure (IRCCM) algorithms based on target intensity and kinematic behavior for a generic imaging IR (IIR) seeker model with the underlying goal of obtaining a better understanding of how expendable IRCM can be used to defeat the latest generation of seekers. The report describes the Intensity Ratio Change (IRC) and LOS Rate Change (LRC) discrimination techniques. The algorithms and the seeker model are implemented in a physics-based simulation product called Tactical Engagement Simulation Software (TESS™). TESS is developed in the MATLAB®/Simulink® environment and is a suite of RF/IR missile software simulators used to evaluate and analyze the effectiveness of countermeasures against various classes of guided threats. The investigation evaluates the algorithm and tests their robustness by presenting the results of batch simulation runs of surface-to-air (SAM) and air-to-air (AAM) IIR missiles engaging a non-maneuvering target platform equipped with expendable IRCM as self-protection. The report discusses how varying critical parameters such track memory time, ratio thresholds and hold time can influence the outcome of an engagement.
Polverino, Pierpaolo; Esposito, Angelo; Pianese, Cesare; Ludwig, Bastian; Iwanschitz, Boris; Mai, Andreas
2016-02-01
In the current energetic scenario, Solid Oxide Fuel Cells (SOFCs) exhibit appealing features which make them suitable for environmental-friendly power production, especially for stationary applications. An example is represented by micro-combined heat and power (μ-CHP) generation units based on SOFC stacks, which are able to produce electric and thermal power with high efficiency and low pollutant and greenhouse gases emissions. However, the main limitations to their diffusion into the mass market consist in high maintenance and production costs and short lifetime. To improve these aspects, the current research activity focuses on the development of robust and generalizable diagnostic techniques, aimed at detecting and isolating faults within the entire system (i.e. SOFC stack and balance of plant). Coupled with appropriate recovery strategies, diagnosis can prevent undesired system shutdowns during faulty conditions, with consequent lifetime increase and maintenance costs reduction. This paper deals with the on-line experimental validation of a model-based diagnostic algorithm applied to a pre-commercial SOFC system. The proposed algorithm exploits a Fault Signature Matrix based on a Fault Tree Analysis and improved through fault simulations. The algorithm is characterized on the considered system and it is validated by means of experimental induction of faulty states in controlled conditions.
International Nuclear Information System (INIS)
Feng, Jonathan L.; Kaplinghat, Manoj; Tu, Huitzu; Yu, Hai-Bo
2009-01-01
Can dark matter be stabilized by charge conservation, just as the electron is in the standard model? We examine the possibility that dark matter is hidden, that is, neutral under all standard model gauge interactions, but charged under an exact (\\rm U)(1) gauge symmetry of the hidden sector. Such candidates are predicted in WIMPless models, supersymmetric models in which hidden dark matter has the desired thermal relic density for a wide range of masses. Hidden charged dark matter has many novel properties not shared by neutral dark matter: (1) bound state formation and Sommerfeld-enhanced annihilation after chemical freeze out may reduce its relic density, (2) similar effects greatly enhance dark matter annihilation in protohalos at redshifts of z ∼ 30, (3) Compton scattering off hidden photons delays kinetic decoupling, suppressing small scale structure, and (4) Rutherford scattering makes such dark matter self-interacting and collisional, potentially impacting properties of the Bullet Cluster and the observed morphology of galactic halos. We analyze all of these effects in a WIMPless model in which the hidden sector is a simplified version of the minimal supersymmetric standard model and the dark matter is a hidden sector stau. We find that charged hidden dark matter is viable and consistent with the correct relic density for reasonable model parameters and dark matter masses in the range 1 GeV ∼ X ∼< 10 TeV. At the same time, in the preferred range of parameters, this model predicts cores in the dark matter halos of small galaxies and other halo properties that may be within the reach of future observations. These models therefore provide a viable and well-motivated framework for collisional dark matter with Sommerfeld enhancement, with novel implications for astrophysics and dark matter searches
Li, Chengqi; Ren, Zhigang; Yang, Bo; An, Qinghao; Yu, Xiangru; Li, Jinping
2017-12-01
In the process of dismounting and assembling the drop switch for the high-voltage electric power live line working (EPL2W) robot, one of the key problems is the precision of positioning for manipulators, gripper and the bolts used to fix drop switch. To solve it, we study the binocular vision system theory of the robot and the characteristic of dismounting and assembling drop switch. We propose a coarse-to-fine image registration algorithm based on image correlation, which can improve the positioning precision of manipulators and bolt significantly. The algorithm performs the following three steps: firstly, the target points are marked respectively in the right and left visions, and then the system judges whether the target point in right vision can satisfy the lowest registration accuracy by using the similarity of target points' backgrounds in right and left visions, this is a typical coarse-to-fine strategy; secondly, the system calculates the epipolar line, and then the regional sequence existing matching points is generated according to neighborhood of epipolar line, the optimal matching image is confirmed by calculating the similarity between template image in left vision and the region in regional sequence according to correlation matching; finally, the precise coordinates of target points in right and left visions are calculated according to the optimal matching image. The experiment results indicate that the positioning accuracy of image coordinate is within 2 pixels, the positioning accuracy in the world coordinate system is within 3 mm, the positioning accuracy of binocular vision satisfies the requirement dismounting and assembling the drop switch.
Directory of Open Access Journals (Sweden)
Schöning André
2016-01-01
Full Text Available Track reconstruction in high track multiplicity environments at current and future high rate particle physics experiments is a big challenge and very time consuming. The search for track seeds and the fitting of track candidates are usually the most time consuming steps in the track reconstruction. Here, a new and fast track reconstruction method based on hit triplets is proposed which exploits a three-dimensional fit model including multiple scattering and hit uncertainties from the very start, including the search for track seeds. The hit triplet based reconstruction method assumes a homogeneous magnetic field which allows to give an analytical solutions for the triplet fit result. This method is highly parallelizable, needs fewer operations than other standard track reconstruction methods and is therefore ideal for the implementation on parallel computing architectures. The proposed track reconstruction algorithm has been studied in the context of the Mu3e-experiment and a typical LHC experiment.
Directory of Open Access Journals (Sweden)
Maslennikov Valeriy Aleksandrovich
2016-06-01
Full Text Available The current methods of predicting the demand of the community for the lines of technical inspection of vehicles do not fully take into account the probabilistic and statistical nature of the complaints of car owners. This results in significant mistakes in the determination of the number of such lines, accompanied by insufficient rhythm of their operation. The design errors related to the complexity of accurate account for calendar fluctuations of the number of appeals can be partially or completely eliminated by using mathematical apparatus of the queuing theory. In this case, the complex technical system is considered as an open multi-channel queuing system with limited queue length. The received flows and serviced requests are considered to be the simplest. From a practical point of view, the replacement of one type of computational model by the other allows ensuring a more sustainable mode of calculating operations using the computer. The paper also provides a calculation expression for defining the lower and upper confidence limits of the dispersion of the average values of the number of arrivals of vehicles at the technical inspection that allows setting the interval of uncertainty for searching the optimal solution.
Yavari, Somayeh; Valadan Zoej, Mohammad Javad; Salehi, Bahram
2018-05-01
The procedure of selecting an optimum number and best distribution of ground control information is important in order to reach accurate and robust registration results. This paper proposes a new general procedure based on Genetic Algorithm (GA) which is applicable for all kinds of features (point, line, and areal features). However, linear features due to their unique characteristics are of interest in this investigation. This method is called Optimum number of Well-Distributed ground control Information Selection (OWDIS) procedure. Using this method, a population of binary chromosomes is randomly initialized. The ones indicate the presence of a pair of conjugate lines as a GCL and zeros specify the absence. The chromosome length is considered equal to the number of all conjugate lines. For each chromosome, the unknown parameters of a proper mathematical model can be calculated using the selected GCLs (ones in each chromosome). Then, a limited number of Check Points (CPs) are used to evaluate the Root Mean Square Error (RMSE) of each chromosome as its fitness value. The procedure continues until reaching a stopping criterion. The number and position of ones in the best chromosome indicate the selected GCLs among all conjugate lines. To evaluate the proposed method, a GeoEye and an Ikonos Images are used over different areas of Iran. Comparing the obtained results by the proposed method in a traditional RFM with conventional methods that use all conjugate lines as GCLs shows five times the accuracy improvement (pixel level accuracy) as well as the strength of the proposed method. To prevent an over-parametrization error in a traditional RFM due to the selection of a high number of improper correlated terms, an optimized line-based RFM is also proposed. The results show the superiority of the combination of the proposed OWDIS method with an optimized line-based RFM in terms of increasing the accuracy to better than 0.7 pixel, reliability, and reducing systematic
KMEANS CLUSTERING FOR HIDDEN MARKOV MODEL
Perrone, M.P.; Connell, S.D.
2004-01-01
An unsupervised kmeans clustering algorithm for hidden Markov models is described and applied to the task of generating subclass models for individual handwritten character classes. The algorithm is compared to a related clustering method and shown to give a relative change in the error rate of as
Liu, Liangyun; Zhang, Bing
2009-09-01
Photosynthetic efficiency is very important, and not yet generally assessable by remote sensing. Much research has proved the possibility of the separation of solar-induced chlorophyll fluorescence (ChlF) from the reflected hyperspectral data. As the 'probe' of plant photosynthesis, it is possible to detect photosynthetic light use efficiency (LUE) by the separated solar-induced ChlF. A diurnal experiment was carried out on winter wheat on Apr. 18, 2008, and the canopy radiance spectra and leaf LUE data were measured synchronously. The solar-induced chlorophyll fluorescence signals at 760nm and 688nm were separated from the reflected radiance spectral based on Fraunhofer lines in two oxygen absorption bands. The result showed that LUE was negatively correlated to the separated chlorophyll signals. The statistical models for LUE based on the solar-induced chlorophyll fluorescence values at 688 nm and 760 nm bands had correlation coefficients (R2) of 0.64 and 0.78, respectively. In addition, photochemical reflectance index (PRI) was also linked to LUE, and a statistical model for LUE based on PRI has a correlation coefficient (R2) of 0.66. The presented method provides a novel solution for monitoring LUE from remote sensing data.
Hidden neuronal correlations in cultured networks
International Nuclear Information System (INIS)
Segev, Ronen; Baruchi, Itay; Hulata, Eyal; Ben-Jacob, Eshel
2004-01-01
Utilization of a clustering algorithm on neuronal spatiotemporal correlation matrices recorded during a spontaneous activity of in vitro networks revealed the existence of hidden correlations: the sequence of synchronized bursting events (SBEs) is composed of statistically distinguishable subgroups each with its own distinct pattern of interneuron spatiotemporal correlations. These findings hint that each of the SBE subgroups can serve as a template for coding, storage, and retrieval of a specific information
Completing Quantum Mechanics with Quantized Hidden Variables
van Enk, S. J.
2015-01-01
I explore the possibility that a quantum system S may be described completely by the combination of its standard quantum state $|\\psi\\rangle$ and a (hidden) quantum state $|\\phi\\rangle$ (that lives in the same Hilbert space), such that the outcome of any standard projective measurement on the system S is determined once the two quantum states are specified. I construct an algorithm that retrieves the standard quantum-mechanical probabilities, which depend only on $|\\psi\\rangle$, by assuming t...
Shanks, Leslie; Siddiqui, M Ruby; Kliescikova, Jarmila; Pearce, Neil; Ariti, Cono; Muluneh, Libsework; Pirou, Erwan; Ritmeijer, Koert; Masiga, Johnson; Abebe, Almaz
2015-02-03
In Ethiopia a tiebreaker algorithm using 3 rapid diagnostic tests (RDTs) in series is used to diagnose HIV. Discordant results between the first 2 RDTs are resolved by a third 'tiebreaker' RDT. Médecins Sans Frontières uses an alternate serial algorithm of 2 RDTs followed by a confirmation test for all double positive RDT results. The primary objective was to compare the performance of the tiebreaker algorithm with a serial algorithm, and to evaluate the addition of a confirmation test to both algorithms. A secondary objective looked at the positive predictive value (PPV) of weakly reactive test lines. The study was conducted in two HIV testing sites in Ethiopia. Study participants were recruited sequentially until 200 positive samples were reached. Each sample was re-tested in the laboratory on the 3 RDTs and on a simple to use confirmation test, the Orgenics Immunocomb Combfirm® (OIC). The gold standard test was the Western Blot, with indeterminate results resolved by PCR testing. 2620 subjects were included with a HIV prevalence of 7.7%. Each of the 3 RDTs had an individual specificity of at least 99%. The serial algorithm with 2 RDTs had a single false positive result (1 out of 204) to give a PPV of 99.5% (95% CI 97.3%-100%). The tiebreaker algorithm resulted in 16 false positive results (PPV 92.7%, 95% CI: 88.4%-95.8%). Adding the OIC confirmation test to either algorithm eliminated the false positives. All the false positives had at least one weakly reactive test line in the algorithm. The PPV of weakly reacting RDTs was significantly lower than those with strongly positive test lines. The risk of false positive HIV diagnosis in a tiebreaker algorithm is significant. We recommend abandoning the tie-breaker algorithm in favour of WHO recommended serial or parallel algorithms, interpreting weakly reactive test lines as indeterminate results requiring further testing except in the setting of blood transfusion, and most importantly, adding a confirmation test
Solovev, V
The SHiP Experiment is a new general-purpose fixed target facility at the SPS to search for hidden particles as predicted by a very large number of recently elaborated models of Hidden Sectors which are capable of accommodating dark matter, neutrino oscillations, and the origin of the full baryon asymmetry in the Universe. Specifically, the experiment is aimed at searching for very weakly interacting long lived particles including Heavy Neutral Leptons - right-handed partners of the active neutrinos; light supersymmetric particles - sgoldstinos, etc.; scalar, axion and vector portals to the hidden sector. The high intensity of the SPS and in particular the large production of charm mesons with the 400 GeV beam allow accessing a wide variety of light long-lived exotic particles of such models and of SUSY. Moreover, the facility is ideally suited to study the interactions of tau neutrinos.
Hidden inventory and safety considerations
International Nuclear Information System (INIS)
Anderson, A.R.; James, R.H.; Morgan, F.
1976-01-01
Preliminary results are described of the evaluation of residual plutonium in a process line used for the production of experimental fast reactor fuel. Initial attention has been focussed on a selection of work boxes used for processing powders and solutions. Amounts of material measured as ''hidden inventory'' are generally less than 0.1 percent of throughput but in one box containing very complex equipment the amount was exceptionally about 0.5 percent. The total surface area of the box and the installed equipment appears to be the most significant factor in determining the amount of plutonium held-up as ''hidden inventory,'' representing an average of about 4 x 10 -4 g cm -2 . Present results are based on gamma spectrometer measurements but neutron techniques are being developed to overcome some of the inherent uncertainties in the gamma method. It is suggested that the routine use of sample plates of known surface area would be valuable in monitoring the deposition of plutonium in work boxes
Directory of Open Access Journals (Sweden)
Minas Bakalchev
2015-10-01
Full Text Available The perception of elements in a system often creates their interdependence, interconditionality, and suppression. The lines from a basic geometrical element have become the model of a reductive world based on isolation according to certain criteria such as function, structure, and social organization. Their traces are experienced in the contemporary world as fragments or ruins of a system of domination of an assumed hierarchical unity. How can one release oneself from such dependence or determinism? How can the lines become less “systematic” and forms more autonomous, and less reductive? How is a form released from modernistic determinism on the new controversial ground? How can these elements or forms of representation become forms of action in the present complex world? In this paper, the meaning of lines through the ideas of Le Corbusier, Leonidov, Picasso, and Hitchcock is presented. Spatial research was made through a series of examples arising from the projects of the architectural studio “Residential Transformations”, which was a backbone for mapping the possibilities ranging from playfulness to exactness, as tactics of transformation in the different contexts of the contemporary world.
An algorithm for generation of DEMs from contour lines considering geomorphic features
Directory of Open Access Journals (Sweden)
Xiao-Ping Rui
2016-04-01
Full Text Available Geomorphic information is omitted from many existing methods of generating gridded digital elevation models (DEMs from contour lines, resulting in significant errors during interpolation. Here, we present an advanced schema for improvement of the comprehensive regionalized method of linear interpolation. This approach uses a moving fitting method for an interpolated point and selects elevation points that are representative of geomorphic features as a whole to improve interpolation quality. A total of 16 points are selected, according to certain criteria, in eight directions surrounding the interpolated point; thus, there are two points in each direction, which is sufficient to provide an accurate representation of the geomorphic features of the DEM. Our method introduces virtual control points to prevent sudden changes in the interpolation results, which helps to overcome problems related to the distortion of the local geospatial distribution in areas where feature geomorphic information is inadequate. We construct the spline interpolation function using intersection points and virtual control points, all of which are applied to compute the point elevation. Moreover, we index all elevation values and spatial points of linear features using the R-tree method to ensure that points related to an interpolated position can be retrieved as quickly as possible. Finally, we test our method using a coal mine elevation dataset. The results confirm that our proposed method can generate DEMs smoothly and, in particular, avoid problems related to local distortion. Resumen La información geomórfica se omite en muchos de los métodos de generación de Modelos Digitales de Elevación (DEM, en inglés que se elaboran a partir de líneas de contorno, lo que resulta en errores significativos durante la interpolación. En este trabajo se presenta un esquema avanzado para el mejoramiento del método comprensivo regionalizado de interpolación lineal. Esta
Evolving the structure of hidden Markov Models
DEFF Research Database (Denmark)
won, K. J.; Prugel-Bennett, A.; Krogh, A.
2006-01-01
A genetic algorithm (GA) is proposed for finding the structure of hidden Markov Models (HMMs) used for biological sequence analysis. The GA is designed to preserve biologically meaningful building blocks. The search through the space of HMM structures is combined with optimization of the emission...... and transition probabilities using the classic Baum-Welch algorithm. The system is tested on the problem of finding the promoter and coding region of C. jejuni. The resulting HMM has a superior discrimination ability to a handcrafted model that has been published in the literature....
DEFF Research Database (Denmark)
Rasmussen, Birgitte; Jensen, Karsten Klint
“The Hidden Values - Transparency in Decision-Making Processes Dealing with Hazardous Activities”. The report seeks to shed light on what is needed to create a transparent framework for political and administrative decisions on the use of GMOs and chemical products. It is our hope that the report...
Adaptive filtering for hidden node detection and tracking in networks.
Hamilton, Franz; Setzer, Beverly; Chavez, Sergio; Tran, Hien; Lloyd, Alun L
2017-07-01
The identification of network connectivity from noisy time series is of great interest in the study of network dynamics. This connectivity estimation problem becomes more complicated when we consider the possibility of hidden nodes within the network. These hidden nodes act as unknown drivers on our network and their presence can lead to the identification of false connections, resulting in incorrect network inference. Detecting the parts of the network they are acting on is thus critical. Here, we propose a novel method for hidden node detection based on an adaptive filtering framework with specific application to neuronal networks. We consider the hidden node as a problem of missing variables when model fitting and show that the estimated system noise covariance provided by the adaptive filter can be used to localize the influence of the hidden nodes and distinguish the effects of different hidden nodes. Additionally, we show that the sequential nature of our algorithm allows for tracking changes in the hidden node influence over time.
Wang, Hongyu; Zhang, Baomin; Zhao, Xun; Li, Cong; Lu, Cunyue
2018-04-01
Conventional stereo vision algorithms suffer from high levels of hardware resource utilization due to algorithm complexity, or poor levels of accuracy caused by inadequacies in the matching algorithm. To address these issues, we have proposed a stereo range-finding technique that produces an excellent balance between cost, matching accuracy and real-time performance, for power line inspection using UAV. This was achieved through the introduction of a special image preprocessing algorithm and a weighted local stereo matching algorithm, as well as the design of a corresponding hardware architecture. Stereo vision systems based on this technique have a lower level of resource usage and also a higher level of matching accuracy following hardware acceleration. To validate the effectiveness of our technique, a stereo vision system based on our improved algorithms were implemented using the Spartan 6 FPGA. In comparative experiments, it was shown that the system using the improved algorithms outperformed the system based on the unimproved algorithms, in terms of resource utilization and matching accuracy. In particular, Block RAM usage was reduced by 19%, and the improved system was also able to output range-finding data in real time.
Directory of Open Access Journals (Sweden)
Huan Xia
2015-10-01
Full Text Available The installation of stationary super-capacitor energy storage system (ESS in metro systems can recycle the vehicle braking energy and improve the pantograph voltage profile. This paper aims to optimize the energy management, location, and size of stationary super-capacitor ESSes simultaneously and obtain the best economic efficiency and voltage profile of metro systems. Firstly, the simulation platform of an urban rail power supply system, which includes trains and super-capacitor energy storage systems, is established. Then, two evaluation functions from the perspectives of economic efficiency and voltage drop compensation are put forward. Ultimately, a novel optimization method that combines genetic algorithms and a simulation platform of urban rail power supply system is proposed, which can obtain the best energy management strategy, location, and size for ESSes simultaneously. With actual parameters of a Chinese metro line applied in the simulation comparison, certain optimal scheme of ESSes’ energy management strategy, location, and size obtained by a novel optimization method can achieve much better performance of metro systems from the perspectives of two evaluation functions. The simulation result shows that with the increase of weight coefficient, the optimal energy management strategy, locations and size of ESSes appear certain regularities, and the best compromise between economic efficiency and voltage drop compensation can be obtained by a novel optimization method, which can provide a valuable reference to subway company.
Luo, G. Y.; Osypiw, D.; Irle, M.
2003-05-01
The dynamic behaviour of wood machining processes affects the surface finish quality of machined workpieces. In order to meet the requirements of increased production efficiency and improved product quality, surface quality information is needed for enhanced process control. However, current methods using high price devices or sophisticated designs, may not be suitable for industrial real-time application. This paper presents a novel approach of surface quality evaluation by on-line vibration analysis using an adaptive spline wavelet algorithm, which is based on the excellent time-frequency localization of B-spline wavelets. A series of experiments have been performed to extract the feature, which is the correlation between the relevant frequency band(s) of vibration with the change of the amplitude and the surface quality. The graphs of the experimental results demonstrate that the change of the amplitude in the selective frequency bands with variable resolution (linear and non-linear) reflects the quality of surface finish, and the root sum square of wavelet power spectrum is a good indication of surface quality. Thus, surface quality can be estimated and quantified at an average level in real time. The results can be used to regulate and optimize the machine's feed speed, maintaining a constant spindle motor speed during cutting. This will lead to higher level control and machining rates while keeping dimensional integrity and surface finish within specification.
Detecting Faults By Use Of Hidden Markov Models
Smyth, Padhraic J.
1995-01-01
Frequency of false alarms reduced. Faults in complicated dynamic system (e.g., antenna-aiming system, telecommunication network, or human heart) detected automatically by method of automated, continuous monitoring. Obtains time-series data by sampling multiple sensor outputs at discrete intervals of t and processes data via algorithm determining whether system in normal or faulty state. Algorithm implements, among other things, hidden first-order temporal Markov model of states of system. Mathematical model of dynamics of system not needed. Present method is "prior" method mentioned in "Improved Hidden-Markov-Model Method of Detecting Faults" (NPO-18982).
Guliyev , Namig; Ismailov , Vugar
2016-01-01
The possibility of approximating a continuous function on a compact subset of the real line by a feedforward single hidden layer neural network with a sigmoidal activation function has been studied in many papers. Such networks can approximate an arbitrary continuous function provided that an unlimited number of neurons in a hidden layer is permitted. In this paper, we consider constructive approximation on any finite interval of $\\mathbb{R}$ by neural networks with only one neuron in the hid...
DEFF Research Database (Denmark)
Krogh, Anders Stærmose; Riis, Søren Kamaric
1999-01-01
A general framework for hybrids of hidden Markov models (HMMs) and neural networks (NNs) called hidden neural networks (HNNs) is described. The article begins by reviewing standard HMMs and estimation by conditional maximum likelihood, which is used by the HNN. In the HNN, the usual HMM probability...... parameters are replaced by the outputs of state-specific neural networks. As opposed to many other hybrids, the HNN is normalized globally and therefore has a valid probabilistic interpretation. All parameters in the HNN are estimated simultaneously according to the discriminative conditional maximum...... likelihood criterion. The HNN can be viewed as an undirected probabilistic independence network (a graphical model), where the neural networks provide a compact representation of the clique functions. An evaluation of the HNN on the task of recognizing broad phoneme classes in the TIMIT database shows clear...
Peppers, Emily
2008-01-01
The Cultural Collections Audit project began at the University of Edinburgh in 2004, searching for hidden treasures in its 'distributed heritage collections' across the university. The objects and collections recorded in the Audit ranged widely from fine art and furniture to historical scientific and teaching equipment and personalia relating to key figures in the university's long tradition of academic excellence. This information was gathered in order to create a central database of informa...
Królikowski, Wojciech
2016-01-01
A hypothetic Hidden Sector of the Universe, consisting of sterile fer\\-mions (``sterinos'') and sterile mediating bosons (``sterons'') of mass dimension 1 (not 2!) --- the last described by an antisymmetric tensor field --- requires to exist also a scalar isovector and scalar isoscalar in order to be able to construct electroweak invariant coupling (before spontaneously breaking its symmetry). The introduced scalar isoscalar might be a resonant source for the diphoton excess of 750 GeV, sugge...
Behr, Yannik; Clinton, John; Cua, Georgia; Cauzzi, Carlo; Heimers, Stefan; Kästli, Philipp; Becker, Jan; Heaton, Thomas
2013-04-01
The Virtual Seismologist (VS) method is a Bayesian approach to regional network-based earthquake early warning (EEW) originally formulated by Cua and Heaton (2007). Implementation of VS into real-time EEW codes has been an on-going effort of the Swiss Seismological Service at ETH Zürich since 2006, with support from ETH Zürich, various European projects, and the United States Geological Survey (USGS). VS is one of three EEW algorithms that form the basis of the California Integrated Seismic Network (CISN) ShakeAlert system, a USGS-funded prototype end-to-end EEW system that could potentially be implemented in California. In Europe, VS is currently operating as a real-time test system in Switzerland. As part of the on-going EU project REAKT (Strategies and Tools for Real-Time Earthquake Risk Reduction), VS installations in southern Italy, western Greece, Istanbul, Romania, and Iceland are planned or underway. In Switzerland, VS has been running in real-time on stations monitored by the Swiss Seismological Service (including stations from Austria, France, Germany, and Italy) since 2010. While originally based on the Earthworm system it has recently been ported to the SeisComp3 system. Besides taking advantage of SeisComp3's picking and phase association capabilities it greatly simplifies the potential installation of VS at networks in particular those already running SeisComp3. We present the architecture of the new SeisComp3 based version and compare its results from off-line tests with the real-time performance of VS in Switzerland over the past two years. We further show that the empirical relationships used by VS to estimate magnitudes and ground motion, originally derived from southern California data, perform well in Switzerland.
Hidden Liquidity: Determinants and Impact
Gökhan Cebiroglu; Ulrich Horst
2012-01-01
We cross-sectionally analyze the presence of aggregated hidden depth and trade volume in the S&P 500 and identify its key determinants. We find that the spread is the main predictor for a stockâ€™s hidden dimension, both in terms of traded and posted liquidity. Our findings moreover suggest that large hidden orders are associated with larger transaction costs, higher price impact and increased volatility. In particular, as large hidden orders fail to attract (latent) liquidity to the market, ...
Pruning Boltzmann networks and hidden Markov models
DEFF Research Database (Denmark)
Pedersen, Morten With; Stork, D.
1996-01-01
We present sensitivity-based pruning algorithms for general Boltzmann networks. Central to our methods is the efficient calculation of a second-order approximation to the true weight saliencies in a cross-entropy error. Building upon previous work which shows a formal correspondence between linear...... Boltzmann chains and hidden Markov models (HMMs), we argue that our method can be applied to HMMs as well. We illustrate pruning on Boltzmann zippers, which are equivalent to two HMMs with cross-connection links. We verify that our second-order approximation preserves the rank ordering of weight saliencies...
Detecting Structural Breaks using Hidden Markov Models
DEFF Research Database (Denmark)
Ntantamis, Christos
Testing for structural breaks and identifying their location is essential for econometric modeling. In this paper, a Hidden Markov Model (HMM) approach is used in order to perform these tasks. Breaks are defined as the data points where the underlying Markov Chain switches from one state to another....... The estimation of the HMM is conducted using a variant of the Iterative Conditional Expectation-Generalized Mixture (ICE-GEMI) algorithm proposed by Delignon et al. (1997), that permits analysis of the conditional distributions of economic data and allows for different functional forms across regimes...
A Constraint Model for Constrained Hidden Markov Models
DEFF Research Database (Denmark)
Christiansen, Henning; Have, Christian Theil; Lassen, Ole Torp
2009-01-01
A Hidden Markov Model (HMM) is a common statistical model which is widely used for analysis of biological sequence data and other sequential phenomena. In the present paper we extend HMMs with constraints and show how the familiar Viterbi algorithm can be generalized, based on constraint solving ...
Energy Technology Data Exchange (ETDEWEB)
Choi, Myung Soo; Yang, Kyong Uk [Chonnam National University, Yeosu (Korea, Republic of); Kondou, Takahiro [Kyushu University, Fukuoka (Japan); Bonkobara, Yasuhiro [University of Miyazaki, Miyazaki (Japan)
2016-03-15
We developed a method for analyzing the free vibration of a structure regarded as a distributed system, by combining the Wittrick-Williams algorithm and the transfer dynamic stiffness coefficient method. A computational algorithm was formulated for analyzing the free vibration of a straight-line beam regarded as a distributed system, to explain the concept of the developed method. To verify the effectiveness of the developed method, the natural frequencies of straight-line beams were computed using the finite element method, transfer matrix method, transfer dynamic stiffness coefficient method, the exact solution, and the developed method. By comparing the computational results of the developed method with those of the other methods, we confirmed that the developed method exhibited superior performance over the other methods in terms of computational accuracy, cost and user convenience.
... A.S.T. Quiz Hidden Stroke Risk Factors for Women Updated:Nov 22,2016 Excerpted from "What Women Need To Know About The Hidden Risk Factors ... 2012) This year, more than 100,000 U.S. women under 65 will have a stroke. Stroke is ...
Higgs Portal into Hidden Sectors
CERN. Geneva
2007-01-01
Several attractive theoretical ideas suggest the existence of one or more 'hidden sectors' consisting of standard model singlet fields, some of which may not be too heavy. There is a profound reason to think that the Higgs sector might provide the first access to these hidden sectors. This scenario could affect Higgs phenomenology in drastic ways.
Hidden Markov Model Application to Transfer The Trader Online Forex Brokers
Directory of Open Access Journals (Sweden)
Farida Suharleni
2012-05-01
Full Text Available Hidden Markov Model is elaboration of Markov chain, which is applicable to cases that can’t directly observe. In this research, Hidden Markov Model is used to know trader’s transition to broker forex online. In Hidden Markov Model, observed state is observable part and hidden state is hidden part. Hidden Markov Model allows modeling system that contains interrelated observed state and hidden state. As observed state in trader’s transition to broker forex online is category 1, category 2, category 3, category 4, category 5 by condition of every broker forex online, whereas as hidden state is broker forex online Marketiva, Masterforex, Instaforex, FBS and Others. First step on application of Hidden Markov Model in this research is making construction model by making a probability of transition matrix (A from every broker forex online. Next step is making a probability of observation matrix (B by making conditional probability of five categories, that is category 1, category 2, category 3, category 4, category 5 by condition of every broker forex online and also need to determine an initial state probability (π from every broker forex online. The last step is using Viterbi algorithm to find hidden state sequences that is broker forex online sequences which is the most possible based on model and observed state that is the five categories. Application of Hidden Markov Model is done by making program with Viterbi algorithm using Delphi 7.0 software with observed state based on simulation data. Example: By the number of observation T = 5 and observed state sequences O = (2,4,3,5,1 is found hidden state sequences which the most possible with observed state O as following : where X1 = FBS, X2 = Masterforex, X3 = Marketiva, X4 = Others, and X5 = Instaforex.
Detecting Hidden Hierarchy of Non Hierarchical Terrorist Networks
DEFF Research Database (Denmark)
Memon, Nasrullah
measures (and combinations of them) to identify key players (important nodes) in terrorist networks. Our recently introduced techniques and algorithms (which are also implemented in the investigative data mining toolkit known as iMiner) will be particularly useful for law enforcement agencies that need...... to analyze terrorist networks and prioritize their targets. Applying recently introduced mathematical methods for constructing the hidden hierarchy of "nonhierarchical" terrorist networks; we present case studies of the terrorist attacks occurred / planned in the past, in order to identify hidden hierarchy...
Oden, Neal L; VanVeldhuisen, Paul C; Wakim, Paul G; Trivedi, Madhukar H; Somoza, Eugene; Lewis, Daniel
2011-09-01
In clinical trials of treatment for stimulant abuse, researchers commonly record both Time-Line Follow-Back (TLFB) self-reports and urine drug screen (UDS) results. To compare the power of self-report, qualitative (use vs. no use) UDS assessment, and various algorithms to generate self-report-UDS composite measures to detect treatment differences via t-test in simulated clinical trial data. We performed Monte Carlo simulations patterned in part on real data to model self-report reliability, UDS errors, dropout, informatively missing UDS reports, incomplete adherence to a urine donation schedule, temporal correlation of drug use, number of days in the study period, number of patients per arm, and distribution of drug-use probabilities. Investigated algorithms include maximum likelihood and Bayesian estimates, self-report alone, UDS alone, and several simple modifications of self-report (referred to here as ELCON algorithms) which eliminate perceived contradictions between it and UDS. Among the algorithms investigated, simple ELCON algorithms gave rise to the most powerful t-tests to detect mean group differences in stimulant drug use. Further investigation is needed to determine if simple, naïve procedures such as the ELCON algorithms are optimal for comparing clinical study treatment arms. But researchers who currently require an automated algorithm in scenarios similar to those simulated for combining TLFB and UDS to test group differences in stimulant use should consider one of the ELCON algorithms. This analysis continues a line of inquiry which could determine how best to measure outpatient stimulant use in clinical trials (NIDA. NIDA Monograph-57: Self-Report Methods of Estimating Drug Abuse: Meeting Current Challenges to Validity. NTIS PB 88248083. Bethesda, MD: National Institutes of Health, 1985; NIDA. NIDA Research Monograph 73: Urine Testing for Drugs of Abuse. NTIS PB 89151971. Bethesda, MD: National Institutes of Health, 1987; NIDA. NIDA Research
Hidden attractors in dynamical systems
Dudkowski, Dawid; Jafari, Sajad; Kapitaniak, Tomasz; Kuznetsov, Nikolay V.; Leonov, Gennady A.; Prasad, Awadhesh
2016-06-01
Complex dynamical systems, ranging from the climate, ecosystems to financial markets and engineering applications typically have many coexisting attractors. This property of the system is called multistability. The final state, i.e., the attractor on which the multistable system evolves strongly depends on the initial conditions. Additionally, such systems are very sensitive towards noise and system parameters so a sudden shift to a contrasting regime may occur. To understand the dynamics of these systems one has to identify all possible attractors and their basins of attraction. Recently, it has been shown that multistability is connected with the occurrence of unpredictable attractors which have been called hidden attractors. The basins of attraction of the hidden attractors do not touch unstable fixed points (if exists) and are located far away from such points. Numerical localization of the hidden attractors is not straightforward since there are no transient processes leading to them from the neighborhoods of unstable fixed points and one has to use the special analytical-numerical procedures. From the viewpoint of applications, the identification of hidden attractors is the major issue. The knowledge about the emergence and properties of hidden attractors can increase the likelihood that the system will remain on the most desirable attractor and reduce the risk of the sudden jump to undesired behavior. We review the most representative examples of hidden attractors, discuss their theoretical properties and experimental observations. We also describe numerical methods which allow identification of the hidden attractors.
International Nuclear Information System (INIS)
Battistin, C; Roudi, Y; Hertz, J; Tyrcha, J
2015-01-01
We propose a new algorithm for inferring the state of hidden spins and reconstructing the connections in a synchronous kinetic Ising model, given the observed history. Focusing on the case in which the hidden spins are conditionally independent of each other given the state of observable spins, we show that calculating the likelihood of the data can be simplified by introducing a set of replicated auxiliary spins. Belief propagation (BP) and susceptibility propagation (SusP) can then be used to infer the states of hidden variables and to learn the couplings. We study the convergence and performance of this algorithm for networks with both Gaussian-distributed and binary bonds. We also study how the algorithm behaves as the fraction of hidden nodes and the amount of data are changed, showing that it outperforms the Thouless–Anderson–Palmer (TAP) equations for reconstructing the connections. (paper)
Wu, Chong; Liu, Liping; Wei, Ming; Xi, Baozhu; Yu, Minghui
2018-03-01
A modified hydrometeor classification algorithm (HCA) is developed in this study for Chinese polarimetric radars. This algorithm is based on the U.S. operational HCA. Meanwhile, the methodology of statistics-based optimization is proposed including calibration checking, datasets selection, membership functions modification, computation thresholds modification, and effect verification. Zhuhai radar, the first operational polarimetric radar in South China, applies these procedures. The systematic bias of calibration is corrected, the reliability of radar measurements deteriorates when the signal-to-noise ratio is low, and correlation coefficient within the melting layer is usually lower than that of the U.S. WSR-88D radar. Through modification based on statistical analysis of polarimetric variables, the localized HCA especially for Zhuhai is obtained, and it performs well over a one-month test through comparison with sounding and surface observations. The algorithm is then utilized for analysis of a squall line process on 11 May 2014 and is found to provide reasonable details with respect to horizontal and vertical structures, and the HCA results—especially in the mixed rain-hail region—can reflect the life cycle of the squall line. In addition, the kinematic and microphysical processes of cloud evolution and the differences between radar-detected hail and surface observations are also analyzed. The results of this study provide evidence for the improvement of this HCA developed specifically for China.
Directory of Open Access Journals (Sweden)
Ahmed Sabah Al-Araji
2017-08-01
Full Text Available This paper presents a new development of an on-line hybrid self-tuning control algorithm of the Field Programmable Gate Array - Proportional Integral Derivative - Pulse Width Modulation (FPGA-PID-PWM controller for DC-DC buck converter which is used in battery operation of mobile applications. The main goal in this work is to propose structure of the hybrid Bees-PSO tuning control algorithm which has a capability of quickly and precisely searching in the global regions in order to obtain optimal gain parameters for the proposed controller to generate the best voltage control action to achieve the desired performance of the Buck converter output. Matlab simulation results and Xilinx development tool Integrated Software Environment (ISE experimental work show the robustness and effectiveness of the proposed on-line hybrid Bees-PSO tuning control algorithm in terms of obtaining smooth and unsaturated state voltage control action and minimizing the tracking voltage error of the Buck converter output. Moreover, the fitness evaluation number is reduced.
International Nuclear Information System (INIS)
Spiekerman, G.
