Sequence comparisons via algorithmic mutual information
Milosavijevic, A.
1994-12-31
One of the main problems in DNA and protein sequence comparisons is to decide whether observed similarity of two sequences should be explained by their relatedness or by mere presence of some shared internal structure, e.g., shared internal tandem repeats. The standard methods that are based on statistics or classical information theory can be used to discover either internal structure or mutual sequence similarity, but cannot take into account both. Consequently, currently used methods for sequence comparison employ {open_quotes}masking{close_quotes} techniques that simply eliminate sequences that exhibit internal repetitive structure prior to sequence comparisons. The {open_quotes}masking{close_quotes} approach precludes discovery of homologous sequences of moderate or low complexity, which abound at both DNA and protein levels. As a solution to this problem, we propose a general method that is based on algorithmic information theory and minimal length encoding. We show that algorithmic mutual information factors out the sequence similarity that is due to shared internal structure and thus enables discovery of truly related sequences. We extend the recently developed algorithmic significance method to show that significance depends exponentially on algorithmic mutual information.
Fast registration algorithm using a variational principle for mutual information
NASA Astrophysics Data System (ADS)
Alexander, Murray E.; Summers, Randy
2003-05-01
A method is proposed for cross-modal image registration based on mutual information (MI) matching criteria. Both conventional and "normalized" MI are considered. MI may be expressed as a functional of a general image displacement field u. The variational principle for MI provides a field equation for u. The method employs a set of "registration points" consisting of a prescribed number of strongest edge points of the reference image, and minimizes an objective function D defined as the sum of the square residuals of the field equation for u at these points, where u is expressed as a sum over a set of basis functions (the affine model is presented here). D has a global minimum when the images are aligned, with a "basin of attraction" typically of width ~0.3 pixels. By pre-filtering with a low-pass filter, and using a multiresolution image pyramid, the basin may be significantly widened. The Levenberg-Marquardt algorithm is used to minimize D. Tests using randomly distributed misalignments of image pairs show that registration accuracy of 0.02 - 0.07 pixels is achieved, when using cubic B-splines for image representation, interpolation, and Parzen window estimation.
Lin, Fen-Fang; Wang, Ke; Yang, Ning; Yan, Shi-Guang; Zheng, Xin-Yu
2012-02-01
In this paper, some main factors such as soil type, land use pattern, lithology type, topography, road, and industry type that affect soil quality were used to precisely obtain the spatial distribution characteristics of regional soil quality, mutual information theory was adopted to select the main environmental factors, and decision tree algorithm See 5.0 was applied to predict the grade of regional soil quality. The main factors affecting regional soil quality were soil type, land use, lithology type, distance to town, distance to water area, altitude, distance to road, and distance to industrial land. The prediction accuracy of the decision tree model with the variables selected by mutual information was obviously higher than that of the model with all variables, and, for the former model, whether of decision tree or of decision rule, its prediction accuracy was all higher than 80%. Based on the continuous and categorical data, the method of mutual information theory integrated with decision tree could not only reduce the number of input parameters for decision tree algorithm, but also predict and assess regional soil quality effectively.
Bhattacharya, Mahua; Das, Arpita
2011-01-01
Medical image fusion has been used to derive the useful complimentary information from multimodal images. The prior step of fusion is registration or proper alignment of test images for accurate extraction of detail information. For this purpose, the images to be fused are geometrically aligned using mutual information (MI) as similarity measuring metric followed by genetic algorithm to maximize MI. The proposed fusion strategy incorporating multi-resolution approach extracts more fine details from the test images and improves the quality of composite fused image. The proposed fusion approach is independent of any manual marking or knowledge of fiducial points and starts the procedure automatically. The performance of proposed genetic-based fusion methodology is compared with fuzzy clustering algorithm-based fusion approach, and the experimental results show that genetic-based fusion technique improves the quality of the fused image significantly over the fuzzy approaches.
On the accuracy of a mutual information algorithm for PET-MR image registration
NASA Astrophysics Data System (ADS)
Karaiskos, P.; Malamitsi, J.; Andreou, J.; Prassopoulos, V.; Valotassiou, V.; Laspas, F.; Sandilos, P.; Torrens, M.
2009-07-01
Image registration has been increasingly used in radiation diagnosis and treatment planning as a means of information integration from different imaging modalities (e.g. MRI, PET, CT). Especially for brain lesions, accurate 3D registration and fusion of MR and PET images can provide comprehensive information about the patient under study by relating functional information from PET images to the detailed anatomical information available in MR images. However, direct PET-MR image fusion in soft tissue is complicated mainly due to the lack of conspicuous anatomical features in PET images. This study describes the implementation and validation of a mutual information registration algorithm for this purpose. Ten patients with brain lesions underwent MR and PET/CT scanning. MR-PET registration was performed a) based on the well validated MR-CT registration technique and copying the transformation to the PET images derived from the PET/CT scan (MR/PET/CT registration method) and b) directly from the MR and PET images without taking into account the CT images (MR/PET registration method). In order to check the registration accuracy of the MR/PET method, the lesion (target) was contoured in the PET images and it was transferred to the MR images using both the above methods. The MR/PET/CT method served as the gold standard for target contouring. Target contours derived by the MR/PET method were compared with the gold standard target contours for each patient and the deviation between the two contours was used to estimate the accuracy of the PET-MR registration method. This deviation was less than 3 mm (i.e. comparable to the imaging voxel of the PET/CT scanning) for 9/10 of the cases studied. Results show that the mutual information algorithm used is able to perform the PET-MR registration reliably and accurately.
NASA Astrophysics Data System (ADS)
Kraskov, Alexander; Stögbauer, Harald; Grassberger, Peter
2004-06-01
We present two classes of improved estimators for mutual information M(X,Y) , from samples of random points distributed according to some joint probability density μ(x,y) . In contrast to conventional estimators based on binnings, they are based on entropy estimates from k -nearest neighbor distances. This means that they are data efficient (with k=1 we resolve structures down to the smallest possible scales), adaptive (the resolution is higher where data are more numerous), and have minimal bias. Indeed, the bias of the underlying entropy estimates is mainly due to nonuniformity of the density at the smallest resolved scale, giving typically systematic errors which scale as functions of k/N for N points. Numerically, we find that both families become exact for independent distributions, i.e. the estimator M̂ (X,Y) vanishes (up to statistical fluctuations) if μ(x,y)=μ(x)μ(y) . This holds for all tested marginal distributions and for all dimensions of x and y . In addition, we give estimators for redundancies between more than two random variables. We compare our algorithms in detail with existing algorithms. Finally, we demonstrate the usefulness of our estimators for assessing the actual independence of components obtained from independent component analysis (ICA), for improving ICA, and for estimating the reliability of blind source separation.
Recchia, Gabriel; Jones, Michael N
2009-08-01
Computational models of lexical semantics, such as latent semantic analysis, can automatically generate semantic similarity measures between words from statistical redundancies in text. These measures are useful for experimental stimulus selection and for evaluating a model's cognitive plausibility as a mechanism that people might use to organize meaning in memory. Although humans are exposed to enormous quantities of speech, practical constraints limit the amount of data that many current computational models can learn from. We follow up on previous work evaluating a simple metric of pointwise mutual information. Controlling for confounds in previous work, we demonstrate that this metric benefits from training on extremely large amounts of data and correlates more closely with human semantic similarity ratings than do publicly available implementations of several more complex models. We also present a simple tool for building simple and scalable models from large corpora quickly and efficiently.
Uncertainty relation for mutual information
NASA Astrophysics Data System (ADS)
Schneeloch, James; Broadbent, Curtis J.; Howell, John C.
2014-12-01
We postulate the existence of a universal uncertainty relation between the quantum and classical mutual informations between pairs of quantum systems. Specifically, we propose that the sum of the classical mutual information, determined by two mutually unbiased pairs of observables, never exceeds the quantum mutual information. We call this the complementary-quantum correlation (CQC) relation and prove its validity for pure states, for states with one maximally mixed subsystem, and for all states when one measurement is minimally disturbing. We provide results of a Monte Carlo simulation suggesting that the CQC relation is generally valid. Importantly, we also show that the CQC relation represents an improvement to an entropic uncertainty principle in the presence of a quantum memory, and that it can be used to verify an achievable secret key rate in the quantum one-time pad cryptographic protocol.
Mutual Coupling Compensation on Spectral-based DOA Algorithm
NASA Astrophysics Data System (ADS)
Sanudin, R.
2016-11-01
Direction of arrival (DOA) estimation using isotropic antenna arrays are commonly being implemented without considering the mutual coupling effect in between the array elements. This paper presents an analysis of DOA estimation with mutual coupling compensation using a linear antenna array. Mutual coupling effect is represented by mutual coupling coefficients and taken into account when calculating the array output. The mutual coupling compensation technique exploits a banded mutual coupling matrix to reduce the computational complexity. The banded matrix reflects the relationship between mutual coupling effect and the element spacing in an antenna array. The analysis is being carried out using the Capon algorithm, one of spectral-based DOA algorithms, for estimating the DOA of incoming signals. Computer simulations are performed to show the performance of the mutual coupling compensation technique on DOA estimation. Simulation results show that, in term of estimation resolution, the mutual coupling compensation technique manages to obtain a comparable results compared to the case without mutual coupling consideration. However, the mutual coupling compensation technique produces significant estimation error compared to the case without mutual coupling. The study concludes that the banded matrix of mutual coupling coefficients should be properly designed to improve the performance of mutual coupling compensation technique in DOA estimation.
Non-rigid registration using higher-order mutual information
NASA Astrophysics Data System (ADS)
Rueckert, D.; Clarkson, M. J.; Hill, D. L. G.; Hawkes, D. J.
2000-03-01
Non-rigid registration of multi-modality images is an important tool for assessing temporal and structural changesbetween images. For rigid registration, voxel similarity measures like mutual information have been shown to alignimages from different modalities accurately and robustly. For non-rigid registration, mutual information can besensitive to local variations of intensity which in MR images may be caused by RF inhomogeneity. The reasonfor the sensitivity of mutual information towards intensity variations stems from the fact that mutual informationignores any spatial information. In this paper we propose an extension of the mutual information framework whichincorporates spatial information about higher-order image structure into the registration process and has the potentialto improve the accuracy and robustness of non-rigid registration in the presence of intensity variations. We haveapplied the non-rigid registration algorithm to a number of simulated MR brain images of a digital phantom whichhave been degraded by a simulated intensity shading and a known deformation. In addition, we have applied thealgorithm for the non-rigid registration of eight pre- and post-operative brain MR images which were acquired withan interventional MR scanner and therefore have substantial intensity shading due to RF field inhomogeneities. Inall cases the second-order estimate of mutual information leads to robust and accurate registration.
Mutual Information Rate and Bounds for It
Baptista, Murilo S.; Rubinger, Rero M.; Viana, Emilson R.; Sartorelli, José C.; Parlitz, Ulrich; Grebogi, Celso
2012-01-01
The amount of information exchanged per unit of time between two nodes in a dynamical network or between two data sets is a powerful concept for analysing complex systems. This quantity, known as the mutual information rate (MIR), is calculated from the mutual information, which is rigorously defined only for random systems. Moreover, the definition of mutual information is based on probabilities of significant events. This work offers a simple alternative way to calculate the MIR in dynamical (deterministic) networks or between two time series (not fully deterministic), and to calculate its upper and lower bounds without having to calculate probabilities, but rather in terms of well known and well defined quantities in dynamical systems. As possible applications of our bounds, we study the relationship between synchronisation and the exchange of information in a system of two coupled maps and in experimental networks of coupled oscillators. PMID:23112809
Mutual information and spontaneous symmetry breaking
NASA Astrophysics Data System (ADS)
Hamma, A.; Giampaolo, S. M.; Illuminati, F.
2016-01-01
We show that the metastable, symmetry-breaking ground states of quantum many-body Hamiltonians have vanishing quantum mutual information between macroscopically separated regions and are thus the most classical ones among all possible quantum ground states. This statement is obvious only when the symmetry-breaking ground states are simple product states, e.g., at the factorization point. On the other hand, symmetry-breaking states are in general entangled along the entire ordered phase, and to show that they actually feature the least macroscopic correlations compared to their symmetric superpositions is highly nontrivial. We prove this result in general, by considering the quantum mutual information based on the two-Rényi entanglement entropy and using a locality result stemming from quasiadiabatic continuation. Moreover, in the paradigmatic case of the exactly solvable one-dimensional quantum X Y model, we further verify the general result by considering also the quantum mutual information based on the von Neumann entanglement entropy.
Mutual Information Between GPS Measurements and Earthquakes
NASA Astrophysics Data System (ADS)
Wang, T.; Bebbington, M. S.
2009-12-01
Prior to the wide deployment of Continuous GPS stations in the early 1990s, there were a number of well-documented deformation rate changes observed before large earthquakes. GPS measurements provide the opportunity for systematic investigation of pre-, co- and post-seismic deformation anomalies, but contain much noise that needs to be filtered out of the observations. Assuming the existence of an earthquake cycle (for example, mainshock--aftershock--quiescence--precursory seismicity), a hidden Markov model (HMM) provides a natural framework for analyzing the observed GPS data. For two case studies of a) deep earthquakes in the central North Island, New Zealand, and b) shallow earthquakes in Southern California, an HMM fitted to the trend ranges of the GPS measurements can classify the deformation data into different patterns which form proxies for states of the earthquake cycle. Mutual information can be used to examine whether there is any relation between these patterns, in particular the Viterbi path, and subsequent (or previous) earthquakes. One class of GPS movements (identified by the HMM as having the largest range of deformation rate changes) appears to have some precursory character for earthquakes with minimum magnitude 5.1 (central North Island, New Zealand, 26 earthquakes in 1747 days) and 4.5 (Southern California, 50 earthquakes in 3815 days). We define a ``Time of Increased Probability'' (TIP) as being a 10-day interval (central North Island, New Zealand) or a 20-day interval (Southern California) following entry (as identified by the Viterbi algorithm) to the `precursory' hidden state, and examine the performance of this in probabilistically forecasting subsequent earthquakes.
Blasting and Zipping: Sequence Alignment and Mutual Information
NASA Astrophysics Data System (ADS)
Penner, Orion; Grassberger, Peter; Paczuski, Maya
2009-03-01
Alignment of biological sequences such as DNA, RNA or proteins is one of the most widely used tools in computational bioscience. While the accomplishments of sequence alignment algorithms are undeniable the fact remains that these algorithms are based upon heuristic scoring schemes. Therefore, these algorithms do not provide model independent and objective measures for how similar two (or more) sequences actually are. Although information theory provides such a similarity measure - the mutual information (MI) - numerous previous attempts to connect sequence alignment and information have not produced realistic estimates for the MI from a given alignment. We report on a simple and flexible approach to get robust estimates of MI from global alignments. The presented results may help establish MI as a reliable tool for evaluating the quality of global alignments, judging the relative merits of different alignment algorithms, and estimating the significance of specific alignments.
Generalized mutual information of quantum critical chains
NASA Astrophysics Data System (ADS)
Alcaraz, F. C.; Rajabpour, M. A.
2015-04-01
We study the generalized mutual information I˜n of the ground state of different critical quantum chains. The generalized mutual information definition that we use is based on the well established concept of the Rényi divergence. We calculate this quantity numerically for several distinct quantum chains having either discrete Z (Q ) symmetries (Q -state Potts model with Q =2 ,3 ,4 and Z (Q ) parafermionic models with Q =5 ,6 ,7 ,8 and also Ashkin-Teller model with different anisotropies) or the U (1 ) continuous symmetries (Klein-Gordon field theory, X X Z and spin-1 Fateev-Zamolodchikov quantum chains with different anisotropies). For the spin chains these calculations were done by expressing the ground-state wave functions in two special bases. Our results indicate some general behavior for particular ranges of values of the parameter n that defines I˜n. For a system, with total size L and subsystem sizes ℓ and L -ℓ , the I˜n has a logarithmic leading behavior given by c/˜n4 log[L/π sin(π/ℓ L ) ] where the coefficient c˜n is linearly dependent on the central charge c of the underlying conformal field theory describing the system's critical properties.
Graph embedded nonparametric mutual information for supervised dimensionality reduction.
Bouzas, Dimitrios; Arvanitopoulos, Nikolaos; Tefas, Anastasios
2015-05-01
In this paper, we propose a novel algorithm for dimensionality reduction that uses as a criterion the mutual information (MI) between the transformed data and their corresponding class labels. The MI is a powerful criterion that can be used as a proxy to the Bayes error rate. Furthermore, recent quadratic nonparametric implementations of MI are computationally efficient and do not require any prior assumptions about the class densities. We show that the quadratic nonparametric MI can be formulated as a kernel objective in the graph embedding framework. Moreover, we propose its linear equivalent as a novel linear dimensionality reduction algorithm. The derived methods are compared against the state-of-the-art dimensionality reduction algorithms with various classifiers and on various benchmark and real-life datasets. The experimental results show that nonparametric MI as an optimization objective for dimensionality reduction gives comparable and in most of the cases better results compared with other dimensionality reduction methods.
Mutual information-based facial expression recognition
NASA Astrophysics Data System (ADS)
Hazar, Mliki; Hammami, Mohamed; Hanêne, Ben-Abdallah
2013-12-01
This paper introduces a novel low-computation discriminative regions representation for expression analysis task. The proposed approach relies on interesting studies in psychology which show that most of the descriptive and responsible regions for facial expression are located around some face parts. The contributions of this work lie in the proposition of new approach which supports automatic facial expression recognition based on automatic regions selection. The regions selection step aims to select the descriptive regions responsible or facial expression and was performed using Mutual Information (MI) technique. For facial feature extraction, we have applied Local Binary Patterns Pattern (LBP) on Gradient image to encode salient micro-patterns of facial expressions. Experimental studies have shown that using discriminative regions provide better results than using the whole face regions whilst reducing features vector dimension.
Quantum mutual information along unitary orbits
NASA Astrophysics Data System (ADS)
Jevtic, Sania; Jennings, David; Rudolph, Terry
2012-05-01
Motivated by thermodynamic considerations, we analyze the variation of the quantum mutual information on a unitary orbit of a bipartite system's state with and without global constraints such as energy conservation. We solve the full optimization problem for the smallest system of two qubits and explore thoroughly the effect of unitary operations on the space of reduced-state spectra. We then provide applications of these ideas to physical processes within closed quantum systems such as a generalized collision model approach to thermal equilibrium and a global Maxwell demon playing tricks on local observers. For higher dimensions, the maximization of correlations is relatively straightforward for equal-sized subsystems, however their minimization displays nontrivial structures. We characterize a set of separable states in which the minimally correlated state resides: a collection of classically correlated states admitting a particular “Young tableau” form. Furthermore, a partial order exists on this set with respect to individual marginal entropies, and the presence of a “see-saw effect” for these entropies forces a finer analysis to determine the optimal tableau.
Sufficient dimension reduction via squared-loss mutual information estimation.
Suzuki, Taiji; Sugiyama, Masashi
2013-03-01
The goal of sufficient dimension reduction in supervised learning is to find the low-dimensional subspace of input features that contains all of the information about the output values that the input features possess. In this letter, we propose a novel sufficient dimension-reduction method using a squared-loss variant of mutual information as a dependency measure. We apply a density-ratio estimator for approximating squared-loss mutual information that is formulated as a minimum contrast estimator on parametric or nonparametric models. Since cross-validation is available for choosing an appropriate model, our method does not require any prespecified structure on the underlying distributions. We elucidate the asymptotic bias of our estimator on parametric models and the asymptotic convergence rate on nonparametric models. The convergence analysis utilizes the uniform tail-bound of a U-process, and the convergence rate is characterized by the bracketing entropy of the model. We then develop a natural gradient algorithm on the Grassmann manifold for sufficient subspace search. The analytic formula of our estimator allows us to compute the gradient efficiently. Numerical experiments show that the proposed method compares favorably with existing dimension-reduction approaches on artificial and benchmark data sets.
Spatial Mutual Information Based Hyperspectral Band Selection for Classification
2015-01-01
The amount of information involved in hyperspectral imaging is large. Hyperspectral band selection is a popular method for reducing dimensionality. Several information based measures such as mutual information have been proposed to reduce information redundancy among spectral bands. Unfortunately, mutual information does not take into account the spatial dependency between adjacent pixels in images thus reducing its robustness as a similarity measure. In this paper, we propose a new band selection method based on spatial mutual information. As validation criteria, a supervised classification method using support vector machine (SVM) is used. Experimental results of the classification of hyperspectral datasets show that the proposed method can achieve more accurate results. PMID:25918742
Classification of radio elements using mutual information: A tool for geological mapping
NASA Astrophysics Data System (ADS)
Kumar, P. T. Krishna; Phoha, V. V.; Iyengar, S. S.
2008-09-01
A broad range of current airborne gamma ray spectrometry (AGRS) applications involve environmental mapping and mineral exploration. One common goal for such applications is the development of an algorithm for reliable on line classification of radio elements. In this paper, we propose the concept of maximization of correlated information as the similarity measure for classification. In order to achieve this similarity measure, we have developed an algorithm using the concept of minimization of mutual information, which is computationally faster, and requiring less memory than the hierarchical agglomerative clustering (HAC) method. The minimization of mutual information is achieved by maximizing the correlated information of the correlation matrix. The correlated information is maximized by the determination of its lower bound using the technique of determinant inequalities developed by us. We demonstrate the robustness of our results using mutual information and its superiority over that of Ward's method of minimum variance for the aerial survey carried out in central India.
NASA Astrophysics Data System (ADS)
Cariou, Claude; Chehdi, Kacem
2013-10-01
We investigate the potential of multidimensional mutual information for the registration of multi-spectral remote sensing images. We devise a gradient flow algorithm which iteratively maximizes the multidimensional mutual information with respect to a differentiable displacement map, accounting for partial derivatives of the multivariate joint distribution and the multivariate marginal of the float image with respect to each variable of the mutual information derivative. The resulting terms are shown to weight the band specific gradients of the warp image, and we propose in addition to compute them with a method based on the k-nearest neighbours. We apply our method to the registration of Ikonos and CHRIS-Proba images over the region of Baabdat, Lebanon, for purposes of cedar pines detection. A comparison between (crossed) single band and multi-band registration results obtained shows that using the multidimensional mutual information brings a significant gain in positional accuracy and is suitable for multispectral remote sensing image registration.
Nonlinear pattern analysis of ventricular premature beats by mutual information
NASA Technical Reports Server (NTRS)
Osaka, M.; Saitoh, H.; Yokoshima, T.; Kishida, H.; Hayakawa, H.; Cohen, R. J.
1997-01-01
The frequency of ventricular premature beats (VPBs) has been related to the risk of mortality. However, little is known about the temporal pattern of occurrence of VPBs and its relationship to autonomic activity. Hence, we applied a general correlation measure, mutual information, to quantify how VPBs are generated over time. We also used mutual information to determine the correlation between VPB production and heart rate in order to evaluate effects of autonomic activity on VPB production. We examined twenty subjects with more than 3000 VPBs/day and simulated random time series of VPB occurrence. We found that mutual information values could be used to characterize quantitatively the temporal patterns of VPB generation. Our data suggest that VPB production is not random and VPBs generated with a higher value of mutual information may be more greatly affected by autonomic activity.
Robust volumetric change detection using mutual information with 3D fractals
NASA Astrophysics Data System (ADS)
Rahmes, Mark; Akbari, Morris; Henning, Ronda; Pokorny, John
2014-06-01
We discuss a robust method for quantifying change of multi-temporal remote sensing point data in the presence of affine registration errors. Three dimensional image processing algorithms can be used to extract and model an electronic module, consisting of a self-contained assembly of electronic components and circuitry, using an ultrasound scanning sensor. Mutual information (MI) is an effective measure of change. We propose a multi-resolution 3D fractal algorithm which is a novel extension to MI or regional mutual information (RMI). Our method is called fractal mutual information (FMI). This extension efficiently takes neighborhood fractal patterns of corresponding voxels (3D pixels) into account. The goal of this system is to quantify the change in a module due to tampering and provide a method for quantitative and qualitative change detection and analysis.
A new mutually reinforcing network node and link ranking algorithm
NASA Astrophysics Data System (ADS)
Wang, Zhenghua; Dueñas-Osorio, Leonardo; Padgett, Jamie E.
2015-10-01
This study proposes a novel Normalized Wide network Ranking algorithm (NWRank) that has the advantage of ranking nodes and links of a network simultaneously. This algorithm combines the mutual reinforcement feature of Hypertext Induced Topic Selection (HITS) and the weight normalization feature of PageRank. Relative weights are assigned to links based on the degree of the adjacent neighbors and the Betweenness Centrality instead of assigning the same weight to every link as assumed in PageRank. Numerical experiment results show that NWRank performs consistently better than HITS, PageRank, eigenvector centrality, and edge betweenness from the perspective of network connectivity and approximate network flow, which is also supported by comparisons with the expensive N-1 benchmark removal criteria based on network efficiency. Furthermore, it can avoid some problems, such as the Tightly Knit Community effect, which exists in HITS. NWRank provides a new inexpensive way to rank nodes and links of a network, which has practical applications, particularly to prioritize resource allocation for upgrade of hierarchical and distributed networks, as well as to support decision making in the design of networks, where node and link importance depend on a balance of local and global integrity.
A new mutually reinforcing network node and link ranking algorithm
Wang, Zhenghua; Dueñas-Osorio, Leonardo; Padgett, Jamie E.
2015-01-01
This study proposes a novel Normalized Wide network Ranking algorithm (NWRank) that has the advantage of ranking nodes and links of a network simultaneously. This algorithm combines the mutual reinforcement feature of Hypertext Induced Topic Selection (HITS) and the weight normalization feature of PageRank. Relative weights are assigned to links based on the degree of the adjacent neighbors and the Betweenness Centrality instead of assigning the same weight to every link as assumed in PageRank. Numerical experiment results show that NWRank performs consistently better than HITS, PageRank, eigenvector centrality, and edge betweenness from the perspective of network connectivity and approximate network flow, which is also supported by comparisons with the expensive N-1 benchmark removal criteria based on network efficiency. Furthermore, it can avoid some problems, such as the Tightly Knit Community effect, which exists in HITS. NWRank provides a new inexpensive way to rank nodes and links of a network, which has practical applications, particularly to prioritize resource allocation for upgrade of hierarchical and distributed networks, as well as to support decision making in the design of networks, where node and link importance depend on a balance of local and global integrity. PMID:26492958
NASA Astrophysics Data System (ADS)
Perotti, Juan Ignacio; Tessone, Claudio Juan; Caldarelli, Guido
2015-12-01
The quest for a quantitative characterization of community and modular structure of complex networks produced a variety of methods and algorithms to classify different networks. However, it is not clear if such methods provide consistent, robust, and meaningful results when considering hierarchies as a whole. Part of the problem is the lack of a similarity measure for the comparison of hierarchical community structures. In this work we give a contribution by introducing the hierarchical mutual information, which is a generalization of the traditional mutual information and makes it possible to compare hierarchical partitions and hierarchical community structures. The normalized version of the hierarchical mutual information should behave analogously to the traditional normalized mutual information. Here the correct behavior of the hierarchical mutual information is corroborated on an extensive battery of numerical experiments. The experiments are performed on artificial hierarchies and on the hierarchical community structure of artificial and empirical networks. Furthermore, the experiments illustrate some of the practical applications of the hierarchical mutual information, namely the comparison of different community detection methods and the study of the consistency, robustness, and temporal evolution of the hierarchical modular structure of networks.
Improved elastic medical image registration using mutual information
NASA Astrophysics Data System (ADS)
Ens, Konstantin; Schumacher, Hanno; Franz, Astrid; Fischer, Bernd
2007-03-01
One of the future-oriented areas of medical image processing is to develop fast and exact algorithms for image registration. By joining multi-modal images we are able to compensate the disadvantages of one imaging modality with the advantages of another modality. For instance, a Computed Tomography (CT) image containing the anatomy can be combined with metabolic information of a Positron Emission Tomography (PET) image. It is quite conceivable that a patient will not have the same position in both imaging systems. Furthermore some regions for instance in the abdomen can vary in shape and position due to different filling of the rectum. So a multi-modal image registration is needed to calculate a deformation field for one image in order to maximize the similarity between the two images, described by a so-called distance measure. In this work, we present a method to adapt a multi-modal distance measure, here mutual information (MI), with weighting masks. These masks are used to enhance relevant image structures and suppress image regions which otherwise would disturb the registration process. The performance of our method is tested on phantom data and real medical images.
Biochemical Machines for the Interconversion of Mutual Information and Work
NASA Astrophysics Data System (ADS)
McGrath, Thomas; Jones, Nick S.; ten Wolde, Pieter Rein; Ouldridge, Thomas E.
2017-01-01
We propose a physically realizable information-driven device consisting of an enzyme in a chemical bath, interacting with pairs of molecules prepared in correlated states. These correlations persist without direct interaction and thus store free energy equal to the mutual information. The enzyme can harness this free energy, and that stored in the individual molecular states, to do chemical work. Alternatively, the enzyme can use the chemical driving to create mutual information. A modified system can function without external intervention, approaching biological systems more closely.
Mutual information in a dilute, asymmetric neural network model
NASA Astrophysics Data System (ADS)
Greenfield, Elliot
We study the computational properties of a neural network consisting of binary neurons with dilute asymmetric synaptic connections. This simple model allows us to simulate large networks which can reflect more of the architecture and dynamics of real neural networks. Our main goal is to determine the dynamical behavior that maximizes the network's ability to perform computations. To this end, we apply information theory, measuring the average mutual information between pairs of pre- and post-synaptic neurons. Communication of information between neurons is an essential requirement for collective computation. Previous workers have demonstrated that neural networks with asymmetric connections undergo a transition from ordered to chaotic behavior as certain network parameters, such as the connectivity, are changed. We find that the average mutual information has a peak near the order-chaos transition, implying that the network can most efficiently communicate information between cells in this region. The mutual information peak becomes increasingly pronounced when the basic model is extended to incorporate more biologically realistic features, such as a variable threshold and nonlinear summation of inputs. We find that the peak in mutual information near the phase transition is a robust feature of the system for a wide range of assumptions about post-synaptic integration.
Cross Correlation versus Normalized Mutual Information on Image Registration
NASA Technical Reports Server (NTRS)
Tan, Bin; Tilton, James C.; Lin, Guoqing
2016-01-01
This is the first study to quantitatively assess and compare cross correlation and normalized mutual information methods used to register images in subpixel scale. The study shows that the normalized mutual information method is less sensitive to unaligned edges due to the spectral response differences than is cross correlation. This characteristic makes the normalized image resolution a better candidate for band to band registration. Improved band-to-band registration in the data from satellite-borne instruments will result in improved retrievals of key science measurements such as cloud properties, vegetation, snow and fire.
Link Prediction in Weighted Networks: A Weighted Mutual Information Model
Zhu, Boyao; Xia, Yongxiang
2016-01-01
The link-prediction problem is an open issue in data mining and knowledge discovery, which attracts researchers from disparate scientific communities. A wealth of methods have been proposed to deal with this problem. Among these approaches, most are applied in unweighted networks, with only a few taking the weights of links into consideration. In this paper, we present a weighted model for undirected and weighted networks based on the mutual information of local network structures, where link weights are applied to further enhance the distinguishable extent of candidate links. Empirical experiments are conducted on four weighted networks, and results show that the proposed method can provide more accurate predictions than not only traditional unweighted indices but also typical weighted indices. Furthermore, some in-depth discussions on the effects of weak ties in link prediction as well as the potential to predict link weights are also given. This work may shed light on the design of algorithms for link prediction in weighted networks. PMID:26849659
Magnetotelluric inversion based on mutual information
NASA Astrophysics Data System (ADS)
Mandolesi, Eric; Jones, Alan G.
2014-10-01
Joint inversion of different geophysical data sets is becoming a more popular and powerful tool, and it has been performed on data sensitive both to the same physical parameter and to different physical parameters. Joint inversion is undertaken to reduce acceptable model space and to increase sensitivity to model parameters that one method alone is unable to resolve adequately. We examine and implement a novel hybrid joint inversion approach. In our inversion scheme a model-the reference model-is fixed, and the information shared with the subsurface structure obtained from another method will be maximized; in our case conductivity structures from magnetotelluric (MT) inversion. During inversion, the joint probability distribution of the MT and the specified reference model is estimated and its entropy minimized in order to guide the inversion result towards a solution that is statistically compatible with the reference model. The powerful feature of this technique is that no explicit relationships between estimated model parameters and reference model ones are presumed: if a link exists in data then it is highlighted in the estimation of the joint probability distribution, if no link is required, then none is enforced. Tests performed verify the robustness of this method and the advantages of it in a 1-D anisotropic scenario are demonstrated. A case study was performed with data from Central Germany, effectively fitting an MT data set from a single station within as minimal an amount of anisotropy as required.
Mutual information area laws for thermal free fermions
NASA Astrophysics Data System (ADS)
Bernigau, H.; Kastoryano, M. J.; Eisert, J.
2015-02-01
We provide a rigorous and asymptotically exact expression of the mutual information of translationally invariant free fermionic lattice systems in a Gibbs state. In order to arrive at this result, we introduce a novel framework for computing determinants of Töplitz operators with smooth symbols, and for treating Töplitz matrices with system size dependent entries. The asymptotically exact mutual information for a partition of the 1D lattice satisfies an area law, with a prefactor which we compute explicitly. As examples, we discuss the fermionic XX model in one dimension and free fermionic models on the torus in higher dimensions in detail. Special emphasis is put on the discussion of the temperature dependence of the mutual information, scaling like the logarithm of the inverse temperature, hence confirming an expression suggested by conformal field theory. We also comment on the applicability of the formalism to treat open systems driven by quantum noise. In the appendix, we derive useful bounds to the mutual information in terms of purities. Finally, we provide a detailed error analysis for finite system sizes. This analysis is valuable in its own right for the abstract theory of Töplitz determinants.
Using Mutual Information for Adaptive Item Comparison and Student Assessment
ERIC Educational Resources Information Center
Liu, Chao-Lin
2005-01-01
The author analyzes properties of mutual information between dichotomous concepts and test items. The properties generalize some common intuitions about item comparison, and provide principled foundations for designing item-selection heuristics for student assessment in computer-assisted educational systems. The proposed item-selection strategies…
Mutual Information Item Selection in Adaptive Classification Testing
ERIC Educational Resources Information Center
Weissman, Alexander
2007-01-01
A general approach for item selection in adaptive multiple-category classification tests is provided. The approach uses mutual information (MI), a special case of the Kullback-Leibler distance, or relative entropy. MI works efficiently with the sequential probability ratio test and alleviates the difficulties encountered with using other local-…
Extracting an entanglement signature from only classical mutual information
NASA Astrophysics Data System (ADS)
Starling, David J.; Broadbent, Curtis J.; Howell, John C.
2011-09-01
We introduce a quantity which is formed using classical notions of mutual information and which is computed using the results of projective measurements. This quantity constitutes a sufficient condition for entanglement and represents the amount of information that can be extracted from a bipartite system for spacelike separated observers. In addition to discussion, we provide simulations as well as experimental results for the singlet and maximally correlated mixed states.
Extracting an entanglement signature from only classical mutual information
Starling, David J.; Howell, John C.; Broadbent, Curtis J.
2011-09-15
We introduce a quantity which is formed using classical notions of mutual information and which is computed using the results of projective measurements. This quantity constitutes a sufficient condition for entanglement and represents the amount of information that can be extracted from a bipartite system for spacelike separated observers. In addition to discussion, we provide simulations as well as experimental results for the singlet and maximally correlated mixed states.
Feature selection based on fusing mutual information and cross-validation
NASA Astrophysics Data System (ADS)
Li, Wei-wei; Liu, Chun-ping; Chen, Ning-qiang; Wang, Zhao-hui
2009-10-01
Many algorithms have been proposed in literature for feature selection; unfortunately, none of them ensures a perfect result. Here we propose an adaptive sequential floating forward feature selection algorithm which achieves accuracy results higher than that of already existing algorithms and naturally adaptive for implementation into the number of best feature subset to be selected. The basic idea of the proposed algorithm is to adopt two relatively well-settled algorithms for the problem at hand and combine mutual information and Cross-Validation through suitable fusion techniques, with the aim of taking advantage of the adopted algorithms' capabilities, at the same time, limiting their deficiencies. This method adaptively obtains the number of features to be selected according to dimensions of original feature set, and Dempster-Shafer Evidential Theory is used to fuse Max-Relevance, Min-Redundancy and CVFS. Extensive experiments show that the higher accuracy of classification and the less redundancy of features could be achieved.
NASA Astrophysics Data System (ADS)
Grieggs, Samuel M.; McLaughlin, Michael J.; Ezekiel, Soundararajan; Blasch, Erik
2015-06-01
As technology and internet use grows at an exponential rate, video and imagery data is becoming increasingly important. Various techniques such as Wide Area Motion imagery (WAMI), Full Motion Video (FMV), and Hyperspectral Imaging (HSI) are used to collect motion data and extract relevant information. Detecting and identifying a particular object in imagery data is an important step in understanding visual imagery, such as content-based image retrieval (CBIR). Imagery data is segmented and automatically analyzed and stored in dynamic and robust database. In our system, we seek utilize image fusion methods which require quality metrics. Many Image Fusion (IF) algorithms have been proposed based on different, but only a few metrics, used to evaluate the performance of these algorithms. In this paper, we seek a robust, objective metric to evaluate the performance of IF algorithms which compares the outcome of a given algorithm to ground truth and reports several types of errors. Given the ground truth of a motion imagery data, it will compute detection failure, false alarm, precision and recall metrics, background and foreground regions statistics, as well as split and merge of foreground regions. Using the Structural Similarity Index (SSIM), Mutual Information (MI), and entropy metrics; experimental results demonstrate the effectiveness of the proposed methodology for object detection, activity exploitation, and CBIR.
Fatakia, Sarosh N.; Costanzi, Stefano; Chow, Carson C.
2009-01-01
G protein-coupled receptors (GPCRs) are a superfamily of seven transmembrane-spanning proteins involved in a wide array of physiological functions and are the most common targets of pharmaceuticals. This study aims to identify a cohort or clique of positions that share high mutual information. Using a multiple sequence alignment of the transmembrane (TM) domains, we calculated the mutual information between all inter-TM pairs of aligned positions and ranked the pairs by mutual information. A mutual information graph was constructed with vertices that corresponded to TM positions and edges between vertices were drawn if the mutual information exceeded a threshold of statistical significance. Positions with high degree (i.e. had significant mutual information with a large number of other positions) were found to line a well defined inter-TM ligand binding cavity for class A as well as class C GPCRs. Although the natural ligands of class C receptors bind to their extracellular N-terminal domains, the possibility of modulating their activity through ligands that bind to their helical bundle has been reported. Such positions were not found for class B GPCRs, in agreement with the observation that there are not known ligands that bind within their TM helical bundle. All identified key positions formed a clique within the MI graph of interest. For a subset of class A receptors we also considered the alignment of a portion of the second extracellular loop, and found that the two positions adjacent to the conserved Cys that bridges the loop with the TM3 qualified as key positions. Our algorithm may be useful for localizing topologically conserved regions in other protein families. PMID:19262747
Bias reduction in the estimation of mutual information.
Zhu, Jie; Bellanger, Jean-Jacques; Shu, Huazhong; Yang, Chunfeng; Le Bouquin Jeannès, Régine
2014-11-01
This paper deals with the control of bias estimation when estimating mutual information from a nonparametric approach. We focus on continuously distributed random data and the estimators we developed are based on a nonparametric k-nearest-neighbor approach for arbitrary metrics. Using a multidimensional Taylor series expansion, a general relationship between the estimation error bias and the neighboring size for the plug-in entropy estimator is established without any assumption on the data for two different norms. The theoretical analysis based on the maximum norm developed coincides with the experimental results drawn from numerical tests made by Kraskov et al. [Phys. Rev. E 69, 066138 (2004)PLEEE81539-375510.1103/PhysRevE.69.066138]. To further validate the novel relation, a weighted linear combination of distinct mutual information estimators is proposed and, using simulated signals, the comparison of different strategies allows for corroborating the theoretical analysis.
Bias reduction in the estimation of mutual information
NASA Astrophysics Data System (ADS)
Zhu, Jie; Bellanger, Jean-Jacques; Shu, Huazhong; Yang, Chunfeng; Le Bouquin Jeannès, Régine
2014-11-01
This paper deals with the control of bias estimation when estimating mutual information from a nonparametric approach. We focus on continuously distributed random data and the estimators we developed are based on a nonparametric k -nearest-neighbor approach for arbitrary metrics. Using a multidimensional Taylor series expansion, a general relationship between the estimation error bias and the neighboring size for the plug-in entropy estimator is established without any assumption on the data for two different norms. The theoretical analysis based on the maximum norm developed coincides with the experimental results drawn from numerical tests made by Kraskov et al. [Phys. Rev. E 69, 066138 (2004), 10.1103/PhysRevE.69.066138]. To further validate the novel relation, a weighted linear combination of distinct mutual information estimators is proposed and, using simulated signals, the comparison of different strategies allows for corroborating the theoretical analysis.
Networks in financial markets based on the mutual information rate
NASA Astrophysics Data System (ADS)
Fiedor, Paweł
2014-05-01
In the last few years there have been many efforts in econophysics studying how network theory can facilitate understanding of complex financial markets. These efforts consist mainly of the study of correlation-based hierarchical networks. This is somewhat surprising as the underlying assumptions of research looking at financial markets are that they are complex systems and thus behave in a nonlinear manner, which is confirmed by numerous studies, making the use of correlations which are inherently dealing with linear dependencies only baffling. In this paper we introduce a way to incorporate nonlinear dynamics and dependencies into hierarchical networks to study financial markets using mutual information and its dynamical extension: the mutual information rate. We show that this approach leads to different results than the correlation-based approach used in most studies, on the basis of 91 companies listed on the New York Stock Exchange 100 between 2003 and 2013, using minimal spanning trees and planar maximally filtered graphs.
Networks in financial markets based on the mutual information rate.
Fiedor, Paweł
2014-05-01
In the last few years there have been many efforts in econophysics studying how network theory can facilitate understanding of complex financial markets. These efforts consist mainly of the study of correlation-based hierarchical networks. This is somewhat surprising as the underlying assumptions of research looking at financial markets are that they are complex systems and thus behave in a nonlinear manner, which is confirmed by numerous studies, making the use of correlations which are inherently dealing with linear dependencies only baffling. In this paper we introduce a way to incorporate nonlinear dynamics and dependencies into hierarchical networks to study financial markets using mutual information and its dynamical extension: the mutual information rate. We show that this approach leads to different results than the correlation-based approach used in most studies, on the basis of 91 companies listed on the New York Stock Exchange 100 between 2003 and 2013, using minimal spanning trees and planar maximally filtered graphs.
Optimization of stable quadruped locomotion using mutual information
NASA Astrophysics Data System (ADS)
Silva, Pedro; Santos, Cristina P.; Polani, Daniel
2013-10-01
Central Pattern Generators (CPG)s have been widely used in the field of robotics to address the task of legged locomotion generation. The adequate configuration of these structures for a given platform can be accessed through evolutionary strategies, according to task dependent selection pressures. Information driven evolution, accounts for information theoretical measures as selection pressures, as an alternative to a fully task dependent selection pressure. In this work we exploit this concept and evaluate the use of mean Mutual Information, as a selection pressure towards a CPG configuration capable of faster, yet more coordinated and stabler locomotion than when only a task dependent selection pressure is used.
Feature Selection for Chemical Sensor Arrays Using Mutual Information
Wang, X. Rosalind; Lizier, Joseph T.; Nowotny, Thomas; Berna, Amalia Z.; Prokopenko, Mikhail; Trowell, Stephen C.
2014-01-01
We address the problem of feature selection for classifying a diverse set of chemicals using an array of metal oxide sensors. Our aim is to evaluate a filter approach to feature selection with reference to previous work, which used a wrapper approach on the same data set, and established best features and upper bounds on classification performance. We selected feature sets that exhibit the maximal mutual information with the identity of the chemicals. The selected features closely match those found to perform well in the previous study using a wrapper approach to conduct an exhaustive search of all permitted feature combinations. By comparing the classification performance of support vector machines (using features selected by mutual information) with the performance observed in the previous study, we found that while our approach does not always give the maximum possible classification performance, it always selects features that achieve classification performance approaching the optimum obtained by exhaustive search. We performed further classification using the selected feature set with some common classifiers and found that, for the selected features, Bayesian Networks gave the best performance. Finally, we compared the observed classification performances with the performance of classifiers using randomly selected features. We found that the selected features consistently outperformed randomly selected features for all tested classifiers. The mutual information filter approach is therefore a computationally efficient method for selecting near optimal features for chemical sensor arrays. PMID:24595058
Part mutual information for quantifying direct associations in networks.
Zhao, Juan; Zhou, Yiwei; Zhang, Xiujun; Chen, Luonan
2016-05-03
Quantitatively identifying direct dependencies between variables is an important task in data analysis, in particular for reconstructing various types of networks and causal relations in science and engineering. One of the most widely used criteria is partial correlation, but it can only measure linearly direct association and miss nonlinear associations. However, based on conditional independence, conditional mutual information (CMI) is able to quantify nonlinearly direct relationships among variables from the observed data, superior to linear measures, but suffers from a serious problem of underestimation, in particular for those variables with tight associations in a network, which severely limits its applications. In this work, we propose a new concept, "partial independence," with a new measure, "part mutual information" (PMI), which not only can overcome the problem of CMI but also retains the quantification properties of both mutual information (MI) and CMI. Specifically, we first defined PMI to measure nonlinearly direct dependencies between variables and then derived its relations with MI and CMI. Finally, we used a number of simulated data as benchmark examples to numerically demonstrate PMI features and further real gene expression data from Escherichia coli and yeast to reconstruct gene regulatory networks, which all validated the advantages of PMI for accurately quantifying nonlinearly direct associations in networks.
Permutation auto-mutual information of electroencephalogram in anesthesia
NASA Astrophysics Data System (ADS)
Liang, Zhenhu; Wang, Yinghua; Ouyang, Gaoxiang; Voss, Logan J.; Sleigh, Jamie W.; Li, Xiaoli
2013-04-01
Objective. The dynamic change of brain activity in anesthesia is an interesting topic for clinical doctors and drug designers. To explore the dynamical features of brain activity in anesthesia, a permutation auto-mutual information (PAMI) method is proposed to measure the information coupling of electroencephalogram (EEG) time series obtained in anesthesia. Approach. The PAMI is developed and applied on EEG data collected from 19 patients under sevoflurane anesthesia. The results are compared with the traditional auto-mutual information (AMI), SynchFastSlow (SFS, derived from the BIS index), permutation entropy (PE), composite PE (CPE), response entropy (RE) and state entropy (SE). Performance of all indices is assessed by pharmacokinetic/pharmacodynamic (PK/PD) modeling and prediction probability. Main results. The PK/PD modeling and prediction probability analysis show that the PAMI index correlates closely with the anesthetic effect. The coefficient of determination R2 between PAMI values and the sevoflurane effect site concentrations, and the prediction probability Pk are higher in comparison with other indices. The information coupling in EEG series can be applied to indicate the effect of the anesthetic drug sevoflurane on the brain activity as well as other indices. The PAMI of the EEG signals is suggested as a new index to track drug concentration change. Significance. The PAMI is a useful index for analyzing the EEG dynamics during general anesthesia.
Mutual information model for link prediction in heterogeneous complex networks
Shakibian, Hadi; Moghadam Charkari, Nasrollah
2017-01-01
Recently, a number of meta-path based similarity indices like PathSim, HeteSim, and random walk have been proposed for link prediction in heterogeneous complex networks. However, these indices suffer from two major drawbacks. Firstly, they are primarily dependent on the connectivity degrees of node pairs without considering the further information provided by the given meta-path. Secondly, most of them are required to use a single and usually symmetric meta-path in advance. Hence, employing a set of different meta-paths is not straightforward. To tackle with these problems, we propose a mutual information model for link prediction in heterogeneous complex networks. The proposed model, called as Meta-path based Mutual Information Index (MMI), introduces meta-path based link entropy to estimate the link likelihood and could be carried on a set of available meta-paths. This estimation measures the amount of information through the paths instead of measuring the amount of connectivity between the node pairs. The experimental results on a Bibliography network show that the MMI obtains high prediction accuracy compared with other popular similarity indices. PMID:28344326
Estimation and classification by sigmoids based on mutual information
NASA Technical Reports Server (NTRS)
Baram, Yoram
1994-01-01
An estimate of the probability density function of a random vector is obtained by maximizing the mutual information between the input and the output of a feedforward network of sigmoidal units with respect to the input weights. Classification problems can be solved by selecting the class associated with the maximal estimated density. Newton's s method, applied to an estimated density, yields a recursive maximum likelihood estimator, consisting of a single internal layer of sigmoids, for a random variable or a random sequence. Applications to the diamond classification and to the prediction of a sun-spot process are demonstrated.
Mutual information measures applied to EEG signals for sleepiness characterization.
Melia, Umberto; Guaita, Marc; Vallverdú, Montserrat; Embid, Cristina; Vilaseca, Isabel; Salamero, Manel; Santamaria, Joan
2015-03-01
Excessive daytime sleepiness (EDS) is one of the main symptoms of several sleep related disorders with a great impact on the patient lives. While many studies have been carried out in order to assess daytime sleepiness, the automatic EDS detection still remains an open problem. In this work, a novel approach to this issue based on non-linear dynamical analysis of EEG signal was proposed. Multichannel EEG signals were recorded during five maintenance of wakefulness (MWT) and multiple sleep latency (MSLT) tests alternated throughout the day from patients suffering from sleep disordered breathing. A group of 20 patients with excessive daytime sleepiness (EDS) was compared with a group of 20 patients without daytime sleepiness (WDS), by analyzing 60-s EEG windows in waking state. Measures obtained from cross-mutual information function (CMIF) and auto-mutual-information function (AMIF) were calculated in the EEG. These functions permitted a quantification of the complexity properties of the EEG signal and the non-linear couplings between different zones of the scalp. Statistical differences between EDS and WDS groups were found in β band during MSLT events (p-value < 0.0001). WDS group presented more complexity than EDS in the occipital zone, while a stronger nonlinear coupling between occipital and frontal zones was detected in EDS patients than in WDS. The AMIF and CMIF measures yielded sensitivity and specificity above 80% and AUC of ROC above 0.85 in classifying EDS and WDS patients.
Classical mutual information in mean-field spin glass models
NASA Astrophysics Data System (ADS)
Alba, Vincenzo; Inglis, Stephen; Pollet, Lode
2016-03-01
We investigate the classical Rényi entropy Sn and the associated mutual information In in the Sherrington-Kirkpatrick (S-K) model, which is the paradigm model of mean-field spin glasses. Using classical Monte Carlo simulations and analytical tools we investigate the S-K model in the n -sheet booklet. This is achieved by gluing together n independent copies of the model, and it is the main ingredient for constructing the Rényi entanglement-related quantities. We find a glassy phase at low temperatures, whereas at high temperatures the model exhibits paramagnetic behavior, consistent with the regular S-K model. The temperature of the paramagnetic-glassy transition depends nontrivially on the geometry of the booklet. At high temperatures we provide the exact solution of the model by exploiting the replica symmetry. This is the permutation symmetry among the fictitious replicas that are used to perform disorder averages (via the replica trick). In the glassy phase the replica symmetry has to be broken. Using a generalization of the Parisi solution, we provide analytical results for Sn and In and for standard thermodynamic quantities. Both Sn and In exhibit a volume law in the whole phase diagram. We characterize the behavior of the corresponding densities, Sn/N and In/N , in the thermodynamic limit. Interestingly, at the critical point the mutual information does not exhibit any crossing for different system sizes, in contrast with local spin models.
Mutual information and redundancy in spontaneous communication between cortical neurons.
Szczepanski, J; Arnold, M; Wajnryb, E; Amigó, J M; Sanchez-Vives, M V
2011-03-01
An important question in neural information processing is how neurons cooperate to transmit information. To study this question, we resort to the concept of redundancy in the information transmitted by a group of neurons and, at the same time, we introduce a novel concept for measuring cooperation between pairs of neurons called relative mutual information (RMI). Specifically, we studied these two parameters for spike trains generated by neighboring neurons from the primary visual cortex in the awake, freely moving rat. The spike trains studied here were spontaneously generated in the cortical network, in the absence of visual stimulation. Under these conditions, our analysis revealed that while the value of RMI oscillated slightly around an average value, the redundancy exhibited a behavior characterized by a higher variability. We conjecture that this combination of approximately constant RMI and greater variable redundancy makes information transmission more resistant to noise disturbances. Furthermore, the redundancy values suggest that neurons can cooperate in a flexible way during information transmission. This mostly occurs via a leading neuron with higher transmission rate or, less frequently, through the information rate of the whole group being higher than the sum of the individual information rates-in other words in a synergetic manner. The proposed method applies not only to the stationary, but also to locally stationary neural signals.
MIDER: Network Inference with Mutual Information Distance and Entropy Reduction
Villaverde, Alejandro F.; Ross, John; Morán, Federico; Banga, Julio R.
2014-01-01
The prediction of links among variables from a given dataset is a task referred to as network inference or reverse engineering. It is an open problem in bioinformatics and systems biology, as well as in other areas of science. Information theory, which uses concepts such as mutual information, provides a rigorous framework for addressing it. While a number of information-theoretic methods are already available, most of them focus on a particular type of problem, introducing assumptions that limit their generality. Furthermore, many of these methods lack a publicly available implementation. Here we present MIDER, a method for inferring network structures with information theoretic concepts. It consists of two steps: first, it provides a representation of the network in which the distance among nodes indicates their statistical closeness. Second, it refines the prediction of the existing links to distinguish between direct and indirect interactions and to assign directionality. The method accepts as input time-series data related to some quantitative features of the network nodes (such as e.g. concentrations, if the nodes are chemical species). It takes into account time delays between variables, and allows choosing among several definitions and normalizations of mutual information. It is general purpose: it may be applied to any type of network, cellular or otherwise. A Matlab implementation including source code and data is freely available (http://www.iim.csic.es/~gingproc/mider.html). The performance of MIDER has been evaluated on seven different benchmark problems that cover the main types of cellular networks, including metabolic, gene regulatory, and signaling. Comparisons with state of the art information–theoretic methods have demonstrated the competitive performance of MIDER, as well as its versatility. Its use does not demand any a priori knowledge from the user; the default settings and the adaptive nature of the method provide good results for a wide
Mortazavi, Atiyeh; Moattar, Mohammad Hossein
2016-01-01
High dimensionality of microarray data sets may lead to low efficiency and overfitting. In this paper, a multiphase cooperative game theoretic feature selection approach is proposed for microarray data classification. In the first phase, due to high dimension of microarray data sets, the features are reduced using one of the two filter-based feature selection methods, namely, mutual information and Fisher ratio. In the second phase, Shapley index is used to evaluate the power of each feature. The main innovation of the proposed approach is to employ Qualitative Mutual Information (QMI) for this purpose. The idea of Qualitative Mutual Information causes the selected features to have more stability and this stability helps to deal with the problem of data imbalance and scarcity. In the third phase, a forward selection scheme is applied which uses a scoring function to weight each feature. The performance of the proposed method is compared with other popular feature selection algorithms such as Fisher ratio, minimum redundancy maximum relevance, and previous works on cooperative game based feature selection. The average classification accuracy on eleven microarray data sets shows that the proposed method improves both average accuracy and average stability compared to other approaches. PMID:27127506
Mortazavi, Atiyeh; Moattar, Mohammad Hossein
2016-01-01
High dimensionality of microarray data sets may lead to low efficiency and overfitting. In this paper, a multiphase cooperative game theoretic feature selection approach is proposed for microarray data classification. In the first phase, due to high dimension of microarray data sets, the features are reduced using one of the two filter-based feature selection methods, namely, mutual information and Fisher ratio. In the second phase, Shapley index is used to evaluate the power of each feature. The main innovation of the proposed approach is to employ Qualitative Mutual Information (QMI) for this purpose. The idea of Qualitative Mutual Information causes the selected features to have more stability and this stability helps to deal with the problem of data imbalance and scarcity. In the third phase, a forward selection scheme is applied which uses a scoring function to weight each feature. The performance of the proposed method is compared with other popular feature selection algorithms such as Fisher ratio, minimum redundancy maximum relevance, and previous works on cooperative game based feature selection. The average classification accuracy on eleven microarray data sets shows that the proposed method improves both average accuracy and average stability compared to other approaches.
Extending the scope of holographic mutual information and chaotic behavior
NASA Astrophysics Data System (ADS)
Sircar, Nilanjan; Sonnenschein, Jacob; Tangarife, Walter
2016-05-01
We extend the use of holography to investigate the scrambling properties of various physical systems. Specifically, we consider: (i) non-conformal backgrounds of black Dp branes, (ii) asymptotically Lifshitz black holes, and (iii) black AdS solutions of Gauss-Bonnet gravity. We use the disruption of the entanglement entropy as a probe of the chaotic features of such systems. Our analysis shows that these theories share the same type of behavior as conformal theories as they undergo chaos; however, in the case of Gauss-Bonnet gravity, we find a stark difference in the evolution of the mutual information for negative Gauss-Bonnet coupling. This may signal an inconsistency of the latter.
Naghibi, Tofigh; Hoffmann, Sarah; Pfister, Beat
2015-08-01
Feature subset selection, as a special case of the general subset selection problem, has been the topic of a considerable number of studies due to the growing importance of data-mining applications. In the feature subset selection problem there are two main issues that need to be addressed: (i) Finding an appropriate measure function than can be fairly fast and robustly computed for high-dimensional data. (ii) A search strategy to optimize the measure over the subset space in a reasonable amount of time. In this article mutual information between features and class labels is considered to be the measure function. Two series expansions for mutual information are proposed, and it is shown that most heuristic criteria suggested in the literature are truncated approximations of these expansions. It is well-known that searching the whole subset space is an NP-hard problem. Here, instead of the conventional sequential search algorithms, we suggest a parallel search strategy based on semidefinite programming (SDP) that can search through the subset space in polynomial time. By exploiting the similarities between the proposed algorithm and an instance of the maximum-cut problem in graph theory, the approximation ratio of this algorithm is derived and is compared with the approximation ratio of the backward elimination method. The experiments show that it can be misleading to judge the quality of a measure solely based on the classification accuracy, without taking the effect of the non-optimum search strategy into account.
