MIRA: mutual information-based reporter algorithm for metabolic networks
Cicek, A. Ercument; Roeder, Kathryn; Ozsoyoglu, Gultekin
2014-01-01
Motivation: Discovering the transcriptional regulatory architecture of the metabolism has been an important topic to understand the implications of transcriptional fluctuations on metabolism. The reporter algorithm (RA) was proposed to determine the hot spots in metabolic networks, around which transcriptional regulation is focused owing to a disease or a genetic perturbation. Using a z-score-based scoring scheme, RA calculates the average statistical change in the expression levels of genes that are neighbors to a target metabolite in the metabolic network. The RA approach has been used in numerous studies to analyze cellular responses to the downstream genetic changes. In this article, we propose a mutual information-based multivariate reporter algorithm (MIRA) with the goal of eliminating the following problems in detecting reporter metabolites: (i) conventional statistical methods suffer from small sample sizes, (ii) as z-score ranges from minus to plus infinity, calculating average scores can lead to canceling out opposite effects and (iii) analyzing genes one by one, then aggregating results can lead to information loss. MIRA is a multivariate and combinatorial algorithm that calculates the aggregate transcriptional response around a metabolite using mutual information. We show that MIRA’s results are biologically sound, empirically significant and more reliable than RA. Results: We apply MIRA to gene expression analysis of six knockout strains of Escherichia coli and show that MIRA captures the underlying metabolic dynamics of the switch from aerobic to anaerobic respiration. We also apply MIRA to an Autism Spectrum Disorder gene expression dataset. Results indicate that MIRA reports metabolites that highly overlap with recently found metabolic biomarkers in the autism literature. Overall, MIRA is a promising algorithm for detecting metabolic drug targets and understanding the relation between gene expression and metabolic activity. Availability and
Mutual information image registration based on improved bee evolutionary genetic algorithm
NASA Astrophysics Data System (ADS)
Xu, Gang; Tu, Jingzhi
2009-07-01
In recent years, the mutual information is regarded as a more efficient similarity metrics in the image registration. According to the features of mutual information image registration, the Bee Evolution Genetic Algorithm (BEGA) is chosen for optimizing parameters, which imitates swarm mating. Besides, we try our best adaptively set the initial parameters to improve the BEGA. The programming result shows the wonderful precision of the algorithm.
IR and visual image registration based on mutual information and PSO-Powell algorithm
NASA Astrophysics Data System (ADS)
Zhuang, Youwen; Gao, Kun; Miu, Xianghu
2014-11-01
Infrared and visual image registration has a wide application in the fields of remote sensing and military. Mutual information (MI) has proved effective and successful in infrared and visual image registration process. To find the most appropriate registration parameters, optimal algorithms, such as Particle Swarm Optimization (PSO) algorithm or Powell search method, are often used. The PSO algorithm has strong global search ability and search speed is fast at the beginning, while the weakness is low search performance in late search stage. In image registration process, it often takes a lot of time to do useless search and solution's precision is low. Powell search method has strong local search ability. However, the search performance and time is more sensitive to initial values. In image registration, it is often obstructed by local maximum and gets wrong results. In this paper, a novel hybrid algorithm, which combined PSO algorithm and Powell search method, is proposed. It combines both advantages that avoiding obstruction caused by local maximum and having higher precision. Firstly, using PSO algorithm gets a registration parameter which is close to global minimum. Based on the result in last stage, the Powell search method is used to find more precision registration parameter. The experimental result shows that the algorithm can effectively correct the scale, rotation and translation additional optimal algorithm. It can be a good solution to register infrared difference of two images and has a greater performance on time and precision than traditional and visible images.
NASA Astrophysics Data System (ADS)
Zhang, Hong; Sun, Yanfeng; Zhai, Bing; Wang, Yiding
2013-07-01
This paper studies on the image registration of the medical images. Wavelet transform is adopted to decompose the medical images because the resolution of the medical image is high and the computational amount of the registration is large. Firstly, the low frequency sub-images are matched. Then source images are matched. The image registration was fulfilled by the ant colony optimization algorithm to search the extremum of the mutual information. The experiment result demonstrates the proposed approach can not only reduce calculation amount, but also skip from the local extremum during optimization process, and search the optimization value.
Research on non rigid registration algorithm of DCE-MRI based on mutual information and optical flow
NASA Astrophysics Data System (ADS)
Yu, Shihua; Wang, Rui; Wang, Kaiyu; Xi, Mengmeng; Zheng, Jiashuo; Liu, Hui
2015-07-01
Image matching plays a very important role in the field of medical image, while the two image registration methods based on the mutual information and the optical flow are very effective. The experimental results show that the two methods have their prominent advantages. The method based on mutual information is good for the overall displacement, while the method based on optical flow is very sensitive to small deformation. In the breast DCE-MRI images studied in this paper, there is not only overall deformation caused by the patient, but also non rigid small deformation caused by respiratory deformation. In view of the above situation, the single-image registration algorithms cannot meet the actual needs of complex situations. After a comprehensive analysis to the advantages and disadvantages of these two methods, this paper proposes a registration algorithm of combining mutual information with optical flow field, and applies subtraction images of the reference image and the floating image as the main criterion to evaluate the registration effect, at the same time, applies the mutual information between image sequence values as auxiliary criterion. With the test of the example, this algorithm has obtained a better accuracy and reliability in breast DCE-MRI image sequences.
Hierarchical clustering using mutual information
NASA Astrophysics Data System (ADS)
Kraskov, A.; Stögbauer, H.; Andrzejak, R. G.; Grassberger, P.
2005-04-01
We present a conceptually simple method for hierarchical clustering of data called mutual information clustering (MIC) algorithm. It uses mutual information (MI) as a similarity measure and exploits its grouping property: The MI between three objects X, Y, and Z is equal to the sum of the MI between X and Y, plus the MI between Z and the combined object (XY). We use this both in the Shannon (probabilistic) version of information theory and in the Kolmogorov (algorithmic) version. We apply our method to the construction of phylogenetic trees from mitochondrial DNA sequences and to the output of independent components analysis (ICA) as illustrated with the ECG of a pregnant woman.
Estimating mutual information.
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 mu(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 M(X,Y) vanishes (up to statistical fluctuations) if mu(x,y)=mu(x)mu(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. PMID:15244698
Mutual information in classical spin models
NASA Astrophysics Data System (ADS)
Wilms, Johannes; Troyer, Matthias; Verstraete, Frank
2011-10-01
The total many-body correlations present in finite temperature classical spin systems are studied using the concept of mutual information. As opposed to zero-temperature quantum phase transitions, the total correlations are not maximal at the phase transition, but reach a maximum in the high-temperature paramagnetic phase. The Shannon mutual information and the Renyi mutual information in both Ising and Potts models in two dimensions are calculated numerically by combining matrix product state algorithms and Monte Carlo sampling techniques.