1988-09-01
A partial blockage of the cooling channels of a fuel element in a swimming pool reactor could lead to vapour generation and to burn-out. To detect such anomalies, a pattern recognition algorithm based on power spectra density (PSD) proposed by Piety was further developed and implemented on a PDP 11/23 for on-line applications. This algorithm identifies anomalies by measuring the PSD on the process signal and comparing them with a standard baseline previously formed. Up to 8 decision discriminants help to recognize spectral changes due to anomalies. In our application, to detect boiling as quickly as possible with sufficient sensitivity, Piety's algorithm was modified using overlapped Fast-Fourier-Transform-Processing and the averaging of the PSDs over a large sample of preceding instantaneous PSDs. This processing allows high sensitivity in detecting weak disturbances without reducing response time. The algorithm was tested with simulation-of-boiling experiments where nitrogen in a cooling channel of a mock-up of a fuel element was injected. Void fractions higher than 30 % in the channel can be detected. In the case of boiling, it is believed that this limit is lower because collapsing bubbles could give rise to stronger fluctuations. The algorithm was also tested with a boiling experiment where the reactor coolant flow was actually reduced. The results showed that the discriminant D5 of Piety's algorithm based on neutron noise obtained from the existing neutron chambers of the reactor control system could sensitively recognize boiling. The detection time amounts to 7-30 s depending on the strength of the disturbances. Other events, which arise during a normal reactor run like scrams, removal of isotope elements without scramming or control rod movements and which could lead to false alarms, can be distinguished from boiling. 49 refs., 104 figs., 5 tabs
SHIFT: server for hidden stops analysis in frame-shifted translation.
Gupta, Arun; Singh, Tiratha Raj
2013-02-23
Frameshift is one of the three classes of recoding. Frame-shifts lead to waste of energy, resources and activity of the biosynthetic machinery. In addition, some peptides synthesized after frame-shifts are probably cytotoxic which serve as plausible cause for innumerable number of diseases and disorders such as muscular dystrophies, lysosomal storage disorders, and cancer. Hidden stop codons occur naturally in coding sequences among all organisms. These codons are associated with the early termination of translation for incorrect reading frame selection and help to reduce the metabolic cost related to the frameshift events. Researchers have identified several consequences of hidden stop codons and their association with myriad disorders. However the wealth of information available is speckled and not effortlessly acquiescent to data-mining. To reduce this gap, this work describes an algorithmic web based tool to study hidden stops in frameshifted translation for all the lineages through respective genetic code systems. This paper describes SHIFT, an algorithmic web application tool that provides a user-friendly interface for identifying and analyzing hidden stops in frameshifted translation of genomic sequences for all available genetic code systems. We have calculated the correlation between codon usage frequencies and the plausible contribution of codons towards hidden stops in an off-frame context. Markovian chains of various order have been used to model hidden stops in frameshifted peptides and their evolutionary association with naturally occurring hidden stops. In order to obtain reliable and persuasive estimates for the naturally occurring and predicted hidden stops statistical measures have been implemented. This paper presented SHIFT, an algorithmic tool that allows user-friendly exploration, analysis, and visualization of hidden stop codons in frameshifted translations. It is expected that this web based tool would serve as a useful complement for
Variational Infinite Hidden Conditional Random Fields
Bousmalis, Konstantinos; Zafeiriou, Stefanos; Morency, Louis-Philippe; Pantic, Maja; Ghahramani, Zoubin
2015-01-01
Hidden conditional random fields (HCRFs) are discriminative latent variable models which have been shown to successfully learn the hidden structure of a given classification problem. An Infinite hidden conditional random field is a hidden conditional random field with a countably infinite number of
International Nuclear Information System (INIS)
Bao Yidong; Hu Sibo; Lang Zhikui; Hu Ping
2005-01-01
A fast simulation scheme for 3D curved binder flanging and blank shape prediction of sheet metal based on one-step inverse finite element method is proposed, in which the total plasticity theory and proportional loading assumption are used. The scheme can be actually used to simulate 3D flanging with complex curve binder shape, and suitable for simulating any type of flanging model by numerically determining the flanging height and flanging lines. Compared with other methods such as analytic algorithm and blank sheet-cut return method, the prominent advantage of the present scheme is that it can directly predict the location of the 3D flanging lines when simulating the flanging process. Therefore, the prediction time of flanging lines will be obviously decreased. Two typical 3D curve binder flanging including stretch and shrink characters are simulated in the same time by using the present scheme and incremental FE non-inverse algorithm based on incremental plasticity theory, which show the validity and high efficiency of the present scheme
Increased taxon sampling reveals thousands of hidden orthologs in flatworms
2017-01-01
Gains and losses shape the gene complement of animal lineages and are a fundamental aspect of genomic evolution. Acquiring a comprehensive view of the evolution of gene repertoires is limited by the intrinsic limitations of common sequence similarity searches and available databases. Thus, a subset of the gene complement of an organism consists of hidden orthologs, i.e., those with no apparent homology to sequenced animal lineages—mistakenly considered new genes—but actually representing rapidly evolving orthologs or undetected paralogs. Here, we describe Leapfrog, a simple automated BLAST pipeline that leverages increased taxon sampling to overcome long evolutionary distances and identify putative hidden orthologs in large transcriptomic databases by transitive homology. As a case study, we used 35 transcriptomes of 29 flatworm lineages to recover 3427 putative hidden orthologs, some unidentified by OrthoFinder and HaMStR, two common orthogroup inference algorithms. Unexpectedly, we do not observe a correlation between the number of putative hidden orthologs in a lineage and its “average” evolutionary rate. Hidden orthologs do not show unusual sequence composition biases that might account for systematic errors in sequence similarity searches. Instead, gene duplication with divergence of one paralog and weak positive selection appear to underlie hidden orthology in Platyhelminthes. By using Leapfrog, we identify key centrosome-related genes and homeodomain classes previously reported as absent in free-living flatworms, e.g., planarians. Altogether, our findings demonstrate that hidden orthologs comprise a significant proportion of the gene repertoire in flatworms, qualifying the impact of gene losses and gains in gene complement evolution. PMID:28400424
Managing Hidden Costs of Offshoring
DEFF Research Database (Denmark)
Larsen, Marcus M.; Pedersen, Torben
2014-01-01
This chapter investigates the concept of the ‘hidden costs’ of offshoring, i.e. unexpected offshoring costs exceeding the initially expected costs. Due to the highly undefined nature of these costs, we position our analysis towards the strategic responses of firms’ realisation of hidden costs....... In this regard, we argue that a major response to the hidden costs of offshoring is the identification and utilisation of strategic mechanisms in the organisational design to eventually achieving system integration in a globally dispersed and disaggregated organisation. This is heavily moderated by a learning......-by-doing process, where hidden costs motivate firms and their employees to search for new and better knowledge on how to successfully manage the organisation. We illustrate this thesis based on the case of the LEGO Group....
The Hidden Costs of Offshoring
DEFF Research Database (Denmark)
Møller Larsen, Marcus; Manning, Stephan; Pedersen, Torben
2011-01-01
of offshoring. Specifically, we propose that hidden costs can be explained by the combination of increasing structural, operational and social complexity of offshoring activities. In addition, we suggest that firm orientation towards organizational design as part of an offshoring strategy and offshoring......This study seeks to explain hidden costs of offshoring, i.e. unexpected costs resulting from the relocation of business tasks and activities outside the home country. We develop a model that highlights the role of complexity, design orientation and experience in explaining hidden costs...... experience moderate the relationship between complexity and hidden costs negatively i.e. reduces the cost generating impact of complexity. We develop three hypotheses and test them on comprehensive data from the Offshoring Research Network (ORN). In general, we find support for our hypotheses. A key result...
Child Abuse: The Hidden Bruises
... for Families - Vietnamese Spanish Facts for Families Guide Child Abuse - The Hidden Bruises No. 5; Updated November 2014 The statistics on physical child abuse are alarming. It is estimated hundreds of thousands ...
Hidden Statistics of Schroedinger Equation
Zak, Michail
2011-01-01
Work was carried out in determination of the mathematical origin of randomness in quantum mechanics and creating a hidden statistics of Schr dinger equation; i.e., to expose the transitional stochastic process as a "bridge" to the quantum world. The governing equations of hidden statistics would preserve such properties of quantum physics as superposition, entanglement, and direct-product decomposability while allowing one to measure its state variables using classical methods.
Hidden Curriculum: An Analytical Definition
Directory of Open Access Journals (Sweden)
Mohammad Reza Andarvazh
2018-03-01
Full Text Available Background: The concept of hidden curriculum was first used by Philip Jackson in 1968, and Hafferty brought this concept to the medical education. Many of the subjects that medical students learn are attributed to this curriculum. So far several definitions have been presented for the hidden curriculum, which on the one hand made this concept richer, and on the other hand, led to confusion and ambiguity.This paper tries to provide a clear and comprehensive definition of it.Methods: In this study, concept analysis of McKenna method was used. Using keywords and searching in the databases, 561 English and 26 Persian references related to the concept was found, then by limitingthe research scope, 125 abstracts and by finding more relevant references, 55 articles were fully studied.Results: After analyzing the definitions by McKenna method, the hidden curriculum is defined as follows: The hidden curriculum is a hidden, powerful, intrinsic in organizational structure and culture and sometimes contradictory message, conveyed implicitly and tacitly in the learning environment by structural and human factors and its contents includes cultural habits and customs, norms, values, belief systems, attitudes, skills, desires and behavioral and social expectations can have a positive or negative effect, unplanned, neither planners nor teachers, nor learners are aware of it. The ultimate consequence of the hidden curriculum includes reproducing the existing class structure, socialization, and familiarizing learners for transmission and joining the professional world.Conclusion: Based on the concept analysis, we arrived at an analytical definition of the hidden curriculum that could be useful for further studies in this area.Keywords: CONCEPT ANALYSIS, HIDDEN CURRICULUM, MCKENNA’S METHOD
Eliseev, Platon; Balantcev, Grigory; Nikishova, Elena; Gaida, Anastasia; Bogdanova, Elena; Enarson, Donald; Ornstein, Tara; Detjen, Anne; Dacombe, Russell; Gospodarevskaya, Elena; Phillips, Patrick P J; Mann, Gillian; Squire, Stephen Bertel; Mariandyshev, Andrei
2016-01-01
In the Arkhangelsk region of Northern Russia, multidrug-resistant (MDR) tuberculosis (TB) rates in new cases are amongst the highest in the world. In 2014, MDR-TB rates reached 31.7% among new cases and 56.9% among retreatment cases. The development of new diagnostic tools allows for faster detection of both TB and MDR-TB and should lead to reduced transmission by earlier initiation of anti-TB therapy. The PROVE-IT (Policy Relevant Outcomes from Validating Evidence on Impact) Russia study aimed to assess the impact of the implementation of line probe assay (LPA) as part of an LPA-based diagnostic algorithm for patients with presumptive MDR-TB focusing on time to treatment initiation with time from first-care seeking visit to the initiation of MDR-TB treatment rather than diagnostic accuracy as the primary outcome, and to assess treatment outcomes. We hypothesized that the implementation of LPA would result in faster time to treatment initiation and better treatment outcomes. A culture-based diagnostic algorithm used prior to LPA implementation was compared to an LPA-based algorithm that replaced BacTAlert and Löwenstein Jensen (LJ) for drug sensitivity testing. A total of 295 MDR-TB patients were included in the study, 163 diagnosed with the culture-based algorithm, 132 with the LPA-based algorithm. Among smear positive patients, the implementation of the LPA-based algorithm was associated with a median decrease in time to MDR-TB treatment initiation of 50 and 66 days compared to the culture-based algorithm (BacTAlert and LJ respectively, ptime to MDR-TB treatment initiation of 78 days when compared to the culture-based algorithm (LJ, ptime to MDR diagnosis and earlier treatment initiation as well as better treatment outcomes for patients with MDR-TB. These findings also highlight the need for further improvements within the health system to reduce both patient and diagnostic delays to truly optimize the impact of new, rapid diagnostics.
Directory of Open Access Journals (Sweden)
Tiannan Ma
2016-12-01
Full Text Available Accurate forecasting of icing thickness has great significance for ensuring the security and stability of the power grid. In order to improve the forecasting accuracy, this paper proposes an icing forecasting system based on the fireworks algorithm and weighted least square support vector machine (W-LSSVM. The method of the fireworks algorithm is employed to select the proper input features with the purpose of eliminating redundant influence. In addition, the aim of the W-LSSVM model is to train and test the historical data-set with the selected features. The capability of this proposed icing forecasting model and framework is tested through simulation experiments using real-world icing data from the monitoring center of the key laboratory of anti-ice disaster, Hunan, South China. The results show that the proposed W-LSSVM-FA method has a higher prediction accuracy and it may be a promising alternative for icing thickness forecasting.
A note on the linear memory Baum-Welch algorithm
DEFF Research Database (Denmark)
Jensen, Jens Ledet
2009-01-01
We demonstrate the simplicity and generality of the recently introduced linear space Baum-Welch algorithm for hidden Markov models. We also point to previous literature on the subject.......We demonstrate the simplicity and generality of the recently introduced linear space Baum-Welch algorithm for hidden Markov models. We also point to previous literature on the subject....
Line-based monocular graph SLAM algorithm%基于图优化的单目线特征SLAM算法
Institute of Scientific and Technical Information of China (English)
董蕊芳; 柳长安; 杨国田; 程瑞营
2017-01-01
A new line based 6-DOF monocular algorithm for using graph simultaneous localization and mapping(SLAM) algoritm was proposed.First,the straight line were applied as a feature instead of points,due to a map consisting of a sparse set of 3D points is unable to describe the structure of the surrounding world.Secondly,most of previous line-based SLAM algorithms were focused on filtering-based solutions suffering from the inconsistent when applied to the inherently non-linear SLAM problem,in contrast,the graph-based solution was used to improve the accuracy of the localization and the consistency of mapping.Thirdly,a special line representation was exploited for combining the Plücker coordinates with the Cayley representation.The Plücker coordinates were used for the 3D line projection function,and the Cayley representation helps to update the line parameters during the non-linear optimization process.Finally,the simulation experiment shows that the proposed algorithm outperforms odometry and EKF-based SLAM in terms of the pose estimation,while the sum of the squared errors (SSE) and root-mean-square error (RMSE) of proposed method are 2.5％ and 10.5％ of odometry,and 22.4％ and 33％ of EKF-based SLAM.The reprojection error is only 45.5 pixels.The real image experiment shows that the proposed algorithm obtains only 958 cm2 and 3.941 3 cm the SSE and RMSE of pose estimation.Therefore,it can be concluded that the proposed algorithm is effective and accuracy.%提出了基于图优化的单目线特征同时定位和地图构建(SLAM)的方法.首先,针对主流视觉SLAM算法因采用点作为特征而导致构建的点云地图稀疏、难以准确表达环境结构信息等缺点,采用直线作为特征来构建地图.然后,根据现有线特征的SLAM算法都是基于滤波器的SLAM框架、存在线性化及更新效率的问题,采用基于图优化的SLAM解决方案以提高定位精度及地图构建的一致性和准确性.将线特征的Plücker坐
The Consensus String Problem and the Complexity of Comparing Hidden Markov Models
DEFF Research Database (Denmark)
Lyngsø, Rune Bang; Pedersen, Christian Nørgaard Storm
2002-01-01
The basic theory of hidden Markov models was developed and applied to problems in speech recognition in the late 1960s, and has since then been applied to numerous problems, e.g. biological sequence analysis. Most applications of hidden Markov models are based on efficient algorithms for computing...... the probability of generating a given string, or computing the most likely path generating a given string. In this paper we consider the problem of computing the most likely string, or consensus string, generated by a given model, and its implications on the complexity of comparing hidden Markov models. We show...... that computing the consensus string, and approximating its probability within any constant factor, is NP-hard, and that the same holds for the closely related labeling problem for class hidden Markov models. Furthermore, we establish the NP-hardness of comparing two hidden Markov models under the L∞- and L1...
Hidden ion population: Revisited
International Nuclear Information System (INIS)
Olsen, R.C.; Chappell, C.R.; Gallagher, D.L.; Green, J.L.; Gurnett, D.A.
1985-01-01
Satellite potentials in the outer plasmasphere range from near zero to +5 to +10 V. Under such conditions ion measurements may not include the low energy core of the plasma population. In eclipse, the photoelectron current drops to zero, and the spacecraft potential can drop to near zero volts. In regions where the ambient plasma density is below 100 cm -3 , previously unobserved portions of the ambient plasma distribution function can become visible in eclipse. A survey of the data obtained from the retarding ion mass spectrometer (RIMS) on Dynamics Explorer 1 shows that the RIMS detector generally measured the isotropic background in both sunlight and eclipse in the plasma-sphere. Absolute density measurements for the ''hidden'' ion population are obtained for the first time using the plasma wave instrument observations of the upper hybrid resonance. Agreement in total density is found in sunlight and eclipse measurements at densities above 80 cm -3 . In eclipse, agreement is found at densities as low as 20 cm -3 . The isotropic plasma composition is primarily H + , with approx.10% He + , and 0.1 to 1.0% O + . A low energy field-aligned ion population appears in eclipse measurements outside the plasmasphere, which is obscured in sunlight. These field-aligned ions can be interpreted as field-aligned flows with densities of a few particles per cubic centimeter, flowing at 5-20 km/s. The problem in measuring these field-aligned flows in sunlight is the masking of the high energy tail of the field-aligned distribution by the isotropic background. Effective measurement of the core of the magnetospheric plasma distribution awaits satellites with active means of controlling the satellite potential
Hidden Markov Model for Stock Selection
Directory of Open Access Journals (Sweden)
Nguyet Nguyen
2015-10-01
Full Text Available The hidden Markov model (HMM is typically used to predict the hidden regimes of observation data. Therefore, this model finds applications in many different areas, such as speech recognition systems, computational molecular biology and financial market predictions. In this paper, we use HMM for stock selection. We first use HMM to make monthly regime predictions for the four macroeconomic variables: inflation (consumer price index (CPI, industrial production index (INDPRO, stock market index (S&P 500 and market volatility (VIX. At the end of each month, we calibrate HMM’s parameters for each of these economic variables and predict its regimes for the next month. We then look back into historical data to find the time periods for which the four variables had similar regimes with the forecasted regimes. Within those similar periods, we analyze all of the S&P 500 stocks to identify which stock characteristics have been well rewarded during the time periods and assign scores and corresponding weights for each of the stock characteristics. A composite score of each stock is calculated based on the scores and weights of its features. Based on this algorithm, we choose the 50 top ranking stocks to buy. We compare the performances of the portfolio with the benchmark index, S&P 500. With an initial investment of $100 in December 1999, over 15 years, in December 2014, our portfolio had an average gain per annum of 14.9% versus 2.3% for the S&P 500.
Genetic Algorithm Optimized Neural Networks Ensemble as ...
African Journals Online (AJOL)
Marquardt algorithm by varying conditions such as inputs, hidden neurons, initialization, training sets and random Gaussian noise injection to ... Several such ensembles formed the population which was evolved to generate the fittest ensemble.
Yang, Yue; Wang, Lei; Wu, Yongjiang; Liu, Xuesong; Bi, Yuan; Xiao, Wei; Chen, Yong
2017-07-01
There is a growing need for the effective on-line process monitoring during the manufacture of traditional Chinese medicine to ensure quality consistency. In this study, the potential of near infrared (NIR) spectroscopy technique to monitor the extraction process of Flos Lonicerae Japonicae was investigated. A new algorithm of synergy interval PLS with genetic algorithm (Si-GA-PLS) was proposed for modeling. Four different PLS models, namely Full-PLS, Si-PLS, GA-PLS, and Si-GA-PLS, were established, and their performances in predicting two quality parameters (viz. total acid and soluble solid contents) were compared. In conclusion, Si-GA-PLS model got the best results due to the combination of superiority of Si-PLS and GA. For Si-GA-PLS, the determination coefficient (Rp2) and root-mean-square error for the prediction set (RMSEP) were 0.9561 and 147.6544 μg/ml for total acid, 0.9062 and 0.1078% for soluble solid contents, correspondingly. The overall results demonstrated that the NIR spectroscopy technique combined with Si-GA-PLS calibration is a reliable and non-destructive alternative method for on-line monitoring of the extraction process of TCM on the production scale.
Boursier, Jérôme; de Ledinghen, Victor; Leroy, Vincent; Anty, Rodolphe; Francque, Sven; Salmon, Dominique; Lannes, Adrien; Bertrais, Sandrine; Oberti, Frederic; Fouchard-Hubert, Isabelle; Calès, Paul
2017-06-01
Chronic liver diseases (CLD) are common, and are therefore mainly managed by non-hepatologists. These physicians lack access to the best non-invasive tests of liver fibrosis, and consequently cannot accurately determine the disease severity. Referral to a hepatologist is then needed. We aimed to implement an algorithm, comprising a new first-line test usable by all physicians, for the detection of advanced liver fibrosis in all CLD patients. Diagnostic study: 3754 CLD patients with liver biopsy were 2:1 randomized into derivation and validation sets. Prognostic study: longitudinal follow-up of 1275 CLD patients with baseline fibrosis tests. Diagnostic study: the easy liver fibrosis test (eLIFT), an "at-a-glance" sum of points attributed to age, gender, gamma-glutamyl transferase, aspartate aminotransferase (AST), platelets and prothrombin time, was developed for the diagnosis of advanced fibrosis. In the validation set, eLIFT and fibrosis-4 (FIB4) had the same sensitivity (78.0% vs. 76.6%, p=0.470) but eLIFT gave fewer false positive results, especially in patients ≥60years old (53.8% vs. 82.0%, ptest. FibroMeter with vibration controlled transient elastography (VCTE) was the most accurate among the eight fibrosis tests evaluated. The sensitivity of the eLIFT-FM VCTE algorithm (first-line eLIFT, second-line FibroMeter VCTE ) was 76.1% for advanced fibrosis and 92.1% for cirrhosis. Prognostic study: patients diagnosed as having "no/mild fibrosis" by the algorithm had excellent liver-related prognosis with thus no need for referral to a hepatologist. The eLIFT-FM VCTE algorithm extends the detection of advanced liver fibrosis to all CLD patients and reduces unnecessary referrals of patients without significant CLD to hepatologists. Blood fibrosis tests and transient elastography accurately diagnose advanced liver fibrosis in the large population of patients having chronic liver disease, but these non-invasive tests are only currently available in specialized
Stargate of the Hidden Multiverse
Directory of Open Access Journals (Sweden)
Alexander Antonov
2016-02-01
Full Text Available Concept of Monoverse, which corresponds to the existing broad interpretation of the second postulate of the special theory of relativity, is not consistent with the modern astrophysical reality — existence of the dark matter and the dark energy, the total mass-energy of which is ten times greater than the mass-energy of the visible universe (which has been considered as the entire universe until very recent . This concept does not allow to explain their rather unusual properties — invisibility and lack of baryon content — which would seem to even destroy the very modern understanding of the term ‘matter’. However, all numerous alternative concepts of Multiverses, which have been proposed until today, are unable to explain these properties of the dark matter and dark energy. This article describes a new concept: the concept of the hidden Multiverse and hidden Supermultiverse, which mutual invisibility of parallel universes is explained by the physical reality of imaginary numbers. This concept completely explains the phenomenon of the dark matter and the dark energy. Moreover, it is shown that the dark matter and the dark energy are the experimental evidence for the existence of the hidden Multiverse. Described structure of the hidden Multiverse is fully consistent with the data obtained by the space stations WMAP and Planck. An extremely important property of the hidden Multiverse is an actual possibility of its permeation through stargate located on the Earth.
Hidden photons in connection to dark matter
Energy Technology Data Exchange (ETDEWEB)
Andreas, Sarah; Ringwald, Andreas [Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany); Goodsell, Mark D. [CPhT, Ecole Polytechnique, Palaiseau (France)
2013-06-15
Light extra U(1) gauge bosons, so called hidden photons, which reside in a hidden sector have attracted much attention since they are a well motivated feature of many scenarios beyond the Standard Model and furthermore could mediate the interaction with hidden sector dark matter.We review limits on hidden photons from past electron beam dump experiments including two new limits from such experiments at KEK and Orsay. In addition, we study the possibility of having dark matter in the hidden sector. A simple toy model and different supersymmetric realisations are shown to provide viable dark matter candidates in the hidden sector that are in agreement with recent direct detection limits.
Hidden photons in connection to dark matter
International Nuclear Information System (INIS)
Andreas, Sarah; Ringwald, Andreas; Goodsell, Mark D.
2013-06-01
Light extra U(1) gauge bosons, so called hidden photons, which reside in a hidden sector have attracted much attention since they are a well motivated feature of many scenarios beyond the Standard Model and furthermore could mediate the interaction with hidden sector dark matter.We review limits on hidden photons from past electron beam dump experiments including two new limits from such experiments at KEK and Orsay. In addition, we study the possibility of having dark matter in the hidden sector. A simple toy model and different supersymmetric realisations are shown to provide viable dark matter candidates in the hidden sector that are in agreement with recent direct detection limits.
The Consensus String Problem and the Complexity of Comparing Hidden Markov Models
DEFF Research Database (Denmark)
Lyngsø, Rune Bang; Pedersen, Christian Nørgaard Storm
2002-01-01
The basic theory of hidden Markov models was developed and applied to problems in speech recognition in the late 1960s, and has since then been applied to numerous problems, e.g. biological sequence analysis. Most applications of hidden Markov models are based on efficient algorithms for computing......-norms. We discuss the applicability of the technique used for proving the hardness of comparing two hidden Markov models under the L1-norm to other measures of distance between probability distributions. In particular, we show that it cannot be used for proving NP-hardness of determining the Kullback...
Storage capacity of the Tilinglike Learning Algorithm
International Nuclear Information System (INIS)
Buhot, Arnaud; Gordon, Mirta B.
2001-01-01
The storage capacity of an incremental learning algorithm for the parity machine, the Tilinglike Learning Algorithm, is analytically determined in the limit of a large number of hidden perceptrons. Different learning rules for the simple perceptron are investigated. The usual Gardner-Derrida rule leads to a storage capacity close to the upper bound, which is independent of the learning algorithm considered
Hidden worlds in quantum physics
Gouesbet, Gérard
2014-01-01
The past decade has witnessed a resurgence in research and interest in the areas of quantum computation and entanglement. This new book addresses the hidden worlds or variables of quantum physics. Author Gérard Gouesbet studied and worked with a former student of Louis de Broglie, a pioneer of quantum physics. His presentation emphasizes the history and philosophical foundations of physics, areas that will interest lay readers as well as professionals and advanced undergraduate and graduate students of quantum physics. The introduction is succeeded by chapters offering background on relevant concepts in classical and quantum mechanics, a brief history of causal theories, and examinations of the double solution, pilot wave, and other hidden-variables theories. Additional topics include proofs of possibility and impossibility, contextuality, non-locality, classification of hidden-variables theories, and stochastic quantum mechanics. The final section discusses how to gain a genuine understanding of quantum mec...
International Nuclear Information System (INIS)
Abdulsadda, Ahmad T; Tan, Xiaobo
2013-01-01
Motivated by the lateral line system of fish, arrays of flow sensors have been proposed as a new sensing modality for underwater robots. Existing studies on such artificial lateral lines (ALLs) have been mostly focused on the localization of a fixed underwater vibrating sphere (dipole source). In this paper we examine the problem of tracking a moving dipole source using an ALL system. Based on an analytical model for the moving dipole-generated flow field, we formulate a nonlinear estimation problem that aims to minimize the error between the measured and model-predicted magnitudes of flow velocities at the sensor sites, which is subsequently solved with the Gauss–Newton scheme. A sliding discrete Fourier transform (SDFT) algorithm is proposed to efficiently compute the evolving signal magnitudes based on the flow velocity measurements. Simulation indicates that it is adequate and more computationally efficient to use only the signal magnitudes corresponding to the dipole vibration frequency. Finally, experiments conducted with an artificial lateral line consisting of six ionic polymer–metal composite (IPMC) flow sensors demonstrate that the proposed scheme is able to simultaneously locate the moving dipole and estimate its vibration amplitude and traveling speed with small errors. (paper)
Kang, Qian; Ru, Qingguo; Liu, Yan; Xu, Lingyan; Liu, Jia; Wang, Yifei; Zhang, Yewen; Li, Hui; Zhang, Qing; Wu, Qing
2016-01-01
An on-line near infrared (NIR) spectroscopy monitoring method with an appropriate multivariate calibration method was developed for the extraction process of Fu-fang Shuanghua oral solution (FSOS). On-line NIR spectra were collected through two fiber optic probes, which were designed to transmit NIR radiation by a 2 mm flange. Partial least squares (PLS), interval PLS (iPLS) and synergy interval PLS (siPLS) algorithms were used comparatively for building the calibration regression models. During the extraction process, the feasibility of NIR spectroscopy was employed to determine the concentrations of chlorogenic acid (CA) content, total phenolic acids contents (TPC), total flavonoids contents (TFC) and soluble solid contents (SSC). High performance liquid chromatography (HPLC), ultraviolet spectrophotometric method (UV) and loss on drying methods were employed as reference methods. Experiment results showed that the performance of siPLS model is the best compared with PLS and iPLS. The calibration models for AC, TPC, TFC and SSC had high values of determination coefficients of (R2) (0.9948, 0.9992, 0.9950 and 0.9832) and low root mean square error of cross validation (RMSECV) (0.0113, 0.0341, 0.1787 and 1.2158), which indicate a good correlation between reference values and NIR predicted values. The overall results show that the on line detection method could be feasible in real application and would be of great value for monitoring the mixed decoction process of FSOS and other Chinese patent medicines.
Detecting hidden particles with MATHUSLA
Evans, Jared A.
2018-03-01
A hidden sector containing light long-lived particles provides a well-motivated place to find new physics. The recently proposed MATHUSLA experiment has the potential to be extremely sensitive to light particles originating from rare meson decays in the very long lifetime region. In this work, we illustrate this strength with the specific example of a light scalar mixed with the standard model-like Higgs boson, a model where MATHUSLA can further probe unexplored parameter space from exotic Higgs decays. Design augmentations should be considered in order to maximize the ability of MATHUSLA to discover very light hidden sector particles.
Hidden Crises and Communication: An Interactional Analysis of Hidden Crises
dr. Annette Klarenbeek
2011-01-01
In this paper I describe the ways in which the communication discipline can make a hidden crisis transparent. For this purpose I examine the concept of crisis entrepreneurship from a communication point of view. Using discourse analysis, I analyse the discursive practices of crisis entrepreneurs in
Hidden Crises and Communication : An Interactional Analysis of Hidden Crises
dr. Annette Klarenbeek
2011-01-01
In this paper I describe the ways in which the communication discipline can make a hidden crisis transparent. For this purpose I examine the concept of crisis entrepreneurship from a communication point of view. Using discourse analysis, I analyse the discursive practices of crisis entrepreneurs in
About Non-Line-Of-Sight Satellite Detection and Exclusion in a 3D Map-Aided Localization Algorithm
Directory of Open Access Journals (Sweden)
François Peyret
2013-01-01
Full Text Available Reliable GPS positioning in city environment is a key issue: actually, signals are prone to multipath, with poor satellite geometry in many streets. Using a 3D urban model to forecast satellite visibility in urban contexts in order to improve GPS localization is the main topic of the present article. A virtual image processing that detects and eliminates possible faulty measurements is the core of this method. This image is generated using the position estimated a priori by the navigation process itself, under road constraints. This position is then updated by measurements to line-of-sight satellites only. This closed-loop real-time processing has shown very first promising full-scale test results.
About Non-Line-Of-Sight Satellite Detection and Exclusion in a 3D Map-Aided Localization Algorithm
Peyraud, Sébastien; Bétaille, David; Renault, Stéphane; Ortiz, Miguel; Mougel, Florian; Meizel, Dominique; Peyret, François
2013-01-01
Reliable GPS positioning in city environment is a key issue actually, signals are prone to multipath, with poor satellite geometry in many streets. Using a 3D urban model to forecast satellite visibility in urban contexts in order to improve GPS localization is the main topic of the present article. A virtual image processing that detects and eliminates possible faulty measurements is the core of this method. This image is generated using the position estimated a priori by the navigation process itself, under road constraints. This position is then updated by measurements to line-of-sight satellites only. This closed-loop real-time processing has shown very first promising full-scale test results. PMID:23344379
Discriminative training of self-structuring hidden control neural models
DEFF Research Database (Denmark)
Sørensen, Helge Bjarup Dissing; Hartmann, Uwe; Hunnerup, Preben
1995-01-01
This paper presents a new training algorithm for self-structuring hidden control neural (SHC) models. The SHC models were trained non-discriminatively for speech recognition applications. Better recognition performance can generally be achieved, if discriminative training is applied instead. Thus...... we developed a discriminative training algorithm for SHC models, where each SHC model for a specific speech pattern is trained with utterances of the pattern to be recognized and with other utterances. The discriminative training of SHC neural models has been tested on the TIDIGITS database...
Kuligowski, J; Quintás, G; Garrigues, S; de la Guardia, M
2010-03-15
A new background correction method for the on-line coupling of gradient liquid chromatography and Fourier transform infrared spectrometry has been developed. It is based on the use of a point-to-point matching algorithm that compares the absorption spectra of the sample data set with those of a previously recorded reference data set in order to select an appropriate reference spectrum. The spectral range used for the point-to-point comparison is selected with minimal user-interaction, thus facilitating considerably the application of the whole method. The background correction method has been successfully tested on a chromatographic separation of four nitrophenols running acetonitrile (0.08%, v/v TFA):water (0.08%, v/v TFA) gradients with compositions ranging from 35 to 85% (v/v) acetonitrile, giving accurate results for both, baseline resolved and overlapped peaks. Copyright (c) 2009 Elsevier B.V. All rights reserved.
Entry deterrence and hidden competition
Lavrutich, Maria; Huisman, Kuno; Kort, Peter
This paper studies strategic investment behavior of firms facing an uncertain demand in a duopoly setting. Firms choose both investment timing and the capacity level while facing additional uncertainty about market participants, which is introduced via the concept of hidden competition. We focus on
Adaptive Partially Hidden Markov Models
DEFF Research Database (Denmark)
Forchhammer, Søren Otto; Rasmussen, Tage
1996-01-01
Partially Hidden Markov Models (PHMM) have recently been introduced. The transition and emission probabilities are conditioned on the past. In this report, the PHMM is extended with a multiple token version. The different versions of the PHMM are applied to bi-level image coding....
The Hidden Dimensions of Databases.
Jacso, Peter
1994-01-01
Discusses methods of evaluating commercial online databases and provides examples that illustrate their hidden dimensions. Topics addressed include size, including the number of records or the number of titles; the number of years covered; and the frequency of updates. Comparisons of Readers' Guide Abstracts and Magazine Article Summaries are…
Hidden supersymmetry and large N
International Nuclear Information System (INIS)
Alfaro, J.
1988-01-01
In this paper we present a new method to deal with the leading order in the large-N expansion of a quantum field theory. The method uses explicitly the hidden supersymmetry that is present in the path-integral formulation of a stochastic process. In addition to this we derive a new relation that is valid in the leading order of the large-N expansion of the hermitian-matrix model for any spacetime dimension. (orig.)
Hybrid Cryptosystem Using Tiny Encryption Algorithm and LUC Algorithm
Rachmawati, Dian; Sharif, Amer; Jaysilen; Andri Budiman, Mohammad
2018-01-01
Security becomes a very important issue in data transmission and there are so many methods to make files more secure. One of that method is cryptography. Cryptography is a method to secure file by writing the hidden code to cover the original file. Therefore, if the people do not involve in cryptography, they cannot decrypt the hidden code to read the original file. There are many methods are used in cryptography, one of that method is hybrid cryptosystem. A hybrid cryptosystem is a method that uses a symmetric algorithm to secure the file and use an asymmetric algorithm to secure the symmetric algorithm key. In this research, TEA algorithm is used as symmetric algorithm and LUC algorithm is used as an asymmetric algorithm. The system is tested by encrypting and decrypting the file by using TEA algorithm and using LUC algorithm to encrypt and decrypt the TEA key. The result of this research is by using TEA Algorithm to encrypt the file, the cipher text form is the character from ASCII (American Standard for Information Interchange) table in the form of hexadecimal numbers and the cipher text size increase by sixteen bytes as the plaintext length is increased by eight characters.
Hidden particle production at the ILC
International Nuclear Information System (INIS)
Fujii, Keisuke; Itoh, Hideo; Okada, Nobuchika; Hano, Hitoshi; Yoshioka, Tamaki
2008-01-01
In a class of new physics models, the new physics sector is completely or partly hidden, namely, a singlet under the standard model (SM) gauge group. Hidden fields included in such new physics models communicate with the standard model sector through higher-dimensional operators. If a cutoff lies in the TeV range, such hidden fields can be produced at future colliders. We consider a scalar field as an example of the hidden fields. Collider phenomenology on this hidden scalar is similar to that of the SM Higgs boson, but there are several features quite different from those of the Higgs boson. We investigate productions of the hidden scalar at the International Linear Collider (ILC) and study the feasibility of its measurements, in particular, how well the ILC distinguishes the scalar from the Higgs boson, through realistic Monte Carlo simulations.
Segmentation of laser range radar images using hidden Markov field models
International Nuclear Information System (INIS)
Pucar, P.
1993-01-01
Segmentation of images in the context of model based stochastic techniques is connected with high, very often unpracticle computational complexity. The objective with this thesis is to take the models used in model based image processing, simplify and use them in suboptimal, but not computationally demanding algorithms. Algorithms that are essentially one-dimensional, and their extensions to two dimensions are given. The model used in this thesis is the well known hidden Markov model. Estimation of the number of hidden states from observed data is a problem that is addressed. The state order estimation problem is of general interest and is not specifically connected to image processing. An investigation of three state order estimation techniques for hidden Markov models is given. 76 refs
Hidden order and disorder effects in URu2Si2
Bernal, O. O.; Moroz, M. E.; Ishida, K.; Murakawa, H.; Reyes, A. P.; Kuhns, P. L.; MacLaughlin, D. E.; Mydosh, J. A.; Gortenmulder, T. J.
2006-05-01
NMR experiments at ambient pressure in URu 2Si 2 demonstrate a linewidth enhancement effect below the hidden order transition temperature T0. We present single-crystal 29Si NMR parameters for various temperatures and for an applied magnetic field perpendicular to the crystal c-axis. By comparing oriented-powder and single-crystal data, we observe that the size of the linewidth enhancement below T0 correlates with the size of the high- T broadening. We measure a 29Si up-field line shift below T0 which indicates the presence of an internal-field average for the entire crystal. This shift also correlates with the high-temperature width. The 101Ru NQR frequency as a function of temperature was also measured. No strong effect on the NQR frequency is observed at T0. Both NMR and NQR measurements suggest a connection between linewidth/disorder effects and the transition to hidden order.
Hidden measurements, hidden variables and the volume representation of transition probabilities
Oliynyk, Todd A.
2005-01-01
We construct, for any finite dimension $n$, a new hidden measurement model for quantum mechanics based on representing quantum transition probabilities by the volume of regions in projective Hilbert space. For $n=2$ our model is equivalent to the Aerts sphere model and serves as a generalization of it for dimensions $n \\geq 3$. We also show how to construct a hidden variables scheme based on hidden measurements and we discuss how joint distributions arise in our hidden variables scheme and th...
Dissipative hidden sector dark matter
Foot, R.; Vagnozzi, S.
2015-01-01
A simple way of explaining dark matter without modifying known Standard Model physics is to require the existence of a hidden (dark) sector, which interacts with the visible one predominantly via gravity. We consider a hidden sector containing two stable particles charged under an unbroken U (1 )' gauge symmetry, hence featuring dissipative interactions. The massless gauge field associated with this symmetry, the dark photon, can interact via kinetic mixing with the ordinary photon. In fact, such an interaction of strength ε ˜10-9 appears to be necessary in order to explain galactic structure. We calculate the effect of this new physics on big bang nucleosynthesis and its contribution to the relativistic energy density at hydrogen recombination. We then examine the process of dark recombination, during which neutral dark states are formed, which is important for large-scale structure formation. Galactic structure is considered next, focusing on spiral and irregular galaxies. For these galaxies we modeled the dark matter halo (at the current epoch) as a dissipative plasma of dark matter particles, where the energy lost due to dissipation is compensated by the energy produced from ordinary supernovae (the core-collapse energy is transferred to the hidden sector via kinetic mixing induced processes in the supernova core). We find that such a dynamical halo model can reproduce several observed features of disk galaxies, including the cored density profile and the Tully-Fisher relation. We also discuss how elliptical and dwarf spheroidal galaxies could fit into this picture. Finally, these analyses are combined to set bounds on the parameter space of our model, which can serve as a guideline for future experimental searches.