NASA Astrophysics Data System (ADS)
Diamant, Idit; Shalhon, Moran; Goldberger, Jacob; Greenspan, Hayit
2016-03-01
Classification of clustered breast microcalcifications into benign and malignant categories is an extremely challenging task for computerized algorithms and expert radiologists alike. In this paper we present a novel method for feature selection based on mutual information (MI) criterion for automatic classification of microcalcifications. We explored the MI based feature selection for various texture features. The proposed method was evaluated on a standardized digital database for screening mammography (DDSM). Experimental results demonstrate the effectiveness and the advantage of using the MI-based feature selection to obtain the most relevant features for the task and thus to provide for improved performance as compared to using all features.
Van Hecke, Wim; Leemans, Alexander; D'Agostino, Emiliano; De Backer, Steve; Vandervliet, Evert; Parizel, Paul M; Sijbers, Jan
2007-11-01
In this paper, a nonrigid coregistration algorithm based on a viscous fluid model is proposed that has been optimized for diffusion tensor images (DTI), in which image correspondence is measured by the mutual information criterion. Several coregistration strategies are introduced and evaluated both on simulated data and on brain intersubject DTI data. Two tensor reorientation methods have been incorporated and quantitatively evaluated. Simulation as well as experimental results show that the proposed viscous fluid model can provide a high coregistration accuracy, although the tensor reorientation was observed to be highly sensitive to the local deformation field. Nevertheless, this coregistration method has demonstrated to significantly improve spatial alignment compared to affine image matching.
Conditional mutual information of bipartite unitaries and scrambling
NASA Astrophysics Data System (ADS)
Ding, Dawei; Hayden, Patrick; Walter, Michael
2016-12-01
One way to diagnose chaos in bipartite unitary channels is via the tripartite information of the corresponding Choi state, which for certain choices of the subsystems reduces to the negative conditional mutual information (CMI). We study this quantity from a quantum information-theoretic perspective to clarify its role in diagnosing scrambling. When the CMI is zero, we find that the channel has a special normal form consisting of local channels between individual inputs and outputs. However, we find that arbitrarily low CMI does not imply arbitrary proximity to a channel of this form, although it does imply a type of approximate recoverability of one of the inputs. When the CMI is maximal, we find that the residual channel from an individual input to an individual output is completely depolarizing when the other input is maximally mixed. However, we again find that this result is not robust. We also extend some of these results to the multipartite case and to the case of Haar-random pure input states. Finally, we look at the relationship between tripartite information and its Rényi-2 version which is directly related to out-of-time-order correlation functions. In particular, we demonstrate an arbitrarily large gap between the two quantities.
NASA Astrophysics Data System (ADS)
Zhao, Xiaojun; Shang, Pengjian; Lin, Aijing
2017-02-01
In this paper, we propose a new method to measure the influence of a third variable on the interactions of two variables. The method called transfer mutual information (TMI) is defined by the difference between the mutual information and the partial mutual information. It is established on the assumption that if the presence or the absence of one variable does make change to the interactions of another two variables, then quantifying this change is supposed to be the influence from this variable to those two variables. Moreover, a normalized TMI and other derivatives of the TMI are introduced as well. The empirical analysis including the simulations as well as real-world applications is investigated to examine this measure and to reveal more information among variables.
Mutual information-based feature selection for radiomics
NASA Astrophysics Data System (ADS)
Oubel, Estanislao; Beaumont, Hubert; Iannessi, Antoine
2016-03-01
Background The extraction and analysis of image features (radiomics) is a promising field in the precision medicine era, with applications to prognosis, prediction, and response to treatment quantification. In this work, we present a mutual information - based method for quantifying reproducibility of features, a necessary step for qualification before their inclusion in big data systems. Materials and Methods Ten patients with Non-Small Cell Lung Cancer (NSCLC) lesions were followed over time (7 time points in average) with Computed Tomography (CT). Five observers segmented lesions by using a semi-automatic method and 27 features describing shape and intensity distribution were extracted. Inter-observer reproducibility was assessed by computing the multi-information (MI) of feature changes over time, and the variability of global extrema. Results The highest MI values were obtained for volume-based features (VBF). The lesion mass (M), surface to volume ratio (SVR) and volume (V) presented statistically significant higher values of MI than the rest of features. Within the same VBF group, SVR showed also the lowest variability of extrema. The correlation coefficient (CC) of feature values was unable to make a difference between features. Conclusions MI allowed to discriminate three features (M, SVR, and V) from the rest in a statistically significant manner. This result is consistent with the order obtained when sorting features by increasing values of extrema variability. MI is a promising alternative for selecting features to be considered as surrogate biomarkers in a precision medicine context.
Abnormal functional connectivity in focal hand dystonia: mutual information analysis in EEG.
Jin, Seung-Hyun; Lin, Peter; Auh, Sungyoung; Hallett, Mark
2011-06-01
The aim of the present study was to investigate functional connectivity in focal hand dystonia patients to understand the pathophysiology underlying their abnormality in movement. We recorded EEGs from 58 electrodes in 15 focal hand dystonia patients and 15 healthy volunteers during rest and a simple finger-tapping task that did not induce any dystonic symptoms. We investigated mutual information, which provides a quantitative measure of linear and nonlinear coupling, in the alpha, beta, and gamma bands. Mean mutual information of all 58 channels and mean of the channels of interest representative of regional functional connectivity over sensorimotor areas (C3, CP3, C4, CP4, FCz, and Cz) were evaluated. For both groups, we found enhanced mutual information during the task compared with the rest condition, specifically in the beta and gamma bands for mean mutual information of all channels, and in all bands for mean mutual information of channels of interest. Comparing the focal hand dystonia patients with the healthy volunteers for both rest and task, there was reduced mutual information in the beta band for both mean mutual information of all channels and mean mutual information of channels of interest. Regarding the properties of the connectivity in the beta band, we found that the majority of the mutual information differences were from linear connectivity. The abnormal beta-band functional connectivity in focal hand dystonia patients suggests deficient brain connectivity.
Analysis of fMRI time series with mutual information.
Gómez-Verdejo, Vanessa; Martínez-Ramón, Manel; Florensa-Vila, José; Oliviero, Antonio
2012-02-01
Neuroimaging plays a fundamental role in the study of human cognitive neuroscience. Functional magnetic resonance imaging (fMRI), based on the Blood Oxygenation Level Dependent signal, is currently considered as a standard technique for a system level understanding of the human brain. The problem of identifying regionally specific effects in neuroimaging data is usually solved by applying Statistical Parametric Mapping (SPM). Here, a mutual information (MI) criterion is used to identify regionally specific effects produced by a task. In particular, two MI estimators are presented for its use in fMRI data. The first one uses a Parzen probability density estimation, and the second one is based on a K Nearest Neighbours (KNN) estimation. Additionally, a statistical measure has been introduced to automatically detect the voxels which are relevant to the fMRI task. Experiments demonstrate the advantages of MI estimators over SPM maps; firstly, providing more significant differences between relevant and irrelevant voxels; secondly, presenting more focalized activation; and, thirdly, detecting small areas related to the task. These findings, and the improved performance of KNN MI estimator in multisubject and multistimuli studies, make the proposed methods a good alternative to SPM.
NSECT sinogram sampling optimization by normalized mutual information
NASA Astrophysics Data System (ADS)
Viana, Rodrigo S.; Galarreta-Valverde, Miguel A.; Mekkaoui, Choukri; Yoriyaz, Hélio; Jackowski, Marcel P.
2015-03-01
Neutron Stimulated Emission Computed Tomography (NSECT) is an emerging noninvasive imaging technique that measures the distribution of isotopes from biological tissue using fast-neutron inelastic scattering reaction. As a high-energy neutron beam illuminates the sample, the excited nuclei emit gamma rays whose energies are unique to the emitting nuclei. Tomographic images of each element in the spectrum can then be reconstructed to represent the spatial distribution of elements within the sample using a first generation tomographic scan. NSECT's high radiation dose deposition, however, requires a sampling strategy that can yield maximum image quality under a reasonable radiation dose. In this work, we introduce an NSECT sinogram sampling technique based on the Normalized Mutual Information (NMI) of the reconstructed images. By applying the Radon Transform on the ground-truth image obtained from a carbon-based synthetic phantom, different NSECT sinogram configurations were simulated and compared by using the NMI as a similarity measure. The proposed methodology was also applied on NSECT images acquired using MCNP5 Monte Carlo simulations of the same phantom to validate our strategy. Results show that NMI can be used to robustly predict the quality of the reconstructed NSECT images, leading to an optimal NSECT acquisition and a minimal absorbed dose by the patient.
Solar flux forecasting using mutual information with an optimal delay
NASA Technical Reports Server (NTRS)
Ashrafi, S.; Conway, D.; Rokni, M.; Sperling, R.; Roszman, L.; Cooley, J.
1993-01-01
Solar flux F(sub 10.7) directly affects the atmospheric density, thereby changing the lifetime and prediction of satellite orbits. For this reason, accurate forecasting of F(sub 10.7) is crucial for orbit determination of spacecraft. Our attempts to model and forecast F(sub 10.7) uncovered highly entangled dynamics. We concluded that the general lack of predictability in solar activity arises from its nonlinear nature. Nonlinear dynamics allow us to predict F(sub 10.7) more accurately than is possible using stochastic methods for time scales shorter than a characteristic horizon, and with about the same accuracy as using stochastic techniques when the forecasted data exceed this horizon. The forecast horizon is a function of two dynamical invariants: the attractor dimension and the Lyapunov exponent. In recent years, estimation of the attractor dimension reconstructed from a time series has become an important tool in data analysis. In calculating the invariants of the system, the first necessary step is the reconstruction of the attractor for the system from the time-delayed values of the time series. The choice of the time delay is critical for this reconstruction. For an infinite amount of noise-free data, the time delay can, in principle, be chosen almost arbitrarily. However, the quality of the phase portraits produced using the time-delay technique is determined by the value chosen for the delay time. Fraser and Swinney have shown that a good choice for this time delay is the one suggested by Shaw, which uses the first local minimum of the mutual information rather than the autocorrelation function to determine the time delay. This paper presents a refinement of this criterion and applies the refined technique to solar flux data to produce a forecast of the solar activity.
Klein, Stefan; Staring, Marius; Pluim, Josien P W
2007-12-01
A popular technique for nonrigid registration of medical images is based on the maximization of their mutual information, in combination with a deformation field parameterized by cubic B-splines. The coordinate mapping that relates the two images is found using an iterative optimization procedure. This work compares the performance of eight optimization methods: gradient descent (with two different step size selection algorithms), quasi-Newton, nonlinear conjugate gradient, Kiefer-Wolfowitz, simultaneous perturbation, Robbins-Monro, and evolution strategy. Special attention is paid to computation time reduction by using fewer voxels to calculate the cost function and its derivatives. The optimization methods are tested on manually deformed CT images of the heart, on follow-up CT chest scans, and on MR scans of the prostate acquired using a BFFE, T1, and T2 protocol. Registration accuracy is assessed by computing the overlap of segmented edges. Precision and convergence properties are studied by comparing deformation fields. The results show that the Robbins-Monro method is the best choice in most applications. With this approach, the computation time per iteration can be lowered approximately 500 times without affecting the rate of convergence by using a small subset of the image, randomly selected in every iteration, to compute the derivative of the mutual information. From the other methods the quasi-Newton and the nonlinear conjugate gradient method achieve a slightly higher precision, at the price of larger computation times.
CSMMI: class-specific maximization of mutual information for action and gesture recognition.
Wan, Jun; Athitsos, Vassilis; Jangyodsuk, Pat; Escalante, Hugo Jair; Ruan, Qiuqi; Guyon, Isabelle
2014-07-01
In this paper, we propose a novel approach called class-specific maximization of mutual information (CSMMI) using a submodular method, which aims at learning a compact and discriminative dictionary for each class. Unlike traditional dictionary-based algorithms, which typically learn a shared dictionary for all of the classes, we unify the intraclass and interclass mutual information (MI) into an single objective function to optimize class-specific dictionary. The objective function has two aims: 1) maximizing the MI between dictionary items within a specific class (intrinsic structure) and 2) minimizing the MI between the dictionary items in a given class and those of the other classes (extrinsic structure). We significantly reduce the computational complexity of CSMMI by introducing an novel submodular method, which is one of the important contributions of this paper. This paper also contributes a state-of-the-art end-to-end system for action and gesture recognition incorporating CSMMI, with feature extraction, learning initial dictionary per each class by sparse coding, CSMMI via submodularity, and classification based on reconstruction errors. We performed extensive experiments on synthetic data and eight benchmark data sets. Our experimental results show that CSMMI outperforms shared dictionary methods and that our end-to-end system is competitive with other state-of-the-art approaches.
Calculation of mutual information for nonlinear communication channel at large signal-to-noise ratio
NASA Astrophysics Data System (ADS)
Terekhov, I. S.; Reznichenko, A. V.; Turitsyn, S. K.
2016-10-01
Using the path-integral technique we examine the mutual information for the communication channel modeled by the nonlinear Schrödinger equation with additive Gaussian noise. The nonlinear Schrödinger equation is one of the fundamental models in nonlinear physics, and it has a broad range of applications, including fiber optical communications—the backbone of the internet. At large signal-to-noise ratio we present the mutual information through the path-integral, which is convenient for the perturbative expansion in nonlinearity. In the limit of small noise and small nonlinearity we derive analytically the first nonzero nonlinear correction to the mutual information for the channel.
Nielsen, Jon F; Ghugre, Nilesh R; Panigrahy, Ashok
2004-11-01
We have investigated the use of two different image coregistration algorithms for identifying local regions of erroneously high fractional anisotropy (FA) as derived from diffusion tensor imaging (DTI) data sets in newborns. The first algorithm uses conventional affine registration of each of the diffusion-weighted images to the unweighted (b = 0) image for each slice, while the second algorithm uses second-order polynomial warping. Similarity between images was determined using the mutual information (MI) criterion, which is the preferred 'cost' criterion for coregistration of images with significantly different image intensity distributions. We have found that subtle differences exist in the FA values resulting from affine and second-order polynomial coregistration and demonstrate that nonlinear distortions introduce artifacts of spatial extent similar to real white matter structures in the newborn subcortex. We show that polynomial coregistration systematically reduces the presence of erroneous regions of high FA and that such artifacts can be identified by visual inspection of FA maps resulting from affine and polynomial coregistrations. Furthermore, we show that nonlinear distortions may be particularly pronounced when acquiring image slices of axial orientation at the height of the nasal cavity. Finally, we show that third-order polynomial MI coregistration (using the images resulting from second-order coregistration as input) has no observable effect on the resulting FA maps.
Measurement point selection in damage detection using the mutual information concept
NASA Astrophysics Data System (ADS)
Trendafilova, I.; Heylen, W.; Van Brussel, H.
2001-06-01
The problem for measurement point selection in damage detection procedures is addressed. The concept of average mutual information is applied in order to find the optimal distance between measurement points. The idea is to select the measurement points in such a way that the taken measurements are independent, i.e. the measurements do not `learn' from each other. The average mutual information can be utilized as a kind of an autocorrelation function for the purpose. It gives the average amount of information that two points `learn' from each other. Thus the minimum of the average mutual information will provide the distance between measurement points with independent measurements. The idea to use the first minimum of the average mutual information is taken from nonlinear dynamics. The proposed approach is demonstrated on a test case. The results show that it is possible to decrease significantly the number of measurement points, without decreasing the precision of the solution.
Discovering Genome-Wide Tag SNPs Based on the Mutual Information of the Variants
Elmas, Abdulkadir; Ou Yang, Tai-Hsien; Wang, Xiaodong
2016-01-01
Exploring linkage disequilibrium (LD) patterns among the single nucleotide polymorphism (SNP) sites can improve the accuracy and cost-effectiveness of genomic association studies, whereby representative (tag) SNPs are identified to sufficiently represent the genomic diversity in populations. There has been considerable amount of effort in developing efficient algorithms to select tag SNPs from the growing large-scale data sets. Methods using the classical pairwise-LD and multi-locus LD measures have been proposed that aim to reduce the computational complexity and to increase the accuracy, respectively. The present work solves the tag SNP selection problem by efficiently balancing the computational complexity and accuracy, and improves the coverage in genomic diversity in a cost-effective manner. The employed algorithm makes use of mutual information to explore the multi-locus association between SNPs and can handle different data types and conditions. Experiments with benchmark HapMap data sets show comparable or better performance against the state-of-the-art algorithms. In particular, as a novel application, the genome-wide SNP tagging is performed in the 1000 Genomes Project data sets, and produced a well-annotated database of tagging variants that capture the common genotype diversity in 2,504 samples from 26 human populations. Compared to conventional methods, the algorithm requires as input only the genotype (or haplotype) sequences, can scale up to genome-wide analyses, and produces accurate solutions with more information-rich output, providing an improved platform for researchers towards the subsequent association studies. PMID:27992465
NASA Astrophysics Data System (ADS)
Koski, J. V.; Maisi, V. F.; Sagawa, T.; Pekola, J. P.
2014-07-01
We validate experimentally a fluctuation relation known as generalized Jarzynski equality governing the work distribution in a feedback-controlled system. The feedback control is performed on a single electron box analogously to the original Szilard engine. In the generalized Jarzynski equality, mutual information is treated on an equal footing with the thermodynamic work. Our measurements provide the first evidence of the role of mutual information in the fluctuation theorem and thermodynamics of irreversible processes.
Drakakis, Georgios; Moledina, Saadiq; Chomenidis, Charalampos; Doganis, Philip; Sarimveis, Haralambos
2016-01-01
Decision trees are renowned in the computational chemistry and machine learning communities for their interpretability. Their capacity and usage are somewhat limited by the fact that they normally work on categorical data. Improvements to known decision tree algorithms are usually carried out by increasing and tweaking parameters, as well as the post-processing of the class assignment. In this work we attempted to tackle both these issues. Firstly, conditional mutual information was used as the criterion for selecting the attribute on which to split instances. The algorithm performance was compared with the results of C4.5 (WEKA's J48) using default parameters and no restrictions. Two datasets were used for this purpose, DrugBank compounds for HRH1 binding prediction and Traditional Chinese Medicine formulation predicted bioactivities for therapeutic class annotation. Secondly, an automated binning method for continuous data was evaluated, namely Scott's normal reference rule, in order to allow any decision tree to easily handle continuous data. This was applied to all approved drugs in DrugBank for predicting the RDKit SLogP property, using the remaining RDKit physicochemical attributes as input.
Marrelec, Guillaume; Messé, Arnaud; Bellec, Pierre
2015-01-01
The use of mutual information as a similarity measure in agglomerative hierarchical clustering (AHC) raises an important issue: some correction needs to be applied for the dimensionality of variables. In this work, we formulate the decision of merging dependent multivariate normal variables in an AHC procedure as a Bayesian model comparison. We found that the Bayesian formulation naturally shrinks the empirical covariance matrix towards a matrix set a priori (e.g., the identity), provides an automated stopping rule, and corrects for dimensionality using a term that scales up the measure as a function of the dimensionality of the variables. Also, the resulting log Bayes factor is asymptotically proportional to the plug-in estimate of mutual information, with an additive correction for dimensionality in agreement with the Bayesian information criterion. We investigated the behavior of these Bayesian alternatives (in exact and asymptotic forms) to mutual information on simulated and real data. An encouraging result was first derived on simulations: the hierarchical clustering based on the log Bayes factor outperformed off-the-shelf clustering techniques as well as raw and normalized mutual information in terms of classification accuracy. On a toy example, we found that the Bayesian approaches led to results that were similar to those of mutual information clustering techniques, with the advantage of an automated thresholding. On real functional magnetic resonance imaging (fMRI) datasets measuring brain activity, it identified clusters consistent with the established outcome of standard procedures. On this application, normalized mutual information had a highly atypical behavior, in the sense that it systematically favored very large clusters. These initial experiments suggest that the proposed Bayesian alternatives to mutual information are a useful new tool for hierarchical clustering. PMID:26406245
NASA Astrophysics Data System (ADS)
Quilty, John; Adamowski, Jan; Khalil, Bahaa; Rathinasamy, Maheswaran
2016-03-01
The input variable selection problem has recently garnered much interest in the time series modeling community, especially within water resources applications, demonstrating that information theoretic (nonlinear)-based input variable selection algorithms such as partial mutual information (PMI) selection (PMIS) provide an improved representation of the modeled process when compared to linear alternatives such as partial correlation input selection (PCIS). PMIS is a popular algorithm for water resources modeling problems considering nonlinear input variable selection; however, this method requires the specification of two nonlinear regression models, each with parametric settings that greatly influence the selected input variables. Other attempts to develop input variable selection methods using conditional mutual information (CMI) (an analog to PMI) have been formulated under different parametric pretenses such as k nearest-neighbor (KNN) statistics or kernel density estimates (KDE). In this paper, we introduce a new input variable selection method based on CMI that uses a nonparametric multivariate continuous probability estimator based on Edgeworth approximations (EA). We improve the EA method by considering the uncertainty in the input variable selection procedure by introducing a bootstrap resampling procedure that uses rank statistics to order the selected input sets; we name our proposed method bootstrap rank-ordered CMI (broCMI). We demonstrate the superior performance of broCMI when compared to CMI-based alternatives (EA, KDE, and KNN), PMIS, and PCIS input variable selection algorithms on a set of seven synthetic test problems and a real-world urban water demand (UWD) forecasting experiment in Ottawa, Canada.
Lenne, Bruno; Blanc, Jean-Luc; Nandrino, Jean-Louis; Gallois, Philippe; Hautecæur, Patrick; Pezard, Laurent
2013-01-01
The disturbance of cortical communication has been hypothesized as an important factor in the appearance of cognitive impairment in (MS). Cortical communication is quantified here in control subjects and patients with relapsing-remitting multiple sclerosis (RRMS) on the basis of mean coherence in the δ, θ, α, β and γ bands and using mutual information computed between pairs of bipolar EEG signals recorded during resting condition. Each patient received also a cognitive assessment using a battery of neuropsychological tests specific to cognitive deficits in MS. No difference was observed for the coherence indices whereas inter-hemispheric and right hemisphere mutual information is significantly lower in patients with MS than in control subjects. Moreover, inter-hemispheric mutual information decrease significantly with illness duration and right mutual information differentiate cognitively deficient and non-deficient patients. Mutual information allows to quantify the cortical communication in patients with RRMS and is related to clinical characteristics. Cortical communication quantified in a resting state might be a potential marker for the neurological damage induced by RRMS. PMID:23242355
Entanglement Entropy and Mutual Information Production Rates in Acoustic Black Holes
Giovanazzi, Stefano
2011-01-07
A method to investigate acoustic Hawking radiation is proposed, where entanglement entropy and mutual information are measured from the fluctuations of the number of particles. The rate of entropy radiated per one-dimensional (1D) channel is given by S={kappa}/12, where {kappa} is the sound acceleration on the sonic horizon. This entropy production is accompanied by a corresponding formation of mutual information to ensure the overall conservation of information. The predictions are confirmed using an ab initio analytical approach in transonic flows of 1D degenerate ideal Fermi fluids.
Entanglement entropy and mutual information production rates in acoustic black holes.
Giovanazzi, Stefano
2011-01-07
A method to investigate acoustic Hawking radiation is proposed, where entanglement entropy and mutual information are measured from the fluctuations of the number of particles. The rate of entropy radiated per one-dimensional (1D) channel is given by S=κ/12, where κ is the sound acceleration on the sonic horizon. This entropy production is accompanied by a corresponding formation of mutual information to ensure the overall conservation of information. The predictions are confirmed using an ab initio analytical approach in transonic flows of 1D degenerate ideal Fermi fluids.
A multilocus linkage disequilibrium measure based on mutual information theory and its applications.
Zhang, Lei; Liu, Jianfeng; Deng, Hong-Wen
2009-12-01
Evaluating the patterns of linkage disequilibrium (LD) is important for association mapping study as well as for studying the genomic architecture of human genome (e.g., haplotype block structures). Commonly used bi-allelic pairwise measures for assessing LD between two loci, such as r(2) and D', may not make full and efficient use of modern multilocus data. Though extended to multilocus scenarios, their performance is still questionable. Meanwhile, most existing measures for an entire multilocus region, such as normalized entropy difference, do not consider existence of LD heterogeneity across the region under investigation. Additionally, these existing multilocus measures cannot handle distant regions where long-range LD patterns may exist. In this study, we proposed a novel multilocus LD measure developed based on mutual information theory. Our proposed measure described LD pattern between two chromosome regions each of which may consist of multiple loci (including multi-allele loci). As such, the proposed measure can better characterize LD patterns between two arbitrary regions. As potential applications, we developed algorithms on the proposed measure for partitioning haplotype blocks and for selecting haplotype tagging SNPs (htSNPs), which were helpful for follow-up association tests. The results on both simulated and empirical data showed that our LD measure had distinct advantages over pairwise and other multilocus measures. First, our measure was more robust, and can capture comprehensively the LD information between neighboring as well as disjointed regions. Second, haplotype blocks were better described via our proposed measure. Furthermore, association tests with htSNPs from the proposed algorithm had improved power over tests on single markers and on haplotypes.
Mutual information-based feature selection for low-cost BCIs based on motor imagery.
Schiatti, L; Faes, L; Tessadori, J; Barresi, G; Mattos, L
2016-08-01
In the present study a feature selection algorithm based on mutual information (MI) was applied to electro-encephalographic (EEG) data acquired during three different motor imagery tasks from two dataset: Dataset I from BCI Competition IV including full scalp recordings from four subjects, and new data recorded from three subjects using the popular low-cost Emotiv EPOC EEG headset. The aim was to evaluate optimal channels and band-power (BP) features for motor imagery tasks discrimination, in order to assess the feasibility of a portable low-cost motor imagery based Brain-Computer Interface (BCI) system. The minimal sub set of features most relevant to task description and less redundant to each other was determined, and the corresponding classification accuracy was assessed offline employing linear support vector machine (SVM) in a 10-fold cross validation scheme. The analysis was performed: (a) on the original full Dataset I from BCI competition IV, (b) on a restricted channels set from Dataset I corresponding to available Emotiv EPOC electrodes locations, and (c) on data recorded with the EPOC system. Results from (a) showed that an offline classification accuracy above 80% can be reached using only 5 features. Limiting the analysis to EPOC channels caused a decrease of classification accuracy, although it still remained above chance level, both for data from (b) and (c). A top accuracy of 70% was achieved using 2 optimal features. These results encourage further research towards the development of portable low cost motor imagery-based BCI systems.
CSMMI: Class-Specific Maximization of Mutual Information for Action and Gesture Recognition.
Wan, Jun; Athitsos, Vassilis; Jangyodsuk, Pat; Escalante, Hugo; Ruan, Qiuqi; Guyon, Isabelle
2014-06-03
In this paper, we propose a novel approach called CSMMI using a submodular method, which aims at learning a compact and discriminative dictionary for each class. Unlike traditional dictionary-based algorithms, which typically learn a shared dictionary for all of the classes, we unify the intra-class and inter-class mutual information (MI) into an single objective function to optimize class-specific dictionary. The objective function has two aims: (1) Maximizing the MI between dictionary items within a specific class (intrinsic structure); (2) Minimizing the MI between the dictionary items in a given class and those of the other classes (extrinsic structure). We significantly reduce the computational complexity of CSMMI by introducing an novel submodular method, which is one of the important contributions of this paper. Our paper also contributes a state-of-the-art endto- end system for action and gesture recognition incorporating CSMMI, with feature extraction, learning initial dictionary per each class by sparse coding, CSMMI via submodularity and classification based on reconstruction errors. We performed extensive experiments on synthetic data and eight benchmark datasets. Our experimental results show that CSMMI outperforms shared dictionary methods and that our end-to-end system is competitive with other state-of-the-art approaches.
NASA Astrophysics Data System (ADS)
Tan, Chao; Wang, Jinyue; Wu, Tong; Qin, Xin; Li, Menglong
2010-12-01
Based on the combination of uninformative variable elimination (UVE), bootstrap and mutual information (MI), a simple ensemble algorithm, named ESPLS, is proposed for spectral multivariate calibration (MVC). In ESPLS, those uninformative variables are first removed; and then a preparatory training set is produced by bootstrap, on which a MI spectrum of retained variables is calculated. The variables that exhibit higher MI than a defined threshold form a subspace on which a candidate partial least-squares (PLS) model is constructed. This process is repeated. After a number of candidate models are obtained, a small part of models is picked out to construct an ensemble model by simple/weighted average. Four near/mid-infrared (NIR/MIR) spectral datasets concerning the determination of six components are used to verify the proposed ESPLS. The results indicate that ESPLS is superior to UVEPLS and its combination with MI-based variable selection (SPLS) in terms of both the accuracy and robustness. Besides, from the perspective of end-users, ESPLS does not increase the complexity of a calibration when enhancing its performance.
NASA Astrophysics Data System (ADS)
Albers, D. J.; Hripcsak, George
2012-03-01
This paper addresses how to calculate and interpret the time-delayed mutual information (TDMI) for a complex, diversely and sparsely measured, possibly non-stationary population of time-series of unknown composition and origin. The primary vehicle used for this analysis is a comparison between the time-delayed mutual information averaged over the population and the time-delayed mutual information of an aggregated population (here, aggregation implies the population is conjoined before any statistical estimates are implemented). Through the use of information theoretic tools, a sequence of practically implementable calculations are detailed that allow for the average and aggregate time-delayed mutual information to be interpreted. Moreover, these calculations can also be used to understand the degree of homo or heterogeneity present in the population. To demonstrate that the proposed methods can be used in nearly any situation, the methods are applied and demonstrated on the time series of glucose measurements from two different subpopulations of individuals from the Columbia University Medical Center electronic health record repository, revealing a picture of the composition of the population as well as physiological features.
NASA Astrophysics Data System (ADS)
Huang, Wung-Hong; Du, Yi-Hsien
2017-02-01
We apply the transformation of mixing azimuthal and internal coordinate or mixing time and internal coordinate to a stack of N black M-branes to find the Melvin spacetime of a stack of N black D-branes with magnetic or electric flux in string theory, after the Kaluza-Klein reduction. We slightly extend previous formulas to investigate the external magnetic and electric effects on the butterfly effect and holographic mutual information. It shows that the Melvin fields do not modify the scrambling time and will enhance the mutual information. In addition, we also T-dualize and twist a stack of N black D-branes to find a Melvin Universe supported by the flux of the NSNS b-field, which describes a non-comutative spacetime. It also shows that the spatial noncommutativity does not modify the scrambling time and will enhance the mutual information. We also study the corrected mutual information in the backreaction geometry due to the shock wave in our three model spacetimes.
NASA Astrophysics Data System (ADS)
Beneduci, Roberto; Bullock, Thomas J.; Busch, Paul; Carmeli, Claudio; Heinosaari, Teiko; Toigo, Alessandro
2013-09-01
We exhibit an operational connection between mutually unbiased bases and symmetric informationally complete positive operator-valued measures. Assuming that the latter exists, we show that there is a strong link between these two structures in all prime power dimensions. We also demonstrate that a similar link cannot exist in dimension 6.
Calculating mutual information for spike trains and other data with distances but no coordinates.
Houghton, Conor
2015-05-01
Many important data types, such as the spike trains recorded from neurons in typical electrophysiological experiments, have a natural notion of distance or similarity between data points, even though there is no obvious coordinate system. Here, a simple Kozachenko-Leonenko estimator is derived for calculating the mutual information between datasets of this type.
Li, Xiaoli; Ouyang, Gaoxiang
2010-08-15
To further understand functional connectivity in the brain, we need to identify the coupling direction between neuronal signals recorded from different brain areas. In this paper, we present a novel methodology based on permutation analysis and conditional mutual information for estimation of a directionality index between two neuronal populations. First, the reliability of this method is numerically assessed with a coupled mass neural model; the simulations show that this method is superior to the conditional mutual information method and the Granger causality method for identifying the coupling direction between unidirectional or bidirectional neuronal populations that are generated by the mass neuronal model. The method is also applied to investigate the coupling direction between neuronal populations in CA1 and CA3 in the rat hippocampal tetanus toxin model of focal epilepsy; the propagation direction of the seizure events could be elucidated through this coupling direction estimation method. All together, these results suggest that the permutation conditional mutual information method is a promising technique for estimating directional coupling between mutually interconnected neuronal populations.
NASA Astrophysics Data System (ADS)
Zhang, Haihong; Guan, Cuntai
2010-10-01
This paper addresses an important issue in a self-paced brain-computer interface (BCI): constructing subject-specific continuous control signal. To this end, we propose an alternative to the conventional regression/classification-based mechanism for building the transformation from EEG features into a univariate control signal. Based on information theory, the mechanism formulates the optimum transformation as maximizing the mutual information between the control signal and the mental state. We introduce a non-parametric mutual information estimate for general output distribution, and then develop a gradient-based algorithm to optimize the transformation using training data. We conduct an offline simulation study using motor imagery data from the BCI Competition IV Data Set I. The results show that the learning algorithm converged quickly, and the proposed method yielded significantly higher BCI performance than the conventional mechanism.
NASA Astrophysics Data System (ADS)
Vargas, David L.
Emerging quantum simulator technologies provide a new challenge to quantum many body theory. Quantifying the emergent order in and predicting the dynamics of such complex quantum systems requires a new approach. We develop such an approach based on complex network analysis of quantum mutual information. First, we establish the usefulness of quantum mutual information complex networks by reproducing the phase diagrams of transverse Ising and Bose-Hubbard models. By quantifying the complexity of quantum cellular automata we then demonstrate the applicability of complex network theory to non-equilibrium quantum dynamics. We conclude with a study of student collaboration networks, correlating a student's role in a collaboration network with their grades. This work thus initiates a quantitative theory of quantum complexity and provides a new tool for physics education research. (Abstract shortened by ProQuest.).
Advanced algorithms for information science
Argo, P.; Brislawn, C.; Fitzgerald, T.J.; Kelley, B.; Kim, W.H.; Mazieres, B.; Roeder, H.; Strottman, D.
1998-12-31
This is the final report of a one-year, Laboratory Directed Research and Development (LDRD) project at Los Alamos National Laboratory (LANL). In a modern information-controlled society the importance of fast computational algorithms facilitating data compression and image analysis cannot be overemphasized. Feature extraction and pattern recognition are key to many LANL projects and the same types of dimensionality reduction and compression used in source coding are also applicable to image understanding. The authors have begun developing wavelet coding which decomposes data into different length-scale and frequency bands. New transform-based source-coding techniques offer potential for achieving better, combined source-channel coding performance by using joint-optimization techniques. They initiated work on a system that compresses the video stream in real time, and which also takes the additional step of analyzing the video stream concurrently. By using object-based compression schemes (where an object is an identifiable feature of the video signal, repeatable in time or space), they believe that the analysis is directly related to the efficiency of the compression.
NASA Astrophysics Data System (ADS)
Tuttle, S. E.; Salvucci, G.
2013-12-01
Validation of remotely sensed soil moisture is complicated by the difference in scale between remote sensing footprints and traditional ground-based soil moisture measurements. To address this issue, a new method was developed to evaluate the useful information content of remotely sensed soil moisture data using only large-scale precipitation (i.e. without modeling). Under statistically stationary conditions [Salvucci, 2001], precipitation conditionally averaged according to soil moisture (denoted E[P|S]) results in a sigmoidal shape in a manner that reflects the dependence of drainage, runoff, and evapotranspiration on soil moisture. However, errors in satellite measurement and algorithmic conversion of satellite data to soil moisture can degrade this relationship. Thus, remotely sensed soil moisture products can be assessed by the degree to which the natural sigmoidal relationship is preserved. The metric of mutual information was used as an error-dependent measure of the strength of the sigmoidal relationship, calculated from a two-dimensional histogram of soil moisture versus precipitation estimated using Gaussian mixture models. Three AMSR-E algorithms (VUA-NASA [Owe et al., 2001], NASA [Njoku et al., 2003], and U. Montana [Jones & Kimball, 2010]) were evaluated with the method for a nine-year period (2002-2011) over the contiguous United States at ¼° latitude-longitude resolution, using precipitation from the North American Land Data Assimilation System (NLDAS). The U. Montana product resulted in the highest mutual information for 57% of the region, followed by VUA-NASA and NASA at 40% and 3%, respectively. Areas where the U. Montana product yielded the maximum mutual information generally coincided with low vegetation biomass and flatter terrain, while the VUA-NASA product contained more useful information in more rugged and highly vegetated areas. Additionally, E[P|S] curves resulting from the Gaussian mixture method can potentially be decomposed into
Large distance expansion of mutual information for disjoint disks in a free scalar theory
NASA Astrophysics Data System (ADS)
Agón, Cesar A.; Cohen-Abbo, Isaac; Schnitzer, Howard J.
2016-11-01
We compute the next-to-leading order term in the long-distance expansion of the mutual information for free scalars in three space-time dimensions. The geometry considered is two disjoint disks separated by a distance r between their centers. No evidence for non-analyticity in the Rényi parameter n for the continuation n → 1 in the next-to-leading order term is found.
Maes, F; Vandermeulen, D; Suetens, P
1999-12-01
Maximization of mutual information of voxel intensities has been demonstrated to be a very powerful criterion for three-dimensional medical image registration, allowing robust and accurate fully automated affine registration of multimodal images in a variety of applications, without the need for segmentation or other preprocessing of the images. In this paper, we investigate the performance of various optimization methods and multiresolution strategies for maximization of mutual information, aiming at increasing registration speed when matching large high-resolution images. We show that mutual information is a continuous function of the affine registration parameters when appropriate interpolation is used and we derive analytic expressions of its derivatives that allow numerically exact evaluation of its gradient. Various multiresolution gradient- and non-gradient-based optimization strategies, such as Powell, simplex, steepest-descent, conjugate-gradient, quasi-Newton and Levenberg-Marquardt methods, are evaluated for registration of computed tomography (CT) and magnetic resonance images of the brain. Speed-ups of a factor of 3 on average compared to Powell's method at full resolution are achieved with similar precision and without a loss of robustness with the simplex, conjugate-gradient and Levenberg-Marquardt method using a two-level multiresolution scheme. Large data sets such as 256(2) x 128 MR and 512(2) x 48 CT images can be registered with subvoxel precision in <5 min CPU time on current workstations.
Spatially weighted mutual information image registration for image guided radiation therapy
Park, Samuel B.; Rhee, Frank C.; Monroe, James I.; Sohn, Jason W.
2010-09-15
Purpose: To develop a new metric for image registration that incorporates the (sub)pixelwise differential importance along spatial location and to demonstrate its application for image guided radiation therapy (IGRT). Methods: It is well known that rigid-body image registration with mutual information is dependent on the size and location of the image subset on which the alignment analysis is based [the designated region of interest (ROI)]. Therefore, careful review and manual adjustments of the resulting registration are frequently necessary. Although there were some investigations of weighted mutual information (WMI), these efforts could not apply the differential importance to a particular spatial location since WMI only applies the weight to the joint histogram space. The authors developed the spatially weighted mutual information (SWMI) metric by incorporating an adaptable weight function with spatial localization into mutual information. SWMI enables the user to apply the selected transform to medically ''important'' areas such as tumors and critical structures, so SWMI is neither dominated by, nor neglects the neighboring structures. Since SWMI can be utilized with any weight function form, the authors presented two examples of weight functions for IGRT application: A Gaussian-shaped weight function (GW) applied to a user-defined location and a structures-of-interest (SOI) based weight function. An image registration example using a synthesized 2D image is presented to illustrate the efficacy of SWMI. The convergence and feasibility of the registration method as applied to clinical imaging is illustrated by fusing a prostate treatment planning CT with a clinical cone beam CT (CBCT) image set acquired for patient alignment. Forty-one trials are run to test the speed of convergence. The authors also applied SWMI registration using two types of weight functions to two head and neck cases and a prostate case with clinically acquired CBCT/MVCT image sets. The
Time-Delayed Mutual Information of the Phase as a Measure of Functional Connectivity
Wilmer, Andreas; de Lussanet, Marc; Lappe, Markus
2012-01-01
We propose a time-delayed mutual information of the phase for detecting nonlinear synchronization in electrophysiological data such as MEG. Palus already introduced the mutual information as a measure of synchronization [1]. To obtain estimates on small data-sets as reliably as possible, we adopt the numerical implementation as proposed by Kraskov and colleagues [2]. An embedding with a parametric time-delay allows a reconstruction of arbitrary nonstationary connective structures – so-called connectivity patterns – in a wide class of systems such as coupled oscillatory or even purely stochastic driven processes [3]. By using this method we do not need to make any assumptions about coupling directions, delay times, temporal dynamics, nonlinearities or underlying mechanisms. For verifying and refining the methods we generate synthetic data-sets by a mutual amplitude coupled network of Rössler oscillators with an a-priori known connective structure. This network is modified in such a way, that the power-spectrum forms a power law, which is also observed in electrophysiological recordings. The functional connectivity measure is tested on robustness to additive uncorrelated noise and in discrimination of linear mixed input data. For the latter issue a suitable de-correlation technique is applied. Furthermore, the compatibility to inverse methods for a source reconstruction in MEG such as beamforming techniques is controlled by dedicated dipole simulations. Finally, the method is applied on an experimental MEG recording. PMID:23028571
Cannon, Jonathan
2017-01-01
Mutual information is a commonly used measure of communication between neurons, but little theory exists describing the relationship between mutual information and the parameters of the underlying neuronal interaction. Such a theory could help us understand how specific physiological changes affect the capacity of neurons to synaptically communicate, and, in particular, they could help us characterize the mechanisms by which neuronal dynamics gate the flow of information in the brain. Here we study a pair of linear-nonlinear-Poisson neurons coupled by a weak synapse. We derive an analytical expression describing the mutual information between their spike trains in terms of synapse strength, neuronal activation function, the time course of postsynaptic currents, and the time course of the background input received by the two neurons. This expression allows mutual information calculations that would otherwise be computationally intractable. We use this expression to analytically explore the interaction of excitation, information transmission, and the convexity of the activation function. Then, using this expression to quantify mutual information in simulations, we illustrate the information-gating effects of neural oscillations and oscillatory coherence, which may either increase or decrease the mutual information across the synapse depending on parameters. Finally, we show analytically that our results can quantitatively describe the selection of one information pathway over another when multiple sending neurons project weakly to a single receiving neuron.
Universal behavior of the Shannon mutual information in nonintegrable self-dual quantum chains
NASA Astrophysics Data System (ADS)
Alcaraz, F. C.
2016-09-01
An existing conjecture states that the Shannon mutual information contained in the ground-state wave function of conformally invariant quantum chains, on periodic lattices, has a leading finite-size scaling behavior that, similarly as the von Neumann entanglement entropy, depends on the value of the central charge of the underlying conformal field theory describing the physical properties. This conjecture applies whenever the ground-state wave function is expressed in some special basis (conformal basis). Its formulation comes mainly from numerical evidences on exactly integrable quantum chains. In this paper, the above conjecture was tested for several general nonintegrable quantum chains. We introduce new families of self-dual Z (Q ) symmetric quantum chains (Q =2 ,3 ,... ). These quantum chains contain nearest-neighbor as well next-nearest-neighbor interactions (coupling constant p ). In the cases Q =2 and Q =3 , they are extensions of the standard quantum Ising and three-state Potts chains, respectively. For Q =4 and Q ≥5 , they are extensions of the Ashkin-Teller and Z (Q ) parafermionic quantum chains. Our studies indicate that these models are interesting on their own. They are critical, conformally invariant, and share the same universality class in a continuous critical line. Moreover, our numerical analysis for Q =2 -8 indicate that the Shannon mutual information exhibits the conjectured behavior irrespective if the conformally invariant quantum chain is exactly integrable or not. For completeness we also calculated, for these new families of quantum chains, the two existing generalizations of the Shannon mutual information, which are based on the Rényi entropy and on the Rényi divergence.
Analysis of phylogenetic signal in protostomial intron patterns using Mutual Information.
Hill, Natascha; Leow, Alexander; Bleidorn, Christoph; Groth, Detlef; Tiedemann, Ralph; Selbig, Joachim; Hartmann, Stefanie
2013-06-01
Many deep evolutionary divergences still remain unresolved, such as those among major taxa of the Lophotrochozoa. As alternative phylogenetic markers, the intron-exon structure of eukaryotic genomes and the patterns of absence and presence of spliceosomal introns appear to be promising. However, given the potential homoplasy of intron presence, the phylogenetic analysis of this data using standard evolutionary approaches has remained a challenge. Here, we used Mutual Information (MI) to estimate the phylogeny of Protostomia using gene structure data, and we compared these results with those obtained with Dollo Parsimony. Using full genome sequences from nine Metazoa, we identified 447 groups of orthologous sequences with 21,732 introns in 4,870 unique intron positions. We determined the shared absence and presence of introns in the corresponding sequence alignments and have made this data available in "IntronBase", a web-accessible and downloadable SQLite database. Our results obtained using Dollo Parsimony are obviously misled through systematic errors that arise from multiple intron loss events, but extensive filtering of data improved the quality of the estimated phylogenies. Mutual Information, in contrast, performs better with larger datasets, but at the same time it requires a complete data set, which is difficult to obtain for orthologs from a large number of taxa. Nevertheless, Mutual Information-based distances proved to be useful in analyzing this kind of data, also because the estimation of MI-based distances is independent of evolutionary models and therefore no pre-definitions of ancestral and derived character states are necessary.
Wang, X-D; Qi, Y-X; Jiang, Z-L
2011-03-01
Many methods had been developed on inferring transcriptional network from gene expression. However, it is still necessary to design new method that discloses more detailed and exact network information. Using network-assisted regression, the authors combined the averaged three-way mutual information (AMI3) and non-linear ordinary differential equation (ODE) model to infer the transcriptional network, and to obtain both the topological structure and the regulatory dynamics. Synthetic and experimental data were used to evaluate the performance of the above approach. In comparison with the previous methods based on mutual information, AMI3 obtained higher precision with the same sensitivity. To describe the regulatory dynamics between transcription factors and target genes, network-assisted regression and regression without network, respectively, were applied in the steady-state and time series microarray data. The results revealed that comparing with regression without network, network-assisted regression increased the precision, but decreased the fitting goodness. Then, the authors reconstructed the transcriptional network of Escherichia coli and simulated the regulatory dynamics of genes. Furthermore, the authors' approach identified potential transcription factors regulating yeast cell cycle. In conclusion, network-assisted regression, combined AMI3 and ODE model, was a more precisely to infer the topological structure and the regulatory dynamics of transcriptional network from microarray data. [Includes supplementary material].
NASA Technical Reports Server (NTRS)
Wolf, David R.
2004-01-01
The topic of this paper is a hierarchy of information-like functions, here named the information correlation functions, where each function of the hierarchy may be thought of as the information between the variables it depends upon. The information correlation functions are particularly suited to the description of the emergence of complex behaviors due to many- body or many-agent processes. They are particularly well suited to the quantification of the decomposition of the information carried among a set of variables or agents, and its subsets. In more graphical language, they provide the information theoretic basis for understanding the synergistic and non-synergistic components of a system, and as such should serve as a forceful toolkit for the analysis of the complexity structure of complex many agent systems. The information correlation functions are the natural generalization to an arbitrary number of sets of variables of the sequence starting with the entropy function (one set of variables) and the mutual information function (two sets). We start by describing the traditional measures of information (entropy) and mutual information.
Mazurowski, Maciej A; Lo, Joseph Y; Harrawood, Brian P; Tourassi, Georgia D
2011-10-01
Development of a computational decision aid for a new medical imaging modality typically is a long and complicated process. It consists of collecting data in the form of images and annotations, development of image processing and pattern recognition algorithms for analysis of the new images and finally testing of the resulting system. Since new imaging modalities are developed more rapidly than ever before, any effort for decreasing the time and cost of this development process could result in maximizing the benefit of the new imaging modality to patients by making the computer aids quickly available to radiologists that interpret the images. In this paper, we make a step in this direction and investigate the possibility of translating the knowledge about the detection problem from one imaging modality to another. Specifically, we present a computer-aided detection (CAD) system for mammographic masses that uses a mutual information-based template matching scheme with intelligently selected templates. We presented principles of template matching with mutual information for mammography before. In this paper, we present an implementation of those principles in a complete computer-aided detection system. The proposed system, through an automatic optimization process, chooses the most useful templates (mammographic regions of interest) using a large database of previously collected and annotated mammograms. Through this process, the knowledge about the task of detecting masses in mammograms is incorporated in the system. Then, we evaluate whether our system developed for screen-film mammograms can be successfully applied not only to other mammograms but also to digital breast tomosynthesis (DBT) reconstructed slices without adding any DBT cases for training. Our rationale is that since mutual information is known to be a robust inter-modality image similarity measure, it has high potential of transferring knowledge between modalities in the context of the mass detection
NASA Astrophysics Data System (ADS)
Zhang, Zhilong; Yang, Guopeng; Chen, Dong; Li, Jicheng; Yang, Weiping
2016-04-01
This paper presents a novel infrared and visual image registration method based on phase grouping and mutual information of gradient orientation. The method is specially designed for infrared image navigation, which is different from familiar multi-sensor image registration methods in the field of remote sensing. The central idea is to firstly extract common salient structural features from visual and infrared images through phase grouping, then registering infrared image to visual image and estimating the exterior parameters of the infrared camera. Two subjects are involved in this reports: (1) In order to estimate image gradient orientation accurately, a new method based on Leguerre-Gauss filter is presented. Then the image are segmented by grouping of pixels based on their gradient orientations and ling support regions are extracted as common salient structural features from infrared and visual images of the same ground scene. (2)In order for registering infrared and visual image, coordinate systems are constructed, coordinate transformations are formularized, and the new similarity measures based on orientation mutual information is presented. Quantitative evaluations on real and simulated image data reviews that the proposed method can provide registration results with improved robustness and accuracy.
de Matos Simoes, Ricardo; Emmert-Streib, Frank
2011-01-01
The inference of gene regulatory networks from gene expression data is a difficult problem because the performance of the inference algorithms depends on a multitude of different factors. In this paper we study two of these. First, we investigate the influence of discrete mutual information (MI) estimators on the global and local network inference performance of the C3NET algorithm. More precisely, we study 4 different MI estimators (Empirical, Miller-Madow, Shrink and Schürmann-Grassberger) in combination with 3 discretization methods (equal frequency, equal width and global equal width discretization). We observe the best global and local inference performance of C3NET for the Miller-Madow estimator with an equal width discretization. Second, our numerical analysis can be considered as a systems approach because we simulate gene expression data from an underlying gene regulatory network, instead of making a distributional assumption to sample thereof. We demonstrate that despite the popularity of the latter approach, which is the traditional way of studying MI estimators, this is in fact not supported by simulated and biological expression data because of their heterogeneity. Hence, our study provides guidance for an efficient design of a simulation study in the context of network inference, supporting a systems approach.
Using Mutual Information to capture Major Concerns of Postural Control in a Tossing activity
Gazula, Harshvardhan; Chang, Chien Chi; Lu, Ming-Lun; Hsiang, Simon M.
2015-01-01
Human body motion for load-tossing activity was partitioned into three phases using four critical events based on the load position viz. lift-off, closest to body, peak and release. For each phase, three objective functions values, viz. mobilization, stabilization and muscular torque utilization, used to control the motion patterns, were then calculated. We hypothesize that the relationships between different objective functions can be extracted using information theory. The kinematic data obtained with 36 treatment combinations (2 tossing distances, 2 tossing heights, 3 weights, and 3 target clearances) was used to estimate the mutual information between each pair of objective functions and construct Chow-Liu trees. Results from this research indicate that there was no dominant concern in the first two phases of the activity; however, torque utilization and mobilization were found to be important factors in the third phase of the load tossing activity. PMID:25680297
Whitmore, Rebecca; Crooks, Valorie A; Snyder, Jeremy
2015-09-01
This study examines the experiences of informal caregivers in medical tourism through an ethics of care lens. We conducted semi-structured interviews with 20 Canadians who had accompanied their friends or family members abroad for surgery, asking questions that dealt with their experiences prior to, during and after travel. Thematic analysis revealed three themes central to an ethics of care: responsibility, vulnerability and mutuality. Ethics of care theorists have highlighted how care has been historically devalued. We posit that medical tourism reproduces dominant narratives about care in a novel care landscape. Informal care goes unaccounted for by the industry, as it occurs in largely private spaces at a geographic distance from the home countries of medical tourists.
Plant-wide process monitoring based on mutual information-multiblock principal component analysis.
Jiang, Qingchao; Yan, Xuefeng
2014-09-01
Multiblock principal component analysis (MBPCA) methods are gaining increasing attentions in monitoring plant-wide processes. Generally, MBPCA assumes that some process knowledge is incorporated for block division; however, process knowledge is not always available. A new totally data-driven MBPCA method, which employs mutual information (MI) to divide the blocks automatically, has been proposed. By constructing sub-blocks using MI, the division not only considers linear correlations between variables, but also takes into account non-linear relations thereby involving more statistical information. The PCA models in sub-blocks reflect more local behaviors of process, and the results in all blocks are combined together by support vector data description. The proposed method is implemented on a numerical process and the Tennessee Eastman process. Monitoring results demonstrate the feasibility and efficiency.
Measuring the usefulness of hidden units in Boltzmann machines with mutual information.
Berglund, Mathias; Raiko, Tapani; Cho, Kyunghyun
2015-04-01
Restricted Boltzmann machines (RBMs) and deep Boltzmann machines (DBMs) are important models in deep learning, but it is often difficult to measure their performance in general, or measure the importance of individual hidden units in specific. We propose to use mutual information to measure the usefulness of individual hidden units in Boltzmann machines. The measure is fast to compute, and serves as an upper bound for the information the neuron can pass on, enabling detection of a particular kind of poor training results. We confirm experimentally that the proposed measure indicates how much the performance of the model drops when some of the units of an RBM are pruned away. We demonstrate the usefulness of the measure for early detection of poor training in DBMs.
Meyer, C R; Boes, J L; Kim, B; Bland, P H; Zasadny, K R; Kison, P V; Koral, K; Frey, K A; Wahl, R L
1997-04-01
This paper applies and evaluates an automatic mutual information-based registration algorithm across a broad spectrum of multimodal volume data sets. The algorithm requires little or no pre-processing, minimal user input and easily implements either affine, i.e. linear or thin-plate spline (TPS) warped registrations. We have evaluated the algorithm in phantom studies as well as in selected cases where few other algorithms could perform as well, if at all, to demonstrate the value of this new method. Pairs of multimodal gray-scale volume data sets were registered by iteratively changing registration parameters to maximize mutual information. Quantitative registration errors were assessed in registrations of a thorax phantom using PET/CT and in the National Library of Medicine's Visible Male using MRI T2-/T1-weighted acquisitions. Registrations of diverse clinical data sets were demonstrated including rotate-translate mapping of PET/MRI brain scans with significant missing data, full affine mapping of thoracic PET/CT and rotate-translate mapping of abdominal SPECT/CT. A five-point thin-plate spline (TPS) warped registration of thoracic PET/CT is also demonstrated. The registration algorithm converged in times ranging between 3.5 and 31 min for affine clinical registrations and 57 min for TPS warping. Mean error vector lengths for rotate-translate registrations were measured to be subvoxel in phantoms. More importantly the rotate-translate algorithm performs well even with missing data. The demonstrated clinical fusions are qualitatively excellent at all levels. We conclude that such automatic, rapid, robust algorithms significantly increase the likelihood that multimodality registrations will be routinely used to aid clinical diagnoses and post-therapeutic assessment in the near future.
Mutual Information in the Air Quality Monitoring Network of Bogota - Colombia
NASA Astrophysics Data System (ADS)
Guerrero, O. J.; Jimenez-Pizarro, R.
2012-12-01
Large urban areas in the developing world are characterized by high population density and a great variety of activities responsible for emission of trace gases and particulate matter to the atmosphere. In general, these pollutants are unevenly distributed over cities according to the location of sources, meteorological variability and geographical features. Urban air quality monitoring networks are primarily designed to protect public health. The meteorological and air quality information gathered by monitoring networks can also be used to understand pollutant sources, sinks, and dispersion processes and to assess the spatial coverage of the network itself. Several statistical and numerical simulation methods allow for the identification of the domain that influences observations at each of the stations, i.e, the zone and respective population truly covered by the measurements. We focused on Bogota, Colombia, a dense city of approximately 9.6 million inhabitants in its metropolitan area. We analyzed the measurements obtained by the Bogotá Air Quality Monitoring Network (RMCAB) between the years 1997 and 2010 for TSP, PM10, CO, NOx and O3. RMCAB is composed of 16 stations, 13 of which are fixed and measure both atmospheric pollutants and meteorological variables. The method applied consisted of a statistical approach based on the mutual information that each station shares with its complement, i.e. the set formed by the other stations of the network. In order to improve our understanding and interpretation of the results, virtual data created for selected receptors along a simple modeled Gaussian plume spreading throughout Bogotá was analyzed. In this Gaussian model, we accounted for the prevailing weather conditions of this city and for different emission features under which the pollutants are emitted. The spatial location of the monitoring stations and emission sources, and the quality of the measurements are relevant factors when assessing the mutual
A frequency-resolved mutual information rate and its application to neural systems.
Bernardi, Davide; Lindner, Benjamin
2015-03-01
The encoding and processing of time-dependent signals into sequences of action potentials of sensory neurons is still a challenging theoretical problem. Although, with some effort, it is possible to quantify the flow of information in the model-free framework of Shannon's information theory, this yields just a single number, the mutual information rate. This rate does not indicate which aspects of the stimulus are encoded. Several studies have identified mechanisms at the cellular and network level leading to low- or high-pass filtering of information, i.e., the selective coding of slow or fast stimulus components. However, these findings rely on an approximation, specifically, on the qualitative behavior of the coherence function, an approximate frequency-resolved measure of information flow, whose quality is generally unknown. Here, we develop an assumption-free method to measure a frequency-resolved information rate about a time-dependent Gaussian stimulus. We demonstrate its application for three paradigmatic descriptions of neural firing: an inhomogeneous Poisson process that carries a signal in its instantaneous firing rate; an integrator neuron (stochastic integrate-and-fire model) driven by a time-dependent stimulus; and the synchronous spikes fired by two commonly driven integrator neurons. In agreement with previous coherence-based estimates, we find that Poisson and integrate-and-fire neurons are broadband and low-pass filters of information, respectively. The band-pass information filtering observed in the coherence of synchronous spikes is confirmed by our frequency-resolved information measure in some but not all parameter configurations. Our results also explicitly show how the response-response coherence can fail as an upper bound on the information rate.