Quantum algorithm for SAT problem andquantum mutual entropy
NASA Astrophysics Data System (ADS)
Ohya, Masanori
2005-02-01
It is von Neumann who opened the window for today's information epoch. He definedquantum entropy including Shannon's information more than 20 years ahead of Shannon, and he explained what computation means mathematically. In this paper I discuss two problems studied recently by me and my coworkers. One of them concerns a quantum algorithm in a generalized sense solving the SAT problem (one of NP complete problems) and another concerns quantum mutual entropy properly describing quantum communication processes.
Mutual information analysis of JPEG2000 contexts
NASA Astrophysics Data System (ADS)
Liu, Zhen; Karam, Lina J.
2003-05-01
Context-based arithmetic coding has been widely adopted in image and video compression and is a key component of the new JPEG2000 image compression standard. In this paper, the contexts used in JPEG2000 are analyzed using the mutual information, which has a direct link with the compression performance. We first show that, when combining the contexts, the mutual information between the contexts and the encoded data will decrease unless the conditional probability distributions of the combined contexts are the same. Given I, the initial number of contexts, and F, the final desired number of contexts, there are S(I, F) possible context classification schemes where S(I, F) is called the Stirling number of the second kind. The optimal classification scheme is the one that gives the maximum mutual information. Instead of exhaustive search, the optimal classification scheme can be obtained through a modified Generalized Lloyd algorithm with the relative entropy as the distortion metric. For binary arithmetic coding, the search complexity can be reduced by using the dynamic programming. Our experimental results show that the JPEG2000 contexts capture very well the correlations among the wavelet coefficients. At the same time, the number of contexts used as part of the standard can be reduced without loss in the coding performance.
Generalized mutual information and Tsirelson's bound
Wakakuwa, Eyuri; Murao, Mio
2014-12-04
We introduce a generalization of the quantum mutual information between a classical system and a quantum system into the mutual information between a classical system and a system described by general probabilistic theories. We apply this generalized mutual information (GMI) to a derivation of Tsirelson's bound from information causality, and prove that Tsirelson's bound can be derived from the chain rule of the GMI. By using the GMI, we formulate the 'no-supersignalling condition' (NSS), that the assistance of correlations does not enhance the capability of classical communication. We prove that NSS is never violated in any no-signalling theory.
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.
Distribution of Mutual Information in Multipartite States
NASA Astrophysics Data System (ADS)
Maziero, Jonas
2014-06-01
Using the relative entropy of total correlation, we derive an expression relating the mutual information of n-partite pure states to the sum of the mutual informations and entropies of its marginals and analyze some of its implications. Besides, by utilizing the extended strong subadditivity of von Neumann entropy, we obtain generalized monogamy relations for the total correlation in three-partite mixed states. These inequalities lead to a tight lower bound for this correlation in terms of the sum of the bipartite mutual informations. We use this bound to propose a measure for residual three-partite total correlation and discuss the non-applicability of this kind of quantifier to measure genuine multiparty correlations.
Efficient algorithm to compute mutually connected components in interdependent networks.
Hwang, S; Choi, S; Lee, Deokjae; Kahng, B
2015-02-01
Mutually connected components (MCCs) play an important role as a measure of resilience in the study of interdependent networks. Despite their importance, an efficient algorithm to obtain the statistics of all MCCs during the removal of links has thus far been absent. Here, using a well-known fully dynamic graph algorithm, we propose an efficient algorithm to accomplish this task. We show that the time complexity of this algorithm is approximately O(N(1.2)) for random graphs, which is more efficient than O(N(2)) of the brute-force algorithm. We confirm the correctness of our algorithm by comparing the behavior of the order parameter as links are removed with existing results for three types of double-layer multiplex networks. We anticipate that this algorithm will be used for simulations of large-size systems that have been previously inaccessible. PMID:25768559
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.
Problem decomposition by mutual information and force-based clustering
NASA Astrophysics Data System (ADS)
Otero, Richard Edward
alternative global optimizer, called MIMIC, which is unrelated to Genetic Algorithms. Advancement to the current practice demonstrates the use of MIMIC as a global method that explicitly models problem structure with mutual information, providing an alternate method for globally searching multi-modal domains. By leveraging discovered problem inter- dependencies, MIMIC may be appropriate for highly coupled problems or those with large function evaluation cost. This work introduces a useful addition to the MIMIC algorithm that enables its use on continuous input variables. By leveraging automatic decision tree generation methods from Machine Learning and a set of randomly generated test problems, decision trees for which method to apply are also created, quantifying decomposition performance over a large region of the design space.
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.
An efficient algorithm for direction finding against unknown mutual coupling.
Wang, Weijiang; Ren, Shiwei; Ding, Yingtao; Wang, Haoyu
2014-01-01
In this paper, an algorithm of direction finding is proposed in the presence of unknown mutual coupling. The preliminary direction of arrival (DOA) is estimated using the whole array for high resolution. Further refinement can then be conducted by estimating the angularly dependent coefficients (ADCs) with the subspace theory. The mutual coupling coefficients are finally determined by solving the least squares problem with all of the ADCs utilized without discarding any. Simulation results show that the proposed method can achieve better performance at a low signal-to-noise ratio (SNR) with a small-sized array and is more robust, compared with the similar processes employing the initial DOA estimation and further improvement iteratively. PMID:25347587
An Efficient Algorithm for Direction Finding against Unknown Mutual Coupling
Wang, Weijiang; Ren, Shiwei; Ding, Yingtao; Wang, Haoyu
2014-01-01
In this paper, an algorithm of direction finding is proposed in the presence of unknown mutual coupling. The preliminary direction of arrival (DOA) is estimated using the whole array for high resolution. Further refinement can then be conducted by estimating the angularly dependent coefficients (ADCs) with the subspace theory. The mutual coupling coefficients are finally determined by solving the least squares problem with all of the ADCs utilized without discarding any. Simulation results show that the proposed method can achieve better performance at a low signal-to-noise ratio (SNR) with a small-sized array and is more robust, compared with the similar processes employing the initial DOA estimation and further improvement iteratively. PMID:25347587
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. PMID:25881367
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.
Glacier Surface Monitoring by Maximizing Mutual Information
NASA Astrophysics Data System (ADS)
Erten, E.; Rossi, C.; Hajnsek, I.
2012-07-01
The contribution of Polarimetric Synthetic Aperture Radar (PolSAR) images compared with the single-channel SAR in terms of temporal scene characterization has been found and described to add valuable information in the literature. However, despite a number of recent studies focusing on single polarized glacier monitoring, the potential of polarimetry to estimate the surface velocity of glaciers has not been explored due to the complex mechanism of polarization through glacier/snow. In this paper, a new approach to the problem of monitoring glacier surface velocity is proposed by means of temporal PolSAR images, using a basic concept from information theory: Mutual Information (MI). The proposed polarimetric tracking method applies the MI to measure the statistical dependence between temporal polarimetric images, which is assumed to be maximal if the images are geometrically aligned. Since the proposed polarimetric tracking method is very powerful and general, it can be implemented into any kind of multivariate remote sensing data such as multi-spectral optical and single-channel SAR images. The proposed polarimetric tracking is then used to retrieve surface velocity of Aletsch glacier located in Switzerland and of Inyltshik glacier in Kyrgyzstan with two different SAR sensors; Envisat C-band (single polarized) and DLR airborne L-band (fully polarimetric) systems, respectively. The effect of number of channel (polarimetry) into tracking investigations demonstrated that the presence of snow, as expected, effects the location of the phase center in different polarization, such as glacier tracking with temporal HH compared to temporal VV channels. Shortly, a change in polarimetric signature of the scatterer can change the phase center, causing a question of how much of what I am observing is motion then penetration. In this paper, it is shown that considering the multi-channel SAR statistics, it is possible to optimize the separate these contributions.