International Nuclear Information System (INIS)
Soleymani, S.; Ranjbar, A.M.; Mirabedini, H.
2001-01-01
One method for on-line fault diagnosis in synchronous generator is stator current harmonics analysis. Then artificial neural network is considered in this paper in order to evaluate stator current harmonics in different loads. Training set of artificial neural network is made ready by generator modeling, finite element method and state space model. Many points from generator capability curve are used in order to complete this set. Artificial neural network which is used in this paper is a percept ron network with a single hidden layer, Eight hidden neurons and back propagation algorithm. Results are indicated that the trained artificial neural network can identify stator current harmonics for arbitrary load from the capability curve. The error is less than 10% in comparison with values obtained directly from the CFE-SS algorithm. The rating parameters of modeled generator are 43950 (kV A), 11(KV), 3000 (rpm), 50 (H Z), (P F=0.8)
Hidden Markov models in automatic speech recognition
Wrzoskowicz, Adam
1993-11-01
This article describes a method for constructing an automatic speech recognition system based on hidden Markov models (HMMs). The author discusses the basic concepts of HMM theory and the application of these models to the analysis and recognition of speech signals. The author provides algorithms which make it possible to train the ASR system and recognize signals on the basis of distinct stochastic models of selected speech sound classes. The author describes the specific components of the system and the procedures used to model and recognize speech. The author discusses problems associated with the choice of optimal signal detection and parameterization characteristics and their effect on the performance of the system. The author presents different options for the choice of speech signal segments and their consequences for the ASR process. The author gives special attention to the use of lexical, syntactic, and semantic information for the purpose of improving the quality and efficiency of the system. The author also describes an ASR system developed by the Speech Acoustics Laboratory of the IBPT PAS. The author discusses the results of experiments on the effect of noise on the performance of the ASR system and describes methods of constructing HMM's designed to operate in a noisy environment. The author also describes a language for human-robot communications which was defined as a complex multilevel network from an HMM model of speech sounds geared towards Polish inflections. The author also added mandatory lexical and syntactic rules to the system for its communications vocabulary.
Hidden long evolutionary memory in a model biochemical network
Ali, Md. Zulfikar; Wingreen, Ned S.; Mukhopadhyay, Ranjan
2018-04-01
We introduce a minimal model for the evolution of functional protein-interaction networks using a sequence-based mutational algorithm, and apply the model to study neutral drift in networks that yield oscillatory dynamics. Starting with a functional core module, random evolutionary drift increases network complexity even in the absence of specific selective pressures. Surprisingly, we uncover a hidden order in sequence space that gives rise to long-term evolutionary memory, implying strong constraints on network evolution due to the topology of accessible sequence space.
Exploring inequality violations by classical hidden variables numerically
International Nuclear Information System (INIS)
Vongehr, Sascha
2013-01-01
There are increasingly suggestions for computer simulations of quantum statistics which try to violate Bell type inequalities via classical, common cause correlations. The Clauser–Horne–Shimony–Holt (CHSH) inequality is very robust. However, we argue that with the Einstein–Podolsky–Rosen setup, the CHSH is inferior to the Bell inequality, although and because the latter must assume anti-correlation of entangled photon singlet states. We simulate how often quantum behavior violates both inequalities, depending on the number of photons. Violating Bell 99% of the time is argued to be an ideal benchmark. We present hidden variables that violate the Bell and CHSH inequalities with 50% probability, and ones which violate Bell 85% of the time when missing 13% anti-correlation. We discuss how to present the quantum correlations to a wide audience and conclude that, when defending against claims of hidden classicality, one should demand numerical simulations and insist on anti-correlation and the full amount of Bell violation. -- Highlights: •The widely assumed superiority of the CHSH fails in the EPR problem. •We simulate Bell type inequalities behavior depending on the number of photons. •The core of Bell’s theorem in the EPR setup is introduced in a simple way understandable to a wide audience. •We present hidden variables that violate both inequalities with 50% probability. •Algorithms have been supplied in form of Mathematica programs
Automatic categorization of web pages and user clustering with mixtures of hidden Markov models
Ypma, A.; Heskes, T.M.; Zaiane, O.R.; Srivastav, J.
2003-01-01
We propose mixtures of hidden Markov models for modelling clickstreams of web surfers. Hence, the page categorization is learned from the data without the need for a (possibly cumbersome) manual categorization. We provide an EM algorithm for training a mixture of HMMs and show that additional static
Efficient tests for equivalence of hidden Markov processes and quantum random walks
U. Faigle; A. Schönhuth (Alexander)
2011-01-01
htmlabstractWhile two hidden Markov process (HMP) resp.~quantum random walk (QRW) parametrizations can differ from one another, the stochastic processes arising from them can be equivalent. Here a polynomial-time algorithm is presented which can determine equivalence of two HMP parametrizations
International Nuclear Information System (INIS)
England, R.W.
1979-01-01
Mr. England contends that these hidden costs add up to a figure much higher than those that appear in the electric utilities' profit and loss account - costs that are borne by Federal taxpayers, by nuclear industry workers, and by all those people who must share their environment with nuclear facilities. Costs he details are additional deaths and illnesses resulting from exposure to radiation, and the use of tax dollars to clean up the lethal garbage produced by those activities. He asserts that careless handling of uranium ore and mill tailings in past years has apparently resulted in serious public health problems in those mining communities. In another example, Mr. England states that the failure to isolate uranium tailings physically from their environment has probably contributed to an acute leukemia rate in Mesa County, Colorado. He mentions much of the technology development for power reactors being done by the Federal government, not by private reactor manufacturers - thus, again, hidden costs that do not show up in electric bills of customers. The back end of the nuclear fuel cycle as a place for Federally subsidized research and development is discussed briefly. 1 figure, 2 tables
On Throughput Improvement of Wireless Ad Hoc Networks with Hidden Nodes
Choi, Hong-Seok; Lim, Jong-Tae
In this letter, we present the throughput analysis of the wireless ad hoc networks based on the IEEE 802.11 MAC (Medium Access Control). Especially, our analysis includes the case with the hidden node problem so that it can be applied to the multi-hop networks. In addition, we suggest a new channel access control algorithm to maximize the network throughput and show the usefulness of the proposed algorithm through simulations.
The Hidden Reason Behind Children's Misbehavior.
Nystul, Michael S.
1986-01-01
Discusses hidden reason theory based on the assumptions that: (1) the nature of people is positive; (2) a child's most basic psychological need is involvement; and (3) a child has four possible choices in life (good somebody, good nobody, bad somebody, or severely mentally ill.) A three step approach for implementing hidden reason theory is…
Hidden neural networks: application to speech recognition
DEFF Research Database (Denmark)
Riis, Søren Kamaric
1998-01-01
We evaluate the hidden neural network HMM/NN hybrid on two speech recognition benchmark tasks; (1) task independent isolated word recognition on the Phonebook database, and (2) recognition of broad phoneme classes in continuous speech from the TIMIT database. It is shown how hidden neural networks...
Insight: Exploring Hidden Roles in Collaborative Play
Directory of Open Access Journals (Sweden)
Tricia Shi
2015-06-01
Full Text Available This paper looks into interaction modes between players in co-located, collaborative games. In particular, hidden traitor games, in which one or more players is secretly working against the group mission, has the effect of increasing paranoia and distrust between players, so this paper looks into the opposite of a hidden traitor – a hidden benefactor. Rather than sabotaging the group mission, the hidden benefactor would help the group achieve the end goal while still having a reason to stay hidden. The paper explores what games with such a role can look like and how the role changes player interactions. Finally, the paper addresses the divide between video game and board game interaction modes; hidden roles are not common within video games, but they are of growing prevalence in board games. This fact, combined with the exploration of hidden benefactors, reveals that hidden roles is a mechanic that video games should develop into in order to match board games’ complexity of player interaction modes.
Hidden variables and locality in quantum theory
International Nuclear Information System (INIS)
Shiva, Vandana.
1978-12-01
The status of hidden variables in quantum theory has been debated since the 1920s. The author examines the no-hidden-variable theories of von Neumann, Kochen, Specker and Bell, and finds that they all share one basic assumption: averaging over the hidden variables should reproduce the quantum mechanical probabilities. Von Neumann also makes a linearity assumption, Kochen and Specker require the preservation of certain functional relations between magnitudes, and Bell proposes a locality condition. It has been assumed that the extrastatistical requirements are needed to serve as criteria of success for the introduction of hidden variables because the statistical condition is trivially satisfied, and that Bell's result is based on a locality condition that is physically motivated. The author shows that the requirement of weak locality, which is not physically motivated, is enough to give Bell's result. The proof of Bell's inequality works equally well for any pair of commuting magnitudes satisfying a condition called the degeneracy principle. None of the no-hidden-variable proofs apply to a class of hidden variable theories that are not phase-space reconstructions of quantum mechanics. The author discusses one of these theories, the Bohm-Bub theory, and finds that hidden variable theories that re all the quantum statistics, for single and sequential measurements, must introduce a randomization process for the hidden variables after each measurement. The philosophical significance of this theory lies in the role it can play in solving the conceptual puzzles posed by quantum theory
Hidden supersymmetry and Fermion number fractionalization
International Nuclear Information System (INIS)
Akhoury, R.
1985-01-01
This paper discusses how a hidden supersymmetry of the underlying field theories can be used to interpret and to calculate fermion number fractionalization in different dimensions. This is made possible by relating it to a corresponding Witten index of the hidden supersymmetry. The closely related anomalies in odd dimensions are also discussed
Helioscope bounds on hidden sector photons
International Nuclear Information System (INIS)
Redondo, J.
2008-01-01
The flux of hypothetical ''hidden photons'' from the Sun is computed under the assumption that they interact with normal matter only through kinetic mixing with the ordinary standard model photon. Requiring that the exotic luminosity is smaller than the standard photon luminosity provides limits for the mixing parameter down to χ -14 , depending on the hidden photon mass. Furthermore, it is pointed point out that helioscopes looking for solar axions are also sensitive to hidden photons. The recent results of the CAST collaboration are used to further constrain the mixing parameter χ at low masses (m γ' <1 eV) where the luminosity bound is weaker. In this regime the solar hidden photon ux has a sizable contribution of longitudinally polarized hidden photons of low energy which are invisible for current helioscopes. (orig.)
Confocal non-line-of-sight imaging based on the light-cone transform
O’Toole, Matthew; Lindell, David B.; Wetzstein, Gordon
2018-03-01
How to image objects that are hidden from a camera’s view is a problem of fundamental importance to many fields of research, with applications in robotic vision, defence, remote sensing, medical imaging and autonomous vehicles. Non-line-of-sight (NLOS) imaging at macroscopic scales has been demonstrated by scanning a visible surface with a pulsed laser and a time-resolved detector. Whereas light detection and ranging (LIDAR) systems use such measurements to recover the shape of visible objects from direct reflections, NLOS imaging reconstructs the shape and albedo of hidden objects from multiply scattered light. Despite recent advances, NLOS imaging has remained impractical owing to the prohibitive memory and processing requirements of existing reconstruction algorithms, and the extremely weak signal of multiply scattered light. Here we show that a confocal scanning procedure can address these challenges by facilitating the derivation of the light-cone transform to solve the NLOS reconstruction problem. This method requires much smaller computational and memory resources than previous reconstruction methods do and images hidden objects at unprecedented resolution. Confocal scanning also provides a sizeable increase in signal and range when imaging retroreflective objects. We quantify the resolution bounds of NLOS imaging, demonstrate its potential for real-time tracking and derive efficient algorithms that incorporate image priors and a physically accurate noise model. Additionally, we describe successful outdoor experiments of NLOS imaging under indirect sunlight.
Schilders, W.H.A.; Meijer, P.B.L.; Ciggaar, E.
2008-01-01
In this paper we discuss the use of the state-space modelling MOESP algorithm to generate precise information about the number of neurons and hidden layers in dynamic neural networks developed for the behavioural modelling of electronic circuits. The Bartels–Stewart algorithm is used to transform
Detecting hidden sources-STUK/HUT team
Energy Technology Data Exchange (ETDEWEB)
Nikkinen, M.; Aarnio, P. [Helsinki Univ. of Technology, Espoo (Finland); Honkamaa, T.; Tiilikainen, H. [Finnish Centre for Radiation and Nuclear Safety, Helsinki (Finland)
1997-12-31
The task of the team was to locate and to identify hidden sources in a specified area in Padasjoki Auttoinen village. The team used AB-420 helicopter of the Finnish Frontier Guard. The team had two measuring systems: HPGe system (relative efficiency 18%) and 5`x5` NaI system. The team found two sources in real-time and additional two sources after 24 h analysis time. After the locations and characteristics of the sources were announced it was found out that altogether six sources would have been possible to find using the measured data. The total number of sources was ten. The NaI detector was good at detecting and locating the sources and HPGe was most useful in identification and calculation of the activity estimates. The following development should be made: 1) larger detectors are needed, 2) the software has to be improved. (This has been performed after the exercise) and 3) the navigation must be based on DGPS. visual navigation causes easily gaps between the flight lines and some sources may not be detected. (au).
Detecting hidden sources-STUK/HUT team
Energy Technology Data Exchange (ETDEWEB)
Nikkinen, M; Aarnio, P [Helsinki Univ. of Technology, Espoo (Finland); Honkamaa, T; Tiilikainen, H [Finnish Centre for Radiation and Nuclear Safety, Helsinki (Finland)
1998-12-31
The task of the team was to locate and to identify hidden sources in a specified area in Padasjoki Auttoinen village. The team used AB-420 helicopter of the Finnish Frontier Guard. The team had two measuring systems: HPGe system (relative efficiency 18%) and 5`x5` NaI system. The team found two sources in real-time and additional two sources after 24 h analysis time. After the locations and characteristics of the sources were announced it was found out that altogether six sources would have been possible to find using the measured data. The total number of sources was ten. The NaI detector was good at detecting and locating the sources and HPGe was most useful in identification and calculation of the activity estimates. The following development should be made: 1) larger detectors are needed, 2) the software has to be improved. (This has been performed after the exercise) and 3) the navigation must be based on DGPS. visual navigation causes easily gaps between the flight lines and some sources may not be detected. (au).
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
Hidden scale invariance of metals
DEFF Research Database (Denmark)
Hummel, Felix; Kresse, Georg; Dyre, Jeppe C.
2015-01-01
Density functional theory (DFT) calculations of 58 liquid elements at their triple point show that most metals exhibit near proportionality between the thermal fluctuations of the virial and the potential energy in the isochoric ensemble. This demonstrates a general “hidden” scale invariance...... of metals making the condensed part of the thermodynamic phase diagram effectively one dimensional with respect to structure and dynamics. DFT computed density scaling exponents, related to the Grüneisen parameter, are in good agreement with experimental values for the 16 elements where reliable data were...... available. Hidden scale invariance is demonstrated in detail for magnesium by showing invariance of structure and dynamics. Computed melting curves of period three metals follow curves with invariance (isomorphs). The experimental structure factor of magnesium is predicted by assuming scale invariant...
Verducci, M
2011-01-01
A number of extensions of the Standard Model result in neutral and weakly-coupled particles that decay to multi hadrons or multi leptons with macroscopic decay lengths. These particles with decay paths that can be comparable with ATLAS detector dimensions represent, from an experimental point of view, a challenge both for the trigger and for the reconstruction capabilities of the ATLAS detector. We will present a set of signature driven triggers for the ATLAS detector that target such displaced decays and evaluate their performances for some benchmark models and describe analysis strategies and limits on the production of such long-lived particles. A first estimation of the Hidden Valley trigger rates has been evaluated with 6 pb-1 of data collected at ATLAS during the data taking of 2010.
A survey of hidden-variables theories
Belinfante, F J
1973-01-01
A Survey of Hidden-Variables Theories is a three-part book on the hidden-variable theories, referred in this book as """"theories of the first kind"""". Part I reviews the motives in developing different types of hidden-variables theories. The quest for determinism led to theories of the first kind; the quest for theories that look like causal theories when applied to spatially separated systems that interacted in the past led to theories of the second kind. Parts II and III further describe the theories of the first kind and second kind, respectively. This book is written to make the literat
A classification of hidden-variable properties
International Nuclear Information System (INIS)
Brandenburger, Adam; Yanofsky, Noson
2008-01-01
Hidden variables are extra components added to try to banish counterintuitive features of quantum mechanics. We start with a quantum-mechanical model and describe various properties that can be asked of a hidden-variable model. We present six such properties and a Venn diagram of how they are related. With two existence theorems and three no-go theorems (EPR, Bell and Kochen-Specker), we show which properties of empirically equivalent hidden-variable models are possible and which are not. Formally, our treatment relies only on classical probability models, and physical phenomena are used only to motivate which models to choose
Meng, Xi; Nguyen, Bao D; Ridge, Clark; Shaka, A J
2009-01-01
High-dimensional (HD) NMR spectra have poorer digital resolution than low-dimensional (LD) spectra, for a fixed amount of experiment time. This has led to "reduced-dimensionality" strategies, in which several LD projections of the HD NMR spectrum are acquired, each with higher digital resolution; an approximate HD spectrum is then inferred by some means. We propose a strategy that moves in the opposite direction, by adding more time dimensions to increase the information content of the data set, even if only a very sparse time grid is used in each dimension. The full HD time-domain data can be analyzed by the filter diagonalization method (FDM), yielding very narrow resonances along all of the frequency axes, even those with sparse sampling. Integrating over the added dimensions of HD FDM NMR spectra reconstitutes LD spectra with enhanced resolution, often more quickly than direct acquisition of the LD spectrum with a larger number of grid points in each of the fewer dimensions. If the extra-dimensions do not appear in the final spectrum, and are used solely to boost information content, we propose the moniker hidden-dimension NMR. This work shows that HD peaks have unmistakable frequency signatures that can be detected as single HD objects by an appropriate algorithm, even though their patterns would be tricky for a human operator to visualize or recognize, and even if digital resolution in an HD FT spectrum is very coarse compared with natural line widths.
Aligning the Hidden Curriculum of Management Education with PRME: An Inquiry-Based Framework
Blasco, Maribel
2012-01-01
This article argues that mainstreaming responsible management education in line with the Principles of Responsible Management Education (PRME) requires close attention to the hidden curriculum (HC), that is, the implicit dimensions of educational experiences. Altering formal curricular goals and content alone is not enough to improve students'…
Swallowing sound detection using hidden markov modeling of recurrence plot features
International Nuclear Information System (INIS)
Aboofazeli, Mohammad; Moussavi, Zahra
2009-01-01
Automated detection of swallowing sounds in swallowing and breath sound recordings is of importance for monitoring purposes in which the recording durations are long. This paper presents a novel method for swallowing sound detection using hidden Markov modeling of recurrence plot features. Tracheal sound recordings of 15 healthy and nine dysphagic subjects were studied. The multidimensional state space trajectory of each signal was reconstructed using the Taken method of delays. The sequences of three recurrence plot features of the reconstructed trajectories (which have shown discriminating capability between swallowing and breath sounds) were modeled by three hidden Markov models. The Viterbi algorithm was used for swallowing sound detection. The results were validated manually by inspection of the simultaneously recorded airflow signal and spectrogram of the sounds, and also by auditory means. The experimental results suggested that the performance of the proposed method using hidden Markov modeling of recurrence plot features was superior to the previous swallowing sound detection methods.
Swallowing sound detection using hidden markov modeling of recurrence plot features
Energy Technology Data Exchange (ETDEWEB)
Aboofazeli, Mohammad [Faculty of Engineering, Department of Electrical and Computer Engineering, University of Manitoba, Winnipeg, Manitoba, R3T 5V6 (Canada)], E-mail: umaboofa@cc.umanitoba.ca; Moussavi, Zahra [Faculty of Engineering, Department of Electrical and Computer Engineering, University of Manitoba, Winnipeg, Manitoba, R3T 5V6 (Canada)], E-mail: mousavi@ee.umanitoba.ca
2009-01-30
Automated detection of swallowing sounds in swallowing and breath sound recordings is of importance for monitoring purposes in which the recording durations are long. This paper presents a novel method for swallowing sound detection using hidden Markov modeling of recurrence plot features. Tracheal sound recordings of 15 healthy and nine dysphagic subjects were studied. The multidimensional state space trajectory of each signal was reconstructed using the Taken method of delays. The sequences of three recurrence plot features of the reconstructed trajectories (which have shown discriminating capability between swallowing and breath sounds) were modeled by three hidden Markov models. The Viterbi algorithm was used for swallowing sound detection. The results were validated manually by inspection of the simultaneously recorded airflow signal and spectrogram of the sounds, and also by auditory means. The experimental results suggested that the performance of the proposed method using hidden Markov modeling of recurrence plot features was superior to the previous swallowing sound detection methods.
UV Photography Shows Hidden Sun Damage
... mcat1=de12", ]; for (var c = 0; c UV photography shows hidden sun damage A UV photograph gives ... developing skin cancer and prematurely aged skin. Normal photography UV photography 18 months of age: This boy's ...
Coding with partially hidden Markov models
DEFF Research Database (Denmark)
Forchhammer, Søren; Rissanen, J.
1995-01-01
Partially hidden Markov models (PHMM) are introduced. They are a variation of the hidden Markov models (HMM) combining the power of explicit conditioning on past observations and the power of using hidden states. (P)HMM may be combined with arithmetic coding for lossless data compression. A general...... 2-part coding scheme for given model order but unknown parameters based on PHMM is presented. A forward-backward reestimation of parameters with a redefined backward variable is given for these models and used for estimating the unknown parameters. Proof of convergence of this reestimation is given....... The PHMM structure and the conditions of the convergence proof allows for application of the PHMM to image coding. Relations between the PHMM and hidden Markov models (HMM) are treated. Results of coding bi-level images with the PHMM coding scheme is given. The results indicate that the PHMM can adapt...
Hidden costs, value lost: uninsurance in America
National Research Council Canada - National Science Library
Committee on the Consequences of Uninsurance
2003-01-01
Hidden Cost, Value Lost , the fifth of a series of six books on the consequences of uninsurance in the United States, illustrates some of the economic and social losses to the country of maintaining...
The hidden epidemic: confronting sexually transmitted diseases
National Research Council Canada - National Science Library
Eng, Thomas R; Butler, William T
.... In addition, STDs increase the risk of HIV transmission. The Hidden Epidemic examines the scope of sexually transmitted infections in the United States and provides a critical assessment of the nation's response to this public health crisis...
Perspective: Disclosing hidden sources of funding.
Resnik, David B
2009-09-01
In this article, the author discusses ethical and policy issues related to the disclosure of hidden sources of funding in research. The author argues that authors have an ethical obligation to disclose hidden sources of funding and that journals should adopt policies to enforce this obligation. Journal policies should require disclosure of hidden sources of funding that authors know about and that have a direct relation to their research. To stimulate this discussion, the author describes a recent case: investigators who conducted a lung cancer screening study had received funding from a private foundation that was supported by a tobacco company, but they did not disclose this relationship to the journal. Investigators and journal editors must be prepared to deal with these issues in a manner that promotes honesty, transparency, fairness, and accountability in research. The development of well-defined, reasonable policies pertaining to hidden sources of funding can be a step in this direction.
Hidden Statistics Approach to Quantum Simulations
Zak, Michail
2010-01-01
Recent advances in quantum information theory have inspired an explosion of interest in new quantum algorithms for solving hard computational (quantum and non-quantum) problems. The basic principle of quantum computation is that the quantum properties can be used to represent structure data, and that quantum mechanisms can be devised and built to perform operations with this data. Three basic non-classical properties of quantum mechanics superposition, entanglement, and direct-product decomposability were main reasons for optimism about capabilities of quantum computers that promised simultaneous processing of large massifs of highly correlated data. Unfortunately, these advantages of quantum mechanics came with a high price. One major problem is keeping the components of the computer in a coherent state, as the slightest interaction with the external world would cause the system to decohere. That is why the hardware implementation of a quantum computer is still unsolved. The basic idea of this work is to create a new kind of dynamical system that would preserve the main three properties of quantum physics superposition, entanglement, and direct-product decomposability while allowing one to measure its state variables using classical methods. In other words, such a system would reinforce the advantages and minimize limitations of both quantum and classical aspects. Based upon a concept of hidden statistics, a new kind of dynamical system for simulation of Schroedinger equation is proposed. The system represents a modified Madelung version of Schroedinger equation. It preserves superposition, entanglement, and direct-product decomposability while allowing one to measure its state variables using classical methods. Such an optimal combination of characteristics is a perfect match for simulating quantum systems. The model includes a transitional component of quantum potential (that has been overlooked in previous treatment of the Madelung equation). The role of the
Petro Rents, Political Institutions, and Hidden Wealth
DEFF Research Database (Denmark)
Andersen, Jørgen Juel; Johannesen, Niels; Lassen, David Dreyer
2017-01-01
Do political institutions limit rent seeking by politicians? We study the transformation of petroleum rents, almost universally under direct government control, into hidden wealth using unique data on bank deposits in offshore financial centers that specialize in secrecy and asset protection. Our...... rulers is diverted to secret accounts. We find very limited evidence that shocks to other types of income not directly controlled by governments affect hidden wealth....
Hidden charm molecules in a finite volume
International Nuclear Information System (INIS)
Albaladejo, M.; Hidalgo-Duque, C.; Nieves, J.; Oset, E.
2014-01-01
In the present paper we address the interaction of charmed mesons in hidden charm channels in a finite box. We use the interaction from a recent model based on heavy quark spin symmetry that predicts molecules of hidden charm in the infinite volume. The energy levels in the box are generated within this model, and several methods for the analysis of these levels ("inverse problem") are investigated. (author)
Workplace ageism: discovering hidden bias.
Malinen, Sanna; Johnston, Lucy
2013-01-01
BACKGROUND/STUDY CONTEXT: Research largely shows no performance differences between older and younger employees, or that older workers even outperform younger employees, yet negative attitudes towards older workers can underpin discrimination. Unfortunately, traditional "explicit" techniques for assessing attitudes (i.e., self-report measures) have serious drawbacks. Therefore, using an approach that is novel to organizational contexts, the authors supplemented explicit with implicit (indirect) measures of attitudes towards older workers, and examined the malleability of both. This research consists of two studies. The authors measured self-report (explicit) attitudes towards older and younger workers with a survey, and implicit attitudes with a reaction-time-based measure of implicit associations. In addition, to test whether attitudes were malleable, the authors measured attitudes before and after a mental imagery intervention, where the authors asked participants in the experimental group to imagine respected and valued older workers from their surroundings. Negative, stable implicit attitudes towards older workers emerged in two studies. Conversely, explicit attitudes showed no age bias and were more susceptible to change intervention, such that attitudes became more positive towards older workers following the experimental manipulation. This research demonstrates the unconscious nature of bias against older workers, and highlights the utility of implicit attitude measures in the context of the workplace. In the current era of aging workforce and skill shortages, implicit measures may be necessary to illuminate hidden workplace ageism.
Hidden slow pulsars in binaries
Tavani, Marco; Brookshaw, Leigh
1993-01-01
The recent discovery of the binary containing the slow pulsar PSR 1718-19 orbiting around a low-mass companion star adds new light on the characteristics of binary pulsars. The properties of the radio eclipses of PSR 1718-19 are the most striking observational characteristics of this system. The surface of the companion star produces a mass outflow which leaves only a small 'window' in orbital phase for the detection of PSR 1718-19 around 400 MHz. At this observing frequency, PSR 1718-19 is clearly observable only for about 1 hr out of the total 6.2 hr orbital period. The aim of this Letter is twofold: (1) to model the hydrodynamical behavior of the eclipsing material from the companion star of PSR 1718-19 and (2) to argue that a population of binary slow pulsars might have escaped detection in pulsar surveys carried out at 400 MHz. The possible existence of a population of partially or totally hidden slow pulsars in binaries will have a strong impact on current theories of binary evolution of neutron stars.
Optical character recognition of handwritten Arabic using hidden Markov models
Aulama, Mohannad M.; Natsheh, Asem M.; Abandah, Gheith A.; Olama, Mohammed M.
2011-04-01
The problem of optical character recognition (OCR) of handwritten Arabic has not received a satisfactory solution yet. In this paper, an Arabic OCR algorithm is developed based on Hidden Markov Models (HMMs) combined with the Viterbi algorithm, which results in an improved and more robust recognition of characters at the sub-word level. Integrating the HMMs represents another step of the overall OCR trends being currently researched in the literature. The proposed approach exploits the structure of characters in the Arabic language in addition to their extracted features to achieve improved recognition rates. Useful statistical information of the Arabic language is initially extracted and then used to estimate the probabilistic parameters of the mathematical HMM. A new custom implementation of the HMM is developed in this study, where the transition matrix is built based on the collected large corpus, and the emission matrix is built based on the results obtained via the extracted character features. The recognition process is triggered using the Viterbi algorithm which employs the most probable sequence of sub-words. The model was implemented to recognize the sub-word unit of Arabic text raising the recognition rate from being linked to the worst recognition rate for any character to the overall structure of the Arabic language. Numerical results show that there is a potentially large recognition improvement by using the proposed algorithms.
Single-hidden-layer feed-forward quantum neural network based on Grover learning.
Liu, Cheng-Yi; Chen, Chein; Chang, Ching-Ter; Shih, Lun-Min
2013-09-01
In this paper, a novel single-hidden-layer feed-forward quantum neural network model is proposed based on some concepts and principles in the quantum theory. By combining the quantum mechanism with the feed-forward neural network, we defined quantum hidden neurons and connected quantum weights, and used them as the fundamental information processing unit in a single-hidden-layer feed-forward neural network. The quantum neurons make a wide range of nonlinear functions serve as the activation functions in the hidden layer of the network, and the Grover searching algorithm outstands the optimal parameter setting iteratively and thus makes very efficient neural network learning possible. The quantum neuron and weights, along with a Grover searching algorithm based learning, result in a novel and efficient neural network characteristic of reduced network, high efficient training and prospect application in future. Some simulations are taken to investigate the performance of the proposed quantum network and the result show that it can achieve accurate learning. Copyright © 2013 Elsevier Ltd. All rights reserved.
J. Haase (Jürgen); C. di Mario (Carlo); P.W.J.C. Serruys (Patrick); M.M.J.M. van der Linden (Mark); D.P. Foley (David); W.J. van der Giessen (Wim)
1993-01-01
textabstractIn the Cardiovascular Measurement System (CMS) the edge-detection algorithm, which was primarily designed for the Philips digital cardiac imaging system (DCI), is applied to cinefilms. Comparative validation of CMS and DCI was performed in vitro and in vivo with intracoronary insertion
National Research Council Canada - National Science Library
Napolitano, Marcello
2002-01-01
This project focused on investigating the potential of on-line learning 'hardware-based' neural approximators and controllers to provide fault tolerance capabilities following sensor and actuator failures...
International Nuclear Information System (INIS)
Behringer, K.; Spiekerman, G.; Yadigaroglu, G.
1984-11-01
The neutron noise signal of an initiation-of-boiling experiment performed at the SAPHIR reactor has been analyzed by the PSD-pattern recognition algorithm of Piety (1977); the results indicate that the onset of boiling can be detected by this method. Improved confidence statements for the statistical decision discriminants are given. (Auth.)
Using hidden Markov models to align multiple sequences.
Mount, David W
2009-07-01
A hidden Markov model (HMM) is a probabilistic model of a multiple sequence alignment (msa) of proteins. In the model, each column of symbols in the alignment is represented by a frequency distribution of the symbols (called a "state"), and insertions and deletions are represented by other states. One moves through the model along a particular path from state to state in a Markov chain (i.e., random choice of next move), trying to match a given sequence. The next matching symbol is chosen from each state, recording its probability (frequency) and also the probability of going to that state from a previous one (the transition probability). State and transition probabilities are multiplied to obtain a probability of the given sequence. The hidden nature of the HMM is due to the lack of information about the value of a specific state, which is instead represented by a probability distribution over all possible values. This article discusses the advantages and disadvantages of HMMs in msa and presents algorithms for calculating an HMM and the conditions for producing the best HMM.
Hidden Markov latent variable models with multivariate longitudinal data.
Song, Xinyuan; Xia, Yemao; Zhu, Hongtu
2017-03-01
Cocaine addiction is chronic and persistent, and has become a major social and health problem in many countries. Existing studies have shown that cocaine addicts often undergo episodic periods of addiction to, moderate dependence on, or swearing off cocaine. Given its reversible feature, cocaine use can be formulated as a stochastic process that transits from one state to another, while the impacts of various factors, such as treatment received and individuals' psychological problems on cocaine use, may vary across states. This article develops a hidden Markov latent variable model to study multivariate longitudinal data concerning cocaine use from a California Civil Addict Program. The proposed model generalizes conventional latent variable models to allow bidirectional transition between cocaine-addiction states and conventional hidden Markov models to allow latent variables and their dynamic interrelationship. We develop a maximum-likelihood approach, along with a Monte Carlo expectation conditional maximization (MCECM) algorithm, to conduct parameter estimation. The asymptotic properties of the parameter estimates and statistics for testing the heterogeneity of model parameters are investigated. The finite sample performance of the proposed methodology is demonstrated by simulation studies. The application to cocaine use study provides insights into the prevention of cocaine use. © 2016, The International Biometric Society.
Directory of Open Access Journals (Sweden)
INTAN S. AHMAD
2008-04-01
Full Text Available This work presents the application of a primal-dual interior point method to minimax optimisation problems. The algorithm differs significantly from previous approaches as it involves a novel non-monotone line search procedure, which is based on the use of standard penalty methods as the merit function used for line search. The crucial novel concept is the discretisation of the penalty parameter used over a finite range of orders of magnitude and the provision of a memory list for each such order. An implementation within a logarithmic barrier algorithm for bounds handling is presented with capabilities for large scale application. Case studies presented demonstrate the capabilities of the proposed methodology, which relies on the reformulation of minimax models into standard nonlinear optimisation models. Some previously reported case studies from the open literature have been solved, and with significantly better optimal solutions identified. We believe that the nature of the non-monotone line search scheme allows the search procedure to escape from local minima, hence the encouraging results obtained.
Probing hidden sector photons through the Higgs window
International Nuclear Information System (INIS)
Ahlers, M.
2008-07-01
We investigate the possibility that a (light) hidden sector extra photon receives its mass via spontaneous symmetry breaking of a hidden sector Higgs boson, the so-called hidden-Higgs. The hidden-photon can mix with the ordinary photon via a gauge kinetic mixing term. The hidden-Higgs can couple to the Standard Model Higgs via a renormalizable quartic term - sometimes called the Higgs Portal. We discuss the implications of this light hidden-Higgs in the context of laser polarization and light-shining-through-the-wall experiments as well as cosmological, astrophysical, and non-Newtonian force measurements. For hidden-photons receiving their mass from a hidden-Higgs we find in the small mass regime significantly stronger bounds than the bounds on massive hidden sector photons alone. (orig.)
Probing hidden sector photons through the Higgs window
International Nuclear Information System (INIS)
Ahlers, Markus; Jaeckel, Joerg; Redondo, Javier; Ringwald, Andreas
2008-01-01
We investigate the possibility that a (light) hidden sector extra photon receives its mass via spontaneous symmetry breaking of a hidden sector Higgs boson, the so-called hidden-Higgs. The hidden-photon can mix with the ordinary photon via a gauge kinetic mixing term. The hidden-Higgs can couple to the standard model Higgs via a renormalizable quartic term - sometimes called the Higgs portal. We discuss the implications of this light hidden-Higgs in the context of laser polarization and light-shining-through-the-wall experiments as well as cosmological, astrophysical, and non-Newtonian force measurements. For hidden-photons receiving their mass from a hidden-Higgs, we find in the small mass regime significantly stronger bounds than the bounds on massive hidden sector photons alone.
Fitting Hidden Markov Models to Psychological Data
Directory of Open Access Journals (Sweden)
Ingmar Visser
2002-01-01
Full Text Available Markov models have been used extensively in psychology of learning. Applications of hidden Markov models are rare however. This is partially due to the fact that comprehensive statistics for model selection and model assessment are lacking in the psychological literature. We present model selection and model assessment statistics that are particularly useful in applying hidden Markov models in psychology. These statistics are presented and evaluated by simulation studies for a toy example. We compare AIC, BIC and related criteria and introduce a prediction error measure for assessing goodness-of-fit. In a simulation study, two methods of fitting equality constraints are compared. In two illustrative examples with experimental data we apply selection criteria, fit models with constraints and assess goodness-of-fit. First, data from a concept identification task is analyzed. Hidden Markov models provide a flexible approach to analyzing such data when compared to other modeling methods. Second, a novel application of hidden Markov models in implicit learning is presented. Hidden Markov models are used in this context to quantify knowledge that subjects express in an implicit learning task. This method of analyzing implicit learning data provides a comprehensive approach for addressing important theoretical issues in the field.
Geometric phases and hidden local gauge symmetry
International Nuclear Information System (INIS)
Fujikawa, Kazuo
2005-01-01
The analysis of geometric phases associated with level crossing is reduced to the familiar diagonalization of the Hamiltonian in the second quantized formulation. A hidden local gauge symmetry, which is associated with the arbitrariness of the phase choice of a complete orthonormal basis set, becomes explicit in this formulation (in particular, in the adiabatic approximation) and specifies physical observables. The choice of a basis set which specifies the coordinate in the functional space is arbitrary in the second quantization, and a subclass of coordinate transformations, which keeps the form of the action invariant, is recognized as the gauge symmetry. We discuss the implications of this hidden local gauge symmetry in detail by analyzing geometric phases for cyclic and noncyclic evolutions. It is shown that the hidden local symmetry provides a basic concept alternative to the notion of holonomy to analyze geometric phases and that the analysis based on the hidden local gauge symmetry leads to results consistent with the general prescription of Pancharatnam. We however note an important difference between the geometric phases for cyclic and noncyclic evolutions. We also explain a basic difference between our hidden local gauge symmetry and a gauge symmetry (or equivalence class) used by Aharonov and Anandan in their definition of generalized geometric phases
Massive hidden photons as lukewarm dark matter
International Nuclear Information System (INIS)
Redondo, Javier; Postma, Marieke
2008-11-01
We study the possibility that a keV-MeV mass hidden photon (HP), i.e. a hidden sector U(1) gauge boson, accounts for the observed amount of dark matter. We focus on the case where the HP interacts with the standard model sector only through kinetic mixing with the photon. The relic abundance is computed including all relevant plasma effects into the photon's self-energy, which leads to a resonant yield almost independent of the HP mass. The HP can decay into three photons. Moreover, if light enough it can be copiously produced in stars. Including bounds from cosmic photon backgrounds and stellar evolution, we find that the hidden photon can only give a subdominant contribution to the dark matter. This negative conclusion may be avoided if another production mechanism besides kinetic mixing is operative. (orig.)
Massive hidden photons as lukewarm dark matter
Energy Technology Data Exchange (ETDEWEB)
Redondo, Javier [Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany); Postma, Marieke [Nationaal Inst. voor Kernfysica en Hoge-Energiefysica (NIKHEF), Amsterdam (Netherlands)
2008-11-15
We study the possibility that a keV-MeV mass hidden photon (HP), i.e. a hidden sector U(1) gauge boson, accounts for the observed amount of dark matter. We focus on the case where the HP interacts with the standard model sector only through kinetic mixing with the photon. The relic abundance is computed including all relevant plasma effects into the photon's self-energy, which leads to a resonant yield almost independent of the HP mass. The HP can decay into three photons. Moreover, if light enough it can be copiously produced in stars. Including bounds from cosmic photon backgrounds and stellar evolution, we find that the hidden photon can only give a subdominant contribution to the dark matter. This negative conclusion may be avoided if another production mechanism besides kinetic mixing is operative. (orig.)