On the application of the auto mutual information rate of decrease to biomedical signals.
Escudero, Javier; Hornero, Roberto; Abasolo, Daniel; Lopez, Miguel
2008-01-01
The auto mutual information function (AMIF) evaluates the signal predictability by assessing linear and non-linear dependencies between two measurements taken from a single time series. Furthermore, the AMIF rate of decrease (AMIFRD) is correlated with signal entropy. This metric has been used to analyze biomedical data, including cardiac and brain activity recordings. Hence, the AMIFRD can be a relevant parameter in the context of biomedical signal analysis. Thus, in this pilot study, we have analyzed a synthetic sequence (a Lorenz system) and real biosignals (electroencephalograms recorded with eyes open and closed) with the AMIFRD. We aimed at illustrating the application of this parameter to biomedical time series. Our results show that the AMIFRD can detect changes in the non-linear dynamics of a sequence and that it can distinguish different physiological conditions.
Quantum Mutual Information as a Probe for Many-Body Localization
NASA Astrophysics Data System (ADS)
De Tomasi, Giuseppe; Bera, Soumya; Bardarson, Jens H.; Pollmann, Frank
2017-01-01
We demonstrate that the quantum mutual information (QMI) is a useful probe to study many-body localization (MBL). First, we focus on the detection of a metal-insulator transition for two different models, the noninteracting Aubry-André-Harper model and the spinless fermionic disordered Hubbard chain. We find that the QMI in the localized phase decays exponentially with the distance between the regions traced out, allowing us to define a correlation length, which converges to the localization length in the case of one particle. Second, we show how the QMI can be used as a dynamical indicator to distinguish an Anderson insulator phase from a MBL phase. By studying the spread of the QMI after a global quench from a random product state, we show that the QMI does not spread in the Anderson insulator phase but grows logarithmically in time in the MBL phase.
Raimondi, G; Chillemi, S; Michelassi, C; Di Garbo, A; Varanini, M; Legramante, J; Balocchi, R
2002-07-01
Orthostatic intolerance is the most serious symptom of cardiovascular deconditioning induced by microgravity. However, the exact mechanisms underlying these alterations have not been completely clarified. Several methods for studying the time series of systolic arterial pressure and RR interval have been proposed both in the time and in the frequency domain. However, these methods did not produce definitive results. In fact heart rate and arterial pressure show a complex pattern of global variability which is likely due to non linear feedback which involves the autonomic nervous system and to "stochastic" influences. Aim of this study was to evaluate the degree of interdependence between the mechanisms responsible for the variability of SAP and RR signals in subjects exposed to head down (HD). This quantification was achieved by using Mutual Information (MI).
Deng, Xiaopeng; Zhao, Daomu
2011-11-01
A single-channel color image encryption is proposed based on the modified Gerchberg-Saxton algorithm (MGSA) and mutual encoding in the Fresnel domain. Similar to the double random phase encoding (DRPE), this encryption scheme also employs a pair of phase-only functions (POFs) as encryption keys. But the two POFs are generated by the use of the MGSA rather than a random function generator. In the encryption process, only one color component is needed to be encrypted when these POFs are mutually served as the second encryption keys. As a result, a more compact and simple color encryption system based on one-time-pad, enabling only one gray cipheretext to be recorded and transmitted when holographic recording is used, is obtained. Moreover, the optical setup is lensless, thus easy to be implemented and the system parameters and wavelength can be served as additional keys to further enhance the security of the system. The feasibility and effectiveness of the proposed method are demonstrated by numerical results.
NASA Astrophysics Data System (ADS)
Luo, Xi-Liu; Wang, Jiang; Han, Chun-Xiao; Deng, Bin; Wei, Xi-Le; Bian, Hong-Rui
2012-02-01
As a convenient approach to the characterization of cerebral cortex electrical information, electroencephalograph (EEG) has potential clinical application in monitoring the acupuncture effects. In this paper, a method composed of the mutual information method and Lempel—Ziv complexity method (MILZC) is proposed to investigate the effects of acupuncture on the complexity of information exchanges between different brain regions based on EEGs. In the experiments, eight subjects are manually acupunctured at ‘Zusanli’ acupuncture point (ST-36) with different frequencies (i.e., 50, 100, 150, and 200 times/min) and the EEGs are recorded simultaneously. First, MILZC values are compared in general. Then average brain connections are used to quantify the effectiveness of acupuncture under the above four frequencies. Finally, significance index P values are used to study the spatiality of the acupuncture effect on the brain. Three main findings are obtained: (i) MILZC values increase during the acupuncture; (ii) manual acupunctures (MAs) with 100 times/min and 150 times/min are more effective than with 50 times/min and 200 times/min; (iii) contralateral hemisphere activation is more prominent than ipsilateral hemisphere's. All these findings suggest that acupuncture contributes to the increase of brain information exchange complexity and the MILZC method can successfully describe these changes.
Evaluating true BCI communication rate through mutual information and language models.
Speier, William; Arnold, Corey; Pouratian, Nader
2013-01-01
Brain-computer interface (BCI) systems are a promising means for restoring communication to patients suffering from "locked-in" syndrome. Research to improve system performance primarily focuses on means to overcome the low signal to noise ratio of electroencephalogric (EEG) recordings. However, the literature and methods are difficult to compare due to the array of evaluation metrics and assumptions underlying them, including that: 1) all characters are equally probable, 2) character selection is memoryless, and 3) errors occur completely at random. The standardization of evaluation metrics that more accurately reflect the amount of information contained in BCI language output is critical to make progress. We present a mutual information-based metric that incorporates prior information and a model of systematic errors. The parameters of a system used in one study were re-optimized, showing that the metric used in optimization significantly affects the parameter values chosen and the resulting system performance. The results of 11 BCI communication studies were then evaluated using different metrics, including those previously used in BCI literature and the newly advocated metric. Six studies' results varied based on the metric used for evaluation and the proposed metric produced results that differed from those originally published in two of the studies. Standardizing metrics to accurately reflect the rate of information transmission is critical to properly evaluate and compare BCI communication systems and advance the field in an unbiased manner.
NASA Astrophysics Data System (ADS)
Sameni, R.; Vrins, F.; Parmentier, F.; Hérail, C.; Vigneron, V.; Verleysen, M.; Jutten, C.; Shamsollahi, M. B.
2006-11-01
Blind source separation (BSS) techniques have revealed to be promising approaches for the noninvasive extraction of fetal cardiac signals from maternal abdominal recordings. From previous studies, it is now believed that a carefully selected array of electrodes well-placed over the abdomen of a pregnant woman contains the required `information' for BSS, to extract the complete fetal components. Based on this idea, previous works have involved array recording systems and sensor selection strategies based on the Mutual Information (MI) criterion. In this paper the previous works have been extended, by considering the 3-dimensional aspects of the cardiac electrical activity. The proposed method has been tested on simulated and real maternal abdominal recordings. The results show that the new sensor selection strategy together with the MI criterion, can be effectively used to select the channels containing the most `information' concerning the fetal ECG components from an array of 72 recordings. The method is hence believed to be useful for the selection of the most informative channels in online applications, considering the different fetal positions and movements.
2006-01-01
system. Our simulation studies and implementation measurements reveal that GUS performs close to, if not better than, the existing algorithms for the...satisfying application time con straints. The most widely studied time constraint is the deadline. A deadline time con straint for an application...optimality criteria, such as resource dependencies and precedence 3 constraints. Scheduling tasks with non-step TUF’s has been studied in the past
Cavagnaro, Daniel R; Myung, Jay I; Pitt, Mark A; Kujala, Janne V
2010-04-01
Discriminating among competing statistical models is a pressing issue for many experimentalists in the field of cognitive science. Resolving this issue begins with designing maximally informative experiments. To this end, the problem to be solved in adaptive design optimization is identifying experimental designs under which one can infer the underlying model in the fewest possible steps. When the models under consideration are nonlinear, as is often the case in cognitive science, this problem can be impossible to solve analytically without simplifying assumptions. However, as we show in this letter, a full solution can be found numerically with the help of a Bayesian computational trick derived from the statistics literature, which recasts the problem as a probability density simulation in which the optimal design is the mode of the density. We use a utility function based on mutual information and give three intuitive interpretations of the utility function in terms of Bayesian posterior estimates. As a proof of concept, we offer a simple example application to an experiment on memory retention.
Verification of 3d Building Models Using Mutual Information in Airborne Oblique Images
NASA Astrophysics Data System (ADS)
Nyaruhuma, A. P.; Gerke, M.; Vosselman, G.
2012-07-01
This paper describes a method for automatic verification of 3D building models using airborne oblique images. The problem being tackled is identifying buildings that are demolished or changed since the models were constructed or identifying wrong models using the images. The models verified are of CityGML LOD2 or higher since their edges are expected to coincide with actual building edges. The verification approach is based on information theory. Corresponding variables between building models and oblique images are used for deriving mutual information for individual edges, faces or whole buildings, and combined for all perspective images available for the building. The wireframe model edges are projected to images and verified using low level image features - the image pixel gradient directions. A building part is only checked against images in which it may be visible. The method has been tested with models constructed using laser points against Pictometry images that are available for most cities of Europe and may be publically viewed in the so called Birds Eye view of the Microsoft Bing Maps. Results are that nearly all buildings are correctly categorised as existing or demolished. Because we now concentrate only on roofs we also used the method to test and compare results from nadir images. This comparison made clear that especially height errors in models can be more reliably detected in oblique images because of the tilted view. Besides overall building verification, results per individual edges can be used for improving the 3D building models.
Klein, Stefan; van der Heide, Uulke A; Lips, Irene M; van Vulpen, Marco; Staring, Marius; Pluim, Josien P W
2008-04-01
An automatic method for delineating the prostate (including the seminal vesicles) in three-dimensional magnetic resonance scans is presented. The method is based on nonrigid registration of a set of prelabeled atlas images. Each atlas image is nonrigidly registered with the target patient image. Subsequently, the deformed atlas label images are fused to yield a single segmentation of the patient image. The proposed method is evaluated on 50 clinical scans, which were manually segmented by three experts. The Dice similarity coefficient (DSC) is used to quantify the overlap between the automatic and manual segmentations. We investigate the impact of several factors on the performance of the segmentation method. For the registration, two similarity measures are compared: Mutual information and a localized version of mutual information. The latter turns out to be superior (median DeltaDSC approximately equal 0.02, p < 0.01 with a paired two-sided Wilcoxon test) and comes at no added computational cost, thanks to the use of a novel stochastic optimization scheme. For the atlas fusion step we consider a majority voting rule and the "simultaneous truth and performance level estimation" algorithm, both with and without a preceding atlas selection stage. The differences between the various fusion methods appear to be small and mostly not statistically significant (p > 0.05). To assess the influence of the atlas composition, two atlas sets are compared. The first set consists of 38 scans of healthy volunteers. The second set is constructed by a leave-one-out approach using the 50 clinical scans that are used for evaluation. The second atlas set gives substantially better performance (DeltaDSC=0.04, p < 0.01), stressing the importance of a careful atlas definition. With the best settings, a median DSC of around 0.85 is achieved, which is close to the median interobserver DSC of 0.87. The segmentation quality is especially good at the prostate-rectum interface, where the
Bader, Brett William; Chew, Peter A.; Abdelali, Ahmed
2008-08-01
We describe an entirely statistics-based, unsupervised, and language-independent approach to multilingual information retrieval, which we call Latent Morpho-Semantic Analysis (LMSA). LMSA overcomes some of the shortcomings of related previous approaches such as Latent Semantic Analysis (LSA). LMSA has an important theoretical advantage over LSA: it combines well-known techniques in a novel way to break the terms of LSA down into units which correspond more closely to morphemes. Thus, it has a particular appeal for use with morphologically complex languages such as Arabic. We show through empirical results that the theoretical advantages of LMSA can translate into significant gains in precision in multilingual information retrieval tests. These gains are not matched either when a standard stemmer is used with LSA, or when terms are indiscriminately broken down into n-grams.
NASA Astrophysics Data System (ADS)
Pahlavani, Parham; Bigdeli, Behnaz
2016-12-01
Hyperspectral images contain extremely rich spectral information that offer great potential to discriminate between various land cover classes. However, these images are usually composed of tens or hundreds of spectrally close bands, which result in high redundancy and great amount of computation time in hyperspectral classification. Furthermore, in the presence of mixed coverage pixels, crisp classifiers produced errors, omission and commission. This paper presents a mutual information-Dempster-Shafer system through an ensemble classification approach for classification of hyperspectral data. First, mutual information is applied to split data into a few independent partitions to overcome high dimensionality. Then, a fuzzy maximum likelihood classifies each band subset. Finally, Dempster-Shafer is applied to fuse the results of the fuzzy classifiers. In order to assess the proposed method, a crisp ensemble system based on a support vector machine as the crisp classifier and weighted majority voting as the crisp fusion method are applied on hyperspectral data. Furthermore, a dimension reduction system is utilized to assess the effectiveness of mutual information band splitting of the proposed method. The proposed methodology provides interesting conclusions on the effectiveness and potentiality of mutual information-Dempster-Shafer based classification of hyperspectral data.
Zheng, Guoyan
2008-01-01
This paper addresses the problem of estimating the 3D rigid pose of a CT volume of an object from its 2D X-ray projections. We use maximization of mutual information, an accurate similarity measure for multi-modal and mono-modal image registration tasks. However, it is known that the standard mutual information measure only takes intensity values into account without considering spatial information and its robustness is questionable. In this paper, instead of directly maximizing mutual information, we propose to use a variational approximation derived from the Kullback-Leibler bound. Spatial information is then incorporated into this variational approximation using a Markov random field model. The newly derived similarity measure has a least-squares form and can be effectively minimized by a multi-resolution Levenberg-Marquardt optimizer. Experimental results are presented on X-ray and CT datasets of a plastic phantom and a cadaveric spine segment.
Registration of 2D to 3D joint images using phase-based mutual information
NASA Astrophysics Data System (ADS)
Dalvi, Rupin; Abugharbieh, Rafeef; Pickering, Mark; Scarvell, Jennie; Smith, Paul
2007-03-01
Registration of two dimensional to three dimensional orthopaedic medical image data has important applications particularly in the area of image guided surgery and sports medicine. Fluoroscopy to computer tomography (CT) registration is an important case, wherein digitally reconstructed radiographs derived from the CT data are registered to the fluoroscopy data. Traditional registration metrics such as intensity-based mutual information (MI) typically work well but often suffer from gross misregistration errors when the image to be registered contains a partial view of the anatomy visible in the target image. Phase-based MI provides a robust alternative similarity measure which, in addition to possessing the general robustness and noise immunity that MI provides, also employs local phase information in the registration process which makes it less susceptible to the aforementioned errors. In this paper, we propose using the complex wavelet transform for computing image phase information and incorporating that into a phase-based MI measure for image registration. Tests on a CT volume and 6 fluoroscopy images of the knee are presented. The femur and the tibia in the CT volume were individually registered to the fluoroscopy images using intensity-based MI, gradient-based MI and phase-based MI. Errors in the coordinates of fiducials present in the bone structures were used to assess the accuracy of the different registration schemes. Quantitative results demonstrate that the performance of intensity-based MI was the worst. Gradient-based MI performed slightly better, while phase-based MI results were the best consistently producing the lowest errors.
Power Spectrum and Mutual Information Analyses of DNA Base (Nucleotide) Sequences
NASA Astrophysics Data System (ADS)
Isohata, Yasuhiko; Hayashi, Masaki
2003-03-01
On the basis of the power spectrum analyses for the base (nucleotide) sequences of various genes, we have studied long-range correlations in total base sequences which are expressed as 1/fα, behaviour of the exponent α for the accumulated base sequences as well as periodicities at short range. In particular from the analysis of content rate distributions of α we have obtained the average value \\barα=0.40± 0.01 and \\barα=0.20± 0.01 for the human genes and S. cerevisiae genes, respectively. We have also performed the analyses using the mutual information function. We show that there exists a clear difference between the content rate distributions of correlation lengths for the sample human genes and the S. cerevisiae genes. We are led to a conjecture that the elongation of the correlation length in the base sequences of genes from the early eukaryote (S. cerevisiae) to the late eukaryote (human) should be the definite reflection of the evolutionary process.
Meyer, Patrick E; Lafitte, Frédéric; Bontempi, Gianluca
2008-01-01
Results This paper presents the R/Bioconductor package minet (version 1.1.6) which provides a set of functions to infer mutual information networks from a dataset. Once fed with a microarray dataset, the package returns a network where nodes denote genes, edges model statistical dependencies between genes and the weight of an edge quantifies the statistical evidence of a specific (e.g transcriptional) gene-to-gene interaction. Four different entropy estimators are made available in the package minet (empirical, Miller-Madow, Schurmann-Grassberger and shrink) as well as four different inference methods, namely relevance networks, ARACNE, CLR and MRNET. Also, the package integrates accuracy assessment tools, like F-scores, PR-curves and ROC-curves in order to compare the inferred network with a reference one. Conclusion The package minet provides a series of tools for inferring transcriptional networks from microarray data. It is freely available from the Comprehensive R Archive Network (CRAN) as well as from the Bioconductor website. PMID:18959772
Variation of entanglement entropy and mutual information in fermion-fermion scattering
NASA Astrophysics Data System (ADS)
Fan, Jinbo; Deng, Yanbin; Huang, Yong-Chang
2017-03-01
We study the behavior of entanglement between different degrees of freedom of scattering fermions, based on an exemplary QED scattering process e+e-→μ+μ- . The variation of entanglement entropy between two fermions from an initial state to the final state was computed, with respect to different entanglement between the ingoing particles. This variation of entanglement entropy is found to be proportional to an area quantity, the total cross section. We also study the spin-momentum and helicity-momentum entanglements within one particle in the aforementioned scattering process. The calculations of the relevant variations of mutual information in the same inertial frame reveals that, for a maximally entangled initial state, the scattering between the particles does not affect the degree of both of these entanglements of one particle in the final state. It is also found that the increasing degree of entanglement between two ingoing particles would restrict the generation of entanglement between spin (helicity) and momentum of one outgoing particle. And the entanglement between spin and momentum within one particle in the final state is shown to always be stronger than that for helicity-momentum for a general initial entanglement state, implying significantly distinct properties of entanglement for the helicity and spin perceived by an inertial observer.
NASA Astrophysics Data System (ADS)
Gencaga, D.; Malakar, N. K.; Lary, D. J.
2014-12-01
In this survey, we present and compare different approaches to estimate Mutual Information (MI) from data to analyse general dependencies between variables of interest in a system. We demonstrate the performance difference of MI versus correlation analysis, which is only optimal in case of linear dependencies. First, we use a piece-wise constant Bayesian methodology using a general Dirichlet prior. In this estimation method, we use a two-stage approach where we approximate the probability distribution first and then calculate the marginal and joint entropies. Here, we demonstrate the performance of this Bayesian approach versus the others for computing the dependency between different variables. We also compare these with linear correlation analysis. Finally, we apply MI and correlation analysis to the identification of the bias in the determination of the aerosol optical depth (AOD) by the satellite based Moderate Resolution Imaging Spectroradiometer (MODIS) and the ground based AErosol RObotic NETwork (AERONET). Here, we observe that the AOD measurements by these two instruments might be different for the same location. The reason of this bias is explored by quantifying the dependencies between the bias and 15 other variables including cloud cover, surface reflectivity and others.
Estimation of Delta Wave by Mutual Information of Heartbeat During Sleep
NASA Astrophysics Data System (ADS)
Kurihara, Yosuke; Watanabe, Kajiro; Kobayashi, Kazuyuki; Tanaka, Hiroshi
The quality of sleep is evaluated based on the sleep stages judged by R-K method or the manual of American Academy of Sleep Medicine. The brainwaves, eye movements, and chin EMG of sleeping subjects are used for the judgment. These methods above, however, require some electrodes to be attached to the head and the face to obtain the brainwaves, eye movements, and chin EMG, thus making the measurements troublesome to be held on a daily basis. If non-invasive measurements of brainwaves, eye movements, and chin EMG are feasible, or their equivalent data can be estimated through other bio-signals, the monitoring of the quality of daily sleeps, which influences the health condition, will be easy. In this paper, we discuss the appearance rate of delta wave occurrences, which is deeply related with the depth of sleep, can be estimated based on the average amount of mutual information calculated by pulse wave signals and body movements measured non-invasively by the pneumatic method. As a result, the root mean square error between the appearance rate of delta wave occurrences measured with a polysomnography and the estimated delta pulse was 14.93%.
Spagnolo, Daniel M.; Gyanchandani, Rekha; Al-Kofahi, Yousef; Stern, Andrew M.; Lezon, Timothy R.; Gough, Albert; Meyer, Dan E.; Ginty, Fiona; Sarachan, Brion; Fine, Jeffrey; Lee, Adrian V.; Taylor, D. Lansing; Chennubhotla, S. Chakra
2016-01-01
Background: Measures of spatial intratumor heterogeneity are potentially important diagnostic biomarkers for cancer progression, proliferation, and response to therapy. Spatial relationships among cells including cancer and stromal cells in the tumor microenvironment (TME) are key contributors to heterogeneity. Methods: We demonstrate how to quantify spatial heterogeneity from immunofluorescence pathology samples, using a set of 3 basic breast cancer biomarkers as a test case. We learn a set of dominant biomarker intensity patterns and map the spatial distribution of the biomarker patterns with a network. We then describe the pairwise association statistics for each pattern within the network using pointwise mutual information (PMI) and visually represent heterogeneity with a two-dimensional map. Results: We found a salient set of 8 biomarker patterns to describe cellular phenotypes from a tissue microarray cohort containing 4 different breast cancer subtypes. After computing PMI for each pair of biomarker patterns in each patient and tumor replicate, we visualize the interactions that contribute to the resulting association statistics. Then, we demonstrate the potential for using PMI as a diagnostic biomarker, by comparing PMI maps and heterogeneity scores from patients across the 4 different cancer subtypes. Estrogen receptor positive invasive lobular carcinoma patient, AL13-6, exhibited the highest heterogeneity score among those tested, while estrogen receptor negative invasive ductal carcinoma patient, AL13-14, exhibited the lowest heterogeneity score. Conclusions: This paper presents an approach for describing intratumor heterogeneity, in a quantitative fashion (via PMI), which departs from the purely qualitative approaches currently used in the clinic. PMI is generalizable to highly multiplexed/hyperplexed immunofluorescence images, as well as spatial data from complementary in situ methods including FISSEQ and CyTOF, sampling many different components
On the Mutual Information of Multi-hop Acoustic Sensors Network in Underwater Wireless Communication
2014-05-01
experimentally measured in underwater .................................................. 33 Figure 20. Matlab simulation Set Up for multi-hop...processing. Also, we have extensively used the Matlab programming in system design and simulation of sensors placement to maximize the data rate, mutual...simulations. Bit error rate testing with Matlab is very simple, but does require some prerequisite knowledge. BER testing requires a transmitter, a receiver
Sun, Leiming; Wang, Chan; Hu, Yue-Qing
2016-01-01
Background. Genome-wide association studies have succeeded in detecting novel common variants which associate with complex diseases. As a result of the fast changes in next generation sequencing technology, a large number of sequencing data are generated, which offers great opportunities to identify rare variants that could explain a larger proportion of missing heritability. Many effective and powerful methods are proposed, although they are usually limited to continuous, dichotomous or ordinal traits. Notice that traits having nominal categorical features are commonly observed in complex diseases, especially in mental disorders, which motivates the incorporation of the characteristics of the categorical trait into association studies with rare and common variants. Methods. We construct two simple and intuitive nonparametric tests, MIT and aMIT, based on mutual information for detecting association between genetic variants in a gene or region and a categorical trait. MIT and aMIT can gauge the difference among the distributions of rare and common variants across a region given every categorical trait value. If there is little association between variants and a categorical trait, MIT or aMIT approximately equals zero. The larger the difference in distributions, the greater values MIT and aMIT have. Therefore, MIT and aMIT have the potential for detecting functional variants. Results.We checked the validity of proposed statistics and compared them to the existing ones through extensive simulation studies with varied combinations of the numbers of variants of rare causal, rare non-causal, common causal, and common non-causal, deleterious and protective, various minor allele frequencies and different levels of linkage disequilibrium. The results show our methods have higher statistical power than conventional ones, including the likelihood based score test, in most cases: (1) there are multiple genetic variants in a gene or region; (2) both protective and deleterious
NASA Astrophysics Data System (ADS)
Khan, Shiraj; Bandyopadhyay, Sharba; Ganguly, Auroop R.; Saigal, Sunil; Erickson, David J., III; Protopopescu, Vladimir; Ostrouchov, George
2007-08-01
Commonly used dependence measures, such as linear correlation, cross-correlogram, or Kendall’s τ , cannot capture the complete dependence structure in data unless the structure is restricted to linear, periodic, or monotonic. Mutual information (MI) has been frequently utilized for capturing the complete dependence structure including nonlinear dependence. Recently, several methods have been proposed for the MI estimation, such as kernel density estimators (KDEs), k -nearest neighbors (KNNs), Edgeworth approximation of differential entropy, and adaptive partitioning of the XY plane. However, outstanding gaps in the current literature have precluded the ability to effectively automate these methods, which, in turn, have caused limited adoptions by the application communities. This study attempts to address a key gap in the literature—specifically, the evaluation of the above methods to choose the best method, particularly in terms of their robustness for short and noisy data, based on comparisons with the theoretical MI estimates, which can be computed analytically, as well with linear correlation and Kendall’s τ . Here we consider smaller data sizes, such as 50, 100, and 1000, and within this study we characterize 50 and 100 data points as very short and 1000 as short. We consider a broader class of functions, specifically linear, quadratic, periodic, and chaotic, contaminated with artificial noise with varying noise-to-signal ratios. Our results indicate KDEs as the best choice for very short data at relatively high noise-to-signal levels whereas the performance of KNNs is the best for very short data at relatively low noise levels as well as for short data consistently across noise levels. In addition, the optimal smoothing parameter of a Gaussian kernel appears to be the best choice for KDEs while three nearest neighbors appear optimal for KNNs. Thus, in situations where the approximate data sizes are known in advance and exploratory data analysis and
NASA Astrophysics Data System (ADS)
Pires, Carlos; Perdigão, Rui
2013-04-01
We assess the Shannon multivariate mutual information (MI) and interaction information (IT), either on a simultaneous or on a time-lagged (up to 3 months) basis, between low-frequency modes of an atmospheric, T63, 3-level, perpetual winter forced, quasi-geostrophic model. For that purpose, Principal Components (PCs) of the spherical-harmonic components of the monthly-mean stream-functions are used. Every single PC time-series (of 1000 years length) is subjected to a prior Gaussian anamorphosis before computing MI and IT. That allows for unambiguously decomposing MI into the positive Gaussian (depending on the Gaussian correlation) and the non-Gaussian MI terms. We use a kernel-based MI estimator. Since marginal Gaussian PDFs are imposed, that makes MI estimation very robust even when using short data. Statistically significant non-Gaussian bivariate MI appears between the variance-dominating PC-pairs of larger space and time-scales with evidence in the bivariate PDF of the mixing of PDFs centered at different weather regimes. The corresponding residual Gaussian MI is due to PCs being uncorrelated and to the weak non-Gaussianity of monthly-based PCs. The Gaussianized PCs in the tail's variance spectrum (of faster variability) do not much differ from Gaussian independent white noises. Trivariate MI I(A,B,C) (also known as total correlation) is computed among simultaneous and time-lagged PCs: A,B,C as well as the interaction information: IT(A,B,C)=I(A,B|C)-I(A,B)=I(A,C|B)-I(A,C)=I(B,C|A)-I(B,C) along with their Gaussian and non-Gaussian counterparts where conditional MI is used. The corresponding non-Gaussian term allows for quantifying nonlinear predictability and causality. For example, we find interactive variable triads of positive non-Gaussian IT where A=X(t+tau), B=Y(t+tau), C=Z(t) where t is time, tau is time-lag and X,Y,Z are arbitrary PCs. Typically it works when X,Y are nearly independent while Z(t) is a mediator variable taking the role of a precursor
An innovative thinking-based intelligent information fusion algorithm.
Lu, Huimin; Hu, Liang; Liu, Gang; Zhou, Jin
2013-01-01
This study proposes an intelligent algorithm that can realize information fusion in reference to the relative research achievements in brain cognitive theory and innovative computation. This algorithm treats knowledge as core and information fusion as a knowledge-based innovative thinking process. Furthermore, the five key parts of this algorithm including information sense and perception, memory storage, divergent thinking, convergent thinking, and evaluation system are simulated and modeled. This algorithm fully develops innovative thinking skills of knowledge in information fusion and is a try to converse the abstract conception of brain cognitive science to specific and operable research routes and strategies. Furthermore, the influences of each parameter of this algorithm on algorithm performance are analyzed and compared with those of classical intelligent algorithms trough test. Test results suggest that the algorithm proposed in this study can obtain the optimum problem solution by less target evaluation times, improve optimization effectiveness, and achieve the effective fusion of information.
Information Theory, Inference and Learning Algorithms
NASA Astrophysics Data System (ADS)
Mackay, David J. C.
2003-10-01
Information theory and inference, often taught separately, are here united in one entertaining textbook. These topics lie at the heart of many exciting areas of contemporary science and engineering - communication, signal processing, data mining, machine learning, pattern recognition, computational neuroscience, bioinformatics, and cryptography. This textbook introduces theory in tandem with applications. Information theory is taught alongside practical communication systems, such as arithmetic coding for data compression and sparse-graph codes for error-correction. A toolbox of inference techniques, including message-passing algorithms, Monte Carlo methods, and variational approximations, are developed alongside applications of these tools to clustering, convolutional codes, independent component analysis, and neural networks. The final part of the book describes the state of the art in error-correcting codes, including low-density parity-check codes, turbo codes, and digital fountain codes -- the twenty-first century standards for satellite communications, disk drives, and data broadcast. Richly illustrated, filled with worked examples and over 400 exercises, some with detailed solutions, David MacKay's groundbreaking book is ideal for self-learning and for undergraduate or graduate courses. Interludes on crosswords, evolution, and sex provide entertainment along the way. In sum, this is a textbook on information, communication, and coding for a new generation of students, and an unparalleled entry point into these subjects for professionals in areas as diverse as computational biology, financial engineering, and machine learning.
Jani, S; Kishan, A; O'Connell, D; King, C; Steinberg, M; Low, D; Lamb, J
2014-06-01
Purpose: To investigate if pelvic nodal coverage for prostate patients undergoing intensity modulated radiotherapy (IMRT) can be predicted using mutual image information computed between planning and cone-beam CTs (CBCTs). Methods: Four patients with high-risk prostate adenocarcinoma were treated with IMRT on a Varian TrueBeam. Plans were designed such that 95% of the nodal planning target volume (PTV) received the prescription dose of 45 Gy (N=1) or 50.4 Gy (N=3). Weekly CBCTs (N=25) were acquired and the nodal clinical target volumes and organs at risk were contoured by a physician. The percent nodal volume receiving prescription dose was recorded as a ground truth. Using the recorded shifts performed by the radiation therapists at the time of image acquisition, CBCTs were aligned with the planning kVCT. Mutual image information (MI) was calculated between the CBCT and the aligned planning CT within the contour of the nodal PTV. Due to variable CBCT fields-of-view, CBCT images covering less than 90% of the nodal volume were excluded from the analysis, resulting in the removal of eight CBCTs. Results: A correlation coefficient of 0.40 was observed between the MI metric and the percent of the nodal target volume receiving the prescription dose. One patient's CBCTs had clear outliers from the rest of the patients. Upon further investigation, we discovered image artifacts that were present only in that patient's images. When those four images were excluded, the correlation improved to 0.81. Conclusion: This pilot study shows the potential of predicting pelvic nodal dosimetry by computing the mutual image information between planning CTs and patient setup CBCTs. Importantly, this technique does not involve manual or automatic contouring of the CBCT images. Additional patients and more robust exclusion criteria will help validate our findings.
Efficient Learning Algorithms with Limited Information
ERIC Educational Resources Information Center
De, Anindya
2013-01-01
The thesis explores efficient learning algorithms in settings which are more restrictive than the PAC model of learning (Valiant) in one of the following two senses: (i) The learning algorithm has a very weak access to the unknown function, as in, it does not get labeled samples for the unknown function (ii) The error guarantee required from the…
NASA Astrophysics Data System (ADS)
Kurihara, Yosuke; Watanabe, Kajiro; Kobayashi, Kazuyuki; Tanaka, Tanaka
Sleep disorders disturb the recovery from mental and physical fatigues, one of the functions of the sleep. The majority of those who with the disorders are suffering from Sleep Apnea Syndrome (SAS). Continuous Hypoxia during sleep due to SAS cause Circulatory Disturbances, such as hypertension and ischemic heart disease, and Malfunction of Autonomic Nervous System, and other severe complications, often times bringing the suffers to death. In order to prevent these from happening, it is important to detect the SAS in its early stage by monitoring the daily respirations during sleep, and to provide appropriate treatments at medical institutions. In this paper, the Pneumatic Method to detect the Apnea period during sleep is proposed. Pneumatic method can measure heartbeat and respiration signal. Respiration signal can be considered as noise against heartbeat signal, and the decrease in the respiration signal due to Apnea increases the Average Mutual Information of heartbeat. The result of scaling analysis of the average mutual information is defined as threshold to detect the apnea period. The root mean square error between the lengths of Apnea measured by Strain Gauge using for reference and those measured by using the proposed method was 3.1 seconds. And, error of the number of apnea times judged by doctor and proposal method in OSAS patients was 3.3 times.
NASA Astrophysics Data System (ADS)
Hachem, Walid; Moustakas, Aris; Pastur, Leonid A.
2015-11-01
Consider a random non-centered multiple antenna radio transmission channel. Assume that the deterministic part of the channel is itself frequency selective and that the random multipath part is represented by an ergodic stationary vector process. In the Hilbert space l2(ℤ), one can associate to this channel a random ergodic self-adjoint operator having a so-called Integrated Density of States (IDS). Shannon's mutual information per receive antenna of this channel coincides then with the integral of a log function with respect to the IDS. In this paper, it is shown that when the numbers of antennas at the transmitter and at the receiver tend to infinity at the same rate, the mutual information per receive antenna tends to a quantity that can be identified and, in fact, is closely related to that obtained within the random matrix approach [I. Telatar, Eur. Trans. Telecommun. 10, 585 (1999)]. This result can be obtained by analyzing the behavior of the Stieltjes transform of the IDS in the regime of the large numbers of antennas.
A robust fuzzy local information C-Means clustering algorithm.
Krinidis, Stelios; Chatzis, Vassilios
2010-05-01
This paper presents a variation of fuzzy c-means (FCM) algorithm that provides image clustering. The proposed algorithm incorporates the local spatial information and gray level information in a novel fuzzy way. The new algorithm is called fuzzy local information C-Means (FLICM). FLICM can overcome the disadvantages of the known fuzzy c-means algorithms and at the same time enhances the clustering performance. The major characteristic of FLICM is the use of a fuzzy local (both spatial and gray level) similarity measure, aiming to guarantee noise insensitiveness and image detail preservation. Furthermore, the proposed algorithm is fully free of the empirically adjusted parameters (a, ¿(g), ¿(s), etc.) incorporated into all other fuzzy c-means algorithms proposed in the literature. Experiments performed on synthetic and real-world images show that FLICM algorithm is effective and efficient, providing robustness to noisy images.
ERIC Educational Resources Information Center
Wang, Chun
2013-01-01
Cognitive diagnostic computerized adaptive testing (CD-CAT) purports to combine the strengths of both CAT and cognitive diagnosis. Cognitive diagnosis models aim at classifying examinees into the correct mastery profile group so as to pinpoint the strengths and weakness of each examinee whereas CAT algorithms choose items to determine those…
Information filtering via weighted heat conduction algorithm
NASA Astrophysics Data System (ADS)
Liu, Jian-Guo; Guo, Qiang; Zhang, Yi-Cheng
2011-06-01
In this paper, by taking into account effects of the user and object correlations on a heat conduction (HC) algorithm, a weighted heat conduction (WHC) algorithm is presented. We argue that the edge weight of the user-object bipartite network should be embedded into the HC algorithm to measure the object similarity. The numerical results indicate that both the accuracy and diversity could be improved greatly compared with the standard HC algorithm and the optimal values reached simultaneously. On the Movielens and Netflix datasets, the algorithmic accuracy, measured by the average ranking score, can be improved by 39.7% and 56.1% in the optimal case, respectively, and the diversity could reach 0.9587 and 0.9317 when the recommendation list equals to 5. Further statistical analysis indicates that, in the optimal case, the distributions of the edge weight are changed to the Poisson form, which may be the reason why HC algorithm performance could be improved. This work highlights the effect of edge weight on a personalized recommendation study, which maybe an important factor affecting personalized recommendation performance.
Dowson, Nicholas; Kadir, Timor; Bowden, Richard
2008-10-01
Recently, the Nonparametric (NP) Windows has been proposed to estimate the statistics of real 1D and 2D signals. NP Windows is accurate, because it is equivalent to sampling images at a high (infinite) resolution for an assumed interpolation model. This paper extends the proposed approach to consider joint distributions of image-pairs. Second, Green's Theorem is used to simplify the previous NP Windows algorithm. Finally, a resolution-aware NP Windows algorithm is proposed to improve robustness to relative scaling between an image pair. Comparative testing of 2D image registration was performed using translation-only and affine transformations. Although more expensive than other methods, NP Windows frequently demonstrated superior performance for bias (distance between ground truth and global maximum) and frequency of convergence. Unlike other methods, the number of samples and the number of bins have little effect on NP Windows and the prior selection of a kernel is not required.
Zheng, Guoyan
2010-10-01
This paper addresses the problem of estimating the 3D rigid poses of a CT volume of an object from its 2D X-ray projection(s). We use maximization of mutual information, an accurate similarity measure for multi-modal and mono-modal image registration tasks. However, it is known that the standard mutual information measures only take intensity values into account without considering spatial information and their robustness is questionable. In this paper, instead of directly maximizing mutual information, we propose to use a variational approximation derived from the Kullback-Leibler bound. Spatial information is then incorporated into this variational approximation using a Markov random field model. The newly derived similarity measure has a least-squares form and can be effectively minimized by a multi-resolution Levenberg-Marquardt optimizer. Experiments were conducted on datasets from two applications: (a) intra-operative patient pose estimation from a limited number (e.g. 2) of calibrated fluoroscopic images, and (b) post-operative cup orientation estimation from a single standard X-ray radiograph with/without gonadal shielding. The experiment on intra-operative patient pose estimation showed a mean target registration accuracy of 0.8mm and a capture range of 11.5mm, while the experiment on estimating the post-operative cup orientation from a single X-ray radiograph showed a mean accuracy below 2 degrees for both anteversion and inclination. More importantly, results from both experiments demonstrated that the newly derived similarity measures were robust to occlusions in the X-ray image(s).
An Image Encryption Algorithm Based on Information Hiding
NASA Astrophysics Data System (ADS)
Ge, Xin; Lu, Bin; Liu, Fenlin; Gong, Daofu
Aiming at resolving the conflict between security and efficiency in the design of chaotic image encryption algorithms, an image encryption algorithm based on information hiding is proposed based on the “one-time pad” idea. A random parameter is introduced to ensure a different keystream for each encryption, which has the characteristics of “one-time pad”, improving the security of the algorithm rapidly without significant increase in algorithm complexity. The random parameter is embedded into the ciphered image with information hiding technology, which avoids negotiation for its transport and makes the application of the algorithm easier. Algorithm analysis and experiments show that the algorithm is secure against chosen plaintext attack, differential attack and divide-and-conquer attack, and has good statistical properties in ciphered images.
Guinea-Martin, Daniel; Mora, Ricardo; Ruiz-Castillo, Javier
2015-01-01
In this article, we study the effects of ethnicity and gender on occupational segregation. Traditionally, researchers have examined the two sources of segregation separately. In contrast, we measure their joint effect by applying a multigroup segregation index-the Mutual Information or M index-to the product of the seven ethnic groups and two genders distinguished in our 2001 Census data for England and Wales. We exploit M's additive decomposability property to pose the following two questions: (i) Is there an interaction effect? (ii) How much does each source contribute to occupational segregation, controlling for the effect of the other? Although the role of ethnicity is non-negligible in the areas where minorities are concentrated, our findings confirm the greater importance of gender over ethnicity as a source of segregation. Moreover, we find a small "dwindling" interaction effect between the two sources of segregation: ethnicity slightly weakens the segregating power of gender and vice versa.
Yang, Bin; Zhang, Wei; Wang, Haifeng; Song, Chuandong; Chen, Yuehui
2016-05-01
Regulatory interactions among target genes and regulatory factors occur instantaneously or with time-delay. In this paper, we propose a novel approach namely TDSDMI based on time-delayed S-system model (TDSS) model and delayed mutual information (DMI) to infer time-delay gene regulatory network (TDGRN). Firstly DMI is proposed to delete redundant regulator factors for each target gene. Secondly restricted gene expression programming (RGEP) is proposed as a new representation of the TDSS model to identify instantaneous and time-delayed interactions. To verify the effectiveness of the proposed method, TDSDMI is applied to both simulated and real biological datasets. Experimental results reveal that TDSDMI performs better than the recent reconstruction methods.
Barman, Shohag; Kwon, Yung-Keun
2017-01-01
Background Inferring a gene regulatory network from time-series gene expression data in systems biology is a challenging problem. Many methods have been suggested, most of which have a scalability limitation due to the combinatorial cost of searching a regulatory set of genes. In addition, they have focused on the accurate inference of a network structure only. Therefore, there is a pressing need to develop a network inference method to search regulatory genes efficiently and to predict the network dynamics accurately. Results In this study, we employed a Boolean network model with a restricted update rule scheme to capture coarse-grained dynamics, and propose a novel mutual information-based Boolean network inference (MIBNI) method. Given time-series gene expression data as an input, the method first identifies a set of initial regulatory genes using mutual information-based feature selection, and then improves the dynamics prediction accuracy by iteratively swapping a pair of genes between sets of the selected regulatory genes and the other genes. Through extensive simulations with artificial datasets, MIBNI showed consistently better performance than six well-known existing methods, REVEAL, Best-Fit, RelNet, CST, CLR, and BIBN in terms of both structural and dynamics prediction accuracy. We further tested the proposed method with two real gene expression datasets for an Escherichia coli gene regulatory network and a fission yeast cell cycle network, and also observed better results using MIBNI compared to the six other methods. Conclusions Taken together, MIBNI is a promising tool for predicting both the structure and the dynamics of a gene regulatory network. PMID:28178334
Cortical Entropy, Mutual Information and Scale-Free Dynamics in Waking Mice
Fagerholm, Erik D.; Scott, Gregory; Shew, Woodrow L.; Song, Chenchen; Leech, Robert; Knöpfel, Thomas; Sharp, David J.
2016-01-01
Some neural circuits operate with simple dynamics characterized by one or a few well-defined spatiotemporal scales (e.g. central pattern generators). In contrast, cortical neuronal networks often exhibit richer activity patterns in which all spatiotemporal scales are represented. Such “scale-free” cortical dynamics manifest as cascades of activity with cascade sizes that are distributed according to a power-law. Theory and in vitro experiments suggest that information transmission among cortical circuits is optimized by scale-free dynamics. In vivo tests of this hypothesis have been limited by experimental techniques with insufficient spatial coverage and resolution, i.e., restricted access to a wide range of scales. We overcame these limitations by using genetically encoded voltage imaging to track neural activity in layer 2/3 pyramidal cells across the cortex in mice. As mice recovered from anesthesia, we observed three changes: (a) cortical information capacity increased, (b) information transmission among cortical regions increased and (c) neural activity became scale-free. Our results demonstrate that both information capacity and information transmission are maximized in the awake state in cortical regions with scale-free network dynamics. PMID:27384059
Information content of ozone retrieval algorithms
NASA Technical Reports Server (NTRS)
Rodgers, C.; Bhartia, P. K.; Chu, W. P.; Curran, R.; Deluisi, J.; Gille, J. C.; Hudson, R.; Mateer, C.; Rusch, D.; Thomas, R. J.
1989-01-01
The algorithms are characterized that were used for production processing by the major suppliers of ozone data to show quantitatively: how the retrieved profile is related to the actual profile (This characterizes the altitude range and vertical resolution of the data); the nature of systematic errors in the retrieved profiles, including their vertical structure and relation to uncertain instrumental parameters; how trends in the real ozone are reflected in trends in the retrieved ozone profile; and how trends in other quantities (both instrumental and atmospheric) might appear as trends in the ozone profile. No serious deficiencies were found in the algorithms used in generating the major available ozone data sets. As the measurements are all indirect in someway, and the retrieved profiles have different characteristics, data from different instruments are not directly comparable.
Mutually Exclusive Uncertainty Relations
NASA Astrophysics Data System (ADS)
Xiao, Yunlong; Jing, Naihuan
2016-11-01
The uncertainty principle is one of the characteristic properties of quantum theory based on incompatibility. Apart from the incompatible relation of quantum states, mutually exclusiveness is another remarkable phenomenon in the information- theoretic foundation of quantum theory. We investigate the role of mutual exclusive physical states in the recent work of stronger uncertainty relations for all incompatible observables by Mccone and Pati and generalize the weighted uncertainty relation to the product form as well as their multi-observable analogues. The new bounds capture both incompatibility and mutually exclusiveness, and are tighter compared with the existing bounds.
Mutually Exclusive Uncertainty Relations.
Xiao, Yunlong; Jing, Naihuan
2016-11-08
The uncertainty principle is one of the characteristic properties of quantum theory based on incompatibility. Apart from the incompatible relation of quantum states, mutually exclusiveness is another remarkable phenomenon in the information- theoretic foundation of quantum theory. We investigate the role of mutual exclusive physical states in the recent work of stronger uncertainty relations for all incompatible observables by Mccone and Pati and generalize the weighted uncertainty relation to the product form as well as their multi-observable analogues. The new bounds capture both incompatibility and mutually exclusiveness, and are tighter compared with the existing bounds.
Mutually Exclusive Uncertainty Relations
Xiao, Yunlong; Jing, Naihuan
2016-01-01
The uncertainty principle is one of the characteristic properties of quantum theory based on incompatibility. Apart from the incompatible relation of quantum states, mutually exclusiveness is another remarkable phenomenon in the information- theoretic foundation of quantum theory. We investigate the role of mutual exclusive physical states in the recent work of stronger uncertainty relations for all incompatible observables by Mccone and Pati and generalize the weighted uncertainty relation to the product form as well as their multi-observable analogues. The new bounds capture both incompatibility and mutually exclusiveness, and are tighter compared with the existing bounds. PMID:27824161
NASA Astrophysics Data System (ADS)
Wang, Xixi; Nagarajan, Mahesh B.; Abidin, Anas Z.; DSouza, Adora; Hobbs, Susan K.; Wismüller, Axel
2015-03-01
Functional MRI (fMRI) is currently used to investigate structural and functional connectivity in human brain networks. To this end, previous studies have proposed computational methods that involve assumptions that can induce information loss, such as assumed linear coupling of the fMRI signals or requiring dimension reduction. This study presents a new computational framework for investigating the functional connectivity in the brain and recovering network structure while reducing the information loss inherent in previous methods. For this purpose, pair-wise mutual information (MI) was extracted from all pixel time series within the brain on resting-state fMRI data. Non-metric topographic mapping of proximity (TMP) data was subsequently applied to recover network structure from the pair-wise MI analysis. Our computational framework is demonstrated in the task of identifying regions of the primary motor cortex network on resting state fMRI data. For ground truth comparison, we also localized regions of the primary motor cortex associated with hand movement in a task-based fMRI sequence with a finger-tapping stimulus function. The similarity between our pair-wise MI clustering results and the ground truth is evaluated using the dice coefficient. Our results show that non-metric clustering with the TMP algorithm, as performed on pair-wise MI analysis, was able to detect the primary motor cortex network and achieved a dice coefficient of 0.53 in terms of overlap with the ground truth. Thus, we conclude that our computational framework can extract and visualize valuable information concerning the underlying network structure between different regions of the brain in resting state fMRI.
Ince, Robin A A; Giordano, Bruno L; Kayser, Christoph; Rousselet, Guillaume A; Gross, Joachim; Schyns, Philippe G
2017-03-01
We begin by reviewing the statistical framework of information theory as applicable to neuroimaging data analysis. A major factor hindering wider adoption of this framework in neuroimaging is the difficulty of estimating information theoretic quantities in practice. We present a novel estimation technique that combines the statistical theory of copulas with the closed form solution for the entropy of Gaussian variables. This results in a general, computationally efficient, flexible, and robust multivariate statistical framework that provides effect sizes on a common meaningful scale, allows for unified treatment of discrete, continuous, unidimensional and multidimensional variables, and enables direct comparisons of representations from behavioral and brain responses across any recording modality. We validate the use of this estimate as a statistical test within a neuroimaging context, considering both discrete stimulus classes and continuous stimulus features. We also present examples of analyses facilitated by these developments, including application of multivariate analyses to MEG planar magnetic field gradients, and pairwise temporal interactions in evoked EEG responses. We show the benefit of considering the instantaneous temporal derivative together with the raw values of M/EEG signals as a multivariate response, how we can separately quantify modulations of amplitude and direction for vector quantities, and how we can measure the emergence of novel information over time in evoked responses. Open-source Matlab and Python code implementing the new methods accompanies this article. Hum Brain Mapp 38:1541-1573, 2017. © 2016 Wiley Periodicals, Inc.
Giordano, Bruno L.; Kayser, Christoph; Rousselet, Guillaume A.; Gross, Joachim; Schyns, Philippe G.
2016-01-01
Abstract We begin by reviewing the statistical framework of information theory as applicable to neuroimaging data analysis. A major factor hindering wider adoption of this framework in neuroimaging is the difficulty of estimating information theoretic quantities in practice. We present a novel estimation technique that combines the statistical theory of copulas with the closed form solution for the entropy of Gaussian variables. This results in a general, computationally efficient, flexible, and robust multivariate statistical framework that provides effect sizes on a common meaningful scale, allows for unified treatment of discrete, continuous, unidimensional and multidimensional variables, and enables direct comparisons of representations from behavioral and brain responses across any recording modality. We validate the use of this estimate as a statistical test within a neuroimaging context, considering both discrete stimulus classes and continuous stimulus features. We also present examples of analyses facilitated by these developments, including application of multivariate analyses to MEG planar magnetic field gradients, and pairwise temporal interactions in evoked EEG responses. We show the benefit of considering the instantaneous temporal derivative together with the raw values of M/EEG signals as a multivariate response, how we can separately quantify modulations of amplitude and direction for vector quantities, and how we can measure the emergence of novel information over time in evoked responses. Open‐source Matlab and Python code implementing the new methods accompanies this article. Hum Brain Mapp 38:1541–1573, 2017. © 2016 Wiley Periodicals, Inc. PMID:27860095
Holledge gauge failure testing using concurrent information processing algorithm
Weeks, G.E.; Daniel, W.E.; Edwards, R.E.; Jannarone, R.J.; Joshi, S.N.; Palakodety, S.S.; Qian, D.
1996-04-11
For several decades, computerized information processing systems and human information processing models have developed with a good deal of mutual influence. Any comprehensive psychology text in this decade uses terms that originated in the computer industry, such as ``cache`` and ``memory``, to describe human information processing. Likewise, many engineers today are using ``artificial intelligence``and ``artificial neural network`` computing tools that originated as models of human thought to solve industrial problems. This paper concerns a recently developed human information processing model, called ``concurrent information processing`` (CIP), and a related set of computing tools for solving industrial problems. The problem of focus is adaptive gauge monitoring; the application is pneumatic pressure repeaters (Holledge gauges) used to measure liquid level and density in the Defense Waste Processing Facility and the Integrated DWPF Melter System.
Javorka, Michal; Krohova, Jana; Czippelova, Barbora; Turianikova, Zuzana; Lazarova, Zuzana; Javorka, Kamil; Faes, Luca
2017-01-31
The study of short-term cardiovascular interactions is classically performed through the bivariate analysis of the interactions between the beat-to-beat variability of heart period (RR interval from the ECG) and systolic blood pressure (SBP). Recent progress in the development of multivariate time series analysis methods is making it possible to explore how directed interactions between two signals change in the context of networks including other coupled signals. Exploiting these advances, the present study aims at assessing directional cardiovascular interactions among the basic variability signals of RR, SBP and diastolic blood pressure (DBP), using an approach which allows direct comparison between bivariate and multivariate coupling measures. To this end, we compute information-theoretic measures of the strength and delay of causal interactions between RR, SBP and DBP using both bivariate and trivariate (conditioned) formulations in a group of healthy subjects in a resting state and during stress conditions induced by head-up tilt (HUT) and mental arithmetics (MA). We find that bivariate measures better quantify the overall (direct+indirect) information transferred between variables, while trivariate measures better reflect the existence and delay of directed interactions. The main physiological results are: (i) the detection during supine rest of strong interactions along the pathway RR���DBP���SBP, reflecting marked Windkessel and/or Frank-Starling effects; (ii) the finding of relatively weak baroreflex effects SBP���RR at rest; (iii) the invariance of cardiovascular interactions during MA, and the emergence of stronger and faster SBP���RR interactions, as well as of weaker RR���DBP interactions, during HUT. These findings support the importance of investigating cardiovascular interactions from a network perspective, and suggest the usefulness of directed information measures to assess physiological mechanisms and track their
Mutual information reveals multiple structural relaxation mechanisms in a model glass former
Dunleavy, Andrew J.; Wiesner, Karoline; Yamamoto, Ryoichi; Royall, C. Patrick
2015-01-01
Among the key challenges to our understanding of solidification in the glass transition is that it is accompanied by little apparent change in structure. Recently, geometric motifs have been identified in glassy liquids, but a causal link between these motifs and solidification remains elusive. One ‘smoking gun’ for such a link would be identical scaling of structural and dynamic lengthscales on approaching the glass transition, but this is highly controversial. Here we introduce an information theoretic approach to determine correlations in displacement for particle relaxation encoded in the initial configuration of a glass-forming liquid. We uncover two populations of particles, one inclined to relax quickly, the other slowly. Each population is correlated with local density and geometric motifs. Our analysis further reveals a dynamic lengthscale similar to that associated with structural properties, which may resolve the discrepancy between structural and dynamic lengthscales. PMID:25608791
Inversion of Magnetotelluric Data in Anisotropic Media Using Maximization of Mutual Information
NASA Astrophysics Data System (ADS)
Mandolesi, E.; Jones, A. G.
2011-12-01
Regularization in inverse geophysics problems has been used extensively, due to the necessity to constrain the model space and to reduce the ill-posedness of several problems. Magnetotelluric (MT) problems suffer from severe non-linearity and ill-posedness, which makes MT inversions extremely challenging. The use of a reference model has been used by many authors in order to drive the inversion process to converge on a model that shares features with the reference, as a result reducing non-uniqueness and improving the model resolution. In our work the reference model drives the inversion keeping the conductivity distribution close to that of the velocity using variation of information as measure of distance between the two pictures. In this way the electrical conductivity and seismic velocity can be compared from a statistical point of view, without the necessity of a common parameterization or a strict geometrical similarity. Our work involves the inversion of MT long-period data, which are sensitive to electrical conductivity, using shear wave velocity maps as reference model in a 1D anisotropic domain. Computation of variation of information is performed through the generation of the joint probability distribution, which allows exploration of the relation between models that fit seismic data and models that fit electrical properties. An approximate agreement between geoelectric strike direction and seismic fast axis have been recognized in different continental lithospheric areas, suggesting a common cause for both the seismic and electric anisotropic behavior. We present an application of this inversion approach to a real dataset from Central Germany, discussing pros and cons of this approach in relation to similar studies on the same area. Due to the minimal assumptions required by this approach, it highlights the possibility of application to different tomography techniques.
Estimation of Information Hiding Algorithms and Parameters
2007-02-21
growing false positives. 15. SUBJECT TERMS Information hiding, reverse-engineering, steganography , steganalysis, watermarking 16. SECURITY...specialist in breaking a covert communication system given very little information. Since it is likely for steganography to be used on very large...multimedia files, e.g. audio and video, there are substantial issues to be addressed on the implementation end of such a system as well as the theoretical
Wang, Luman; Mo, Qiaochu; Wang, Jianxin
2015-01-01
Most current gene coexpression databases support the analysis for linear correlation of gene pairs, but not nonlinear correlation of them, which hinders precisely evaluating the gene-gene coexpression strengths. Here, we report a new database, MIrExpress, which takes advantage of the information theory, as well as the Pearson linear correlation method, to measure the linear correlation, nonlinear correlation, and their hybrid of cell-specific gene coexpressions in immune cells. For a given gene pair or probe set pair input by web users, both mutual information (MI) and Pearson correlation coefficient (r) are calculated, and several corresponding values are reported to reflect their coexpression correlation nature, including MI and r values, their respective rank orderings, their rank comparison, and their hybrid correlation value. Furthermore, for a given gene, the top 10 most relevant genes to it are displayed with the MI, r, or their hybrid perspective, respectively. Currently, the database totally includes 16 human cell groups, involving 20,283 human genes. The expression data and the calculated correlation results from the database are interactively accessible on the web page and can be implemented for other related applications and researches.
Hao, Xuejun; Xu, Dongrong; Bansal, Ravi; Dong, Zhengchao; Liu, Jun; Wang, Zhishun; Kangarlu, Alayar; Liu, Feng; Duan, Yunsuo; Shova, Satie; Gerber, Andrew J; Peterson, Bradley S
2013-02-01
Differing imaging modalities provide unique channels of information to probe differing aspects of the brain's structural or functional organization. In combination, differing modalities provide complementary and mutually informative data about tissue organization that is more than their sum. We acquired and spatially coregistered data in four MRI modalities--anatomical MRI, functional MRI, diffusion tensor imaging (DTI), and magnetic resonance spectroscopy (MRS)--from 20 healthy adults to understand how interindividual variability in measures from one modality account for variability in measures from other modalities at each voxel of the brain. We detected significant correlations of local volumes with the magnitude of functional activation, suggesting that underlying variation in local volumes contributes to individual variability in functional activation. We also detected significant inverse correlations of NAA (a putative measure of neuronal density and viability) with volumes of white matter in the frontal cortex, with DTI-based measures of tissue organization within the superior longitudinal fasciculus, and with the magnitude of functional activation and default-mode activity during simple visual and motor tasks, indicating that substantial variance in local volumes, white matter organization, and functional activation derives from an underlying variability in the number or density of neurons in those regions. Many of these imaging measures correlated with measures of intellectual ability within differing brain tissues and differing neural systems, demonstrating that the neural determinants of intellectual capacity involve numerous and disparate features of brain tissue organization, a conclusion that could be made with confidence only when imaging the same individuals with multiple MRI modalities.