Mutual information-based LPI optimisation for radar network
NASA Astrophysics Data System (ADS)
Shi, Chenguang; Zhou, Jianjiang; Wang, Fei; Chen, Jun
2015-07-01
Radar network can offer significant performance improvement for target detection and information extraction employing spatial diversity. For a fixed number of radars, the achievable mutual information (MI) for estimating the target parameters may extend beyond a predefined threshold with full power transmission. In this paper, an effective low probability of intercept (LPI) optimisation algorithm is presented to improve LPI performance for radar network. Based on radar network system model, we first provide Schleher intercept factor for radar network as an optimisation metric for LPI performance. Then, a novel LPI optimisation algorithm is presented, where for a predefined MI threshold, Schleher intercept factor for radar network is minimised by optimising the transmission power allocation among radars in the network such that the enhanced LPI performance for radar network can be achieved. The genetic algorithm based on nonlinear programming (GA-NP) is employed to solve the resulting nonconvex and nonlinear optimisation problem. Some simulations demonstrate that the proposed algorithm is valuable and effective to improve the LPI performance for radar network.
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
[Human cerebral image registration using generalized mutual information].
Zhang, Jingzhou; Li, Ting; Zhang, Jia
2008-12-01
Medical image registration is a highlight of actual research on medical image processing. Based onsimilarity measure of Shannon entropy, a new generalized distance measurement based on Rényi entropy applied to image rigid registration is introduced and is called here generalized mutual information (GMI). It is used in three dimensional cerebral image registration experiments. The simulation results show that generalized distance measurement and Shannon entropy measurement apply to different areas; that the registration measure based o n generalized distance is a natural extension of mutual information of Shannon entropy. The results prove that generalized mutual information uses less time than simple mutual information does, and the new similarity measure manifests higher degree of consistency between the two cerebral registration images. Also, the registration results provide the clinical diagnoses with more important references. In conclusion, generalized mutual information has satisfied the demands of clinical application to a wide extent. PMID:19166197
Mutual information between SSH and SST fields
NASA Astrophysics Data System (ADS)
Le goff, Clément; Chapron, Bertrand; Fablet, Ronan; Tandeo, Pierre; Autret, Emmanuelle; Ailliot, Pierre
2015-04-01
Mutual information between SST and SSH Investigations to relate satellite SST and SSH measurements in the Agulhas return current region are presented. In this study, we focus on the use of SSH and SST maps obtained during the year 2004, corresponding to a particularly well-sampled period for altimetry. The SST and SSH anomalies are then obtained as high-pass filtered fields, to analyze scales smaller than approximately 300km. As revealed, we clearly distinguish different regimes. During the winter months, a marked strong correlation between fields of SSH and SST anomalies is clearly revealed. During the summer months, a much lower correlation is found. Further conditioning the analysis to separate the areas of positive and negative SSH anomalies, it is then obtained, for both summer and winter periods, that aeras of negative SSH anomalies always correspond with areas of negative SST anomalies. This high correspondance also applies in winter but only for areas of positive SSH anomalies, which indeed well match with areas of positive SST anomalies. In summer, this high correspondance is lost, and areas with positive SSH anomalies do not necessarily correspond to positive SST anomalies. Accordingly, such an effect affects and weakens the overall SST/SSH correlation during the summer months. Yet, the areas of positive SSH anomalies are not fully disconnected from the areas of positive SST anomalies. For these cases, observations and results demonstrate a systematic spatial shift between them. This suggests the influence of the mixed layer depth and wind speed to control the spatial correspondance between SST and SSH anomalies, especially below regions of positive SSH anomalies. In such cases, the upper layer SST anomalies are certainly advected by the interior flow to also provide means to relate surface observations and interior dynamics.
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)
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.
Quantum Conditional Mutual Information, Reconstructed States, and State Redistribution.
Brandão, Fernando G S L; Harrow, Aram W; Oppenheim, Jonathan; Strelchuk, Sergii
2015-07-31
We give two strengthenings of an inequality for the quantum conditional mutual information of a tripartite quantum state recently proved by Fawzi and Renner, connecting it with the ability to reconstruct the state from its bipartite reductions. Namely, we show that the conditional mutual information is an upper bound on the regularized relative entropy distance between the quantum state and its reconstructed version. It is also an upper bound for the measured relative entropy distance of the state to its reconstructed version. The main ingredient of the proof is the fact that the conditional mutual information is the optimal quantum communication rate in the task of state redistribution. PMID:26274402
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.
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. PMID:26764762
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.
Model term selection for spatio-temporal system identification using mutual information
NASA Astrophysics Data System (ADS)
Wang, Shu; Wei, Hua-Liang; Coca, Daniel; Billings, Stephen A.
2013-02-01
A new mutual information based algorithm is introduced for term selection in spatio-temporal models. A generalised cross validation procedure is also introduced for model length determination and examples based on cellular automata, coupled map lattice and partial differential equations are described.
Rényi generalizations of the conditional quantum mutual information
Berta, Mario; Seshadreesan, Kaushik P.; Wilde, Mark M.
2015-02-15
The conditional quantum mutual information I(A; B|C) of a tripartite state ρ{sub ABC} is an information quantity which lies at the center of many problems in quantum information theory. Three of its main properties are that it is non-negative for any tripartite state, that it decreases under local operations applied to systems A and B, and that it obeys the duality relation I(A; B|C) = I(A; B|D) for a four-party pure state on systems ABCD. The conditional mutual information also underlies the squashed entanglement, an entanglement measure that satisfies all of the axioms desired for an entanglement measure. As such, it has been an open question to find Rényi generalizations of the conditional mutual information, that would allow for a deeper understanding of the original quantity and find applications beyond the traditional memoryless setting of quantum information theory. The present paper addresses this question, by defining different α-Rényi generalizations I{sub α}(A; B|C) of the conditional mutual information, some of which we can prove converge to the conditional mutual information in the limit α → 1. Furthermore, we prove that many of these generalizations satisfy non-negativity, duality, and monotonicity with respect to local operations on one of the systems A or B (with it being left as an open question to prove that monotonicity holds with respect to local operations on both systems). The quantities defined here should find applications in quantum information theory and perhaps even in other areas of physics, but we leave this for future work. We also state a conjecture regarding the monotonicity of the Rényi conditional mutual informations defined here with respect to the Rényi parameter α. We prove that this conjecture is true in some special cases and when α is in a neighborhood of one.