Religious Tolerance in the Hidden Curriculum
Directory of Open Access Journals (Sweden)
Kevin Nobel Kurniawan
2018-03-01
Full Text Available Religious intolerance is spreading within the Indonesian institution of education. Previous studies have shown that the growth of intolerance is due to the state’s regulation and pedagogical apparatus. In contrast to the previous studies, I argue that the intolerance is related to hidden curriculum applied by the institution of education. Normatively, the hidden curriculum contains the value of religious tolerance. However, factually, the author found that there are practices of intolerance, through the formal and informal spheres in the school’s structure, within the hidden curriculum. This article applies a qualitative approach with a mixed method research strategy to analyze data collected from students, teachers, and alumnis through field observation, in-depth interview, and survey.
PELACAKAN DAN PENGENALAN WAJAH MENGGUNAKAN METODE EMBEDDED HIDDEN MARKOV MODELS
Directory of Open Access Journals (Sweden)
Arie Wirawan Margono
2004-01-01
Full Text Available Tracking and recognizing human face becomes one of the important research subjects nowadays, where it is applicable in security system like room access, surveillance, as well as searching for person identity in police database. Because of applying in security case, it is necessary to have robust system for certain conditions such as: background influence, non-frontal face pose of male or female in different age and race. The aim of this research is to develop software which combines human face tracking using CamShift algorithm and face recognition system using Embedded Hidden Markov Models. The software uses video camera (webcam for real-time input, video AVI for dynamic input, and image file for static input. The software uses Object Oriented Programming (OOP coding style with C++ programming language, Microsoft Visual C++ 6.0® compiler, and assisted by some libraries of Intel Image Processing Library (IPL and Intel Open Source Computer Vision (OpenCV. System testing shows that object tracking based on skin complexion using CamShift algorithm comes out well, for tracking of single or even two face objects at once. Human face recognition system using Embedded Hidden Markov Models method has reach accuracy percentage of 82.76%, using 341 human faces in database that consists of 31 individuals with 11 poses and 29 human face testers. Abstract in Bahasa Indonesia : Pelacakan dan pengenalan wajah manusia merupakan salah satu bidang yang cukup berkembang dewasa ini, dimana aplikasi dapat diterapkan dalam bidang keamanan (security system seperti ijin akses masuk ruangan, pengawasan lokasi (surveillance, maupun pencarian identitas individu pada database kepolisian. Karena diterapkan dalam kasus keamanan, dibutuhkan sistem yang handal terhadap beberapa kondisi, seperti: pengaruh latar belakang, pose wajah non-frontal terhadap pria maupun wanita dalam perbedaan usia dan ras. Tujuan penelitiam ini adalah untuk membuat perangkat lunak yang menggabungkan
Hidden treasures - 50 km points of interests
Lommi, Matias; Kortelainen, Jaana
2015-04-01
Tampere is third largest city in Finland and a regional centre. During 70's there occurred several communal mergers. Nowadays this local area has both strong and diversed identity - from wilderness and agricultural fields to high density city living. Outside the city center there are interesting geological points unknown for modern city settlers. There is even a local proverb, "Go abroad to Teisko!". That is the area the Hidden Treasures -student project is focused on. Our school Tammerkoski Upper Secondary School (or Gymnasium) has emphasis on visual arts. We are going to offer our art students scientific and artistic experiences and knowledge about the hidden treasures of Teisko area and involve the Teisko inhabitants into this project. Hidden treasures - Precambrian subduction zone and a volcanism belt with dense bed of gold (Au) and arsenic (As), operating goldmines and quarries of minerals and metamorphic slates. - North of subduction zone a homogenic precambrian magmastone area with quarries, products known as Kuru Grey. - Former ashores of post-glasial Lake Näsijärvi and it's sediments enabled the developing agriculture and sustained settlement. Nowadays these ashores have both scenery and biodiversity values. - Old cattle sheds and dairy buildings made of local granite stones related to cultural stonebuilding inheritance. - Local active community of Kapee, about 100 inhabitants. Students will discover information of these "hidden" phenomena, and rendering this information trough Enviromental Art Method. Final form of this project will be published in several artistic and informative geocaches. These caches are achieved by a GPS-based special Hidden Treasures Cycling Route and by a website guiding people to find these hidden points of interests.
A Fast SVD-Hidden-nodes based Extreme Learning Machine for Large-Scale Data Analytics.
Deng, Wan-Yu; Bai, Zuo; Huang, Guang-Bin; Zheng, Qing-Hua
2016-05-01
Big dimensional data is a growing trend that is emerging in many real world contexts, extending from web mining, gene expression analysis, protein-protein interaction to high-frequency financial data. Nowadays, there is a growing consensus that the increasing dimensionality poses impeding effects on the performances of classifiers, which is termed as the "peaking phenomenon" in the field of machine intelligence. To address the issue, dimensionality reduction is commonly employed as a preprocessing step on the Big dimensional data before building the classifiers. In this paper, we propose an Extreme Learning Machine (ELM) approach for large-scale data analytic. In contrast to existing approaches, we embed hidden nodes that are designed using singular value decomposition (SVD) into the classical ELM. These SVD nodes in the hidden layer are shown to capture the underlying characteristics of the Big dimensional data well, exhibiting excellent generalization performances. The drawback of using SVD on the entire dataset, however, is the high computational complexity involved. To address this, a fast divide and conquer approximation scheme is introduced to maintain computational tractability on high volume data. The resultant algorithm proposed is labeled here as Fast Singular Value Decomposition-Hidden-nodes based Extreme Learning Machine or FSVD-H-ELM in short. In FSVD-H-ELM, instead of identifying the SVD hidden nodes directly from the entire dataset, SVD hidden nodes are derived from multiple random subsets of data sampled from the original dataset. Comprehensive experiments and comparisons are conducted to assess the FSVD-H-ELM against other state-of-the-art algorithms. The results obtained demonstrated the superior generalization performance and efficiency of the FSVD-H-ELM. Copyright © 2016 Elsevier Ltd. All rights reserved.
The origin of the hidden supersymmetry
International Nuclear Information System (INIS)
Jakubsky, Vit; Nieto, Luis-Miguel; Plyushchay, Mikhail S.
2010-01-01
The hidden supersymmetry and related tri-supersymmetric structure of the free particle system, the Dirac delta potential problem and the Aharonov-Bohm effect (planar, bound state, and tubule models) are explained by a special nonlocal unitary transformation, which for the usual N=2 supercharges has a nature of Foldy-Wouthuysen transformation. We show that in general case, the bosonized supersymmetry of nonlocal, parity even systems emerges in the same construction, and explain the origin of the unusual N=2 supersymmetry of electron in three-dimensional parity even magnetic field. The observation extends to include the hidden superconformal symmetry.
Signatures of a hidden cosmic microwave background.
Jaeckel, Joerg; Redondo, Javier; Ringwald, Andreas
2008-09-26
If there is a light Abelian gauge boson gamma' in the hidden sector its kinetic mixing with the photon can produce a hidden cosmic microwave background (HCMB). For meV masses, resonant oscillations gammagamma' happen after big bang nucleosynthesis (BBN) but before CMB decoupling, increasing the effective number of neutrinos Nnu(eff) and the baryon to photon ratio, and distorting the CMB blackbody spectrum. The agreement between BBN and CMB data provides new constraints. However, including Lyman-alpha data, Nnu(eff) > 3 is preferred. It is tempting to attribute this effect to the HCMB. The interesting parameter range will be tested in upcoming laboratory experiments.
Hidden simplicity of gauge theory amplitudes
Energy Technology Data Exchange (ETDEWEB)
Drummond, J M, E-mail: drummond@lapp.in2p3.f [LAPTH, Universite de Savoie, CNRS, B.P. 110, F-74941 Annecy-le-Vieux, Cedex (France)
2010-11-07
These notes were given as lectures at the CERN Winter School on Supergravity, Strings and Gauge Theory 2010. We describe the structure of scattering amplitudes in gauge theories, focussing on the maximally supersymmetric theory to highlight the hidden symmetries which appear. Using the Britto, Cachzo, Feng and Witten (BCFW) recursion relations we solve the tree-level S-matrix in N=4 super Yang-Mills theory and describe how it produces a sum of invariants of a large symmetry algebra. We review amplitudes in the planar theory beyond tree level, describing the connection between amplitudes and Wilson loops, and discuss the implications of the hidden symmetries.
Searching for hidden sectors in multiparticle production at the LHC
Sanchis-Lozano, Miguel-Angel; Moreno-Picot, Salvador
2016-01-01
We study the impact of a hidden sector beyond the Standard Model, e.g. a Hidden Valley model, on factorial moments and cumulants of multiplicity distributions in multiparticle production with a special emphasis on the prospects for LHC results.
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...
Hidden Markov Model-based Pedestrian Navigation System using MEMS Inertial Sensors
Directory of Open Access Journals (Sweden)
Zhang Yingjun
2015-02-01
Full Text Available In this paper, a foot-mounted pedestrian navigation system using MEMS inertial sensors is implemented, where the zero-velocity detection is abstracted into a hidden Markov model with 4 states and 15 observations. Moreover, an observations extraction algorithm has been developed to extract observations from sensor outputs; sample sets are used to train and optimize the model parameters by the Baum-Welch algorithm. Finally, a navigation system is developed, and the performance of the pedestrian navigation system is evaluated using indoor and outdoor field tests, and the results show that position error is less than 3% of total distance travelled.
Under-reported data analysis with INAR-hidden Markov chains.
Fernández-Fontelo, Amanda; Cabaña, Alejandra; Puig, Pedro; Moriña, David
2016-11-20
In this work, we deal with correlated under-reported data through INAR(1)-hidden Markov chain models. These models are very flexible and can be identified through its autocorrelation function, which has a very simple form. A naïve method of parameter estimation is proposed, jointly with the maximum likelihood method based on a revised version of the forward algorithm. The most-probable unobserved time series is reconstructed by means of the Viterbi algorithm. Several examples of application in the field of public health are discussed illustrating the utility of the models. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.
Compressing the hidden variable space of a qubit
Montina, Alberto
2010-01-01
In previously exhibited hidden variable models of quantum state preparation and measurement, the number of continuous hidden variables describing the actual state of a single realization is never smaller than the quantum state manifold dimension. We introduce a simple model for a qubit whose hidden variable space is one-dimensional, i.e., smaller than the two-dimensional Bloch sphere. The hidden variable probability distributions associated with the quantum states satisfy reasonable criteria ...
Hidden Markov Models for Human Genes
DEFF Research Database (Denmark)
Baldi, Pierre; Brunak, Søren; Chauvin, Yves
1997-01-01
We analyse the sequential structure of human genomic DNA by hidden Markov models. We apply models of widely different design: conventional left-right constructs and models with a built-in periodic architecture. The models are trained on segments of DNA sequences extracted such that they cover com...
The Hidden Cost of Buying a Computer.
Johnson, Michael
1983-01-01
In order to process data in a computer, application software must be either developed or purchased. Costs for modifications of the software package and maintenance are often hidden. The decision to buy or develop software packages should be based upon factors of time and maintenance. (MLF)
Hidden symmetries in five-dimensional supergravity
International Nuclear Information System (INIS)
Poessel, M.
2003-05-01
This thesis is concerned with the study of hidden symmetries in supergravity, which play an important role in the present picture of supergravity and string theory. Concretely, the appearance of a hidden G 2(+2) /SO(4) symmetry is studied in the dimensional reduction of d=5, N=2 supergravity to three dimensions - a parallel model to the more famous E 8(+8) /SO(16) case in eleven-dimensional supergravity. Extending previous partial results for the bosonic part, I give a derivation that includes fermionic terms. This sheds new light on the appearance of the local hidden symmetry SO(4) in the reduction, and shows up an unusual feature which follows from an analysis of the R-symmetry associated with N=4 supergravity and of the supersymmetry variations, and which has no parallel in the eleven-dimensional case: The emergence of an additional SO(3) as part of the enhanced local symmetry, invisible in the dimensional reduction of the gravitino, and corresponding to the fact that, of the SO(4) used in the coset model, only the diagonal SO(3) is visible immediately upon dimensional reduction. The uncovering of the hidden symmetries proceeds via the construction of the proper coset gravity in three dimensions, and matching it with the Lagrangian obtained from the reduction. (orig.)
Discovering hidden sectors with monophoton Z' searches
International Nuclear Information System (INIS)
Gershtein, Yuri; Petriello, Frank; Quackenbush, Seth; Zurek, Kathryn M.
2008-01-01
In many theories of physics beyond the standard model, from extra dimensions to Hidden Valleys and models of dark matter, Z ' bosons mediate between standard model particles and hidden sector states. We study the feasibility of observing such hidden states through an invisibly decaying Z ' at the LHC. We focus on the process pp→γZ ' →γXX † , where X is any neutral, (quasi-) stable particle, whether a standard model neutrino or a new state. This complements a previous study using pp→ZZ ' →l + l - XX † . Only the Z ' mass and two effective charges are needed to describe this process. If the Z ' decays invisibly only to standard model neutrinos, then these charges are predicted by observation of the Z ' through the Drell-Yan process, allowing discrimination between Z ' decays to standard model ν's and invisible decays to new states. We carefully discuss all backgrounds and systematic errors that affect this search. We find that hidden sector decays of a 1 TeV Z ' can be observed at 5σ significance with 50 fb -1 at the LHC. Observation of a 1.5 TeV state requires super-LHC statistics of 1 ab -1 . Control of the systematic errors, in particular, the parton distribution function uncertainty of the dominant Zγ background, is crucial to maximize the LHC search reach.
Hidden Markov models for labeled sequences
DEFF Research Database (Denmark)
Krogh, Anders Stærmose
1994-01-01
A hidden Markov model for labeled observations, called a class HMM, is introduced and a maximum likelihood method is developed for estimating the parameters of the model. Instead of training it to model the statistics of the training sequences it is trained to optimize recognition. It resembles MMI...
Directory of Open Access Journals (Sweden)
Shan Pang
2016-01-01
Full Text Available A new aero gas turbine engine gas path component fault diagnosis method based on multi-hidden-layer extreme learning machine with optimized structure (OM-ELM was proposed. OM-ELM employs quantum-behaved particle swarm optimization to automatically obtain the optimal network structure according to both the root mean square error on training data set and the norm of output weights. The proposed method is applied to handwritten recognition data set and a gas turbine engine diagnostic application and is compared with basic ELM, multi-hidden-layer ELM, and two state-of-the-art deep learning algorithms: deep belief network and the stacked denoising autoencoder. Results show that, with optimized network structure, OM-ELM obtains better test accuracy in both applications and is more robust to sensor noise. Meanwhile it controls the model complexity and needs far less hidden nodes than multi-hidden-layer ELM, thus saving computer memory and making it more efficient to implement. All these advantages make our method an effective and reliable tool for engine component fault diagnosis tool.
Hidden State Conditional Random Field for Abnormal Activity Recognition in Smart Homes
Directory of Open Access Journals (Sweden)
Yu Tong
2015-03-01
Full Text Available As the number of elderly people has increased worldwide, there has been a surge of research into assistive technologies to provide them with better care by recognizing their normal and abnormal activities. However, existing abnormal activity recognition (AAR algorithms rarely consider sub-activity relations when recognizing abnormal activities. This paper presents an application of the Hidden State Conditional Random Field (HCRF method to detect and assess abnormal activities that often occur in elderly persons’ homes. Based on HCRF, this paper designs two AAR algorithms, and validates them by comparing them with a feature vector distance based algorithm in two experiments. The results demonstrate that the proposed algorithms favorably outperform the competitor, especially when abnormal activities have same sensor type and sensor number as normal activities.
THE APPROACHING TRAIN DETECTION ALGORITHM
S. V. Bibikov
2015-01-01
The paper deals with detection algorithm for rail vibroacoustic waves caused by approaching train on the background of increased noise. The urgency of algorithm development for train detection in view of increased rail noise, when railway lines are close to roads or road intersections is justified. The algorithm is based on the method of weak signals detection in a noisy environment. The information statistics ultimate expression is adjusted. We present the results of algorithm research and t...
Basic problems solving for two-dimensional discrete 3 × 4 order hidden markov model
International Nuclear Information System (INIS)
Wang, Guo-gang; Gan, Zong-liang; Tang, Gui-jin; Cui, Zi-guan; Zhu, Xiu-chang
2016-01-01
A novel model is proposed to overcome the shortages of the classical hypothesis of the two-dimensional discrete hidden Markov model. In the proposed model, the state transition probability depends on not only immediate horizontal and vertical states but also on immediate diagonal state, and the observation symbol probability depends on not only current state but also on immediate horizontal, vertical and diagonal states. This paper defines the structure of the model, and studies the three basic problems of the model, including probability calculation, path backtracking and parameters estimation. By exploiting the idea that the sequences of states on rows or columns of the model can be seen as states of a one-dimensional discrete 1 × 2 order hidden Markov model, several algorithms solving the three questions are theoretically derived. Simulation results further demonstrate the performance of the algorithms. Compared with the two-dimensional discrete hidden Markov model, there are more statistical characteristics in the structure of the proposed model, therefore the proposed model theoretically can more accurately describe some practical problems.
Energy Technology Data Exchange (ETDEWEB)
Okayasu, S.; Kuratani, T.; Imai, H. [Ajinomoto Co. Inc., Tokyo (Japan)
1995-03-15
Automatic control of incinerators for their stable operation has been desired for the preservation of the environment in the factory. An on-line fuzzy control system has been successfully introduced for temperature control of the fluidized bed of incinerator for industrial wastes. In this case, manual control can be applied to the plant instead of a PID control system, because of the complexity of the waste materials and the large delay in detection of the temperature change in the fluidized bed sand. On the basis of analyzing the dynamic performance of the process and the know-how of skilled operators, membership functions and fuzzy control rules are selected, then determined carefully for the system. Introduction of the system resulted in almost the same performance as manual control. Subsequently the operators are freed from manual operation in the control room for an hour. 6 refs., 5 figs., 4 tabs.
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.
Extended abstract of a hidden agenda
Energy Technology Data Exchange (ETDEWEB)
Goguen, J.; Malcolm, G. [Oxford Univ. (United Kingdom)
1996-12-31
The initial goal of our hidden research programme was both straightforward and ambitious: give a semantics for software engineering, and in particular for the object paradigm, supporting correctness proofs that are as simple and mechanical as possible. This emphasizes proofs rather than models, and thus suggests an equational approach, rather than one based on higher order logic, denotational semantics, or any kind of model, because equational proofs achieve maximal simplicity and mechanization, and yet are fully expressive. We introduce powerful coinduction techniques for proving behavioral properties of complex systems. We make the no doubt outrageous claim that our hidden approach gives simpler proofs than other formalisms; this is because we exploit algebraic structure that most other approaches discard.
Laser experiments explore the hidden sector
International Nuclear Information System (INIS)
Ahlers, M.
2007-11-01
Recently, the laser experiments BMV and GammeV, searching for light shining through walls, have published data and calculated new limits on the allowed masses and couplings for axion-like particles. In this note we point out that these experiments can serve to constrain a much wider variety of hidden-sector particles such as, e.g., minicharged particles and hidden-sector photons. The new experiments improve the existing bounds from the older BFRT experiment by a factor of two. Moreover, we use the new PVLAS constraints on a possible rotation and ellipticity of light after it has passed through a strong magnetic field to constrain pure minicharged particle models. For masses -7 times the electron electric charge. This is the best laboratory bound and comparable to bounds inferred from the energy spectrum of the cosmic microwave background. (orig.)
Quantum mechanics and hidden superconformal symmetry
Bonezzi, R.; Corradini, O.; Latini, E.; Waldron, A.
2017-12-01
Solvability of the ubiquitous quantum harmonic oscillator relies on a spectrum generating osp (1 |2 ) superconformal symmetry. We study the problem of constructing all quantum mechanical models with a hidden osp (1 |2 ) symmetry on a given space of states. This problem stems from interacting higher spin models coupled to gravity. In one dimension, we show that the solution to this problem is the Vasiliev-Plyushchay family of quantum mechanical models with hidden superconformal symmetry obtained by viewing the harmonic oscillator as a one dimensional Dirac system, so that Grassmann parity equals wave function parity. These models—both oscillator and particlelike—realize all possible unitary irreducible representations of osp (1 |2 ).
Hidden Costs and the Role of Modularity
DEFF Research Database (Denmark)
Larsen, Marcus M.
2013-01-01
that the inability to effectively estimate the costs of implementing an activity in a foreign location has a negative impact on the process performance of that activity. Performance is deterred as operations are likely to be disrupted by opportunity costs and managerial responses. However, this relationship......This paper addresses estimation errors in strategic decision-making processes due to hidden costs. While previous research has investigated the antecedents of hidden costs, this paper investigates performance consequences. Using unique data on 221 offshoring implementations, it is argued...... is mitigated by the degree of modularity in the activity as it reduces the need for costly coordination in offshoring. This paper contributes to research on offshoring and strategic decision-making by emphasizing the importance of organizational design and of estimating the costs of internal organizational...
Wan, Weibing; Yuan, Lingfeng; Zhao, Qunfei; Fang, Tao
2018-01-01
Saliency detection has been applied to the target acquisition case. This paper proposes a two-dimensional hidden Markov model (2D-HMM) that exploits the hidden semantic information of an image to detect its salient regions. A spatial pyramid histogram of oriented gradient descriptors is used to extract features. After encoding the image by a learned dictionary, the 2D-Viterbi algorithm is applied to infer the saliency map. This model can predict fixation of the targets and further creates robust and effective depictions of the targets' change in posture and viewpoint. To validate the model with a human visual search mechanism, two eyetrack experiments are employed to train our model directly from eye movement data. The results show that our model achieves better performance than visual attention. Moreover, it indicates the plausibility of utilizing visual track data to identify targets.
Optimized hardware framework of MLP with random hidden layers for classification applications
Zyarah, Abdullah M.; Ramesh, Abhishek; Merkel, Cory; Kudithipudi, Dhireesha
2016-05-01
Multilayer Perceptron Networks with random hidden layers are very efficient at automatic feature extraction and offer significant performance improvements in the training process. They essentially employ large collection of fixed, random features, and are expedient for form-factor constrained embedded platforms. In this work, a reconfigurable and scalable architecture is proposed for the MLPs with random hidden layers with a customized building block based on CORDIC algorithm. The proposed architecture also exploits fixed point operations for area efficiency. The design is validated for classification on two different datasets. An accuracy of ~ 90% for MNIST dataset and 75% for gender classification on LFW dataset was observed. The hardware has 299 speed-up over the corresponding software realization.
The Hidden Gifts of Quiet Kids
Trierweiler, Hannah
2006-01-01
The author relates that she was an introvert child. It has always taken her time and energy to find her place in a group. As a grown-up, she still needed quiet time to regroup during a busy day. In this article, the author presents an interview with Marti Olsen Laney, author of "The Hidden Gifts of the Introverted Child." During the interview,…
A masking index for quantifying hidden glitches
Berti-Equille, Laure; Loh, J. M.; Dasu, T.
2015-01-01
Data glitches are errors in a dataset. They are complex entities that often span multiple attributes and records. When they co-occur in data, the presence of one type of glitch can hinder the detection of another type of glitch. This phenomenon is called masking. In this paper, we define two important types of masking and propose a novel, statistically rigorous indicator called masking index for quantifying the hidden glitches. We outline four cases of masking: outliers masked by missing valu...
Cold dark matter from the hidden sector
International Nuclear Information System (INIS)
Arias, Paola; Pontificia Univ. Catolica de Chile, Santiago
2012-02-01
Weakly interacting slim particles (WISPs) such as hidden photons (HP) and axion-like particles (ALPs) have been proposed as cold dark matter candidates. They might be produced non-thermally via the misalignment mechanism, similarly to cold axions. In this talk we review the main processes of thermalisation of HP and we compute the parameter space that may survive as cold dark matter population until today. Our findings are quite encouraging for experimental searches in the laboratory in the near future.
Cold dark matter from the hidden sector
Energy Technology Data Exchange (ETDEWEB)
Arias, Paola [Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany); Pontificia Univ. Catolica de Chile, Santiago (Chile). Facultad de Fisica
2012-02-15
Weakly interacting slim particles (WISPs) such as hidden photons (HP) and axion-like particles (ALPs) have been proposed as cold dark matter candidates. They might be produced non-thermally via the misalignment mechanism, similarly to cold axions. In this talk we review the main processes of thermalisation of HP and we compute the parameter space that may survive as cold dark matter population until today. Our findings are quite encouraging for experimental searches in the laboratory in the near future.
Hidden histories: challenges for pedagogy and participation
Morrice, Linda
2013-01-01
Higher Education has become and an increasingly diverse and globalised system in which the binaries between ‘traditional’ and ‘non-traditional’ students, exclusion and inclusion have less resonance and analytical purchase. Drawing on research with refugees Linda will suggest that higher education can be marked simultaneously by belonging and recognition, deficit and exclusion. Complex differences and inequalities remain hidden and unspoken, raising new questions and challenges for pedagogy an...
Hidden sector behind the CKM matrix
Okawa, Shohei; Omura, Yuji
2017-08-01
The small quark mixing, described by the Cabibbo-Kobayashi-Maskawa (CKM) matrix in the standard model, may be a clue to reveal new physics around the TeV scale. We consider a simple scenario that extra particles in a hidden sector radiatively mediate the flavor violation to the quark sector around the TeV scale and effectively realize the observed CKM matrix. The lightest particle in the hidden sector, whose contribution to the CKM matrix is expected to be dominant, is a good dark matter (DM) candidate. There are many possible setups to describe this scenario, so that we investigate some universal predictions of this kind of model, focusing on the contribution of DM to the quark mixing and flavor physics. In this scenario, there is an explicit relation between the CKM matrix and flavor violating couplings, such as four-quark couplings, because both are radiatively induced by the particles in the hidden sector. Then, we can explicitly find the DM mass region and the size of Yukawa couplings between the DM and quarks, based on the study of flavor physics and DM physics. In conclusion, we show that DM mass in our scenario is around the TeV scale, and the Yukawa couplings are between O (0.01 ) and O (1 ). The spin-independent DM scattering cross section is estimated as O (10-9) [pb]. An extra colored particle is also predicted at the O (10 ) TeV scale.
Accelerating Information Retrieval from Profile Hidden Markov Model Databases.
Tamimi, Ahmad; Ashhab, Yaqoub; Tamimi, Hashem
2016-01-01
Profile Hidden Markov Model (Profile-HMM) is an efficient statistical approach to represent protein families. Currently, several databases maintain valuable protein sequence information as profile-HMMs. There is an increasing interest to improve the efficiency of searching Profile-HMM databases to detect sequence-profile or profile-profile homology. However, most efforts to enhance searching efficiency have been focusing on improving the alignment algorithms. Although the performance of these algorithms is fairly acceptable, the growing size of these databases, as well as the increasing demand for using batch query searching approach, are strong motivations that call for further enhancement of information retrieval from profile-HMM databases. This work presents a heuristic method to accelerate the current profile-HMM homology searching approaches. The method works by cluster-based remodeling of the database to reduce the search space, rather than focusing on the alignment algorithms. Using different clustering techniques, 4284 TIGRFAMs profiles were clustered based on their similarities. A representative for each cluster was assigned. To enhance sensitivity, we proposed an extended step that allows overlapping among clusters. A validation benchmark of 6000 randomly selected protein sequences was used to query the clustered profiles. To evaluate the efficiency of our approach, speed and recall values were measured and compared with the sequential search approach. Using hierarchical, k-means, and connected component clustering techniques followed by the extended overlapping step, we obtained an average reduction in time of 41%, and an average recall of 96%. Our results demonstrate that representation of profile-HMMs using a clustering-based approach can significantly accelerate data retrieval from profile-HMM databases.
Accelerating Information Retrieval from Profile Hidden Markov Model Databases.
Directory of Open Access Journals (Sweden)
Ahmad Tamimi
Full Text Available Profile Hidden Markov Model (Profile-HMM is an efficient statistical approach to represent protein families. Currently, several databases maintain valuable protein sequence information as profile-HMMs. There is an increasing interest to improve the efficiency of searching Profile-HMM databases to detect sequence-profile or profile-profile homology. However, most efforts to enhance searching efficiency have been focusing on improving the alignment algorithms. Although the performance of these algorithms is fairly acceptable, the growing size of these databases, as well as the increasing demand for using batch query searching approach, are strong motivations that call for further enhancement of information retrieval from profile-HMM databases. This work presents a heuristic method to accelerate the current profile-HMM homology searching approaches. The method works by cluster-based remodeling of the database to reduce the search space, rather than focusing on the alignment algorithms. Using different clustering techniques, 4284 TIGRFAMs profiles were clustered based on their similarities. A representative for each cluster was assigned. To enhance sensitivity, we proposed an extended step that allows overlapping among clusters. A validation benchmark of 6000 randomly selected protein sequences was used to query the clustered profiles. To evaluate the efficiency of our approach, speed and recall values were measured and compared with the sequential search approach. Using hierarchical, k-means, and connected component clustering techniques followed by the extended overlapping step, we obtained an average reduction in time of 41%, and an average recall of 96%. Our results demonstrate that representation of profile-HMMs using a clustering-based approach can significantly accelerate data retrieval from profile-HMM databases.
Mian, Shahid; Ball, Graham; Hornbuckle, Jo; Holding, Finn; Carmichael, James; Ellis, Ian; Ali, Selman; Li, Geng; McArdle, Stephanie; Creaser, Colin; Rees, Robert
2003-09-01
An ability to predict the likelihood of cellular response towards particular chemotherapeutic agents based upon protein expression patterns could facilitate the identification of biological molecules with previously undefined roles in the process of chemoresistance/chemosensitivity, and if robust enough these patterns might also be exploited towards the development of novel predictive assays. To ascertain whether proteomic based molecular profiling in conjunction with artificial neural network (ANN) algorithms could be applied towards the specific recognition of phenotypic patterns between either control or drug treated and chemosensitive or chemoresistant cellular populations, a combined approach involving MALDI-TOF matrix-assisted laser desorption/ionization-time of flight mass spectrometry, Ciphergen protein chip technology and ANN algorithms have been applied to specifically identify proteomic 'fingerprints' indicative of treatment regimen for chemosensitive (MCF-7, T47D) and chemoresistant (MCF-7/ADR) breast cancer cell lines following exposure to Doxorubicin or Paclitaxel. The results indicate that proteomic patterns can be identified by ANN algorithms to correctly assign 'class' for treatment regimen (e.g. control/drug treated or chemosensitive/chemoresistant) with a high degree of accuracy using boot-strap statistical validation techniques and that biomarker ion patterns indicative of response/non-response phenotypes are associated with MCF-7 and MCF-7/ADR cells exposed to Doxorubicin. We have also examined the predictive capability of this approach towards MCF-7 and T47D cells to ascertain whether prediction could be made based upon treatment regimen irrespective of cell lineage. Models were identified that could correctly assign class (control or Paclitaxel treatment) for 35/38 samples of an independent dataset. A similar level of predictive capability was also found (> 92%; n = 28) when proteomic patterns derived from the drug resistant cell line MCF-7
Basic problems and solution methods for two-dimensional continuous 3 × 3 order hidden Markov model
International Nuclear Information System (INIS)
Wang, Guo-gang; Tang, Gui-jin; Gan, Zong-liang; Cui, Zi-guan; Zhu, Xiu-chang
2016-01-01
A novel model referred to as two-dimensional continuous 3 × 3 order hidden Markov model is put forward to avoid the disadvantages of the classical hypothesis of two-dimensional continuous hidden Markov model. This paper presents three equivalent definitions of the model, in which the state transition probability relies on not only immediate horizontal and vertical states but also immediate diagonal state, and in which the probability density of the observation relies on not only current state but also immediate horizontal and vertical states. The paper focuses on the three basic problems of the model, namely probability density calculation, parameters estimation and path backtracking. Some algorithms solving the questions are theoretically derived, by exploiting the idea that the sequences of states on rows or columns of the model can be viewed as states of a one-dimensional continuous 1 × 2 order hidden Markov model. Simulation results further demonstrate the performance of the algorithms. Because there are more statistical characteristics in the structure of the proposed new model, it can more accurately describe some practical problems, as compared to two-dimensional continuous hidden Markov model.
Directory of Open Access Journals (Sweden)
Nor Hazwani Idris
2017-06-01
Full Text Available Transmission line act as a medium of transportation for electrical energy from a power station to the consumer. There are many factors that could cause the cascading collapse such as instability of voltage and frequency, the change of environment and weather, the software and operator error and also the failure in protection system. Protection system plays an important function in maintaining the stability and reliability of the power grid. Hidden failures in relay protection systems are the primary factors for triggering the cascading collapse. This paper presents an Artificial Neural Network (ANN model for prediction of cascading collapse occurrence due to the effect of hidden failure of protection system. The ANN model has been developed through the normalized training and testing data process with optimum number of hidden layer, the momentum rate and the learning rate. The ANN model employs probability of hidden failure, random number of line limit power flow and exposed line as its input while trip index of cascading collapse occurrence as its output. IEEE 14 bus system is used in this study to illustrate the proposed approach. The performance of the results is analysed in terms of its Mean Square Error (MSE and Correlation Coefficient (R. The results show the ANN model produce reliable prediction of cascading collapse occurrence.
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
Microwave background constraints on mixing of photons with hidden photons
International Nuclear Information System (INIS)
Mirizzi, Alessandro; Redondo, Javier; Sigl, Guenter
2008-12-01
Various extensions of the Standard Model predict the existence of hidden photons kinetically mixing with the ordinary photon. This mixing leads to oscillations between photons and hidden photons, analogous to the observed oscillations between different neutrino flavors. In this context, we derive new bounds on the photon-hidden photon mixing parameters using the high precision cosmic microwave background spectral data collected by the Far Infrared Absolute Spectrophotometer instrument on board of the Cosmic Background Explorer. Requiring the distortions of the CMB induced by the photon-hidden photon mixing to be smaller than experimental upper limits, this leads to a bound on the mixing angle χ 0 -7 - 10 -5 for hidden photon masses between 10 -14 eV and 10 -7 eV. This low-mass and low-mixing region of the hidden photon parameter space was previously unconstrained. (orig.)
Microwave background constraints on mixing of photons with hidden photons
Energy Technology Data Exchange (ETDEWEB)
Mirizzi, Alessandro [Max-Planck-Institut fuer Physik, Muenchen (Germany); Redondo, Javier [Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany); Sigl, Guenter [Hamburg Univ. (Germany). 2. Inst. fuer Theoretische Physik
2008-12-15
Various extensions of the Standard Model predict the existence of hidden photons kinetically mixing with the ordinary photon. This mixing leads to oscillations between photons and hidden photons, analogous to the observed oscillations between different neutrino flavors. In this context, we derive new bounds on the photon-hidden photon mixing parameters using the high precision cosmic microwave background spectral data collected by the Far Infrared Absolute Spectrophotometer instrument on board of the Cosmic Background Explorer. Requiring the distortions of the CMB induced by the photon-hidden photon mixing to be smaller than experimental upper limits, this leads to a bound on the mixing angle {chi}{sub 0}
VISIBLE COSTS AND HIDDEN COSTS IN THE BAKING INDUSTRY
Directory of Open Access Journals (Sweden)
Criveanu Maria
2013-04-01
Full Text Available Hidden costs are present in the activity of any company, hardly identified in the traditional administrative accounting. The high levels of the hidden costs and their unknown presence have serious consequences on the decisions made by the managers. This paper aims at presenting some aspects related to the hidden costs that occur in the activity of the companies in the baking industry and the possibilities to reduce their level.
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.
Compressing the hidden variable space of a qubit
International Nuclear Information System (INIS)
Montina, Alberto
2011-01-01
In previously exhibited hidden variable models of quantum state preparation and measurement, the number of continuous hidden variables describing the actual state of single realizations is never smaller than the quantum state manifold dimension. We introduce a simple model for a qubit whose hidden variable space is one-dimensional, i.e., smaller than the two-dimensional Bloch sphere. The hidden variable probability distributions associated with quantum states satisfy reasonable criteria of regularity. Possible generalizations of this shrinking to an N-dimensional Hilbert space are discussed.
Zipf exponent of trajectory distribution in the hidden Markov model
Bochkarev, V. V.; Lerner, E. Yu
2014-03-01
This paper is the first step of generalization of the previously obtained full classification of the asymptotic behavior of the probability for Markov chain trajectories for the case of hidden Markov models. The main goal is to study the power (Zipf) and nonpower asymptotics of the frequency list of trajectories of hidden Markov frequencys and to obtain explicit formulae for the exponent of the power asymptotics. We consider several simple classes of hidden Markov models. We prove that the asymptotics for a hidden Markov model and for the corresponding Markov chain can be essentially different.
Zipf exponent of trajectory distribution in the hidden Markov model
International Nuclear Information System (INIS)
Bochkarev, V V; Lerner, E Yu
2014-01-01
This paper is the first step of generalization of the previously obtained full classification of the asymptotic behavior of the probability for Markov chain trajectories for the case of hidden Markov models. The main goal is to study the power (Zipf) and nonpower asymptotics of the frequency list of trajectories of hidden Markov frequencys and to obtain explicit formulae for the exponent of the power asymptotics. We consider several simple classes of hidden Markov models. We prove that the asymptotics for a hidden Markov model and for the corresponding Markov chain can be essentially different
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
Hidden acoustic information revealed by intentional nonlinearity
Dowling, David R.
2017-11-01
Acoustic waves are omnipresent in modern life and are well described by the linearized equations of fluid dynamics. Once generated, acoustic waves carry and collect information about their source and the environment through which they propagate, respectively, and this information may be retrieved by analyzing recordings of these waves. Because of this, acoustics is the primary means for observation, surveillance, reconnaissance, and remote sensing in otherwise opaque environments, such as the Earth's oceans and crust, and the interior of the human body. For such information-retrieval tasks, acoustic fields are nearly always interrogated within their recorded frequency range or bandwidth. However, this frequency-range restriction is not general; acoustic fields may also carry (hidden) information at frequencies outside their bandwidth. Although such a claim may seem counter intuitive, hidden acoustic-field information can be revealed by re-introducing a marquee trait of fluid dynamics: nonlinearity. In particular, an intentional quadratic nonlinearity - a form of intra-signal heterodyning - can be used to obtain acoustic field information at frequencies outside a recorded acoustic field's bandwidth. This quadratic nonlinearity enables a variety of acoustic remote sensing applications that were long thought to be impossible. In particular, it allows the detrimental effects of sparse recordings and random scattering to be suppressed when the original acoustic field has sufficient bandwidth. In this presentation, the topic is developed heuristically, with a just brief exposition of the relevant mathematics. Hidden acoustic field information is then revealed from simulated and measured acoustic fields in simple and complicated acoustic environments involving frequencies from a few Hertz to more than 100 kHz, and propagation distances from tens of centimeters to hundreds of kilometers. Sponsored by ONR, NAVSEA, and NSF.