A region growing vessel segmentation algorithm based on spectrum information.
Jiang, Huiyan; He, Baochun; Fang, Di; Ma, Zhiyuan; Yang, Benqiang; Zhang, Libo
2013-01-01
We propose a region growing vessel segmentation algorithm based on spectrum information. First, the algorithm does Fourier transform on the region of interest containing vascular structures to obtain its spectrum information, according to which its primary feature direction will be extracted. Then combined edge information with primary feature direction computes the vascular structure's center points as the seed points of region growing segmentation. At last, the improved region growing method with branch-based growth strategy is used to segment the vessels. To prove the effectiveness of our algorithm, we use the retinal and abdomen liver vascular CT images to do experiments. The results show that the proposed vessel segmentation algorithm can not only extract the high quality target vessel region, but also can effectively reduce the manual intervention.
Integrating a priori information in edge-linking algorithms
NASA Astrophysics Data System (ADS)
Farag, Aly A.; Cao, Yu; Yeap, Yuen-Pin
1992-09-01
This research presents an approach to integrate a priori information to the path metric of the LINK algorithm. The zero-crossing contours of the $DEL2G are taken as a gross estimate of the boundaries in the image. This estimate of the boundaries is used to define the swath of important information, and to provide a distance measure for edge localization. During the linking process, a priori information plays important roles in (1) dramatically reducing the search space because the actual path lies within +/- 2 (sigma) f from the prototype contours ((sigma) f is the standard deviation of the Gaussian kernel used in the edge enhancement step); (2) breaking the ties when the search metrics give uncertain information; and (3) selecting the set of goal nodes for the search algorithm. We show that the integration of a priori information in the LINK algorithms provides faster and more accurate edge linking.
NASA Astrophysics Data System (ADS)
Wen, Xueda; Matsuura, Shunji; Ryu, Shinsei
2016-06-01
We develop an approach based on edge theories to calculate the entanglement entropy and related quantities in (2+1)-dimensional topologically ordered phases. Our approach is complementary to, e.g., the existing methods using replica trick and Witten's method of surgery, and applies to a generic spatial manifold of genus g , which can be bipartitioned in an arbitrary way. The effects of fusion and braiding of Wilson lines can be also straightforwardly studied within our framework. By considering a generic superposition of states with different Wilson line configurations, through an interference effect, we can detect, by the entanglement entropy, the topological data of Chern-Simons theories, e.g., the R symbols, monodromy, and topological spins of quasiparticles. Furthermore, by using our method, we calculate other entanglement/correlation measures such as the mutual information and the entanglement negativity. In particular, it is found that the entanglement negativity of two adjacent noncontractible regions on a torus provides a simple way to distinguish Abelian and non-Abelian topological orders.
Amin, Ruhul; Islam, S K Hafizul; Biswas, G P; Khan, Muhammad Khurram; Obaidat, Mohammad S
2015-11-01
In order to access remote medical server, generally the patients utilize smart card to login to the server. It has been observed that most of the user (patient) authentication protocols suffer from smart card stolen attack that means the attacker can mount several common attacks after extracting smart card information. Recently, Lu et al.'s proposes a session key agreement protocol between the patient and remote medical server and claims that the same protocol is secure against relevant security attacks. However, this paper presents several security attacks on Lu et al.'s protocol such as identity trace attack, new smart card issue attack, patient impersonation attack and medical server impersonation attack. In order to fix the mentioned security pitfalls including smart card stolen attack, this paper proposes an efficient remote mutual authentication protocol using smart card. We have then simulated the proposed protocol using widely-accepted AVISPA simulation tool whose results make certain that the same protocol is secure against active and passive attacks including replay and man-in-the-middle attacks. Moreover, the rigorous security analysis proves that the proposed protocol provides strong security protection on the relevant security attacks including smart card stolen attack. We compare the proposed scheme with several related schemes in terms of computation cost and communication cost as well as security functionalities. It has been observed that the proposed scheme is comparatively better than related existing schemes.
NASA Astrophysics Data System (ADS)
Kawamura, Tetsuo; Horio, Yoshihiko; Hasegawa, Mikio
The tabu search was implemented on a neural network with chaotic neuro-dynamics. This chaotic exponential tabu search shows great performance in solving quadratic assignment problems (QAPs). To exploit inherent parallel processing abilities of analog hardware systems, a synchronous updating scheme, where all the neurons in the network are updated at the same time, was proposed. However, several neurons may fire simultaneously with the synchronous updating. As a result, we cannot determine only one candidate for the 2-opt exchange from the many fired neurons. To solve this problem, several neuron selection methods, which select one specific neuron among the fired neurons, were proposed. These neuron selection methods improved the performance of the synchronous updating scheme. In this paper, we analyze the dynamics of the chaotic neural network with the neuron selection methods by means of the spatial and temporal mutual information. Through the analyses, the network solution search dynamics of the exponential chaotic tabu search with different neuron selection methods are evaluated.
Hao, Yong; Sun, Xu-dong; Cai, Li-jun; Liu, Yan-de
2012-01-01
Near infrared diffuse reflectance (NIRS) and ultraviolet (UV) spectral analysis were adopted for quantitative determination of octane number and monoaromatics in fuel oil. Partial least squares regression (PLSR) was used for construction of vibrational spectral calibration models. Variables selection strategy based on mutual information (MI) theory was introduced to optimize the models for improving the precision and reducing the complexity. The results indicate that MI-PLSR method can effectively improve the predictive ability of the models and simplify them. For octane number models, the root mean square error of prediction (RMSEP) and the number of calibration variables were reduced from 0.288 and 401 to 0.111 and 112, respectively, and correlation coefficient (R) was improved from 0.985 to 0.998. For monoaromatics models, RMSEP and the number of calibration variables were reduced from 0.753 and 572 to 0.478 and 37, respectively, and R was improved from 0.996 to 0.998. Vibrational spectral analysis combined with MI-PLSR method can be used for quantitative analysis of fuel oil properties, and improve the cost-effectiveness.
Na, Sun Hee; Jin, Seung-Hyun; Kim, Soo Yong
2006-11-01
Sleep deprivation can affect the waking electroencephalogram (EEG) that may reflect functional organization of the brain. We examined the effect of total sleep deprivation (TSD) on functional organization between different cortical areas from the waking EEG. Waking EEG data were recorded from 18 healthy male volunteers with eyes closed after 8-h night's sleep and after 24 h of TSD. The averaged cross mutual information (A-CMI) after 24 h of TSD were compared to before TSD. 24 h of TSD yielded the decreased A-CMIs in the inter-hemispheric C3-F4, C3-F8, and C3-C4 pairs: therefore, the electrodes that contribute to pairs with significant decrease of A-CMI were C3, F4, F8, and C4. The decreased A-CMIs between C3 and right frontal and central brain areas after 24 h of TSD may reflect the changes of cortico-cortical functional organization by homeostatic process during TSD. Our results of the frontal-area-related A-CMI decreases may support that the frontal brain regions are related to the homeostatic deterioration of brain function due to TSD.
NASA Astrophysics Data System (ADS)
Ji, Songbai; Hartov, Alex; Roberts, David; Paulsen, Keith
2008-03-01
Intraoperative ultrasound (iUS) has emerged as a practical neuronavigational tool for brain shift compensation in image-guided tumor resection surgeries. The use of iUS is optimized when coregistered with preoperative magnetic resonance images (pMR) of the patient's head. However, the fiducial-based registration alone does not necessarily optimize the alignment of internal anatomical structures deep in the brain (e.g., tumor) between iUS and pMR. In this paper, we investigated and evaluated an image-based re-registration scheme to maximize the normalized mutual information (nMI) between iUS and pMR to improve tumor boundary alignment using the fiducial registration as a starting point for optimization. We show that this scheme significantly (p<<0.001) reduces tumor boundary misalignment pre-durotomy. The same technique was employed to measure tumor displacement post-durotomy, and the locally measured tumor displacement was assimilated into a biomechanical model to estimate whole-brain deformation. Our results demonstrate that the nMI re-registration pre-durotomy is critical for obtaining accurate measurement of tumor displacement, which significantly improved model response at the craniotomy when compared with stereopsis data acquired independently from the tumor registration. This automatic and computationally efficient (<2min) re-registration technique is feasible for routine clinical use in the operating room (OR).
Fuzzy Information Retrieval Using Genetic Algorithms and Relevance Feedback.
ERIC Educational Resources Information Center
Petry, Frederick E.; And Others
1993-01-01
Describes an approach that combines concepts from information retrieval, fuzzy set theory, and genetic programing to improve weighted Boolean query formulation via relevance feedback. Highlights include background on information retrieval systems; genetic algorithms; subproblem formulation; and preliminary results based on a testbed. (Contains 12…
Imaging for dismantlement verification: information management and analysis algorithms
Seifert, Allen; Miller, Erin A.; Myjak, Mitchell J.; Robinson, Sean M.; Jarman, Kenneth D.; Misner, Alex C.; Pitts, W. Karl; Woodring, Mitchell L.
2010-09-01
The level of detail discernible in imaging techniques has generally excluded them from consideration as verification tools in inspection regimes. An image will almost certainly contain highly sensitive information, and storing a comparison image will almost certainly violate a cardinal principle of information barriers: that no sensitive information be stored in the system. To overcome this problem, some features of the image might be reduced to a few parameters suitable for definition as an attribute. However, this process must be performed with care. Computing the perimeter, area, and intensity of an object, for example, might reveal sensitive information relating to shape, size, and material composition. This paper presents three analysis algorithms that reduce full image information to non-sensitive feature information. Ultimately, the algorithms are intended to provide only a yes/no response verifying the presence of features in the image. We evaluate the algorithms on both their technical performance in image analysis, and their application with and without an explicitly constructed information barrier. The underlying images can be highly detailed, since they are dynamically generated behind the information barrier. We consider the use of active (conventional) radiography alone and in tandem with passive (auto) radiography.
Ren, X; Gao, H; Sharp, G
2015-06-15
Purpose: The delineation of targets and organs-at-risk is a critical step during image-guided radiation therapy, for which manual contouring is the gold standard. However, it is often time-consuming and may suffer from intra- and inter-rater variability. The purpose of this work is to investigate the automated segmentation. Methods: The automatic segmentation here is based on mutual information (MI), with the atlas from Public Domain Database for Computational Anatomy (PDDCA) with manually drawn contours.Using dice coefficient (DC) as the quantitative measure of segmentation accuracy, we perform leave-one-out cross-validations for all PDDCA images sequentially, during which other images are registered to each chosen image and DC is computed between registered contour and ground truth. Meanwhile, six strategies, including MI, are selected to measure the image similarity, with MI to be the best. Then given a target image to be segmented and an atlas, automatic segmentation consists of: (a) the affine registration step for image positioning; (b) the active demons registration method to register the atlas to the target image; (c) the computation of MI values between the deformed atlas and the target image; (d) the weighted image fusion of three deformed atlas images with highest MI values to form the segmented contour. Results: MI was found to be the best among six studied strategies in the sense that it had the highest positive correlation between similarity measure (e.g., MI values) and DC. For automated segmentation, the weighted image fusion of three deformed atlas images with highest MI values provided the highest DC among four proposed strategies. Conclusion: MI has the highest correlation with DC, and therefore is an appropriate choice for post-registration atlas selection in atlas-based segmentation. Xuhua Ren and Hao Gao were partially supported by the NSFC (#11405105), the 973 Program (#2015CB856000) and the Shanghai Pujiang Talent Program (#14PJ1404500)
Web multimedia information retrieval using improved Bayesian algorithm.
Yu, Yi-Jun; Chen, Chun; Yu, Yi-Min; Lin, Huai-Zhong
2003-01-01
The main thrust of this paper is application of a novel data mining approach on the log of user's feedback to improve web multimedia information retrieval performance. A user space model was constructed based on data mining, and then integrated into the original information space model to improve the accuracy of the new information space model. It can remove clutter and irrelevant text information and help to eliminate mismatch between the page author's expression and the user's understanding and expectation. User space model was also utilized to discover the relationship between high-level and low-level features for assigning weight. The authors proposed improved Bayesian algorithm for data mining. Experiment proved that the authors' proposed algorithm was efficient.
NASA Astrophysics Data System (ADS)
Zhou, Tianci; Chen, Xiao; Faulkner, Thomas; Fradkin, Eduardo
2016-09-01
We investigate the entanglement entropy (EE) of circular entangling cuts in the 2 + 1-dimensional quantum Lifshitz model. The ground state in this model is a spatially conformal invariant state of the Rokhsar-Kivelson type, whose amplitude is the Gibbs weight of 2D Euclidean free boson. We show that the finite subleading corrections of EE to the area-law term, as well as the mutual information, are conformal invariants and calculate them for cylinder, disk-like and spherical manifolds with various spatial cuts. The subtlety due to the boson compactification in the replica trick is carefully addressed. We find that in the geometry of a punctured plane with many small holes, the constant piece of EE is proportional to the number of holes, indicating the ability of entanglement to detect topological information of the configuration. Finally, we compare the mutual information of two small distant disks with Cardy’s relativistic CFT scaling proposal. We find that in the quantum Lifshitz model, the mutual information also scales at long distance with a power determined by the lowest scaling dimension local operator in the theory.
Crossover Improvement for the Genetic Algorithm in Information Retrieval.
ERIC Educational Resources Information Center
Vrajitoru, Dana
1998-01-01
In information retrieval (IR), the aim of genetic algorithms (GA) is to help a system to find, in a huge documents collection, a good reply to a query expressed by the user. Analysis of phenomena seen during the implementation of a GA for IR has led to a new crossover operation, which is introduced and compared to other learning methods.…
C. elegans locomotion analysis using algorithmic information theory.
Skandari, Roghieh; Le Bihan, Nicolas; Manton, Jonathan H
2015-01-01
This article investigates the use of algorithmic information theory to analyse C. elegans datasets. The ability of complexity measures to detect similarity in animals' behaviours is demonstrated and their strengths are compared to methods such as histograms. Introduced quantities are illustrated on a couple of real two-dimensional C. elegans datasets to investigate the thermotaxis and chemotaxis behaviours.
Alpatov, A. V.; Vikhrov, S. P.; Rybina, N. V.
2015-04-15
The processes of self-organization of the surface structure of hydrogenated amorphous silicon are studied by the methods of fluctuation analysis and average mutual information on the basis of atomic-force-microscopy images of the surface. It is found that all of the structures can be characterized by a correlation vector and represented as a superposition of harmonic components and noise. It is shown that, under variations in the technological parameters of the production of a-Si:H films, the correlation properties of their structure vary as well. As the substrate temperature is increased, the formation of structural irregularities becomes less efficient; in this case, the length of the correlation vector and the degree of structural ordering increase. It is shown that the procedure based on the method of fluctuation analysis in combination with the method of average mutual information provides a means for studying the self-organization processes in any structures on different length scales.
A Motion Detection Algorithm Using Local Phase Information
Lazar, Aurel A.; Ukani, Nikul H.; Zhou, Yiyin
2016-01-01
Previous research demonstrated that global phase alone can be used to faithfully represent visual scenes. Here we provide a reconstruction algorithm by using only local phase information. We also demonstrate that local phase alone can be effectively used to detect local motion. The local phase-based motion detector is akin to models employed to detect motion in biological vision, for example, the Reichardt detector. The local phase-based motion detection algorithm introduced here consists of two building blocks. The first building block measures/evaluates the temporal change of the local phase. The temporal derivative of the local phase is shown to exhibit the structure of a second order Volterra kernel with two normalized inputs. We provide an efficient, FFT-based algorithm for implementing the change of the local phase. The second processing building block implements the detector; it compares the maximum of the Radon transform of the local phase derivative with a chosen threshold. We demonstrate examples of applying the local phase-based motion detection algorithm on several video sequences. We also show how the locally detected motion can be used for segmenting moving objects in video scenes and compare our local phase-based algorithm to segmentation achieved with a widely used optic flow algorithm. PMID:26880882
Methods of information theory and algorithmic complexity for network biology.
Zenil, Hector; Kiani, Narsis A; Tegnér, Jesper
2016-03-01
We survey and introduce concepts and tools located at the intersection of information theory and network biology. We show that Shannon's information entropy, compressibility and algorithmic complexity quantify different local and global aspects of synthetic and biological data. We show examples such as the emergence of giant components in Erdös-Rényi random graphs, and the recovery of topological properties from numerical kinetic properties simulating gene expression data. We provide exact theoretical calculations, numerical approximations and error estimations of entropy, algorithmic probability and Kolmogorov complexity for different types of graphs, characterizing their variant and invariant properties. We introduce formal definitions of complexity for both labeled and unlabeled graphs and prove that the Kolmogorov complexity of a labeled graph is a good approximation of its unlabeled Kolmogorov complexity and thus a robust definition of graph complexity.
Based on Multi-sensor Information Fusion Algorithm of TPMS Research
NASA Astrophysics Data System (ADS)
Yulan, Zhou; Yanhong, Zang; Yahong, Lin
In the paper are presented algorithms of TPMS (Tire Pressure Monitoring System) based on multi-sensor information fusion. A Unified mathematical models of information fusion are constructed and three algorithms are used to deal with, which include algorithm based on Bayesian, algorithm based on the relative distance (an improved algorithm of bayesian theory of evidence), algorithm based on multi-sensor weighted fusion. The calculating results shows that the algorithm based on d-s evidence theory of multisensor fusion method better than the algorithm the based on information fusion method or the bayesian method.
Optical tomographic memories: algorithms for the efficient information readout
NASA Astrophysics Data System (ADS)
Pantelic, Dejan V.
1990-07-01
Tomographic alogithms are modified in order to reconstruct the inf ormation previously stored by focusing laser radiation in a volume of photosensitive media. Apriori information about the position of bits of inf ormation is used. 1. THE PRINCIPLES OF TOMOGRAPHIC MEMORIES Tomographic principles can be used to store and reconstruct the inf ormation artificially stored in a bulk of a photosensitive media 1 The information is stored by changing some characteristics of a memory material (e. g. refractive index). Radiation from the two independent light sources (e. g. lasers) is f ocused inside the memory material. In this way the intensity of the light is above the threshold only in the localized point where the light rays intersect. By scanning the material the information can be stored in binary or nary format. When the information is stored it can be read by tomographic methods. However the situation is quite different from the classical tomographic problem. Here a lot of apriori information is present regarding the p0- sitions of the bits of information profile representing single bit and a mode of operation (binary or n-ary). 2. ALGORITHMS FOR THE READOUT OF THE TOMOGRAPHIC MEMORIES Apriori information enables efficient reconstruction of the memory contents. In this paper a few methods for the information readout together with the simulation results will be presented. Special attention will be given to the noise considerations. Two different
An object tracking algorithm with embedded gyro information
NASA Astrophysics Data System (ADS)
Zhang, Yutong; Yan, Ding; Yuan, Yating
2017-01-01
The high speed attitude maneuver of Unmanned Aerial Vehicle (UAV) always causes large motion between adjacent frames of the video stream produced from the camera fixed on the UAV body, which will severely disrupt the performance of image object tracking process. To solve this problem, this paper proposes a method that using a gyroscope fixed on the camera to measure the angular velocity of camera, and then the object position's substantial change in the video stream is predicted. We accomplished the object tracking based on template matching. Experimental result shows that the object tracking algorithm's performance is improved in its efficiency and robustness with embedded gyroscope information.
Network algorithms for information analysis using the Titan Toolkit.
McLendon, William Clarence, III; Baumes, Jeffrey; Wilson, Andrew T.; Wylie, Brian Neil; Shead, Timothy M.
2010-07-01
The analysis of networked activities is dramatically more challenging than many traditional kinds of analysis. A network is defined by a set of entities (people, organizations, banks, computers, etc.) linked by various types of relationships. These entities and relationships are often uninteresting alone, and only become significant in aggregate. The analysis and visualization of these networks is one of the driving factors behind the creation of the Titan Toolkit. Given the broad set of problem domains and the wide ranging databases in use by the information analysis community, the Titan Toolkit's flexible, component based pipeline provides an excellent platform for constructing specific combinations of network algorithms and visualizations.
Information dynamics algorithm for detecting communities in networks
NASA Astrophysics Data System (ADS)
Massaro, Emanuele; Bagnoli, Franco; Guazzini, Andrea; Lió, Pietro
2012-11-01
The problem of community detection is relevant in many scientific disciplines, from social science to statistical physics. Given the impact of community detection in many areas, such as psychology and social sciences, we have addressed the issue of modifying existing well performing algorithms by incorporating elements of the domain application fields, i.e. domain-inspired. We have focused on a psychology and social network-inspired approach which may be useful for further strengthening the link between social network studies and mathematics of community detection. Here we introduce a community-detection algorithm derived from the van Dongen's Markov Cluster algorithm (MCL) method [4] by considering networks' nodes as agents capable to take decisions. In this framework we have introduced a memory factor to mimic a typical human behavior such as the oblivion effect. The method is based on information diffusion and it includes a non-linear processing phase. We test our method on two classical community benchmark and on computer generated networks with known community structure. Our approach has three important features: the capacity of detecting overlapping communities, the capability of identifying communities from an individual point of view and the fine tuning the community detectability with respect to prior knowledge of the data. Finally we discuss how to use a Shannon entropy measure for parameter estimation in complex networks.
The accurate reconstruction of gene regulatory networks from large scale molecular profile datasets represents one of the grand challenges of Systems Biology. The Algorithm for the Reconstruction of Accurate Cellular Networks (ARACNe) represents one of the most effective tools to accomplish this goal. However, the initial Fixed Bandwidth (FB) implementation is both inefficient and unable to deal with sample sets providing largely uneven coverage of the probability density space.
Thermodynamic cost of computation, algorithmic complexity and the information metric
NASA Technical Reports Server (NTRS)
Zurek, W. H.
1989-01-01
Algorithmic complexity is discussed as a computational counterpart to the second law of thermodynamics. It is shown that algorithmic complexity, which is a measure of randomness, sets limits on the thermodynamic cost of computations and casts a new light on the limitations of Maxwell's demon. Algorithmic complexity can also be used to define distance between binary strings.
On Distribution Reduction and Algorithm Implementation in Inconsistent Ordered Information Systems
Zhang, Yanqin
2014-01-01
As one part of our work in ordered information systems, distribution reduction is studied in inconsistent ordered information systems (OISs). Some important properties on distribution reduction are studied and discussed. The dominance matrix is restated for reduction acquisition in dominance relations based information systems. Matrix algorithm for distribution reduction acquisition is stepped. And program is implemented by the algorithm. The approach provides an effective tool for the theoretical research and the applications for ordered information systems in practices. For more detailed and valid illustrations, cases are employed to explain and verify the algorithm and the program which shows the effectiveness of the algorithm in complicated information systems. PMID:25258721
On distribution reduction and algorithm implementation in inconsistent ordered information systems.
Zhang, Yanqin
2014-01-01
As one part of our work in ordered information systems, distribution reduction is studied in inconsistent ordered information systems (OISs). Some important properties on distribution reduction are studied and discussed. The dominance matrix is restated for reduction acquisition in dominance relations based information systems. Matrix algorithm for distribution reduction acquisition is stepped. And program is implemented by the algorithm. The approach provides an effective tool for the theoretical research and the applications for ordered information systems in practices. For more detailed and valid illustrations, cases are employed to explain and verify the algorithm and the program which shows the effectiveness of the algorithm in complicated information systems.
NASA Astrophysics Data System (ADS)
Chen, Lei; Li, Dehua; Yang, Jie
2007-12-01
Constructing virtual international strategy environment needs many kinds of information, such as economy, politic, military, diploma, culture, science, etc. So it is very important to build an information auto-extract, classification, recombination and analysis management system with high efficiency as the foundation and component of military strategy hall. This paper firstly use improved Boost algorithm to classify obtained initial information, then use a strategy intelligence extract algorithm to extract strategy intelligence from initial information to help strategist to analysis information.
An Introduction to Genetic Algorithms and to Their Use in Information Retrieval.
ERIC Educational Resources Information Center
Jones, Gareth; And Others
1994-01-01
Genetic algorithms, a class of nondeterministic algorithms in which the role of chance makes the precise nature of a solution impossible to guarantee, seem to be well suited to combinatorial-optimization problems in information retrieval. Provides an introduction to techniques and characteristics of genetic algorithms and illustrates their…
NASA Astrophysics Data System (ADS)
A. AL-Salhi, Yahya E.; Lu, Songfeng
2016-08-01
Quantum steganography can solve some problems that are considered inefficient in image information concealing. It researches on Quantum image information concealing to have been widely exploited in recent years. Quantum image information concealing can be categorized into quantum image digital blocking, quantum image stereography, anonymity and other branches. Least significant bit (LSB) information concealing plays vital roles in the classical world because many image information concealing algorithms are designed based on it. Firstly, based on the novel enhanced quantum representation (NEQR), image uniform blocks clustering around the concrete the least significant Qu-block (LSQB) information concealing algorithm for quantum image steganography is presented. Secondly, a clustering algorithm is proposed to optimize the concealment of important data. Finally, we used Con-Steg algorithm to conceal the clustered image blocks. Information concealing located on the Fourier domain of an image can achieve the security of image information, thus we further discuss the Fourier domain LSQu-block information concealing algorithm for quantum image based on Quantum Fourier Transforms. In our algorithms, the corresponding unitary Transformations are designed to realize the aim of concealing the secret information to the least significant Qu-block representing color of the quantum cover image. Finally, the procedures of extracting the secret information are illustrated. Quantum image LSQu-block image information concealing algorithm can be applied in many fields according to different needs.
NASA Astrophysics Data System (ADS)
Núñez-Acosta, Elisa; Lerma, Claudia; Márquez, Manlio F.; José, Marco V.
2012-02-01
Herein we introduce the Mutual Information Function (MIF) as a mathematical method to analyze ventricular bigeminy in certain pathological conditions of the heart known to be associated with frequent ventricular arrhythmias. In particular, we show that the MIF is sensitive enough to detect the bigeminy pattern in symbolic series from patients with Andersen-Tawil syndrome as well as in a group of patients from the Sudden Cardiac Death Holter Databases. The results confirm that MIF is an adequate method to detect the autocorrelation between the appearance of sinus and ventricular premature beats resulting in a bigeminy pattern. It is also shown that MIF reflects the bigeminy patterns as a function of the percentage of ventricular premature beats present in the symbolic series and also as a function of the percentage of bigeminy. The MIF was also useful to establish a consistent difference in the bigeminy pattern related to the diurnal and nocturnal periods presumably associated to the circadian rhythm of the heart. Understanding of the ventricular bigeminy patterns throughout 24-hours could provide some insights into the pathogenesis of ventricular tachyarrhythmias in these pathological conditions.
Ken, Soléakhéna; Di Gennaro, Giancarlo; Giulietti, Giovanni; Sebastiano, Fabio; De Carli, Diego; Garreffa, Girolamo; Colonnese, Claudio; Passariello, Roberto; Lotterie, Jean-Albert; Maraviglia, Bruno
2007-07-01
Patients with drug-resistant focal epilepsy may require intracranial investigations with subdural electrodes. These must be correctly localized with respect to the brain cortical surface and require appropriate monitoring. For this purpose, coregistration techniques, which fuse preimplantation 3D magnetic resonance imaging scans with postimplantation computed tomography scans, have been implemented. In order to reduce localization errors due to the fusion process, we used a coregistration method based on the maximization of mutual information (MI) in 11 patients with extratemporal epilepsy who were invasively investigated. Our registration method is based on three processing steps: rigid-body transformation for coregistration, computation of MI as a similarity measure and the use of the Downhill Simplex optimization method. After consistency analysis, the shift of the registration method reached 0.14+/-0.27 mm in translation and 0.03+/-0.14 degrees in rotation, and the accuracies assessed on voxels of skull surface and voxels of the center of the brain volume were 1.42+/-0.61 and 1.15+/-0.53 mm, respectively. The accuracy of the fusion process reached submillimeter range, and results were considered reliable for surgical planning in all studied patients.
Fast Multiscale Algorithms for Information Representation and Fusion
2012-07-01
4 5.1 Experiment: LIDAR Dataset (MSVD using nearest neighbors...implementation of the new multiscale SVD (MSVD) algorithms. We applied the MSVD to a publicly available LIDAR dataset for the purposes of distinguishing...between vegetation and the forest floor. The final results are presented in this report (initial results were reported in the previous quarterly report
A Survey of Stemming Algorithms in Information Retrieval
ERIC Educational Resources Information Center
Moral, Cristian; de Antonio, Angélica; Imbert, Ricardo; Ramírez, Jaime
2014-01-01
Background: During the last fifty years, improved information retrieval techniques have become necessary because of the huge amount of information people have available, which continues to increase rapidly due to the use of new technologies and the Internet. Stemming is one of the processes that can improve information retrieval in terms of…
Algorithm for shortest path search in Geographic Information Systems by using reduced graphs.
Rodríguez-Puente, Rafael; Lazo-Cortés, Manuel S
2013-01-01
The use of Geographic Information Systems has increased considerably since the eighties and nineties. As one of their most demanding applications we can mention shortest paths search. Several studies about shortest path search show the feasibility of using graphs for this purpose. Dijkstra's algorithm is one of the classic shortest path search algorithms. This algorithm is not well suited for shortest path search in large graphs. This is the reason why various modifications to Dijkstra's algorithm have been proposed by several authors using heuristics to reduce the run time of shortest path search. One of the most used heuristic algorithms is the A* algorithm, the main goal is to reduce the run time by reducing the search space. This article proposes a modification of Dijkstra's shortest path search algorithm in reduced graphs. It shows that the cost of the path found in this work, is equal to the cost of the path found using Dijkstra's algorithm in the original graph. The results of finding the shortest path, applying the proposed algorithm, Dijkstra's algorithm and A* algorithm, are compared. This comparison shows that, by applying the approach proposed, it is possible to obtain the optimal path in a similar or even in less time than when using heuristic algorithms.
Developing Information Power Grid Based Algorithms and Software
NASA Technical Reports Server (NTRS)
Dongarra, Jack
1998-01-01
This exploratory study initiated our effort to understand performance modeling on parallel systems. The basic goal of performance modeling is to understand and predict the performance of a computer program or set of programs on a computer system. Performance modeling has numerous applications, including evaluation of algorithms, optimization of code implementations, parallel library development, comparison of system architectures, parallel system design, and procurement of new systems. Our work lays the basis for the construction of parallel libraries that allow for the reconstruction of application codes on several distinct architectures so as to assure performance portability. Following our strategy, once the requirements of applications are well understood, one can then construct a library in a layered fashion. The top level of this library will consist of architecture-independent geometric, numerical, and symbolic algorithms that are needed by the sample of applications. These routines should be written in a language that is portable across the targeted architectures.
Research on Quantum Algorithms at the Institute for Quantum Information
2009-10-17
developed earlier by Aliferis, Gottesman, and Preskill to encompass leakage-reduction units, such as those based on quantum teleportation . They also...NUMBER QA - Research on Quantum Algorithms at the Institute for W91INF-05-I-0294 Quantum lnfonnation 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6...ABSTRACT The central goals ofour project are (I) to bring large-scale quantum computers closer to realization by proposing and analyzing new schemes for
Infrared image non-rigid registration based on regional information entropy demons algorithm
NASA Astrophysics Data System (ADS)
Lu, Chaoliang; Ma, Lihua; Yu, Ming; Cui, Shumin; Wu, Qingrong
2015-02-01
Infrared imaging fault detection which is treated as an ideal, non-contact, non-destructive testing method is applied to the circuit board fault detection. Since Infrared images obtained by handheld infrared camera with wide-angle lens have both rigid and non-rigid deformations. To solve this problem, a new demons algorithm based on regional information entropy was proposed. The new method overcame the shortcomings of traditional demons algorithm that was sensitive to the intensity. First, the information entropy image was gotten by computing regional information entropy of the image. Then, the deformation between the two images was calculated that was the same as demons algorithm. Experimental results demonstrated that the proposed algorithm has better robustness in intensity inconsistent images registration compared with the traditional demons algorithm. Achieving accurate registration between intensity inconsistent infrared images provided strong support for the temperature contrast.
ERIC Educational Resources Information Center
Chen, Hsinchun
1995-01-01
Presents an overview of artificial-intelligence-based inductive learning techniques and their use in information science research. Three methods are discussed: the connectionist Hopfield network; the symbolic ID3/ID5R; evolution-based genetic algorithms. The knowledge representations and algorithms of these methods are examined in the context of…
Binzel, R.P. )
1989-11-01
Since 1985, planetary astronomers have been working to take advantage of a once-per-century apparent alignment between Pluto and its satellite, Charon, which has allowed mutual occultation and transit events to be observed. There events, which will cease in 1990, have permitted the first precise determinations of their individual radii, densities, and surface compositions. In addition, information on their surface albedo distributions can be obtained.
NASA Astrophysics Data System (ADS)
Popov, A.; Zolotarev, V.; Bychkov, S.
2016-11-01
This paper examines the results of experimental studies of a previously submitted combined algorithm designed to increase the reliability of information systems. The data that illustrates the organization and conduct of the studies is provided. Within the framework of a comparison of As a part of the study conducted, the comparison of the experimental data of simulation modeling and the data of the functioning of the real information system was made. The hypothesis of the homogeneity of the logical structure of the information systems was formulated, thus enabling to reconfigure the algorithm presented, - more specifically, to transform it into the model for the analysis and prediction of arbitrary information systems. The results presented can be used for further research in this direction. The data of the opportunity to predict the functioning of the information systems can be used for strategic and economic planning. The algorithm can be used as a means for providing information security.
Warszycki, Dawid; Śmieja, Marek; Kafel, Rafał
2017-02-09
The Average Information Content Maximization algorithm (AIC-MAX) based on mutual information maximization was recently introduced to select the most discriminatory features. Here, this methodology was applied to select the most significant bits from the Klekota-Roth fingerprint for serotonin receptors ligands as well as to select the most important features for distinguishing ligands with activity for one receptor versus another. The interpretation of selected bits and machine-learning experiments performed using the reduced interpretations outperformed the raw fingerprints and indicated the most important structural features of the analyzed ligands in terms of activity and selectivity. Moreover, the AIC-MAX methodology applied here for serotonin receptor ligands can also be applied to other target classes.
Evolution of mutualism between species
Post, W.M.; Travis, C.C.; DeAngelis, D.L.
1980-01-01
Recent theoretical work on mutualism, the interaction between species populations that is mutually beneficial, is reviewed. Several ecological facts that should be addressed in the construction of dynamic models for mutualism are examined. Basic terminology is clarified. (PSB)
Representing Uncertain Geographical Information with Algorithmic Map Caricatures
NASA Astrophysics Data System (ADS)
Brunsdon, Chris
2016-04-01
A great deal of geographical information - including the results ion data analysis - is imprecise in some way. For example the the results of geostatistical interpolation should consist not only of point estimates of the value of some quantity at points in space, but also of confidence intervals or standard errors of these estimators. Similarly, mappings of contour lines derived form such interpolations will also be characterised by uncertainty. However, most computerized cartography tools are designed to provide 'crisp' representations of geographical information, such as sharply drawn lines, or clearly delineated areas. In this talk, the use of 'fuzzy' or 'sketchy' cartographic tools will be demonstrated - where maps have a hand-drawn appearance and the degree of 'roughness' and other related characteristics can be used to convey the degree of uncertainty associated with estimated quantities being mapped. The tools used to do this are available as an R package, which will be described in the talk.
Developing Information Power Grid Based Algorithms and Software
NASA Technical Reports Server (NTRS)
Dongarra, Jack
1998-01-01
This was an exploratory study to enhance our understanding of problems involved in developing large scale applications in a heterogeneous distributed environment. It is likely that the large scale applications of the future will be built by coupling specialized computational modules together. For example, efforts now exist to couple ocean and atmospheric prediction codes to simulate a more complete climate system. These two applications differ in many respects. They have different grids, the data is in different unit systems and the algorithms for inte,-rating in time are different. In addition the code for each application is likely to have been developed on different architectures and tend to have poor performance when run on an architecture for which the code was not designed, if it runs at all. Architectural differences may also induce differences in data representation which effect precision and convergence criteria as well as data transfer issues. In order to couple such dissimilar codes some form of translation must be present. This translation should be able to handle interpolation from one grid to another as well as construction of the correct data field in the correct units from available data. Even if a code is to be developed from scratch, a modular approach will likely be followed in that standard scientific packages will be used to do the more mundane tasks such as linear algebra or Fourier transform operations. This approach allows the developers to concentrate on their science rather than becoming experts in linear algebra or signal processing. Problems associated with this development approach include difficulties associated with data extraction and translation from one module to another, module performance on different nodal architectures, and others. In addition to these data and software issues there exists operational issues such as platform stability and resource management.
Feature weighted naïve Bayes algorithm for information retrieval of enterprise systems
NASA Astrophysics Data System (ADS)
Wang, Li; Ji, Ping; Qi, Jing; Shan, Siqing; Bi, Zhuming; Deng, Weiguo; Zhang, Naijing
2014-01-01
Automated information retrieval is critical for enterprise information systems to acquire knowledge from the vast amount of data sets. One challenge in information retrieval is text classification. Current practices rely heavily on the classical naïve Bayes algorithm due to its simplicity and robustness. However, results from this algorithm are not always satisfactory. In this article, the limitations of the naïve Bayes algorithm are discussed, and it is found that the assumption on the independence of terms is the main reason for an unsatisfactory classification in many real-world applications. To overcome the limitations, the dependent factors are considered by integrating a term frequency-inverse document frequency (TF-IDF) weighting algorithm in the naïve Bayes classification. Moreover, the TF-IDF algorithm itself is improved so that both frequencies and distribution information are taken into consideration. To illustrate the effectiveness of the proposed method, two simulation experiments were conducted, and the comparisons with other classification methods have shown that the proposed method has outperformed other existing algorithms in terms of precision and index recall rate.
Wang, Jeen-Shing; Lin, Che-Wei; Yang, Ya-Ting C; Ho, Yu-Jen
2012-10-01
This paper presents a walking pattern classification and a walking distance estimation algorithm using gait phase information. A gait phase information retrieval algorithm was developed to analyze the duration of the phases in a gait cycle (i.e., stance, push-off, swing, and heel-strike phases). Based on the gait phase information, a decision tree based on the relations between gait phases was constructed for classifying three different walking patterns (level walking, walking upstairs, and walking downstairs). Gait phase information was also used for developing a walking distance estimation algorithm. The walking distance estimation algorithm consists of the processes of step count and step length estimation. The proposed walking pattern classification and walking distance estimation algorithm have been validated by a series of experiments. The accuracy of the proposed walking pattern classification was 98.87%, 95.45%, and 95.00% for level walking, walking upstairs, and walking downstairs, respectively. The accuracy of the proposed walking distance estimation algorithm was 96.42% over a walking distance.
Experiments in Discourse Analysis Impact on Information Classification and Retrieval Algorithms.
ERIC Educational Resources Information Center
Morato, Jorge; Llorens, J.; Genova, G.; Moreiro, J. A.
2003-01-01
Discusses the inclusion of contextual information in indexing and retrieval systems to improve results and the ability to carry out text analysis by means of linguistic knowledge. Presents research that investigated whether discourse variables have an impact on information and retrieval and classification algorithms. (Author/LRW)
A General Algorithm for Reusing Krylov Subspace Information. I. Unsteady Navier-Stokes
NASA Technical Reports Server (NTRS)
Carpenter, Mark H.; Vuik, C.; Lucas, Peter; vanGijzen, Martin; Bijl, Hester
2010-01-01
A general algorithm is developed that reuses available information to accelerate the iterative convergence of linear systems with multiple right-hand sides A x = b (sup i), which are commonly encountered in steady or unsteady simulations of nonlinear equations. The algorithm is based on the classical GMRES algorithm with eigenvector enrichment but also includes a Galerkin projection preprocessing step and several novel Krylov subspace reuse strategies. The new approach is applied to a set of test problems, including an unsteady turbulent airfoil, and is shown in some cases to provide significant improvement in computational efficiency relative to baseline approaches.
General A Scheme to Share Information via Employing Discrete Algorithm to Quantum States
NASA Astrophysics Data System (ADS)
Kang, Guo-Dong; Fang, Mao-Fa
2011-02-01
We propose a protocol for information sharing between two legitimate parties (Bob and Alice) via public-key cryptography. In particular, we specialize the protocol by employing discrete algorithm under mod that maps integers to quantum states via photon rotations. Based on this algorithm, we find that the protocol is secure under various classes of attacks. Specially, owe to the algorithm, the security of the classical privacy contained in the quantum public-key and the corresponding ciphertext is guaranteed. And the protocol is robust against the impersonation attack and the active wiretapping attack by designing particular checking processing, thus the protocol is valid.
Algorithmic information theory and the hidden variable question
NASA Technical Reports Server (NTRS)
Fuchs, Christopher
1992-01-01
The admissibility of certain nonlocal hidden-variable theories are explained via information theory. Consider a pair of Stern-Gerlach devices with fixed nonparallel orientations that periodically perform spin measurements on identically prepared pairs of electrons in the singlet spin state. Suppose the outcomes are recorded as binary strings l and r (with l sub n and r sub n denoting their n-length prefixes). The hidden-variable theories considered here require that there exists a recursive function which may be used to transform l sub n into r sub n for any n. This note demonstrates that such a theory cannot reproduce all the statistical predictions of quantum mechanics. Specifically, consider an ensemble of outcome pairs (l,r). From the associated probability measure, the Shannon entropies H sub n and H bar sub n for strings l sub n and pairs (l sub n, r sub n) may be formed. It is shown that such a theory requires that the absolute value of H bar sub n - H sub n be bounded - contrasting the quantum mechanical prediction that it grow with n.
Deciphering the Minimal Algorithm for Development and Information-genesis
NASA Astrophysics Data System (ADS)
Li, Zhiyuan; Tang, Chao; Li, Hao
During development, cells with identical genomes acquires different fates in a highly organized manner. In order to decipher the principles underlining development, we used C.elegans as the model organism. Based on a large set of microscopy imaging, we first constructed a ``standard worm'' in silico: from the single zygotic cell to about 500 cell stage, the lineage, position, cell-cell contact and gene expression dynamics are quantified for each cell in order to investigate principles underlining these intensive data. Next, we reverse-engineered the possible gene-gene/cell-cell interaction rules that are capable of running a dynamic model recapitulating the early fate decisions during C.elegans development. we further formulized the C.elegans embryogenesis in the language of information genesis. Analysis towards data and model uncovered the global landscape of development in the cell fate space, suggested possible gene regulatory architectures and cell signaling processes, revealed diversity and robustness as the essential trade-offs in development, and demonstrated general strategies in building multicellular organisms.
Wu, Jian; Peng, Dao-Li
2011-04-01
The difference analysis of spectrum among tree species and the improvement of classification algorithm are the difficult points of extracting tree species information using remote sensing images, and are also the keys to improving the accuracy in the tree species information extraction in farmland returned to forests area. TM images were selected in this study, and the spectral indexes that could distinguish tree species information were filtered by analyzing tree species spectrum. Afterwards, the information of tree species was extracted using improved support vector machine algorithm. Although errors and confusion exist, this method shows satisfying results with an overall accuracy of 81.7%. The corresponding result of the traditional method is 72.5%. The method in this paper can achieve a more precise information extraction of tree species and the results can meet the demand of accurate monitoring and decision-making. This method is significant to the rapid assessment of project quality.
Mutually Exclusive, Complementary, or . . .
ERIC Educational Resources Information Center
Schloemer, Cathy G.
2016-01-01
Whether students are beginning their study of probability or are well into it, distinctions between complementary sets and mutually exclusive sets can be confusing. Cathy Schloemer writes in this article that for years she used typical classroom examples but was not happy with the student engagement or the level of understanding they produced.…
ERIC Educational Resources Information Center
Siskin, Leslie Santee
2016-01-01
Building on an expanded concept of mutual adaptation, this chapter explores a distinctive and successful aspect of International Baccalaureate's effort to scale up, as they moved to expand their programs and support services in Title I schools. Based on a three-year, mixed-methods study, it offers a case where we see not only local adaptations…
NASA Astrophysics Data System (ADS)
Wu, Qiong; Wang, Jihua; Wang, Cheng; Xu, Tongyu
2016-09-01
Genetic algorithm (GA) has a significant effect in the band optimization selection of Partial Least Squares (PLS) correction model. Application of genetic algorithm in selection of characteristic bands can achieve the optimal solution more rapidly, effectively improve measurement accuracy and reduce variables used for modeling. In this study, genetic algorithm as a module conducted band selection for the application of hyperspectral imaging in nondestructive testing of corn seedling leaves, and GA-PLS model was established. In addition, PLS quantitative model of full spectrum and experienced-spectrum region were established in order to suggest the feasibility of genetic algorithm optimizing wave bands, and model robustness was evaluated. There were 12 characteristic bands selected by genetic algorithm. With reflectance values of corn seedling component information at spectral characteristic wavelengths corresponding to 12 characteristic bands as variables, a model about SPAD values of corn leaves acquired was established by PLS, and modeling results showed r = 0.7825. The model results were better than those of PLS model established in full spectrum and experience-based selected bands. The results suggested that genetic algorithm can be used for data optimization and screening before establishing the corn seedling component information model by PLS method and effectively increase measurement accuracy and greatly reduce variables used for modeling.
Binary 3D image interpolation algorithm based global information and adaptive curves fitting
NASA Astrophysics Data System (ADS)
Zhang, Tian-yi; Zhang, Jin-hao; Guan, Xiang-chen; Li, Qiu-ping; He, Meng
2013-08-01
Interpolation is a necessary processing step in 3-D reconstruction because of the non-uniform resolution. Conventional interpolation methods simply use two slices to obtain the missing slices between the two slices .when the key slice is missing, those methods may fail to recover it only employing the local information .And the surface of 3D object especially for the medical tissues may be highly complicated, so a single interpolation can hardly get high-quality 3D image. We propose a novel binary 3D image interpolation algorithm. The proposed algorithm takes advantages of the global information. It chooses the best curve adaptively from lots of curves based on the complexity of the surface of 3D object. The results of this algorithm are compared with other interpolation methods on artificial objects and real breast cancer tumor to demonstrate the excellent performance.
A Fuzzy Genetic Algorithm Approach to an Adaptive Information Retrieval Agent.
ERIC Educational Resources Information Center
Martin-Bautista, Maria J.; Vila, Maria-Amparo; Larsen, Henrik Legind
1999-01-01
Presents an approach to a Genetic Information Retrieval Agent Filter (GIRAF) that filters and ranks documents retrieved from the Internet according to users' preferences by using a Genetic Algorithm and fuzzy set theory to handle the imprecision of users' preferences and users' evaluation of the retrieved documents. (Author/LRW)
Technology Transfer Automated Retrieval System (TEKTRAN)
Crop canopy sensors have proven effective at determining site-specific nitrogen (N) needs, but several Midwest states use different algorithms to predict site-specific N need. The objective of this research was to determine if soil information can be used to improve the Missouri canopy sensor algori...
76 FR 35084 - Mutual to Stock Conversion Application
Federal Register 2010, 2011, 2012, 2013, 2014
2011-06-15
... Office of Thrift Supervision Mutual to Stock Conversion Application AGENCY: Office of Thrift Supervision... following information collection. Title of Proposal: Mutual to Stock Conversion Application. OMB Number... proposed stock conversion. The purpose of the information collection is to provide OTS with the...
Code of Federal Regulations, 2012 CFR
2012-04-01
... mutual), mutual marine insurance companies, mutual fire insurance companies issuing perpetual policies... Companies § 1.831-3 Tax on insurance companies (other than life or mutual), mutual marine insurance... insurance business within the United States, and all mutual marine insurance companies and mutual fire...
NASA Astrophysics Data System (ADS)
Zhang, Chun; Fei, Shu-Min; Zhou, Xing-Peng
2012-12-01
In this paper, we explore the technology of tracking a group of targets with correlated motions in a wireless sensor network. Since a group of targets moves collectively and is restricted within a limited region, it is not worth consuming scarce resources of sensors in computing the trajectory of each single target. Hence, in this paper, the problem is modeled as tracking a geographical continuous region covered by all targets. A tracking algorithm is proposed to estimate the region covered by the target group in each sampling period. Based on the locations of sensors and the azimuthal angle of arrival (AOA) information, the estimated region covering all the group members is obtained. Algorithm analysis provides the fundamental limits to the accuracy of localizing a target group. Simulation results show that the proposed algorithm is superior to the existing hull algorithm due to the reduction in estimation error, which is between 10% and 40% of the hull algorithm, with a similar density of sensors. And when the density of sensors increases, the localization accuracy of the proposed algorithm improves dramatically.
A Novel Algorithm for the Precise Calculation of the Maximal Information Coefficient
Zhang, Yi; Jia, Shili; Huang, Haiyun; Qiu, Jiqing; Zhou, Changjie
2014-01-01
Measuring associations is an important scientific task. A novel measurement method maximal information coefficient (MIC) was proposed to identify a broad class of associations. As foreseen by its authors, MIC implementation algorithm ApproxMaxMI is not always convergent to real MIC values. An algorithm called SG (Simulated annealing and Genetic) was developed to facilitate the optimal calculation of MIC, and the convergence of SG was proved based on Markov theory. When run on fruit fly data set including 1,000,000 pairs of gene expression profiles, the mean squared difference between SG and the exhaustive algorithm is 0.00075499, compared with 0.1834 in the case of ApproxMaxMI. The software SGMIC and its manual are freely available at http://lxy.depart.hebust.edu.cn/SGMIC/SGMIC.htm. PMID:25322794
Defense mutualisms enhance plant diversification
Weber, Marjorie G.; Agrawal, Anurag A.
2014-01-01
The ability of plants to form mutualistic relationships with animal defenders has long been suspected to influence their evolutionary success, both by decreasing extinction risk and by increasing opportunity for speciation through an expanded realized niche. Nonetheless, the hypothesis that defense mutualisms consistently enhance plant diversification across lineages has not been well tested due to a lack of phenotypic and phylogenetic information. Using a global analysis, we show that the >100 vascular plant families in which species have evolved extrafloral nectaries (EFNs), sugar-secreting organs that recruit arthropod mutualists, have twofold higher diversification rates than families that lack species with EFNs. Zooming in on six distantly related plant clades, trait-dependent diversification models confirmed the tendency for lineages with EFNs to display increased rates of diversification. These results were consistent across methodological approaches. Inference using reversible-jump Markov chain Monte Carlo (MCMC) to model the placement and number of rate shifts revealed that high net diversification rates in EFN clades were driven by an increased number of positive rate shifts following EFN evolution compared with sister clades, suggesting that EFNs may be indirect facilitators of diversification. Our replicated analysis indicates that defense mutualisms put lineages on a path toward increased diversification rates within and between clades, and is concordant with the hypothesis that mutualistic interactions with animals can have an impact on deep macroevolutionary patterns and enhance plant diversity. PMID:25349406
Study of information hiding algorithm based on GHM and color transfer theory
NASA Astrophysics Data System (ADS)
Ren, Shuai; Mu, De-Jun; Zhang, Tao; Hu, Wei
2009-11-01
Taking the feature that the energy of the image would gather and spread on four components ( LL 2, LH 2, HL 2 and HH 2) in the sub-image after first-order GHM multi-wavelet-transform. And by using the color control ability of lαβ color space in color transfer theory (CTT), an information hiding algorithm based on GHM-CTT is proposed. In this way, the robust parameters are embedded in the LL 2, the hidden information is set in LH 2 and HL 2 with RAID4, and fragile sign is set in HH 2. The consistence between the embedded data bits’ order and the embedded code of the sub-image is improved by using the chaotic mapping and the genetic algorithm. Experimental results indicate that the GHM-CTT can increase the imperceptibility by 15.72% averagely and robustness by 18.89% at least.
Sera White
2012-04-01
This thesis presents a research study using one year of driving data obtained from plug-in hybrid electric vehicles (PHEV) located in Sacramento and San Francisco, California to determine the effectiveness of incorporating geographic information into vehicle performance algorithms. Sacramento and San Francisco were chosen because of the availability of high resolution (1/9 arc second) digital elevation data. First, I present a method for obtaining instantaneous road slope, given a latitude and longitude, and introduce its use into common driving intensity algorithms. I show that for trips characterized by >40m of net elevation change (from key on to key off), the use of instantaneous road slope significantly changes the results of driving intensity calculations. For trips exhibiting elevation loss, algorithms ignoring road slope overestimated driving intensity by as much as 211 Wh/mile, while for trips exhibiting elevation gain these algorithms underestimated driving intensity by as much as 333 Wh/mile. Second, I describe and test an algorithm that incorporates vehicle route type into computations of city and highway fuel economy. Route type was determined by intersecting trip GPS points with ESRI StreetMap road types and assigning each trip as either city or highway route type according to whichever road type comprised the largest distance traveled. The fuel economy results produced by the geographic classification were compared to the fuel economy results produced by algorithms that assign route type based on average speed or driving style. Most results were within 1 mile per gallon ({approx}3%) of one another; the largest difference was 1.4 miles per gallon for charge depleting highway trips. The methods for acquiring and using geographic data introduced in this thesis will enable other vehicle technology researchers to incorporate geographic data into their research problems.
Bat-Inspired Algorithm Based Query Expansion for Medical Web Information Retrieval.
Khennak, Ilyes; Drias, Habiba
2017-02-01
With the increasing amount of medical data available on the Web, looking for health information has become one of the most widely searched topics on the Internet. Patients and people of several backgrounds are now using Web search engines to acquire medical information, including information about a specific disease, medical treatment or professional advice. Nonetheless, due to a lack of medical knowledge, many laypeople have difficulties in forming appropriate queries to articulate their inquiries, which deem their search queries to be imprecise due the use of unclear keywords. The use of these ambiguous and vague queries to describe the patients' needs has resulted in a failure of Web search engines to retrieve accurate and relevant information. One of the most natural and promising method to overcome this drawback is Query Expansion. In this paper, an original approach based on Bat Algorithm is proposed to improve the retrieval effectiveness of query expansion in medical field. In contrast to the existing literature, the proposed approach uses Bat Algorithm to find the best expanded query among a set of expanded query candidates, while maintaining low computational complexity. Moreover, this new approach allows the determination of the length of the expanded query empirically. Numerical results on MEDLINE, the on-line medical information database, show that the proposed approach is more effective and efficient compared to the baseline.
ERIC Educational Resources Information Center
Engelmann, Tanja; Kolodziej, Richard; Hesse, Friedrich W.
2014-01-01
Empirical studies have proven the effectiveness of the knowledge and information awareness approach of Engelmann and colleagues for improving collaboration and collaborative problem-solving performance of spatially distributed group members. This approach informs group members about both their collaborators' knowledge structures and their…
FIPSDock: a new molecular docking technique driven by fully informed swarm optimization algorithm.
Liu, Yu; Zhao, Lei; Li, Wentao; Zhao, Dongyu; Song, Miao; Yang, Yongliang
2013-01-05
The accurate prediction of protein-ligand binding is of great importance for rational drug design. We present herein a novel docking algorithm called as FIPSDock, which implements a variant of the Fully Informed Particle Swarm (FIPS) optimization method and adopts the newly developed energy function of AutoDock 4.20 suite for solving flexible protein-ligand docking problems. The search ability and docking accuracy of FIPSDock were first evaluated by multiple cognate docking experiments. In a benchmarking test for 77 protein/ligand complex structures derived from GOLD benchmark set, FIPSDock has obtained a successful predicting rate of 93.5% and outperformed a few docking programs including particle swarm optimization (PSO)@AutoDock, SODOCK, AutoDock, DOCK, Glide, GOLD, FlexX, Surflex, and MolDock. More importantly, FIPSDock was evaluated against PSO@AutoDock, SODOCK, and AutoDock 4.20 suite by cross-docking experiments of 74 protein-ligand complexes among eight protein targets (CDK2, ESR1, F2, MAPK14, MMP8, MMP13, PDE4B, and PDE5A) derived from Sutherland-crossdock-set. Remarkably, FIPSDock is superior to PSO@AutoDock, SODOCK, and AutoDock in seven out of eight cross-docking experiments. The results reveal that FIPS algorithm might be more suitable than the conventional genetic algorithm-based algorithms in dealing with highly flexible docking problems.
Covariant mutually unbiased bases
NASA Astrophysics Data System (ADS)
Carmeli, Claudio; Schultz, Jussi; Toigo, Alessandro
2016-06-01
The connection between maximal sets of mutually unbiased bases (MUBs) in a prime-power dimensional Hilbert space and finite phase-space geometries is well known. In this article, we classify MUBs according to their degree of covariance with respect to the natural symmetries of a finite phase-space, which are the group of its affine symplectic transformations. We prove that there exist maximal sets of MUBs that are covariant with respect to the full group only in odd prime-power dimensional spaces, and in this case, their equivalence class is actually unique. Despite this limitation, we show that in dimension 2r covariance can still be achieved by restricting to proper subgroups of the symplectic group, that constitute the finite analogues of the oscillator group. For these subgroups, we explicitly construct the unitary operators yielding the covariance.
SSA-ME Detection of cancer driver genes using mutual exclusivity by small subnetwork analysis
Pulido-Tamayo, Sergio; Weytjens, Bram; De Maeyer, Dries; Marchal, Kathleen
2016-01-01
Because of its clonal evolution a tumor rarely contains multiple genomic alterations in the same pathway as disrupting the pathway by one gene often is sufficient to confer the complete fitness advantage. As a result, many cancer driver genes display mutual exclusivity across tumors. However, searching for mutually exclusive gene sets requires analyzing all possible combinations of genes, leading to a problem which is typically too computationally complex to be solved without a stringent a priori filtering, restricting the mutations included in the analysis. To overcome this problem, we present SSA-ME, a network-based method to detect cancer driver genes based on independently scoring small subnetworks for mutual exclusivity using a reinforced learning approach. Because of the algorithmic efficiency, no stringent upfront filtering is required. Analysis of TCGA cancer datasets illustrates the added value of SSA-ME: well-known recurrently mutated but also rarely mutated drivers are prioritized. We show that using mutual exclusivity to detect cancer driver genes is complementary to state-of-the-art approaches. This framework, in which a large number of small subnetworks are being analyzed in order to solve a computationally complex problem (SSA), can be generically applied to any problem in which local neighborhoods in a network hold useful information. PMID:27808240
Bearing fault component identification using information gain and machine learning algorithms
NASA Astrophysics Data System (ADS)
Vinay, Vakharia; Kumar, Gupta Vijay; Kumar, Kankar Pavan
2015-04-01
In the present study an attempt has been made to identify various bearing faults using machine learning algorithm. Vibration signals obtained from faults in inner race, outer race, rolling element and combined faults are considered. Raw vibration signal cannot be used directly since vibration signals are masked by noise. To overcome this difficulty combined time frequency domain method such as wavelet transform is used. Further wavelet selection criteria based on minimum permutation entropy is employed to select most appropriate base wavelet. Statistical features from selected wavelet coefficients are calculated to form feature vector. To reduce size of feature vector information gain attribute selection method is employed. Modified feature set is fed in to machine learning algorithm such as random forest and self-organizing map for getting maximize fault identification efficiency. Results obtained revealed that attribute selection method shows improvement in fault identification accuracy of bearing components.