Quadratic mutual information for dimensionality reduction and classification
NASA Astrophysics Data System (ADS)
Gray, David M.; Principe, José C.
2010-04-01
A research area based on the application of information theory to machine learning has attracted considerable interest in the last few years. This research area has been coined information-theoretic learning within the community. In this paper we apply elements of information-theoretic learning to the problem of automatic target recognition (ATR). A number of researchers have previously shown the benefits of designing classifiers based on maximizing the mutual information between the class data and the class labels. Following prior research in information-theoretic learning, in the current results we show that quadratic mutual information, derived using a special case of the more general Renyi's entropy, can be used for classifier design. In this implementation, a simple subspace projection classifier is formulated to find the optimal projection weights such that the quadratic mutual information between the class data and the class labels is maximized. This subspace projection accomplishes a dimensionality reduction of the raw data set wherein information about the class membership is retained while irrelevant information is discarded. A subspace projection based on this criterion preserves as much class discriminability as possible within the subspace. For this paper, laser radar images are used to demonstrate the results. Classification performance against this data set is compared for a gradient descent MLP classifier and a quadratic mutual information MLP classifier.
Thermalization of mutual information in hyperscaling violating backgrounds
NASA Astrophysics Data System (ADS)
Tanhayi, M. Reza
2016-03-01
We study certain features of scaling behaviors of the mutual information during a process of thermalization, more precisely we extend the time scaling behavior of mutual information which has been discussed in [1] to time-dependent hyperscaling violating geometries. We use the holographic description of entanglement entropy for two disjoint system consisting of two parallel strips whose widths are much larger than the separation between them. We show that during the thermalization process, the dynamical exponent plays a crucial rule in reading the general time scaling behavior of mutual information (e.g., at the pre-local-equilibration regime). It is shown that the scaling violating parameter can be employed to define an effective dimension.
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
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
Mutual Information for the Detection of Crush
Harding, Peter; Gwynne, Steve; Amos, Martyn
2011-01-01
Fatal crush conditions occur in crowds with tragic frequency. Event organizers and architects are often criticised for failing to consider the causes and implications of crush, but the reality is that both the prediction and prevention of such conditions offer a significant technical challenge. Full treatment of physical force within crowd simulations is precise but often computationally expensive; the more common method of human interpretation of results is computationally “cheap” but subjective and time-consuming. This paper describes an alternative method for the analysis of crowd behaviour, which uses information theory to measure crowd disorder. We show how this technique may be easily incorporated into an existing simulation framework, and validate it against an historical event. Our results show that this method offers an effective and efficient route towards automatic detection of the onset of crush. PMID:22229055
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-…
Two-Level Document Ranking Using Mutual Information in Natural Language Information Retrieval.
ERIC Educational Resources Information Center
Kang, Hyun-Kyu; Choi, Key-Sun
1997-01-01
Discussion of information retrieval and relevance focuses on mutual information, a measure which represents the relation between two words. A model of a natural-language information-retrieval system that is based on a two-level document-ranking method using mutual information is presented, and a Korean encyclopedia test collection is explained.…
On the Time Complexity of Dijkstra's Three-State Mutual Exclusion Algorithm
NASA Astrophysics Data System (ADS)
Kimoto, Masahiro; Tsuchiya, Tatsuhiro; Kikuno, Tohru
In this letter we give a lower bound on the worst-case time complexity of Dijkstra's three-state mutual exclusion algorithm by specifying a concrete behavior of the algorithm. We also show that our result is more accurate than the known best bound.
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.
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
Motion Estimation Based on Mutual Information and Adaptive Multi-Scale Thresholding.
Xu, Rui; Taubman, David; Naman, Aous Thabit
2016-03-01
This paper proposes a new method of calculating a matching metric for motion estimation. The proposed method splits the information in the source images into multiple scale and orientation subbands, reduces the subband values to a binary representation via an adaptive thresholding algorithm, and uses mutual information to model the similarity of corresponding square windows in each image. A moving window strategy is applied to recover a dense estimated motion field whose properties are explored. The proposed matching metric is a sum of mutual information scores across space, scale, and orientation. This facilitates the exploitation of information diversity in the source images. Experimental comparisons are performed amongst several related approaches, revealing that the proposed matching metric is better able to exploit information diversity, generating more accurate motion fields. PMID:26742132
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.
Scale-Space Mutual Information for Textural-Patterns Characterization
Seedahmed, Gamal H.; Ward, Andy L.
2005-08-22
The essence of image texture is typically understood by two aspects. First, within a texture-pattern there is a significant variation in intensity values between nearby pixels. Second, texture is a homogeneous property at some spatial scale larger than the spatial resolution of the image. Motivated by the essential aspects of image texture, this paper proposes a novel methodology that combines the use of scale-space and mutual information to characterize textural-patterns. Scale-space offers the mechanism for a multi-scale representation of the image, which will be used to address the scale aspect of texture. On the other hand, mutual information provides a measure to quantify the dependency relationship across the scale-space. It has been found that the proposed methodology has the potential to capture different properties of texture such as periodicity, scale, fineness, coarseness, and spatial extent or size. Practical examples are provided to demonstrate the applicability of the proposed methodology.
Entanglement entropy and mutual information in Bose-Einstein condensates
Ding Wenxin; Yang Kun
2009-07-15
In this paper we study the entanglement properties of free nonrelativistic Bose gases. At zero temperature, we calculate the bipartite block entanglement entropy of the system and find that it diverges logarithmically with the particle number in the subsystem. For finite temperatures, we study the mutual information between the two blocks. We first analytically study an infinite-range hopping model, then numerically study a set of long-range hopping models in one dimension that exhibit Bose-Einstein condensation. In both cases we find that a Bose-Einstein condensate, if present, makes a divergent contribution to the mutual information which is proportional to the logarithm of the number of particles in the condensate in the subsystem. The prefactor of the logarithmic divergent term is model dependent.
Mutual information as an order parameter for quantum synchronization
NASA Astrophysics Data System (ADS)
Ameri, V.; Eghbali-Arani, M.; Mari, A.; Farace, A.; Kheirandish, F.; Giovannetti, V.; Fazio, R.
2015-01-01
Spontaneous synchronization is a fundamental phenomenon, important in many theoretical studies and applications. Recently, this effect has been analyzed and observed in a number of physical systems close to the quantum-mechanical regime. In this work we propose mutual information as a useful order parameter which can capture the emergence of synchronization in very different contexts, ranging from semiclassical to intrinsically quantum-mechanical systems. Specifically, we first study the synchronization of two coupled Van der Pol oscillators in both classical and quantum regimes and later we consider the synchronization of two qubits inside two coupled optical cavities. In all these contexts, we find that mutual information can be used as an appropriate figure of merit for determining the synchronization phases independently of the specific details of the system.
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.
Part mutual information for quantifying direct associations in networks.