Sun, Wei; Ding, Wei; Yan, Huifang; Duan, Shunli
2018-06-01
Shoe-mounted pedestrian navigation systems based on micro inertial sensors rely on zero velocity updates to correct their positioning errors in time, which effectively makes determining the zero velocity interval play a key role during normal walking. However, as walking gaits are complicated, and vary from person to person, it is difficult to detect walking gaits with a fixed threshold method. This paper proposes a pedestrian gait classification method based on a hidden Markov model. Pedestrian gait data are collected with a micro inertial measurement unit installed at the instep. On the basis of analyzing the characteristics of the pedestrian walk, a single direction angular rate gyro output is used to classify gait features. The angular rate data are modeled into a univariate Gaussian mixture model with three components, and a four-state left–right continuous hidden Markov model (CHMM) is designed to classify the normal walking gait. The model parameters are trained and optimized using the Baum–Welch algorithm and then the sliding window Viterbi algorithm is used to decode the gait. Walking data are collected through eight subjects walking along the same route at three different speeds; the leave-one-subject-out cross validation method is conducted to test the model. Experimental results show that the proposed algorithm can accurately detect different walking gaits of zero velocity interval. The location experiment shows that the precision of CHMM-based pedestrian navigation improved by 40% when compared to the angular rate threshold method.
An Approach of Diagnosis Based On The Hidden Markov Chains Model
Directory of Open Access Journals (Sweden)
Karim Bouamrane
2008-07-01
Full Text Available Diagnosis is a key element in industrial system maintenance process performance. A diagnosis tool is proposed allowing the maintenance operators capitalizing on the knowledge of their trade and subdividing it for better performance improvement and intervention effectiveness within the maintenance process service. The Tool is based on the Markov Chain Model and more precisely the Hidden Markov Chains (HMC which has the system failures determination advantage, taking into account the causal relations, stochastic context modeling of their dynamics and providing a relevant diagnosis help by their ability of dubious information use. Since the FMEA method is a well adapted artificial intelligence field, the modeling with Markov Chains is carried out with its assistance. Recently, a dynamic programming recursive algorithm, called 'Viterbi Algorithm', is being used in the Hidden Markov Chains field. This algorithm provides as input to the HMC a set of system observed effects and generates at exit the various causes having caused the loss from one or several system functions.
A Dynamic Hidden Forwarding Path Planning Method Based on Improved Q-Learning in SDN Environments
Directory of Open Access Journals (Sweden)
Yun Chen
2018-01-01
Full Text Available Currently, many methods are available to improve the target network’s security. The vast majority of them cannot obtain an optimal attack path and interdict it dynamically and conveniently. Almost all defense strategies aim to repair known vulnerabilities or limit services in target network to improve security of network. These methods cannot response to the attacks in real-time because sometimes they need to wait for manufacturers releasing corresponding countermeasures to repair vulnerabilities. In this paper, we propose an improved Q-learning algorithm to plan an optimal attack path directly and automatically. Based on this path, we use software-defined network (SDN to adjust routing paths and create hidden forwarding paths dynamically to filter vicious attack requests. Compared to other machine learning algorithms, Q-learning only needs to input the target state to its agents, which can avoid early complex training process. We improve Q-learning algorithm in two aspects. First, a reward function based on the weights of hosts and attack success rates of vulnerabilities is proposed, which can adapt to different network topologies precisely. Second, we remove the actions and merge them into every state that reduces complexity from O(N3 to O(N2. In experiments, after deploying hidden forwarding paths, the security of target network is boosted significantly without having to repair network vulnerabilities immediately.
Recovering a hidden polarization by ghost polarimetry.
Janassek, Patrick; Blumenstein, Sébastien; Elsäßer, Wolfgang
2018-02-15
By exploiting polarization correlations of light from a broadband fiber-based amplified spontaneous emission source we succeed in reconstructing a hidden polarization in a ghost polarimetry experiment in close analogy to ghost imaging and ghost spectroscopy. Thereby, an original linear polarization state in the object arm of a Mach-Zehnder interferometer configuration which has been camouflaged by a subsequent depolarizer is recovered by correlating it with light from a reference beam. The variation of a linear polarizer placed inside the reference beam results in a Malus law type second-order intensity correlation with high contrast, thus measuring a ghost polarigram.
Hidden Scale Invariance in Condensed Matter
DEFF Research Database (Denmark)
Dyre, J. C.
2014-01-01
. This means that the phase diagram becomes effectively one-dimensional with regard to several physical properties. Liquids and solids with isomorphs include most or all van der Waals bonded systems and metals, as well as weakly ionic or dipolar systems. On the other hand, systems with directional bonding...... (hydrogen bonds or covalent bonds) or strong Coulomb forces generally do not exhibit hidden scale invariance. The article reviews the theory behind this picture of condensed matter and the evidence for it coming from computer simulations and experiments...
Uncovering the Hidden Costs of Offshoring
DEFF Research Database (Denmark)
Larsen, Marcus M.; Manning, Stephan; Pedersen, Torben
2013-01-01
This study investigates estimation errors due to hidden costs—the costs of implementation that are neglected in strategic decision-making processes—in the context of services offshoring. Based on data from the Offshoring Research Network, we find that decision makers are more likely to make cost......-estimation errors given increasing configuration and task complexity in captive offshoring and offshore outsourcing, respectively. Moreover, we show that experience and a strong orientation toward organizational design in the offshoring strategy reduce the cost-estimation errors that follow from complexity. Our...
The hidden face of the petroleum
International Nuclear Information System (INIS)
Laurent, E.
2006-02-01
For the first time, a book reveals what that was hidden to the public opinions: why the petroleum crisis of 1973 what only a manipulation, an arrangement between the OPEC and the petroleum companies, why the data concerning the petroleum reserves are wrong and increased by the producers countries, how Washington used the Saudi petroleum weapon to create the Soviet Union fall, and why from march 2001 maps of the Iraq (where were drawn the future petroleum explorations) were working documents for the vice President Cheney and petroleum managers for the ''secret society''. (A.L.B.)
The hidden costs of nuclear power
International Nuclear Information System (INIS)
Keough, C.
1981-01-01
The two basic hidden costs of nuclear power are public money and public health. Nuclear power appears to be economical because many of the costs of producins electricity in these plants are paid by the federal government. So, like it or not, the citizens are footing the bill with their taxes. Design and development of plants have been paid for with public money, and disposal and cleanup costs will also be paid in this manner. The economic and health costs associated with nuclear accidents are staggering
Linear feature detection algorithm for astronomical surveys - I. Algorithm description
Bektešević, Dino; Vinković, Dejan
2017-11-01
Computer vision algorithms are powerful tools in astronomical image analyses, especially when automation of object detection and extraction is required. Modern object detection algorithms in astronomy are oriented towards detection of stars and galaxies, ignoring completely the detection of existing linear features. With the emergence of wide-field sky surveys, linear features attract scientific interest as possible trails of fast flybys of near-Earth asteroids and meteors. In this work, we describe a new linear feature detection algorithm designed specifically for implementation in big data astronomy. The algorithm combines a series of algorithmic steps that first remove other objects (stars and galaxies) from the image and then enhance the line to enable more efficient line detection with the Hough algorithm. The rate of false positives is greatly reduced thanks to a step that replaces possible line segments with rectangles and then compares lines fitted to the rectangles with the lines obtained directly from the image. The speed of the algorithm and its applicability in astronomical surveys are also discussed.
Inferring topologies of complex networks with hidden variables.
Wu, Xiaoqun; Wang, Weihan; Zheng, Wei Xing
2012-10-01
Network topology plays a crucial role in determining a network's intrinsic dynamics and function, thus understanding and modeling the topology of a complex network will lead to greater knowledge of its evolutionary mechanisms and to a better understanding of its behaviors. In the past few years, topology identification of complex networks has received increasing interest and wide attention. Many approaches have been developed for this purpose, including synchronization-based identification, information-theoretic methods, and intelligent optimization algorithms. However, inferring interaction patterns from observed dynamical time series is still challenging, especially in the absence of knowledge of nodal dynamics and in the presence of system noise. The purpose of this work is to present a simple and efficient approach to inferring the topologies of such complex networks. The proposed approach is called "piecewise partial Granger causality." It measures the cause-effect connections of nonlinear time series influenced by hidden variables. One commonly used testing network, two regular networks with a few additional links, and small-world networks are used to evaluate the performance and illustrate the influence of network parameters on the proposed approach. Application to experimental data further demonstrates the validity and robustness of our method.
Hidden Semi-Markov Models for Predictive Maintenance
Directory of Open Access Journals (Sweden)
Francesco Cartella
2015-01-01
Full Text Available Realistic predictive maintenance approaches are essential for condition monitoring and predictive maintenance of industrial machines. In this work, we propose Hidden Semi-Markov Models (HSMMs with (i no constraints on the state duration density function and (ii being applied to continuous or discrete observation. To deal with such a type of HSMM, we also propose modifications to the learning, inference, and prediction algorithms. Finally, automatic model selection has been made possible using the Akaike Information Criterion. This paper describes the theoretical formalization of the model as well as several experiments performed on simulated and real data with the aim of methodology validation. In all performed experiments, the model is able to correctly estimate the current state and to effectively predict the time to a predefined event with a low overall average absolute error. As a consequence, its applicability to real world settings can be beneficial, especially where in real time the Remaining Useful Lifetime (RUL of the machine is calculated.
Hidden Connectivity in Networks with Vulnerable Classes of Nodes
Directory of Open Access Journals (Sweden)
Sebastian M. Krause
2016-10-01
Full Text Available In many complex systems representable as networks, nodes can be separated into different classes. Often these classes can be linked to a mutually shared vulnerability. Shared vulnerabilities may be due to a shared eavesdropper or correlated failures. In this paper, we show the impact of shared vulnerabilities on robust connectivity and how the heterogeneity of node classes can be exploited to maintain functionality by utilizing multiple paths. Percolation is the field of statistical physics that is generally used to analyze connectivity in complex networks, but in its existing forms, it cannot treat the heterogeneity of multiple vulnerable classes. To analyze the connectivity under these constraints, we describe each class as a color and develop a “color-avoiding” percolation. We present an analytic theory for random networks and a numerical algorithm for all networks, with which we can determine which nodes are color-avoiding connected and whether the maximal set percolates in the system. We find that the interaction of topology and color distribution implies a rich critical behavior, with critical values and critical exponents depending both on the topology and on the color distribution. Applying our physics-based theory to the Internet, we show how color-avoiding percolation can be used as the basis for new topologically aware secure communication protocols. Beyond applications to cybersecurity, our framework reveals a new layer of hidden structure in a wide range of natural and technological systems.
Clustering Multivariate Time Series Using Hidden Markov Models
Directory of Open Access Journals (Sweden)
Shima Ghassempour
2014-03-01
Full Text Available In this paper we describe an algorithm for clustering multivariate time series with variables taking both categorical and continuous values. Time series of this type are frequent in health care, where they represent the health trajectories of individuals. The problem is challenging because categorical variables make it difficult to define a meaningful distance between trajectories. We propose an approach based on Hidden Markov Models (HMMs, where we first map each trajectory into an HMM, then define a suitable distance between HMMs and finally proceed to cluster the HMMs with a method based on a distance matrix. We test our approach on a simulated, but realistic, data set of 1,255 trajectories of individuals of age 45 and over, on a synthetic validation set with known clustering structure, and on a smaller set of 268 trajectories extracted from the longitudinal Health and Retirement Survey. The proposed method can be implemented quite simply using standard packages in R and Matlab and may be a good candidate for solving the difficult problem of clustering multivariate time series with categorical variables using tools that do not require advanced statistic knowledge, and therefore are accessible to a wide range of researchers.
A Synthetic Indicator of a Company's Level of Intellectual Capital as a Hidden Value
Directory of Open Access Journals (Sweden)
Przemysław Dominiak
2016-01-01
Full Text Available The authors of the paper analyzed 21 common methods of measuring a company's intellectual capital, finding that none of them meet all 6 demands that a model indicator should satisfy. As a result, a new method was developed, which meets the conditions for a model indicator. Using the chosen expert method, a synthetic indicator of a company's level of intellectual capital (WPKI has been determined. The authors of the paper determine the WPKI indicator for public construction companies using the algorithm defining a hidden value. (original abstract
Memetic Approaches for Optimizing Hidden Markov Models: A Case Study in Time Series Prediction
Bui, Lam Thu; Barlow, Michael
We propose a methodology for employing memetics (local search) within the framework of evolutionary algorithms to optimize parameters of hidden markov models. With this proposal, the rate and frequency of using local search are automatically changed over time either at a population or individual level. At the population level, we allow the rate of using local search to decay over time to zero (at the final generation). At the individual level, each individual is equipped with information of when it will do local search and for how long. This information evolves over time alongside the main elements of the chromosome representing the individual.
International Nuclear Information System (INIS)
An, Yun-Kyu; Song, Homin; Sohn, Hoon
2014-01-01
This paper presents a wireless ultrasonic wavefield imaging (WUWI) technique for detecting hidden damage inside a steel box girder bridge. The proposed technique allows (1) complete wireless excitation of piezoelectric transducers and noncontact sensing of the corresponding responses using laser beams, (2) autonomous damage visualization without comparing against baseline data previously accumulated from the pristine condition of a target structure and (3) robust damage diagnosis even for real structures with complex structural geometries. First, a new WUWI hardware system was developed by integrating optoelectronic-based signal transmitting and receiving devices and a scanning laser Doppler vibrometer. Next, a damage visualization algorithm, self-referencing f-k filter (SRF), was introduced to isolate and visualize only crack-induced ultrasonic modes from measured ultrasonic wavefield images. Finally, the performance of the proposed technique was validated through hidden crack visualization at a decommissioned Ramp-G Bridge in South Korea. The experimental results reveal that the proposed technique instantaneously detects and successfully visualizes hidden cracks even in the complex structure of a real bridge. (paper)
Population decoding of motor cortical activity using a generalized linear model with hidden states.
Lawhern, Vernon; Wu, Wei; Hatsopoulos, Nicholas; Paninski, Liam
2010-06-15
Generalized linear models (GLMs) have been developed for modeling and decoding population neuronal spiking activity in the motor cortex. These models provide reasonable characterizations between neural activity and motor behavior. However, they lack a description of movement-related terms which are not observed directly in these experiments, such as muscular activation, the subject's level of attention, and other internal or external states. Here we propose to include a multi-dimensional hidden state to address these states in a GLM framework where the spike count at each time is described as a function of the hand state (position, velocity, and acceleration), truncated spike history, and the hidden state. The model can be identified by an Expectation-Maximization algorithm. We tested this new method in two datasets where spikes were simultaneously recorded using a multi-electrode array in the primary motor cortex of two monkeys. It was found that this method significantly improves the model-fitting over the classical GLM, for hidden dimensions varying from 1 to 4. This method also provides more accurate decoding of hand state (reducing the mean square error by up to 29% in some cases), while retaining real-time computational efficiency. These improvements on representation and decoding over the classical GLM model suggest that this new approach could contribute as a useful tool to motor cortical decoding and prosthetic applications. Copyright (c) 2010 Elsevier B.V. All rights reserved.
Population Decoding of Motor Cortical Activity using a Generalized Linear Model with Hidden States
Lawhern, Vernon; Wu, Wei; Hatsopoulos, Nicholas G.; Paninski, Liam
2010-01-01
Generalized linear models (GLMs) have been developed for modeling and decoding population neuronal spiking activity in the motor cortex. These models provide reasonable characterizations between neural activity and motor behavior. However, they lack a description of movement-related terms which are not observed directly in these experiments, such as muscular activation, the subject's level of attention, and other internal or external states. Here we propose to include a multi-dimensional hidden state to address these states in a GLM framework where the spike count at each time is described as a function of the hand state (position, velocity, and acceleration), truncated spike history, and the hidden state. The model can be identified by an Expectation-Maximization algorithm. We tested this new method in two datasets where spikes were simultaneously recorded using a multi-electrode array in the primary motor cortex of two monkeys. It was found that this method significantly improves the model-fitting over the classical GLM, for hidden dimensions varying from 1 to 4. This method also provides more accurate decoding of hand state (lowering the Mean Square Error by up to 29% in some cases), while retaining real-time computational efficiency. These improvements on representation and decoding over the classical GLM model suggest that this new approach could contribute as a useful tool to motor cortical decoding and prosthetic applications. PMID:20359500
Energy Technology Data Exchange (ETDEWEB)
Beyreuther, Moritz; Wassermann, Joachim [Department of Earth and Environmental Sciences (Geophys. Observatory), Ludwig Maximilians Universitaet Muenchen, D-80333 (Germany); Carniel, Roberto [Dipartimento di Georisorse e Territorio Universitat Degli Studi di Udine, I-33100 (Italy)], E-mail: roberto.carniel@uniud.it
2008-10-01
A possible interaction of (volcano-) tectonic earthquakes with the continuous seismic noise recorded in the volcanic island of Tenerife was recently suggested, but existing catalogues seem to be far from being self consistent, calling for the development of automatic detection and classification algorithms. In this work we propose the adoption of a methodology based on Hidden Markov Models (HMMs), widely used already in other fields, such as speech classification.
Global Update and Trends of Hidden Hunger, 1995-2011: The Hidden Hunger Index
Stevens, Gretchen A.; Ezzati, Majid; Black, Robert E.; Kraemer, Klaus
2015-01-01
Background Deficiencies in essential vitamins and minerals–also termed hidden hunger–are pervasive and hold negative consequences for the cognitive and physical development of children. Methods This analysis evaluates the change in hidden hunger over time in the form of one composite indicator–the Hidden Hunger Index (HHI)–using an unweighted average of prevalence estimates from the Nutrition Impact Model Study for anemia due to iron deficiency, vitamin A deficiency, and stunting (used as a proxy indicator for zinc deficiency). Net changes from 1995–2011 and population weighted regional means for various time periods are measured. Findings Globally, hidden hunger improved (-6.7 net change in HHI) from 1995–2011. Africa was the only region to see a deterioration in hidden hunger (+1.9) over the studied time period; East Asia and the Pacific performed exceptionally well (-13.0), while other regions improved only slightly. Improvements in HHI were mostly due to reductions in zinc and vitamin A deficiencies, while anemia due to iron deficiency persisted and even increased. Interpretation This analysis is critical for informing and tracking the impact of policy and programmatic efforts to reduce micronutrient deficiencies, to advance the global nutrition agenda, and to achieve the Millennium Development Goals (MDGs). However, there remains an unmet need to invest in gathering frequent, nationally representative, high-quality micronutrient data as we renew our efforts to scale up nutrition, and as we enter the post-2015 development agenda. Funding Preparation of this manuscript was funded by Sight and Life. There was no funding involved in the study design, data collection, analysis, or decision to publish. PMID:26673631
Global Update and Trends of Hidden Hunger, 1995-2011: The Hidden Hunger Index.
Directory of Open Access Journals (Sweden)
Julie C Ruel-Bergeron
Full Text Available Deficiencies in essential vitamins and minerals-also termed hidden hunger-are pervasive and hold negative consequences for the cognitive and physical development of children.This analysis evaluates the change in hidden hunger over time in the form of one composite indicator-the Hidden Hunger Index (HHI-using an unweighted average of prevalence estimates from the Nutrition Impact Model Study for anemia due to iron deficiency, vitamin A deficiency, and stunting (used as a proxy indicator for zinc deficiency. Net changes from 1995-2011 and population weighted regional means for various time periods are measured.Globally, hidden hunger improved (-6.7 net change in HHI from 1995-2011. Africa was the only region to see a deterioration in hidden hunger (+1.9 over the studied time period; East Asia and the Pacific performed exceptionally well (-13.0, while other regions improved only slightly. Improvements in HHI were mostly due to reductions in zinc and vitamin A deficiencies, while anemia due to iron deficiency persisted and even increased.This analysis is critical for informing and tracking the impact of policy and programmatic efforts to reduce micronutrient deficiencies, to advance the global nutrition agenda, and to achieve the Millennium Development Goals (MDGs. However, there remains an unmet need to invest in gathering frequent, nationally representative, high-quality micronutrient data as we renew our efforts to scale up nutrition, and as we enter the post-2015 development agenda.Preparation of this manuscript was funded by Sight and Life. There was no funding involved in the study design, data collection, analysis, or decision to publish.
Hidden in plain sight: the formal, informal, and hidden curricula of a psychiatry clerkship.
Wear, Delese; Skillicorn, Jodie
2009-04-01
To examine perceptions of the formal, informal, and hidden curricula in psychiatry as they are observed and experienced by (1) attending physicians who have teaching responsibilities for residents and medical students, (2) residents who are taught by those same physicians and who have teaching responsibilities for medical students, and (3) medical students who are taught by attendings and residents during their psychiatry rotation. From June to November 2007, the authors conducted focus groups with attendings, residents, and students in one midwestern academic setting. The sessions were audiotaped, transcribed, and analyzed for themes surrounding the formal, informal, and hidden curricula. All three groups offered a similar belief that the knowledge, skills, and values of the formal curriculum focused on building relationships. Similarly, all three suggested that elements of the informal and hidden curricula were expressed primarily as the values arising from attendings' role modeling, as the nature and amount of time attendings spend with patients, and as attendings' advice arising from experience and intuition versus "textbook learning." Whereas students and residents offered negative values arising from the informal and hidden curricula, attendings did not, offering instead the more positive values they intended to encourage through the informal and hidden curricula. The process described here has great potential in local settings across all disciplines. Asking teachers and learners in any setting to think about how they experience the educational environment and what sense they make of all curricular efforts can provide a reality check for educators and a values check for learners as they critically reflect on the meanings of what they are learning.
Detecting Seismic Events Using a Supervised Hidden Markov Model
Burks, L.; Forrest, R.; Ray, J.; Young, C.
2017-12-01
We explore the use of supervised hidden Markov models (HMMs) to detect seismic events in streaming seismogram data. Current methods for seismic event detection include simple triggering algorithms, such as STA/LTA and the Z-statistic, which can lead to large numbers of false positives that must be investigated by an analyst. The hypothesis of this study is that more advanced detection methods, such as HMMs, may decreases false positives while maintaining accuracy similar to current methods. We train a binary HMM classifier using 2 weeks of 3-component waveform data from the International Monitoring System (IMS) that was carefully reviewed by an expert analyst to pick all seismic events. Using an ensemble of simple and discrete features, such as the triggering of STA/LTA, the HMM predicts the time at which transition occurs from noise to signal. Compared to the STA/LTA detection algorithm, the HMM detects more true events, but the false positive rate remains unacceptably high. Future work to potentially decrease the false positive rate may include using continuous features, a Gaussian HMM, and multi-class HMMs to distinguish between types of seismic waves (e.g., P-waves and S-waves). Acknowledgement: Sandia National Laboratories is a multi-mission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC., a wholly owned subsidiary of Honeywell International, Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA-0003525.SAND No: SAND2017-8154 A
Executable Pseudocode for Graph Algorithms
B. Ó Nualláin (Breanndán)
2015-01-01
textabstract Algorithms are written in pseudocode. However the implementation of an algorithm in a conventional, imperative programming language can often be scattered over hundreds of lines of code thus obscuring its essence. This can lead to difficulties in understanding or verifying the
Atlas of solar hidden photon emission
Energy Technology Data Exchange (ETDEWEB)
Redondo, Javier [Departamento de Física Teórica, Universidad de Zaragoza,Pedro Cerbuna 12, E-50009, Zaragoza (Spain); Max-Planck-Institut für Physik, Werner-Heisenberg-Institut,Föhringer Ring 6, 80805 München (Germany)
2015-07-20
Hidden photons, gauge bosons of a U(1) symmetry of a hidden sector, can constitute the dark matter of the universe and a smoking gun for large volume compactifications of string theory. In the sub-eV mass range, a possible discovery experiment consists on searching the copious flux of these particles emitted from the Sun in a helioscope setup à la Sikivie. In this paper, we compute in great detail the flux of HPs from the Sun, a necessary ingredient for interpreting such experiments. We provide a detailed exposition of transverse photon-HP oscillations in inhomogenous media, with special focus on resonance oscillations, which play a leading role in many cases. The region of the Sun emitting HPs resonantly is a thin spherical shell for which we justify an averaged-emission formula and which implies a distinctive morphology of the angular distribution of HPs on Earth in many cases. Low mass HPs with energies in the visible and IR have resonances very close to the photosphere where the solar plasma is not fully ionised and requires building a detailed model of solar refraction and absorption. We present results for a broad range of HP masses (from 0–1 keV) and energies (from the IR to the X-ray range), the most complete atlas of solar HP emission to date.
Atlas of solar hidden photon emission
Energy Technology Data Exchange (ETDEWEB)
Redondo, Javier, E-mail: redondo@mpp.mpg.de [Departamento de Física Teórica, Universidad de Zaragoza, Pedro Cerbuna 12, E-50009, Zaragoza, España (Spain)
2015-07-01
Hidden photons, gauge bosons of a U(1) symmetry of a hidden sector, can constitute the dark matter of the universe and a smoking gun for large volume compactifications of string theory. In the sub-eV mass range, a possible discovery experiment consists on searching the copious flux of these particles emitted from the Sun in a helioscope setup à la Sikivie. In this paper, we compute in great detail the flux of HPs from the Sun, a necessary ingredient for interpreting such experiments. We provide a detailed exposition of transverse photon-HP oscillations in inhomogenous media, with special focus on resonance oscillations, which play a leading role in many cases. The region of the Sun emitting HPs resonantly is a thin spherical shell for which we justify an averaged-emission formula and which implies a distinctive morphology of the angular distribution of HPs on Earth in many cases. Low mass HPs with energies in the visible and IR have resonances very close to the photosphere where the solar plasma is not fully ionised and requires building a detailed model of solar refraction and absorption. We present results for a broad range of HP masses (from 0–1 keV) and energies (from the IR to the X-ray range), the most complete atlas of solar HP emission to date.
Bayesian structural inference for hidden processes
Strelioff, Christopher C.; Crutchfield, James P.
2014-04-01
We introduce a Bayesian approach to discovering patterns in structurally complex processes. The proposed method of Bayesian structural inference (BSI) relies on a set of candidate unifilar hidden Markov model (uHMM) topologies for inference of process structure from a data series. We employ a recently developed exact enumeration of topological ɛ-machines. (A sequel then removes the topological restriction.) This subset of the uHMM topologies has the added benefit that inferred models are guaranteed to be ɛ-machines, irrespective of estimated transition probabilities. Properties of ɛ-machines and uHMMs allow for the derivation of analytic expressions for estimating transition probabilities, inferring start states, and comparing the posterior probability of candidate model topologies, despite process internal structure being only indirectly present in data. We demonstrate BSI's effectiveness in estimating a process's randomness, as reflected by the Shannon entropy rate, and its structure, as quantified by the statistical complexity. We also compare using the posterior distribution over candidate models and the single, maximum a posteriori model for point estimation and show that the former more accurately reflects uncertainty in estimated values. We apply BSI to in-class examples of finite- and infinite-order Markov processes, as well to an out-of-class, infinite-state hidden process.
Hidden ion population of the magnetosphere
International Nuclear Information System (INIS)
Olsen, R.C.
1982-01-01
Particle data from two geosynchronous satellites (Applied Technology Satellite 6 and SCATHA) show a normally hidden ion population appearing when the satellites are in the earth's shadow. Ion and electron data show the spacecraft potential dropping from +10 V in sunlight to +4 and +5 V in eclipse at local midnight, in low-energy (T/sub e/ -2 ), isotropic ion population appears which was invisible in sunlight because of the larger positive spacecraft potential. Higher-energy populations generally cover the tails of the hidden ion populations, so they cannot be inferred from daylight data. The isotropic populations appears only in a few percent of the spacecraft eclipse events, appearing only at times of low Kp (2 or less, preceded by a day with Σ Kp< or =20). A low-energy (T = 1--2 eV) field-aligned population often appears with and without the isotropic population, at slightly higher flux levels. These fluxes are visible in sunlight, but again the distribution functions obtained in eclipse differ from those that would be inferred from daylight data. Measurement of the thermal plasma population on a consistent basis, particularly in the plasma sheet, will require some method of controlling the detector potential with respect to the ambient plamsa
ESO's Hidden Treasures Brought to Light
2011-01-01
ESO's Hidden Treasures 2010 astrophotography competition attracted nearly 100 entries, and ESO is delighted to announce the winners. Hidden Treasures gave amateur astronomers the opportunity to search ESO's vast archives of astronomical data for a well-hidden cosmic gem. Astronomy enthusiast Igor Chekalin from Russia won the first prize in this difficult but rewarding challenge - the trip of a lifetime to ESO's Very Large Telescope at Paranal, Chile. The pictures of the Universe that can be seen in ESO's releases are impressive. However, many hours of skilful work are required to assemble the raw greyscale data captured by the telescopes into these colourful images, correcting them for distortions and unwanted signatures of the instrument, and enhancing them so as to bring out the details contained in the astronomical data. ESO has a team of professional image processors, but for the ESO's Hidden Treasures 2010 competition, the experts decided to give astronomy and photography enthusiasts the opportunity to show the world what they could do with the mammoth amount of data contained in ESO's archives. The enthusiasts who responded to the call submitted nearly 100 entries in total - far exceeding initial expectations, given the difficult nature of the challenge. "We were completely taken aback both by the quantity and the quality of the images that were submitted. This was not a challenge for the faint-hearted, requiring both an advanced knowledge of data processing and an artistic eye. We are thrilled to have discovered so many talented people," said Lars Lindberg Christensen, Head of ESO's education and Public Outreach Department. Digging through many terabytes of professional astronomical data, the entrants had to identify a series of greyscale images of a celestial object that would reveal the hidden beauty of our Universe. The chance of a great reward for the lucky winner was enough to spur on the competitors; the first prize being a trip to ESO's Very Large
Epitope discovery with phylogenetic hidden Markov models.
LENUS (Irish Health Repository)
Lacerda, Miguel
2010-05-01
Existing methods for the prediction of immunologically active T-cell epitopes are based on the amino acid sequence or structure of pathogen proteins. Additional information regarding the locations of epitopes may be acquired by considering the evolution of viruses in hosts with different immune backgrounds. In particular, immune-dependent evolutionary patterns at sites within or near T-cell epitopes can be used to enhance epitope identification. We have developed a mutation-selection model of T-cell epitope evolution that allows the human leukocyte antigen (HLA) genotype of the host to influence the evolutionary process. This is one of the first examples of the incorporation of environmental parameters into a phylogenetic model and has many other potential applications where the selection pressures exerted on an organism can be related directly to environmental factors. We combine this novel evolutionary model with a hidden Markov model to identify contiguous amino acid positions that appear to evolve under immune pressure in the presence of specific host immune alleles and that therefore represent potential epitopes. This phylogenetic hidden Markov model provides a rigorous probabilistic framework that can be combined with sequence or structural information to improve epitope prediction. As a demonstration, we apply the model to a data set of HIV-1 protein-coding sequences and host HLA genotypes.
Pentaquarks with hidden charm as hadroquarkonia
Energy Technology Data Exchange (ETDEWEB)
Eides, Michael I. [University of Kentucky, Department of Physics and Astronomy, Lexington, KY (United States); Petersburg Nuclear Physics Institute, St. Petersburg (Russian Federation); Petrov, Victor Yu. [Petersburg Nuclear Physics Institute, St. Petersburg (Russian Federation); Polyakov, Maxim V. [Petersburg Nuclear Physics Institute, St. Petersburg (Russian Federation); Ruhr-Universitaet Bochum, Institut fuer Theoretische Physik II, Bochum (Germany)
2018-01-15
We consider hidden charm pentaquarks as hadroquarkonium states in a QCD inspired approach. Pentaquarks arise naturally as bound states of quarkonia excitations and ordinary baryons. The LHCb P{sub c}(4450) pentaquark is interpreted as a ψ{sup '}-nucleon bound state with spin-parity J{sup P} = 3/2{sup -}. The partial decay width Γ(P{sub c}(4450) → J/ψ + N) ∼ 11 MeV is calculated and turned out to be in agreement with the experimental data for P{sub c}(4450). The P{sub c}(4450) pentaquark is predicted to be a member of one of the two almost degenerate hidden-charm baryon octets with spin-parities J{sup P} = 1/2{sup -}, 3/2{sup -}. The masses and decay widths of the octet pentaquarks are calculated. The widths are small and comparable with the width of the P{sub c}(4450) pentaquark, and the masses of the octet pentaquarks satisfy the Gell-Mann-Okubo relation. Interpretation of pentaquarks as loosely bound Σ{sub c} anti D* and Σ{sub c}{sup *} anti D* deuteronlike states is also considered. We determine quantum numbers of these bound states and calculate their masses in the one-pion exchange scenario. The hadroquarkonium and molecular approaches to exotic hadrons are compared and the relative advantages and drawbacks of each approach are discussed. (orig.)
Low energy theorems of hidden local symmetries
International Nuclear Information System (INIS)
Harada, Masayasu; Kugo, Taichiro; Yamawaki, Koichi.
1994-01-01
We prove to all orders of the loop expansion the low energy theorems of hidden local symmetries in four-dimensional nonlinear sigma models based on the coset space G/H, with G and H being arbitrary compact groups. Although the models are non-renormalizable, the proof is done in an analogous manner to the renormalization proof of gauge theories and two-dimensional nonlinear sigma models by restricting ourselves to the operators with two derivatives (counting a hidden gauge boson field as one derivative), i.e., with dimension 2, which are the only operators relevant to the low energy limit. Through loop-wise mathematical induction based on the Ward-Takahashi identity for the BRS symmetry, we solve renormalization equation for the effective action up to dimension-2 terms plus terms with the relevant BRS sources. We then show that all the quantum corrections to the dimension-2 operators, including the finite parts as well as the divergent ones, can be entirely absorbed into a re-definition (renormalization) of the parameters and the fields in the dimension-2 part of the tree-level Lagrangian. (author)
Black holes, hidden symmetries, and complete integrability.
Frolov, Valeri P; Krtouš, Pavel; Kubizňák, David
2017-01-01
The study of higher-dimensional black holes is a subject which has recently attracted vast interest. Perhaps one of the most surprising discoveries is a realization that the properties of higher-dimensional black holes with the spherical horizon topology and described by the Kerr-NUT-(A)dS metrics are very similar to the properties of the well known four-dimensional Kerr metric. This remarkable result stems from the existence of a single object called the principal tensor. In our review we discuss explicit and hidden symmetries of higher-dimensional Kerr-NUT-(A)dS black hole spacetimes. We start with discussion of the Killing and Killing-Yano objects representing explicit and hidden symmetries. We demonstrate that the principal tensor can be used as a "seed object" which generates all these symmetries. It determines the form of the geometry, as well as guarantees its remarkable properties, such as special algebraic type of the spacetime, complete integrability of geodesic motion, and separability of the Hamilton-Jacobi, Klein-Gordon, and Dirac equations. The review also contains a discussion of different applications of the developed formalism and its possible generalizations.
A Polarimetric Search for Hidden Quasars in Three Radio-selected Ultraluminous Infrared Galaxies
International Nuclear Information System (INIS)
Tran, H.D.; Brotherton, M.S.; Stanford, S.A.; Breugel, W. van; Dey, A.; Stern, D.; Antonucci, R.
1999-01-01
We have carried out a spectropolarimetric search for hidden broad-line quasars in three ultraluminous infrared galaxies (ULIRGs) discovered in the positional correlations between sources detected in deep radio surveys and the IRAS Faint Source Catalog. Only the high-ionization Seyfert 2 galaxy TF J1736+1122 is highly polarized, displaying a broad-line spectrum visible in polarized light. The other two objects, TF J1020+6436 and FF J1614+3234, display spectra dominated by a population of young (A type) stars similar to those of open-quotes E+Aclose quotes galaxies. They are unpolarized, showing no sign of hidden broad-line regions. The presence of young starburst components in all three galaxies indicates that the ULIRG phenomenon encompasses both active galactic nuclei (AGNs) and starburst activity, but the most energetic ULIRGs do not necessarily harbor open-quotes buried quasars.close quotes We find that a luminous infrared galaxy is most likely to host an obscured quasar if it exhibits a high-ionization ([O iii] λ5007/Hβ approx-gt 5) spectrum typical of a 'classic' Seyfert 2 galaxy with little or no Balmer absorption lines, is 'ultraluminous' (L IR approx-gt 10 12 L circle-dot ), and has a 'warm' IR color (f 25 /f 60 approx-gt 0.25). The detection of hidden quasars in this group but not in the low-ionization, starburst-dominated ULIRGs (classified as LINERs or H ii galaxies) may indicate an evolutionary connection, with the latter being found in younger systems. copyright copyright 1999. The American Astronomical Society
Unraveling the hidden heterogeneities of breast cancer based on functional miRNA cluster.
Directory of Open Access Journals (Sweden)
Li Li
Full Text Available It has become increasingly clear that the current taxonomy of clinical phenotypes is mixed with molecular heterogeneity, which potentially affects the treatment effect for involved patients. Defining the hidden molecular-distinct diseases using modern large-scale genomic approaches is therefore useful for refining clinical practice and improving intervention strategies. Given that microRNA expression profiling has provided a powerful way to dissect hidden genetic heterogeneity for complex diseases, the aim of the study was to develop a bioinformatics approach that identifies microRNA features leading to the hidden subtyping of complex clinical phenotypes. The basic strategy of the proposed method was to identify optimal miRNA clusters by iteratively partitioning the sample and feature space using the two-ways super-paramagnetic clustering technique. We evaluated the obtained optimal miRNA cluster by determining the consistency of co-expression and the chromosome location among the within-cluster microRNAs, and concluded that the optimal miRNA cluster could lead to a natural partition of disease samples. We applied the proposed method to a publicly available microarray dataset of breast cancer patients that have notoriously heterogeneous phenotypes. We obtained a feature subset of 13 microRNAs that could classify the 71 breast cancer patients into five subtypes with significantly different five-year overall survival rates (45%, 82.4%, 70.6%, 100% and 60% respectively; p = 0.008. By building a multivariate Cox proportional-hazards prediction model for the feature subset, we identified has-miR-146b as one of the most significant predictor (p = 0.045; hazard ratios = 0.39. The proposed algorithm is a promising computational strategy for dissecting hidden genetic heterogeneity for complex diseases, and will be of value for improving cancer diagnosis and treatment.
An introduction to hidden Markov models for biological sequences
DEFF Research Database (Denmark)
Krogh, Anders Stærmose
1998-01-01
A non-matematical tutorial on hidden Markov models (HMMs) plus a description of one of the applications of HMMs: gene finding.......A non-matematical tutorial on hidden Markov models (HMMs) plus a description of one of the applications of HMMs: gene finding....
Asymptotics for Estimating Equations in Hidden Markov Models
DEFF Research Database (Denmark)
Hansen, Jørgen Vinsløv; Jensen, Jens Ledet
Results on asymptotic normality for the maximum likelihood estimate in hidden Markov models are extended in two directions. The stationarity assumption is relaxed, which allows for a covariate process influencing the hidden Markov process. Furthermore a class of estimating equations is considered...
Secret Codes: The Hidden Curriculum of Semantic Web Technologies
Edwards, Richard; Carmichael, Patrick
2012-01-01
There is a long tradition in education of examination of the hidden curriculum, those elements which are implicit or tacit to the formal goals of education. This article draws upon that tradition to open up for investigation the hidden curriculum and assumptions about students and knowledge that are embedded in the coding undertaken to facilitate…
Searching for hidden sector in multiparticle production at LHC
Directory of Open Access Journals (Sweden)
Miguel-Angel Sanchis-Lozano
2016-03-01
Full Text Available We study the impact of a hidden sector beyond the Standard Model, e.g. a Hidden Valley model, on factorial moments and cumulants of multiplicity distributions in multiparticle production with a special emphasis on the prospects for LHC results.
Hidden Agendas in Marriage: Affective and Longitudinal Dimensions.
Krokoff, Lowell J.