Robust CPD Algorithm for Non-Rigid Point Set Registration Based on Structure Information
Peng, Lei; Li, Guangyao; Xiao, Mang; Xie, Li
2016-01-01
Recently, the Coherent Point Drift (CPD) algorithm has become a very popular and efficient method for point set registration. However, this method does not take into consideration the neighborhood structure information of points to find the correspondence and requires a manual assignment of the outlier ratio. Therefore, CPD is not robust for large degrees of degradation. In this paper, an improved method is proposed to overcome the two limitations of CPD. A structure descriptor, such as shape context, is used to perform the auxiliary calculation of the correspondence, and the proportion of each GMM component is adjusted by the similarity. The outlier ratio is formulated in the EM framework so that it can be automatically calculated and optimized iteratively. The experimental results on both synthetic data and real data demonstrate that the proposed method described here is more robust to deformation, noise, occlusion, and outliers than CPD and other state-of-the-art algorithms. PMID:26866918
An information-bearing seed for nucleating algorithmic self-assembly.
Barish, Robert D; Schulman, Rebecca; Rothemund, Paul W K; Winfree, Erik
2009-04-14
Self-assembly creates natural mineral, chemical, and biological structures of great complexity. Often, the same starting materials have the potential to form an infinite variety of distinct structures; information in a seed molecule can determine which form is grown as well as where and when. These phenomena can be exploited to program the growth of complex supramolecular structures, as demonstrated by the algorithmic self-assembly of DNA tiles. However, the lack of effective seeds has limited the reliability and yield of algorithmic crystals. Here, we present a programmable DNA origami seed that can display up to 32 distinct binding sites and demonstrate the use of seeds to nucleate three types of algorithmic crystals. In the simplest case, the starting materials are a set of tiles that can form crystalline ribbons of any width; the seed directs assembly of a chosen width with >90% yield. Increased structural diversity is obtained by using tiles that copy a binary string from layer to layer; the seed specifies the initial string and triggers growth under near-optimal conditions where the bit copying error rate is <0.2%. Increased structural complexity is achieved by using tiles that generate a binary counting pattern; the seed specifies the initial value for the counter. Self-assembly proceeds in a one-pot annealing reaction involving up to 300 DNA strands containing >17 kb of sequence information. In sum, this work demonstrates how DNA origami seeds enable the easy, high-yield, low-error-rate growth of algorithmic crystals as a route toward programmable bottom-up fabrication.
Code of Federal Regulations, 2012 CFR
2012-04-01
... mutual), mutual marine insurance companies, and mutual fire insurance companies issuing perpetual... insurance companies (other than life or mutual), mutual marine insurance companies, and mutual fire... marine insurance companies and mutual fire insurance companies exclusively issuing either...
NASA Astrophysics Data System (ADS)
Friesdorf, Florian; Pangercic, Dejan; Bubb, Heiner; Beetz, Michael
In mac, an ergonomic dialog-system and algorithms will be developed that enable human experts and companions to be integrated into knowledge gathering and decision making processes of highly complex cognitive systems (e.g. Assistive Household as manifested further in the paper). In this event we propose to join algorithms and methodologies coming from Ergonomics and Artificial Intelligence that: a) make cognitive systems more congenial for non-expert humans, b) facilitate their comprehension by utilizing a high-level expandable control code for human experts and c) augment representation of such cognitive system into “deep representation” obtained through an interaction with human companions.
An algorithmic and information-theoretic approach to multimetric index construction
Schoolmaster, Donald R.; Grace, James B.; Schweiger, E. William; Guntenspergen, Glenn R.; Mitchell, Brian R.; Miller, Kathryn M.; Little, Amanda M.
2013-01-01
The use of multimetric indices (MMIs), such as the widely used index of biological integrity (IBI), to measure, track, summarize and infer the overall impact of human disturbance on biological communities has been steadily growing in recent years. Initially, MMIs were developed for aquatic communities using pre-selected biological metrics as indicators of system integrity. As interest in these bioassessment tools has grown, so have the types of biological systems to which they are applied. For many ecosystem types the appropriate biological metrics to use as measures of biological integrity are not known a priori. As a result, a variety of ad hoc protocols for selecting metrics empirically has developed. However, the assumptions made by proposed protocols have not be explicitly described or justified, causing many investigators to call for a clear, repeatable methodology for developing empirically derived metrics and indices that can be applied to any biological system. An issue of particular importance that has not been sufficiently addressed is the way that individual metrics combine to produce an MMI that is a sensitive composite indicator of human disturbance. In this paper, we present and demonstrate an algorithm for constructing MMIs given a set of candidate metrics and a measure of human disturbance. The algorithm uses each metric to inform a candidate MMI, and then uses information-theoretic principles to select MMIs that capture the information in the multidimensional system response from among possible MMIs. Such an approach can be used to create purely empirical (data-based) MMIs or can, optionally, be influenced by expert opinion or biological theory through the use of a weighting vector to create value-weighted MMIs. We demonstrate the algorithm with simulated data to demonstrate the predictive capacity of the final MMIs and with real data from wetlands from Acadia and Rocky Mountain National Parks. For the Acadia wetland data, the algorithm identified
ERIC Educational Resources Information Center
Stanford Univ., CA. School Mathematics Study Group.
This is the second unit of a 15-unit School Mathematics Study Group (SMSG) mathematics text for high school students. Topics presented in the first chapter (Informal Algorithms and Flow Charts) include: changing a flat tire; algorithms, flow charts, and computers; assignment and variables; input and output; using a variable as a counter; decisions…
NASA Astrophysics Data System (ADS)
Cohn, T. A.; Lane, W. L.; Baier, W. G.
This paper presents the expected moments algorithm (EMA), a simple and efficient method for incorporating historical and paleoflood information into flood frequency studies. EMA can utilize three types of at-site flood information: systematic stream gage record; information about the magnitude of historical floods; and knowledge of the number of years in the historical period when no large flood occurred. EMA employs an iterative procedure to compute method-of-moments parameter estimates. Initial parameter estimates are calculated from systematic stream gage data. These moments are then updated by including the measured historical peaks and the expected moments, given the previously estimated parameters, of the below-threshold floods from the historical period. The updated moments result in new parameter estimates, and the last two steps are repeated until the algorithm converges. Monte Carlo simulations compare EMA, Bulletin 17B's [United States Water Resources Council, 1982] historically weighted moments adjustment, and maximum likelihood estimators when fitting the three parameters of the log-Pearson type III distribution. These simulations demonstrate that EMA is more efficient than the Bulletin 17B method, and that it is nearly as efficient as maximum likelihood estimation (MLE). The experiments also suggest that EMA has two advantages over MLE when dealing with the log-Pearson type III distribution: It appears that EMA estimates always exist and that they are unique, although neither result has been proven. EMA can be used with binomial or interval-censored data and with any distributional family amenable to method-of-moments estimation.
Cohn, T.A.; Lane, W.L.; Baier, W.G.
1997-01-01
This paper presents the expected moments algorithm (EMA), a simple and efficient method for incorporating historical and paleoflood information into flood frequency studies. EMA can utilize three types of at-site flood information: systematic stream gage record: information about the magnitude of historical floods; and knowledge of the number of years in the historical period when no large flood occurred. EMA employs an iterative procedure to compute method-of-moments parameter estimates. Initial parameter estimates are calculated from systematic stream gage data. These moments are then updated by including the measured historical peaks and the expected moments, given the previously estimated parameters of the below-threshold floods from the historical period. The updated moments result in new parameter estimates, and the last two steps are repeated until the algorithm converges. Monte Carlo simulations compare EMA, Bulletin 17B's [United States Water Resources Council, 1982] historically weighted moments adjustment, and maximum likelihood estimators when fitting the three parameters of the log-Pearson type III distribution. These simulations demonstrate that EMA is more efficient than the Bulletin 17B method, and that it is nearly as efficient as maximum likelihood estimation (MLE). The experiments also suggest that EMA has two advantages over MLE when dealing with the log-Pearson type III distribution: It appears that EMA estimates always exist and that they are unique, although neither result has been proven. EMA can be used with binomial or interval-censored data and with any distributional family amenable to method-of-moments estimation.
Devine, Sean D
2016-02-01
Replication can be envisaged as a computational process that is able to generate and maintain order far-from-equilibrium. Replication processes, can self-regulate, as the drive to replicate can counter degradation processes that impact on a system. The capability of replicated structures to access high quality energy and eject disorder allows Landauer's principle, in conjunction with Algorithmic Information Theory, to quantify the entropy requirements to maintain a system far-from-equilibrium. Using Landauer's principle, where destabilising processes, operating under the second law of thermodynamics, change the information content or the algorithmic entropy of a system by ΔH bits, replication processes can access order, eject disorder, and counter the change without outside interventions. Both diversity in replicated structures, and the coupling of different replicated systems, increase the ability of the system (or systems) to self-regulate in a changing environment as adaptation processes select those structures that use resources more efficiently. At the level of the structure, as selection processes minimise the information loss, the irreversibility is minimised. While each structure that emerges can be said to be more entropically efficient, as such replicating structures proliferate, the dissipation of the system as a whole is higher than would be the case for inert or simpler structures. While a detailed application to most real systems would be difficult, the approach may well be useful in understanding incremental changes to real systems and provide broad descriptions of system behaviour.
Gopinath, T; Kumar, Anil
2006-12-01
Hadamard spectroscopy has earlier been used to speed-up multi-dimensional NMR experiments. In this work, we speed-up the two-dimensional quantum computing scheme, by using Hadamard spectroscopy in the indirect dimension, resulting in a scheme which is faster and requires the Fourier transformation only in the direct dimension. Two and three qubit quantum gates are implemented with an extra observer qubit. We also use one-dimensional Hadamard spectroscopy for binary information storage by spatial encoding and implementation of a parallel search algorithm.
Spectral image analysis of mutual illumination between florescent objects.
Tominaga, Shoji; Kato, Keiji; Hirai, Keita; Horiuchi, Takahiko
2016-08-01
This paper proposes a method for modeling and component estimation of the spectral images of the mutual illumination phenomenon between two fluorescent objects. First, we briefly describe the bispectral characteristics of a single fluorescent object, which are summarized as a Donaldson matrix. We suppose that two fluorescent objects with different bispectral characteristics are located close together under a uniform illumination. Second, we model the mutual illumination between two objects. It is shown that the spectral composition of the mutual illumination is summarized with four components: (1) diffuse reflection, (2) diffuse-diffuse interreflection, (3) fluorescent self-luminescence, and (4) interreflection by mutual fluorescent illumination. Third, we develop algorithms for estimating the spectral image components from the observed images influenced by the mutual illumination. When the exact Donaldson matrices caused by the mutual illumination influence are unknown, we have to solve a non-linear estimation problem to estimate both the spectral functions and the location weights. An iterative algorithm is then proposed to solve the problem based on the alternate estimation of the spectral functions and the location weights. In our experiments, the feasibility of the proposed method is shown in three cases: the known Donaldson matrices, weak interreflection, and strong interreflection.
[Biological mutualism, concepts and models].
Perru, Olivier
2011-01-01
Mutualism is a biological association for a mutual benefit between two different species. In this paper, firstly, we examine the history and signification of mutualism in relation to symbiosis. Then, we consider the link between concepts and models of mutualism. Models of mutualism depend on different concepts we use: If mutualism is situated at populations' level, it will be expressed by Lotka-Volterra models, concerning exclusively populations' size. If mutualism is considered as a resources' exchange or a biological market increasing the fitness of these organisms, it will be described at an individual level by a cost-benefit model. Our analysis will be limited to the history and epistemology of Lotka-Volterra models and we hypothesize that these models are adapted at first to translate dynamic evolutions of mutualism. They render stability or variations of size and assume that there are clear distinctions and a state of equilibrium between populations of different species. Italian mathematician Vito Volterra demonstrated that biological associations consist in a constant relation between some species. In 1931 and 1935, Volterra described the general form of antagonistic or mutualistic biological associations by the same differential equations. We recognize that these equations have been more used to model competition or prey-predator interactions, but a simple sign change allows describing mutualism. The epistemological problem is the following: Volterra's equations help us to conceptualize a global phenomenon. However, mutualistic interactions may have stronger effects away from equilibrium and these effects may be better understood at individual level. We conclude that, between 1985 and 2000, some researchers carried on working and converting Lotka-Volterra models but this description appeared as insufficient. So, other researchers adopted an economical viewpoint, considering mutualism as a biological market.
Tang, Xiao-yan; Gao, Kun; Ni, Guo-qiang; Zhu, Zhen-yu; Cheng, Hao-bo
2013-09-01
An improved N-FINDR endmember extraction algorithm by combining manifold learning and spatial information is presented under nonlinear mixing assumptions. Firstly, adaptive local tangent space alignment is adapted to seek potential intrinsic low-dimensional structures of hyperspectral high-diemensional data and reduce original data into a low-dimensional space. Secondly, spatial preprocessing is used by enhancing each pixel vector in spatially homogeneous areas, according to the continuity of spatial distribution of the materials. Finally, endmembers are extracted by looking for the largest simplex volume. The proposed method can increase the precision of endmember extraction by solving the nonlinearity of hyperspectral data and taking advantage of spatial information. Experimental results on simulated and real hyperspectral data demonstrate that the proposed approach outperformed the geodesic simplex volume maximization (GSVM), vertex component analysis (VCA) and spatial preprocessing N-FINDR method (SPPNFINDR).
Cryptanalysis on a scheme to share information via employing a discrete algorithm to quantum states
NASA Astrophysics Data System (ADS)
Amellal, H.; Meslouhi, A.; El Baz, M.; Hassouni, Y.; El Allati, A.
2017-03-01
Recently, Yang and Hwang [Int. J. Theor. Phys. 53, 224 (2014)] demonstrated that the scheme to share information via employing discrete algorithm to quantum states presented by Kang and Fang [Commun. Theor. Phys. 55, 239 (2011)] suffers from a major vulnerability allowing an eavesdropper to perform a measurement and resend attack. By introducing an additional checking state framework, the authors have proposed an improved protocol to overcome this weakness. This work calls into question the invoked vulnerability in order to clarify a misinterpretation in the same protocol stages also introduce a possible leakage information strategy, known as a faked state attack, despite the proposed improvement, which means that the same security problem may persist. Finally, an upgrading technic was introduced in order to enhance the security transmission.
Network algorithmics and the emergence of information integration in cortical models
NASA Astrophysics Data System (ADS)
Nathan, Andre; Barbosa, Valmir C.
2011-07-01
An information-theoretic framework known as integrated information theory (IIT) has been introduced recently for the study of the emergence of consciousness in the brain [D. Balduzzi and G. Tononi, PLoS Comput. Biol.1553-734X10.1371/journal.pcbi.1000091 4, e1000091 (2008)]. IIT purports that this phenomenon is to be equated with the generation of information by the brain surpassing the information that the brain’s constituents already generate independently of one another. IIT is not fully plausible in its modeling assumptions nor is it testable due to severe combinatorial growth embedded in its key definitions. Here we introduce an alternative to IIT which, while inspired in similar information-theoretic principles, seeks to address some of IIT’s shortcomings to some extent. Our alternative framework uses the same network-algorithmic cortical model we introduced earlier [A. Nathan and V. C. Barbosa, Phys. Rev. EPLEEE81539-375510.1103/PhysRevE.81.021916 81, 021916 (2010)] and, to allow for somewhat improved testability relative to IIT, adopts the well-known notions of information gain and total correlation applied to a set of variables representing the reachability of neurons by messages in the model’s dynamics. We argue that these two quantities relate to each other in such a way that can be used to quantify the system’s efficiency in generating information beyond that which does not depend on integration. We give computational results on our cortical model and on variants thereof that are either structurally random in the sense of an Erdős-Rényi random directed graph or structurally deterministic. We have found that our cortical model stands out with respect to the others in the sense that many of its instances are capable of integrating information more efficiently than most of those others’ instances.
Network algorithmics and the emergence of information integration in cortical models.
Nathan, Andre; Barbosa, Valmir C
2011-07-01
An information-theoretic framework known as integrated information theory (IIT) has been introduced recently for the study of the emergence of consciousness in the brain [D. Balduzzi and G. Tononi, PLoS Comput. Biol. 4, e1000091 (2008)]. IIT purports that this phenomenon is to be equated with the generation of information by the brain surpassing the information that the brain's constituents already generate independently of one another. IIT is not fully plausible in its modeling assumptions nor is it testable due to severe combinatorial growth embedded in its key definitions. Here we introduce an alternative to IIT which, while inspired in similar information-theoretic principles, seeks to address some of IIT's shortcomings to some extent. Our alternative framework uses the same network-algorithmic cortical model we introduced earlier [A. Nathan and V. C. Barbosa, Phys. Rev. E 81, 021916 (2010)] and, to allow for somewhat improved testability relative to IIT, adopts the well-known notions of information gain and total correlation applied to a set of variables representing the reachability of neurons by messages in the model's dynamics. We argue that these two quantities relate to each other in such a way that can be used to quantify the system's efficiency in generating information beyond that which does not depend on integration. We give computational results on our cortical model and on variants thereof that are either structurally random in the sense of an Erdős-Rényi random directed graph or structurally deterministic. We have found that our cortical model stands out with respect to the others in the sense that many of its instances are capable of integrating information more efficiently than most of those others' instances.
Dai, James Y; Leblanc, Michael; Smith, Nicholas L; Psaty, Bruce; Kooperberg, Charles
2009-10-01
Association studies have been widely used to identify genetic liability variants for complex diseases. While scanning the chromosomal region 1 single nucleotide polymorphism (SNP) at a time may not fully explore linkage disequilibrium, haplotype analyses tend to require a fairly large number of parameters, thus potentially losing power. Clustering algorithms, such as the cladistic approach, have been proposed to reduce the dimensionality, yet they have important limitations. We propose a SNP-Haplotype Adaptive REgression (SHARE) algorithm that seeks the most informative set of SNPs for genetic association in a targeted candidate region by growing and shrinking haplotypes with 1 more or less SNP in a stepwise fashion, and comparing prediction errors of different models via cross-validation. Depending on the evolutionary history of the disease mutations and the markers, this set may contain a single SNP or several SNPs that lay a foundation for haplotype analyses. Haplotype phase ambiguity is effectively accounted for by treating haplotype reconstruction as a part of the learning procedure. Simulations and a data application show that our method has improved power over existing methodologies and that the results are informative in the search for disease-causal loci.
NASA Astrophysics Data System (ADS)
Chernyavskiy, Andrey; Khamitov, Kamil; Teplov, Alexey; Voevodin, Vadim; Voevodin, Vladimir
2016-10-01
In recent years, quantum information technologies (QIT) showed great development, although, the way of the implementation of QIT faces the serious difficulties, some of which are challenging computational tasks. This work is devoted to the deep and broad analysis of the parallel algorithmic properties of such tasks. As an example we take one- and two-qubit transformations of a many-qubit quantum state, which are the most critical kernels of many important QIT applications. The analysis of the algorithms uses the methodology of the AlgoWiki project (algowiki-project.org) and consists of two parts: theoretical and experimental. Theoretical part includes features like sequential and parallel complexity, macro structure, and visual information graph. Experimental part was made by using the petascale Lomonosov supercomputer (Moscow State University, Russia) and includes the analysis of locality and memory access, scalability and the set of more specific dynamic characteristics of realization. This approach allowed us to obtain bottlenecks and generate ideas of efficiency improvement.
Nicolazzi, E L; Biffani, S; Jansen, G
2013-04-01
Routine genomic evaluations frequently include a preliminary imputation step, requiring high accuracy and reduced computing time. A new algorithm, PedImpute (http://dekoppel.eu/pedimpute/), was developed and compared with findhap (http://aipl.arsusda.gov/software/findhap/) and BEAGLE (http://faculty.washington.edu/browning/beagle/beagle.html), using 19,904 Holstein genotypes from a 4-country international collaboration (United States, Canada, UK, and Italy). Different scenarios were evaluated on a sample subset that included only single nucleotide polymorphism from the Bovine low-density (LD) Illumina BeadChip (Illumina Inc., San Diego, CA). Comparative criteria were computing time, percentage of missing alleles, percentage of wrongly imputed alleles, and the allelic squared correlation. Imputation accuracy on ungenotyped animals was also analyzed. The algorithm PedImpute was slightly more accurate and faster than findhap and BEAGLE when sire, dam, and maternal grandsire were genotyped at high density. On the other hand, BEAGLE performed better than both PedImpute and findhap for animals with at least one close relative not genotyped or genotyped at low density. However, computing time and resources using BEAGLE were incompatible with routine genomic evaluations in Italy. Error rate and allelic squared correlation attained by PedImpute ranged from 0.2 to 1.1% and from 96.6 to 99.3%, respectively. When complete genomic information on sire, dam, and maternal grandsire are available, as expected to be the case in the close future in (at least) dairy cattle, and considering accuracies obtained and computation time required, PedImpute represents a valuable choice in routine evaluations among the algorithms tested.
Improved Sampling Algorithms in the Risk-Informed Safety Margin Characterization Toolkit
Mandelli, Diego; Smith, Curtis Lee; Alfonsi, Andrea; Rabiti, Cristian; Cogliati, Joshua Joseph
2015-09-01
The RISMC approach is developing advanced set of methodologies and algorithms in order to perform Probabilistic Risk Analyses (PRAs). In contrast to classical PRA methods, which are based on Event-Tree and Fault-Tree methods, the RISMC approach largely employs system simulator codes applied to stochastic analysis tools. The basic idea is to randomly perturb (by employing sampling algorithms) timing and sequencing of events and internal parameters of the system codes (i.e., uncertain parameters) in order to estimate stochastic parameters such as core damage probability. This approach applied to complex systems such as nuclear power plants requires to perform a series of computationally expensive simulation runs given a large set of uncertain parameters. These types of analysis are affected by two issues. Firstly, the space of the possible solutions (a.k.a., the issue space or the response surface) can be sampled only very sparsely, and this precludes the ability to fully analyze the impact of uncertainties on the system dynamics. Secondly, large amounts of data are generated and tools to generate knowledge from such data sets are not yet available. This report focuses on the first issue and in particular employs novel methods that optimize the information generated by the sampling process by sampling unexplored and risk-significant regions of the issue space: adaptive (smart) sampling algorithms. They infer system response from surrogate models constructed from existing samples and predict the most relevant location of the next sample. It is therefore possible to understand features of the issue space with a small number of carefully selected samples. In this report, we will present how it is possible to perform adaptive sampling using the RISMC toolkit and highlight the advantages compared to more classical sampling approaches such Monte-Carlo. We will employ RAVEN to perform such statistical analyses using both analytical cases but also another RISMC code: RELAP-7.
NASA Technical Reports Server (NTRS)
Knox, C. E.
1979-01-01
Navigation position estimates are based on range information form a randomly located DME and MLS back azimuth angular information. The MLS volmetric coverage checks are performed to ensure that proper navigation inputs are being utilized. These algorithms and volumetric checks were designed so that they could be added to most existing area navigation systems with minimum software modification.
2012-01-01
The fields of molecular biology and computer science have cooperated over recent years to create a synergy between the cybernetic and biosemiotic relationship found in cellular genomics to that of information and language found in computational systems. Biological information frequently manifests its "meaning" through instruction or actual production of formal bio-function. Such information is called Prescriptive Information (PI). PI programs organize and execute a prescribed set of choices. Closer examination of this term in cellular systems has led to a dichotomy in its definition suggesting both prescribed data and prescribed algorithms are constituents of PI. This paper looks at this dichotomy as expressed in both the genetic code and in the central dogma of protein synthesis. An example of a genetic algorithm is modeled after the ribosome, and an examination of the protein synthesis process is used to differentiate PI data from PI algorithms. PMID:22413926
NASA Astrophysics Data System (ADS)
Xie, Li; Li, Guangyao; Xiao, Mang; Peng, Lei
2016-04-01
Various kinds of remote sensing image classification algorithms have been developed to adapt to the rapid growth of remote sensing data. Conventional methods typically have restrictions in either classification accuracy or computational efficiency. Aiming to overcome the difficulties, a new solution for remote sensing image classification is presented in this study. A discretization algorithm based on information entropy is applied to extract features from the data set and a vector space model (VSM) method is employed as the feature representation algorithm. Because of the simple structure of the feature space, the training rate is accelerated. The performance of the proposed method is compared with two other algorithms: back propagation neural networks (BPNN) method and ant colony optimization (ACO) method. Experimental results confirm that the proposed method is superior to the other algorithms in terms of classification accuracy and computational efficiency.
Comments on "A robust fuzzy local information C-means clustering algorithm".
Celik, Turgay; Lee, Hwee Kuan
2013-03-01
In a recent paper, Krinidis and Chatzis proposed a variation of fuzzy c-means algorithm for image clustering. The local spatial and gray-level information are incorporated in a fuzzy way through an energy function. The local minimizers of the designed energy function to obtain the fuzzy membership of each pixel and cluster centers are proposed. In this paper, it is shown that the local minimizers of Krinidis and Chatzis to obtain the fuzzy membership and the cluster centers in an iterative manner are not exclusively solutions for true local minimizers of their designed energy function. Thus, the local minimizers of Krinidis and Chatzis do not converge to the correct local minima of the designed energy function not because of tackling to the local minima, but because of the design of energy function.
Algorithms for biomagnetic source imaging with prior anatomical and physiological information
Hughett, Paul William
1995-12-01
This dissertation derives a new method for estimating current source amplitudes in the brain and heart from external magnetic field measurements and prior knowledge about the probable source positions and amplitudes. The minimum mean square error estimator for the linear inverse problem with statistical prior information was derived and is called the optimal constrained linear inverse method (OCLIM). OCLIM includes as special cases the Shim-Cho weighted pseudoinverse and Wiener estimators but allows more general priors and thus reduces the reconstruction error. Efficient algorithms were developed to compute the OCLIM estimate for instantaneous or time series data. The method was tested in a simulated neuromagnetic imaging problem with five simultaneously active sources on a grid of 387 possible source locations; all five sources were resolved, even though the true sources were not exactly at the modeled source positions and the true source statistics differed from the assumed statistics.
NASA Astrophysics Data System (ADS)
Zhou, Tingting; Gu, Lingjia; Ren, Ruizhi; Cao, Qiong
2016-09-01
With the rapid development of remote sensing technology, the spatial resolution and temporal resolution of satellite imagery also have a huge increase. Meanwhile, High-spatial-resolution images are becoming increasingly popular for commercial applications. The remote sensing image technology has broad application prospects in intelligent traffic. Compared with traditional traffic information collection methods, vehicle information extraction using high-resolution remote sensing image has the advantages of high resolution and wide coverage. This has great guiding significance to urban planning, transportation management, travel route choice and so on. Firstly, this paper preprocessed the acquired high-resolution multi-spectral and panchromatic remote sensing images. After that, on the one hand, in order to get the optimal thresholding for image segmentation, histogram equalization and linear enhancement technologies were applied into the preprocessing results. On the other hand, considering distribution characteristics of road, the normalized difference vegetation index (NDVI) and normalized difference water index (NDWI) were used to suppress water and vegetation information of preprocessing results. Then, the above two processing result were combined. Finally, the geometric characteristics were used to completed road information extraction. The road vector extracted was used to limit the target vehicle area. Target vehicle extraction was divided into bright vehicles extraction and dark vehicles extraction. Eventually, the extraction results of the two kinds of vehicles were combined to get the final results. The experiment results demonstrated that the proposed algorithm has a high precision for the vehicle information extraction for different high resolution remote sensing images. Among these results, the average fault detection rate was about 5.36%, the average residual rate was about 13.60% and the average accuracy was approximately 91.26%.
Exact Test of Independence Using Mutual Information
2014-05-23
1000 × 0.05 = 50. Entropy 2014, 16 2844 Importantly, the permutation test, which does not preserve Markov order, resulted in 489 Type I errors! Using...Block 13 ARO Report Number Block 13: Supplementary Note © 2014 . Published in Entropy , Vol. Ed. 0 16, (7) (2014), (, (7). DoD Components reserve a...official Department of the Army position, policy or decision, unless so designated by other documentation. ... Entropy 2014, 16, 2839-2849; doi:10.3390
Xia, Peng; Shimozato, Yuki; Tahara, Tatsuki; Kakue, Takashi; Awatsuji, Yasuhiro; Nishio, Kenzo; Ura, Shogo; Kubota, Toshihiro; Matoba, Osamu
2013-01-01
We propose an image reconstruction algorithm for recovering high-frequency information in parallel phase-shifting digital holography. The proposed algorithm applies three kinds of interpolations and generates three different kinds of object waves. A Fourier transform is applied to each object wave, and the spatial-frequency domain is divided into 3×3 segments for each Fourier-transformed object wave. After that the segment in which interpolation error is the least among the segments having the same address of the segment in the spatial-frequency domain is extracted. The extracted segments are combined to generate an information-enhanced spatial-frequency spectrum of the object wave, and after that the formed spatial-frequency spectrum is inversely Fourier transformed. Then the high-frequency information of the reconstructed image is recovered. The effectiveness of the proposed algorithm was verified by a numerical simulation and an experiment.
Beyer, Hans-Georg
2014-01-01
The convergence behaviors of so-called natural evolution strategies (NES) and of the information-geometric optimization (IGO) approach are considered. After a review of the NES/IGO ideas, which are based on information geometry, the implications of this philosophy w.r.t. optimization dynamics are investigated considering the optimization performance on the class of positive quadratic objective functions (the ellipsoid model). Exact differential equations describing the approach to the optimizer are derived and solved. It is rigorously shown that the original NES philosophy optimizing the expected value of the objective functions leads to very slow (i.e., sublinear) convergence toward the optimizer. This is the real reason why state of the art implementations of IGO algorithms optimize the expected value of transformed objective functions, for example, by utility functions based on ranking. It is shown that these utility functions are localized fitness functions that change during the IGO flow. The governing differential equations describing this flow are derived. In the case of convergence, the solutions to these equations exhibit an exponentially fast approach to the optimizer (i.e., linear convergence order). Furthermore, it is proven that the IGO philosophy leads to an adaptation of the covariance matrix that equals in the asymptotic limit-up to a scalar factor-the inverse of the Hessian of the objective function considered.
Algorithmic information content, Church-Turing thesis, physical entropy, and Maxwell's demon
Zurek, W.H.
1990-01-01
Measurements convert alternative possibilities of its potential outcomes into the definiteness of the record'' -- data describing the actual outcome. The resulting decrease of statistical entropy has been, since the inception of the Maxwell's demon, regarded as a threat to the second law of thermodynamics. For, when the statistical entropy is employed as the measure of the useful work which can be extracted from the system, its decrease by the information gathering actions of the observer would lead one to believe that, at least from the observer's viewpoint, the second law can be violated. I show that the decrease of ignorance does not necessarily lead to the lowering of disorder of the measured physical system. Measurements can only convert uncertainty (quantified by the statistical entropy) into randomness of the outcome (given by the algorithmic information content of the data). The ability to extract useful work is measured by physical entropy, which is equal to the sum of these two measures of disorder. So defined physical entropy is, on the average, constant in course of the measurements carried out by the observer on an equilibrium system. 27 refs., 6 figs.
NASA Technical Reports Server (NTRS)
Knox, C. E.; Vicroy, D. D.; Scanlon, C.
1984-01-01
Simulation and flight tests were conducted to compare the accuracy of two algorithms designed to compute a position estimate with an airborne navigation computer. Both algorithms used ILS localizer and DME radio signals to compute a position difference vector to be used as an input to the navigation computer position estimate filter. The results of these tests show that the position estimate accuracy and response to artificially induced errors are improved when the position estimate is computed by an algorithm that geometrically combines DME and ILS localizer information to form a single component of error rather than by an algorithm that produces two independent components of error, one from a DMD input and the other from the ILS localizer input.
Mutual intentions as a causal framework for social groups.
Noyes, Alexander; Dunham, Yarrow
2017-02-24
Children's early emerging intuitive theories are specialized for different conceptual domains. Recently attention has turned to children's concepts of social groups, finding that children believe that many social groups mark uniquely social information such as allegiances and obligations. But another critical component of intuitive theories, the causal beliefs that underlie category membership, has received less attention. We propose that children believe membership in these groups is constituted by mutual intentions: i.e., all group members (including the individual) intend for an individual to be a member and all group members (including the individual) have common knowledge of these intentions. Children in a broad age range (4-9) applied a mutual-intentional framework to newly encountered social groups early in development (Experiment 1, 2, 4). Further, they deploy this mutual-intentional framework selectively, withholding it from essentialized social categories such as gender (Experiment 3). Mutual intentionality appears to be a vital aspect of children's naïve sociology.
Sparse Bayesian Learning for DOA Estimation with Mutual Coupling
Dai, Jisheng; Hu, Nan; Xu, Weichao; Chang, Chunqi
2015-01-01
Sparse Bayesian learning (SBL) has given renewed interest to the problem of direction-of-arrival (DOA) estimation. It is generally assumed that the measurement matrix in SBL is precisely known. Unfortunately, this assumption may be invalid in practice due to the imperfect manifold caused by unknown or misspecified mutual coupling. This paper describes a modified SBL method for joint estimation of DOAs and mutual coupling coefficients with uniform linear arrays (ULAs). Unlike the existing method that only uses stationary priors, our new approach utilizes a hierarchical form of the Student t prior to enforce the sparsity of the unknown signal more heavily. We also provide a distinct Bayesian inference for the expectation-maximization (EM) algorithm, which can update the mutual coupling coefficients more efficiently. Another difference is that our method uses an additional singular value decomposition (SVD) to reduce the computational complexity of the signal reconstruction process and the sensitivity to the measurement noise. PMID:26501284
Tahara, Tatsuki; Shimozato, Yuki; Xia, Peng; Ito, Yasunori; Awatsuji, Yasuhiro; Nishio, Kenzo; Ura, Shogo; Matoba, Osamu; Kubota, Toshihiro
2012-08-27
We propose an image-reconstruction algorithm of parallel phase-shifting digital holography (PPSDH) which is a technique of single-shot phase-shifting interferometry. In the conventional algorithms in PPSDH, the residual 0th-order diffraction wave and the conjugate images cannot be removed completely and a part of space-bandwidth information is discarded. The proposed algorithm can remove these residual images by modifying the calculation of phase-shifting interferometry and by using Fourier transform technique, respectively. Then, several types of complex amplitudes are derived from a recorded hologram according to the directions in which the neighboring pixels used for carrying out the spatial phase-shifting interferometry are aligned. Several distributions are Fourier-transformed and wide space-bandwidth information of the object wave is obtained by selecting the spectrum among the Fourier-transformed images in each region of the spatial frequency domain and synthesizing a Fourier-transformed image from the spectrum.
Che, Yanting; Wang, Qiuying; Gao, Wei; Yu, Fei
2015-10-05
In this paper, an improved inertial frame alignment algorithm for a marine SINS under mooring conditions is proposed, which significantly improves accuracy. Since the horizontal alignment is easy to complete, and a characteristic of gravity is that its component in the horizontal plane is zero, we use a clever method to improve the conventional inertial alignment algorithm. Firstly, a large misalignment angle model and a dimensionality reduction Gauss-Hermite filter are employed to establish the fine horizontal reference frame. Based on this, the projection of the gravity in the body inertial coordinate frame can be calculated easily. Then, the initial alignment algorithm is accomplished through an inertial frame alignment algorithm. The simulation and experiment results show that the improved initial alignment algorithm performs better than the conventional inertial alignment algorithm, and meets the accuracy requirements of a medium-accuracy marine SINS.
Molina, Iñigo; Martinez, Estibaliz; Arquero, Agueda; Pajares, Gonzalo; Sanchez, Javier
2012-01-01
Landcover is subject to continuous changes on a wide variety of temporal and spatial scales. Those changes produce significant effects in human and natural activities. Maintaining an updated spatial database with the occurred changes allows a better monitoring of the Earth’s resources and management of the environment. Change detection (CD) techniques using images from different sensors, such as satellite imagery, aerial photographs, etc., have proven to be suitable and secure data sources from which updated information can be extracted efficiently, so that changes can also be inventoried and monitored. In this paper, a multisource CD methodology for multiresolution datasets is applied. First, different change indices are processed, then different thresholding algorithms for change/no_change are applied to these indices in order to better estimate the statistical parameters of these categories, finally the indices are integrated into a change detection multisource fusion process, which allows generating a single CD result from several combination of indices. This methodology has been applied to datasets with different spectral and spatial resolution properties. Then, the obtained results are evaluated by means of a quality control analysis, as well as with complementary graphical representations. The suggested methodology has also been proved efficiently for identifying the change detection index with the higher contribution. PMID:22737023
Sim, Kwang Mong; Guo, Yuanyuan; Shi, Benyun
2009-02-01
Automated negotiation provides a means for resolving differences among interacting agents. For negotiation with complete information, this paper provides mathematical proofs to show that an agent's optimal strategy can be computed using its opponent's reserve price (RP) and deadline. The impetus of this work is using the synergy of Bayesian learning (BL) and genetic algorithm (GA) to determine an agent's optimal strategy in negotiation (N) with incomplete information. BLGAN adopts: 1) BL and a deadline-estimation process for estimating an opponent's RP and deadline and 2) GA for generating a proposal at each negotiation round. Learning the RP and deadline of an opponent enables the GA in BLGAN to reduce the size of its search space (SP) by adaptively focusing its search on a specific region in the space of all possible proposals. SP is dynamically defined as a region around an agent's proposal P at each negotiation round. P is generated using the agent's optimal strategy determined using its estimations of its opponent's RP and deadline. Hence, the GA in BLGAN is more likely to generate proposals that are closer to the proposal generated by the optimal strategy. Using GA to search around a proposal generated by its current strategy, an agent in BLGAN compensates for possible errors in estimating its opponent's RP and deadline. Empirical results show that agents adopting BLGAN reached agreements successfully, and achieved: 1) higher utilities and better combined negotiation outcomes (CNOs) than agents that only adopt GA to generate their proposals, 2) higher utilities than agents that adopt BL to learn only RP, and 3) higher utilities and better CNOs than agents that do not learn their opponents' RPs and deadlines.
Enhancing a diffusion algorithm for 4D image segmentation using local information
NASA Astrophysics Data System (ADS)
Lösel, Philipp; Heuveline, Vincent
2016-03-01
Inspired by the diffusion of a particle, we present a novel approach for performing a semiautomatic segmentation of tomographic images in 3D, 4D or higher dimensions to meet the requirements of high-throughput measurements in a synchrotron X-ray microtomograph. Given a small number of 2D-slices with at least two manually labeled segments, one can either analytically determine the probability that an intelligently weighted random walk starting at one labeled pixel will be at a certain time at a specific position in the dataset or determine the probability approximately by performing several random walks. While the weights of a random walk take into account local information at the starting point, the random walk itself can be in any dimension. Starting a great number of random walks in each labeled pixel, a voxel in the dataset will be hit by several random walks over time. Hence, the image can be segmented by assigning each voxel to the label where the random walks most likely started from. Due to the high scalability of random walks, this approach is suitable for high throughput measurements. Additionally, we describe an interactively adjusted active contours slice by slice method considering local information, where we start with one manually labeled slice and move forward in any direction. This approach is superior with respect to accuracy towards the diffusion algorithm but inferior in the amount of tedious manual processing steps. The methods were applied on 3D and 4D datasets and evaluated by means of manually labeled images obtained in a realistic scenario with biologists.
2004-12-01
employ genetic algorithms . In principle, calculation of the free energy change upon binding of two proteins should allow determination of the... Genetic Algorithm Approach to Protein Docking in CAPRI round 1. Proteins 52: 10-14. Glaser, F., Pupko, T., Paz, I., Bell, R.E., Bechor-Shental, D... genetic algorithm and an empirical binding free energy function. Journal of Computational Chemistry 19: 1639-1662. Palma, P.N., Krippahl, L., Wampler
ERIC Educational Resources Information Center
Losee, Robert M.
1996-01-01
The grammars of natural languages may be learned by using genetic algorithm systems such as LUST (Linguistics Using Sexual Techniques) that reproduce and mutate grammatical rules and parts-of-speech tags. In document retrieval or filtering systems, applying tags to the list of terms representing a document provides additional information about…
Mutual Respect and Civic Education
ERIC Educational Resources Information Center
Bird, Colin
2010-01-01
Contemporary theories of civic education frequently appeal to an ideal of mutual respect in the context of ethical, ethical and religious disagreement. This paper critically examines two recently popular criticisms of this ideal. The first, coming from a postmodern direction, charges that the ideal is hypocritical in its effort to be maximally…
Hospital mutual aid evacuation plan.
Phillips, R
1997-02-01
Health care facilities need to be prepared for disasters such as floods, tornadoes and earthquakes. Rochester, NY, and its surrounding communities devised a hospital mutual aid evacuation plan in the event a disaster occurs and also to comply with the Joint Commission. This document discusses the plan's development process and also provides the end result.
NASA Astrophysics Data System (ADS)
Crow, W. T.; Wagner, W.
2009-12-01
Applying basic data assimilation techniques to the evaluation of remote-sensing products can clarify the impact of sensor design issues on the value of retrievals for hydrologic applications. For instance, the impact of incidence angle on the accuracy of radar surface soil moisture retrievals is largely unknown due to discrepancies in theoretical backscatter models as well as limitations in the availability of sufficiently-extensive ground-based soil moisture observations for validation purposes. In this presentation we will describe and apply a data assimilation evaluation technique for scatterometer-based surface soil moisture retrievals that does not require ground-based soil moisture observations to examine the sensitivity of retrieval skill to variations in incidence angle. Past results with the approach have shown that it is capable of detecting relative variations in the correlation between anomalies in remotely-sensed surface soil moisture retrievals and ground-truth soil moisture measurements. Application of the evaluation approach to the TU-Wien WARP5.0 European Space Radar (ERS) soil moisture data set over two regional-scale (~1000 km) domains in the Southern United States indicates a relative reduction in anomaly correlation-based skill of between 20% and 30% when moving between the lowest (< 26 degrees) and highest ERS (> 50 degrees) incidence angle ranges. These changes in anomaly-based correlation provide a useful proxy for relative variations in the value of estimates for data assimilation applications and can therefore be used to inform the design of appropriate retrieval algorithms. For example, the observed sensitivity of correlation-based skill with incidence angle is in approximate agreement with soil moisture retrieval uncertainty predictions made using the WARP5.0 backscatter model. However, the coupling of a bare soil backscatter model with the so-called "vegetation water cloud" model is shown to generally over-estimate the impact of
NASA Technical Reports Server (NTRS)
Freedman, Ellis; Ryan, Robert; Pagnutti, Mary; Holekamp, Kara; Gasser, Gerald; Carver, David; Greer, Randy
2007-01-01
Spectral Dark Subtraction (SDS) provides good ground reflectance estimates across a variety of atmospheric conditions with no knowledge of those conditions. The algorithm may be sensitive to errors from stray light, calibration, and excessive haze/water vapor. SDS seems to provide better estimates than traditional algorithms using on-site atmospheric measurements much of the time.
Morran, Levi T.; Penley, McKenna J.; Byrd, Victoria S.; Meyer, Andrew J.; O’Sullivan, Timothy S.; Bashey, Farrah; Goodrich-Blair, Heidi; Lively, Curtis M.
2016-01-01
The coevolution of interacting species can lead to co-dependent mutualists. Little is known about the effect of selection on partners within verses apart from the association. Here, we determined the effect of selection on bacteria (Xenorhabdus nematophila) both within and apart from its mutualistic partner (a nematode, Steinernema carpocapsae). In nature, the two species cooperatively infect and kill arthropods. We passaged the bacteria either together with (M+), or isolated from (M−), nematodes under two different selection regimes: random selection (S−) and selection for increased virulence against arthropod hosts (S+). We found that the isolated bacteria evolved greater virulence under selection for greater virulence (M−S+) than under random selection (M−S−). In addition, the response to selection in the isolated bacteria (M−S+) caused a breakdown of the mutualism following reintroduction to the nematode. Finally, selection for greater virulence did not alter the evolutionary trajectories of bacteria passaged within the mutualism (M+S+ = M+S−), indicating that selection for the maintenance of the mutualism was stronger than selection for increased virulence. The results show that selection on isolated mutualists can rapidly breakdown beneficial interactions between species, but that selection within a mutualism can supersede external selection, potentially generating co-dependence over time. PMID:26867502
DRAMMS: deformable registration via attribute matching and mutual-saliency weighting.
Ou, Yangming; Davatzikos, Christos
2009-01-01
A general-purpose deformable registration algorithm referred to as "DRAMMS" is presented in this paper. DRAMMS adds to the literature of registration methods that bridge between the traditional voxel-wise methods and landmark/feature-based methods. In particular, DRAMMS extracts Gabor attributes at each voxel and selects the optimal components, so that they form a highly distinctive morphological signature reflecting the anatomical context around each voxel in a multi-scale and multi-resolution fashion. Compared with intensity or mutual-information based methods, the high-dimensional optimal Gabor attributes render different anatomical regions relatively distinctively identifiable and therefore help establish more accurate and reliable correspondence. Moreover, the optimal Gabor attribute vector is constructed in a way that generalizes well, i.e., it can be applied to different registration tasks, regardless of the image contents under registration. A second characteristic of DRAMMS is that it is based on a cost function that weights different voxel pairs according to a metric referred to as "mutual-saliency", which reflects the uniqueness (reliability) of anatomical correspondences implied by the tentative transformation. As a result, image voxels do not contribute equally to the optimization process, as in most voxel-wise methods, or in a binary selection fashion, as in most landmark/feature-based methods. Instead, they contribute according to a continuously-valued mutual-saliency map, which is dynamically updated during the algorithm's evolution. The general applicability and accuracy of DRAMMS are demonstrated by experiments in simulated images, inter-subject images, single-/multi-modality images, and longitudinal images, from human and mouse brains, breast, heart, and prostate.
Assessing particle kinematics via template matching algorithms.
Weber, M; Fink, M; Fortov, V; Lipaev, A; Molotkov, V; Morfill, G; Petrov, O; Pustylnik, M; Thoma, M; Thomas, H; Usachev, A; Raeth, C
2016-04-18
Template matching algorithms represent a viable tool to locate particles in optical images. A crucial factor of the performance of these methods is the choice of the similarity measure. Recently, it was shown in [Gao and Helgeson, Opt. Express 22 (2014)] that the correlation coefficient (CC) leads to good results. Here, we introduce the mutual information (MI) as a nonlinear similarity measure and compare the performance of the MI and the CC for different noise scenarios. It turns out that the mutual information leads to superior results in the case of signal dependent noise. We propose a novel approach to estimate the velocity of particles which is applicable in imaging scenarios where the particles appear elongated due to their movement. By designing a bank of anisotropic templates supposed to fit the elongation of the particles we are able to reliably estimate their velocity and direction of motion out of a single image.
Cho, Gyoun-Yon; Lee, Seo-Joon; Lee, Tae-Ro
2015-01-01
Recent medical information systems are striving towards real-time monitoring models to care patients anytime and anywhere through ECG signals. However, there are several limitations such as data distortion and limited bandwidth in wireless communications. In order to overcome such limitations, this research focuses on compression. Few researches have been made to develop a specialized compression algorithm for ECG data transmission in real-time monitoring wireless network. Not only that, recent researches' algorithm is not appropriate for ECG signals. Therefore this paper presents a more developed algorithm EDLZW for efficient ECG data transmission. Results actually showed that the EDLZW compression ratio was 8.66, which was a performance that was 4 times better than any other recent compression method widely used today.
Mutuality in the provision of Scottish healthcare.
Howieson, Brian
2015-11-01
The backdrop to this article is provided by the Better Health, Better Care Action Plan (Scottish Government, 2007), Section 1 of which is entitled 'Towards a Mutual NHS'. According to Better Health, Better Care (Scottish Government, 2007: 5): 'Mutual organisations are designed to serve their members. They are designed to gather people around a common sense of purpose. They are designed to bring the organisation together in what people often call "co-production."' The aim of this article is to précis the current knowledge of mutuality in the provision of Scottish healthcare. In detail, it will: introduce the 'mutual' organisation; offer a historical perspective of mutuality; suggest why healthcare mutuality is important; and briefly, detail the differences in mutual health-care policy in England and Scotland. It is hoped that this analysis will help researchers and practitioners alike appreciate further the philosophy of mutuality in the provision of Scottish healthcare.
NASA Technical Reports Server (NTRS)
Hoang, TY
1994-01-01
A real-time, high-rate precision navigation Kalman filter algorithm is developed and analyzed. This Navigation algorithm blends various navigation data collected during terminal area approach of an instrumented helicopter. Navigation data collected include helicopter position and velocity from a global position system in differential mode (DGPS) as well as helicopter velocity and attitude from an inertial navigation system (INS). The goal of the Navigation algorithm is to increase the DGPS accuracy while producing navigational data at the 64 Hertz INS update rate. It is important to note that while the data was post flight processed, the Navigation algorithm was designed for real-time analysis. The design of the Navigation algorithm resulted in a nine-state Kalman filter. The Kalman filter's state matrix contains position, velocity, and velocity bias components. The filter updates positional readings with DGPS position, INS velocity, and velocity bias information. In addition, the filter incorporates a sporadic data rejection scheme. This relatively simple model met and exceeded the ten meter absolute positional requirement. The Navigation algorithm results were compared with truth data derived from a laser tracker. The helicopter flight profile included terminal glideslope angles of 3, 6, and 9 degrees. Two flight segments extracted during each terminal approach were used to evaluate the Navigation algorithm. The first segment recorded small dynamic maneuver in the lateral plane while motion in the vertical plane was recorded by the second segment. The longitudinal, lateral, and vertical averaged positional accuracies for all three glideslope approaches are as follows (mean plus or minus two standard deviations in meters): longitudinal (-0.03 plus or minus 1.41), lateral (-1.29 plus or minus 2.36), and vertical (-0.76 plus or minus 2.05).
NASA Astrophysics Data System (ADS)
Kikuchi, N.; Yoshida, Y.; Uchino, O.; Morino, I.; Yokota, T.
2016-11-01
We present an algorithm for retrieving column-averaged dry air mole fraction of carbon dioxide (XCO2) and methane (XCH4) from reflected spectra in the shortwave infrared (SWIR) measured by the TANSO-FTS (Thermal And Near infrared Sensor for carbon Observation Fourier Transform Spectrometer) sensor on board the Greenhouse gases Observing SATellite (GOSAT). The algorithm uses the two linear polarizations observed by TANSO-FTS to improve corrections to the interference effects of atmospheric aerosols, which degrade the accuracy in the retrieved greenhouse gas concentrations. To account for polarization by the land surface reflection in the forward model, we introduced a bidirectional reflection matrix model that has two parameters to be retrieved simultaneously with other state parameters. The accuracy in XCO2 and XCH4 values retrieved with the algorithm was evaluated by using simulated retrievals over both land and ocean, focusing on the capability of the algorithm to correct imperfect prior knowledge of aerosols. To do this, we first generated simulated TANSO-FTS spectra using a global distribution of aerosols computed by the aerosol transport model SPRINTARS. Then the simulated spectra were submitted to the algorithms as measurements both with and without polarization information, adopting a priori profiles of aerosols that differ from the true profiles. We found that the accuracy of XCO2 and XCH4, as well as profiles of aerosols, retrieved with polarization information was considerably improved over values retrieved without polarization information, for simulated observations over land with aerosol optical thickness greater than 0.1 at 1.6 μm.
Xiao, Chuan-Le; Chen, Xiao-Zhou; Du, Yang-Li; Sun, Xuesong; Zhang, Gong; He, Qing-Yu
2013-01-04
Mass spectrometry has become one of the most important technologies in proteomic analysis. Tandem mass spectrometry (LC-MS/MS) is a major tool for the analysis of peptide mixtures from protein samples. The key step of MS data processing is the identification of peptides from experimental spectra by searching public sequence databases. Although a number of algorithms to identify peptides from MS/MS data have been already proposed, e.g. Sequest, OMSSA, X!Tandem, Mascot, etc., they are mainly based on statistical models considering only peak-matches between experimental and theoretical spectra, but not peak intensity information. Moreover, different algorithms gave different results from the same MS data, implying their probable incompleteness and questionable reproducibility. We developed a novel peptide identification algorithm, ProVerB, based on a binomial probability distribution model of protein tandem mass spectrometry combined with a new scoring function, making full use of peak intensity information and, thus, enhancing the ability of identification. Compared with Mascot, Sequest, and SQID, ProVerB identified significantly more peptides from LC-MS/MS data sets than the current algorithms at 1% False Discovery Rate (FDR) and provided more confident peptide identifications. ProVerB is also compatible with various platforms and experimental data sets, showing its robustness and versatility. The open-source program ProVerB is available at http://bioinformatics.jnu.edu.cn/software/proverb/ .
76 FR 36625 - Mutual Holding Company
Federal Register 2010, 2011, 2012, 2013, 2014
2011-06-22
... Office of Thrift Supervision Mutual Holding Company AGENCY: Office of Thrift Supervision (OTS), Treasury... collection. Title of Proposal: Mutual Holding Company. OMB Number: 1550-0072. Form Numbers: MHC-1 (OTS Form... whether the applicant meets the statutory and regulatory criteria to form a mutual holding company...
76 FR 20458 - Mutual Holding Company
Federal Register 2010, 2011, 2012, 2013, 2014
2011-04-12
... Office of Thrift Supervision Mutual Holding Company AGENCY: Office of Thrift Supervision (OTS), Treasury... collection. Title of Proposal: Mutual Holding Company. OMB Number: 1550-0072. Form Numbers: MHC-1 (OTS Form... whether the applicant meets the statutory and regulatory criteria to form a mutual holding company...
NASA Astrophysics Data System (ADS)
Gao, Min; Huang, Shutao; Zhong, Xia
2009-09-01
The establishment of multi-source database was designed to promote the informatics process of the geological disposal of High-level Radioactive Waste, the integration of multi-dimensional and multi-source information and its application are related to computer software and hardware. Based on the analysis of data resources in Beishan area, Gansu Province, and combined with GIS technologies and methods. This paper discusses the technical ideas of how to manage, fully share and rapidly retrieval the information resources in this area by using open source code GDAL and Quadtree algorithm, especially in terms of the characteristics of existing data resources, spatial data retrieval algorithm theory, programming design and implementation of the ideas.
NASA Astrophysics Data System (ADS)
Gao, Min; Huang, Shutao; Zhong, Xia
2010-11-01
The establishment of multi-source database was designed to promote the informatics process of the geological disposal of High-level Radioactive Waste, the integration of multi-dimensional and multi-source information and its application are related to computer software and hardware. Based on the analysis of data resources in Beishan area, Gansu Province, and combined with GIS technologies and methods. This paper discusses the technical ideas of how to manage, fully share and rapidly retrieval the information resources in this area by using open source code GDAL and Quadtree algorithm, especially in terms of the characteristics of existing data resources, spatial data retrieval algorithm theory, programming design and implementation of the ideas.
Waveguide mutually pumped phase conjugators.
James, S W; Youden, K E; Jeffrey, P M; Eason, R W; Chandler, P J; Zhang, L; Townsend, P D
1993-09-20
The operation of the bridge mutually pumped phase conjugator is reported in a planar waveguide structure in photorefractive BaTiO(3). The waveguide was fabricated by the technique of ion implantation, using 1.5-MeVH(+) ions at a dose of 10(16) ions/cm(2). An order of magnitude decrease in response time is observed in the waveguide as compared with typical values obtained in bulk crystals, probably as a result of a combination of the optical confinement within the waveguide and possible modification of the charge-transport properties induced by the implantation process.
Wideband Direction of Arrival Estimation in the Presence of Unknown Mutual Coupling.
Li, Weixing; Zhang, Yue; Lin, Jianzhi; Guo, Rui; Chen, Zengping
2017-02-06
This paper investigates a subarray based algorithm for direction of arrival (DOA) estimation of wideband uniform linear array (ULA), under the presence of frequency-dependent mutual coupling effects. Based on the Toeplitz structure of mutual coupling matrices, the whole array is divided into the middle subarray and the auxiliary subarray. Then two-sided correlation transformation is applied to the correlation matrix of the middle subarray instead of the whole array. In this way, the mutual coupling effects can be eliminated. Finally, the multiple signal classification (MUSIC) method is utilized to derive the DOAs. For the condition when the blind angles exist, we refine DOA estimation by using a simple approach based on the frequency-dependent mutual coupling matrixes (MCMs). The proposed method can achieve high estimation accuracy without any calibration sources. It has a low computational complexity because iterative processing is not required. Simulation results validate the effectiveness and feasibility of the proposed algorithm.
Wideband Direction of Arrival Estimation in the Presence of Unknown Mutual Coupling
Li, Weixing; Zhang, Yue; Lin, Jianzhi; Guo, Rui; Chen, Zengping
2017-01-01
This paper investigates a subarray based algorithm for direction of arrival (DOA) estimation of wideband uniform linear array (ULA), under the presence of frequency-dependent mutual coupling effects. Based on the Toeplitz structure of mutual coupling matrices, the whole array is divided into the middle subarray and the auxiliary subarray. Then two-sided correlation transformation is applied to the correlation matrix of the middle subarray instead of the whole array. In this way, the mutual coupling effects can be eliminated. Finally, the multiple signal classification (MUSIC) method is utilized to derive the DOAs. For the condition when the blind angles exist, we refine DOA estimation by using a simple approach based on the frequency-dependent mutual coupling matrixes (MCMs). The proposed method can achieve high estimation accuracy without any calibration sources. It has a low computational complexity because iterative processing is not required. Simulation results validate the effectiveness and feasibility of the proposed algorithm. PMID:28178177
A general framework for effectiveness concepts in mutualisms.