Zhao, Juan; Zhou, Yiwei; Zhang, Xiujun; Chen, Luonan
2016-05-01
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. PMID:27092000
Track-to-Track Data Association using Mutual Information
NASA Astrophysics Data System (ADS)
Hussein, I.; Roscoe, C.; Wilkins, M.; Schumacher, P.
In this paper, we build on recent work to further investigate the use of mutual information to solve various association problems in space situational awareness. Specifically, we solve the track-to-track association (TTTA) problem where we seek to associate a given set of tracks at one point in time with another set of tracks at a different time instance. Both sets of tracks are uncertain and are probabilistically described using multivariate normal distributions. This allows for a closed-form solution, based on the unscented transform and on mutual information. Future work will focus on developing a similar solution when uncertainty is analytic but not Gaussian or when it is completely non-analytic -e.g., when the uncertainty is described using a particle cloud. The proposed solution is inspired by a similar solution based on the unscented transform and mutual information for the observation-to-observation association (OTOA) problem that was developed by the authors in the past. This solution can be adjusted to address the classical observation-to-track association problem (OTTA), which will be the focus of future research. We will demonstrate the main result in simulation for LEO, MEO, GTO, and GEO orbit regimes to show general applicability.
Anisotropic magnetotelluric inversion using a mutual information constraint
NASA Astrophysics Data System (ADS)
Mandolesi, E.; Jones, A. G.
2012-12-01
In recent years, several authors pointed that the electrical conductivity of many subsurface structures cannot be described properly by a scalar field. With the development of field devices and techniques, data quality improved to the point that the anisotropy in conductivity of rocks (microscopic anisotropy) and tectonic structures (macroscopic anisotropy) cannot be neglected. Therefore a correct use of high quality data has to include electrical anisotropy and a correct interpretation of anisotropic data characterizes directly a non-negligible part of the subsurface. In this work we test an inversion routine that takes advantage of the classic Levenberg-Marquardt (LM) algorithm to invert magnetotelluric (MT) data generated from a bi-dimensional (2D) anisotropic domain. The LM method is routinely used in inverse problems due its performance and robustness. In non-linear inverse problems -such the MT problem- the LM method provides a spectacular compromise betwee quick and secure convergence at the price of the explicit computation and storage of the sensitivity matrix. Regularization in inverse MT problems has been used extensively, due to the necessity to constrain model space and to reduce the ill-posedness of the anisotropic MT problem, which makes MT inversions extremely challenging. In order to reduce non-uniqueness of the MT problem and to reach a model compatible with other different tomographic results from the same target region, we used a mutual information (MI) based constraint. MI is a basic quantity in information theory that can be used to define a metric between images, and it is routinely used in fields as computer vision, image registration and medical tomography, to cite some applications. We -thus- inverted for the model that best fits the anisotropic data and that is the closest -in a MI sense- to a tomographic model of the target area. The advantage of this technique is that the tomographic model of the studied region may be produced by any
Link Prediction in Complex Networks: A Mutual Information Perspective
Tan, Fei; Xia, Yongxiang; Zhu, Boyao
2014-01-01
Topological properties of networks are widely applied to study the link-prediction problem recently. Common Neighbors, for example, is a natural yet efficient framework. Many variants of Common Neighbors have been thus proposed to further boost the discriminative resolution of candidate links. In this paper, we reexamine the role of network topology in predicting missing links from the perspective of information theory, and present a practical approach based on the mutual information of network structures. It not only can improve the prediction accuracy substantially, but also experiences reasonable computing complexity. PMID:25207920
NASA Astrophysics Data System (ADS)
Shi, Jun; Xiao, Zhiheng; Zhou, Shichong
2010-07-01
Image segmentation is very important in the field of image processing. The pulse coupled neural network (PCNN) has been efficiently applied to image processing, especially for image segmentation. In this study, a simplified PCNN (S-PCNN) model is proposed, the fuzzy mutual information (FMI) is improved as optimization criterion for S-PCNN, and then the S-PCNN and improved FMI (IFMI) based segmentation algorithm is proposed and applied for the segmentation of breast tumor in ultrasound image. To validate the proposed algorithm, a comparative experiment is implemented to segment breast images not only by our proposed algorithm, but also by the improved C-V algorithm, the max-entropy-based PCNN algorithm, the MI-based PCNN algorithm, and the IFMI-based PCNN algorithm. The results show that the breast lesions are well segmented by the proposed algorithm without image preprocessing, with the mean Hausdorff of distance of 5.631+/-0.822, mean average minimum Euclidean distance of 0.554+/-0.049, mean Tanimoto coefficient of 0.961+/-0.019, and mean misclassified error of 0.038+/-0.004. These values of evaluation indices are better than those of other segmentation algorithms. The results indicate that the proposed algorithm has excellent segmentation accuracy and strong robustness against noise, and it has the potential for breast ultrasound computer-aided diagnosis (CAD).
Lachmann, Alexander; Giorgi, Federico M.; Lopez, Gonzalo; Califano, Andrea
2016-01-01
Summary: 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. Here, we present a completely new implementation of the algorithm, based on an Adaptive Partitioning strategy (AP) for estimating the Mutual Information. The new AP implementation (ARACNe-AP) achieves a dramatic improvement in computational performance (200× on average) over the previous methodology, while preserving the Mutual Information estimator and the Network inference accuracy of the original algorithm. Given that the previous version of ARACNe is extremely demanding, the new version of the algorithm will allow even researchers with modest computational resources to build complex regulatory networks from hundreds of gene expression profiles. Availability and Implementation: A JAVA cross-platform command line executable of ARACNe, together with all source code and a detailed usage guide are freely available on Sourceforge (http://sourceforge.net/projects/aracne-ap). JAVA version 8 or higher is required. Contact: califano@c2b2.columbia.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27153652
Gaining (mutual) information about quark/gluon discrimination
NASA Astrophysics Data System (ADS)
Larkoski, Andrew J.; Thaler, Jesse; Waalewijn, Wouter J.
2014-11-01
Discriminating quark jets from gluon jets is an important but challenging problem in jet substructure. In this paper, we use the concept of mutual information to illuminate the physics of quark/gluon tagging. Ideal quark/gluon separation requires only one bit of truth information, so even if two discriminant variables are largely uncorrelated, they can still share the same "truth overlap". Mutual information can be used to diagnose such situations, and thus determine which discriminant variables are redundant and which can be combined to improve performance. Using both parton showers and analytic resummation, we study a two-parameter family of generalized angularities, which includes familiar infrared and collinear (IRC) safe observables like thrust and broadening, as well as IRC unsafe variants like p {/T D } and hadron multiplicity. At leading-logarithmic (LL) order, the bulk of these variables exhibit Casimir scaling, such that their truth overlap is a universal function of the color factor ratio C A /C F . Only at next-to-leading-logarithmic (NLL) order can one see a difference in quark/gluon performance. For the IRC safe angularities, we show that the quark/gluon performance can be improved by combining angularities with complementary angular exponents. Interestingly, LL order, NLL order, Pythia 8, and Herwig++ all exhibit similar correlations between observables, but there are significant differences in the predicted quark/gluon discrimination power. For the IRC unsafe angularities, we show that the mutual information can be calculated analytically with the help of a nonperturbative "weighted-energy function", providing evidence for the complementarity of safe and unsafe observables for quark/gluon discrimination.