1990-01-01
Examines how couples' discussions of troublesome problems reveal hidden agendas (issues not directly discussed or explored). Finds disgust and contempt are at the core of both love and respect agendas for husbands and wives. Finds that wives' more than husbands' hidden agendas are directly predictive of how negatively they argue at home. (SR)
Hidden symmetries in minimal five-dimensional supergravity
International Nuclear Information System (INIS)
Poessel, Markus; Silva, Sebastian
2004-01-01
We study the hidden symmetries arising in the dimensional reduction of d=5, N=2 supergravity to three dimensions. Extending previous partial results for the bosonic part, we give a derivation that includes fermionic terms, shedding light on the appearance of the local hidden symmetry SO(4) in the reduction
Abelian hidden sectors at a GeV
International Nuclear Information System (INIS)
Morrissey, David E.; Poland, David; Zurek, Kathryn M.
2009-01-01
We discuss mechanisms for naturally generating GeV-scale hidden sectors in the context of weak-scale supersymmetry. Such low mass scales can arise when hidden sectors are more weakly coupled to supersymmetry breaking than the visible sector, as happens when supersymmetry breaking is communicated to the visible sector by gauge interactions under which the hidden sector is uncharged, or if the hidden sector is sequestered from gravity-mediated supersymmetry breaking. We study these mechanisms in detail in the context of gauge and gaugino mediation, and present specific models of Abelian GeV-scale hidden sectors. In particular, we discuss kinetic mixing of a U(1) x gauge force with hypercharge, singlets or bi-fundamentals which couple to both sectors, and additional loop effects. Finally, we investigate the possible relevance of such sectors for dark matter phenomenology, as well as for low- and high-energy collider searches.
Identifying hidden sexual bridging communities in Chicago.
Youm, Yoosik; Mackesy-Amiti, Mary Ellen; Williams, Chyvette T; Ouellet, Lawrence J
2009-07-01
Bridge populations can play a central role in the spread of human immunodeficiency virus (HIV) by providing transmission links between higher and lower prevalence populations. While social network methods are well suited to the study of bridge populations, analyses tend to focus on dyads (i.e., risk between drug and/or sex partners) and ignore bridges between distinct subpopulations. This study takes initial steps toward moving the analysis of sexual network linkages beyond individual and risk group levels to a community level in which Chicago's 77 community areas are examined as subpopulations for the purpose of identifying potential bridging communities. Of particular interest are "hidden" bridging communities; that is, areas with above-average levels of sexual ties with other areas but whose below-average AIDS prevalence may hide their potential importance for HIV prevention. Data for this analysis came from the first wave of recruiting at the Chicago Sexual Acquisition and Transmission of HIV Cooperative Agreement Program site. Between August 2005 through October 2006, respondent-driven sampling was used to recruit users of heroin, cocaine, or methamphetamine, men who have sex with men regardless of drug use, the sex partners of these two groups, and sex partners of the sex partners. In this cross-sectional study of the sexual transmission of HIV, participants completed a network-focused computer-assisted self-administered interview, which included questions about the geographic locations of sexual contacts with up to six recent partners. Bridging scores for each area were determined using a matrix representing Chicago's 77 community areas and were assessed using two measures: non-redundant ties and flow betweenness. Bridging measures and acquired immunodeficiency syndrome (AIDS) case prevalence rates were plotted for each community area on charts representing four conditions: below-average bridging and AIDS prevalence, below-average bridging and above
Predicting the Perceptual Consequences of Hidden Hearing Loss
Directory of Open Access Journals (Sweden)
Andrew J. Oxenham
2016-12-01
Full Text Available Recent physiological studies in several rodent species have revealed that permanent damage can occur to the auditory system after exposure to a noise that produces only a temporary shift in absolute thresholds. The damage has been found to occur in the synapses between the cochlea’s inner hair cells and the auditory nerve, effectively severing part of the connection between the ear and the brain. This synaptopathy has been termed hidden hearing loss because its effects are not thought to be revealed in standard clinical, behavioral, or physiological measures of absolute threshold. It is currently unknown whether humans suffer from similar deficits after noise exposure. Even if synaptopathy occurs in humans, it remains unclear what the perceptual consequences might be or how they should best be measured. Here, we apply a simple theoretical model, taken from signal detection theory, to provide some predictions for what perceptual effects could be expected for a given loss of synapses. Predictions are made for a number of basic perceptual tasks, including tone detection in quiet and in noise, frequency discrimination, level discrimination, and binaural lateralization. The model’s predictions are in line with the empirical observations that a 50% loss of synapses leads to changes in threshold that are too small to be reliably measured. Overall, the model provides a simple initial quantitative framework for understanding and predicting the perceptual effects of synaptopathy in humans.
… To be hidden does not mean to be merely revealed – Part 1 Artistic research on hidden curriculum
Directory of Open Access Journals (Sweden)
Annette Krause
2015-09-01
Full Text Available This text revisits the long-term project Hidden Curriculum, initiated by Annette Krauss. The project addresses unquestioned routines, hierarchies of knowledge (part 1, and the role of the body in learning processes (part 2 from the perspective of secondary/high school education (in the research on a hidden curriculum. A deeper analysis of educational studies on the phenomenon of ‘hidden curriculum’ in relation to the feminist and critical pedagogies of bell hooks, Paulo Freire, and Jacques Rancière brings forward important insights generated through the artistic research within hidden curriculum. The aim of this text is to address academic canons, corporeality, and investigate everyday norms through revisiting the framework, results, and processes of the collaborative research into hidden curriculum with secondary high school students.
Dynamic portfolio optimization across hidden market regimes
DEFF Research Database (Denmark)
Nystrup, Peter; Madsen, Henrik; Lindström, Erik
2017-01-01
Regime-based asset allocation has been shown to add value over rebalancing to static weights and, in particular, reduce potential drawdowns by reacting to changes in market conditions. The predominant approach in previous studies has been to specify in advance a static decision rule for changing...... the allocation based on the state of financial markets or the economy. In this article, model predictive control (MPC) is used to dynamically optimize a portfolio based on forecasts of the mean and variance of financial returns from a hidden Markov model with time-varying parameters. There are computational...... than a buy-and-hold investment in various major stock market indices. This is after accounting for transaction costs, with a one-day delay in the implementation of allocation changes, and with zero-interest cash as the only alternative to the stock indices. Imposing a trading penalty that reduces...
Supersymmetric leptogenesis with a light hidden sector
International Nuclear Information System (INIS)
De Simone, Andrea
2010-04-01
Supersymmetric scenarios incorporating thermal leptogenesis as the origin of the observed matter-antimatter asymmetry generically predict abundances of the primordial elements which are in conflict with observations. In this paper we pro- pose a simple way to circumvent this tension and accommodate naturally ther- mal leptogenesis and primordial nucleosynthesis. We postulate the existence of a light hidden sector, coupled very weakly to the Minimal Supersymmetric Standard Model, which opens up new decay channels for the next-to-lightest supersymmetric particle, thus diluting its abundance during nucleosynthesis. We present a general model-independent analysis of this mechanism as well as two concrete realizations, and describe the relevant cosmological and astrophysical bounds and implications for this dark matter scenario. Possible experimental signatures at colliders and in cosmic-ray observations are also discussed. (orig.)
Nuclear scissors modes and hidden angular momenta
Energy Technology Data Exchange (ETDEWEB)
Balbutsev, E. B., E-mail: balbuts@theor.jinr.ru; Molodtsova, I. V. [Joint Institute for Nuclear Research (Russian Federation); Schuck, P. [Université Paris-Sud, Institut de Physique Nucléaire, IN2P3–CNRS (France)
2017-01-15
The coupled dynamics of low-lying modes and various giant resonances are studied with the help of the Wigner Function Moments method generalized to take into account spin degrees of freedom and pair correlations simultaneously. The method is based on Time-Dependent Hartree–Fock–Bogoliubov equations. The model of the harmonic oscillator including spin–orbit potential plus quadrupole–quadrupole and spin–spin interactions is considered. New low-lying spin-dependent modes are analyzed. Special attention is paid to the scissors modes. A new source of nuclear magnetism, connected with counter-rotation of spins up and down around the symmetry axis (hidden angular momenta), is discovered. Its inclusion into the theory allows one to improve substantially the agreement with experimental data in the description of energies and transition probabilities of scissors modes.
Neuroevolution Mechanism for Hidden Markov Model
Directory of Open Access Journals (Sweden)
Nabil M. Hewahi
2011-12-01
Full Text Available Hidden Markov Model (HMM is a statistical model based on probabilities. HMM is becoming one of the major models involved in many applications such as natural language
processing, handwritten recognition, image processing, prediction systems and many more. In this research we are concerned with finding out the best HMM for a certain application domain. We propose a neuroevolution process that is based first on converting the HMM to a neural network, then generating many neural networks at random where each represents a HMM. We proceed by
applying genetic operators to obtain new set of neural networks where each represents HMMs, and updating the population. Finally select the best neural network based on a fitness function.
Improved hidden Markov model for nosocomial infections.
Khader, Karim; Leecaster, Molly; Greene, Tom; Samore, Matthew; Thomas, Alun
2014-12-01
We propose a novel hidden Markov model (HMM) for parameter estimation in hospital transmission models, and show that commonly made simplifying assumptions can lead to severe model misspecification and poor parameter estimates. A standard HMM that embodies two commonly made simplifying assumptions, namely a fixed patient count and binomially distributed detections is compared with a new alternative HMM that does not require these simplifying assumptions. Using simulated data, we demonstrate how each of the simplifying assumptions used by the standard model leads to model misspecification, whereas the alternative model results in accurate parameter estimates. © The Authors 2013. Published by Oxford University Press on behalf of the Institute of Mathematics and its Applications. All rights reserved.
The elliptic genus and Hidden symmetry
International Nuclear Information System (INIS)
Jaffe, A.
2001-01-01
We study the elliptic genus (a partition function) in certain interacting, twist quantum field theories. Without twists, these theories have N=2 supersymmetry. The twists provide a regularization, and also partially break the supersymmetry. In spite of the regularization, one can establish a homotopy of the elliptic genus in a coupling parameter. Our construction relies on a priori estimates and other methods from constructive quantum field theory; this mathematical underpinning allows us to justify evaluating the elliptic genus at one endpoint of the homotopy. We obtain a version of Witten's proposed formula for the elliptic genus in terms of classical theta functions. As a consequence, the elliptic genus has a hidden SL(2,Z) symmetry characteristic of conformal theory, even though the underlying theory is not conformal. (orig.)
Hidden conformal symmetry of extremal black holes
International Nuclear Information System (INIS)
Chen Bin; Long Jiang; Zhang Jiaju
2010-01-01
We study the hidden conformal symmetry of extremal black holes. We introduce a new set of conformal coordinates to write the SL(2,R) generators. We find that the Laplacian of the scalar field in many extremal black holes, including Kerr(-Newman), Reissner-Nordstrom, warped AdS 3 , and null warped black holes, could be written in terms of the SL(2,R) quadratic Casimir. This suggests that there exist dual conformal field theory (CFT) descriptions of these black holes. From the conformal coordinates, the temperatures of the dual CFTs could be read directly. For the extremal black hole, the Hawking temperature is vanishing. Correspondingly, only the left (right) temperature of the dual CFT is nonvanishing, and the excitations of the other sector are suppressed. In the probe limit, we compute the scattering amplitudes of the scalar off the extremal black holes and find perfect agreement with the CFT prediction.
Exact solution of the hidden Markov processes
Saakian, David B.
2017-11-01
We write a master equation for the distributions related to hidden Markov processes (HMPs) and solve it using a functional equation. Thus the solution of HMPs is mapped exactly to the solution of the functional equation. For a general case the latter can be solved only numerically. We derive an exact expression for the entropy of HMPs. Our expression for the entropy is an alternative to the ones given before by the solution of integral equations. The exact solution is possible because actually the model can be considered as a generalized random walk on a one-dimensional strip. While we give the solution for the two second-order matrices, our solution can be easily generalized for the L values of the Markov process and M values of observables: We should be able to solve a system of L functional equations in the space of dimension M -1 .
Social exclusion, health and hidden homelessness.
Watson, J; Crawley, J; Kane, D
2016-10-01
Homelessness and poverty are extreme forms of social exclusion which extend beyond the lack of physical or material needs. The purpose of this study was to explore and expand the concept of social exclusion within the social determinants of health perspective - to understand how the social environment, health behaviours and health status are associated with material and social deprivation. Fundamental qualitative description with tones of focused ethnography. Participants who identified as hidden homeless described their everyday living conditions and how these everyday conditions were impacted and influenced by their social environments, coping/health behaviours and current health status. Research Ethics Board approval was granted and informed consents were obtained from 21 participants prior to the completion of individual interviews. Qualitative content analysis examined the descriptions of men and women experiencing hidden homelessness. Participants described the 'lack of quality social interactions and supports' and their 'daily struggles of street life'. They also shared the 'pain of addiction' and how coping strategies influenced health. Participants were hopeful that their insights would 'better the health of homeless people' by helping shape public policy and funding of community resources that would reduce barriers and improve overall health. Health professionals who understand health behaviours as coping mechanisms for poor quality social environments can provide more comprehensive and holistic care. The findings of this study can be used to support the importance of housing as a key factor in the health and well-being of people experiencing poverty, homelessness and social exclusion; and consequently, reinforces the need for a national housing strategy. Copyright © 2016 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.
Skyrmions with holography and hidden local symmetry
International Nuclear Information System (INIS)
Nawa, Kanabu; Hosaka, Atsushi; Suganuma, Hideo
2009-01-01
We study baryons as Skyrmions in holographic QCD with D4/D8/D8 multi-D brane system in type IIA superstring theory, and also in the nonlinear sigma model with hidden local symmetry. Comparing these two models, we find that the extra dimension and its nontrivial curvature can largely change the role of (axial) vector mesons for baryons in four-dimensional space-time. In the hidden local symmetry approach, the ρ-meson field as a massive Yang-Mills field has a singular configuration in Skyrmion, which gives a strong repulsion for the baryon as a stabilizer. When the a 1 meson is added in this approach, the stability of Skyrmion is lost by the cancellation of ρ and a 1 contributions. On the contrary, in holographic QCD, the ρ-meson field does not appear as a massive Yang-Mills field due to the extra dimension and its nontrivial curvature. We show that the ρ-meson field has a regular configuration in Skyrmion, which gives a weak attraction for the baryon in holographic QCD. We argue that Skyrmion with π, ρ, and a 1 mesons become stable due to the curved extra dimension and also the presence of the Skyrme term in holographic QCD. From this result, we also discuss the features of our truncated-resonance analysis on baryon properties with π and ρ mesons below the cutoff scale M KK ∼1 GeV in holographic QCD, which is compared with other 5D instanton analysis.
Tao, C.-S.; Chen, S.-W.; Li, Y.-Z.; Xiao, S.-P.
2017-09-01
Land cover classification is an important application for polarimetric synthetic aperture radar (PolSAR) data utilization. Rollinvariant polarimetric features such as H / Ani / text-decoration: overline">α / Span are commonly adopted in PolSAR land cover classification. However, target orientation diversity effect makes PolSAR images understanding and interpretation difficult. Only using the roll-invariant polarimetric features may introduce ambiguity in the interpretation of targets' scattering mechanisms and limit the followed classification accuracy. To address this problem, this work firstly focuses on hidden polarimetric feature mining in the rotation domain along the radar line of sight using the recently reported uniform polarimetric matrix rotation theory and the visualization and characterization tool of polarimetric coherence pattern. The former rotates the acquired polarimetric matrix along the radar line of sight and fully describes the rotation characteristics of each entry of the matrix. Sets of new polarimetric features are derived to describe the hidden scattering information of the target in the rotation domain. The latter extends the traditional polarimetric coherence at a given rotation angle to the rotation domain for complete interpretation. A visualization and characterization tool is established to derive new polarimetric features for hidden information exploration. Then, a classification scheme is developed combing both the selected new hidden polarimetric features in rotation domain and the commonly used roll-invariant polarimetric features with a support vector machine (SVM) classifier. Comparison experiments based on AIRSAR and multi-temporal UAVSAR data demonstrate that compared with the conventional classification scheme which only uses the roll-invariant polarimetric features, the proposed classification scheme achieves both higher classification accuracy and better robustness. For AIRSAR data, the overall classification
Directory of Open Access Journals (Sweden)
C.-S. Tao
2017-09-01
Full Text Available Land cover classification is an important application for polarimetric synthetic aperture radar (PolSAR data utilization. Rollinvariant polarimetric features such as H / Ani / α / Span are commonly adopted in PolSAR land cover classification. However, target orientation diversity effect makes PolSAR images understanding and interpretation difficult. Only using the roll-invariant polarimetric features may introduce ambiguity in the interpretation of targets’ scattering mechanisms and limit the followed classification accuracy. To address this problem, this work firstly focuses on hidden polarimetric feature mining in the rotation domain along the radar line of sight using the recently reported uniform polarimetric matrix rotation theory and the visualization and characterization tool of polarimetric coherence pattern. The former rotates the acquired polarimetric matrix along the radar line of sight and fully describes the rotation characteristics of each entry of the matrix. Sets of new polarimetric features are derived to describe the hidden scattering information of the target in the rotation domain. The latter extends the traditional polarimetric coherence at a given rotation angle to the rotation domain for complete interpretation. A visualization and characterization tool is established to derive new polarimetric features for hidden information exploration. Then, a classification scheme is developed combing both the selected new hidden polarimetric features in rotation domain and the commonly used roll-invariant polarimetric features with a support vector machine (SVM classifier. Comparison experiments based on AIRSAR and multi-temporal UAVSAR data demonstrate that compared with the conventional classification scheme which only uses the roll-invariant polarimetric features, the proposed classification scheme achieves both higher classification accuracy and better robustness. For AIRSAR data, the overall classification accuracy
A Hidden Markov Model for Urban-Scale Traffic Estimation Using Floating Car Data.
Wang, Xiaomeng; Peng, Ling; Chi, Tianhe; Li, Mengzhu; Yao, Xiaojing; Shao, Jing
2015-01-01
Urban-scale traffic monitoring plays a vital role in reducing traffic congestion. Owing to its low cost and wide coverage, floating car data (FCD) serves as a novel approach to collecting traffic data. However, sparse probe data represents the vast majority of the data available on arterial roads in most urban environments. In order to overcome the problem of data sparseness, this paper proposes a hidden Markov model (HMM)-based traffic estimation model, in which the traffic condition on a road segment is considered as a hidden state that can be estimated according to the conditions of road segments having similar traffic characteristics. An algorithm based on clustering and pattern mining rather than on adjacency relationships is proposed to find clusters with road segments having similar traffic characteristics. A multi-clustering strategy is adopted to achieve a trade-off between clustering accuracy and coverage. Finally, the proposed model is designed and implemented on the basis of a real-time algorithm. Results of experiments based on real FCD confirm the applicability, accuracy, and efficiency of the model. In addition, the results indicate that the model is practicable for traffic estimation on urban arterials and works well even when more than 70% of the probe data are missing.
Hidden Markov model tracking of continuous gravitational waves from young supernova remnants
Sun, L.; Melatos, A.; Suvorova, S.; Moran, W.; Evans, R. J.
2018-02-01
Searches for persistent gravitational radiation from nonpulsating neutron stars in young supernova remnants are computationally challenging because of rapid stellar braking. We describe a practical, efficient, semicoherent search based on a hidden Markov model tracking scheme, solved by the Viterbi algorithm, combined with a maximum likelihood matched filter, the F statistic. The scheme is well suited to analyzing data from advanced detectors like the Advanced Laser Interferometer Gravitational Wave Observatory (Advanced LIGO). It can track rapid phase evolution from secular stellar braking and stochastic timing noise torques simultaneously without searching second- and higher-order derivatives of the signal frequency, providing an economical alternative to stack-slide-based semicoherent algorithms. One implementation tracks the signal frequency alone. A second implementation tracks the signal frequency and its first time derivative. It improves the sensitivity by a factor of a few upon the first implementation, but the cost increases by 2 to 3 orders of magnitude.
Aucouturier, Jean-Julien; Nonaka, Yulri; Katahira, Kentaro; Okanoya, Kazuo
2011-11-01
The paper describes an application of machine learning techniques to identify expiratory and inspiration phases from the audio recording of human baby cries. Crying episodes were recorded from 14 infants, spanning four vocalization contexts in their first 12 months of age; recordings from three individuals were annotated manually to identify expiratory and inspiratory sounds and used as training examples to segment automatically the recordings of the other 11 individuals. The proposed algorithm uses a hidden Markov model architecture, in which state likelihoods are estimated either with Gaussian mixture models or by converting the classification decisions of a support vector machine. The algorithm yields up to 95% classification precision (86% average), and its ability generalizes over different babies, different ages, and vocalization contexts. The technique offers an opportunity to quantify expiration duration, count the crying rate, and other time-related characteristics of baby crying for screening, diagnosis, and research purposes over large populations of infants.
Non-statistically populated autoionizing levels of Li-like carbon: Hidden-crossings
International Nuclear Information System (INIS)
Deveney, E.F.; Krause, H.F.; Jones, N.L.
1995-01-01
The intensities of the Auger-electron lines from autoionizing (AI) states of Li-like (1s2s2l) configurations excited in ion-atom collisions vary as functions of the collision parameters such as, for example, the collision velocity. A statistical population of the three-electron levels is at best incomplete and underscores the intricate dynamical development of the electronic states. The authors compare several experimental studies to calculations using ''hidden-crossing'' techniques to explore some of the details of these Auger-electron intensity variation phenomena. The investigations show promising results suggesting that Auger-electron intensity variations can be used to probe collision dynamics
Hidden gauge structure of supersymmetric free differential algebras
Energy Technology Data Exchange (ETDEWEB)
Andrianopoli, Laura [DISAT, Politecnico di Torino,Corso Duca degli Abruzzi 24, I-10129 Turin (Italy); INFN - Sezione di Torino,Torino (Italy); D’Auria, Riccardo [DISAT, Politecnico di Torino,Corso Duca degli Abruzzi 24, I-10129 Turin (Italy); Ravera, Lucrezia [DISAT, Politecnico di Torino,Corso Duca degli Abruzzi 24, I-10129 Turin (Italy); INFN - Sezione di Torino,Torino (Italy)
2016-08-16
The aim of this paper is to clarify the role of the nilpotent fermionic generator Q{sup ′} introduced in http://dx.doi.org/10.1016/0550-3213(82)90376-5 and appearing in the hidden supergroup underlying the free differential algebra (FDA) of D=11 supergravity. We give a physical explanation of its role by looking at the gauge properties of the theory. We find that its presence is necessary, in order that the extra 1-forms of the hidden supergroup give rise to the correct gauge transformations of the p-forms of the FDA. This interpretation is actually valid for any supergravity containing antisymmetric tensor fields, and any supersymmetric FDA can always be traded for a hidden Lie superalgebra containing extra fermionic nilpotent generators. As an interesting example we construct the hidden superalgebra associated with the FDA of N=2, D=7 supergravity. In this case we are able to parametrize the mutually non local 2- and 3-form B{sup (2)} and B{sup (3)} in terms of hidden 1-forms and find that supersymmetry and gauge invariance require in general the presence of two nilpotent fermionic generators in the hidden algebra. We propose that our approach, where all the invariances of the FDA are expressed as Lie derivatives of the p-forms in the hidden supergroup manifold, could be an appropriate framework to discuss theories defined in enlarged versions of superspace recently considered in the literature, such us double field theory and its generalizations.
Animated construction of line drawings
Fu, Hongbo; Zhou, Shizhe; Liu, Ligang; Mitra, Niloy J.
2011-01-01
system produces plausible animated constructions of input line drawings, with no or little user intervention. We test our algorithm on a range of input sketches, with varying degree of complexity and structure, and evaluate the results via a user study
Sociocultural Dimension of Hidden Content in a Professional Language Curriculum
Directory of Open Access Journals (Sweden)
Ekaterina E. Shishlova
2017-12-01
Full Text Available Introduction: studying curriculum as a pedagogical problem has traditionally been reduced to the analysis of its explicit content, set in official educational documents. However, a much less studied hidden content plays a significant role in education. So, what is the role of the hidden curriculum during professional language training? The purpose of the article is to determine the potential impact of hidden curriculum on students’ conceptual worldview. Comparing the worldview presented in textbooks with students’ one has allowed us to estimate the rate of influence of hidden curr iculum. Materials and Methods: the methodological basis of the work is the cultural concept of personalityoriented education. The methodology for studying the role of hidden curriculum includes four stages: at the first stage, the authors set the criteria for selecting textbooks for analysis and do the selection; at the second stage, the authors select sociocultural concepts for analysis; at the third stage, the scheme of analysis is designed and the analysis of textbooks is done; at the fourth stage, the authors identify the potential influence of hidden curriculum on students’ conceptual worldview. Results: the structure of hidden curriculum has been determined and the scheme for analysing its subject component has been developed. The authors have identified a significant influence of hidden curriculum on students’ worldview, which represents the scientific novelty of the article. Discussion and Conclusions: the article gives the definition of a hidden curriculum which is new for Russian pedagogy and presents a methodology for its analysis in EFL textbooks. That analysis is recommended to be conducted when selecting teaching materials both i n languages and other humanities.
Garrido, M.A.; Iturriaga, C.; Márquez, A.; Portillo, J.R.; Reyes, P.; Wolff, A.; Eades, P.; Takaoka, T.
2001-01-01
Graphical features on map, charts, diagrams and graph drawings usually must be annotated with text labels in order to convey their meaning. In this paper we focus on a problem that arises when labeling schematized maps, e.g. for subway networks. We present algorithms for labeling points on a line
Multilayer Neural Networks with Extensively Many Hidden Units
International Nuclear Information System (INIS)
Rosen-Zvi, Michal; Engel, Andreas; Kanter, Ido
2001-01-01
The information processing abilities of a multilayer neural network with a number of hidden units scaling as the input dimension are studied using statistical mechanics methods. The mapping from the input layer to the hidden units is performed by general symmetric Boolean functions, whereas the hidden layer is connected to the output by either discrete or continuous couplings. Introducing an overlap in the space of Boolean functions as order parameter, the storage capacity is found to scale with the logarithm of the number of implementable Boolean functions. The generalization behavior is smooth for continuous couplings and shows a discontinuous transition to perfect generalization for discrete ones
Update on hidden sectors with dark forces and dark matter
Energy Technology Data Exchange (ETDEWEB)
Andreas, Sarah
2012-11-15
Recently there has been much interest in hidden sectors, especially in the context of dark matter and ''dark forces'', since they are a common feature of beyond standard model scenarios like string theory and SUSY and additionally exhibit interesting phenomenological aspects. Various laboratory experiments place limits on the so-called hidden photon and continuously further probe and constrain the parameter space; an updated overview is presented here. Furthermore, for several hidden sector models with light dark matter we study the viability with respect to the relic abundance and direct detection experiments.
Hidden photon dark matter search with large metallic mirror
International Nuclear Information System (INIS)
Doebrich, Babette; Lindner, Axel; Daumiller, Kai; Engel, Ralph; Roth, Markus; Kowalski, Marek
2014-10-01
If Dark Matter is composed of hidden-sector photons that kinetically mix with photons of the visible sector, then Dark Matter has a tiny oscillating electric field component. Its presence would lead to a small amount of visible radiation being emitted from a conducting surface, with the photon frequency given approximately by the mass of the hidden photon. Here, we report on experimental efforts that have started recently to search for such hidden photon Dark Matter in the (sub-)eV regime with a prototype mirror for the Auger fluorescence detector at the Karlsruhe Institute for Technology.
Naturally light hidden photons in LARGE volume string compactifications
International Nuclear Information System (INIS)
Goodsell, M.; Jaeckel, J.; Redondo, J.; Ringwald, A.
2009-09-01
Extra ''hidden'' U(1) gauge factors are a generic feature of string theory that is of particular phenomenological interest. They can kinetically mix with the Standard Model photon and are thereby accessible to a wide variety of astrophysical and cosmological observations and laboratory experiments. In this paper we investigate the masses and the kinetic mixing of hidden U(1)s in LARGE volume compactifications of string theory. We find that in these scenarios the hidden photons can be naturally light and that their kinetic mixing with the ordinary electromagnetic photon can be of a size interesting for near future experiments and observations. (orig.)
Hidden Area and Mechanical Nonlinearities in Freestanding Graphene
Nicholl, Ryan J. T.; Lavrik, Nickolay V.; Vlassiouk, Ivan; Srijanto, Bernadeta R.; Bolotin, Kirill I.
2017-06-01
We investigated the effect of out-of-plane crumpling on the mechanical response of graphene membranes. In our experiments, stress was applied to graphene membranes using pressurized gas while the strain state was monitored through two complementary techniques: interferometric profilometry and Raman spectroscopy. By comparing the data obtained through these two techniques, we determined the geometric hidden area which quantifies the crumpling strength. While the devices with hidden area ˜0 % obeyed linear mechanics with biaxial stiffness 428 ±10 N /m , specimens with hidden area in the range 0.5%-1.0% were found to obey an anomalous nonlinear Hooke's law with an exponent ˜0.1 .
Context Tree Estimation in Variable Length Hidden Markov Models
Dumont, Thierry
2011-01-01
We address the issue of context tree estimation in variable length hidden Markov models. We propose an estimator of the context tree of the hidden Markov process which needs no prior upper bound on the depth of the context tree. We prove that the estimator is strongly consistent. This uses information-theoretic mixture inequalities in the spirit of Finesso and Lorenzo(Consistent estimation of the order for Markov and hidden Markov chains(1990)) and E.Gassiat and S.Boucheron (Optimal error exp...
Local models and hidden nonlocality in Quantum Theory
Guerini, Leonardo
2014-01-01
This Master's thesis has two central subjects: the simulation of correlations generated by local measurements on entangled quantum states by local hidden-variables models and the revelation of hidden nonlocality. We present and detail the Werner's local model and the hidden nonlocality of some Werner states of dimension $d\\geq5$, the Gisin-Degorre's local model for a Werner state of dimension $d=2$ and the local model of Hirsch et al. for mixtures of the singlet state and noise, all of them f...
Suppressing the QCD axion abundance by hidden monopoles
International Nuclear Information System (INIS)
Kawasaki, Masahiro
2015-11-01
We study the Witten effect of hidden monopoles on the QCD axion dynamics, and show that its abundance as well as isocurvature perturbations can be significantly suppressed if there is a sufficient amount of hidden monopoles. When the hidden monopoles make up a significant fraction of dark matter, the Witten effect suppresses the abundance of axion with the decay constant smaller than 10 12 GeV. The cosmological domain wall problem of the QCD axion can also be avoided, relaxing the upper bound on the decay constant when the Peccei-Quinn symmetry is spontaneously broken after inflation.
High Energy Colliders and Hidden Sectors
Dror, Asaf Jeff
This thesis explores two dominant frontiers of theoretical physics, high energy colliders and hidden sectors. The Large Hadron Collider (LHC) is just starting to reach its maximum operational capabilities. However, already with the current data, large classes of models are being put under significant pressure. It is crucial to understand whether the (thus far) null results are a consequence of a lack of solution to the hierarchy problem around the weak scale or requires expanding the search strategy employed at the LHC. It is the duty of the current generation of physicists to design new searches to ensure that no stone is left unturned. To this end, we study the sensitivity of the LHC to the couplings in the Standard Model top sector. We find it can significantly improve the measurements on ZtRtR coupling by a novel search strategy, making use of an implied unitarity violation in such models. Analogously, we show that other couplings in the top sector can also be measured with the same technique. Furthermore, we critically analyze a set of anomalies in the LHC data and how they may appear from consistent UV completions. We also propose a technique to measure lifetimes of new colored particles with non-trivial spin. While the high energy frontier will continue to take data, it is likely the only collider of its kind for the next couple decades. On the other hand, low-energy experiments have a promising future with many new proposed experiments to probe the existence of particles well below the weak scale but with small couplings to the Standard Model. In this work we survey the different possibilities, focusingon the constraints as well as possible new hidden sector dynamics. In particular, we show that vector portals which couple to an anomalous current, e.g., baryon number, are significantly constrained from flavor changing meson decays and rare Z decays. Furthermore, we present a new mechanism for dark matter freezeout which depletes the dark sector through an
Alleviating hidden hunger. Approaches that work
International Nuclear Information System (INIS)
Kennedy, E.; Mannar, V.; Iyengar, V.
2003-01-01
The world has come a long way in understanding the nature, magnitude and range of solutions to micronutrient malnutrition - often called 'hidden hunger'. The most sustainable solutions - that is those that are likely to be maintained in the long term - almost surely will include food-based approaches including diet diversity, food fortification and biofortification. Food fortification and biofortification could be some of the most cost-effective of all public health interventions and thus within the economic reach of even the world's poorest. In order to implement them in a sustainable manner, a combination of technical, operational, economic, behavioural and political factors need to be addressed. In some ways the technological issues are the easiest. Because of attention to research, we now have a variety of ways for both single and multiple micronutrients to reach the target population. We also know what is needed in order to ensure delivery systems. The key factor for continued success in reducing micronutrient malnutrition through fortification is a political commitment at the national and international level and creating effective public-private partnerships at the national level. The payoff for eliminating hidden hunger through nutrient fortification is enormous and few other public health interventions offer such a promising health, nutrition and economic success story. Nuclear and isotopic techniques are valuable tools in helping to meet the multifaceted challenges posed by nutritional disorders affecting the entire human life span (embryonic to elderly). Among the numerous applications available, isotopic techniques are uniquely well suited for targeting and tracking progress in food and nutrition development programmes (See box: How Nutrients are Tracked). These include: use of the stable isotopes of iron (Fe) and zinc (Zn) as a kind of gold standard in studies of their bioavailability from foods; trace element bioavailability and pool sizes for
Prediction of Annual Rainfall Pattern Using Hidden Markov Model ...
African Journals Online (AJOL)
ADOWIE PERE
Hidden Markov model is very influential in stochastic world because of its ... the earth from the clouds. The usual ... Rainfall modelling and ... Markov Models have become popular tools ... environment sciences, University of Jos, plateau state,.
New limits on hidden photons from past electron beam dumps
International Nuclear Information System (INIS)
Andreas, Sarah; Niebuhr, Carsten; Ringwald, Andreas
2012-09-01
Hidden sectors with light extra U(1) gauge bosons, so called hidden photons, have recently attracted some attention because they are a common feature of physics beyond the Standard Model like string theory and SUSY and additionally are phenomenologically of great interest regarding recent astrophysical observations. The hidden photon is already constrained by various laboratory experiments and presently searched for in running as well as upcoming experiments. We summarize the current status of limits on hidden photons from past electron beam dump experiments including two new limits from such experiments at KEK and Orsay that have so far not been considered. All our limits take into account the experimental acceptances obtained from Monte Carlo simulations.
Search for hidden particles with the SHiP experiment
Energy Technology Data Exchange (ETDEWEB)
Hagner, Caren; Bick, Daniel; Bieschke, Stefan; Ebert, Joachim; Schmidt-Parzefall, Walter [Universitaet Hamburg, Institut fuer Experimentalphysik, Luruper Chaussee 149, 22761 Hamburg (Germany)
2016-07-01
Many theories beyond the standard model predict long lived neutral (hidden) particles. There might be a whole Hidden Sector (HS) of weakly interacting particles, which cannot be detected in existing high energy experiments. The SHiP experiment (Search for Hidden Particles) requires a high intensity beam dump, which could be realized by a new facility at the CERN SPS accelerator. New superweakly interacting particles with masses below O(10) GeV could be produced in the beam dump and detected in a general purpose Hidden Sector (HS) detector. In addition there will be a dedicated tau neutrino subdetector. I present the major requirements and technical challenges for the HS detector and discuss how the HS can be accessed through several portals: neutrino portal, scalar portal, vector portal and many more.
Cosmological abundance of the QCD axion coupled to hidden photons
Kitajima, Naoya; Sekiguchi, Toyokazu; Takahashi, Fuminobu
2018-06-01
We study the cosmological evolution of the QCD axion coupled to hidden photons. For a moderately strong coupling, the motion of the axion field leads to an explosive production of hidden photons by tachyonic instability. We use lattice simulations to evaluate the cosmological abundance of the QCD axion. In doing so, we incorporate the backreaction of the produced hidden photons on the axion dynamics, which becomes significant in the non-linear regime. We find that the axion abundance is suppressed by at most O (102) for the decay constant fa =1016GeV, compared to the case without the coupling. For a sufficiently large coupling, the motion of the QCD axion becomes strongly damped, and as a result, the axion abundance is enhanced. Our results show that the cosmological upper bound on the axion decay constant can be relaxed by a few hundred for a certain range of the coupling to hidden photons.
Dopamine reward prediction errors reflect hidden state inference across time
Starkweather, Clara Kwon; Babayan, Benedicte M.; Uchida, Naoshige; Gershman, Samuel J.
2017-01-01
Midbrain dopamine neurons signal reward prediction error (RPE), or actual minus expected reward. The temporal difference (TD) learning model has been a cornerstone in understanding how dopamine RPEs could drive associative learning. Classically, TD learning imparts value to features that serially track elapsed time relative to observable stimuli. In the real world, however, sensory stimuli provide ambiguous information about the hidden state of the environment, leading to the proposal that TD learning might instead compute a value signal based on an inferred distribution of hidden states (a ‘belief state’). In this work, we asked whether dopaminergic signaling supports a TD learning framework that operates over hidden states. We found that dopamine signaling exhibited a striking difference between two tasks that differed only with respect to whether reward was delivered deterministically. Our results favor an associative learning rule that combines cached values with hidden state inference. PMID:28263301
On the LHC sensitivity for non-thermalised hidden sectors
Kahlhoefer, Felix
2018-04-01
We show under rather general assumptions that hidden sectors that never reach thermal equilibrium in the early Universe are also inaccessible for the LHC. In other words, any particle that can be produced at the LHC must either have been in thermal equilibrium with the Standard Model at some point or must be produced via the decays of another hidden sector particle that has been in thermal equilibrium. To reach this conclusion, we parametrise the cross section connecting the Standard Model to the hidden sector in a very general way and use methods from linear programming to calculate the largest possible number of LHC events compatible with the requirement of non-thermalisation. We find that even the HL-LHC cannot possibly produce more than a few events with energy above 10 GeV involving states from a non-thermalised hidden sector.
Risk from the frontlines of a hidden epidemic sexuality, masculinities ...
African Journals Online (AJOL)
Risk from the frontlines of a hidden epidemic sexuality, masculinities and social pressures ... It frames risk in the context of the dynamics governing sexuality, underlined ... MSM risk and practice, in these contexts, are consequently shaped by ...
New limits on hidden photons from past electron beam dumps
Energy Technology Data Exchange (ETDEWEB)
Andreas, Sarah; Niebuhr, Carsten; Ringwald, Andreas
2012-09-15
Hidden sectors with light extra U(1) gauge bosons, so called hidden photons, have recently attracted some attention because they are a common feature of physics beyond the Standard Model like string theory and SUSY and additionally are phenomenologically of great interest regarding recent astrophysical observations. The hidden photon is already constrained by various laboratory experiments and presently searched for in running as well as upcoming experiments. We summarize the current status of limits on hidden photons from past electron beam dump experiments including two new limits from such experiments at KEK and Orsay that have so far not been considered. All our limits take into account the experimental acceptances obtained from Monte Carlo simulations.
A two particle hidden sector and the oscillations with photons
Energy Technology Data Exchange (ETDEWEB)
Alvarez, Pedro D. [Universidad de Antofagasta, Departamento de Fisica, Antofagasta (Chile); Arias, Paola; Maldonado, Carlos [Universidad de Santiago de Chile, Departmento de Fisica, Santiago (Chile)
2018-01-15
We present a detailed study of the oscillations and optical properties for vacuum, in a model for the dark sector that contains axion-like particles and hidden photons. We provide bounds for the couplings versus the mass, using current results from ALPS-I and PVLAS. We also discuss the challenges for the detection of models with more than one hidden particle in light shining trough wall-like experiments. (orig.)