Schupp, Eugene W; Jordano, Pedro; Gómez, José María
2017-03-28
A core interest in studies of mutualistic interactions is the 'effectiveness' of mutualists in providing benefits to their partners. In plant-animal mutualisms it is widely accepted that the total effect of a mutualist on its partner is estimated as (1) a 'quantity' component multiplied by (2) a 'quality' component, although the meanings of 'effectiveness,' 'quantity,' and 'quality' and which terms are applied to these metrics vary greatly across studies. In addition, a similar quantity × quality = total effect approach has not been applied to other types of mutualisms, although it could be informative. Lastly, when a total effect approach has been applied, it has invariably been from a phytocentric perspective, focussing on the effects of animal mutualists on their plant partner. This lack of a common framework of 'effectiveness' of mutualistic interactions limits generalisation and the development of a broader understanding of the ecology and evolution of mutualisms. In this paper, we propose a general framework and demonstrate its utility by applying it to both partners in five different types of mutualisms: pollination, seed dispersal, plant protection, rhizobial, and mycorrhizal mutualisms. We then briefly discuss the flexibility of the framework, potential limitations, and relationship to other approaches.
Mutual Aid Agreements: Essential Legal Tools for Public Health Preparedness and Response
Stier, Daniel D.; Goodman, Richard A.
2007-01-01
Mutual aid is the sharing of supplies, equipment, personnel, and information across political boundaries. States must have agreements in place to ensure mutual aid to facilitate effective responses to public health emergencies and to detect and control potential infectious disease outbreaks. The 2005 hurricanes triggered activation of the Emergency Management Assistance Compact (EMAC), a mutual aid agreement among the 50 states, the District of Columbia, Puerto Rico, and the US Virgin Islands. Although EMAC facilitated the movement of an unprecedented amount of mutual aid to disaster areas, inadequacies in the response demonstrated a need for improvement. Mutual aid may also be beneficial in circumstances where EMAC is not activated. We discuss the importance of mutual aid, examine obstacles, and identify legal “gaps” that must be filled to strengthen preparedness. PMID:17413085
Mutually-antagonistic interactions in baseball networks
NASA Astrophysics Data System (ADS)
Saavedra, Serguei; Powers, Scott; McCotter, Trent; Porter, Mason A.; Mucha, Peter J.
2010-03-01
We formulate the head-to-head matchups between Major League Baseball pitchers and batters from 1954 to 2008 as a bipartite network of mutually-antagonistic interactions. We consider both the full network and single-season networks, which exhibit structural changes over time. We find interesting structure in the networks and examine their sensitivity to baseball’s rule changes. We then study a biased random walk on the matchup networks as a simple and transparent way to (1) compare the performance of players who competed under different conditions and (2) include information about which particular players a given player has faced. We find that a player’s position in the network does not correlate with his placement in the random walker ranking. However, network position does have a substantial effect on the robustness of ranking placement to changes in head-to-head matchups.
NASA Astrophysics Data System (ADS)
Dao, P.; Heinrich-Josties, E.; Boroson, T.
2016-09-01
Automated detection of changes of GEO satellites using photometry is fundamentally dependent on near real time association of non-resolved signatures and object identification. Non-statistical algorithms which rely on fixed positional boundaries for associating objects often results in mistags [1]. Photometry has been proposed to reduce the occurrence of mistags. In past attempts to include photometry, (1) the problem of correlation (with the catalog) has been decoupled from the photometry-based detection of change and mistagging and (2) positional information has not been considered simultaneously with photometry. The technique used in this study addresses both problems. It takes advantage of the fusion of both types of information and processes all information concurrently in a single statistics-based framework. This study demonstrates with Las Cumbres Observatory Global Telescope Network (LCOGT) data that metric information, i.e. right ascension, declination, photometry and GP element set, can be used concurrently to confidently associate (identify) GEO objects. All algorithms can easily be put into a framework to process data in near-real-time.
ERIC Educational Resources Information Center
Booker, Queen Esther
2009-01-01
An approach used to tackle the problem of helping online students find the classes they want and need is a filtering technique called "social information filtering," a general approach to personalized information filtering. Social information filtering essentially automates the process of "word-of-mouth" recommendations: items are recommended to a…
Cross-language opinion lexicon extraction using mutual-reinforcement label propagation.
Lin, Zheng; Tan, Songbo; Liu, Yue; Cheng, Xueqi; Xu, Xueke
2013-01-01
There is a growing interest in automatically building opinion lexicon from sources such as product reviews. Most of these methods depend on abundant external resources such as WordNet, which limits the applicability of these methods. Unsupervised or semi-supervised learning provides an optional solution to multilingual opinion lexicon extraction. However, the datasets are imbalanced in different languages. For some languages, the high-quality corpora are scarce or hard to obtain, which limits the research progress. To solve the above problems, we explore a mutual-reinforcement label propagation framework. First, for each language, a label propagation algorithm is applied to a word relation graph, and then a bilingual dictionary is used as a bridge to transfer information between two languages. A key advantage of this model is its ability to make two languages learn from each other and boost each other. The experimental results show that the proposed approach outperforms baseline significantly.
Learning factorizations in estimation of distribution algorithms using affinity propagation.
Santana, Roberto; Larrañaga, Pedro; Lozano, José A
2010-01-01
Estimation of distribution algorithms (EDAs) that use marginal product model factorizations have been widely applied to a broad range of mainly binary optimization problems. In this paper, we introduce the affinity propagation EDA (AffEDA) which learns a marginal product model by clustering a matrix of mutual information learned from the data using a very efficient message-passing algorithm known as affinity propagation. The introduced algorithm is tested on a set of binary and nonbinary decomposable functions and using a hard combinatorial class of problem known as the HP protein model. The results show that the algorithm is a very efficient alternative to other EDAs that use marginal product model factorizations such as the extended compact genetic algorithm (ECGA) and improves the quality of the results achieved by ECGA when the cardinality of the variables is increased.
Analysis of Network Clustering Algorithms and Cluster Quality Metrics at Scale
Kobourov, Stephen; Gallant, Mike; Börner, Katy
2016-01-01
Overview Notions of community quality underlie the clustering of networks. While studies surrounding network clustering are increasingly common, a precise understanding of the realtionship between different cluster quality metrics is unknown. In this paper, we examine the relationship between stand-alone cluster quality metrics and information recovery metrics through a rigorous analysis of four widely-used network clustering algorithms—Louvain, Infomap, label propagation, and smart local moving. We consider the stand-alone quality metrics of modularity, conductance, and coverage, and we consider the information recovery metrics of adjusted Rand score, normalized mutual information, and a variant of normalized mutual information used in previous work. Our study includes both synthetic graphs and empirical data sets of sizes varying from 1,000 to 1,000,000 nodes. Cluster Quality Metrics We find significant differences among the results of the different cluster quality metrics. For example, clustering algorithms can return a value of 0.4 out of 1 on modularity but score 0 out of 1 on information recovery. We find conductance, though imperfect, to be the stand-alone quality metric that best indicates performance on the information recovery metrics. Additionally, our study shows that the variant of normalized mutual information used in previous work cannot be assumed to differ only slightly from traditional normalized mutual information. Network Clustering Algorithms Smart local moving is the overall best performing algorithm in our study, but discrepancies between cluster evaluation metrics prevent us from declaring it an absolutely superior algorithm. Interestingly, Louvain performed better than Infomap in nearly all the tests in our study, contradicting the results of previous work in which Infomap was superior to Louvain. We find that although label propagation performs poorly when clusters are less clearly defined, it scales efficiently and accurately to large
Code of Federal Regulations, 2014 CFR
2014-04-01
... mutual), mutual marine insurance companies, and mutual fire insurance companies issuing perpetual policies. 1.831-1 Section 1.831-1 Internal Revenue INTERNAL REVENUE SERVICE, DEPARTMENT OF THE TREASURY... insurance companies (other than life or mutual), mutual marine insurance companies, and mutual...
Code of Federal Regulations, 2013 CFR
2013-04-01
... mutual), mutual marine insurance companies, and mutual fire insurance companies issuing perpetual policies. 1.831-1 Section 1.831-1 Internal Revenue INTERNAL REVENUE SERVICE, DEPARTMENT OF THE TREASURY... insurance companies (other than life or mutual), mutual marine insurance companies, and mutual...
NASA Technical Reports Server (NTRS)
Carter, Richard G.
1989-01-01
For optimization problems associated with engineering design, parameter estimation, image reconstruction, and other optimization/simulation applications, low accuracy function and gradient values are frequently much less expensive to obtain than high accuracy values. Here, researchers investigate the computational performance of trust region methods for nonlinear optimization when high accuracy evaluations are unavailable or prohibitively expensive, and confirm earlier theoretical predictions when the algorithm is convergent even with relative gradient errors of 0.5 or more. The proper choice of the amount of accuracy to use in function and gradient evaluations can result in orders-of-magnitude savings in computational cost.
Construction of bacteria-eukaryote synthetic mutualism.
Kubo, Isao; Hosoda, Kazufumi; Suzuki, Shingo; Yamamoto, Kayo; Kihara, Kumiko; Mori, Kotaro; Yomo, Tetsuya
2013-08-01
Mutualism is ubiquitous in nature but is known to be intrinsically vulnerable with regard to both population dynamics and evolution. Synthetic ecology has indicated that it is feasible for organisms to establish novel mutualism merely through encountering each other by showing that it is feasible to construct synthetic mutualism between organisms. However, bacteria-eukaryote mutualism, which is ecologically important, has not yet been constructed. In this study, we synthetically constructed mutualism between a bacterium and a eukaryote by using two model organisms. We mixed a bacterium, Escherichia coli (a genetically engineered glutamine auxotroph), and an amoeba, Dictyostelium discoideum, in 14 sets of conditions in which each species could not grow in monoculture but potentially could grow in coculture. Under a single condition in which the bacterium and amoeba mutually compensated for the lack of required nutrients (lipoic acid and glutamine, respectively), both species grew continuously through several subcultures, essentially establishing mutualism. Our results shed light on the establishment of bacteria-eukaryote mutualism and indicate that a bacterium and eukaryote pair in nature also has a non-negligible possibility of establishing novel mutualism if the organisms are potentially mutualistic.
Canonical information analysis
NASA Astrophysics Data System (ADS)
Vestergaard, Jacob Schack; Nielsen, Allan Aasbjerg
2015-03-01
Canonical correlation analysis is an established multivariate statistical method in which correlation between linear combinations of multivariate sets of variables is maximized. In canonical information analysis introduced here, linear correlation as a measure of association between variables is replaced by the information theoretical, entropy based measure mutual information, which is a much more general measure of association. We make canonical information analysis feasible for large sample problems, including for example multispectral images, due to the use of a fast kernel density estimator for entropy estimation. Canonical information analysis is applied successfully to (1) simple simulated data to illustrate the basic idea and evaluate performance, (2) fusion of weather radar and optical geostationary satellite data in a situation with heavy precipitation, and (3) change detection in optical airborne data. The simulation study shows that canonical information analysis is as accurate as and much faster than algorithms presented in previous work, especially for large sample sizes. URL:
2013-01-01
Background Adequate health literacy is important for people to maintain good health and manage diseases and injuries. Educational text, either retrieved from the Internet or provided by a doctor’s office, is a popular method to communicate health-related information. Unfortunately, it is difficult to write text that is easy to understand, and existing approaches, mostly the application of readability formulas, have not convincingly been shown to reduce the difficulty of text. Objective To develop an evidence-based writer support tool to improve perceived and actual text difficulty. To this end, we are developing and testing algorithms that automatically identify difficult sections in text and provide appropriate, easier alternatives; algorithms that effectively reduce text difficulty will be included in the support tool. This work describes the user evaluation with an independent writer of an automated simplification algorithm using term familiarity. Methods Term familiarity indicates how easy words are for readers and is estimated using term frequencies in the Google Web Corpus. Unfamiliar words are algorithmically identified and tagged for potential replacement. Easier alternatives consisting of synonyms, hypernyms, definitions, and semantic types are extracted from WordNet, the Unified Medical Language System (UMLS), and Wiktionary and ranked for a writer to choose from to simplify the text. We conducted a controlled user study with a representative writer who used our simplification algorithm to simplify texts. We tested the impact with representative consumers. The key independent variable of our study is lexical simplification, and we measured its effect on both perceived and actual text difficulty. Participants were recruited from Amazon’s Mechanical Turk website. Perceived difficulty was measured with 1 metric, a 5-point Likert scale. Actual difficulty was measured with 3 metrics: 5 multiple-choice questions alongside each text to measure understanding
Code of Federal Regulations, 2010 CFR
2010-04-01
... business within the United States, and all mutual marine insurance companies and mutual fire or flood insurance companies exclusively issuing perpetual policies or whose principal business is the issuance of...) Foreign insurance companies not carrying on an insurance business within the United States are not...
Code of Federal Regulations, 2011 CFR
2011-04-01
... insurance business within the United States, and all mutual marine insurance companies and mutual fire or flood insurance companies exclusively issuing perpetual policies or whose principal business is the...) Foreign insurance companies not carrying on an insurance business within the United States are not...
Code of Federal Regulations, 2014 CFR
2014-04-01
... 26 Internal Revenue 8 2014-04-01 2014-04-01 false Tax on insurance companies (other than life or... beginning after December 31, 1962. 1.831-3 Section 1.831-3 Internal Revenue INTERNAL REVENUE SERVICE... Companies § 1.831-3 Tax on insurance companies (other than life or mutual), mutual marine...
Code of Federal Regulations, 2013 CFR
2013-04-01
... 26 Internal Revenue 8 2013-04-01 2013-04-01 false Tax on insurance companies (other than life or... beginning after December 31, 1962. 1.831-3 Section 1.831-3 Internal Revenue INTERNAL REVENUE SERVICE... Companies § 1.831-3 Tax on insurance companies (other than life or mutual), mutual marine...
2010-01-01
Background The amount of available biological information is rapidly increasing and the focus of biological research has moved from single components to networks and even larger projects aiming at the analysis, modelling and simulation of biological networks as well as large scale comparison of cellular properties. It is therefore essential that biological knowledge is easily accessible. However, most information is contained in the written literature in an unstructured way, so that methods for the systematic extraction of knowledge directly from the primary literature have to be deployed. Description Here we present a text mining algorithm for the extraction of kinetic information such as KM, Ki, kcat etc. as well as associated information such as enzyme names, EC numbers, ligands, organisms, localisations, pH and temperatures. Using this rule- and dictionary-based approach, it was possible to extract 514,394 kinetic parameters of 13 categories (KM, Ki, kcat, kcat/KM, Vmax, IC50, S0.5, Kd, Ka, t1/2, pI, nH, specific activity, Vmax/KM) from about 17 million PubMed abstracts and combine them with other data in the abstract. A manual verification of approx. 1,000 randomly chosen results yielded a recall between 51% and 84% and a precision ranging from 55% to 96%, depending of the category searched. The results were stored in a database and are available as "KID the KInetic Database" via the internet. Conclusions The presented algorithm delivers a considerable amount of information and therefore may aid to accelerate the research and the automated analysis required for today's systems biology approaches. The database obtained by analysing PubMed abstracts may be a valuable help in the field of chemical and biological kinetics. It is completely based upon text mining and therefore complements manually curated databases. The database is available at http://kid.tu-bs.de. The source code of the algorithm is provided under the GNU General Public Licence and available on
Li, Xiangrong; Zhao, Xupei; Duan, Xiabin; Wang, Xiaoliang
2015-01-01
It is generally acknowledged that the conjugate gradient (CG) method achieves global convergence--with at most a linear convergence rate--because CG formulas are generated by linear approximations of the objective functions. The quadratically convergent results are very limited. We introduce a new PRP method in which the restart strategy is also used. Moreover, the method we developed includes not only n-step quadratic convergence but also both the function value information and gradient value information. In this paper, we will show that the new PRP method (with either the Armijo line search or the Wolfe line search) is both linearly and quadratically convergent. The numerical experiments demonstrate that the new PRP algorithm is competitive with the normal CG method.
Li, Xiangrong; Zhao, Xupei; Duan, Xiabin; Wang, Xiaoliang
2015-01-01
It is generally acknowledged that the conjugate gradient (CG) method achieves global convergence—with at most a linear convergence rate—because CG formulas are generated by linear approximations of the objective functions. The quadratically convergent results are very limited. We introduce a new PRP method in which the restart strategy is also used. Moreover, the method we developed includes not only n-step quadratic convergence but also both the function value information and gradient value information. In this paper, we will show that the new PRP method (with either the Armijo line search or the Wolfe line search) is both linearly and quadratically convergent. The numerical experiments demonstrate that the new PRP algorithm is competitive with the normal CG method. PMID:26381742
NASA Astrophysics Data System (ADS)
Siregar, B.; Gunawan, D.; Andayani, U.; Sari Lubis, Elita; Fahmi, F.
2017-01-01
Food delivery system is one kind of geographical information systems (GIS) that can be applied through digitation process. The main case in food delivery system is the way to determine the shortest path and food delivery vehicle movement tracking. Therefore, to make sure that the digitation process of food delivery system can be applied efficiently, it is needed to add shortest path determination facility and food delivery vehicle tracking. This research uses A Star (A*) algorithm for determining shortest path and location-based system (LBS) programming for moving food delivery vehicle object tracking. According to this research, it is generated the integrated system that can be used by food delivery driver, customer, and administrator in terms of simplifying the food delivery system. Through the application of shortest path and the tracking of moving vehicle, thus the application of food delivery system in the scope of geographical information system (GIS) can be executed.
A novel seizure detection algorithm informed by hidden Markov model event states
NASA Astrophysics Data System (ADS)
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.
Rastogi, Ravi; Pawluk, Dianne T V
2013-01-01
An increasing amount of information content used in school, work, and everyday living is presented in graphical form. Unfortunately, it is difficult for people who are blind or visually impaired to access this information, especially when many diagrams are needed. One problem is that details, even in relatively simple visual diagrams, can be very difficult to perceive using touch. With manually created tactile diagrams, these details are often presented in separate diagrams which must be selected from among others. Being able to actively zoom in on an area of a single diagram so that the details can be presented at a reasonable size for exploration purposes seems a simpler approach for the user. However, directly using visual zooming methods have some limitations when used haptically. Therefore, a new zooming method is proposed to avoid these pitfalls. A preliminary experiment was performed to examine the usefulness of the algorithm compared to not using zooming. The results showed that the number of correct responses improved with the developed zooming algorithm and participants found it to be more usable than not using zooming for exploration of a floor map.
Cloud classification from satellite data using a fuzzy sets algorithm: A polar example
NASA Technical Reports Server (NTRS)
Key, J. R.; Maslanik, J. A.; Barry, R. G.
1988-01-01
Where spatial boundaries between phenomena are diffuse, classification methods which construct mutually exclusive clusters seem inappropriate. The Fuzzy c-means (FCM) algorithm assigns each observation to all clusters, with membership values as a function of distance to the cluster center. The FCM algorithm is applied to AVHRR data for the purpose of classifying polar clouds and surfaces. Careful analysis of the fuzzy sets can provide information on which spectral channels are best suited to the classification of particular features, and can help determine likely areas of misclassification. General agreement in the resulting classes and cloud fraction was found between the FCM algorithm, a manual classification, and an unsupervised maximum likelihood classifier.
Cloud classification from satellite data using a fuzzy sets algorithm - A polar example
NASA Technical Reports Server (NTRS)
Key, J. R.; Maslanik, J. A.; Barry, R. G.
1989-01-01
Where spatial boundaries between phenomena are diffuse, classification methods which construct mutually exclusive clusters seem inappropriate. The Fuzzy c-means (FCM) algorithm assigns each observation to all clusters, with membership values as a function of distance to the cluster center. The FCM algorithm is applied to AVHRR data for the purpose of classifying polar clouds and surfaces. Careful analysis of the fuzzy sets can provide information on which spectral channels are best suited to the classification of particular features, and can help determine like areas of misclassification. General agreement in the resulting classes and cloud fraction was found between the FCM algorithm, a manual classification, and an unsupervised maximum likelihood classifier.
[Maintaining solidarity: is mutuality the solution?].
Gevers, J K M; Ploem, M C
2013-01-01
Solidarity is essentially the willingness to contribute to the community and its demands, which may even involve contributing more than one is expecting to receive. Another principle is mutuality: this refers to a balance between rights and obligations or between mutual obligations. In its advisory document 'The importance of mutuality......solidarity takes work!', The Dutch Council for Public Health and Health Care underlines the importance of ensuring solidarity within the Dutch health care system, e.g. by encouraging patients to take responsibility for their own health, possibly by introducing elements of mutuality. In our contribution, we comment on the Council's advice. Although we fully agree with the overall conclusion that solidarity should be maintained within the system, we do not see how the introduction of increased mutuality will contribute to this goal.
On Using Genetic Algorithms for Multimodal Relevance Optimization in Information Retrieval.
ERIC Educational Resources Information Center
Boughanem, M.; Christment, C.; Tamine, L.
2002-01-01
Presents a genetic relevance optimization process performed in an information retrieval system that uses genetic techniques for solving multimodal problems (niching) and query reformulation techniques. Explains that the niching technique allows the process to reach different relevance regions of the document space, and that query reformulations…
Spatial and Social Diffusion of Information and Influence: Models and Algorithms
ERIC Educational Resources Information Center
Doo, Myungcheol
2012-01-01
In this dissertation research, we argue that spatial alarms and activity-based social networks are two fundamentally new types of information and influence diffusion channels. Such new channels have the potential of enriching our professional experiences and our personal life quality in many unprecedented ways. First, we develop an activity driven…
Multi-Transiting Systems and Exoplanet Mutual Events
NASA Astrophysics Data System (ADS)
Coughlin, Jared; Ragozzine, D.; Holman, M. J.
2011-01-01
Until recently, studies of transiting exoplanets- planets that cross in front of their host star- have focused almost exclusively upon systems where there is only one transiting planet. Those studies that have considered additional planets have mostly done so with the goal of determining the perturbing effects that additional planets would have upon the orbit, and therefore the light curve, of the transiting planet. This work considers, in detail, a specific type of event known as an exoplanet mutual event. Such events occur when one planet passes in front of another. While such events can occur whether or not these planets are transiting, predicting and understanding these events is best done in systems with multiple transiting planets. We estimate, through an ensemble simulation, how frequently exoplanet mutual events occur and which systems are most likely to undergo exoplanet mutual events. We also investigate what information can be learned about not only the planets themselves but also the orbital architecture in such systems. We conclude that while ODT (overlapping double-transit) events occur with a much lower frequency than PPO (planet-planet occultation) events, ODT mutual events are capable of producing detectable signals, that Kepler will detect a few, and recommend that candidate systems for these events, such as KOI 191, be observed in short cadence(Steffen et. al 2010, Holman et. al 2010). This work is supported in part by the NSF REU and DOD ASSURE programs under NSF grant no. 0754568 and by the Smithsonian Institution.
Ecological genomics of mutualism decline in nitrogen-fixing bacteria
Klinger, Christie R.; Lau, Jennifer A.
2016-01-01
Anthropogenic changes can influence mutualism evolution; however, the genomic regions underpinning mutualism that are most affected by environmental change are generally unknown, even in well-studied model mutualisms like the interaction between legumes and their nitrogen (N)-fixing rhizobia. Such genomic information can shed light on the agents and targets of selection maintaining cooperation in nature. We recently demonstrated that N-fertilization has caused an evolutionary decline in mutualistic partner quality in the rhizobia that form symbiosis with clover. Here, population genomic analyses of N-fertilized versus control rhizobium populations indicate that evolutionary differentiation at a key symbiosis gene region on the symbiotic plasmid (pSym) contributes to partner quality decline. Moreover, patterns of genetic variation at selected loci were consistent with recent positive selection within N-fertilized environments, suggesting that N-rich environments might select for less beneficial rhizobia. By studying the molecular population genomics of a natural bacterial population within a long-term ecological field experiment, we find that: (i) the N environment is indeed a potent selective force mediating mutualism evolution in this symbiosis, (ii) natural variation in rhizobium partner quality is mediated in part by key symbiosis genes on the symbiotic plasmid, and (iii) differentiation at selected genes occurred in the context of otherwise recombining genomes, resembling eukaryotic models of adaptation. PMID:26962142
NASA Technical Reports Server (NTRS)
Brenner, Richard; Lala, Jaynarayan H.; Nagle, Gail A.; Schor, Andrei; Turkovich, John
1994-01-01
This program demonstrated the integration of a number of technologies that can increase the availability and reliability of launch vehicles while lowering costs. Availability is increased with an advanced guidance algorithm that adapts trajectories in real-time. Reliability is increased with fault-tolerant computers and communication protocols. Costs are reduced by automatically generating code and documentation. This program was realized through the cooperative efforts of academia, industry, and government. The NASA-LaRC coordinated the effort, while Draper performed the integration. Georgia Institute of Technology supplied a weak Hamiltonian finite element method for optimal control problems. Martin Marietta used MATLAB to apply this method to a launch vehicle (FENOC). Draper supplied the fault-tolerant computing and software automation technology. The fault-tolerant technology includes sequential and parallel fault-tolerant processors (FTP & FTPP) and authentication protocols (AP) for communication. Fault-tolerant technology was incrementally incorporated. Development culminated with a heterogeneous network of workstations and fault-tolerant computers using AP. Draper's software automation system, ASTER, was used to specify a static guidance system based on FENOC, navigation, flight control (GN&C), models, and the interface to a user interface for mission control. ASTER generated Ada code for GN&C and C code for models. An algebraic transform engine (ATE) was developed to automatically translate MATLAB scripts into ASTER.
Onset of fights and mutual assessment in ant founding queens.
Berthelot, Kévin; Portugal, Felipe Ramon; Jeanson, Raphaël
2017-03-01
In animals, the progress and outcome of contests can be influenced by an individual's own condition, their opponent's condition or a combination of the two. The use of chemical information to assess the quality of rivals has been underestimated despite its central role in the regulation of social interactions in many taxa. Here, we studied pairwise contests between founding queens of the ant Lasius niger to investigate whether the decision to engage in agonistic interactions relies on self-assessment or mutual assessment. Queens modulated their aggressive behaviours depending on both their own status and their opponent's status. We found no influence of lipid stores or size on the onset of fights. However, differences in cuticular chemical signatures linked to fertility status accurately predicted the probability of behaving aggressively in pairs. Our study thus suggests that ant queens could rely on mutual assessment via chemical cues to make informed decisions about fight initiation.
12 CFR 575.3 - Mutual holding company reorganizations.
Code of Federal Regulations, 2014 CFR
2014-01-01
... 12 Banks and Banking 6 2014-01-01 2012-01-01 true Mutual holding company reorganizations. 575.3... COMPANIES § 575.3 Mutual holding company reorganizations. A mutual savings association may reorganize to become a mutual holding company, or join in a mutual holding company reorganization as an...
12 CFR 239.3 - Mutual holding company reorganizations.
Code of Federal Regulations, 2014 CFR
2014-01-01
... 12 Banks and Banking 4 2014-01-01 2014-01-01 false Mutual holding company reorganizations. 239.3... RESERVE SYSTEM (CONTINUED) MUTUAL HOLDING COMPANIES (REGULATION MM) Mutual Holding Companies § 239.3 Mutual holding company reorganizations. (a) A mutual savings association may not reorganize to become...
12 CFR 575.3 - Mutual holding company reorganizations.
Code of Federal Regulations, 2013 CFR
2013-01-01
... 12 Banks and Banking 6 2013-01-01 2012-01-01 true Mutual holding company reorganizations. 575.3... COMPANIES § 575.3 Mutual holding company reorganizations. A mutual savings association may reorganize to become a mutual holding company, or join in a mutual holding company reorganization as an...
12 CFR 239.3 - Mutual holding company reorganizations.
Code of Federal Regulations, 2013 CFR
2013-01-01
... 12 Banks and Banking 4 2013-01-01 2013-01-01 false Mutual holding company reorganizations. 239.3... RESERVE SYSTEM (CONTINUED) MUTUAL HOLDING COMPANIES (REGULATION MM) Mutual Holding Companies § 239.3 Mutual holding company reorganizations. (a) A mutual savings association may not reorganize to become...
12 CFR 575.3 - Mutual holding company reorganizations.
Code of Federal Regulations, 2010 CFR
2010-01-01
... 12 Banks and Banking 5 2010-01-01 2010-01-01 false Mutual holding company reorganizations. 575.3... COMPANIES § 575.3 Mutual holding company reorganizations. A mutual savings association may reorganize to become a mutual holding company, or join in a mutual holding company reorganization as an...
12 CFR 575.3 - Mutual holding company reorganizations.
Code of Federal Regulations, 2011 CFR
2011-01-01
... 12 Banks and Banking 5 2011-01-01 2011-01-01 false Mutual holding company reorganizations. 575.3... COMPANIES § 575.3 Mutual holding company reorganizations. A mutual savings association may reorganize to become a mutual holding company, or join in a mutual holding company reorganization as an...
12 CFR 239.3 - Mutual holding company reorganizations.
Code of Federal Regulations, 2012 CFR
2012-01-01
... 12 Banks and Banking 4 2012-01-01 2012-01-01 false Mutual holding company reorganizations. 239.3... RESERVE SYSTEM (CONTINUED) MUTUAL HOLDING COMPANIES (REGULATION MM) Mutual Holding Companies § 239.3 Mutual holding company reorganizations. (a) A mutual savings association may not reorganize to become...
12 CFR 575.3 - Mutual holding company reorganizations.
Code of Federal Regulations, 2012 CFR
2012-01-01
... 12 Banks and Banking 6 2012-01-01 2012-01-01 false Mutual holding company reorganizations. 575.3... COMPANIES § 575.3 Mutual holding company reorganizations. A mutual savings association may reorganize to become a mutual holding company, or join in a mutual holding company reorganization as an...
Some properties of probability inversion algorithms to elicit expert opinion.
NASA Astrophysics Data System (ADS)
Lark, Murray
2015-04-01
Probability inversion methods have been developed to infer underlying expert utility functions from rankings that experts offer of subsets of scenarios. The method assumes that the expert ranking reflects an underlying utility, which can be modelled as a function of predictive covariates. This is potentially useful as a method for the extraction of expert opinions for prediction in new scenarios. Two particular algorithms are considered here, the IPF algorithm and the PURE algorithm. The former always converges for consistent sets of rankings and finds a solution which minimizes the mutual information of the estimated utilities and an initial random sample of proposed utilities drawn in the algorithm. In this poster I report some empirical studies on the probability inversion procedure, investigating the effects of the size of the expert panel, the consistency and quality of the expert panel and the validity of the predictive covariates. These results have practical implications for the design of elicitation by probability inversion methods.
NASA Astrophysics Data System (ADS)
Mallas, Georgios; Brooks, Dana H.; Rosenthal, Amir; Vinegoni, Claudio; Calfon, Marcella A.; Razansky, R. Nika; Jaffer, Farouc A.; Ntziachristos, Vasilis
2011-03-01
Intravascular Near-Infrared Fluorescence (NIRF) imaging is a promising imaging modality to image vessel biology and high-risk plaques in vivo. We have developed a NIRF fiber optic catheter and have presented the ability to image atherosclerotic plaques in vivo, using appropriate NIR fluorescent probes. Our catheter consists of a 100/140 μm core/clad diameter housed in polyethylene tubing, emitting NIR laser light at a 90 degree angle compared to the fiber's axis. The system utilizes a rotational and a translational motor for true 2D imaging and operates in conjunction with a coaxial intravascular ultrasound (IVUS) device. IVUS datasets provide 3D images of the internal structure of arteries and are used in our system for anatomical mapping. Using the IVUS images, we are building an accurate hybrid fluorescence-IVUS data inversion scheme that takes into account photon propagation through the blood filled lumen. This hybrid imaging approach can then correct for the non-linear dependence of light intensity on the distance of the fluorescence region from the fiber tip, leading to quantitative imaging. The experimental and algorithmic developments will be presented and the effectiveness of the algorithm showcased with experimental results in both saline and blood-like preparations. The combined structural and molecular information obtained from these two imaging modalities are positioned to enable the accurate diagnosis of biologically high-risk atherosclerotic plaques in the coronary arteries that are responsible for heart attacks.
NASA Astrophysics Data System (ADS)
Guo, Rui; Li, Weixing; Zhang, Yue; Chen, Zengping
2016-01-01
A direction of arrival (DOA) estimation algorithm for coherent signals in the presence of unknown mutual coupling is proposed. A group of auxiliary sensors in a uniform linear array are applied to eliminate the effects on the orthogonality of subspaces brought by mutual coupling. Then, a Toeplitz matrix, whose rank is independent of the coherency between impinging signals, is reconstructed to eliminate the rank loss of the spatial covariance matrix. Therefore, the signal and noise subspaces can be estimated properly. This method can estimate the DOAs of coherent signals under unknown mutual coupling accurately without any iteration and calibration sources. It has a low computational burden and high accuracy. Simulation results demonstrate the effectiveness of the algorithm.
Zheng, Ying; Yeh, Chen-Wei; Yang, Chi-Da; Jang, Shi-Shang; Chu, I-Ming
2007-08-31
Biological information generated by high-throughput technology has made systems approach feasible for many biological problems. By this approach, optimization of metabolic pathway has been successfully applied in the amino acid production. However, in this technique, gene modifications of metabolic control architecture as well as enzyme expression levels are coupled and result in a mixed integer nonlinear programming problem. Furthermore, the stoichiometric complexity of metabolic pathway, along with strong nonlinear behaviour of the regulatory kinetic models, directs a highly rugged contour in the whole optimization problem. There may exist local optimal solutions wherein the same level of production through different flux distributions compared with global optimum. The purpose of this work is to develop a novel stochastic optimization approach-information guided genetic algorithm (IGA) to discover the local optima with different levels of modification of the regulatory loop and production rates. The novelties of this work include the information theory, local search, and clustering analysis to discover the local optima which have physical meaning among the qualified solutions.
NASA Astrophysics Data System (ADS)
Horn, Florian; Bayer, Florian; Pelzer, Georg; Rieger, Jens; Ritter, André; Weber, Thomas; Zang, Andrea; Michel, Thilo; Anton, Gisela
2014-03-01
Grating-based X-ray phase-contrast imaging is a promising imaging modality to increase soft tissue contrast in comparison to conventional attenuation-based radiography. Complementary and otherwise inaccessible information is provided by the dark-field image, which shows the sub-pixel size granularity of the measured object. This could especially turn out to be useful in mammography, where tumourous tissue is connected with the presence of supertiny microcalcifications. In addition to the well-established image reconstruction process, an analysis method was introduced by Modregger, 1 which is based on deconvolution of the underlying scattering distribution within a single pixel revealing information about the sample. Subsequently, the different contrast modalities can be calculated with the scattering distribution. The method already proved to deliver additional information in the higher moments of the scattering distribution and possibly reaches better image quality with respect to an increased contrast-to-noise ratio. Several measurements were carried out using melamine foams as phantoms. We analysed the dependency of the deconvolution-based method with respect to the dark-field image on different parameters such as dose, number of iterations of the iterative deconvolution-algorithm and dark-field signal. A disagreement was found in the reconstructed dark-field values between the FFT method and the iterative method. Usage of the resulting characteristics might be helpful in future applications.
NASA Astrophysics Data System (ADS)
Li, Si Jia; Cao, Xiang Yu; Xu, Li Ming; Zhou, Long Jian; Yang, Huan Huan; Han, Jiang Feng; Zhang, Zhao; Zhang, Di; Liu, Xiao; Zhang, Chen; Zheng, Yue Jun; Zhao, Yi
2016-11-01
We proposed an ultra-broadband reflective metamaterial with controlling the scattering electromagnetic fields based on a polarization convertor. The unit cell of the polarization convertor was composed of a three layers substrate with double metallic split-rings structure and a metal ground plane. The proposed polarization convertor and that with rotation angle of 90 deg had been employed as the “0” and “1” elements to design the digital reflective metamaterial. The numbers of the “0” and “1” elements were chosen based on the information entropy theory. Then, the optimized combinational format was selected by genetic optimization algorithm. The scattering electromagnetic fields had been manipulated due to destructive interference, which was attributed to the control of phase and amplitude by the proposed polarization convertor. Simulated and experimental results indicated that the reflective metamaterial exhibited significantly RCS reduction in an ultra-broad frequency band for both normal and oblique incidences.
Li, Si Jia; Cao, Xiang Yu; Xu, Li Ming; Zhou, Long Jian; Yang, Huan Huan; Han, Jiang Feng; Zhang, Zhao; Zhang, Di; Liu, Xiao; Zhang, Chen; Zheng, Yue Jun; Zhao, Yi
2016-11-22
We proposed an ultra-broadband reflective metamaterial with controlling the scattering electromagnetic fields based on a polarization convertor. The unit cell of the polarization convertor was composed of a three layers substrate with double metallic split-rings structure and a metal ground plane. The proposed polarization convertor and that with rotation angle of 90 deg had been employed as the "0" and "1" elements to design the digital reflective metamaterial. The numbers of the "0" and "1" elements were chosen based on the information entropy theory. Then, the optimized combinational format was selected by genetic optimization algorithm. The scattering electromagnetic fields had been manipulated due to destructive interference, which was attributed to the control of phase and amplitude by the proposed polarization convertor. Simulated and experimental results indicated that the reflective metamaterial exhibited significantly RCS reduction in an ultra-broad frequency band for both normal and oblique incidences.
Li, Si Jia; Cao, Xiang Yu; Xu, Li Ming; Zhou, Long Jian; Yang, Huan Huan; Han, Jiang Feng; Zhang, Zhao; Zhang, Di; Liu, Xiao; Zhang, Chen; Zheng, Yue Jun; Zhao, Yi
2016-01-01
We proposed an ultra-broadband reflective metamaterial with controlling the scattering electromagnetic fields based on a polarization convertor. The unit cell of the polarization convertor was composed of a three layers substrate with double metallic split-rings structure and a metal ground plane. The proposed polarization convertor and that with rotation angle of 90 deg had been employed as the “0” and “1” elements to design the digital reflective metamaterial. The numbers of the “0” and “1” elements were chosen based on the information entropy theory. Then, the optimized combinational format was selected by genetic optimization algorithm. The scattering electromagnetic fields had been manipulated due to destructive interference, which was attributed to the control of phase and amplitude by the proposed polarization convertor. Simulated and experimental results indicated that the reflective metamaterial exhibited significantly RCS reduction in an ultra-broad frequency band for both normal and oblique incidences. PMID:27874082
Sakhanenko, Nikita A.
2015-01-01
Abstract Information theory is valuable in multiple-variable analysis for being model-free and nonparametric, and for the modest sensitivity to undersampling. We previously introduced a general approach to finding multiple dependencies that provides accurate measures of levels of dependency for subsets of variables in a data set, which is significantly nonzero only if the subset of variables is collectively dependent. This is useful, however, only if we can avoid a combinatorial explosion of calculations for increasing numbers of variables. The proposed dependence measure for a subset of variables, τ, differential interaction information, Δ(τ), has the property that for subsets of τ some of the factors of Δ(τ) are significantly nonzero, when the full dependence includes more variables. We use this property to suppress the combinatorial explosion by following the “shadows” of multivariable dependency on smaller subsets. Rather than calculating the marginal entropies of all subsets at each degree level, we need to consider only calculations for subsets of variables with appropriate “shadows.” The number of calculations for n variables at a degree level of d grows therefore, at a much smaller rate than the binomial coefficient (n, d), but depends on the parameters of the “shadows” calculation. This approach, avoiding a combinatorial explosion, enables the use of our multivariable measures on very large data sets. We demonstrate this method on simulated data sets, and characterize the effects of noise and sample numbers. In addition, we analyze a data set of a few thousand mutant yeast strains interacting with a few thousand chemical compounds. PMID:26335709
Sakhanenko, Nikita A; Galas, David J
2015-11-01
Information theory is valuable in multiple-variable analysis for being model-free and nonparametric, and for the modest sensitivity to undersampling. We previously introduced a general approach to finding multiple dependencies that provides accurate measures of levels of dependency for subsets of variables in a data set, which is significantly nonzero only if the subset of variables is collectively dependent. This is useful, however, only if we can avoid a combinatorial explosion of calculations for increasing numbers of variables. The proposed dependence measure for a subset of variables, τ, differential interaction information, Δ(τ), has the property that for subsets of τ some of the factors of Δ(τ) are significantly nonzero, when the full dependence includes more variables. We use this property to suppress the combinatorial explosion by following the "shadows" of multivariable dependency on smaller subsets. Rather than calculating the marginal entropies of all subsets at each degree level, we need to consider only calculations for subsets of variables with appropriate "shadows." The number of calculations for n variables at a degree level of d grows therefore, at a much smaller rate than the binomial coefficient (n, d), but depends on the parameters of the "shadows" calculation. This approach, avoiding a combinatorial explosion, enables the use of our multivariable measures on very large data sets. We demonstrate this method on simulated data sets, and characterize the effects of noise and sample numbers. In addition, we analyze a data set of a few thousand mutant yeast strains interacting with a few thousand chemical compounds.
Economic game theory for mutualism and cooperation.
Archetti, Marco; Scheuring, István; Hoffman, Moshe; Frederickson, Megan E; Pierce, Naomi E; Yu, Douglas W
2011-12-01
We review recent work at the interface of economic game theory and evolutionary biology that provides new insights into the evolution of partner choice, host sanctions, partner fidelity feedback and public goods. (1) The theory of games with asymmetrical information shows that the right incentives allow hosts to screen-out parasites and screen-in mutualists, explaining successful partner choice in the absence of signalling. Applications range from ant-plants to microbiomes. (2) Contract theory distinguishes two longstanding but weakly differentiated explanations of host response to defectors: host sanctions and partner fidelity feedback. Host traits that selectively punish misbehaving symbionts are parsimoniously interpreted as pre-adaptations. Yucca-moth and legume-rhizobia mutualisms are argued to be examples of partner fidelity feedback. (3) The theory of public goods shows that cooperation in multi-player interactions can evolve in the absence of assortment, in one-shot social dilemmas among non-kin. Applications include alarm calls in vertebrates and exoenzymes in microbes.
Mycorrhiza: A Common Form of Mutualism.
ERIC Educational Resources Information Center
Medve, Richard J.
1978-01-01
Mycorrhizae are among the most common examples of mutualism. This article discusses their structure, symbolic relationship, factors affecting formation and applying research. Questions are posed and answers suggested. (MA)
Phenological shifts and the fate of mutualisms
Rafferty, Nicole E.; CaraDonna, Paul J.; Bronstein, Judith L.
2014-01-01
Climate change is altering the timing of life history events in a wide array of species, many of which are involved in mutualistic interactions. Because many mutualisms can form only if partner species are able to locate each other in time, differential phenological shifts are likely to influence their strength, duration and outcome. At the extreme, climate change-driven shifts in phenology may result in phenological mismatch: the partial or complete loss of temporal overlap of mutualistic species. We have a growing understanding of how, when, and why phenological change can alter one type of mutualism–pollination. However, as we show here, there has been a surprising lack of attention to other types of mutualism. We generate a set of predictions about the characteristics that may predispose mutualisms in general to phenological mismatches. We focus not on the consequences of such mismatches but rather on the likelihood that mismatches will develop. We explore the influence of three key characteristics of mutualism: 1) intimacy, 2) seasonality and duration, and 3) obligacy and specificity. We predict that the following characteristics of mutualism may increase the likelihood of phenological mismatch: 1) a non-symbiotic life history in which co-dispersal is absent; 2) brief, seasonal interactions; and 3) facultative, generalized interactions. We then review the limited available data in light of our a priori predictions and point to mutualisms that are more and less likely to be at risk of becoming phenologically mismatched, emphasizing the need for research on mutualisms other than plant–pollinator interactions. Future studies should explicitly focus on mutualism characteristics to determine whether and how changing phenologies will affect mutualistic interactions. PMID:25883391
Improving quantum state estimation with mutually unbiased bases.
Adamson, R B A; Steinberg, A M
2010-07-16
When used in quantum state estimation, projections onto mutually unbiased bases have the ability to maximize information extraction per measurement and to minimize redundancy. We present the first experimental demonstration of quantum state tomography of two-qubit polarization states to take advantage of mutually unbiased bases. We demonstrate improved state estimation as compared to standard measurement strategies and discuss how this can be understood from the structure of the measurements we use. We experimentally compared our method to the standard state estimation method for three different states and observe that the infidelity was up to 1.84 ± 0.06 times lower by using our technique than it was by using standard state estimation methods.
Qualitative teamwork issues and strategies: coordination through mutual adjustment.
Hall, Wendy A; Long, Bonita; Bermbach, Nicole; Jordan, Sharalyn; Patterson, Kathryn
2005-03-01
Multidisciplinary research teams that include faculty, students, and volunteers can be challenging and enriching for all participants. Although such teams are becoming commonplace, minimal guidance is available about strategies to enhance team effectiveness. In this article, the authors highlight strategies to guide qualitative teamwork through coordination of team members and tasks based on mutual adjustment. Using a grounded theory exemplar, they focus on issues of (a) building the team, (b) developing reflexivity and theoretical sensitivity, (c) tackling analytic and methodological procedures, and (d) developing dissemination guidelines. Sharing information, articulating project goals and elements, acknowledging variation in individual goals, and engaging in reciprocity and respectful collaboration are key elements of mutual adjustment. The authors summarize conclusions about the costs and benefits of the process.
Borthwick, Kenneth M; Smelser, Diane T; Bock, Jonathan A; Elmore, James R; Ryer, Evan J; Ye, Zi; Pacheco, Jennifer A.; Carrell, David S.; Michalkiewicz, Michael; Thompson, William K; Pathak, Jyotishman; Bielinski, Suzette J; Denny, Joshua C; Linneman, James G; Peissig, Peggy L; Kho, Abel N; Gottesman, Omri; Parmar, Harpreet; Kullo, Iftikhar J; McCarty, Catherine A; Böttinger, Erwin P; Larson, Eric B; Jarvik, Gail P; Harley, John B; Bajwa, Tanvir; Franklin, David P; Carey, David J; Kuivaniemi, Helena; Tromp, Gerard
2015-01-01
Background and objective We designed an algorithm to identify abdominal aortic aneurysm cases and controls from electronic health records to be shared and executed within the “electronic Medical Records and Genomics” (eMERGE) Network. Materials and methods Structured Query Language, was used to script the algorithm utilizing “Current Procedural Terminology” and “International Classification of Diseases” codes, with demographic and encounter data to classify individuals as case, control, or excluded. The algorithm was validated using blinded manual chart review at three eMERGE Network sites and one non-eMERGE Network site. Validation comprised evaluation of an equal number of predicted cases and controls selected at random from the algorithm predictions. After validation at the three eMERGE Network sites, the remaining eMERGE Network sites performed verification only. Finally, the algorithm was implemented as a workflow in the Konstanz Information Miner, which represented the logic graphically while retaining intermediate data for inspection at each node. The algorithm was configured to be independent of specific access to data and was exportable (without data) to other sites. Results The algorithm demonstrated positive predictive values (PPV) of 92.8% (CI: 86.8-96.7) and 100% (CI: 97.0-100) for cases and controls, respectively. It performed well also outside the eMERGE Network. Implementation of the transportable executable algorithm as a Konstanz Information Miner workflow required much less effort than implementation from pseudo code, and ensured that the logic was as intended. Discussion and conclusion This ePhenotyping algorithm identifies abdominal aortic aneurysm cases and controls from the electronic health record with high case and control PPV necessary for research purposes, can be disseminated easily, and applied to high-throughput genetic and other studies. PMID:27054044
Carvalho, Benilton S.; Bilevicius, Elizabeth; Alvim, Marina K. M.; Lopes-Cendes, Iscia
2017-01-01
Mesial temporal lobe epilepsy is the most common form of adult epilepsy in surgical series. Currently, the only characteristic used to predict poor response to clinical treatment in this syndrome is the presence of hippocampal sclerosis. Single nucleotide polymorphisms (SNPs) located in genes encoding drug transporter and metabolism proteins could influence response to therapy. Therefore, we aimed to evaluate whether combining information from clinical variables as well as SNPs in candidate genes could improve the accuracy of predicting response to drug therapy in patients with mesial temporal lobe epilepsy. For this, we divided 237 patients into two groups: 75 responsive and 162 refractory to antiepileptic drug therapy. We genotyped 119 SNPs in ABCB1, ABCC2, CYP1A1, CYP1A2, CYP1B1, CYP2C9, CYP2C19, CYP2D6, CYP2E1, CYP3A4, and CYP3A5 genes. We used 98 additional SNPs to evaluate population stratification. We assessed a first scenario using only clinical variables and a second one including SNP information. The random forests algorithm combined with leave-one-out cross-validation was used to identify the best predictive model in each scenario and compared their accuracies using the area under the curve statistic. Additionally, we built a variable importance plot to present the set of most relevant predictors on the best model. The selected best model included the presence of hippocampal sclerosis and 56 SNPs. Furthermore, including SNPs in the model improved accuracy from 0.4568 to 0.8177. Our findings suggest that adding genetic information provided by SNPs, located on drug transport and metabolism genes, can improve the accuracy for predicting which patients with mesial temporal lobe epilepsy are likely to be refractory to drug treatment, making it possible to identify patients who may benefit from epilepsy surgery sooner. PMID:28052106
Yang, Liu; Lu, Yinzhi; Zhong, Yuanchang; Wu, Xuegang; Yang, Simon X.
2015-01-01
Energy resource limitation is a severe problem in traditional wireless sensor networks (WSNs) because it restricts the lifetime of network. Recently, the emergence of energy harvesting techniques has brought with them the expectation to overcome this problem. In particular, it is possible for a sensor node with energy harvesting abilities to work perpetually in an Energy Neutral state. In this paper, a Multi-hop Energy Neutral Clustering (MENC) algorithm is proposed to construct the optimal multi-hop clustering architecture in energy harvesting WSNs, with the goal of achieving perpetual network operation. All cluster heads (CHs) in the network act as routers to transmit data to base station (BS) cooperatively by a multi-hop communication method. In addition, by analyzing the energy consumption of intra- and inter-cluster data transmission, we give the energy neutrality constraints. Under these constraints, every sensor node can work in an energy neutral state, which in turn provides perpetual network operation. Furthermore, the minimum network data transmission cycle is mathematically derived using convex optimization techniques while the network information gathering is maximal. Simulation results show that our protocol can achieve perpetual network operation, so that the consistent data delivery is guaranteed. In addition, substantial improvements on the performance of network throughput are also achieved as compared to the famous traditional clustering protocol LEACH and recent energy harvesting aware clustering protocols. PMID:26712764
NASA Technical Reports Server (NTRS)
Peddle, Derek R.; Huemmrich, K. Fred; Hall, Forrest G.; Masek, Jeffrey G.; Soenen, Scott A.; Jackson, Chris D.
2011-01-01
Canopy reflectance model inversion using look-up table approaches provides powerful and flexible options for deriving improved forest biophysical structural information (BSI) compared with traditional statistical empirical methods. The BIOPHYS algorithm is an improved, physically-based inversion approach for deriving BSI for independent use and validation and for monitoring, inventory and quantifying forest disturbance as well as input to ecosystem, climate and carbon models. Based on the multiple-forward mode (MFM) inversion approach, BIOPHYS results were summarized from different studies (Minnesota/NASA COVER; Virginia/LEDAPS; Saskatchewan/BOREAS), sensors (airborne MMR; Landsat; MODIS) and models (GeoSail; GOMS). Applications output included forest density, height, crown dimension, branch and green leaf area, canopy cover, disturbance estimates based on multi-temporal chronosequences, and structural change following recovery from forest fires over the last century. Good correspondences with validation field data were obtained. Integrated analyses of multiple solar and view angle imagery further improved retrievals compared with single pass data. Quantifying ecosystem dynamics such as the area and percent of forest disturbance, early regrowth and succession provide essential inputs to process-driven models of carbon flux. BIOPHYS is well suited for large-area, multi-temporal applications involving multiple image sets and mosaics for assessing vegetation disturbance and quantifying biophysical structural dynamics and change. It is also suitable for integration with forest inventory, monitoring, updating, and other programs.
Yang, Liu; Lu, Yinzhi; Zhong, Yuanchang; Wu, Xuegang; Yang, Simon X
2015-12-26
Energy resource limitation is a severe problem in traditional wireless sensor networks (WSNs) because it restricts the lifetime of network. Recently, the emergence of energy harvesting techniques has brought with them the expectation to overcome this problem. In particular, it is possible for a sensor node with energy harvesting abilities to work perpetually in an Energy Neutral state. In this paper, a Multi-hop Energy Neutral Clustering (MENC) algorithm is proposed to construct the optimal multi-hop clustering architecture in energy harvesting WSNs, with the goal of achieving perpetual network operation. All cluster heads (CHs) in the network act as routers to transmit data to base station (BS) cooperatively by a multi-hop communication method. In addition, by analyzing the energy consumption of intra- and inter-cluster data transmission, we give the energy neutrality constraints. Under these constraints, every sensor node can work in an energy neutral state, which in turn provides perpetual network operation. Furthermore, the minimum network data transmission cycle is mathematically derived using convex optimization techniques while the network information gathering is maximal. Simulation results show that our protocol can achieve perpetual network operation, so that the consistent data delivery is guaranteed. In addition, substantial improvements on the performance of network throughput are also achieved as compared to the famous traditional clustering protocol LEACH and recent energy harvesting aware clustering protocols.
NASA Astrophysics Data System (ADS)
Hou, W.; Wang, J.; Xu, X.; Leitch, J. W.; Delker, T.; Chen, G.
2015-12-01
This paper includes a series of studies that aim to develop a hyperspectral remote sensing technique for retrieving aerosol properties from a newly developed instrument GEO-TASO (Geostationary Trance gas and Aerosol Sensor Optimization) that measures the radiation at 0.4-0.7 wavelengths at spectral resolution of 0.02 nm. GEOS-TASO instrument is a prototype instrument of TEMPO (Tropospheric Emissions: Monitoring of Pollution), which will be launched in 2022 to measure aerosols, O3, and other trace gases from a geostationary orbit over the N-America. The theoretical framework of optimized inversion algorithm and the information content analysis such as degree of freedom for signal (DFS) will be discussed for hyperspectral remote sensing in visible bands, as well as the application to GEO-TASO, which has mounted on the NASA HU-25C aircraft and gathered several days' of airborne hyperspectral data for our studies. Based on the optimization theory and different from the traditional lookup table (LUT) retrieval technique, our inversion method intends to retrieve the aerosol parameters and surface reflectance simultaneously, in which UNL-VRTM (UNified Linearized Radiative Transfer Model) is employed for forward model and Jacobians calculation, meanwhile, principal component analysis (PCA) is used to constrain the hyperspectral surface reflectance.The information content analysis provides the theoretical analysis guidance about what kind of aerosol parameters could be retrieved from GeoTASO hyperspectral remote sensing to the practical inversion study. Besides, the inversion conducted iteratively until the modeled spectral radiance fits with GeoTASO measurements by a Quasi-Newton method called L-BFGS-B (Large scale BFGS Bound constrained). Finally, the retrieval results of aerosol optical depth and other aerosol parameters are compared against those retrieved by AEROENT and/or in situ measurements such as DISCOVER-AQ during the aircraft campaign.
Algorithms and Algorithmic Languages.
ERIC Educational Resources Information Center
Veselov, V. M.; Koprov, V. M.
This paper is intended as an introduction to a number of problems connected with the description of algorithms and algorithmic languages, particularly the syntaxes and semantics of algorithmic languages. The terms "letter, word, alphabet" are defined and described. The concept of the algorithm is defined and the relation between the algorithm and…
Sorokine, Alexandre; Schlicher, Bob G.; Ward, Richard C.; ...
2015-05-22
This paper describes an original approach to generating scenarios for the purpose of testing the algorithms used to detect special nuclear materials (SNM) that incorporates the use of ontologies. Separating the signal of SNM from the background requires sophisticated algorithms. To assist in developing such algorithms, there is a need for scenarios that capture a very wide range of variables affecting the detection process, depending on the type of detector being used. To provide such a cpability, we developed an ontology-driven information system (ODIS) for generating scenarios that can be used in creating scenarios for testing of algorithms for SNMmore » detection. The ontology-driven scenario generator (ODSG) is an ODIS based on information supplied by subject matter experts and other documentation. The details of the creation of the ontology, the development of the ontology-driven information system, and the design of the web user interface (UI) are presented along with specific examples of scenarios generated using the ODSG. We demonstrate that the paradigm behind the ODSG is capable of addressing the problem of semantic complexity at both the user and developer levels. Compared to traditional approaches, an ODIS provides benefits such as faithful representation of the users' domain conceptualization, simplified management of very large and semantically diverse datasets, and the ability to handle frequent changes to the application and the UI. Furthermore, the approach makes possible the generation of a much larger number of specific scenarios based on limited user-supplied information« less
Sorokine, Alexandre; Schlicher, Bob G.; Ward, Richard C.; Wright, Michael C.; Kruse, Kara L.; Bhaduri, Budhendra; Slepoy, Alexander
2015-05-22
This paper describes an original approach to generating scenarios for the purpose of testing the algorithms used to detect special nuclear materials (SNM) that incorporates the use of ontologies. Separating the signal of SNM from the background requires sophisticated algorithms. To assist in developing such algorithms, there is a need for scenarios that capture a very wide range of variables affecting the detection process, depending on the type of detector being used. To provide such a cpability, we developed an ontology-driven information system (ODIS) for generating scenarios that can be used in creating scenarios for testing of algorithms for SNM detection. The ontology-driven scenario generator (ODSG) is an ODIS based on information supplied by subject matter experts and other documentation. The details of the creation of the ontology, the development of the ontology-driven information system, and the design of the web user interface (UI) are presented along with specific examples of scenarios generated using the ODSG. We demonstrate that the paradigm behind the ODSG is capable of addressing the problem of semantic complexity at both the user and developer levels. Compared to traditional approaches, an ODIS provides benefits such as faithful representation of the users' domain conceptualization, simplified management of very large and semantically diverse datasets, and the ability to handle frequent changes to the application and the UI. Furthermore, the approach makes possible the generation of a much larger number of specific scenarios based on limited user-supplied information
Integrating plant carbon dynamics with mutualism ecology.