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.
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. PMID:25638417
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.
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
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. PMID:26352993
Long-range mutual information and topological uncertainty principle
NASA Astrophysics Data System (ADS)
Jian, Chao-Ming; Kim, Isaac; Qi, Xiao-Liang
Ordered phases in Landau paradigm can be diagnosed by a local order parameter, whereas topologically ordered phases cannot be detected in such a way. In this paper, we propose long-range mutual information (LRMI) as a unified diagnostic for both conventional long-range order and topological order. Using the LRMI, we characterize orders in n +1D gapped systems as m-membrane condensates with 0 <= m <= n-1. The familiar conventional order and 2 +1D topological orders are respectively identified as 0-membrane and 1-membrane condensates. We propose and study the topological uncertainty principle, which describes the non-commuting nature of non-local order parameters in topological orders.
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.
Mutual information as a measure of image quality for 3D dynamic lung imaging with EIT
Crabb, M G; Davidson, J L; Little, R; Wright, P; Morgan, A R; Miller, C A; Naish, J H; Parker, G J M; Kikinis, R; McCann, H; Lionheart, W R B
2014-01-01
We report on a pilot study of dynamic lung electrical impedance tomography (EIT) at the University of Manchester. Low-noise EIT data at 100 frames per second (fps) were obtained from healthy male subjects during controlled breathing, followed by magnetic resonance imaging (MRI) subsequently used for spatial validation of the EIT reconstruction. The torso surface in the MR image and electrode positions obtained using MRI fiducial markers informed the construction of a 3D finite element model extruded along the caudal-distal axis of the subject. Small changes in the boundary that occur during respiration were accounted for by incorporating the sensitivity with respect to boundary shape into a robust temporal difference reconstruction algorithm. EIT and MRI images were co-registered using the open source medical imaging software, 3D Slicer. A quantitative comparison of quality of different EIT reconstructions was achieved through calculation of the mutual information with a lung-segmented MR image. EIT reconstructions using a linear shape correction algorithm reduced boundary image artefacts, yielding better contrast of the lungs, and had 10% greater mutual information compared with a standard linear EIT reconstruction. PMID:24710978
Optimal and Suboptimal Noises Enhancing Mutual Information in Threshold System
NASA Astrophysics Data System (ADS)
Zhai, Qiqing; Wang, Youguo
2016-05-01
In this paper, we investigate the efficacy of noise enhancing information transmission in a threshold system. At first, in the frame of stochastic resonance (SR), optimal noise (Opt N) is derived to maximize mutual information (MI) of this nonlinear system. When input signal is discrete (binary), the optimal SR noise is found to have a finite distribution. In contrast, when input signal is continuous, the optimal SR noise is a constant one. In addition, suboptimal SR noises are explored as well with optimization methods when the types of noise added into the system are predetermined. We find that for small thresholds, suboptimal noises do not exist. Only when thresholds reach some level, do suboptimal noises come into effect. Meanwhile, we have discussed the impact of tails in noise distribution on SR effect. Finally, this paper extends the single-threshold system to an array of multi-threshold devices and presents the corresponding efficacy of information transmission produced by optimal and suboptimal SR noises. These results may be beneficial to quantization and coding.
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.
Automatic Registration of Multi-Source Data Using Mutual Information
NASA Astrophysics Data System (ADS)
Parmehr, E. G.; Zhang, C.; Fraser, C. S.
2012-07-01
Automatic image registration is a basic step in multi-sensor data integration in remote sensing and photogrammetric applications such as data fusion. The effectiveness of Mutual Information (MI) as a technique for automated multi-sensor image registration has previously been demonstrated for medical and remote sensing applications. In this paper, a new General Weighted MI (GWMI) approach that improves the robustness of MI to local maxima, particularly in the case of registering optical imagery and 3D point clouds, is presented. Two different methods including a Gaussian Mixture Model (GMM) and Kernel Density Estimation have been used to define the weight function of joint probability, regardless of the modality of the data being registered. The Expectation Maximizing method is then used to estimate parameters of GMM, and in order to reduce the cost of computation, a multi-resolution strategy has been used. The performance of the proposed GWMI method for the registration of aerial orthotoimagery and LiDAR range and intensity information has been experimentally evaluated and the results obtained are presented.
Mutual Algorithm-Architecture Analysis for Real - Parallel Systems in Particle Physics Experiments.
NASA Astrophysics Data System (ADS)
Ni, Ping
Data acquisition from particle colliders requires real-time detection of tracks and energy clusters from collision events occurring at intervals of tens of mus. Beginning with the specification of a benchmark track-finding algorithm, parallel implementations have been developed. A revision of the routing scheme for performing reductions such as a tree sum, called the reduced routing distance scheme, has been developed and analyzed. The scheme reduces inter-PE communication time for narrow communication channel systems. A new parallel algorithm, called the interleaved tree sum, for parallel reduction problems has been developed that increases efficiency of processor use. Detailed analysis of this algorithm with different routing schemes is presented. Comparable parallel algorithms are analyzed, also taking into account the architectural parameters that play an important role in this parallel algorithm analysis. Computation and communication times are analyzed to guide the design of a custom system based on a massively parallel processing component. Developing an optimal system requires mutual analysis of algorithm and architecture parameters. It is shown that matching a processor array size to the parallelism of the problem does not always produce the best system design. Based on promising benchmark simulation results, an application specific hardware prototype board, called Dasher, has been built using two Blitzen chips. The processing array is a mesh-connected SIMD system with 256 PEs. Its design is discussed, with details on the software environment.
A mutual-information-based mining method for marine abnormal association rules
NASA Astrophysics Data System (ADS)
Cunjin, Xue; Wanjiao, Song; Lijuan, Qin; Qing, Dong; Xiaoyang, Wen
2015-03-01
Long time series of remote sensing images are a key source of data for exploring large-scale marine abnormal association patterns, but pose significant challenges for traditional approaches to spatiotemporal analysis. This paper proposes a mutual-information-based quantitative association rule-mining algorithm (MIQarma) to address these challenges. MIQarma comprises three key steps. First, MIQarma calculates the asymmetrical mutual information between items with one scan of the database, and extracts pair-wise related items according to the user-specified information threshold. Second, a linking-pruning-generating recursive loop generates (k+1)-dimensional candidate association rules from k-dimensional rules on basis of the user-specified minimum support threshold, and this step is repeated until no more candidate association rules are generated. Finally, strong association rules are generated according to the user-specified minimum evaluation indicators. To demonstrate the feasibility and efficiency of MIQarma, we present two case studies: one considers performance analysis and the other identifies marine abnormal association relationships.
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.