Rare Z boson decays to a hidden sector
Blinov, Nikita; Izaguirre, Eder; Shuve, Brian
2018-01-01
We demonstrate that rare decays of the Standard Model Z boson can be used to discover and characterize the nature of new hidden-sector particles. We propose new searches for these particles in soft, high-multiplicity leptonic final states at the Large Hadron Collider. The proposed searches are sensitive to low-mass particles produced in Z decays, and we argue that these striking signatures can shed light on the hidden-sector couplings and mechanism for mass generation.
Anticipating hidden text salting in emails (extended abstract)
Lioma, Christina; Moens, Marie-Francine; Gomez, Juan Carlos; De Beer, Jan; Bergholz, Andre; Paass, Gerhard; Horkan, Patrick
2008-01-01
Salting is the intentional addition or distortion of content, aimed to evade automatic filtering. Salting is usually found in spam emails. Salting can also be hidden in phishing emails, which aim to steal personal information from users. We present a novel method that detects hidden salting tricks as visual anomalies in text. We solely use these salting tricks to successfully classify emails as phishing (F-measure >90%).
Hidden twelve-dimensional super Poincare symmetry in eleven dimensions
International Nuclear Information System (INIS)
Bars, Itzhak; Deliduman, Cemsinan; Pasqua, Andrea; Zumino, Bruno
2004-01-01
First, we review a result in our previous paper, of how a ten-dimensional superparticle, taken off-shell, has a hidden eleven-dimensional super Poincare symmetry. Then, we show that the physical sector is defined by three first-class constraints which preserve the full eleven-dimensional symmetry. Applying the same concepts to the eleven-dimensional superparticle, taken off-shell, we discover a hidden twelve-dimensional super Poincare symmetry that governs the theory
Hidden charged dark matter and chiral dark radiation
Ko, P.; Nagata, Natsumi; Tang, Yong
2017-10-01
In the light of recent possible tensions in the Hubble constant H0 and the structure growth rate σ8 between the Planck and other measurements, we investigate a hidden-charged dark matter (DM) model where DM interacts with hidden chiral fermions, which are charged under the hidden SU(N) and U(1) gauge interactions. The symmetries in this model assure these fermions to be massless. The DM in this model, which is a Dirac fermion and singlet under the hidden SU(N), is also assumed to be charged under the U(1) gauge symmetry, through which it can interact with the chiral fermions. Below the confinement scale of SU(N), the hidden quark condensate spontaneously breaks the U(1) gauge symmetry such that there remains a discrete symmetry, which accounts for the stability of DM. This condensate also breaks a flavor symmetry in this model and Nambu-Goldstone bosons associated with this flavor symmetry appear below the confinement scale. The hidden U(1) gauge boson and hidden quarks/Nambu-Goldstone bosons are components of dark radiation (DR) above/below the confinement scale. These light fields increase the effective number of neutrinos by δNeff ≃ 0.59 above the confinement scale for N = 2, resolving the tension in the measurements of the Hubble constant by Planck and Hubble Space Telescope if the confinement scale is ≲1 eV. DM and DR continuously scatter with each other via the hidden U(1) gauge interaction, which suppresses the matter power spectrum and results in a smaller structure growth rate. The DM sector couples to the Standard Model sector through the exchange of a real singlet scalar mixing with the Higgs boson, which makes it possible to probe our model in DM direct detection experiments. Variants of this model are also discussed, which may offer alternative ways to investigate this scenario.
Hidden Structural Codes in Protein Intrinsic Disorder.
Borkosky, Silvia S; Camporeale, Gabriela; Chemes, Lucía B; Risso, Marikena; Noval, María Gabriela; Sánchez, Ignacio E; Alonso, Leonardo G; de Prat Gay, Gonzalo
2017-10-17
Intrinsic disorder is a major structural category in biology, accounting for more than 30% of coding regions across the domains of life, yet consists of conformational ensembles in equilibrium, a major challenge in protein chemistry. Anciently evolved papillomavirus genomes constitute an unparalleled case for sequence to structure-function correlation in cases in which there are no folded structures. E7, the major transforming oncoprotein of human papillomaviruses, is a paradigmatic example among the intrinsically disordered proteins. Analysis of a large number of sequences of the same viral protein allowed for the identification of a handful of residues with absolute conservation, scattered along the sequence of its N-terminal intrinsically disordered domain, which intriguingly are mostly leucine residues. Mutation of these led to a pronounced increase in both α-helix and β-sheet structural content, reflected by drastic effects on equilibrium propensities and oligomerization kinetics, and uncovers the existence of local structural elements that oppose canonical folding. These folding relays suggest the existence of yet undefined hidden structural codes behind intrinsic disorder in this model protein. Thus, evolution pinpoints conformational hot spots that could have not been identified by direct experimental methods for analyzing or perturbing the equilibrium of an intrinsically disordered protein ensemble.
Dietary phytate, zinc and hidden zinc deficiency.
Sandstead, Harold H; Freeland-Graves, Jeanne H
2014-10-01
Epidemiological data suggest at least one in five humans are at risk of zinc deficiency. This is in large part because the phytate in cereals and legumes has not been removed during food preparation. Phytate, a potent indigestible ligand for zinc prevents it's absorption. Without knowledge of the frequency of consumption of foods rich in phytate, and foods rich in bioavailable zinc, the recognition of zinc deficiency early in the illness may be difficult. Plasma zinc is insensitive to early zinc deficiency. Serum ferritin concentration≤20μg/L is a potential indirect biomarker. Early effects of zinc deficiency are chemical, functional and may be "hidden". The clinical problem is illustrated by 2 studies that involved US Mexican-American children, and US premenopausal women. The children were consuming home diets that included traditional foods high in phytate. The premenopausal women were not eating red meat on a regular basis, and their consumption of phytate was mainly from bran breakfast cereals. In both studies the presence of zinc deficiency was proven by functional responses to controlled zinc treatment. In the children lean-mass, reasoning, and immunity were significantly affected. In the women memory, reasoning, and eye-hand coordination were significantly affected. A screening self-administered food frequency questionnaire for office might help caregiver's identify patients at risk of zinc deficiency. Copyright © 2014 Elsevier GmbH. All rights reserved.
Natural inflation with hidden scale invariance
Directory of Open Access Journals (Sweden)
Neil D. Barrie
2016-05-01
Full Text Available We propose a new class of natural inflation models based on a hidden scale invariance. In a very generic Wilsonian effective field theory with an arbitrary number of scalar fields, which exhibits scale invariance via the dilaton, the potential necessarily contains a flat direction in the classical limit. This flat direction is lifted by small quantum corrections and inflation is realised without need for an unnatural fine-tuning. In the conformal limit, the effective potential becomes linear in the inflaton field, yielding to specific predictions for the spectral index and the tensor-to-scalar ratio, being respectively: ns−1≈−0.025(N⋆60−1 and r≈0.0667(N⋆60−1, where N⋆≈30–65 is a number of efolds during observable inflation. This predictions are in reasonable agreement with cosmological measurements. Further improvement of the accuracy of these measurements may turn out to be critical in falsifying our scenario.
Gauging hidden symmetries in two dimensions
International Nuclear Information System (INIS)
Samtleben, Henning; Weidner, Martin
2007-01-01
We initiate the systematic construction of gauged matter-coupled supergravity theories in two dimensions. Subgroups of the affine global symmetry group of toroidally compactified supergravity can be gauged by coupling vector fields with minimal couplings and a particular topological term. The gauge groups typically include hidden symmetries that are not among the target-space isometries of the ungauged theory. The gaugings constructed in this paper are described group-theoretically in terms of a constant embedding tensor subject to a number of constraints which parametrizes the different theories and entirely encodes the gauged Lagrangian. The prime example is the bosonic sector of the maximally supersymmetric theory whose ungauged version admits an affine e 9 global symmetry algebra. The various parameters (related to higher-dimensional p-form fluxes, geometric and non-geometric fluxes, etc.) which characterize the possible gaugings, combine into an embedding tensor transforming in the basic representation of e 9 . This yields an infinite-dimensional class of maximally supersymmetric theories in two dimensions. We work out and discuss several examples of higher-dimensional origin which can be systematically analyzed using the different gradings of e 9
Academic mobbing: hidden health hazard at workplace.
Khoo, Sb
2010-01-01
Academic mobbing is a non-violent, sophisticated, 'ganging up' behaviour adopted by academicians to "wear and tear" a colleague down emotionally through unjustified accusation, humiliation, general harassment and emotional abuse. These are directed at the target under a veil of lies and justifications so that they are "hidden" to others and difficult to prove. Bullies use mobbing activities to hide their own weaknesses and incompetence. Targets selected are often intelligent, innovative high achievers, with good integrity and principles. Mobbing activities appear trivial and innocuous on its own but the frequency and pattern of their occurrence over long period of time indicates an aggressive manipulation to "eliminate" the target. Mobbing activities typically progress through five stereotypical phases that begins with an unsolved minor conflict between two workers and ultimately escalates into a senseless mobbing whereby the target is stigmatized and victimized to justify the behaviours of the bullies. The result is always physical, mental, social distress or illness and, most often, expulsion of target from the workplace. Organizations are subjected to great financial loss, loss of key workers and a tarnished public image and reputation. Public awareness, education, effective counselling, establishment of anti-bullying policies and legislations at all levels are necessary to curb academic mobbing. General practitioners (GPs) play an important role in supporting patients subjected to mental and physical health injury caused by workplace bullying and mobbing.
Hidden-Sector Dynamics and the Supersymmetric Seesaw
Campbell, Bruce A; Maybury, David W
2008-01-01
In light of recent analyses that have shown that nontrivial hidden-sector dynamics in models of supersymmetry breaking can lead to a significant impact on the predicted low-energy supersymmetric spectrum, we extend these studies to consider hidden-sector effects in extensions of the MSSM to include a seesaw model for neutrino masses. A dynamical hidden sector in an interval of mass scales below the seesaw scale would yield renormalization-group running involving both the anomalous dimension from the hidden sector and the seesaw-extended MSSM renormalization group equations (RGEs). These effects interfere in general, altering the generational mixing of the sleptons, and allowing for a substantial change to the expected level of charged-lepton flavour violation in seesaw-extended MSSM models. These results provide further support for recent theoretical observations that knowledge of the hidden sector is required in order to make concrete low-energy predictions, if the hidden sector is strongly coupled. In parti...
A Facility to Search for Hidden Particles (SHiP) at the CERN SPS
Anelli, M.; Arduini, G.; Back, J.J.; Bagulya, A.; Baldini, W.; Baranov, A.; Barker, G.J.; Barsuk, S.; Battistin, M.; Bauche, J.; Bay, A.; Bayliss, V.; Bellagamba, L.; Bencivenni, G.; Bertani, M.; Bezshyyko, O.; Bick, D.; Bingefors, N.; Blondel, A.; Bogomilov, M.; Boyarsky, A.; Bonacorsi, D.; Bondarenko, D.; Bonivento, W.; Borburgh, J.; Bradshaw, T.; Brenner, R.; Breton, D.; Brook, N.; Bruschi, M.; Buonaura, A.; Buontempo, S.; Cadeddu, S.; Calcaterra, A.; Calviani, M.; Campanelli, M.; Capoccia, C.; Cecchetti, A.; Chatterjee, A.; Chauveau, J.; Chepurnov, A.; Chernyavskiy, M.; Ciambrone, P.; Cicalo, C.; Conti, G.; Cornelis, K.; Courthold, M.; Dallavalle, M.G.; D'Ambrosio, N.; De Lellis, G.; De Serio, M.; Dedenko, L.; Di Crescenzo, A.; Di Marco, N.; Dib, C.; Dietrich, J.; Dijkstra, H.; Domenici, D.; Donskov, S.; Druzhkin, D.; Ebert, J.; Egede, U.; Egorov, A.; Egorychev, V.; Alaoui, M. A. El; Enik, T.; Etenko, A.; Fabbri, F.; Fabbri, L.; Fedorova, G.; Felici, G.; Ferro-Luzzi, M.; Fini, R.A.; Franke, M.; Fraser, M.; Galati, G.; Giacobbe, B.; Goddard, B.; Golinka-Bezshyyko, L.; Golubkov, D.; Golutvin, A.; Gorbunov, D.; Graverini, E.; Grenard, J-L; Guler, A.M.; Hagner, C.; Hakobyan, H.; Helo, J.C.; van Herwijnen, E.; Horvath, D.; Iacovacci, M.; Iaselli, G.; Jacobsson, R.; Kadenko, I.; Kamiscioglu, M.; Kamiscioglu, C.; Khaustov, G.; Khotjansev, A.; Kilminster, B.; Kim, V.; Kitagawa, N.; Kodama, K.; Kolesnikov, A.; Kolev, D.; Komatsu, M.; Konovalova, N.; Koretskiy, S.; Korolko, I.; Korzenev, A.; Kovalenko, S.; Kudenko, Y.; Kuznetsova, E.; Lacker, H.; Lai, A.; Lanfranchi, G.; Lauria, A.; Lebbolo, H.; Levy, J. -M.; Lista, L.; Loverre, P.; Lukiashin, A.; Lyubovitskij, V.E.; Malinin, A.; Manfredi, M.; Perillo-Marcone, A.; Marrone, A.; Matev, R.; Messomo, E.N.; Mermod, P.; Mikado, S.; Mikhaylov, Yu.; Miller, J.; Milstead, D.; Mineev, O.; Mingazheva, R.; Mitselmakher, G.; Miyanishi, M.; Monacelli, P.; Montanari, A.; Montesi, M.C.; Morello, G.; Morishima, K.; Movtchan, S.; Murzin, V.; Naganawa, N.; Naka, T.; Nakamura, M.; Nakano, T.; Nurakhov, N.; Obinyakov, B.; Ocalan, K.; Ogawa, S.; Oreshkin, V.; Orlov, A.; Osborne, J.; Pacholek, P.; Panman, J.; Paoloni, A.; Paparella, L.; Pastore, A.; Patel, M.; Petridis, K.; Petrushin, M.; Poli-Lener, M.; Polukhina, N.; Polyakov, V.; Prokudin, M.; Puddu, G.; Pupilli, F.; Rademakers, F.; Rakai, A.; Rawlings, T.; Redi, F.; Ricciardi, S.; Rinaldesi, R.; Roganova, T.; Rogozhnikov, A.; Rokujo, H.; Romaniouk, A.; Rosa, G.; Rostovtseva, I.; Rovelli, T.; Ruchayskiy, O.; Ruf, T.; Saitta, G.; Samoylenko, V.; Samsonov, V.; Ull, A. Sanz; Saputi, A.; Sato, O.; Schmidt-Parzefall, W.; Serra, N.; Sgobba, S.; Shaposhnikov, M.; Shatalov, P.; Shaykhiev, A.; Shchutska, L.; Shevchenko, V.; Shibuya, H.; Shitov, Y.; Silverstein, S.; Simone, S.; Skorokhvatov, M.; Smirnov, S.; Solodko, E.; Sosnovtsev, V.; Spighi, R.; Spinetti, M.; Starkov, N.; Storaci, B.; Strabel, C.; Strolin, P.; Takahashi, S.; Teterin, P.; Tioukov, V.; Tommasini, D.; Treille, D.; Tsenov, R.; Tshchedrina, T.; Ustyuzhanin, A.; Vannucci, F.; Venturi, V.; Villa, M.; Vincke, Heinz; Vincke, Helmut; Vladymyrov, M.; Xella, S.; Yalvac, M.; Yershov, N.; Yilmaz, D.; Yilmazer, A.U.; Vankova-Kirilova, G.; Zaitsev, Y.; Zoccoli, A.; CERN. Geneva. SPS and PS Experiments Committee; SPSC
2015-01-01
A new general purpose fixed target facility is proposed at the CERN SPS accelerator which is aimed at exploring the domain of hidden particles and make measurements with tau neutrinos. Hidden particles are predicted by a large number of models beyond the Standard Model. The high intensity of the SPS 400~GeV beam allows probing a wide variety of models containing light long-lived exotic particles with masses below ${\\cal O}$(10)~GeV/c$^2$, including very weakly interacting low-energy SUSY states. The experimental programme of the proposed facility is capable of being extended in the future, e.g. to include direct searches for Dark Matter and Lepton Flavour Violation. The facility will be serviced by a new dedicated beam line branched off the splitter section on the North Area. It is followed by a new target station and a magnetic shield to suppress beam induced background. The proposed orientation of the beam line and the underground complex allows reserving more than 100~m of space beyond the experiment...
Spatial Region Estimation for Autonomous CoT Clustering Using Hidden Markov Model
Directory of Open Access Journals (Sweden)
Joon‐young Jung
2018-02-01
Full Text Available This paper proposes a hierarchical dual filtering (HDF algorithm to estimate the spatial region between a Cloud of Things (CoT gateway and an Internet of Things (IoT device. The accuracy of the spatial region estimation is important for autonomous CoT clustering. We conduct spatial region estimation using a hidden Markov model (HMM with a raw Bluetooth received signal strength indicator (RSSI. However, the accuracy of the region estimation using the validation data is only 53.8%. To increase the accuracy of the spatial region estimation, the HDF algorithm removes the high‐frequency signals hierarchically, and alters the parameters according to whether the IoT device moves. The accuracy of spatial region estimation using a raw RSSI, Kalman filter, and HDF are compared to evaluate the effectiveness of the HDF algorithm. The success rate and root mean square error (RMSE of all regions are 0.538, 0.622, and 0.75, and 0.997, 0.812, and 0.5 when raw RSSI, a Kalman filter, and HDF are used, respectively. The HDF algorithm attains the best results in terms of the success rate and RMSE of spatial region estimation using HMM.
Optimization of line configuration and balancing for flexible machining lines
Liu, Xuemei; Li, Aiping; Chen, Zurui
2016-05-01
Line configuration and balancing is to select the type of line and allot a given set of operations as well as machines to a sequence of workstations to realize high-efficiency production. Most of the current researches for machining line configuration and balancing problems are related to dedicated transfer lines with dedicated machine workstations. With growing trends towards great product variety and fluctuations in market demand, dedicated transfer lines are being replaced with flexible machining line composed of identical CNC machines. This paper deals with the line configuration and balancing problem for flexible machining lines. The objective is to assign operations to workstations and find the sequence of execution, specify the number of machines in each workstation while minimizing the line cycle time and total number of machines. This problem is subject to precedence, clustering, accessibility and capacity constraints among the features, operations, setups and workstations. The mathematical model and heuristic algorithm based on feature group strategy and polychromatic sets theory are presented to find an optimal solution. The feature group strategy and polychromatic sets theory are used to establish constraint model. A heuristic operations sequencing and assignment algorithm is given. An industrial case study is carried out, and multiple optimal solutions in different line configurations are obtained. The case studying results show that the solutions with shorter cycle time and higher line balancing rate demonstrate the feasibility and effectiveness of the proposed algorithm. This research proposes a heuristic line configuration and balancing algorithm based on feature group strategy and polychromatic sets theory which is able to provide better solutions while achieving an improvement in computing time.
New algorithms for parallel MRI
International Nuclear Information System (INIS)
Anzengruber, S; Ramlau, R; Bauer, F; Leitao, A
2008-01-01
Magnetic Resonance Imaging with parallel data acquisition requires algorithms for reconstructing the patient's image from a small number of measured lines of the Fourier domain (k-space). In contrast to well-known algorithms like SENSE and GRAPPA and its flavors we consider the problem as a non-linear inverse problem. However, in order to avoid cost intensive derivatives we will use Landweber-Kaczmarz iteration and in order to improve the overall results some additional sparsity constraints.
A hidden Ising model for ChIP-chip data analysis
Mo, Q.
2010-01-28
Motivation: Chromatin immunoprecipitation (ChIP) coupled with tiling microarray (chip) experiments have been used in a wide range of biological studies such as identification of transcription factor binding sites and investigation of DNA methylation and histone modification. Hidden Markov models are widely used to model the spatial dependency of ChIP-chip data. However, parameter estimation for these models is typically either heuristic or suboptimal, leading to inconsistencies in their applications. To overcome this limitation and to develop an efficient software, we propose a hidden ferromagnetic Ising model for ChIP-chip data analysis. Results: We have developed a simple, but powerful Bayesian hierarchical model for ChIP-chip data via a hidden Ising model. Metropolis within Gibbs sampling algorithm is used to simulate from the posterior distribution of the model parameters. The proposed model naturally incorporates the spatial dependency of the data, and can be used to analyze data with various genomic resolutions and sample sizes. We illustrate the method using three publicly available datasets and various simulated datasets, and compare it with three closely related methods, namely TileMap HMM, tileHMM and BAC. We find that our method performs as well as TileMap HMM and BAC for the high-resolution data from Affymetrix platform, but significantly outperforms the other three methods for the low-resolution data from Agilent platform. Compared with the BAC method which also involves MCMC simulations, our method is computationally much more efficient. Availability: A software called iChip is freely available at http://www.bioconductor.org/. Contact: moq@mskcc.org. © The Author 2010. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org.
Directory of Open Access Journals (Sweden)
Xiao-zheng Du
2016-01-01
Full Text Available Data mining has the potential to provide information for improving clinical acupuncture strategies by uncovering hidden rules between acupuncture manipulation and therapeutic effects in a data set. In this study, we performed acupuncture on 30 patients with hemiplegia due to acute ischemic stroke. All participants were pre-screened to ensure that they exhibited immediate responses to acupuncture. We used a twirling reinforcing acupuncture manipulation at the specific lines between the bilateral Baihui (GV20 and Taiyang (EX-HN5. We collected neurologic deficit score, simplified Fugl-Meyer assessment score, muscle strength of the proximal and distal hemiplegic limbs, ratio of the maximal H-reflex to the maximal M-wave (H max /M max , muscle tension at baseline and immediately after treatment, and the syndromes of traditional Chinese medicine at baseline. We then conducted data mining using an association algorithm and an artificial neural network backpropagation algorithm. We found that the twirling reinforcing manipulation had no obvious therapeutic difference in traditional Chinese medicine syndromes of "Deficiency and Excess". The change in the muscle strength of the upper distal and lower proximal limbs was one of the main factors affecting the immediate change in Fugl-Meyer scores. Additionally, we found a positive correlation between the muscle tension change of the upper limb and H max /M max immediate change, and both positive and negative correlations existed between the muscle tension change of the lower limb and immediate H max /M max change. Additionally, when the difference value of muscle tension for the upper and lower limbs was > 0 or < 0, the difference value of H max /M max was correspondingly positive or negative, indicating the scalp acupuncture has a bidirectional effect on muscle tension in hemiplegic limbs. Therefore, acupuncture with twirling reinforcing manipulation has distinct effects on acute ischemic stroke patients
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
An Efficient Hierarchy Algorithm for Community Detection in Complex Networks
Directory of Open Access Journals (Sweden)
Lili Zhang
2014-01-01
Full Text Available Community structure is one of the most fundamental and important topology characteristics of complex networks. The research on community structure has wide applications and is very important for analyzing the topology structure, understanding the functions, finding the hidden properties, and forecasting the time-varying of the networks. This paper analyzes some related algorithms and proposes a new algorithm—CN agglomerative algorithm based on graph theory and the local connectedness of network to find communities in network. We show this algorithm is distributed and polynomial; meanwhile the simulations show it is accurate and fine-grained. Furthermore, we modify this algorithm to get one modified CN algorithm and apply it to dynamic complex networks, and the simulations also verify that the modified CN algorithm has high accuracy too.
Unsupervised Learning Through Randomized Algorithms for High-Volume High-Velocity Data (ULTRA-HV).
Energy Technology Data Exchange (ETDEWEB)
Pinar, Ali [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Kolda, Tamara G. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Carlberg, Kevin Thomas [Wake Forest Univ., Winston-Salem, MA (United States); Ballard, Grey [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Mahoney, Michael [Univ. of California, Berkeley, CA (United States)
2018-01-01
Through long-term investments in computing, algorithms, facilities, and instrumentation, DOE is an established leader in massive-scale, high-fidelity simulations, as well as science-leading experimentation. In both cases, DOE is generating more data than it can analyze and the problem is intensifying quickly. The need for advanced algorithms that can automatically convert the abundance of data into a wealth of useful information by discovering hidden structures is well recognized. Such efforts however, are hindered by the massive volume of the data and its high velocity. Here, the challenge is developing unsupervised learning methods to discover hidden structure in high-volume, high-velocity data.
Fuzzy hidden Markov chains segmentation for volume determination and quantitation in PET
Energy Technology Data Exchange (ETDEWEB)
Hatt, M [INSERM U650, Laboratoire du Traitement de l' Information Medicale (LaTIM), CHU Morvan, Bat 2bis (I3S), 5 avenue Foch, Brest, 29609 (France); Lamare, F [INSERM U650, Laboratoire du Traitement de l' Information Medicale (LaTIM), CHU Morvan, Bat 2bis (I3S), 5 avenue Foch, Brest, 29609, (France); Boussion, N [INSERM U650, Laboratoire du Traitement de l' Information Medicale (LaTIM), CHU Morvan, Bat 2bis (I3S), 5 avenue Foch, Brest, 29609 (France); Turzo, A [INSERM U650, Laboratoire du Traitement de l' Information Medicale (LaTIM), CHU Morvan, Bat 2bis (I3S), 5 avenue Foch, Brest, 29609 (France); Collet, C [Ecole Nationale Superieure de Physique de Strasbourg (ENSPS), ULP, Strasbourg, F-67000 (France); Salzenstein, F [Institut d' Electronique du Solide et des Systemes (InESS), ULP, Strasbourg, F-67000 (France); Roux, C [INSERM U650, Laboratoire du Traitement de l' Information Medicale (LaTIM), CHU Morvan, Bat 2bis (I3S), 5 avenue Foch, Brest, 29609 (France); Jarritt, P [Medical Physics Agency, Royal Victoria Hospital, Belfast (United Kingdom); Carson, K [Medical Physics Agency, Royal Victoria Hospital, Belfast (United Kingdom); Rest, C Cheze-Le [INSERM U650, Laboratoire du Traitement de l' Information Medicale (LaTIM), CHU Morvan, Bat 2bis (I3S), 5 avenue Foch, Brest, 29609 (France); Visvikis, D [INSERM U650, Laboratoire du Traitement de l' Information Medicale (LaTIM), CHU Morvan, Bat 2bis (I3S), 5 avenue Foch, Brest, 29609 (France)
2007-07-21
Accurate volume of interest (VOI) estimation in PET is crucial in different oncology applications such as response to therapy evaluation and radiotherapy treatment planning. The objective of our study was to evaluate the performance of the proposed algorithm for automatic lesion volume delineation; namely the fuzzy hidden Markov chains (FHMC), with that of current state of the art in clinical practice threshold based techniques. As the classical hidden Markov chain (HMC) algorithm, FHMC takes into account noise, voxel intensity and spatial correlation, in order to classify a voxel as background or functional VOI. However the novelty of the fuzzy model consists of the inclusion of an estimation of imprecision, which should subsequently lead to a better modelling of the 'fuzzy' nature of the object of interest boundaries in emission tomography data. The performance of the algorithms has been assessed on both simulated and acquired datasets of the IEC phantom, covering a large range of spherical lesion sizes (from 10 to 37 mm), contrast ratios (4:1 and 8:1) and image noise levels. Both lesion activity recovery and VOI determination tasks were assessed in reconstructed images using two different voxel sizes (8 mm{sup 3} and 64 mm{sup 3}). In order to account for both the functional volume location and its size, the concept of % classification errors was introduced in the evaluation of volume segmentation using the simulated datasets. Results reveal that FHMC performs substantially better than the threshold based methodology for functional volume determination or activity concentration recovery considering a contrast ratio of 4:1 and lesion sizes of <28 mm. Furthermore differences between classification and volume estimation errors evaluated were smaller for the segmented volumes provided by the FHMC algorithm. Finally, the performance of the automatic algorithms was less susceptible to image noise levels in comparison to the threshold based techniques. The
Hidden burden of malaria in Indian women
Directory of Open Access Journals (Sweden)
Sharma Vinod P
2009-12-01
Full Text Available Abstract Malaria is endemic in India with an estimated 70-100 million cases each year (1.6-1.8 million reported by NVBDCP; of this 50-55% are Plasmodium vivax and 45-50% Plasmodium falciparum. A recent study on malaria in pregnancy reported from undivided Madhya Pradesh state (includes Chhattisgarh state, that an estimated over 220,000 pregnant women contract malaria infection each year. Malaria in pregnancy caused- abortions 34.5%; stillbirths 9%; and maternal deaths 0.45%. Bulk of this tragic outcome can be averted by following the Roll Back Malaria/WHO recommendations of the use of malaria prevention i.e. indoor residual spraying (IRS/insecticide-treated bed nets (ITN preferably long-lasting treated bed nets (LLIN; intermittent preventive therapy (IPT; early diagnosis, prompt and complete treatment using microscopic/malaria rapid diagnostics test (RDT and case management. High incidence in pregnancy has arisen because of malaria surveillance lacking coverage, lack of age and sex wise data, staff shortages, and intermittent preventive treatment (IPT applicable in high transmission states/pockets is not included in the national drug policy- an essential component of fighting malaria in pregnancy in African settings. Inadequate surveillance and gross under-reporting has been highlighted time and again for over three decades. As a result the huge problem of malaria in pregnancy reported occasionally by researchers has remained hidden. Malaria in pregnancy may quicken severity in patients with drug resistant parasites, anaemia, endemic poverty, and malnutrition. There is, therefore, urgent need to streamline malaria control strategies to make a difference in tackling this grim scenario in human health.
Hydrogeophysical investigations at Hidden Dam, Raymond, California
Minsley, Burke J.; Burton, Bethany L.; Ikard, Scott; Powers, Michael H.
2011-01-01
Self-potential and direct current resistivity surveys are carried out at the Hidden Dam site in Raymond, California to assess present-day seepage patterns and better understand the hydrogeologic mechanisms that likely influence seepage. Numerical modeling is utilized in conjunction with the geophysical measurements to predict variably-saturated flow through typical two-dimensional dam cross-sections as a function of reservoir elevation. Several different flow scenarios are investigated based on the known hydrogeology, as well as information about typical subsurface structures gained from the resistivity survey. The flow models are also used to simulate the bulk electrical resistivity in the subsurface under varying saturation conditions, as well as the self-potential response using petrophysical relationships and electrokinetic coupling equations.The self-potential survey consists of 512 measurements on the downstream area of the dam, and corroborates known seepage areas on the northwest side of the dam. Two direct-current resistivity profiles, each approximately 2,500 ft (762 m) long, indicate a broad sediment channel under the northwest side of the dam, which may be a significant seepage pathway through the foundation. A focusing of seepage in low-topography areas downstream of the dam is confirmed from the numerical flow simulations, which is also consistent with past observations. Little evidence of seepage is identified from the self-potential data on the southeast side of the dam, also consistent with historical records, though one possible area of focused seepage is identified near the outlet works. Integration of the geophysical surveys, numerical modeling, and observation well data provides a framework for better understanding seepage at the site through a combined hydrogeophysical approach.
'Hidden messages' emerging from Afrocentric management perspectives
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H. Van den Heuvel
2008-12-01
Full Text Available Purpose: This paper aims to examine how 'African management' discourse has emerged in South Africa. Altogether, it has stimulated debates - sometimes in controversial ways - on 'taboo issues', e.g. relating to 'cultural diversity' and 'ethnicity'. The stimulation of such debates within organisations is probably a more valuable contribution than a static, essentialised 'African identity' that it proclaims. Design/Methodology/Approach: The paper draws on a qualitative research project conducted in South Africa in 2003-2004. Its relevance lies in gaining in-depth insights into ('non-western' local management discourse. It seeks to contribute to the body of knowledge on political and cultural contexts in which South African organizations operate, and how they impact on local management perspectives, and vice versa. Findings: The research findings make clear how and under what circumstances 'African management' discourse has come about in South Africa, and how it could be interpreted. Implications: 'African management' advocates allegedly attempt to revise dominant management thinking and promote 'humane-ness' and participatory decision-making in South African organisations, in search of a contextualised management approach. Amongst others, it has produced new meanings of 'Africanness' and has opened up space for 'hidden messages', resentments and aspirations to become openly articulated. This throws another light on phenomena such as cultural diversity and ethnicity that usually tend to be 'neutralised'. This may turn out to be far healthier for blooming organisational cultures in South Africa than relentlessly hammering on prescribed 'corporate values'. Originality/Value: This paper informs the reader in detail about the emergence and evolvement of 'African management' discourse in South Africa. It is a unique attempt to develop an interpretative viewpoint on this intriguing phenomenon that offers a potentially valuable contribution in reading
Identifying hidden voice and video streams
Fan, Jieyan; Wu, Dapeng; Nucci, Antonio; Keralapura, Ram; Gao, Lixin
2009-04-01
Given the rising popularity of voice and video services over the Internet, accurately identifying voice and video traffic that traverse their networks has become a critical task for Internet service providers (ISPs). As the number of proprietary applications that deliver voice and video services to end users increases over time, the search for the one methodology that can accurately detect such services while being application independent still remains open. This problem becomes even more complicated when voice and video service providers like Skype, Microsoft, and Google bundle their voice and video services with other services like file transfer and chat. For example, a bundled Skype session can contain both voice stream and file transfer stream in the same layer-3/layer-4 flow. In this context, traditional techniques to identify voice and video streams do not work. In this paper, we propose a novel self-learning classifier, called VVS-I , that detects the presence of voice and video streams in flows with minimum manual intervention. Our classifier works in two phases: training phase and detection phase. In the training phase, VVS-I first extracts the relevant features, and subsequently constructs a fingerprint of a flow using the power spectral density (PSD) analysis. In the detection phase, it compares the fingerprint of a flow to the existing fingerprints learned during the training phase, and subsequently classifies the flow. Our classifier is not only capable of detecting voice and video streams that are hidden in different flows, but is also capable of detecting different applications (like Skype, MSN, etc.) that generate these voice/video streams. We show that our classifier can achieve close to 100% detection rate while keeping the false positive rate to less that 1%.
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.
Big data algorithms, analytics, and applications
Li, Kuan-Ching; Yang, Laurence T; Cuzzocrea, Alfredo
2015-01-01
Data are generated at an exponential rate all over the world. Through advanced algorithms and analytics techniques, organizations can harness this data, discover hidden patterns, and use the findings to make meaningful decisions. Containing contributions from leading experts in their respective fields, this book bridges the gap between the vastness of big data and the appropriate computational methods for scientific and social discovery. It also explores related applications in diverse sectors, covering technologies for media/data communication, elastic media/data storage, cross-network media/
Directory of Open Access Journals (Sweden)
OMER MAHMOUD
2007-08-01
Full Text Available One of the essential factors that affect the performance of Artificial Neural Networks is the learning algorithm. The performance of Multilayer Feed Forward Artificial Neural Network performance in image compression using different learning algorithms is examined in this paper. Based on Gradient Descent, Conjugate Gradient, Quasi-Newton techniques three different error back propagation algorithms have been developed for use in training two types of neural networks, a single hidden layer network and three hidden layers network. The essence of this study is to investigate the most efficient and effective training methods for use in image compression and its subsequent applications. The obtained results show that the Quasi-Newton based algorithm has better performance as compared to the other two algorithms.
Infinite hidden conditional random fields for human behavior analysis.
Bousmalis, Konstantinos; Zafeiriou, Stefanos; Morency, Louis-Philippe; Pantic, Maja
2013-01-01
Hidden conditional random fields (HCRFs) are discriminative latent variable models that have been shown to successfully learn the hidden structure of a given classification problem (provided an appropriate validation of the number of hidden states). In this brief, we present the infinite HCRF (iHCRF), which is a nonparametric model based on hierarchical Dirichlet processes and is capable of automatically learning the optimal number of hidden states for a classification task. We show how we learn the model hyperparameters with an effective Markov-chain Monte Carlo sampling technique, and we explain the process that underlines our iHCRF model with the Restaurant Franchise Rating Agencies analogy. We show that the iHCRF is able to converge to a correct number of represented hidden states, and outperforms the best finite HCRFs--chosen via cross-validation--for the difficult tasks of recognizing instances of agreement, disagreement, and pain. Moreover, the iHCRF manages to achieve this performance in significantly less total training, validation, and testing time.
Yang, Sejung; Lee, Byung-Uk
2015-01-01
In certain image acquisitions processes, like in fluorescence microscopy or astronomy, only a limited number of photons can be collected due to various physical constraints. The resulting images suffer from signal dependent noise, which can be modeled as a Poisson distribution, and a low signal-to-noise ratio. However, the majority of research on noise reduction algorithms focuses on signal independent Gaussian noise. In this paper, we model noise as a combination of Poisson and Gaussian probability distributions to construct a more accurate model and adopt the contourlet transform which provides a sparse representation of the directional components in images. We also apply hidden Markov models with a framework that neatly describes the spatial and interscale dependencies which are the properties of transformation coefficients of natural images. In this paper, an effective denoising algorithm for Poisson-Gaussian noise is proposed using the contourlet transform, hidden Markov models and noise estimation in the transform domain. We supplement the algorithm by cycle spinning and Wiener filtering for further improvements. We finally show experimental results with simulations and fluorescence microscopy images which demonstrate the improved performance of the proposed approach. PMID:26352138
A fast and accurate online sequential learning algorithm for feedforward networks.
Liang, Nan-Ying; Huang, Guang-Bin; Saratchandran, P; Sundararajan, N
2006-11-01
In this paper, we develop an online sequential learning algorithm for single hidden layer feedforward networks (SLFNs) with additive or radial basis function (RBF) hidden nodes in a unified framework. The algorithm is referred to as online sequential extreme learning machine (OS-ELM) and can learn data one-by-one or chunk-by-chunk (a block of data) with fixed or varying chunk size. The activation functions for additive nodes in OS-ELM can be any bounded nonconstant piecewise continuous functions and the activation functions for RBF nodes can be any integrable piecewise continuous functions. In OS-ELM, the parameters of hidden nodes (the input weights and biases of additive nodes or the centers and impact factors of RBF nodes) are randomly selected and the output weights are analytically determined based on the sequentially arriving data. The algorithm uses the ideas of ELM of Huang et al. developed for batch learning which has been shown to be extremely fast with generalization performance better than other batch training methods. Apart from selecting the number of hidden nodes, no other control parameters have to be manually chosen. Detailed performance comparison of OS-ELM is done with other popular sequential learning algorithms on benchmark problems drawn from the regression, classification and time series prediction areas. The results show that the OS-ELM is faster than the other sequential algorithms and produces better generalization performance.
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....
Hidden beauty baryon states in the local hidden gauge approach with heavy quark spin symmetry
Energy Technology Data Exchange (ETDEWEB)
Xiao, C.W.; Oset, E. [Centro Mixto Universidad de Valencia-CSIC, Institutos de Investigacion de Paterna, Departamento de Fisica Teorica and IFIC, Valencia (Spain)
2013-11-15
Using a coupled-channel unitary approach, combining the heavy quark spin symmetry and the dynamics of the local hidden gauge, we investigate the meson-baryon interaction with hidden beauty and obtain several new states of N around 11 GeV. We consider the basis of states {eta}{sub b} N, {Upsilon};N, B {Lambda}{sub b}, B {Sigma}{sub b}, B{sup *}{Lambda}{sub b}, B{sup *}{Sigma}{sub b}, B{sup *}{Sigma}{sub b}{sup *} and find four basic bound states which correspond to B {Sigma}{sub b}, B {Sigma}{sub b}{sup *}, B{sup *}{Sigma}{sub b} and B{sup *}{Sigma}{sub b}{sup *}, decaying mostly into {eta}{sub b} N and {Upsilon}N and with a binding energy about 50-130 MeV with respect to the thresholds of the corresponding channel. All of them have isospin I = 1/2, and we find no bound states or resonances in I = 3/2. The B {Sigma}{sub b} state appears in J = 1/2, the B {Sigma}{sub b}{sup *} in J = 3/2, the B{sup *}{Sigma}{sub b} appears nearly degenerate in J = 1/2, 3/2 and the B{sup *}{Sigma}{sub b}{sup *} appears nearly degenerate in J = 1/2, 3/2, 5/2. These states have a width from 2-110 MeV, with conservative estimates of uncertainties, except for the one in J = 5/2 which has zero width since it cannot decay into any of the states of the basis chosen. We make generous estimates of the uncertainties and find that within very large margins these states appear bound. (orig.)