Pringle, Elizabeth G
2016-04-01
Plants reward microbial and animal mutualists with carbohydrates to obtain nutrients, defense, pollination, and dispersal. Under a fixed carbon budget, plants must allocate carbon to their mutualists at the expense of allocation to growth, reproduction, or storage. Such carbon trade-offs are indirectly expressed when a plant exhibits reduced growth or fecundity in the presence of its mutualist. Because carbon regulates the costs of all plant mutualisms, carbon dynamics are a common platform for integrating these costs in the face of ecological complexity and context dependence. The ecophysiology of whole-plant carbon allocation could thus elucidate the ecology and evolution of plant mutualisms. If mutualisms are costly to plants, then they must be important but frequently underestimated sinks in the terrestrial carbon cycle.
Conceptual Alignment: How Brains Achieve Mutual Understanding.
Stolk, Arjen; Verhagen, Lennart; Toni, Ivan
2016-03-01
We share our thoughts with other minds, but we do not understand how. Having a common language certainly helps, but infants' and tourists' communicative success clearly illustrates that sharing thoughts does not require signals with a pre-assigned meaning. In fact, human communicators jointly build a fleeting conceptual space in which signals are a means to seek and provide evidence for mutual understanding. Recent work has started to capture the neural mechanisms supporting those fleeting conceptual alignments. The evidence suggests that communicators and addressees achieve mutual understanding by using the same computational procedures, implemented in the same neuronal substrate, and operating over temporal scales independent from the signals' occurrences.
NASA Astrophysics Data System (ADS)
Schiff, Steven J.; So, Paul; Chang, Taeun; Burke, Robert E.; Sauer, Tim
1996-12-01
A method to characterize dynamical interdependence among nonlinear systems is derived based on mutual nonlinear prediction. Systems with nonlinear correlation will show mutual nonlinear prediction when standard analysis with linear cross correlation might fail. Mutual nonlinear prediction also provides information on the directionality of the coupling between systems. Furthermore, the existence of bidirectional mutual nonlinear prediction in unidirectionally coupled systems implies generalized synchrony. Numerical examples studied include three classes of unidirectionally coupled systems: systems with identical parameters, nonidentical parameters, and stochastic driving of a nonlinear system. This technique is then applied to the activity of motoneurons within a spinal cord motoneuron pool. The interrelationships examined include single neuron unit firing, the total number of neurons discharging at one time as measured by the integrated monosynaptic reflex, and intracellular measurements of integrated excitatory postsynaptic potentials (EPSP's). Dynamical interdependence, perhaps generalized synchrony, was identified in this neuronal network between simultaneous single unit firings, between units and the population, and between units and intracellular EPSP's.
2011-01-01
Background Envenomation by crotaline snakes (rattlesnake, cottonmouth, copperhead) is a complex, potentially lethal condition affecting thousands of people in the United States each year. Treatment of crotaline envenomation is not standardized, and significant variation in practice exists. Methods A geographically diverse panel of experts was convened for the purpose of deriving an evidence-informed unified treatment algorithm. Research staff analyzed the extant medical literature and performed targeted analyses of existing databases to inform specific clinical decisions. A trained external facilitator used modified Delphi and structured consensus methodology to achieve consensus on the final treatment algorithm. Results A unified treatment algorithm was produced and endorsed by all nine expert panel members. This algorithm provides guidance about clinical and laboratory observations, indications for and dosing of antivenom, adjunctive therapies, post-stabilization care, and management of complications from envenomation and therapy. Conclusions Clinical manifestations and ideal treatment of crotaline snakebite differ greatly, and can result in severe complications. Using a modified Delphi method, we provide evidence-informed treatment guidelines in an attempt to reduce variation in care and possibly improve clinical outcomes. PMID:21291549
Mutual Group Hypnosis: A Social Interaction Analysis.
ERIC Educational Resources Information Center
Sanders, Shirley
Mutual Group Hypnosis is discussed in terms of its similarity to group dynamics in general and in terms of its similarity to a social interaction program (Role Modeling) designed to foster the expression of warmth and acceptance among group members. Hypnosis also fosters a regression to prelogical thought processes in the service of the ego. Group…
Mutually unbiased bases and generalized Bell states
Klimov, Andrei B.; Sych, Denis; Sanchez-Soto, Luis L.; Leuchs, Gerd
2009-05-15
We employ a straightforward relation between mutually unbiased and Bell bases to extend the latter in terms of a direct construction for the former. We analyze in detail the properties of these generalized Bell states, showing that they constitute an appropriate tool for testing entanglement in bipartite multiqudit systems.
Do Mutual Children Cement Bonds in Stepfamilies?
ERIC Educational Resources Information Center
Ganong, Lawrence H.; Coleman, Marilyn
1988-01-01
Interviewed 105 midwestern stepfamilies, 39 of whom had reproduced together. Found no significant differences between families with mutual children and those without in terms of marital adjustment, stepparent- and parent-child relationships, and stepfamily affect. It was not possible to predict which families were most likely to reproduce together…
Mutual diffusion of interacting membrane proteins.
Abney, J R; Scalettar, B A; Owicki, J C
1989-01-01
The generalized Stokes-Einstein equation is used, together with the two-dimensional pressure equation, to analyze mutual diffusion in concentrated membrane systems. These equations can be used to investigate the role that both direct and hydrodynamic interactions play in determining diffusive behavior. Here only direct interactions are explicitly incorporated into the theory at high densities; however, both direct and hydrodynamic interactions are analyzed for some dilute solutions. We look at diffusion in the presence of weak attractions, soft repulsions, and hard-core repulsions. It is found that, at low densities, attractions retard mutual diffusion while repulsions enhance it. Mechanistically, attractions tend to tether particles together and oppose the dissipation of gradients or fluctuations in concentration, while repulsions provide a driving force that pushes particles apart. At higher concentrations, changes in the structure of the fluid enhance mutual diffusion even in the presence of attractions. It is shown that the theoretical description of postelectrophoresis relaxation and fluorescence correlation spectroscopy experiments must be modified if interacting systems are studied. The effects of interactions on mutual diffusion coefficients have probably already been seen in postelectrophoresis relaxation experiments. PMID:2775829
Spencer, W.A.; Goode, S.R.
1997-10-01
ICP emission analyses are prone to errors due to changes in power level, nebulization rate, plasma temperature, and sample matrix. As a result, accurate analyses of complex samples often require frequent bracketing with matrix matched standards. Information needed to track and correct the matrix errors is contained in the emission spectrum. But most commercial software packages use only the analyte line emission to determine concentrations. Changes in plasma temperature and the nebulization rate are reflected by changes in the hydrogen line widths, the oxygen emission, and neutral ion line ratios. Argon and off-line emissions provide a measure to correct the power level and the background scattering occurring in the polychromator. The authors` studies indicated that changes in the intensity of the Ar 404.4 nm line readily flag most matrix and plasma condition modifications. Carbon lines can be used to monitor the impact of organics on the analyses and calcium and argon lines can be used to correct for spectral drift and alignment. Spectra of contaminated groundwater and simulated defense waste glasses were obtained using a Thermo Jarrell Ash ICP that has an echelle CID detector system covering the 190-850 nm range. The echelle images were translated to the FITS data format, which astronomers recommend for data storage. Data reduction packages such as those in the ESO-MIDAS/ECHELLE and DAOPHOT programs were tried with limited success. The radial point spread function was evaluated as a possible improved peak intensity measurement instead of the common pixel averaging approach used in the commercial ICP software. Several algorithms were evaluated to align and automatically scale the background and reference spectra. A new data reduction approach that utilizes standard reference images, successive subtractions, and residual analyses has been evaluated to correct for matrix effects.
12 CFR 12.101 - National bank disclosure of remuneration for mutual fund transactions.
Code of Federal Regulations, 2010 CFR
2010-01-01
... OF THE TREASURY RECORDKEEPING AND CONFIRMATION REQUIREMENTS FOR SECURITIES TRANSACTIONS... may fulfill its obligation to disclose information on the source and amount of remuneration, required by § 12.4, for mutual fund transactions by providing this information to the customer in a...
Mutuality and solidarity: assessing risks and sharing losses.
Wilkie, D
1997-08-29
Mutuality is the principle of private, commercial insurance; individuals enter the pool for sharing losses, and pay according to the best estimate of the risk they bring with them. Solidarity is the sharing of losses with payment according to some other scheme; this is the principle of state social insurance; essential features of solidarity are comprehensiveness and compulsion. Private insurance is subject to the uberrima fides principle, or utmost good faith; each side declares all it knows about the risk. The Disability Discrimination Act requires insurers to justify disability discrimination on the basis of relevant information, acturial, statistical or medical, on which it is reasonable to rely. It could be very damaging to private insurance to abandon uberrima fides. However, although some genetic information is clearly useful to underwriters, other information may be so general as to be of little use. The way in which mortality rates are assessed is also explained.
Tsanas, Athanasios; Zañartu, Matías; Little, Max A; Fox, Cynthia; Ramig, Lorraine O; Clifford, Gari D
2014-05-01
There has been consistent interest among speech signal processing researchers in the accurate estimation of the fundamental frequency (F(0)) of speech signals. This study examines ten F(0) estimation algorithms (some well-established and some proposed more recently) to determine which of these algorithms is, on average, better able to estimate F(0) in the sustained vowel /a/. Moreover, a robust method for adaptively weighting the estimates of individual F(0) estimation algorithms based on quality and performance measures is proposed, using an adaptive Kalman filter (KF) framework. The accuracy of the algorithms is validated using (a) a database of 117 synthetic realistic phonations obtained using a sophisticated physiological model of speech production and (b) a database of 65 recordings of human phonations where the glottal cycles are calculated from electroglottograph signals. On average, the sawtooth waveform inspired pitch estimator and the nearly defect-free algorithms provided the best individual F(0) estimates, and the proposed KF approach resulted in a ∼16% improvement in accuracy over the best single F(0) estimation algorithm. These findings may be useful in speech signal processing applications where sustained vowels are used to assess vocal quality, when very accurate F(0) estimation is required.
Tsanas, Athanasios; Zañartu, Matías; Little, Max A.; Fox, Cynthia; Ramig, Lorraine O.; Clifford, Gari D.
2014-01-01
There has been consistent interest among speech signal processing researchers in the accurate estimation of the fundamental frequency (F0) of speech signals. This study examines ten F0 estimation algorithms (some well-established and some proposed more recently) to determine which of these algorithms is, on average, better able to estimate F0 in the sustained vowel /a/. Moreover, a robust method for adaptively weighting the estimates of individual F0 estimation algorithms based on quality and performance measures is proposed, using an adaptive Kalman filter (KF) framework. The accuracy of the algorithms is validated using (a) a database of 117 synthetic realistic phonations obtained using a sophisticated physiological model of speech production and (b) a database of 65 recordings of human phonations where the glottal cycles are calculated from electroglottograph signals. On average, the sawtooth waveform inspired pitch estimator and the nearly defect-free algorithms provided the best individual F0 estimates, and the proposed KF approach resulted in a ∼16% improvement in accuracy over the best single F0 estimation algorithm. These findings may be useful in speech signal processing applications where sustained vowels are used to assess vocal quality, when very accurate F0 estimation is required. PMID:24815269
Plant invasions--the role of mutualisms.
Richardson, D M; Allsopp, N; D'Antonio, C M; Milton, S J; Rejmánek, M
2000-02-01
Many introduced plant species rely on mutualisms in their new habitats to overcome barriers to establishment and to become naturalized and, in some cases, invasive. Mutualisms involving animal-mediated pollination and seed dispersal, and symbioses between plant roots and microbiota often facilitate invasions. The spread of many alien plants, particularly woody ones, depends on pollinator mutualisms. Most alien plants are well served by generalist pollinators (insects and birds), and pollinator limitation does not appear to be a major barrier for the spread of introduced plants (special conditions relating to Ficus and orchids are described). Seeds of many of the most notorious plant invaders are dispersed by animals, mainly birds and mammals. Our review supports the view that tightly coevolved, plant-vertebrate seed dispersal systems are extremely rare. Vertebrate-dispersed plants are generally not limited reproductively by the lack of dispersers. Most mycorrhizal plants form associations with arbuscular mycorrhizal fungi which, because of their low specificity, do not seem to play a major role in facilitating or hindering plant invasions (except possibly on remote islands such as the Galapagos which are poor in arbuscular mycorrhizal fungi). The lack of symbionts has, however, been a major barrier for many ectomycorrhizal plants, notably for Pinus spp. in parts of the southern hemisphere. The roles of nitrogen-fixing associations between legumes and rhizobia and between actinorhizal plants and Frankia spp. in promoting or hindering invasions have been virtually ignored in the invasions literature. Symbionts required to induce nitrogen fixation in many plants are extremely widespread, but intentional introductions of symbionts have altered the invasibility of many, if not most, systems. Some of the world's worst invasive alien species only invaded after the introduction of symbionts. Mutualisms in the new environment sometimes re-unite the same species that form
Hardware device binding and mutual authentication
Hamlet, Jason R; Pierson, Lyndon G
2014-03-04
Detection and deterrence of device tampering and subversion by substitution may be achieved by including a cryptographic unit within a computing device for binding multiple hardware devices and mutually authenticating the devices. The cryptographic unit includes a physically unclonable function ("PUF") circuit disposed in or on the hardware device, which generates a binding PUF value. The cryptographic unit uses the binding PUF value during an enrollment phase and subsequent authentication phases. During a subsequent authentication phase, the cryptographic unit uses the binding PUF values of the multiple hardware devices to generate a challenge to send to the other device, and to verify a challenge received from the other device to mutually authenticate the hardware devices.
Mutual synchronization of weakly coupled gyrotrons
Rozental, R. M.; Glyavin, M. Yu.; Sergeev, A. S.; Zotova, I. V.; Ginzburg, N. S.
2015-09-15
The processes of synchronization of two weakly coupled gyrotrons are studied within the framework of non-stationary equations with non-fixed longitudinal field structure. With the allowance for a small difference of the free oscillation frequencies of the gyrotrons, we found a certain range of parameters where mutual synchronization is possible while a high electronic efficiency is remained. It is also shown that synchronization regimes can be realized even under random fluctuations of the parameters of the electron beams.
Three-Ship Mutual Interference Tests
1965-11-16
increase beyond this event; the data before Event 500 do not show these effects. Short duration transmit-receive misalignment as observed aboard GARCIA , is...on BELKNAP and GARCIA have not been noted on McCLOY. ii 10 CONFIDENTIAL CONFIDENTIAL TRACOR, jNC - , S, Aig? Te~oS 3. CORRECTED SEA TEST LOG Complete...frequency band causing mutual influence. In this example, chart #1 shows BELKNAP and GARCIA influencing McCLOY at a higher frequency band. Sanborn
Combating isolation: Building mutual mentoring networks
NASA Astrophysics Data System (ADS)
Cox, Anne J.
2015-12-01
Women physicists can often feel isolated at work. Support from a grant through the ADVANCE program of the National Science Foundation (U.S. government funding) created mutual mentoring networks aimed at combating isolation specifically for women faculty at undergraduate-only institutions. This paper will discuss the organization of one such network, what contributed to its success, some of the outcomes, and how it might be implemented in other contexts.
47 CFR 90.165 - Procedures for mutually exclusive applications.
Code of Federal Regulations, 2010 CFR
2010-10-01
... SPECIAL RADIO SERVICES PRIVATE LAND MOBILE RADIO SERVICES Applications and Authorizations Special Rules Governing Facilities Used to Provide Commercial Mobile Radio Services § 90.165 Procedures for mutually exclusive applications. Mutually exclusive commercial mobile radio service applications are processed...
Observations of Pluto-Charon mutual events
Blanco, C.; Di Martino, M.; Ferreri, W.; Osservatorio Astronomico, Turin )
1989-07-01
As part of the planned 'Pluto-Charon Mutual Eclipse Season Campaign', one mutual event was observed at the ESO Observatory on July 10, 1986 and seven mutual events were observed at the Serra La Nave stellar station of Catania Astrophysical Observatory from April 29 to July 21, 1987. At ESO the measurements were performed at the 61-cm Bochum telescope equipped with a photon-counting system and U, B, V, filters; at Serra La Nave the Cassegrain focus of the 91-cm reflector was equipped with a photon-counting system and B and V filters. The observed light losses and contact times do not show relevant systematic deviations from the predicted ones. An examination of the behavior of the B and V light curves gives slight indications of a different slope of the B and V light loss of the same event for a superior or an inferior event, and shows that the superior events are shallower at wavelengths longer than B. 6 refs.
[Research on the application of pattern selection algorithm based on bioinformatic data].
Li, Xin; Zhao, Chun; Wang, Huihui; Zhao, Fangfang
2011-10-01
Pattern selection plays an important role in data mining and pattern recognition, especially for large scale bioinformatic data. There are many problems in this field, such as algorithm complexity and numbers of the best feature subset. In this paper, we propose a new pattern selection algorithm, carrying out pattern selection base on Mutual Information (MI). Pattern subset evaluation index was studied to ensure the best feature subset. To pattern selection, algorithm bases on the correlation of patterns and label, as well as the redundancy of each pattern. Neurofuzzy Pattern Subset Evaluation Index was researched to make sure which is the best subset for our pattern subset evaluation. To verify the effectiveness of our method, several experiments are carried out on the data of gene expression of mouse from Leiden University and UCI datasets. The experimental results indicated that our algorithm achieved better results in the complexity and accuracy.
NASA Technical Reports Server (NTRS)
Dasarathy, B. V.
1976-01-01
An algorithm is proposed for dimensionality reduction in the context of clustering techniques based on histogram analysis. The approach is based on an evaluation of the hills and valleys in the unidimensional histograms along the different features and provides an economical means of assessing the significance of the features in a nonparametric unsupervised data environment. The method has relevance to remote sensing applications.
Mutual information, perceptual independence, and holistic face perception.
Fitousi, Daniel
2013-07-01
The concept of perceptual independence is ubiquitous in psychology. It addresses the question of whether two (or more) dimensions are perceived independently. Several authors have proposed perceptual independence (or its lack thereof) as a viable measure of holistic face perception (Loftus, Oberg, & Dillon, Psychological Review 111:835-863, 2004; Wenger & Ingvalson, Learning, Memory, and Cognition 28:872-892, 2002). According to this notion, the processing of facial features occurs in an interactive manner. Here, I examine this idea from the perspective of two theories of perceptual independence: the multivariate uncertainty analysis (MUA; Garner & Morton, Definitions, models, and experimental paradigms. Psychological Bulletin 72:233-259, 1969), and the general recognition theory (GRT; Ashby & Townsend, Psychological Review 93:154-179, 1986). The goals of the study were to (1) introduce the MUA, (2) examine various possible relations between MUA and GRT using numerical simulations, and (3) apply the MUA to two consensual markers of holistic face perception(-)recognition of facial features (Farah, Wilson, Drain, & Tanaka, Psychological Review 105:482-498, 1998) and the composite face effect (Young, Hellawell, & Hay, Perception 16:747-759, 1987). The results suggest that facial holism is generated by violations of several types of perceptual independence. They highlight the important theoretical role played by converging operations in the study of holistic face perception.
Integration of Particle-gas Systems with Stiff Mutual Drag Interaction
NASA Astrophysics Data System (ADS)
Yang, Chao-Chin; Johansen, Anders
2016-06-01
Numerical simulation of numerous mm/cm-sized particles embedded in a gaseous disk has become an important tool in the study of planet formation and in understanding the dust distribution in observed protoplanetary disks. However, the mutual drag force between the gas and the particles can become so stiff—particularly because of small particles and/or strong local solid concentration—that an explicit integration of this system is computationally formidable. In this work, we consider the integration of the mutual drag force in a system of Eulerian gas and Lagrangian solid particles. Despite the entanglement between the gas and the particles under the particle-mesh construct, we are able to devise a numerical algorithm that effectively decomposes the globally coupled system of equations for the mutual drag force, and makes it possible to integrate this system on a cell-by-cell basis, which considerably reduces the computational task required. We use an analytical solution for the temporal evolution of each cell to relieve the time-step constraint posed by the mutual drag force, as well as to achieve the highest degree of accuracy. To validate our algorithm, we use an extensive suite of benchmarks with known solutions in one, two, and three dimensions, including the linear growth and the nonlinear saturation of the streaming instability. We demonstrate numerical convergence and satisfactory consistency in all cases. Our algorithm can, for example, be applied to model the evolution of the streaming instability with mm/cm-sized pebbles at high mass loading, which has important consequences for the formation scenarios of planetesimals.
Identity theory and personality theory: mutual relevance.
Stryker, Sheldon
2007-12-01
Some personality psychologists have found a structural symbolic interactionist frame and identity theory relevant to their work. This frame and theory, developed in sociology, are first reviewed. Emphasized in the review are a multiple identity conception of self, identities as internalized expectations derived from roles embedded in organized networks of social interaction, and a view of social structures as facilitators in bringing people into networks or constraints in keeping them out, subsequently, attention turns to a discussion of the mutual relevance of structural symbolic interactionism/identity theory and personality theory, looking to extensions of the current literature on these topics.
Creating a culture of mutual respect.
Kaplan, Kathryn; Mestel, Pamela; Feldman, David L
2010-04-01
The Joint Commission mandates that hospitals seeking accreditation have a process to define and address disruptive behavior. Leaders at Maimonides Medical Center, Brooklyn, New York, took the initiative to create a code of mutual respect that not only requires respectful behavior, but also encourages sensitivity and awareness to the causes of frustration that often lead to inappropriate behavior. Steps to implementing the code included selecting code advocates, setting up a system for mediating disputes, tracking and addressing operational system issues, providing training for personnel, developing a formal accountability process, and measuring the results.
NASA Astrophysics Data System (ADS)
Tezuka, Miwa; Kanno, Kazutaka; Bunsen, Masatoshi
2016-08-01
Reservoir computing is a machine-learning paradigm based on information processing in the human brain. We numerically demonstrate reservoir computing with a slowly modulated mask signal for preprocessing by using a mutually coupled optoelectronic system. The performance of our system is quantitatively evaluated by a chaotic time series prediction task. Our system can produce comparable performance with reservoir computing with a single feedback system and a fast modulated mask signal. We showed that it is possible to slow down the modulation speed of the mask signal by using the mutually coupled system in reservoir computing.
Herbivores alter the fitness benefits of a plant-rhizobium mutualism
NASA Astrophysics Data System (ADS)
Heath, Katy D.; Lau, Jennifer A.
2011-03-01
Mutualisms are best understood from a community perspective, since third-party species have the potential to shift the costs and benefits in interspecific interactions. We manipulated plant genotypes, the presence of rhizobium mutualists, and the presence of a generalist herbivore and assessed the performance of all players in order to test whether antagonists might alter the fitness benefits of plant-rhizobium mutualism, and vice versa how mutualists might alter the fitness consequences of plant-herbivore antagonism. We found that plants in our experiment formed more associations with rhizobia (root nodules) in the presence of herbivores, thereby increasing the fitness benefits of mutualism for rhizobia. In contrast, the effects of rhizobia on herbivores were weak. Our data support a community-dependent view of these ecological interactions, and suggest that consideration of the aboveground herbivore community can inform ecological and evolutionary studies of legume-rhizobium interactions.
NASA Astrophysics Data System (ADS)
Snyder
1998-04-01
It has been shown by Einstein, Podolsky, and Rosen that in quantum mechanics two different wave functions can simultaneously characterize the same physical existent. This result means that one can make predictions regarding simultaneous, mutually exclusive features of a physical existent. It is important to ask whether people have the capacity to make observations of mutually exclusive phenomena simultaneously? Our everyday experience informs us that a human observer is capable of observing only one set of physical circumstances at a time. Evidence from psychology, though, indicates that people indeed have the capacity to make observations of mutually exclusive phenomena simultaneously, even though this capacity is not generally recognized. Working independently, Sigmund Freud and William James provided some of this evidence. How the nature of the quantum mechanical wave function is associated with the problem posed by Einstein, Podolsky, and Rosen, is addressed at the end of the paper.
Han, Fang; Wang, Zhijie; Fan, Hong
2017-01-01
This paper proposed a new method to determine the neuronal tuning curves for maximum information efficiency by computing the optimum firing rate distribution. Firstly, we proposed a general definition for the information efficiency, which is relevant to mutual information and neuronal energy consumption. The energy consumption is composed of two parts: neuronal basic energy consumption and neuronal spike emission energy consumption. A parameter to model the relative importance of energy consumption is introduced in the definition of the information efficiency. Then, we designed a combination of exponential functions to describe the optimum firing rate distribution based on the analysis of the dependency of the mutual information and the energy consumption on the shape of the functions of the firing rate distributions. Furthermore, we developed a rapid algorithm to search the parameter values of the optimum firing rate distribution function. Finally, we found with the rapid algorithm that a combination of two different exponential functions with two free parameters can describe the optimum firing rate distribution accurately. We also found that if the energy consumption is relatively unimportant (important) compared to the mutual information or the neuronal basic energy consumption is relatively large (small), the curve of the optimum firing rate distribution will be relatively flat (steep), and the corresponding optimum tuning curve exhibits a form of sigmoid if the stimuli distribution is normal. PMID:28270760
Han, Fang; Wang, Zhijie; Fan, Hong
2017-01-01
This paper proposed a new method to determine the neuronal tuning curves for maximum information efficiency by computing the optimum firing rate distribution. Firstly, we proposed a general definition for the information efficiency, which is relevant to mutual information and neuronal energy consumption. The energy consumption is composed of two parts: neuronal basic energy consumption and neuronal spike emission energy consumption. A parameter to model the relative importance of energy consumption is introduced in the definition of the information efficiency. Then, we designed a combination of exponential functions to describe the optimum firing rate distribution based on the analysis of the dependency of the mutual information and the energy consumption on the shape of the functions of the firing rate distributions. Furthermore, we developed a rapid algorithm to search the parameter values of the optimum firing rate distribution function. Finally, we found with the rapid algorithm that a combination of two different exponential functions with two free parameters can describe the optimum firing rate distribution accurately. We also found that if the energy consumption is relatively unimportant (important) compared to the mutual information or the neuronal basic energy consumption is relatively large (small), the curve of the optimum firing rate distribution will be relatively flat (steep), and the corresponding optimum tuning curve exhibits a form of sigmoid if the stimuli distribution is normal.
Galois-unitary operators that cycle mutually-unbiased bases
NASA Astrophysics Data System (ADS)
Dang, Hoan; Appleby, Marcus; Bengtsson, Ingemar
2015-03-01
Wigner's theorem states that probability-preserving transformations of quantum states must be either unitary or anti-unitary. However, if we restrict ourselves to a subspace of a Hilbert space, it is possible to generalize the notion of anti-unitaries. Such transformations were recently constructed in search of Symmetric Informationally-Complete (SIC) states. They are called Galois-unitaries (g-unitaries for short), as they are unitaries composed with Galois automorphisms of a chosen number field extension. Despite certain bizarre behaviors of theirs, we show that g-unitaries are indeed useful in the theory of Mutually-Unbiased Bases (MUBs), as they help solve the MUB-cycling problem and provide a construction of MUB-balanced states. HD was supported by the Natural Sciences and Engineering Research Council of Canada and the Vanier Canada Graduate Scholarship
1982-09-01
MARKETING * by A. Charnes W. W. Cooper *D. B. Learner*F. Y. Phillips* CENTER FOR CYBEI! NTIC STU[)IES The Universityof Texas Austin,Texas 78712 CM a a I 0...34,.. u.. 29 061. L1..<i’ I Research Report CCS 397 AN MDI MODEL AND AN ALGORITHM FOR COMPOSITE HYPOTHESES TESTING AND ESTIMATION IN MARKETING * by A...Charn~s W. V. Cooper D. E. Lea-nir* .. F. ".Philli,.)s* --. Original: July 1981 Revispd: September.1981.Second Revision: Septembr 1982 0, 0 gt’, * Market
2003-04-01
Science, volume 888, 1995, ISSN 0302-9743. [127] Giancoli , Douglas C. General Physics , Prentice Hall, INC, Englewood Cliffs, NJ. [128]Harmon, S. “A...59 3.4 Vulnerability Metrics with physical analogs...theoretical physics for information flow analysis on network and for extraction of patterns of typical network behav- ior. The information traffic can
ERIC Educational Resources Information Center
Rastogi, Ravi; Pawluk, Dianne T. V.
2013-01-01
An increasing amount of information content used in school, work, and everyday living is presented in graphical form. Unfortunately, it is difficult for people who are blind or visually impaired to access this information, especially when many diagrams are needed. One problem is that details, even in relatively simple visual diagrams, can be very…
Abduallah, Yasser; Byron, Kevin; Du, Zongxuan; Cervantes-Cervantes, Miguel
2017-01-01
Gene regulation is a series of processes that control gene expression and its extent. The connections among genes and their regulatory molecules, usually transcription factors, and a descriptive model of such connections are known as gene regulatory networks (GRNs). Elucidating GRNs is crucial to understand the inner workings of the cell and the complexity of gene interactions. To date, numerous algorithms have been developed to infer gene regulatory networks. However, as the number of identified genes increases and the complexity of their interactions is uncovered, networks and their regulatory mechanisms become cumbersome to test. Furthermore, prodding through experimental results requires an enormous amount of computation, resulting in slow data processing. Therefore, new approaches are needed to expeditiously analyze copious amounts of experimental data resulting from cellular GRNs. To meet this need, cloud computing is promising as reported in the literature. Here, we propose new MapReduce algorithms for inferring gene regulatory networks on a Hadoop cluster in a cloud environment. These algorithms employ an information-theoretic approach to infer GRNs using time-series microarray data. Experimental results show that our MapReduce program is much faster than an existing tool while achieving slightly better prediction accuracy than the existing tool. PMID:28243601
Abduallah, Yasser; Turki, Turki; Byron, Kevin; Du, Zongxuan; Cervantes-Cervantes, Miguel; Wang, Jason T L
2017-01-01
Gene regulation is a series of processes that control gene expression and its extent. The connections among genes and their regulatory molecules, usually transcription factors, and a descriptive model of such connections are known as gene regulatory networks (GRNs). Elucidating GRNs is crucial to understand the inner workings of the cell and the complexity of gene interactions. To date, numerous algorithms have been developed to infer gene regulatory networks. However, as the number of identified genes increases and the complexity of their interactions is uncovered, networks and their regulatory mechanisms become cumbersome to test. Furthermore, prodding through experimental results requires an enormous amount of computation, resulting in slow data processing. Therefore, new approaches are needed to expeditiously analyze copious amounts of experimental data resulting from cellular GRNs. To meet this need, cloud computing is promising as reported in the literature. Here, we propose new MapReduce algorithms for inferring gene regulatory networks on a Hadoop cluster in a cloud environment. These algorithms employ an information-theoretic approach to infer GRNs using time-series microarray data. Experimental results show that our MapReduce program is much faster than an existing tool while achieving slightly better prediction accuracy than the existing tool.
Supporting Mutual Understanding in a Visual Dialogue Between Analyst and Computer
Chappell, Alan R.; Cowell, Andrew J.; Thurman, David A.; Thomson, Judi R.
2004-09-20
The Knowledge Associates for Novel Intelligence (KANI) project is developing a system of automated “associates” to actively support and participate in the information analysis task. The primary goal of KANI is to use automatically extracted information in a reasoning system that draws on the strengths of both a human analyst and automated reasoning. The interface between the two agents is a key element in achieving this goal. The KANI interface seeks to support a visual dialogue with mixed-initiative manipulation of information and reasoning components. To be successful, the interface must achieve mutual understanding between the analyst and KANI of the other’s actions. Toward this mutual understanding, KANI allows the analyst to work at multiple levels of abstraction over the reasoning process, links the information presented across these levels to make use of interaction context, and provides querying facilities to allow exploration and explanation.
2D/3D registration algorithm for lung brachytherapy
Zvonarev, P. S.; Farrell, T. J.; Hunter, R.; Wierzbicki, M.; Hayward, J. E.; Sur, R. K.
2013-02-15
Purpose: A 2D/3D registration algorithm is proposed for registering orthogonal x-ray images with a diagnostic CT volume for high dose rate (HDR) lung brachytherapy. Methods: The algorithm utilizes a rigid registration model based on a pixel/voxel intensity matching approach. To achieve accurate registration, a robust similarity measure combining normalized mutual information, image gradient, and intensity difference was developed. The algorithm was validated using a simple body and anthropomorphic phantoms. Transfer catheters were placed inside the phantoms to simulate the unique image features observed during treatment. The algorithm sensitivity to various degrees of initial misregistration and to the presence of foreign objects, such as ECG leads, was evaluated. Results: The mean registration error was 2.2 and 1.9 mm for the simple body and anthropomorphic phantoms, respectively. The error was comparable to the interoperator catheter digitization error of 1.6 mm. Preliminary analysis of data acquired from four patients indicated a mean registration error of 4.2 mm. Conclusions: Results obtained using the proposed algorithm are clinically acceptable especially considering the complications normally encountered when imaging during lung HDR brachytherapy.
Mutual potential between two rigid bodies with arbitrary shapes and mass distributions
NASA Astrophysics Data System (ADS)
Hou, Xiyun; Scheeres, Daniel J.; Xin, Xiaosheng
2016-09-01
Formulae to compute the mutual potential, force, and torque between two rigid bodies are given. These formulae are expressed in Cartesian coordinates using inertia integrals. They are valid for rigid bodies with arbitrary shapes and mass distributions. By using recursive relations, these formulae can be easily implemented on computers. Comparisons with previous studies show their superiority in computation speed. Using the algorithm as a tool, the planar problem of two ellipsoids is studied. Generally, potential truncated at the second order is good enough for a qualitative description of the mutual dynamics. However, for ellipsoids with very large non-spherical terms, higher order terms of the potential should be considered, at the cost of a higher computational cost. Explicit formulae of the potential truncated to the fourth order are given.
Mutual potential between two rigid bodies with arbitrary shapes and mass distributions
NASA Astrophysics Data System (ADS)
Hou, Xiyun; Scheeres, Daniel J.; Xin, Xiaosheng
2017-03-01
Formulae to compute the mutual potential, force, and torque between two rigid bodies are given. These formulae are expressed in Cartesian coordinates using inertia integrals. They are valid for rigid bodies with arbitrary shapes and mass distributions. By using recursive relations, these formulae can be easily implemented on computers. Comparisons with previous studies show their superiority in computation speed. Using the algorithm as a tool, the planar problem of two ellipsoids is studied. Generally, potential truncated at the second order is good enough for a qualitative description of the mutual dynamics. However, for ellipsoids with very large non-spherical terms, higher order terms of the potential should be considered, at the cost of a higher computational cost. Explicit formulae of the potential truncated to the fourth order are given.
Graphical Calculi and Mutually Unbiassed Embeddings of Classical Logic
NASA Astrophysics Data System (ADS)
Duncan, Ross
2008-03-01
While arbitrary quantum states may not be freely cloned or deleted [1], we note, following [2], that these distinctively classical operations may be performed on states which lie within a given basis. Each basis therefore provides an embedding of classical logic into a quantum state space. This work provides a categorical axiomatisation (cf [3]) of the interaction of such embeddings when distinct mutually unbiassed bases [4] are used. We provide a graphical language (cf. [5]) for the classical operations that each embedding provides, and demonstrate that this system captures many properties of multi-partite entangled states and can simulate quantum algorithms. [1] W. Wootters and W. Zurek. A single quantum cannot be cloned, 1982. A.K. Pati and S. L. Braunstein. Impossibility of deleting an unknown quantum state, 2000. [2] B. Coecke and D. Pavlovic (2007) Quantum measurements without sums. arXiv:quant-ph/0608035. [3] S. Abramsky and B. Coecke (2004) A categorical semantics of quantum protocols. arXiv:quant-ph/0402130. [4] J. Schwinger (1960) Unitary operator bases. Proceedings of the National Academy of Sciences of the U.S.A. 46 [5] B. Coecke (2005) Kindergarten quantum mechanics. arXiv:quant-ph/0510032
Concurrent behavior: Are the interpretations mutually exclusive?
Lyon, David O.
1982-01-01
The experimental literature is replete with examples of behavior which occur concurrently with a schedule of reinforcement. These concurrent behaviors, often with similar topographies and occurring under like circumstances, may be interpreted as functionally autonomous, collateral, adjunctive, superstitious or mediating behavior. The degree to which the interaction of concurrent and schedule controlled behavior is used in the interpretation of behavior illustrated the importance of distinguishing among these interpretations by experimental procedure. The present paper reviews the characteristics of these interpretations, and discusses the experimental procedures necessary to distinguish among them. The paper concludes that the interpretations are mutually exclusive and refer to distinct behaviors, but that the distinction between any two of the interpretations requires more than one experimental procedure. PMID:22478568
Propagating Resource Constraints Using Mutual Exclusion Reasoning
NASA Technical Reports Server (NTRS)
Frank, Jeremy; Sanchez, Romeo; Do, Minh B.; Clancy, Daniel (Technical Monitor)
2001-01-01
One of the most recent techniques for propagating resource constraints in Constraint Based scheduling is Energy Constraint. This technique focuses in precedence based scheduling, where precedence relations are taken into account rather than the absolute position of activities. Although, this particular technique proved to be efficient on discrete unary resources, it provides only loose bounds for jobs using discrete multi-capacity resources. In this paper we show how mutual exclusion reasoning can be used to propagate time bounds for activities using discrete resources. We show that our technique based on critical path analysis and mutex reasoning is just as effective on unary resources, and also shows that it is more effective on multi-capacity resources, through both examples and empirical study.
NASA Astrophysics Data System (ADS)
Rover, J.; Goldhaber, M. B.; Holen, C.; Dittmeier, R.; Wika, S.; Steinwand, D.; Dahal, D.; Tolk, B.; Quenzer, R.; Nelson, K.; Wylie, B. K.; Coan, M.
2015-12-01
Multi-year land cover mapping from remotely sensed data poses challenges. Producing land cover products at spatial and temporal scales required for assessing longer-term trends in land cover change are typically a resource-limited process. A recently developed approach utilizes open source software libraries to automatically generate datasets, decision tree classifications, and data products while requiring minimal user interaction. Users are only required to supply coordinates for an area of interest, land cover from an existing source such as National Land Cover Database and percent slope from a digital terrain model for the same area of interest, two target acquisition year-day windows, and the years of interest between 1984 and present. The algorithm queries the Landsat archive for Landsat data intersecting the area and dates of interest. Cloud-free pixels meeting the user's criteria are mosaicked to create composite images for training the classifiers and applying the classifiers. Stratification of training data is determined by the user and redefined during an iterative process of reviewing classifiers and resulting predictions. The algorithm outputs include yearly land cover raster format data, graphics, and supporting databases for further analysis. Additional analytical tools are also incorporated into the automated land cover system and enable statistical analysis after data are generated. Applications tested include the impact of land cover change and water permanence. For example, land cover conversions in areas where shrubland and grassland were replaced by shale oil pads during hydrofracking of the Bakken Formation were quantified. Analytical analysis of spatial and temporal changes in surface water included identifying wetlands in the Prairie Pothole Region of North Dakota with potential connectivity to ground water, indicating subsurface permeability and geochemistry.
On the Mutual Coupling Between Circular Resonant Slots
NASA Technical Reports Server (NTRS)
Abou-Khousa, M. A.; Kharkovsky, S.; Zoughi, R.
2007-01-01
For near- and far-field microwave imaging purposes, array of circular resonant slots can be utilized to sample the electric field at a given reference plane. In general, the sensitivity of such array probes is impaired by the mutual coupling present between the radiating elements. The mutual coupling problem poses a design tradeoff between the resolution of the array and its sensitivity. In this paper, we investigate the mutual coupling between circular resonant slots in conducting ground plane both numerically and experimentally. Based on the analysis of the dominant coupling mechanism, i.e., the surface currents, various remedies to reduce the slots' mutual coupling are proposed and verified.
On the Mutual Coupling between Circular Resonant Slots
NASA Technical Reports Server (NTRS)
Abou-Khousa, M. A.; Kharkovshy, S.; Zoughi, R.
2007-01-01
For near- and far-field microwave imaging purposes, array of circular resonant slots can be utilized to sample the electric field at a given reference plane. In general, the sensitivity of such an array is impaired by the existing mutual coupling between the radiating elements or in this case circular slots. The mutual coupling problem imposes a design tradeoff between the resolution of the array and the overall system sensitivity and dynamic range. In this paper, the mutual coupling between circular resonant slots in conducting ground plane is investigated both numerically and experimentally. In particular, the mutual coupling in the E- and H-plane configurations of two identical slots is studied.
Mutual Events in the Uranian satellite system in 2007
NASA Astrophysics Data System (ADS)
Arlot, J. E.
2008-09-01
The equinox time on the giant planets When the Sun crosses the equatorial plane of a giant planet, it is the equinox time occurring every half orbit of the planet, i.e. every 6 years for Jupiter, 14 years for Saturn, 42 years for Uranus and 82 years for Neptune. Except Neptune, each planet have several major satellites orbiting in the equatorial plane, then, during the equinox time, the satellites will eclipse each other mutually. Since the Earth follows the Sun, during the equinox time, a terrestrial observer will see each satellite occulting each other during the same period. These events may be observed with photometric receivers since the light from the satellites will decrease during the events. The light curve will provide information on the geometric configuration of the the satellites at the time of the event with an accuracy of a few kilometers, not depending on the distance of the satellite system. Then, we are able to get an astrometric observation with an accuracy several times better than using direct imaging for positions. Equinox on Uranus in 2007 In 2007, it was equinox time on Uranus. The Sun crossed the equatorial plane of Uranus on December 6, 2007. Since the opposition Uranus-Sun was at the end of August 2007, observations were performed from May to December 2007. Since the declination of Uranus was between -5 and -6 degrees, observations were better to make in the southern hemisphere. However, some difficulties had to be solved: the faintness of the satellites (magnitude between 14 and 16), the brightness of the planet (magnitude 5) making difficult the photometric observation of the satellites. The used of K' filter associated to a large telescope allows to increase the number of observable events. Dynamics of the Uranian satellites One of the goals of the observations was to evaluate the accuracy of the current dynamical models of the motion of the satellites. This knowledge is important for several reasons: most of time the Uranian system is
Kim, Wangdo; Espanha, Margarida M; Veloso, António P; Araújo, Duarte; João, Filipa; Carrão, Luis; Kohles, Sean S
2013-03-27
Traditional locomotion studies emphasize an optimization of the desired movement trajectories while ignoring sensory feedback. We propose an information based theory that locomotion is neither triggered nor commanded but controlled. The basis for this control is the information derived from perceiving oneself in the world. Control therefore lies in the human-environment system. In order to test this hypothesis, we derived a mathematical foundation characterizing the energy that is required to perform a rotational twist, with small amplitude, of the instantaneous axes of the knee (IAK). We have found that the joint's perception of the ground reaction force may be replaced by the co-perception of muscle activation with appropriate intensities. This approach generated an accurate comparison with known joint forces and appears appropriate in so far as predicting the effect on the knee when it is free to twist about the IAK.
Mutual Orbits, Size, Density, and Interior of Visualized Multiple Asteroids
NASA Astrophysics Data System (ADS)
Marchis, F.; Vachier, F.; Durech, J.; Berthier, J.; Hanus, J.
2012-12-01
Since 2001 our team collected Adaptive Optics Observations of high-size ratio multiple asteroids (e.g. 22 Kalliope, 130 Elektra, 624 Hektor) and large similarly-sized binary asteroids (90 Antiope, 617 Patroclus) using 8-10m class telescopes such as Gemini North, VLT-UT4, and W.M. Keck II telescopes and archive data from HST. Using a new genetic-based algorithm, named GENOID (Vachier et al. 2012), we derived the orbital parameters of ~16 multiple asteroids, including 13 main-belt asteroids, 2 Jupiter-trojan asteroids and one Transneptunian asteroid. This efficient algorithm allows us to explore a wide range or orbital solutions without any a priori constrain on the system. Two types of dynamical models, one purely Keplerian and a dynamical one (which fits as well the size and J2/J4 of the primary) can be used. In the last case, we can also infer the distribution of material in the primary. The volume of these asteroids is derived by combining mid-IR observations from Spitzer/IRS, IRAS, WISE or AKARI with lightcurve inversion technique and stellar occultations. The bulk density derived for these asteroids confirmed a relationship between their taxonomic classes and their composition with an average density of ~3.5 g/cc for M-type asteroids, ~1 g/cc for C/P/D-type and ~2 g/cc for S-type. We will present an overview of our analysis emphasizing the most recent results in particular the size, shape and internal structure of (624) Hektor. We will also discuss new directions of investigations using more performant AO systems soon available on 8-10m class telescopes. More accessible multi-user campaigns to observe stellar occultation and also mutual event between the components of the systems aiming at refining the size & shape of the primary and the size of the satellite(s) will be described. GENOID algorithm provides orbital solution directly implemented in the IMCCE ephemerides allowing the predictions of these events and the position of the satellite(s).
NASA Astrophysics Data System (ADS)
Akakin, Hatice C.; Gokozan, Hamza; Otero, Jose; Gurcan, Metin N.
2015-03-01
We propose a method to detect and segment the oligodendrocytes and gliomas in OLIG2 immunoperoxidase stained tissue sections. Segmentation of cell nuclei is essential for automatic, fast, accurate and consistent analysis of pathology images. In general, glioma cells and oligodendrocytes mostly differ in shape and size within the tissue slide. In OLIG2 stained tissue images, gliomas are represented with irregularly shaped nuclei with varying sizes and brown shades. On the other hand, oligodendrocytes have more regular round nuclei shapes and are smaller in size when compared to glioma cells found in oligodendroglioma, astrocytomas, or oligoastrocytomas. The first task is to detect the OLIG2 positive cell regions within a region of interest image selected from a whole slide. The second task is to segment each cell nucleus and count the number of cell nuclei. However, the cell nuclei belonging to glioma cases have particularly irregular nuclei shapes and form cell clusters by touching or overlapping with each other. In addition to this clustered structure, the shading of the brown stain and the texture of the nuclei differ slightly within a tissue image. The final step of the algorithm is to classify glioma cells versus oligodendrocytes. Our method starts with color segmentation to detect positively stained cells followed by the classification of single individual cells and cell clusters by K-means clustering. Detected cell clusters are segmented with the H-minima based watershed algorithm. The novel aspects of our work are: 1) the detection and segmentation of multiple-type, positively-stained nuclei by incorporating only minimal prior information; and 2) adaptively determining clustering parameters to adjust to the natural variation in staining as well as the underlying cellular structure while accommodating multiple cell types in the image. Performance of the algorithm to detect individual cells is evaluated by sensitivity and precision metrics. Promising
Higher Education and Foster Grandparent Programs: Exploring Mutual Benefits
ERIC Educational Resources Information Center
Peacock, James R.; O'Quin, Jo Ann
2006-01-01
The purpose of this article is to highlight ways in which programs within institutions of higher education and Foster Grandparent Programs can interact to their mutual benefit. Given federal and state initiatives to develop linkages between institutions of higher education and community service sites, mutual benefits exist at the program level for…
76 FR 20459 - Mutual to Stock Conversion Application
Federal Register 2010, 2011, 2012, 2013, 2014
2011-04-12
... Office of Thrift Supervision Mutual to Stock Conversion Application AGENCY: Office of Thrift Supervision... collection. Title of Proposal: Mutual to Stock Conversion Application. OMB Number: 1550-0014. Form Numbers... furnished in the application in order to determine the safety and soundness of the proposed stock...
47 CFR 90.165 - Procedures for mutually exclusive applications.
Code of Federal Regulations, 2011 CFR
2011-10-01
... SPECIAL RADIO SERVICES PRIVATE LAND MOBILE RADIO SERVICES Applications and Authorizations Special Rules... exclusive applications. Mutually exclusive commercial mobile radio service applications are processed in... 47 Telecommunication 5 2011-10-01 2011-10-01 false Procedures for mutually exclusive...
47 CFR 22.131 - Procedures for mutually exclusive applications.
Code of Federal Regulations, 2010 CFR
2010-10-01
... SERVICES PUBLIC MOBILE SERVICES Licensing Requirements and Procedures Applications and Notifications § 22... procedures in this section for processing mutually exclusive applications in the Public Mobile Services... 47 Telecommunication 2 2010-10-01 2010-10-01 false Procedures for mutually exclusive...
Mutuality, Self-Silencing, and Disordered Eating in College Women
ERIC Educational Resources Information Center
Wechsler, Lisa S.; Riggs, Shelley A.; Stabb, Sally D.; Marshall, David M.
2006-01-01
The current study examined patterns of association among mutuality, self-silencing, and disordered eating in an ethnically diverse sample of college women (N = 149). Partner mutuality and overall self-silencing were negatively correlated and together were associated with six disordered eating indices. All four self-silencing subscales were…
7 CFR 550.13 - Mutuality of interest.
Code of Federal Regulations, 2010 CFR
2010-01-01
... 7 Agriculture 6 2010-01-01 2010-01-01 false Mutuality of interest. 550.13 Section 550.13 Agriculture Regulations of the Department of Agriculture (Continued) AGRICULTURAL RESEARCH SERVICE, DEPARTMENT.... Mutual interest exists when both parties benefit in the same qualitative way from the objectives of...
7 CFR 550.13 - Mutuality of interest.
Code of Federal Regulations, 2012 CFR
2012-01-01
... 7 Agriculture 6 2012-01-01 2012-01-01 false Mutuality of interest. 550.13 Section 550.13 Agriculture Regulations of the Department of Agriculture (Continued) AGRICULTURAL RESEARCH SERVICE, DEPARTMENT.... Mutual interest exists when both parties benefit in the same qualitative way from the objectives of...
7 CFR 550.13 - Mutuality of interest.
Code of Federal Regulations, 2014 CFR
2014-01-01
... 7 Agriculture 6 2014-01-01 2014-01-01 false Mutuality of interest. 550.13 Section 550.13 Agriculture Regulations of the Department of Agriculture (Continued) AGRICULTURAL RESEARCH SERVICE, DEPARTMENT.... Mutual interest exists when both parties benefit in the same qualitative way from the objectives of...
7 CFR 550.13 - Mutuality of interest.
Code of Federal Regulations, 2011 CFR
2011-01-01
... 7 Agriculture 6 2011-01-01 2011-01-01 false Mutuality of interest. 550.13 Section 550.13 Agriculture Regulations of the Department of Agriculture (Continued) AGRICULTURAL RESEARCH SERVICE, DEPARTMENT.... Mutual interest exists when both parties benefit in the same qualitative way from the objectives of...
7 CFR 550.13 - Mutuality of interest.
Code of Federal Regulations, 2013 CFR
2013-01-01
... 7 Agriculture 6 2013-01-01 2013-01-01 false Mutuality of interest. 550.13 Section 550.13 Agriculture Regulations of the Department of Agriculture (Continued) AGRICULTURAL RESEARCH SERVICE, DEPARTMENT.... Mutual interest exists when both parties benefit in the same qualitative way from the objectives of...
47 CFR 90.165 - Procedures for mutually exclusive applications.
Code of Federal Regulations, 2012 CFR
2012-10-01
... 47 Telecommunication 5 2012-10-01 2012-10-01 false Procedures for mutually exclusive applications... filing dates) as acceptable for filing. (4) Window filing group. A window filing group comprises mutually exclusive applications whose filing date is within an announced filing window. An announced filing window...
Mutualism between tree shrews and pitcher plants
Moran, Jonathan A; Chin, Lijin
2010-01-01
Three species of Nepenthes pitcher plants from Borneo engage in a mutualistic interaction with mountain tree shrews, the basis of which is the exchange of nutritional resources. The plants produce modified “toilet pitchers” that produce copious amounts of exudates, the latter serving as a food source for tree shrews. The exudates are only accessible to the tree shrews when they position their hindquarters over the pitcher orifice. Tree shrews mark valuable resources with feces and regularly defecate into the pitchers when they visit them to feed. Feces represent a valuable source of nitrogen for these Nepenthes species, but there are many facets of the mutualism that are yet to be investigated. These include, but are not limited to, seasonal variation in exudate production rates by the plants, behavioral ecology of visiting tree shrews and the mechanism by which the plants signal to tree shrews that their pitchers represent a food source. Further research into this extraordinary animal-plant interaction is required to gain a better understanding of the benefits to the participating species. PMID:20861680
Observation of mutual neutralization in detached plasma
NASA Astrophysics Data System (ADS)
Akira, Tonegawa; Isao, Shirota; Ken'ichi, Yoshida; Masataka, Ono; Kazutaka, Kawamura; Tuguhiro, Watanabe; Nobuyoshi, Ohyabu; Hajime, Suzuki; Kazuo, Takayama
2001-10-01
Mutual neutralization in collisions between negative ions and positive ions in molecular activated recombination (MAR) has been observed in a high density magnetized sheet plasma source TPDSHEET-IV(Test Plasma produced by Directed current for SHEET plasma) device. Measurements of the negative ion density of hydrogen atom, the electron density, electron temperature, and the heat load to the target plate were carried out in hydrogen high density plasma with hydrogen gas puff. A cylindrical probe made of tungsten ( 0.4 x 2 cm) was used to measure the spatial profiles of H- by a probe-assisted laser photodetachment The Balmer spectra of visible light emission from hydrogen or helium atoms were detected in front of the target plate. A small amount of secondary hydrogen gas puffing into a hydrogen plasma reduced strongly the heat flux to the target and increased rapidly the density of negative ions of hydrogen atom in the circumference of the plasma, while the conventional radiative and three-body recombination processes were disappeared. These results can be well explained by taking the charge exchange recombination of MAR in the detached plasma into account.
A semi-supervised classification algorithm using the TAD-derived background as training data
NASA Astrophysics Data System (ADS)
Fan, Lei; Ambeau, Brittany; Messinger, David W.
2013-05-01
In general, spectral image classification algorithms fall into one of two categories: supervised and unsupervised. In unsupervised approaches, the algorithm automatically identifies clusters in the data without a priori information about those clusters (except perhaps the expected number of them). Supervised approaches require an analyst to identify training data to learn the characteristics of the clusters such that they can then classify all other pixels into one of the pre-defined groups. The classification algorithm presented here is a semi-supervised approach based on the Topological Anomaly Detection (TAD) algorithm. The TAD algorithm defines background components based on a mutual k-Nearest Neighbor graph model of the data, along with a spectral connected components analysis. Here, the largest components produced by TAD are used as regions of interest (ROI's),or training data for a supervised classification scheme. By combining those ROI's with a Gaussian Maximum Likelihood (GML) or a Minimum Distance to the Mean (MDM) algorithm, we are able to achieve a semi supervised classification method. We test this classification algorithm against data collected by the HyMAP sensor over the Cooke City, MT area and University of Pavia scene.
Thepsoonthorn, C.; Yokozuka, T.; Miura, S.; Ogawa, K.; Miyake, Y.
2016-01-01
As prior knowledge is claimed to be an essential key to achieve effective education, we are interested in exploring whether prior knowledge enhances communication effectiveness. To demonstrate the effects of prior knowledge, mutual gaze convergence and head nodding synchrony are observed as indicators of communication effectiveness. We conducted an experiment on lecture task between lecturer and student under 2 conditions: prior knowledge and non-prior knowledge. The students in prior knowledge condition were provided the basic information about the lecture content and were assessed their understanding by the experimenter before starting the lecture while the students in non-prior knowledge had none. The result shows that the interaction in prior knowledge condition establishes significantly higher mutual gaze convergence (t(15.03) = 6.72, p < 0.0001; α = 0.05, n = 20) and head nodding synchrony (t(16.67) = 1.83, p = 0.04; α = 0.05, n = 19) compared to non-prior knowledge condition. This study reveals that prior knowledge facilitates mutual gaze convergence and head nodding synchrony. Furthermore, the interaction with and without prior knowledge can be evaluated by measuring or observing mutual gaze convergence and head nodding synchrony. PMID:27910902
Bargagli, Anna Maria; Colais, Paola; Agabiti, Nera; Mayer, Flavia; Buttari, Fabio; Centonze, Diego; Di Folco, Marta; Filippini, Graziella; Francia, Ada; Galgani, Simonetta; Gasperini, Claudio; Giuliani, Manuela; Mirabella, Massimiliano; Nociti, Viviana; Pozzilli, Carlo; Davoli, Marina
2016-04-01
Compared with other areas of the country, very limited data are available on multiple sclerosis (MS) prevalence in Central Italy. We aimed to estimate MS prevalence in the Lazio region and its geographical distribution using regional health information systems (HIS). To identify MS cases we used data from drug prescription, hospital discharge and ticket exemption registries. Crude, age- and gender-specific prevalence estimates on December 31, 2011 were calculated. To compare MS prevalence between different areas within the region, we calculated age- and gender-adjusted prevalence and prevalence ratios using a multivariate Poisson regression model. Crude prevalence rate was 130.5/100,000 (95 % CI 127.5-133.5): 89.7/100,000 for males and 167.9/100,000 for females. The overall prevalence rate standardized to the European Standard Population was 119.6/100,000 (95 % CI 116.8-122.4). We observed significant differences in MS prevalence within the region, with estimates ranging from 96.3 (95 % CI 86.4-107.3) for Latina to 169.6 (95 % CI 147.6-194.9) for Rieti. Most districts close to the coast showed lower prevalence estimates compared to those situated in the eastern mountainous area of the region. In conclusion, this study produced a MS prevalence estimate at regional level using population-based health administrative databases. Our results showed the Lazio region is a high-risk area for MS, although with an uneven geographical distribution. While some limitations must be considered including possible prevalence underestimation, HIS represent a valuable source of information to measure the burden of SM, useful for epidemiological surveillance and healthcare planning.
Information filtering on coupled social networks.
Nie, Da-Cheng; Zhang, Zi-Ke; Zhou, Jun-Lin; Fu, Yan; Zhang, Kui
2014-01-01
In this paper, based on the coupled social networks (CSN), we propose a hybrid algorithm to nonlinearly integrate both social and behavior information of online users. Filtering algorithm, based on the coupled social networks, considers the effects of both social similarity and personalized preference. Experimental results based on two real datasets, Epinions and Friendfeed, show that the hybrid pattern can not only provide more accurate recommendations, but also enlarge the recommendation coverage while adopting global metric. Further empirical analyses demonstrate that the mutual reinforcement and rich-club phenomenon can also be found in coupled social networks where the identical individuals occupy the core position of the online system. This work may shed some light on the in-depth understanding of the structure and function of coupled social networks.