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. PMID:24983106
NASA Astrophysics Data System (ADS)
Litva, John; Zeytinoglu, Mehmet
1990-07-01
A study of the effects of mutual coupling on the performance on direction finding algorithms is presented. The MUltiple SIgnal Classification (MUSIC) and maximum likelihood (ML) algorithms resolved non-coherent and coherent incident wave fields with relative ease when ideal array response models were used. When array output vectors were simulated using free space and lossy ground models which include mutual coupling effects, the performance of the unmodified direction finding algorithms declined sharply. In particular, estimates from unmodified algorithms exhibited a constant, deterministic bias term. Algorithms modified for this bias term displayed a significant residual bias in attempts to resolve incident wave field with closely spaced source signals. Array steering vectors are the main components through which the array models are coupled. Free space and lossy ground response modes that take mutual coupling effects into consideration were modified by assembling array steering vectors directly from simulated raw data. These modified algorithms exhibited exemplary performance in resolving fields from closely spaced source signals when the array output vectors were derived from the same free space or lossy ground models. The MUSIC algorithm permitted array steering vectors modified with free space response data to be used with the array output derived for the lossy ground response mode. However, it was applicable only to non-coherent source signals. The ML algorithm performed equally well with non-correlated and coherent source signals but it had to be perfectly matched with the actual array response. Computation requirements were very demanding for the ML algorithm.
Worst-case mutual information trajectories in concatenated codes with asymptotic interleavers
NASA Technical Reports Server (NTRS)
Divsalar, D.; Shamai, S.
2002-01-01
In this summary we present extremal average mutual information values carried by the extrinsic loglikelihood under the constraint of a given mean and variance while accounting for the consistency feature of loglikelihoods.
NASA Astrophysics Data System (ADS)
Zheng, Fawen; Wan, Yongshan; Song, Keunyea; Sun, Detong; Hedgepeth, Marion
2016-01-01
Soil pore water salinity plays an important role in the distribution of vegetation and biogeochemical processes in coastal floodplain ecosystems. In this study, artificial neural networks (ANNs) were applied to simulate the pore water salinity of a tidal floodplain in Florida. We present an approach based on embedding theory with mutual information to reconstruct ANN model input time series from one system state variable. Mutual information between system output and input was computed and the local minimum mutual information points were used to determine a time lag vector for time series embedding and reconstruction, with which the mutual information weighted average method was developed to compute the components of reconstructed time series. The optimal embedding dimension was obtained by optimizing model performance. The method was applied to simulate soil pore water salinity dynamics at 12 probe locations in the tidal floodplain influenced by saltwater intrusion using 4 years (2005-2008) data, in which adjacent river water salinity was used to reconstruct model input. The simulated electrical conductivity of the pore water showed close agreement with field observations (RMSE and ), suggesting the reconstructed input by the proposed approach provided adequate input information for ANN modeling. Multiple linear regression model, partial mutual information algorithm for input variable selection, k-NN algorithm, and simple time delay embedding were also used to further verify the merit of the proposed approach.
NASA Astrophysics Data System (ADS)
Zhang, Yongfei; Cao, Haiheng; Jiang, Hongxu; Li, Bo
2016-04-01
As remote sensing image applications are often characterized with limited bandwidth and high-quality demands, higher coding performance of remote sensing images are desirable. The embedded block coding with optimal truncation (EBCOT) is the fundamental part of JPEG2000 image compression standard. However, EBCOT only considers correlation within a sub-band and utilizes a context template of eight spatially neighboring coefficients in prediction. The existing optimization methods in literature using the current context template prove little performance improvements. To address this problem, this paper presents a new mutual information (MI)-based context template selection and modeling method. By further considering the correlation across the sub-bands, the potential prediction coefficients, including neighbors, far neighbors, parent and parent neighbors, are comprehensively examined and selected in such a manner that achieves a nice trade-off between the MI-based correlation criterion and the prediction complexity. Based on the selected context template, a high-order prediction model, which jointly considers the weight and the significance state of each coefficient, is proposed. Experimental results show that the proposed algorithm consistently outperforms the benchmark JPEG2000 standard and state-of-the-art algorithms in term of coding efficiency at a competitive computational cost, which makes it desirable in real-time compression applications, especially for remote sensing images.
Temporal subtraction in chest radiography: Mutual information as a measure of image quality
Armato, Samuel G. III; Sensakovic, William F.; Passen, Samantha J.; Engelmann, Roger; MacMahon, Heber
2009-12-15
Purpose: Temporal subtraction is used to detect the interval change in chest radiographs and aid radiologists in patient diagnosis. This method registers two temporally different images by geometrically warping the lung region, or ''lung mask,'' of a previous radiographic image to align with the current image. The gray levels of every pixel in the current image are subtracted from the gray levels of the corresponding pixels in the warped previous image to form a temporal subtraction image. While temporal subtraction images effectively enhance areas of pathologic change, misregistration of the images can mislead radiologists by obscuring the interval change or by creating artifacts that mimic change. The purpose of this study was to investigate the utility of mutual information computed between two registered radiographic chest images as a metric for distinguishing between clinically acceptable and clinically unacceptable temporal subtraction images.Methods: A radiologist subjectively rated the image quality of 138 temporal subtraction images using a 1 (poor) to 5 (excellent) scale. To objectively assess the registration accuracy depicted in the temporal subtraction images, which is the main factor that affects the quality of these images, mutual information was computed on the two constituent registered images prior to their subtraction to generate a temporal subtraction image. Mutual information measures the joint entropy of the current image and the warped previous image, yielding a higher value when the gray levels of spatially matched pixels in each image are consistent. Mutual information values were correlated with the radiologist's subjective ratings. To improve this correlation, mutual information was computed from a spatially limited lung mask, which was cropped from the bottom by 10%-60%. Additionally, the number of gray-level values used in the joint entropy histogram was varied. The ability of mutual information to predict the clinical acceptability of
Mutual information and the fidelity of response of gene regulatory models
NASA Astrophysics Data System (ADS)
Tabbaa, Omar P.; Jayaprakash, C.
2014-08-01
We investigate cellular response to extracellular signals by using information theory techniques motivated by recent experiments. We present results for the steady state of the following gene regulatory models found in both prokaryotic and eukaryotic cells: a linear transcription-translation model and a positive or negative auto-regulatory model. We calculate both the information capacity and the mutual information exactly for simple models and approximately for the full model. We find that (1) small changes in mutual information can lead to potentially important changes in cellular response and (2) there are diminishing returns in the fidelity of response as the mutual information increases. We calculate the information capacity using Gillespie simulations of a model for the TNF-α-NF-κ B network and find good agreement with the measured value for an experimental realization of this network. Our results provide a quantitative understanding of the differences in cellular response when comparing experimentally measured mutual information values of different gene regulatory models. Our calculations demonstrate that Gillespie simulations can be used to compute the mutual information of more complex gene regulatory models, providing a potentially useful tool in synthetic biology.
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.
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
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
Entanglement entropy and mutual information production rates in acoustic black holes.
Giovanazzi, Stefano
2011-01-01
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. PMID:21231730
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.
Monogamy and backflow of mutual information in non-Markovian thermal baths
NASA Astrophysics Data System (ADS)
Costa, A. C. S.; Angelo, R. M.; Beims, M. W.