A Self-Adaptive Hidden Markov Model for Emotion Classification in Chinese Microblogs
Directory of Open Access Journals (Sweden)
Li Liu
2015-01-01
we propose a modified version of hidden Markov model (HMM classifier, called self-adaptive HMM, whose parameters are optimized by Particle Swarm Optimization algorithms. Since manually labeling large-scale dataset is difficult, we also employ the entropy to decide whether a new unlabeled tweet shall be contained in the training dataset after being assigned an emotion using our HMM-based approach. In the experiment, we collected about 200,000 Chinese tweets from Sina Weibo. The results show that the F-score of our approach gets 76% on happiness and fear and 65% on anger, surprise, and sadness. In addition, the self-adaptive HMM classifier outperforms Naive Bayes and Support Vector Machine on recognition of happiness, anger, and sadness.
Non-intrusive gesture recognition system combining with face detection based on Hidden Markov Model
Jin, Jing; Wang, Yuanqing; Xu, Liujing; Cao, Liqun; Han, Lei; Zhou, Biye; Li, Minggao
2014-11-01
A non-intrusive gesture recognition human-machine interaction system is proposed in this paper. In order to solve the hand positioning problem which is a difficulty in current algorithms, face detection is used for the pre-processing to narrow the search area and find user's hand quickly and accurately. Hidden Markov Model (HMM) is used for gesture recognition. A certain number of basic gesture units are trained as HMM models. At the same time, an improved 8-direction feature vector is proposed and used to quantify characteristics in order to improve the detection accuracy. The proposed system can be applied in interaction equipments without special training for users, such as household interactive television
A Coupled Hidden Markov Random Field Model for Simultaneous Face Clustering and Tracking in Videos
Wu, Baoyuan
2016-10-25
Face clustering and face tracking are two areas of active research in automatic facial video processing. They, however, have long been studied separately, despite the inherent link between them. In this paper, we propose to perform simultaneous face clustering and face tracking from real world videos. The motivation for the proposed research is that face clustering and face tracking can provide useful information and constraints to each other, thus can bootstrap and improve the performances of each other. To this end, we introduce a Coupled Hidden Markov Random Field (CHMRF) to simultaneously model face clustering, face tracking, and their interactions. We provide an effective algorithm based on constrained clustering and optimal tracking for the joint optimization of cluster labels and face tracking. We demonstrate significant improvements over state-of-the-art results in face clustering and tracking on several videos.
A Method for Driving Route Predictions Based on Hidden Markov Model
Directory of Open Access Journals (Sweden)
Ning Ye
2015-01-01
Full Text Available We present a driving route prediction method that is based on Hidden Markov Model (HMM. This method can accurately predict a vehicle’s entire route as early in a trip’s lifetime as possible without inputting origins and destinations beforehand. Firstly, we propose the route recommendation system architecture, where route predictions play important role in the system. Secondly, we define a road network model, normalize each of driving routes in the rectangular coordinate system, and build the HMM to make preparation for route predictions using a method of training set extension based on K-means++ and the add-one (Laplace smoothing technique. Thirdly, we present the route prediction algorithm. Finally, the experimental results of the effectiveness of the route predictions that is based on HMM are shown.
Krauter, Johann; Osten, Wolfgang
2018-03-01
There are a wide range of applications for micro-electro-mechanical systems (MEMS). The automotive and consumer market is the strongest driver for the growing MEMS industry. A 100 % test of MEMS is particularly necessary since these are often used for safety-related purposes such as the ESP (Electronic Stability Program) system. The production of MEMS is a fully automated process that generates 90 % of the costs during the packaging and dicing steps. Nowadays, an electrical test is carried out on each individual MEMS component before these steps. However, after encapsulation, MEMS are opaque to visible light and other defects cannot be detected. Therefore, we apply an infrared low-coherence interferometer for the topography measurement of those hidden structures. A lock-in algorithm-based method is shown to calculate the object height and to reduce ghost steps due to the 2π -unambiguity. Finally, measurements of different MEMS-based sensors are presented.
Naive scoring of human sleep based on a hidden Markov model of the electroencephalogram.
Yaghouby, Farid; Modur, Pradeep; Sunderam, Sridhar
2014-01-01
Clinical sleep scoring involves tedious visual review of overnight polysomnograms by a human expert. Many attempts have been made to automate the process by training computer algorithms such as support vector machines and hidden Markov models (HMMs) to replicate human scoring. Such supervised classifiers are typically trained on scored data and then validated on scored out-of-sample data. Here we describe a methodology based on HMMs for scoring an overnight sleep recording without the benefit of a trained initial model. The number of states in the data is not known a priori and is optimized using a Bayes information criterion. When tested on a 22-subject database, this unsupervised classifier agreed well with human scores (mean of Cohen's kappa > 0.7). The HMM also outperformed other unsupervised classifiers (Gaussian mixture models, k-means, and linkage trees), that are capable of naive classification but do not model dynamics, by a significant margin (p < 0.05).
Bi-dimension decomposed hidden Markov models for multi-person activity recognition
Institute of Scientific and Technical Information of China (English)
Wei-dong ZHANG; Feng CHEN; Wen-li XU
2009-01-01
We present a novel model for recognizing long-term complex activities involving multiple persons. The proposed model, named 'decomposed hidden Markov model' (DHMM), combines spatial decomposition and hierarchical abstraction to capture multi-modal, long-term dependent and multi-scale characteristics of activities. Decomposition in space and time offers conceptual advantages of compaction and clarity, and greatly reduces the size of state space as well as the number of parameters.DHMMs are efficient even when the number of persons is variable. We also introduce an efficient approximation algorithm for inference and parameter estimation. Experiments on multi-person activities and multi-modal individual activities demonstrate that DHMMs are more efficient and reliable than familiar models, such as coupled HMMs, hierarchical HMMs, and multi-observation HMMs.
Sebastian, Tunny; Jeyaseelan, Visalakshi; Jeyaseelan, Lakshmanan; Anandan, Shalini; George, Sebastian; Bangdiwala, Shrikant I
2018-01-01
Hidden Markov models are stochastic models in which the observations are assumed to follow a mixture distribution, but the parameters of the components are governed by a Markov chain which is unobservable. The issues related to the estimation of Poisson-hidden Markov models in which the observations are coming from mixture of Poisson distributions and the parameters of the component Poisson distributions are governed by an m-state Markov chain with an unknown transition probability matrix are explained here. These methods were applied to the data on Vibrio cholerae counts reported every month for 11-year span at Christian Medical College, Vellore, India. Using Viterbi algorithm, the best estimate of the state sequence was obtained and hence the transition probability matrix. The mean passage time between the states were estimated. The 95% confidence interval for the mean passage time was estimated via Monte Carlo simulation. The three hidden states of the estimated Markov chain are labelled as 'Low', 'Moderate' and 'High' with the mean counts of 1.4, 6.6 and 20.2 and the estimated average duration of stay of 3, 3 and 4 months, respectively. Environmental risk factors were studied using Markov ordinal logistic regression analysis. No significant association was found between disease severity levels and climate components.
Benoit, Julia S; Chan, Wenyaw; Luo, Sheng; Yeh, Hung-Wen; Doody, Rachelle
2016-04-30
Understanding the dynamic disease process is vital in early detection, diagnosis, and measuring progression. Continuous-time Markov chain (CTMC) methods have been used to estimate state-change intensities but challenges arise when stages are potentially misclassified. We present an analytical likelihood approach where the hidden state is modeled as a three-state CTMC model allowing for some observed states to be possibly misclassified. Covariate effects of the hidden process and misclassification probabilities of the hidden state are estimated without information from a 'gold standard' as comparison. Parameter estimates are obtained using a modified expectation-maximization (EM) algorithm, and identifiability of CTMC estimation is addressed. Simulation studies and an application studying Alzheimer's disease caregiver stress-levels are presented. The method was highly sensitive to detecting true misclassification and did not falsely identify error in the absence of misclassification. In conclusion, we have developed a robust longitudinal method for analyzing categorical outcome data when classification of disease severity stage is uncertain and the purpose is to study the process' transition behavior without a gold standard. Copyright © 2016 John Wiley & Sons, Ltd.
The Applications of Genetic Algorithms in Medicine
Directory of Open Access Journals (Sweden)
Ali Ghaheri
2015-11-01
Full Text Available A great wealth of information is hidden amid medical research data that in some cases cannot be easily analyzed, if at all, using classical statistical methods. Inspired by nature, metaheuristic algorithms have been developed to offer optimal or near-optimal solutions to complex data analysis and decision-making tasks in a reasonable time. Due to their powerful features, metaheuristic algorithms have frequently been used in other fields of sciences. In medicine, however, the use of these algorithms are not known by physicians who may well benefit by applying them to solve complex medical problems. Therefore, in this paper, we introduce the genetic algorithm and its applications in medicine. The use of the genetic algorithm has promising implications in various medical specialties including radiology, radiotherapy, oncology, pediatrics, cardiology, endocrinology, surgery, obstetrics and gynecology, pulmonology, infectious diseases, orthopedics, rehabilitation medicine, neurology, pharmacotherapy, and health care management. This review introduces the applications of the genetic algorithm in disease screening, diagnosis, treatment planning, pharmacovigilance, prognosis, and health care management, and enables physicians to envision possible applications of this metaheuristic method in their medical career.
The Applications of Genetic Algorithms in Medicine.
Ghaheri, Ali; Shoar, Saeed; Naderan, Mohammad; Hoseini, Sayed Shahabuddin
2015-11-01
A great wealth of information is hidden amid medical research data that in some cases cannot be easily analyzed, if at all, using classical statistical methods. Inspired by nature, metaheuristic algorithms have been developed to offer optimal or near-optimal solutions to complex data analysis and decision-making tasks in a reasonable time. Due to their powerful features, metaheuristic algorithms have frequently been used in other fields of sciences. In medicine, however, the use of these algorithms are not known by physicians who may well benefit by applying them to solve complex medical problems. Therefore, in this paper, we introduce the genetic algorithm and its applications in medicine. The use of the genetic algorithm has promising implications in various medical specialties including radiology, radiotherapy, oncology, pediatrics, cardiology, endocrinology, surgery, obstetrics and gynecology, pulmonology, infectious diseases, orthopedics, rehabilitation medicine, neurology, pharmacotherapy, and health care management. This review introduces the applications of the genetic algorithm in disease screening, diagnosis, treatment planning, pharmacovigilance, prognosis, and health care management, and enables physicians to envision possible applications of this metaheuristic method in their medical career.].
Gauge mediation scenario with hidden sector renormalization in MSSM
International Nuclear Information System (INIS)
Arai, Masato; Kawai, Shinsuke; Okada, Nobuchika
2010-01-01
We study the hidden sector effects on the mass renormalization of a simplest gauge-mediated supersymmetry breaking scenario. We point out that possible hidden sector contributions render the soft scalar masses smaller, resulting in drastically different sparticle mass spectrum at low energy. In particular, in the 5+5 minimal gauge-mediated supersymmetry breaking with high messenger scale (that is favored by the gravitino cold dark matter scenario), we show that a stau can be the next lightest superparticle for moderate values of hidden sector self-coupling. This provides a very simple theoretical model of long-lived charged next lightest superparticles, which imply distinctive signals in ongoing and upcoming collider experiments.
Gauge mediation scenario with hidden sector renormalization in MSSM
Arai, Masato; Kawai, Shinsuke; Okada, Nobuchika
2010-02-01
We study the hidden sector effects on the mass renormalization of a simplest gauge-mediated supersymmetry breaking scenario. We point out that possible hidden sector contributions render the soft scalar masses smaller, resulting in drastically different sparticle mass spectrum at low energy. In particular, in the 5+5¯ minimal gauge-mediated supersymmetry breaking with high messenger scale (that is favored by the gravitino cold dark matter scenario), we show that a stau can be the next lightest superparticle for moderate values of hidden sector self-coupling. This provides a very simple theoretical model of long-lived charged next lightest superparticles, which imply distinctive signals in ongoing and upcoming collider experiments.
Multivariate longitudinal data analysis with mixed effects hidden Markov models.
Raffa, Jesse D; Dubin, Joel A
2015-09-01
Multiple longitudinal responses are often collected as a means to capture relevant features of the true outcome of interest, which is often hidden and not directly measurable. We outline an approach which models these multivariate longitudinal responses as generated from a hidden disease process. We propose a class of models which uses a hidden Markov model with separate but correlated random effects between multiple longitudinal responses. This approach was motivated by a smoking cessation clinical trial, where a bivariate longitudinal response involving both a continuous and a binomial response was collected for each participant to monitor smoking behavior. A Bayesian method using Markov chain Monte Carlo is used. Comparison of separate univariate response models to the bivariate response models was undertaken. Our methods are demonstrated on the smoking cessation clinical trial dataset, and properties of our approach are examined through extensive simulation studies. © 2015, The International Biometric Society.
Applications of hidden symmetries to black hole physics
International Nuclear Information System (INIS)
Frolov, Valeri
2011-01-01
This work is a brief review of applications of hidden symmetries to black hole physics. Symmetry is one of the most important concepts of the science. In physics and mathematics the symmetry allows one to simplify a problem, and often to make it solvable. According to the Noether theorem symmetries are responsible for conservation laws. Besides evident (explicit) spacetime symmetries, responsible for conservation of energy, momentum, and angular momentum of a system, there also exist what is called hidden symmetries, which are connected with higher order in momentum integrals of motion. A remarkable fact is that black holes in four and higher dimensions always possess a set ('tower') of explicit and hidden symmetries which make the equations of motion of particles and light completely integrable. The paper gives a general review of the recently obtained results. The main focus is on understanding why at all black holes have something (symmetry) to hide.
Discovering Hidden Controlling Parameters using Data Analytics and Dimensional Analysis
Del Rosario, Zachary; Lee, Minyong; Iaccarino, Gianluca
2017-11-01
Dimensional Analysis is a powerful tool, one which takes a priori information and produces important simplifications. However, if this a priori information - the list of relevant parameters - is missing a relevant quantity, then the conclusions from Dimensional Analysis will be incorrect. In this work, we present novel conclusions in Dimensional Analysis, which provide a means to detect this failure mode of missing or hidden parameters. These results are based on a restated form of the Buckingham Pi theorem that reveals a ridge function structure underlying all dimensionless physical laws. We leverage this structure by constructing a hypothesis test based on sufficient dimension reduction, allowing for an experimental data-driven detection of hidden parameters. Both theory and examples will be presented, using classical turbulent pipe flow as the working example. Keywords: experimental techniques, dimensional analysis, lurking variables, hidden parameters, buckingham pi, data analysis. First author supported by the NSF GRFP under Grant Number DGE-114747.
Supersymmetry, p-brane duality, and hidden spacetime dimensions
International Nuclear Information System (INIS)
Bars, I.
1996-01-01
A global superalgebra with 32 supercharges and all possible central extensions is studied in order to extract some general properties of duality and hidden dimensions in a theory that treats p-branes democratically. The maximal number of dimensions is 12, with signature (10,2), containing one space and one time dimension that are hidden from the point of view of perturbative ten-dimensional string theory or its compactifications. When the theory is compactified on R d-1,1 circle-times T c+1,1 with d+c+2=12, there are isometry groups that relate to the hidden dimensions as well as to duality. Their combined intersecting classification schemes provide some properties of nonperturbative states and their couplings. copyright 1996 The American Physical Society
Analysing the hidden curriculum: use of a cultural web.
Mossop, Liz; Dennick, Reg; Hammond, Richard; Robbé, Iain
2013-02-01
Major influences on learning about medical professionalism come from the hidden curriculum. These influences can contribute positively or negatively towards the professional enculturation of clinical students. The fact that there is no validated method for identifying the components of the hidden curriculum poses problems for educators considering professionalism. The aim of this study was to analyse whether a cultural web, adapted from a business context, might assist in the identification of elements of the hidden curriculum at a UK veterinary school. A qualitative approach was used. Seven focus groups consisting of three staff groups and four student groups were organised. Questioning was framed using the cultural web, which is a model used by business owners to assess their environment and consider how it affects their employees and customers. The focus group discussions were recorded, transcribed and analysed thematically using a combination of a priori and emergent themes. The cultural web identified elements of the hidden curriculum for both students and staff. These included: core assumptions; routines; rituals; control systems; organisational factors; power structures, and symbols. Discussions occurred about how and where these issues may affect students' professional identity development. The cultural web framework functioned well to help participants identify elements of the hidden curriculum. These aspects aligned broadly with previously described factors such as role models and institutional slang. The influence of these issues on a student's development of a professional identity requires discussion amongst faculty staff, and could be used to develop learning opportunities for students. The framework is promising for the analysis of the hidden curriculum and could be developed as an instrument for implementation in other clinical teaching environments. © Blackwell Publishing Ltd 2013.
QCD sum rule study of hidden-charm pentaquarks
Energy Technology Data Exchange (ETDEWEB)
Chen, Hua-Xing; Cui, Er-Liang [Beihang University, School of Physics and Beijing Key Laboratory of Advanced Nuclear Materials and Physics, Beijing (China); Chen, Wei; Steele, T.G. [University of Saskatchewan, Department of Physics and Engineering Physics, Saskatoon, Saskatchewan (Canada); Liu, Xiang [Lanzhou University, School of Physical Science and Technology, Lanzhou (China); Lanzhou University and Institute of Modern Physics of CAS, Research Center for Hadron and CSR Physics, Lanzhou (China); Zhu, Shi-Lin [Peking University, School of Physics and State Key Laboratory of Nuclear Physics and Technology, Beijing (China); Collaborative Innovation Center of Quantum Matter, Beijing (China); Peking University, Center of High Energy Physics, Beijing (China)
2016-10-15
We study the mass spectra of hidden-charm pentaquarks having spin J = (1)/(2)/(3)/(2)/(5)/(2) and quark contents uudc anti c. We systematically construct all the relevant local hidden-charm pentaquark currents, and we select some of them to perform QCD sum rule analyses. We find that the P{sub c}(4380) and P{sub c}(4450) can be identified as hidden-charm pentaquark states composed of an anti-charmed meson and a charmed baryon. Besides them, we also find (a) the lowest-lying hidden-charm pentaquark state of J{sup P} = 1/2{sup -} has the mass 4.33{sup +0.17}{sub -0.13} GeV, while the one of J{sup P} = 1/2{sup +} is significantly higher, that is, around 4.7-4.9 GeV; (b) the lowest-lying hidden-charm pentaquark state of J{sup P} = 3/2{sup -} has the mass 4.37{sup +0.18}{sub -0.13} GeV, consistent with the P{sub c}(4380) of J{sup P} = 3/2{sup -}, while the one of J{sup P} = 3/2{sup +} is also significantly higher, that is, above 4.6 GeV; (c) the hidden-charm pentaquark state of J{sup P} = 5/2{sup -} has a mass around 4.5-4.6 GeV, slightly larger than the P{sub c}(4450) of J{sup P} = 5/2{sup +}. (orig.)
Development of a Fault Monitoring Technique for Wind Turbines Using a Hidden Markov Model.
Shin, Sung-Hwan; Kim, SangRyul; Seo, Yun-Ho
2018-06-02
Regular inspection for the maintenance of the wind turbines is difficult because of their remote locations. For this reason, condition monitoring systems (CMSs) are typically installed to monitor their health condition. The purpose of this study is to propose a fault detection algorithm for the mechanical parts of the wind turbine. To this end, long-term vibration data were collected over two years by a CMS installed on a 3 MW wind turbine. The vibration distribution at a specific rotating speed of main shaft is approximated by the Weibull distribution and its cumulative distribution function is utilized for determining the threshold levels that indicate impending failure of mechanical parts. A Hidden Markov model (HMM) is employed to propose the statistical fault detection algorithm in the time domain and the method whereby the input sequence for HMM is extracted is also introduced by considering the threshold levels and the correlation between the signals. Finally, it was demonstrated that the proposed HMM algorithm achieved a greater than 95% detection success rate by using the long-term signals.
Ma, Xiang; Schonfeld, Dan; Khokhar, Ashfaq A
2009-06-01
In this paper, we propose a novel solution to an arbitrary noncausal, multidimensional hidden Markov model (HMM) for image and video classification. First, we show that the noncausal model can be solved by splitting it into multiple causal HMMs and simultaneously solving each causal HMM using a fully synchronous distributed computing framework, therefore referred to as distributed HMMs. Next we present an approximate solution to the multiple causal HMMs that is based on an alternating updating scheme and assumes a realistic sequential computing framework. The parameters of the distributed causal HMMs are estimated by extending the classical 1-D training and classification algorithms to multiple dimensions. The proposed extension to arbitrary causal, multidimensional HMMs allows state transitions that are dependent on all causal neighbors. We, thus, extend three fundamental algorithms to multidimensional causal systems, i.e., 1) expectation-maximization (EM), 2) general forward-backward (GFB), and 3) Viterbi algorithms. In the simulations, we choose to limit ourselves to a noncausal 2-D model whose noncausality is along a single dimension, in order to significantly reduce the computational complexity. Simulation results demonstrate the superior performance, higher accuracy rate, and applicability of the proposed noncausal HMM framework to image and video classification.
Low-intensity interference effects and hidden-variable theories
Energy Technology Data Exchange (ETDEWEB)
Buonomano, V [Universidade Estadual de Campinas (Brazil). Inst. de Matematica
1978-05-11
The double-slit interference experiment and other similar experiments in the low-intensity limit (that is, one photon in the apparatus at a time) are examined in the spirit of Bell's work from the point of view of hidden-variable theories. It is found that there exists a class of hidden-variable theories which disagrees with quantum mechanics for a certain type of interference experiment. A manufactured conceptualization of this class, which is a particle view of interference, is described. An experiment, which appears to be feasible, is proposed to examine this disagreement.
Application of Hidden Markov Models in Biomolecular Simulations.
Shukla, Saurabh; Shamsi, Zahra; Moffett, Alexander S; Selvam, Balaji; Shukla, Diwakar
2017-01-01
Hidden Markov models (HMMs) provide a framework to analyze large trajectories of biomolecular simulation datasets. HMMs decompose the conformational space of a biological molecule into finite number of states that interconvert among each other with certain rates. HMMs simplify long timescale trajectories for human comprehension, and allow comparison of simulations with experimental data. In this chapter, we provide an overview of building HMMs for analyzing bimolecular simulation datasets. We demonstrate the procedure for building a Hidden Markov model for Met-enkephalin peptide simulation dataset and compare the timescales of the process.
Enhanced axion-photon coupling in GUT with hidden photon
Daido, Ryuji; Takahashi, Fuminobu; Yokozaki, Norimi
2018-05-01
We show that the axion coupling to photons can be enhanced in simple models with a single Peccei-Quinn field, if the gauge coupling unification is realized by a large kinetic mixing χ = O (0.1) between hypercharge and unbroken hidden U(1)H. The key observation is that the U(1)H gauge coupling should be rather strong to induce such large kinetic mixing, leading to enhanced contributions of hidden matter fields to the electromagnetic anomaly. We find that the axion-photon coupling is enhanced by about a factor of 10-100 with respect to the GUT-axion models with E / N = 8 / 3.
Hidden Neural Networks: A Framework for HMM/NN Hybrids
DEFF Research Database (Denmark)
Riis, Søren Kamaric; Krogh, Anders Stærmose
1997-01-01
This paper presents a general framework for hybrids of hidden Markov models (HMM) and neural networks (NN). In the new framework called hidden neural networks (HNN) the usual HMM probability parameters are replaced by neural network outputs. To ensure a probabilistic interpretation the HNN is nor...... HMMs on TIMIT continuous speech recognition benchmarks. On the task of recognizing five broad phoneme classes an accuracy of 84% is obtained compared to 76% for a standard HMM. Additionally, we report a preliminary result of 69% accuracy on the TIMIT 39 phoneme task...
Search for hidden Higgs decay in ATLAS detector
International Nuclear Information System (INIS)
Gabrielli, A.
2013-01-01
In this paper, a brief overview of the search for the Higgs boson in Hidden Valley models is given. Hidden Valley models predict Higgs decays to neutral particles, which can be also long lived with decay paths comparable to the LHC detectors dimensions. Decay final states consist of collimated leptons (Lepton Jets). Results are presented of a search for Higgs decays to long lived particles in the ATLAS detector at the LHC, based on 1.92 fb −1 data collected during 2011 at a 7TeV center-of-mass energy.
From the solar system fo hidden cosmic structures
Energy Technology Data Exchange (ETDEWEB)
Benes, K
1987-01-01
The development of experimental astrophysics showed that in the evolution of planets, natural processes of a common nature take place. They include, e.g., radiogenic heat, the production of magmas, volcanic activity, degassing, etc. The solar system is a cosmic formation in an advanced stage of development and it is a realistic assumption that in the Galaxy other hidden planetary systems in various stages of development exist. The views on the possibility of the origination of life in other systems differ; life, however, is seen as a hidden property of cosmic matter. (M.D.).
Hidden order and disorder effects in URu{sub 2}Si{sub 2}
Energy Technology Data Exchange (ETDEWEB)
Bernal, O.O. [California State University, Los Angeles, CA (United States)]. E-mail: obernal@calstatela.edu; Moroz, M.E. [California State University, Los Angeles, CA (United States); Ishida, K. [Graduate School of Science, Kyoto University, Kyoto (Japan); Murakawa, H. [Graduate School of Science, Kyoto University, Kyoto (Japan); Reyes, A.P. [National High Magnetic Field Lab, Tallahassee, FL (United States); Kuhns, P.L. [National High Magnetic Field Lab, Tallahassee, FL (United States); MacLaughlin, D.E. [University of California, Riverside, CA (United States); Mydosh, J.A. [Max Planck Institute for Chemical Physics of Solids, Dresden (Germany); Gortenmulder, T.J. [Kamerlingh Onnes Lab, Leiden University (Netherlands)
2006-05-01
NMR experiments at ambient pressure in URu{sub 2}Si{sub 2} demonstrate a linewidth enhancement effect below the hidden order transition temperature T{sub 0}. We present single-crystal {sup 29}Si NMR parameters for various temperatures and for an applied magnetic field perpendicular to the crystal c-axis. By comparing oriented-powder and single-crystal data, we observe that the size of the linewidth enhancement below T{sub 0} correlates with the size of the high-T broadening. We measure a {sup 29}Si up-field line shift below T{sub 0} which indicates the presence of an internal-field average for the entire crystal. This shift also correlates with the high-temperature width. The {sup 101}Ru NQR frequency as a function of temperature was also measured. No strong effect on the NQR frequency is observed at T{sub 0}. Both NMR and NQR measurements suggest a connection between linewidth/disorder effects and the transition to hidden order.
Auten, Ashley A; Beauchamp, Lauren N; Joshua Taylor; Hardinger, Karen L
2013-06-01
The interaction between grapefruit-containing beverages and immunosuppressants is not well defined in the literature. This study was conducted to investigate possible sources of grapefruit juice or grapefruit extract in common US-manufactured beverages. The goal was to identify those products that might serve as hidden sources of dietary grapefruit intake, increasing a transplant patient's risk for drug interactions. A careful review of the ingredients of the 3 largest US beverage manufacturer's product lines was conducted through manufacturer correspondence, product labeling examination, and online nutrition database research. Focus was placed on citrus-flavored soft drinks, teas, and juice products and their impact on a patient's immunosuppressant regimens. Twenty-three beverages were identified that contained grapefruit. Five did not contain the word "grapefruit" in the product name. In addition to the confirmed grapefruit-containing products, 17 products were identified as possibly containing grapefruit juice or grapefruit extract. A greater emphasis should be placed upon properly educating patients regarding hidden sources of grapefruit in popular US beverages and the potential for food-drug interactions.
Protein secondary structure prediction for a single-sequence using hidden semi-Markov models
Directory of Open Access Journals (Sweden)
Borodovsky Mark
2006-03-01
Full Text Available Abstract Background The accuracy of protein secondary structure prediction has been improving steadily towards the 88% estimated theoretical limit. There are two types of prediction algorithms: Single-sequence prediction algorithms imply that information about other (homologous proteins is not available, while algorithms of the second type imply that information about homologous proteins is available, and use it intensively. The single-sequence algorithms could make an important contribution to studies of proteins with no detected homologs, however the accuracy of protein secondary structure prediction from a single-sequence is not as high as when the additional evolutionary information is present. Results In this paper, we further refine and extend the hidden semi-Markov model (HSMM initially considered in the BSPSS algorithm. We introduce an improved residue dependency model by considering the patterns of statistically significant amino acid correlation at structural segment borders. We also derive models that specialize on different sections of the dependency structure and incorporate them into HSMM. In addition, we implement an iterative training method to refine estimates of HSMM parameters. The three-state-per-residue accuracy and other accuracy measures of the new method, IPSSP, are shown to be comparable or better than ones for BSPSS as well as for PSIPRED, tested under the single-sequence condition. Conclusions We have shown that new dependency models and training methods bring further improvements to single-sequence protein secondary structure prediction. The results are obtained under cross-validation conditions using a dataset with no pair of sequences having significant sequence similarity. As new sequences are added to the database it is possible to augment the dependency structure and obtain even higher accuracy. Current and future advances should contribute to the improvement of function prediction for orphan proteins inscrutable
Hidden Pair of Supermassive Black Holes
Kohler, Susanna
2015-08-01
Could a pair of supermassive black holes (SMBHs) be lurking at the center of the galaxy Mrk 231? A recent study finds that this may be the case and the unique spectrum of this galaxy could be the key to discovering more hidden binary SMBH systems.Where Are the Binary Supermassive Black Holes?Its believed that most, if not all, galaxies have an SMBH at their centers. As two galaxies merge, the two SMBHs should evolve into a closely-bound binary system before they eventually merge. Given the abundance of galaxy mergers, we would expect to see the kinematic and visual signatures of these binary SMBHs among observed active galactic nuclei yet such evidence for sub-parsec binary SMBH systems remains scarce and ambiguous. This has led researchers to wonder: is there another way that we might detect these elusive systems?A collaboration led by Chang-Shuo Yan (National Astronomical Observatories, Chinese Academy of Sciences) thinks that there is. The group suggests that these systems might have distinct signatures in their optical-to-UV spectra, and they identify a system that might be just such a candidate: Mrk 231.A Binary CandidateProposed model of Mrk 231. Two supermassive black holes, each with their own mini-disk, orbit each other in the center of a circumbinary disk. The secondary black hole has cleared gap in the circumbinary disk as a result of its orbit around the primary black hole. [Yan et al. 2015]Mrk 231 is a galaxy with a disturbed morphology and tidal tails strong clues that it might be in the final stages of a galactic merger. In addition to these signs, Mrk 231 also has an unusual spectrum for a quasar: its continuum emission displays an unexpected drop in the near-UV band.Yan and her collaborators propose that the odd behavior of Mrk 231s spectrum can be explained if the center of the galaxy houses a pair of SMBHs each with its own mini accretion disk surrounded by a circumbinary accretion disk. As the secondary SMBH orbits the primary SMBH (with a
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...
The cylindrical K-function and Poisson line cluster point processes
DEFF Research Database (Denmark)
Møller, Jesper; Safavimanesh, Farzaneh; Rasmussen, Jakob G.
Poisson line cluster point processes, is also introduced. Parameter estimation based on moment methods or Bayesian inference for this model is discussed when the underlying Poisson line process and the cluster memberships are treated as hidden processes. To illustrate the methodologies, we analyze two...
On-line dynamic monitoring automotive exhausts: using BP-ANN for distinguishing multi-components
Zhao, Yudi; Wei, Ruyi; Liu, Xuebin
2017-10-01
Remote sensing-Fourier Transform infrared spectroscopy (RS-FTIR) is one of the most important technologies in atmospheric pollutant monitoring. It is very appropriate for on-line dynamic remote sensing monitoring of air pollutants, especially for the automotive exhausts. However, their absorption spectra are often seriously overlapped in the atmospheric infrared window bands, i.e. MWIR (3 5μm). Artificial Neural Network (ANN) is an algorithm based on the theory of the biological neural network, which simplifies the partial differential equation with complex construction. For its preferable performance in nonlinear mapping and fitting, in this paper we utilize Back Propagation-Artificial Neural Network (BP-ANN) to quantitatively analyze the concentrations of four typical industrial automotive exhausts, including CO, NO, NO2 and SO2. We extracted the original data of these automotive exhausts from the HITRAN database, most of which virtually overlapped, and established a mixed multi-component simulation environment. Based on Beer-Lambert Law, concentrations can be retrieved from the absorbance of spectra. Parameters including learning rate, momentum factor, the number of hidden nodes and iterations were obtained when the BP network was trained with 80 groups of input data. By improving these parameters, the network can be optimized to produce necessarily higher precision for the retrieved concentrations. This BP-ANN method proves to be an effective and promising algorithm on dealing with multi-components analysis of automotive exhausts.
HIDDEN SEQUENCES IN RESULTS OF TESTS IDENTIFYING
Directory of Open Access Journals (Sweden)
Sviatoslav Yutskevych
2013-10-01
Full Text Available Normal 0 false false false MicrosoftInternetExplorer4 Describes a method and a general algorithm for the experimental data series corresponding to a given recurrence relation search program. Search-analytical model different from the existing search models is offered /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Обычная таблица"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Times New Roman"; mso-ansi-language:#0400; mso-fareast-language:#0400; mso-bidi-language:#0400;}
Photoacoustic imaging of hidden dental caries by using a fiber-based probing system
Koyama, Takuya; Kakino, Satoko; Matsuura, Yuji
2017-04-01
Photoacoustic method to detect hidden dental caries is proposed. It was found that high frequency ultrasonic waves are generated from hidden carious part when radiating laser light to occlusal surface of model tooth. By making a map of intensity of these high frequency components, photoacoustic images of hidden caries were successfully obtained. A photoacoustic imaging system using a bundle of hollow optical fiber was fabricated for using clinical application, and clear photoacoustic image of hidden caries was also obtained by this system.
Low-scale gravity mediation in warped extra dimension and collider phenomenology on hidden sector
International Nuclear Information System (INIS)
Itoh, H.; Okada, N.; Yamashita, T.
2007-01-01
We propose a new scenario of gravity-mediated supersymmetry breaking (gravity mediation) in a supersymmetric Randall-Sundrum model, where the gravity mediation takes place at a low scale due to the warped metric. We investigate collider phenomenology involving the hidden sector field, and find a possibility that the hidden sector field can be produced at the LHC and the ILC. The hidden sector may no longer be hidden. (author)
A quick survey of text categorization algorithms
Directory of Open Access Journals (Sweden)
Dan MUNTEANU
2007-12-01
Full Text Available This paper contains an overview of basic formulations and approaches to text classification. This paper surveys the algorithms used in text categorization: handcrafted rules, decision trees, decision rules, on-line learning, linear classifier, Rocchio’s algorithm, k Nearest Neighbor (kNN, Support Vector Machines (SVM.
Color Image Secret Watermarking Erase and Write Algorithm Based on SIFT
Qu, Jubao
The use of adaptive characteristics of SIFT, image features, the implementation of the write, erase operations on Extraction and color image hidden watermarking. From the experimental results, this algorithm has better imperceptibility and at the same time, is robust against geometric attacks and common signal processing.
On the hidden maxwell superalgebra underlying D = 4 supergravity
Energy Technology Data Exchange (ETDEWEB)
Penafiel, D.M. [Departamento de Fisica, Universidad de Concepcion (Chile); DISAT, Politecnico di Torino (Italy); Istituto Nazionale di Fisica Nucleare (INFN), Sezione di Torino (Italy); Ravera, L. [DISAT, Politecnico di Torino (Italy); Istituto Nazionale di Fisica Nucleare (INFN), Sezione di Torino (Italy)
2017-09-15
In this work, we expand the hidden AdS-Lorentz superalgebra underlying D = 4 supergravity, reaching a (hidden) Maxwell superalgebra. The latter can be viewed as an extension involving cosmological constant of the superalgebra underlying D = 4 supergravity in flat spacetime. We write the Maurer-Cartan equations in this context and we find some interesting extensions of the antisymmetric 3-form A{sup (3)} appearing in the Free Differential Algebra in Minkowski space. The structure of Free Differential Algebras is obtained by considering the zero curvature equations. We write the parametrization of A{sup (3)} in terms of 1-forms and we rend the topological features of its extensions manifest. We interestingly find out that the structure of these extensions, and consequently the structure of the corresponding boundary contribution dA{sup (3)}, strongly depends on the form of the extra fermionic generator appearing in the hidden Maxwell superalgebra. The model we develop in this work is defined in an enlarged superspace with respect to the ordinary one, and the extra bosonic and fermionic 1-forms required for the closure of the hidden Maxwell superalgebra must be considered as physical fields in this enlarged superspace. (copyright 2017 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim)
Generalized inequalities for quantum correlations with hidden variables
International Nuclear Information System (INIS)
Vinduska, M.
1991-01-01
Renowned inequalities for quantum correlations are generalized for the case when quantum system cannot be described with an absolute independent measure of the probability. Such a formulation appears to be suitable for the formulation of the hidden variables theory in terms of non-Euclidean geometry. 10 refs
Hidden conic quadratic representation of some nonconvex quadratic optimization problems
Ben-Tal, A.; den Hertog, D.
The problem of minimizing a quadratic objective function subject to one or two quadratic constraints is known to have a hidden convexity property, even when the quadratic forms are indefinite. The equivalent convex problem is a semidefinite one, and the equivalence is based on the celebrated
Measurement problem and local hidden variables with entangled photons
Directory of Open Access Journals (Sweden)
Muchowski Eugen
2017-12-01
Full Text Available It is shown that there is no remote action with polarization measurements of photons in singlet state. A model is presented introducing a hidden parameter which determines the polarizer output. This model is able to explain the polarization measurement results with entangled photons. It is not ruled out by Bell’s Theorem.
The incompatibility between local hidden variable theories and the ...
Indian Academy of Sciences (India)
I discuss in detail the result that the Bell's inequalities derived in the context of local hidden variable theories for discrete quantized observables can be satisfied only if a fundamental conservation law is violated on the average. This result shows that such theories are physically nonviable, and makes the demarcating criteria ...
A novel design of hidden web crawler using ontology
Manvi; Bhatia, Komal Kumar; Dixit, Ashutosh
2015-01-01
Deep Web is content hidden behind HTML forms. Since it represents a large portion of the structured, unstructured and dynamic data on the Web, accessing Deep-Web content has been a long challenge for the database community. This paper describes a crawler for accessing Deep-Web using Ontologies. Performance evaluation of the proposed work showed that this new approach has promising results.
Hidden symmetries of the Principal Chiral Model unveiled
International Nuclear Information System (INIS)
Devchand, C.; Schiff, J.
1996-12-01
By relating the two-dimensional U(N) Principal Chiral Model to a Simple linear system we obtain a free-field parametrization of solutions. Obvious symmetry transformations on the free-field data give symmetries of the model. In this way all known 'hidden symmetries' and Baecklund transformations, as well as a host of new symmetries, arise. (author). 21 refs