Information Filtering on Coupled Social Networks
Nie, Da-Cheng; Zhang, Zi-Ke; Zhou, Jun-Lin; Fu, Yan; Zhang, Kui
2014-01-01
In this paper, based on the coupled social networks (CSN), we propose a hybrid algorithm to nonlinearly integrate both social and behavior information of online users. Filtering algorithm, based on the coupled social networks, considers the effects of both social similarity and personalized preference. Experimental results based on two real datasets, Epinions and Friendfeed, show that the hybrid pattern can not only provide more accurate recommendations, but also enlarge the recommendation coverage while adopting global metric. Further empirical analyses demonstrate that the mutual reinforcement and rich-club phenomenon can also be found in coupled social networks where the identical individuals occupy the core position of the online system. This work may shed some light on the in-depth understanding of the structure and function of coupled social networks. PMID:25003525
Evaluation of Demons- and FEM-Based Registration Algorithms for Lung Cancer.
Yang, Juan; Li, Dengwang; Yin, Yong; Zhao, Fen; Wang, Hongjun
2016-04-01
We evaluated and compared the accuracy of 2 deformable image registration algorithms in 4-dimensional computed tomography images for patients with lung cancer. Ten patients with non-small cell lung cancer or small cell lung cancer were enrolled in this institutional review board-approved study. The displacement vector fields relative to a specific reference image were calculated by using the diffeomorphic demons (DD) algorithm and the finite element method (FEM)-based algorithm. The registration accuracy was evaluated by using normalized mutual information (NMI), the sum of squared intensity difference (SSD), modified Hausdorff distance (dH_M), and ratio of gross tumor volume (rGTV) difference between reference image and deformed phase image. We also compared the registration speed of the 2 algorithms. Of all patients, the FEM-based algorithm showed stronger ability in aligning 2 images than the DD algorithm. The means (±standard deviation) of NMI were 0.86 (±0.05) and 0.90 (±0.05) using the DD algorithm and the FEM-based algorithm, respectively. The means of SSD were 0.006 (±0.003) and 0.003 (±0.002) using the DD algorithm and the FEM-based algorithm, respectively. The means of dH_M were 0.04 (±0.02) and 0.03 (±0.03) using the DD algorithm and the FEM-based algorithm, respectively. The means of rGTV were 3.9% (±1.01%) and 2.9% (±1.1%) using the DD algorithm and the FEM-based algorithm, respectively. However, the FEM-based algorithm costs a longer time than the DD algorithm, with the average running time of 31.4 minutes compared to 21.9 minutes for all patients. The preliminary results showed that the FEM-based algorithm was more accurate than the DD algorithm while compromised with the registration speed.
NASA Astrophysics Data System (ADS)
Shorikov, A. F.
2016-12-01
This article discusses the discrete-time dynamical system consisting from two controlled objects and described by a linear recurrent vector equations in the presence of uncertain perturbations. This dynamical system has two levels of a control: dominant level (the first level or the level I) and subordinate level (the second level or the level II) and both have different linear terminal criterions of functioning and united a priori by determined information and control connections. It is assumed that the sets constraining all a priori undefined parameters are known and they are a finite sets or convex, closed and bounded polyhedrons in the corresponding finite-dimensional vector spaces. For the dynamical system in question, we propose a mathematical formalization in the form of solving two-level hierarchical minimax program control problem with incomplete information. In this article for solving of the investigated problem is proposed the algorithm that has a form of a recurrent procedure of solving a linear programming and a finite optimization problems. The results obtained in this article can be used for computer simulation of an actual dynamical processes and for designing controlling and navigation systems.
Pareschi, Fabio; Albertini, Pierluigi; Frattini, Giovanni; Mangia, Mauro; Rovatti, Riccardo; Setti, Gianluca
2016-02-01
We report the design and implementation of an Analog-to-Information Converter (AIC) based on Compressed Sensing (CS). The system is realized in a CMOS 180 nm technology and targets the acquisition of bio-signals with Nyquist frequency up to 100 kHz. To maximize performance and reduce hardware complexity, we co-design hardware together with acquisition and reconstruction algorithms. The resulting AIC outperforms previously proposed solutions mainly thanks to two key features. First, we adopt a novel method to deal with saturations in the computation of CS measurements. This allows no loss in performance even when 60% of measurements saturate. Second, the system is able to adapt itself to the energy distribution of the input by exploiting the so-called rakeness to maximize the amount of information contained in the measurements. With this approach, the 16 measurement channels integrated into a single device are expected to allow the acquisition and the correct reconstruction of most biomedical signals. As a case study, measurements on real electrocardiograms (ECGs) and electromyograms (EMGs) show signals that these can be reconstructed without any noticeable degradation with a compression rate, respectively, of 8 and 10.
Research on polarization imaging information parsing method
NASA Astrophysics Data System (ADS)
Yuan, Hongwu; Zhou, Pucheng; Wang, Xiaolong
2016-11-01
Polarization information parsing plays an important role in polarization imaging detection. This paper focus on the polarization information parsing method: Firstly, the general process of polarization information parsing is given, mainly including polarization image preprocessing, multiple polarization parameters calculation, polarization image fusion and polarization image tracking, etc.; And then the research achievements of the polarization information parsing method are presented, in terms of polarization image preprocessing, the polarization image registration method based on the maximum mutual information is designed. The experiment shows that this method can improve the precision of registration and be satisfied the need of polarization information parsing; In terms of multiple polarization parameters calculation, based on the omnidirectional polarization inversion model is built, a variety of polarization parameter images are obtained and the precision of inversion is to be improve obviously; In terms of polarization image fusion , using fuzzy integral and sparse representation, the multiple polarization parameters adaptive optimal fusion method is given, and the targets detection in complex scene is completed by using the clustering image segmentation algorithm based on fractal characters; In polarization image tracking, the average displacement polarization image characteristics of auxiliary particle filtering fusion tracking algorithm is put forward to achieve the smooth tracking of moving targets. Finally, the polarization information parsing method is applied to the polarization imaging detection of typical targets such as the camouflage target, the fog and latent fingerprints.
Mutually unbiased bases as minimal Clifford covariant 2-designs
NASA Astrophysics Data System (ADS)
Zhu, Huangjun
2015-06-01
Mutually unbiased bases (MUBs) are interesting for various reasons. The most attractive example of (a complete set of) MUBs is the one constructed by Ivanović as well as Wootters and Fields, which is referred to as the canonical MUB. Nevertheless, little is known about anything that is unique to this MUB. We show that the canonical MUB in any prime power dimension is uniquely determined by an extremal orbit of the (restricted) Clifford group except in dimension 3, in which case the orbit defines a special symmetric informationally complete measurement (SIC), known as the Hesse SIC. Here the extremal orbit is the orbit with the smallest number of pure states. Quite surprisingly, this characterization does not rely on any concept that is related to bases or unbiasedness. As a corollary, the canonical MUB is the unique minimal 2-design covariant with respect to the Clifford group except in dimension 3. In addition, these MUBs provide an infinite family of highly symmetric frames and positive-operator-valued measures (POVMs), which are of independent interest.
Ganesh Kumar, Pugalendhi; Kavitha, Muthu Subash; Ahn, Byeong-Cheol
2016-01-01
This study describes a novel approach to reducing the challenges of highly nonlinear multiclass gene expression values for cancer diagnosis. To build a fruitful system for cancer diagnosis, in this study, we introduced two levels of gene selection such as filtering and embedding for selection of potential genes and the most relevant genes associated with cancer, respectively. The filter procedure was implemented by developing a fuzzy rough set (FR)-based method for redefining the criterion function of f-information (FI) to identify the potential genes without discretizing the continuous gene expression values. The embedded procedure is implemented by means of a water swirl algorithm (WSA), which attempts to optimize the rule set and membership function required to classify samples using a fuzzy-rule-based multiclassification system (FRBMS). Two novel update equations are proposed in WSA, which have better exploration and exploitation abilities while designing a self-learning FRBMS. The efficiency of our new approach was evaluated on 13 multicategory and 9 binary datasets of cancer gene expression. Additionally, the performance of the proposed FRFI-WSA method in designing an FRBMS was compared with existing methods for gene selection and optimization such as genetic algorithm (GA), particle swarm optimization (PSO), and artificial bee colony algorithm (ABC) on all the datasets. In the global cancer map with repeated measurements (GCM_RM) dataset, the FRFI-WSA showed the smallest number of 16 most relevant genes associated with cancer using a minimal number of 26 compact rules with the highest classification accuracy (96.45%). In addition, the statistical validation used in this study revealed that the biological relevance of the most relevant genes associated with cancer and their linguistics detected by the proposed FRFI-WSA approach are better than those in the other methods. The simple interpretable rules with most relevant genes and effectively classified
Ahn, Byeong-Cheol
2016-01-01
This study describes a novel approach to reducing the challenges of highly nonlinear multiclass gene expression values for cancer diagnosis. To build a fruitful system for cancer diagnosis, in this study, we introduced two levels of gene selection such as filtering and embedding for selection of potential genes and the most relevant genes associated with cancer, respectively. The filter procedure was implemented by developing a fuzzy rough set (FR)-based method for redefining the criterion function of f-information (FI) to identify the potential genes without discretizing the continuous gene expression values. The embedded procedure is implemented by means of a water swirl algorithm (WSA), which attempts to optimize the rule set and membership function required to classify samples using a fuzzy-rule-based multiclassification system (FRBMS). Two novel update equations are proposed in WSA, which have better exploration and exploitation abilities while designing a self-learning FRBMS. The efficiency of our new approach was evaluated on 13 multicategory and 9 binary datasets of cancer gene expression. Additionally, the performance of the proposed FRFI-WSA method in designing an FRBMS was compared with existing methods for gene selection and optimization such as genetic algorithm (GA), particle swarm optimization (PSO), and artificial bee colony algorithm (ABC) on all the datasets. In the global cancer map with repeated measurements (GCM_RM) dataset, the FRFI-WSA showed the smallest number of 16 most relevant genes associated with cancer using a minimal number of 26 compact rules with the highest classification accuracy (96.45%). In addition, the statistical validation used in this study revealed that the biological relevance of the most relevant genes associated with cancer and their linguistics detected by the proposed FRFI-WSA approach are better than those in the other methods. The simple interpretable rules with most relevant genes and effectively classified
Entanglement patterns in mutually unbiased basis sets
Lawrence, Jay
2011-08-15
A few simply stated rules govern the entanglement patterns that can occur in mutually unbiased basis sets (MUBs) and constrain the combinations of such patterns that can coexist in full complements of MUBs. We consider Hilbert spaces of prime power dimensions (D=p{sup N}), as realized by systems of N prime-state particles, where full complements of D+1 MUBs are known to exist, and we assume only that MUBs are eigenbases of generalized Pauli operators, without using any particular construction. The general rules include the following: (1) In any MUB, a given particle appears either in a pure state or totally entangled and (2) in any full MUB complement, each particle is pure in (p+1) bases (not necessarily the same ones) and totally entangled in the remaining (p{sup N}-p). It follows that the maximum number of product bases is p+1 and, when this number is realized, all remaining (p{sup N}-p) bases in the complement are characterized by the total entanglement of every particle. This ''standard distribution'' is inescapable for two-particle systems (of any p), where only product and generalized Bell bases are admissible MUB types. This and the following results generalize previous results for qubits [Phys. Rev. A 65. 032320 (2002); Phys. Rev. A 72, 062310 (2005)] and qutrits [Phys. Rev. A 70, 012302 (2004)], drawing particularly upon [Phys. Rev. A 72, 062310 (2005)]. With three particles there are three MUB types, and these may be combined in (p+2) different ways to form full complements. With N=4, there are 6 MUB types for p=2, but new MUB types become possible with larger p, and these are essential to realizing full complements. With this example, we argue that new MUB types that show new entanglement patterns should enter with every step in N and, also, when N is a prime plus 1, at a critical p value, p=N-1. Such MUBs should play critical roles in filling complements.
Sarkar, Saradwata; Johnson, Timothy D.; Ma, Bing; Chenevert, Thomas L.; Bland, Peyton H.; Park, Hyunjin; Schott, Anne F.; Ross, Brian D.; Meyer, Charles R.
2012-07-01
Purpose: Assuming that early tumor volume change is a biomarker for response to therapy, accurate quantification of early volume changes could aid in adapting an individual patient's therapy and lead to shorter clinical trials. We investigated an image registration-based approach for tumor volume change quantification that may more reliably detect smaller changes that occur in shorter intervals than can be detected by existing algorithms. Methods and Materials: Variance and bias of the registration-based approach were evaluated using retrospective, in vivo, very-short-interval diffusion magnetic resonance imaging scans where true zero tumor volume change is unequivocally known and synthetic data, respectively. The interval scans were nonlinearly registered using two similarity measures: mutual information (MI) and normalized cross-correlation (NCC). Results: The 95% confidence interval of the percentage volume change error was (-8.93% to 10.49%) for MI-based and (-7.69%, 8.83%) for NCC-based registrations. Linear mixed-effects models demonstrated that error in measuring volume change increased with increase in tumor volume and decreased with the increase in the tumor's normalized mutual information, even when NCC was the similarity measure being optimized during registration. The 95% confidence interval of the relative volume change error for the synthetic examinations with known changes over {+-}80% of reference tumor volume was (-3.02% to 3.86%). Statistically significant bias was not demonstrated. Conclusion: A low-noise, low-bias tumor volume change measurement algorithm using nonlinear registration is described. Errors in change measurement were a function of tumor volume and the normalized mutual information content of the tumor.
NASA Technical Reports Server (NTRS)
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.
Mathematical algorithms for approximate reasoning
NASA Technical Reports Server (NTRS)
Murphy, John H.; Chay, Seung C.; Downs, Mary M.
1988-01-01
Most state of the art expert system environments contain a single and often ad hoc strategy for approximate reasoning. Some environments provide facilities to program the approximate reasoning algorithms. However, the next generation of expert systems should have an environment which contain a choice of several mathematical algorithms for approximate reasoning. To meet the need for validatable and verifiable coding, the expert system environment must no longer depend upon ad hoc reasoning techniques but instead must include mathematically rigorous techniques for approximate reasoning. Popular approximate reasoning techniques are reviewed, including: certainty factors, belief measures, Bayesian probabilities, fuzzy logic, and Shafer-Dempster techniques for reasoning. A group of mathematically rigorous algorithms for approximate reasoning are focused on that could form the basis of a next generation expert system environment. These algorithms are based upon the axioms of set theory and probability theory. To separate these algorithms for approximate reasoning various conditions of mutual exclusivity and independence are imposed upon the assertions. Approximate reasoning algorithms presented include: reasoning with statistically independent assertions, reasoning with mutually exclusive assertions, reasoning with assertions that exhibit minimum overlay within the state space, reasoning with assertions that exhibit maximum overlay within the state space (i.e. fuzzy logic), pessimistic reasoning (i.e. worst case analysis), optimistic reasoning (i.e. best case analysis), and reasoning with assertions with absolutely no knowledge of the possible dependency among the assertions. A robust environment for expert system construction should include the two modes of inference: modus ponens and modus tollens. Modus ponens inference is based upon reasoning towards the conclusion in a statement of logical implication, whereas modus tollens inference is based upon reasoning away
Brown, Christopher A.; Brown, Kevin S.
2010-01-01
Correlated amino acid substitution algorithms attempt to discover groups of residues that co-fluctuate due to either structural or functional constraints. Although these algorithms could inform both ab initio protein folding calculations and evolutionary studies, their utility for these purposes has been hindered by a lack of confidence in their predictions due to hard to control sources of error. To complicate matters further, naive users are confronted with a multitude of methods to choose from, in addition to the mechanics of assembling and pruning a dataset. We first introduce a new pair scoring method, called ZNMI (Z-scored-product Normalized Mutual Information), which drastically improves the performance of mutual information for co-fluctuating residue prediction. Second and more important, we recast the process of finding coevolving residues in proteins as a data-processing pipeline inspired by the medical imaging literature. We construct an ensemble of alignment partitions that can be used in a cross-validation scheme to assess the effects of choices made during the procedure on the resulting predictions. This pipeline sensitivity study gives a measure of reproducibility (how similar are the predictions given perturbations to the pipeline?) and accuracy (are residue pairs with large couplings on average close in tertiary structure?). We choose a handful of published methods, along with ZNMI, and compare their reproducibility and accuracy on three diverse protein families. We find that (i) of the algorithms tested, while none appear to be both highly reproducible and accurate, ZNMI is one of the most accurate by far and (ii) while users should be wary of predictions drawn from a single alignment, considering an ensemble of sub-alignments can help to determine both highly accurate and reproducible couplings. Our cross-validation approach should be of interest both to developers and end users of algorithms that try to detect correlated amino acid substitutions
47 CFR 27.321 - Mutually exclusive applications.
Code of Federal Regulations, 2011 CFR
2011-10-01
... MISCELLANEOUS WIRELESS COMMUNICATIONS SERVICES Application, Licensing, and Processing Rules for WCS § 27.321... Commission's rules governing the Wireless Communications Services involved. The Commission uses the general procedures in this section for processing mutually exclusive applications in the Wireless...
47 CFR 27.321 - Mutually exclusive applications.
Code of Federal Regulations, 2013 CFR
2013-10-01
... MISCELLANEOUS WIRELESS COMMUNICATIONS SERVICES Application, Licensing, and Processing Rules for WCS § 27.321... Commission's rules governing the Wireless Communications Services involved. The Commission uses the general procedures in this section for processing mutually exclusive applications in the Wireless...
47 CFR 27.321 - Mutually exclusive applications.
Code of Federal Regulations, 2010 CFR
2010-10-01
... MISCELLANEOUS WIRELESS COMMUNICATIONS SERVICES Application, Licensing, and Processing Rules for WCS § 27.321... Commission's rules governing the Wireless Communications Services involved. The Commission uses the general procedures in this section for processing mutually exclusive applications in the Wireless...
47 CFR 27.321 - Mutually exclusive applications.
Code of Federal Regulations, 2014 CFR
2014-10-01
... MISCELLANEOUS WIRELESS COMMUNICATIONS SERVICES Application, Licensing, and Processing Rules for WCS § 27.321... Commission's rules governing the Wireless Communications Services involved. The Commission uses the general procedures in this section for processing mutually exclusive applications in the Wireless...
47 CFR 27.321 - Mutually exclusive applications.
Code of Federal Regulations, 2012 CFR
2012-10-01
... MISCELLANEOUS WIRELESS COMMUNICATIONS SERVICES Application, Licensing, and Processing Rules for WCS § 27.321... Commission's rules governing the Wireless Communications Services involved. The Commission uses the general procedures in this section for processing mutually exclusive applications in the Wireless...
Mutual impedance of nonplanar-skew sinusoidal dipoles
NASA Technical Reports Server (NTRS)
Richmond, J. H.; Geary, N. H.
1975-01-01
The mutual impedance expressions for parallel dipoles in terms of sine-integrals and cosine-integrals have been published by King (1957). The investigation reported provides analogous expressions for nonparallel dipoles. The expressions presented are most useful when the monopoles are close together. The theory of moment methods shows an approach for employing the mutual impedance of filamentary sinusoidal dipoles to calculate the impedance and scattering properties of straight and bent wires with small but finite diameter.
Viscosity and mutual diffusion in strongly asymmetric binary ionic mixtures
Bastea, Sorin
2005-05-01
We present molecular dynamics simulation results for the viscosity and mutual diffusion constant of a strongly asymmetric binary ionic mixture. We compare the results with available theoretical models previously tested for much smaller asymmetries. For the case of viscosity we propose a predictive framework based on the linear mixing rule, while for mutual diffusion we discuss some consistency problems of widely used Boltzmann-equation-based models.
Viscosity and mutual diffusion in strongly asymmetric plasma mixtures
Bastea, S
2004-09-07
The authors present molecular dynamics simulation results for the viscosity and mutual diffusion constant of a strongly asymmetric two-component plasma (TCP). They compare the results with available theoretical models previously tested for much smaller asymmetries. for the case of viscosity they propose a new predictive framework based on the linear mixing rule, while for mutual diffusion they point out some consistency problems of widely used Boltzmann equation based models.
Quantum process reconstruction based on mutually unbiased basis
Fernandez-Perez, A.; Saavedra, C.; Klimov, A. B.
2011-05-15
We study a quantum process reconstruction based on the use of mutually unbiased projectors (MUB projectors) as input states for a D-dimensional quantum system, with D being a power of a prime number. This approach connects the results of quantum-state tomography using mutually unbiased bases with the coefficients of a quantum process, expanded in terms of MUB projectors. We also study the performance of the reconstruction scheme against random errors when measuring probabilities at the MUB projectors.
An invasive plant-fungal mutualism reduces arthropod diversity.
Rudgers, Jennifer A; Clay, Keith
2008-08-01
Ecological theory holds that competition and predation are the most important biotic forces affecting the composition of communities. Here, we expand this framework by demonstrating that mutualism can fundamentally alter community and food web structure. In large, replicated field plots, we manipulated the mutualism between a dominant plant (Lolium arundinaceum) and symbiotic fungal endophyte (Neotyphodium coenophialum). The presence of the mutualism reduced arthropod abundance up to 70%, reduced arthropod diversity nearly 20%, shifted arthropod species composition relative to endophyte-free plots and suppressed the biomass and richness of other plant species in the community. Herbivorous arthropods were more strongly affected than carnivores, and for both herbivores and carnivores, effects of the mutualism appeared to propagate indirectly via organisms occurring more basally in the food web. The influence of the mutualism was as great or greater than previously documented effects of competition and predation on arthropod communities. Our work demonstrates that a keystone mutualism can significantly reduce arthropod biodiversity at a broad community scale.
One improved LSB steganography algorithm
NASA Astrophysics Data System (ADS)
Song, Bing; Zhang, Zhi-hong
2013-03-01
It is easy to be detected by X2 and RS steganalysis with high accuracy that using LSB algorithm to hide information in digital image. We started by selecting information embedded location and modifying the information embedded method, combined with sub-affine transformation and matrix coding method, improved the LSB algorithm and a new LSB algorithm was proposed. Experimental results show that the improved one can resist the X2 and RS steganalysis effectively.
ERIC Educational Resources Information Center
Denissen, Jaap J. A.; van Aken, Marcel A. G.; Dubas, Judith S.
2009-01-01
According to J. Belsky's (1984) process model of parenting, both adolescents' and parents' personality should exert a significant impact on the quality of their mutual relationship. Using multi-informant, symmetric data on the Big Five personality traits and the relationship quality of mothers, fathers, and two adolescent children, the current…
Information-theoretic analysis of x-ray scatter and phase architectures for anomaly detection
NASA Astrophysics Data System (ADS)
Coccarelli, David; Gong, Qian; Stoian, Razvan-Ionut; Greenberg, Joel A.; Gehm, Michael E.; Lin, Yuzhang; Huang, Liang-Chih; Ashok, Amit
2016-05-01
Conventional performance analysis of detection systems confounds the effects of the system architecture (sources, detectors, system geometry, etc.) with the effects of the detection algorithm. Previously, we introduced an information-theoretic approach to this problem by formulating a performance metric, based on Cauchy-Schwarz mutual information, that is analogous to the channel capacity concept from communications engineering. In this work, we discuss the application of this metric to study novel screening systems based on x-ray scatter or phase. Our results show how effective use of this metric can impact design decisions for x-ray scatter and phase systems.
Lu, Chunhong; Zhu, Zhaomin; Gu, Xiaofeng
2014-09-01
In this paper, we develop a novel feature selection algorithm based on the genetic algorithm (GA) using a specifically devised trace-based separability criterion. According to the scores of class separability and variable separability, this criterion measures the significance of feature subset, independent of any specific classification. In addition, a mutual information matrix between variables is used as features for classification, and no prior knowledge about the cardinality of feature subset is required. Experiments are performed by using a standard lung cancer dataset. The obtained solutions are verified with three different classifiers, including the support vector machine (SVM), the back-propagation neural network (BPNN), and the K-nearest neighbor (KNN), and compared with those obtained by the whole feature set, the F-score and the correlation-based feature selection methods. The comparison results show that the proposed intelligent system has a good diagnosis performance and can be used as a promising tool for lung cancer diagnosis.
Art and Mathematics--Mutual Enrichment.
ERIC Educational Resources Information Center
Pumfrey, Elizabeth; Beardon, Toni
2002-01-01
Presents some activities for both art and mathematics classrooms. Traces the history of geometric art and focuses on a way of drawing tiling using LOGO programming. Describes some of the work on tessellations by the mathematician Roger Penrose and the artist M.C. Escher. Provides websites for further information. (KHR)
A frequency domain blind deconvolution algorithm in acoustics
NASA Astrophysics Data System (ADS)
Gramann, Mark R.; Erling, Josh G.; Roan, Michael J.
2003-10-01
It is common in acoustics to measure a signal that has been corrupted by an unknown filtering function during propagation from an unknown source. Blind deconvolution is a technique for learning and applying the inverse of the unknown channel impulse response in order to recover the original source signal. One approach to accomplishing this task is based on an adaptive nonlinear algorithm using mutual information as a cost function [A. J. Bell and T. J. Sejnowski, Neural Comput. 7, 1129-1159 (1995)]. A new frequency domain implementation of this algorithm is presented which greatly reduces computational cost. The frequency domain approach allows adaptive learning rates to be applied individually to each frequency bin of the inverse filter. This technique can lead to improved convergence times for filters with a large spread of frequency response magnitudes. Preliminary results suggest that a factor of two reduction in convergence time and a factor of ten reduction in computational cost can be attained. Experimental results for several simple acoustical systems are presented comparing the performance of the pre-existing time domain algorithm and the new frequency domain implementation. [Work supported by Dr. David Drumheller, ONR Code 333, Contract No. N00014-00-G-0058.
Implementation of several mathematical algorithms to breast tissue density classification
NASA Astrophysics Data System (ADS)
Quintana, C.; Redondo, M.; Tirao, G.
2014-02-01
The accuracy of mammographic abnormality detection methods is strongly dependent on breast tissue characteristics, where a dense breast tissue can hide lesions causing cancer to be detected at later stages. In addition, breast tissue density is widely accepted to be an important risk indicator for the development of breast cancer. This paper presents the implementation and the performance of different mathematical algorithms designed to standardize the categorization of mammographic images, according to the American College of Radiology classifications. These mathematical techniques are based on intrinsic properties calculations and on comparison with an ideal homogeneous image (joint entropy, mutual information, normalized cross correlation and index Q) as categorization parameters. The algorithms evaluation was performed on 100 cases of the mammographic data sets provided by the Ministerio de Salud de la Provincia de Córdoba, Argentina—Programa de Prevención del Cáncer de Mama (Department of Public Health, Córdoba, Argentina, Breast Cancer Prevention Program). The obtained breast classifications were compared with the expert medical diagnostics, showing a good performance. The implemented algorithms revealed a high potentiality to classify breasts into tissue density categories.
Persistence of pollination mutualisms in the presence of ants.
Wang, Yuanshi; Wang, Shikun
2015-01-01
This paper considers plant-pollinator-ant systems in which the plant-pollinator interaction is mutualistic but ants have both positive and negative effects on plants. The ants also interfere with pollinators by preventing them from accessing plants. While a Beddington-DeAngelis (BD) formula can describe the plant-pollinator interaction, the formula is extended in this paper to characterize the pollination mutualism under the ant interference. Then, a plant-pollinator-ant system with the extended BD functional response is discussed, and global dynamics of the model demonstrate the mechanisms by which pollination mutualism can persist in the presence of ants. When the ant interference is strong, it can result in extinction of pollinators. Moreover, if the ants depend on pollination mutualism for survival, the strong interference could drive pollinators into extinction, which consequently lead to extinction of the ants themselves. When the ant interference is weak, a cooperation between plant-ant and plant-pollinator mutualisms could occur, which promotes survival of both ants and pollinators, especially in the case that ants (respectively, pollinators) cannot survive in the absence of pollinators (respectively, ants). Even when the level of ant interference remains invariant, varying ants' negative effect on plants can result in survival/extinction of both ants and pollinators. Therefore, our results provide an explanation for the persistence of pollination mutualism when there exist ants.
Population dynamics and mutualism: Functional responses of benefits and costs
Holland, J. Nathaniel; DeAngelis, Donald L.; Bronstein, Judith L.
2002-01-01
We develop an approach for studying population dynamics resulting from mutualism by employing functional responses based on density‐dependent benefits and costs. These functional responses express how the population growth rate of a mutualist is modified by the density of its partner. We present several possible dependencies of gross benefits and costs, and hence net effects, to a mutualist as functions of the density of its partner. Net effects to mutualists are likely a monotonically saturating or unimodal function of the density of their partner. We show that fundamental differences in the growth, limitation, and dynamics of a population can occur when net effects to that population change linearly, unimodally, or in a saturating fashion. We use the mutualism between senita cactus and its pollinating seed‐eating moth as an example to show the influence of different benefit and cost functional responses on population dynamics and stability of mutualisms. We investigated two mechanisms that may alter this mutualism's functional responses: distribution of eggs among flowers and fruit abortion. Differences in how benefits and costs vary with density can alter the stability of this mutualism. In particular, fruit abortion may allow for a stable equilibrium where none could otherwise exist.
Mutualism Disruption Threatens Global Plant Biodiversity: A Systematic Review
Aslan, Clare E.; Zavaleta, Erika S.; Tershy, Bernie; Croll, Donald
2013-01-01
Background As global environmental change accelerates, biodiversity losses can disrupt interspecific interactions. Extinctions of mutualist partners can create “widow” species, which may face reduced ecological fitness. Hypothetically, such mutualism disruptions could have cascading effects on biodiversity by causing additional species coextinctions. However, the scope of this problem – the magnitude of biodiversity that may lose mutualist partners and the consequences of these losses – remains unknown. Methodology/Principal Findings We conducted a systematic review and synthesis of data from a broad range of sources to estimate the threat posed by vertebrate extinctions to the global biodiversity of vertebrate-dispersed and -pollinated plants. Though enormous research gaps persist, our analysis identified Africa, Asia, the Caribbean, and global oceanic islands as geographic regions at particular risk of disruption of these mutualisms; within these regions, percentages of plant species likely affected range from 2.1–4.5%. Widowed plants are likely to experience reproductive declines of 40–58%, potentially threatening their persistence in the context of other global change stresses. Conclusions Our systematic approach demonstrates that thousands of species may be impacted by disruption in one class of mutualisms, but extinctions will likely disrupt other mutualisms, as well. Although uncertainty is high, there is evidence that mutualism disruption directly threatens significant biodiversity in some geographic regions. Conservation measures with explicit focus on mutualistic functions could be necessary to bolster populations of widowed species and maintain ecosystem functions. PMID:23840571
Behavioral mechanisms underlie an ant-plant mutualism.
Rudgers, Jennifer A; Hodgen, Jillian G; White, J Wilson
2003-03-01
Predators can reduce herbivory by consuming herbivores (a consumptive effect) and by altering herbivore behavior, life history, physiology or distribution (non-consumptive effects). The non-consumptive, or trait-mediated, effects of predators on prey may have important functions in the dynamics of communities. In a facultative ant-plant mutualism, we investigated whether these non-consumptive effects influenced the host plants of prey. Here, predaceous ants (Forelius pruinosus) consume and disturb a dominant lepidopteran folivore (Bucculatrix thurberiella) of wild cotton plants (Gossypium thurberi). Season-long ant exclusion experiments revealed that ants had a larger proportional effect on damage by B. thurberiella than on caterpillar abundance, a result that suggests ants have a strong non-consumptive effect. Behavioral experiments conducted in two populations over 2 years demonstrated that B. thurberiella caterpillars were substantially less likely to damage wild cotton leaves in the presence of ants due to ant-induced changes in caterpillar behavior. In the absence of ants caterpillars spent more time stationary (potential feeding time) and less time dropping from leaves by a thread of silk than when ants were present. Furthermore, ants altered the spatial distribution of both caterpillars and damage; caterpillars spent relatively more time on the upper surfaces of leaves and caused damage further from the leaf margin in ant exclusion treatments. Both direct encounters with ants and information conveyed when ants walked onto leaves were key events leading to the anti-predator behaviors of caterpillars. This study contributes to a small body of evidence from terrestrial systems demonstrating that the trait-mediated effects of predators can cascade to the host plants of prey.
NASA Technical Reports Server (NTRS)
Abrams, D.; Williams, C.
1999-01-01
This thesis describes several new quantum algorithms. These include a polynomial time algorithm that uses a quantum fast Fourier transform to find eigenvalues and eigenvectors of a Hamiltonian operator, and that can be applied in cases for which all know classical algorithms require exponential time.
NASA Astrophysics Data System (ADS)
Zhu, Liujun; Xiao, Pengfeng; Feng, Xuezhi; Zhang, Xueliang; Huang, Yinyou; Li, Chengxi
2016-12-01
High-spatial and -temporal resolution snow cover maps for mountain areas are needed for hydrological applications and snow hazard monitoring. The Chinese GF-1 satellite is potential to provide such information with a spatial resolution of 8 m and a revisit of 4 days. The main challenge for the extraction of multi-temporal snow cover from high-spatial resolution images is that the observed spectral signature of snow and snow-free areas is non-stationary in both spatial and temporal domains. As a result, successful extraction requires adequate labelled samples for each image, which is difficult to be achieved. To solve this problem, a semi-supervised multi-temporal classification method for snow cover extraction (MSCE) is proposed. This method extends the co-training based algorithms from single image classification to multi-temporal ones. Multi-temporal images in MSCE are treated as different descriptions of the same land surface, and consequently, each pixel has multiple sets of features. Independent classifiers are trained on each feature set using a few labelled samples, and then, they are iteratively re-trained in a mutual learning way using a great number of unlabelled samples. The main principle behind MSCE is that the multi-temporal difference of land surface in spectral space can be the source of mutual learning inspired by the co-training paradigm, providing a new strategy to deal with multi-temporal image classification. The experimental findings of multi-temporal GF-1 images confirm the effectiveness of the proposed method.
About mutually unbiased bases in even and odd prime power dimensions
NASA Astrophysics Data System (ADS)
Durt, Thomas
2005-06-01
Mutually unbiased bases generalize the X, Y and Z qubit bases. They possess numerous applications in quantum information science. It is well known that in prime power dimensions N = pm (with p prime and m a positive integer), there exists a maximal set of N + 1 mutually unbiased bases. In the present paper, we derive an explicit expression for those bases, in terms of the (operations of the) associated finite field (Galois division ring) of N elements. This expression is shown to be equivalent to the expressions previously obtained by Ivanovic (1981 J. Phys. A: Math. Gen. 14 3241) in odd prime dimensions, and Wootters and Fields (1989 Ann. Phys. 191 363) in odd prime power dimensions. In even prime power dimensions, we derive a new explicit expression for the mutually unbiased bases. The new ingredients of our approach are, basically, the following: we provide a simple expression of the generalized Pauli group in terms of the additive characters of the field, and we derive an exact groupal composition law between the elements of the commuting subsets of the generalized Pauli group, renormalized by a well-chosen phase-factor.
Kumar, Pardeep; Ylianttila, Mika; Gurtov, Andrei; Lee, Sang-Gon; Lee, Hoon-Jae
2014-02-11
Robust security is highly coveted in real wireless sensor network (WSN) applications since wireless sensors' sense critical data from the application environment. This article presents an efficient and adaptive mutual authentication framework that suits real heterogeneous WSN-based applications (such as smart homes, industrial environments, smart grids, and healthcare monitoring). The proposed framework offers: (i) key initialization; (ii) secure network (cluster) formation (i.e., mutual authentication and dynamic key establishment); (iii) key revocation; and (iv) new node addition into the network. The correctness of the proposed scheme is formally verified. An extensive analysis shows the proposed scheme coupled with message confidentiality, mutual authentication and dynamic session key establishment, node privacy, and message freshness. Moreover, the preliminary study also reveals the proposed framework is secure against popular types of attacks, such as impersonation attacks, man-in-the-middle attacks, replay attacks, and information-leakage attacks. As a result, we believe the proposed framework achieves efficiency at reasonable computation and communication costs and it can be a safeguard to real heterogeneous WSN applications.
Kumar, Pardeep; Ylianttila, Mika; Gurtov, Andrei; Lee, Sang-Gon; Lee, Hoon-Jae
2014-01-01
Robust security is highly coveted in real wireless sensor network (WSN) applications since wireless sensors' sense critical data from the application environment. This article presents an efficient and adaptive mutual authentication framework that suits real heterogeneous WSN-based applications (such as smart homes, industrial environments, smart grids, and healthcare monitoring). The proposed framework offers: (i) key initialization; (ii) secure network (cluster) formation (i.e., mutual authentication and dynamic key establishment); (iii) key revocation; and (iv) new node addition into the network. The correctness of the proposed scheme is formally verified. An extensive analysis shows the proposed scheme coupled with message confidentiality, mutual authentication and dynamic session key establishment, node privacy, and message freshness. Moreover, the preliminary study also reveals the proposed framework is secure against popular types of attacks, such as impersonation attacks, man-in-the-middle attacks, replay attacks, and information-leakage attacks. As a result, we believe the proposed framework achieves efficiency at reasonable computation and communication costs and it can be a safeguard to real heterogeneous WSN applications. PMID:24521942
NASA Astrophysics Data System (ADS)
Brakensiek, Joshua; Ragozzine, D.
2012-10-01
The transit method for discovering extra-solar planets relies on detecting regular diminutions of light from stars due to the shadows of planets passing in between the star and the observer. NASA's Kepler Mission has successfully discovered thousands of exoplanet candidates using this technique, including hundreds of stars with multiple transiting planets. In order to estimate the frequency of these valuable systems, our research concerns the efficient calculation of geometric probabilities for detecting multiple transiting extrasolar planets around the same parent star. In order to improve on previous studies that used numerical methods (e.g., Ragozzine & Holman 2010, Tremaine & Dong 2011), we have constructed an efficient, analytical algorithm which, given a collection of conjectured exoplanets orbiting a star, computes the probability that any particular group of exoplanets are transiting. The algorithm applies theorems of elementary differential geometry to compute the areas bounded by circular curves on the surface of a sphere (see Ragozzine & Holman 2010). The implemented algorithm is more accurate and orders of magnitude faster than previous algorithms, based on comparison with Monte Carlo simulations. Expanding this work, we have also developed semi-analytical methods for determining the frequency of exoplanet mutual events, i.e., the geometric probability two planets will transit each other (Planet-Planet Occultation) and the probability that this transit occurs simultaneously as they transit their star (Overlapping Double Transits; see Ragozzine & Holman 2010). The latter algorithm can also be applied to calculating the probability of observing transiting circumbinary planets (Doyle et al. 2011, Welsh et al. 2012). All of these algorithms have been coded in C and will be made publicly available. We will present and advertise these codes and illustrate their value for studying exoplanetary systems.
12 CFR Appendix A to Part 239 - Mutual Holding Company Model Charter
Code of Federal Regulations, 2014 CFR
2014-01-01
... 12 Banks and Banking 4 2014-01-01 2014-01-01 false Mutual Holding Company Model Charter A Appendix... RESERVE SYSTEM (CONTINUED) MUTUAL HOLDING COMPANIES (REGULATION MM) Pt. 239, App. A Appendix A to Part 239—Mutual Holding Company Model Charter FEDERAL MUTUAL HOLDING COMPANY CHARTER Section 1: Corporate...
12 CFR >appendix A to Part 239 - Mutual Holding Company Model Charter
Code of Federal Regulations, 2013 CFR
2013-01-01
... 12 Banks and Banking 4 2013-01-01 2013-01-01 false Mutual Holding Company Model Charter A... FEDERAL RESERVE SYSTEM (CONTINUED) MUTUAL HOLDING COMPANIES (REGULATION MM) Pt. 239, App. A >Appendix A to Part 239—Mutual Holding Company Model Charter FEDERAL MUTUAL HOLDING COMPANY CHARTER Section...
12 CFR Appendix C to Part 239 - Mutual Holding Company Model Bylaws
Code of Federal Regulations, 2012 CFR
2012-01-01
... 12 Banks and Banking 4 2012-01-01 2012-01-01 false Mutual Holding Company Model Bylaws C Appendix... RESERVE SYSTEM (CONTINUED) MUTUAL HOLDING COMPANIES (REGULATION MM) Pt. 239, App. C Appendix C to Part 239—Mutual Holding Company Model Bylaws MODEL BYLAWS FOR MUTUAL HOLDING COMPANIES The term “trustees” may...
12 CFR Appendix A to Part 239 - Mutual Holding Company Model Charter
Code of Federal Regulations, 2012 CFR
2012-01-01
... 12 Banks and Banking 4 2012-01-01 2012-01-01 false Mutual Holding Company Model Charter A Appendix... RESERVE SYSTEM (CONTINUED) MUTUAL HOLDING COMPANIES (REGULATION MM) Pt. 239, App. A Appendix A to Part 239—Mutual Holding Company Model Charter FEDERAL MUTUAL HOLDING COMPANY CHARTER Section 1: Corporate...
12 CFR Appendix C to Part 239 - Mutual Holding Company Model Bylaws
Code of Federal Regulations, 2013 CFR
2013-01-01
... 12 Banks and Banking 4 2013-01-01 2013-01-01 false Mutual Holding Company Model Bylaws C Appendix... RESERVE SYSTEM (CONTINUED) MUTUAL HOLDING COMPANIES (REGULATION MM) Pt. 239, App. C Appendix C to Part 239—Mutual Holding Company Model Bylaws MODEL BYLAWS FOR MUTUAL HOLDING COMPANIES The term “trustees” may...
12 CFR Appendix C to Part 239 - Mutual Holding Company Model Bylaws
Code of Federal Regulations, 2014 CFR
2014-01-01
... 12 Banks and Banking 4 2014-01-01 2014-01-01 false Mutual Holding Company Model Bylaws C Appendix... RESERVE SYSTEM (CONTINUED) MUTUAL HOLDING COMPANIES (REGULATION MM) Pt. 239, App. C Appendix C to Part 239—Mutual Holding Company Model Bylaws MODEL BYLAWS FOR MUTUAL HOLDING COMPANIES The term “trustees” may...
Long-range RNA pairings contribute to mutually exclusive splicing.
Yue, Yuan; Yang, Yun; Dai, Lanzhi; Cao, Guozheng; Chen, Ran; Hong, Weiling; Liu, Baoping; Shi, Yang; Meng, Yijun; Shi, Feng; Xiao, Mu; Jin, Yongfeng
2016-01-01
Mutually exclusive splicing is an important means of increasing the protein repertoire, by which the Down's syndrome cell adhesion molecule (Dscam) gene potentially generates 38,016 different isoforms in Drosophila melanogaster. However, the regulatory mechanisms remain obscure due to the complexity of the Dscam exon cluster. Here, we reveal a molecular model for the regulation of the mutually exclusive splicing of the serpent pre-mRNA based on competition between upstream and downstream RNA pairings. Such dual RNA pairings confer fine tuning of the inclusion of alternative exons. Moreover, we demonstrate that the splicing outcome of alternative exons is mediated in relative pairing strength-correlated mode. Combined comparative genomics analysis and experimental evidence revealed similar bidirectional structural architectures in exon clusters 4 and 9 of the Dscam gene. Our findings provide a novel mechanistic framework for the regulation of mutually exclusive splicing and may offer potentially applicable insights into long-range RNA-RNA interactions in gene regulatory networks.
Occurrence and characteristics of mutual interference between LIDAR scanners
NASA Astrophysics Data System (ADS)
Kim, Gunzung; Eom, Jeongsook; Park, Seonghyeon; Park, Yongwan
2015-05-01
The LIDAR scanner is at the heart of object detection of the self-driving car. Mutual interference between LIDAR scanners has not been regarded as a problem because the percentage of vehicles equipped with LIDAR scanners was very rare. With the growing number of autonomous vehicle equipped with LIDAR scanner operated close to each other at the same time, the LIDAR scanner may receive laser pulses from other LIDAR scanners. In this paper, three types of experiments and their results are shown, according to the arrangement of two LIDAR scanners. We will show the probability that any LIDAR scanner will interfere mutually by considering spatial and temporal overlaps. It will present some typical mutual interference scenario and report an analysis of the interference mechanism.
Arrays of mutually coupled receiver coils: theory and application.
Wright, S M; Magin, R L; Kelton, J R
1991-01-01
Specialized receiver coils having a small sensitive region can provide an improvement in SNR for MR imaging and spectroscopy, at the expense of limiting the usable field of view. This work presents a technique for designing coil arrays that allows the size and location of the sensitive region to be selected remotely. Only one element of the coil array is directly connected to the receiver, allowing flexibility in system design and implementation. A method is presented for the analysis and design of mutually coupled coil arrays of any number of elements of arbitrary shape. The analysis includes mutual coupling effects between primary coils, to allow multiple primary coils to be used simultaneously. A controller system allows remote selection of the sensitive region and automatically matches the impedance of the array to the preamplifier. Results obtained using a mutually coupled coil array designed for spine imaging are shown.
Homosexual mutuality: variation on a theme by Erik Erikson.
Sohier, R
The exploratory descriptive study described here was conducted in order to produce the initial empirical evidence to support reformulation of the theoretical construct of heterosexual mutuality (Erikson, 1975). Six persons were interviewed in depth on tape in order to locate them on one of four identity statuses constructed by Marcia (1964, 1966, 1973). The tool was modified and extended to meet the purposes of the study. The questions are directed toward illumination of conflictual moments in the life cycle when the ability to make appropriate decisions engenders character growth, and supports the personality integration of adulthood. An ability to make decisions results in personality integration. The small study provides evidence that there exists a homosexual mutuality (contrary to Erikson's position) which is no less valuable than heterosexual mutuality, and forms an equal basis for adult personality integration.
Empirical study of the tails of mutual fund size
NASA Astrophysics Data System (ADS)
Schwarzkopf, Yonathan; Farmer, J. Doyne
2010-06-01
The mutual fund industry manages about a quarter of the assets in the U.S. stock market and thus plays an important role in the U.S. economy. The question of how much control is concentrated in the hands of the largest players is best quantitatively discussed in terms of the tail behavior of the mutual fund size distribution. We study the distribution empirically and show that the tail is much better described by a log-normal than a power law, indicating less concentration than, for example, personal income. The results are highly statistically significant and are consistent across fifteen years. This contradicts a recent theory concerning the origin of the power law tails of the trading volume distribution. Based on the analysis in a companion paper, the log-normality is to be expected, and indicates that the distribution of mutual funds remains perpetually out of equilibrium.
Ma, Jingjing; Liu, Jie; Ma, Wenping; Gong, Maoguo; Jiao, Licheng
2014-01-01
Community structure is one of the most important properties in social networks. In dynamic networks, there are two conflicting criteria that need to be considered. One is the snapshot quality, which evaluates the quality of the community partitions at the current time step. The other is the temporal cost, which evaluates the difference between communities at different time steps. In this paper, we propose a decomposition-based multiobjective community detection algorithm to simultaneously optimize these two objectives to reveal community structure and its evolution in dynamic networks. It employs the framework of multiobjective evolutionary algorithm based on decomposition to simultaneously optimize the modularity and normalized mutual information, which quantitatively measure the quality of the community partitions and temporal cost, respectively. A local search strategy dealing with the problem-specific knowledge is incorporated to improve the effectiveness of the new algorithm. Experiments on computer-generated and real-world networks demonstrate that the proposed algorithm can not only find community structure and capture community evolution more accurately, but also be steadier than the two compared algorithms. PMID:24723806
Zen and the brain: mutually illuminating topics.
Austin, James H
2013-10-24
Zen Buddhist meditative practices emphasize the long-term, mindful training of attention and awareness during one's ordinary daily-life activities, the shedding of egocentric behaviors, and the skillful application of one's innate compassionate resources of insight-wisdom toward others and oneself. This review focuses on how such a comprehensive approach to training the brain could relate to a distinctive flavor of Zen: its emphasis on direct experience, with special reference to those major acute states of awakening that create deep transformations of consciousness and behavior. In Japanese, these advanced states are called kensho and satori. Ten key concepts are reviewed. They begin by distinguishing between the concentrative and receptive forms of meditation, noticing the complementary ways that they each train our normal "top-down" and "bottom-up" modes of attentive processing. Additional concepts distinguish between our two major processing pathways. The self-centered, egocentric frame of reference processes information in relation to our body (our soma) or to our mental functions (our psyche). The other-centered frame of reference processes information anonymously. Its prefix, allo- simply means "other" in Greek. Subsequent concepts consider how these useful Greek words-ego/allo, soma/psyche-correlate with the normal functional anatomy of important thalamo ↔ cortical connections. A plausible model then envisions how a triggering stimulus that captures attention could prompt the reticular nucleus to release GABA; how its selective inhibition of the dorsal thalamus could then block both our higher somatic and psychic cortical functions; so as to: (a) delete the maladaptive aspects of selfhood, while also (b) releasing the direct, all-inclusive, globally-unified experience of other. Two final concepts consider how the long-term meditative training of intuitive functions relates to certain kinds of word-free spatial tasks that involve insightful creative
Zen and the brain: mutually illuminating topics
Austin, James H.
2013-01-01
Zen Buddhist meditative practices emphasize the long-term, mindful training of attention and awareness during one's ordinary daily-life activities, the shedding of egocentric behaviors, and the skillful application of one's innate compassionate resources of insight-wisdom toward others and oneself. This review focuses on how such a comprehensive approach to training the brain could relate to a distinctive flavor of Zen: its emphasis on direct experience, with special reference to those major acute states of awakening that create deep transformations of consciousness and behavior. In Japanese, these advanced states are called kensho and satori. Ten key concepts are reviewed. They begin by distinguishing between the concentrative and receptive forms of meditation, noticing the complementary ways that they each train our normal “top–down” and “bottom–up” modes of attentive processing. Additional concepts distinguish between our two major processing pathways. The self-centered, egocentric frame of reference processes information in relation to our body (our soma) or to our mental functions (our psyche). The other-centered frame of reference processes information anonymously. Its prefix, allo- simply means “other” in Greek. Subsequent concepts consider how these useful Greek words—ego/allo, soma/psyche—correlate with the normal functional anatomy of important thalamo ↔ cortical connections. A plausible model then envisions how a triggering stimulus that captures attention could prompt the reticular nucleus to release GABA; how its selective inhibition of the dorsal thalamus could then block both our higher somatic and psychic cortical functions; so as to: (a) delete the maladaptive aspects of selfhood, while also (b) releasing the direct, all-inclusive, globally-unified experience of other. Two final concepts consider how the long-term meditative training of intuitive functions relates to certain kinds of word-free spatial tasks that involve
Inclusive Flavour Tagging Algorithm
NASA Astrophysics Data System (ADS)
Likhomanenko, Tatiana; Derkach, Denis; Rogozhnikov, Alex
2016-10-01
Identifying the flavour of neutral B mesons production is one of the most important components needed in the study of time-dependent CP violation. The harsh environment of the Large Hadron Collider makes it particularly hard to succeed in this task. We present an inclusive flavour-tagging algorithm as an upgrade of the algorithms currently used by the LHCb experiment. Specifically, a probabilistic model which efficiently combines information from reconstructed vertices and tracks using machine learning is proposed. The algorithm does not use information about underlying physics process. It reduces the dependence on the performance of lower level identification capacities and thus increases the overall performance. The proposed inclusive flavour-tagging algorithm is applicable to tag the flavour of B mesons in any proton-proton experiment.
Analysis of the Mutual Inductance Particle Velocimeter (MIPV)
1974-11-01
yKeU’v-T-.-’j-i^fi.T mmmmmm AD/A-004 219 ANALYSIS OF THE MUTUAL INDUCTANCE PARTICLE VELOCIMETER (MIPV) Joseph D. Renick Air Force...REPORT DOCUMENTATION PAGE 1. REPORT NUMBER AFWL-TR-74-205 2. GOVT ACCESSION NO 4. TITLE fand SubtUU.) ANALYSIS OF THE MUTUAL INDUCTANCE...Resistance as a Function of Stress for Several Metals 109 C-2 Geometry for One-Dimensional Shock Response Analysis HI C-3 Shock Equilibration of
Analysis and Synthesis of Microstrip Antennas Including Mutual Coupling
1988-09-01
E N 11. TITLE (/b*I* Secwfty OuodlCaUOn~) Analysis and Synthesis of Microstrip Antennas Including Mutual Coupling 12. PERSONAL AUTHOR(S) K~oichiro...GROUP SUB-GROUP Array Antennas, Microstrip Antennas, Array Analysis, Array Synthesis, Array Theory, Microwave Network Analysi! 19. ABSTRACT (Continue...VIRGI-J~NIA TECH ANALYSIS AND SYNTHESIS OF [. MICROSTRIP ANTENNAS INCLUDING MUTUAL COUPLING o0000 0 0 a o 0 0 0 0 0 o 0 00 0 00 o00000 0o000 0 0 0 a 0 0 0o
Separability criteria via sets of mutually unbiased measurements.
Liu, Lu; Gao, Ting; Yan, Fengli
2015-08-17
Mutually unbiased measurements (MUMs) are generalized from the concept of mutually unbiased bases (MUBs) and include the complete set of MUBs as a special case, but they are superior to MUBs as they do not need to be rank one projectors. We investigate entanglement detection using sets of MUMs and derive separability criteria for multipartite qudit systems, arbitrary high-dimensional bipartite systems of a d1-dimensional subsystem and a d2-dimensional subsystem, and multipartite systems of multi-level subsystems. These criteria are of the advantages of more effective and wider application range than previous criteria. They provide experimental implementation in detecting entanglement of unknown quantum states.
Synchronization and time shifts of dynamical patterns for mutually delay-coupled fiber ring lasers.
Shaw, Leah B; Schwartz, Ira B; Rogers, Elizabeth A; Roy, Rajarshi
2006-03-01
A pair of coupled erbium doped fiber ring lasers is used to explore the dynamics of coupled spatiotemporal systems. The lasers are mutually coupled with a coupling delay less than the cavity round-trip time. We study synchronization between the two lasers in the experiment and in a delay differential equation model of the system. Because the lasers are internally perturbed by spontaneous emission, we include a noise source in the model to obtain stochastic realizations of the deterministic equations. Both amplitude synchronization and phase synchronization are considered. We use the Hilbert transform to define the phase variable and compute phase synchronization. We find that synchronization increases with coupling strength in the experiment and the model. When the time series from two lasers are time shifted in either direction by the delay time, approximately equal synchronization is frequently observed, so that a clear leader and follower cannot be identified. We define an algorithm to determine which laser leads the other when the synchronization is sufficiently different with one direction of time shift, and statistics of switches in leader and follower are studied. The frequency of switching between leader and follower increases with coupling strength, as might be expected since the lasers mutually influence each other more effectively with stronger coupling.
Intention-Disguised Algorithmic Trading
NASA Astrophysics Data System (ADS)
Yuen, William; Syverson, Paul; Liu, Zhenming; Thorpe, Christopher
Large market participants (LMPs) must often execute trades while keeping their intentions secret. Sometimes secrecy is required before trades are completed to prevent other traders from anticipating (and exploiting) the price impact of their trades. This is known as "front-running". In other cases, LMPs with proprietary trading strategies wish to keep their positions secret even after trading because their strategies and positions contain valuable information. LMPs include hedge funds, mutual funds, and other specialized market players.
Kelley, Brendan P; Klochko, Chad; Halabi, Safwan; Siegal, Daniel
2016-06-01
Retrospective data mining has tremendous potential in research but is time and labor intensive. Current data mining software contains many advanced search features but is limited in its ability to identify patients who meet multiple complex independent search criteria. Simple keyword and Boolean search techniques are ineffective when more complex searches are required, or when a search for multiple mutually inclusive variables becomes important. This is particularly true when trying to identify patients with a set of specific radiologic findings or proximity in time across multiple different imaging modalities. Another challenge that arises in retrospective data mining is that much variation still exists in how image findings are described in radiology reports. We present an algorithmic approach to solve this problem and describe a specific use case scenario in which we applied our technique to a real-world data set in order to identify patients who matched several independent variables in our institution's picture archiving and communication systems (PACS) database.
A Mutual Support Group for Young Problem Gamblers
ERIC Educational Resources Information Center
Binde, Per
2012-01-01
A Swedish mutual support group for young problem gamblers is described and discussed. During the study period, 116 weekly meetings occurred, usually involving six to ten participants; in total, 69 problem gamblers (66 male and three female), aged 17-25, and 23 partners and friends attended the meetings. Half the gamblers had problems with Internet…
77 FR 48566 - The Hartford Mutual Funds, Inc., et al.;
Federal Register 2010, 2011, 2012, 2013, 2014
2012-08-14
... From the Federal Register Online via the Government Publishing Office SECURITIES AND EXCHANGE COMMISSION The Hartford Mutual Funds, Inc., et al.; Notice of Application August 8, 2012. AGENCY: Securities and Exchange Commission (``Commission''). ACTION: Notice of an application under section 6(c) of...
47 CFR 101.45 - Mutually exclusive applications.
Code of Federal Regulations, 2014 CFR
2014-10-01
... SERVICES FIXED MICROWAVE SERVICES Applications and Licenses Processing of Applications § 101.45 Mutually... fixed point-to-point microwave applications for authorization under this part will be entitled to... not available in other bands. During the initial filing window, frequency coordination is not...
47 CFR 101.45 - Mutually exclusive applications.
Code of Federal Regulations, 2013 CFR
2013-10-01
... SERVICES FIXED MICROWAVE SERVICES Applications and Licenses Processing of Applications § 101.45 Mutually... fixed point-to-point microwave applications for authorization under this part will be entitled to... not available in other bands. During the initial filing window, frequency coordination is not...
47 CFR 101.45 - Mutually exclusive applications.
Code of Federal Regulations, 2012 CFR
2012-10-01
... SERVICES FIXED MICROWAVE SERVICES Applications and Licenses Processing of Applications § 101.45 Mutually... fixed point-to-point microwave applications for authorization under this part will be entitled to... not available in other bands. During the initial filing window, frequency coordination is not...
47 CFR 101.45 - Mutually exclusive applications.
Code of Federal Regulations, 2011 CFR
2011-10-01
... SERVICES FIXED MICROWAVE SERVICES Applications and Licenses Processing of Applications § 101.45 Mutually... fixed point-to-point microwave applications for authorization under this part will be entitled to... not available in other bands. During the initial filing window, frequency coordination is not...
47 CFR 101.45 - Mutually exclusive applications.
Code of Federal Regulations, 2010 CFR
2010-10-01
... SERVICES FIXED MICROWAVE SERVICES Applications and Licenses Processing of Applications § 101.45 Mutually... fixed point-to-point microwave applications for authorization under this part will be entitled to... not available in other bands. During the initial filing window, frequency coordination is not...