2014-07-01
We investigate the dynamics of information among the parties of tripartite systems. We start by proving two results concerning the monogamy of mutual information. The first one states that mutual information is monogamous for generic tripartite pure states. The second shows that, in general, mutual information is monogamous only if the amount of genuine tripartite correlations is large enough. Then, we analyze the internal dynamics of tripartite systems whose parties do not exchange energy. In particular, we allow for one of the subsystems to play the role of a finite thermal bath. As a result, we find a typical scenario in which local information tends to be converted into delocalized information. Moreover, we show that (i) the information flow is reversible for finite thermal baths at low temperatures, (ii) monogamy of mutual information is respected throughout the dynamics, and (iii) genuine tripartite correlations are typically present. Finally, we analytically calculate a quantity capable of revealing favorable regimes for non-Markovianity in our model.
What are the differences between Bayesian classifiers and mutual-information classifiers?
Hu, Bao-Gang
2014-02-01
In this paper, both Bayesian and mutual-information classifiers are examined for binary classifications with or without a reject option. The general decision rules are derived for Bayesian classifiers with distinctions on error types and reject types. A formal analysis is conducted to reveal the parameter redundancy of cost terms when abstaining classifications are enforced. The redundancy implies an intrinsic problem of nonconsistency for interpreting cost terms. If no data are given to the cost terms, we demonstrate the weakness of Bayesian classifiers in class-imbalanced classifications. On the contrary, mutual-information classifiers are able to provide an objective solution from the given data, which shows a reasonable balance among error types and reject types. Numerical examples of using two types of classifiers are given for confirming the differences, including the extremely class-imbalanced cases. Finally, we briefly summarize the Bayesian and mutual-information classifiers in terms of their application advantages and disadvantages, respectively. PMID:24807026
The Impact of Different Sources of Fluctuations on Mutual Information in Biochemical Networks
Chevalier, Michael; Venturelli, Ophelia; El-Samad, Hana
2015-01-01
Stochastic fluctuations in signaling and gene expression limit the ability of cells to sense the state of their environment, transfer this information along cellular pathways, and respond to it with high precision. Mutual information is now often used to quantify the fidelity with which information is transmitted along a cellular pathway. Mutual information calculations from experimental data have mostly generated low values, suggesting that cells might have relatively low signal transmission fidelity. In this work, we demonstrate that mutual information calculations might be artificially lowered by cell-to-cell variability in both initial conditions and slowly fluctuating global factors across the population. We carry out our analysis computationally using a simple signaling pathway and demonstrate that in the presence of slow global fluctuations, every cell might have its own high information transmission capacity but that population averaging underestimates this value. We also construct a simple synthetic transcriptional network and demonstrate using experimental measurements coupled to computational modeling that its operation is dominated by slow global variability, and hence that its mutual information is underestimated by a population averaged calculation. PMID:26484538
The Impact of Different Sources of Fluctuations on Mutual Information in Biochemical Networks.
Chevalier, Michael; Venturelli, Ophelia; El-Samad, Hana
2015-10-01
Stochastic fluctuations in signaling and gene expression limit the ability of cells to sense the state of their environment, transfer this information along cellular pathways, and respond to it with high precision. Mutual information is now often used to quantify the fidelity with which information is transmitted along a cellular pathway. Mutual information calculations from experimental data have mostly generated low values, suggesting that cells might have relatively low signal transmission fidelity. In this work, we demonstrate that mutual information calculations might be artificially lowered by cell-to-cell variability in both initial conditions and slowly fluctuating global factors across the population. We carry out our analysis computationally using a simple signaling pathway and demonstrate that in the presence of slow global fluctuations, every cell might have its own high information transmission capacity but that population averaging underestimates this value. We also construct a simple synthetic transcriptional network and demonstrate using experimental measurements coupled to computational modeling that its operation is dominated by slow global variability, and hence that its mutual information is underestimated by a population averaged calculation. PMID:26484538
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.
Identifying relevant group of miRNAs in cancer using fuzzy mutual information.
Pal, Jayanta Kumar; Ray, Shubhra Sankar; Pal, Sankar K
2016-04-01
MicroRNAs (miRNAs) act as a major biomarker of cancer. All miRNAs in human body are not equally important for cancer identification. We propose a methodology, called FMIMS, which automatically selects the most relevant miRNAs for a particular type of cancer. In FMIMS, miRNAs are initially grouped by using a SVM-based algorithm; then the group with highest relevance is determined and the miRNAs in that group are finally ranked for selection according to their redundancy. Fuzzy mutual information is used in computing the relevance of a group and the redundancy of miRNAs within it. Superiority of the most relevant group to all others, in deciding normal or cancer, is demonstrated on breast, renal, colorectal, lung, melanoma and prostate data. The merit of FMIMS as compared to several existing methods is established. While 12 out of 15 selected miRNAs by FMIMS corroborate with those of biological investigations, three of them viz., "hsa-miR-519," "hsa-miR-431" and "hsa-miR-320c" are possible novel predictions for renal cancer, lung cancer and melanoma, respectively. The selected miRNAs are found to be involved in disease-specific pathways by targeting various genes. The method is also able to detect the responsible miRNAs even at the primary stage of cancer. The related code is available at http://www.jayanta.droppages.com/FMIMS.html . PMID:26264058
On the feature selection criterion based on an approximation of multidimensional mutual information.
Balagani, Kiran S; Phoha, Vir V
2010-07-01
We derive the feature selection criterion presented in [CHECK END OF SENTENCE] and [CHECK END OF SENTENCE] from the multidimensional mutual information between features and the class. Our derivation: 1) specifies and validates the lower-order dependency assumptions of the criterion and 2) mathematically justifies the utility of the criterion by relating it to Bayes classification error. PMID:20489237
Calculating mutual information for spike trains and other data with distances but no coordinates
Houghton, Conor
2015-01-01
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. PMID:26064650
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.
Successful network inference from time-series data using mutual information rate
NASA Astrophysics Data System (ADS)
Bianco-Martinez, E.; Rubido, N.; Antonopoulos, Ch. G.; Baptista, M. S.
2016-04-01
This work uses an information-based methodology to infer the connectivity of complex systems from observed time-series data. We first derive analytically an expression for the Mutual Information Rate (MIR), namely, the amount of information exchanged per unit of time, that can be used to estimate the MIR between two finite-length low-resolution noisy time-series, and then apply it after a proper normalization for the identification of the connectivity structure of small networks of interacting dynamical systems. In particular, we show that our methodology successfully infers the connectivity for heterogeneous networks, different time-series lengths or coupling strengths, and even in the presence of additive noise. Finally, we show that our methodology based on MIR successfully infers the connectivity of networks composed of nodes with different time-scale dynamics, where inference based on Mutual Information fails.
Successful network inference from time-series data using mutual information rate.
Bianco-Martinez, E; Rubido, N; Antonopoulos, Ch G; Baptista, M S
2016-04-01
This work uses an information-based methodology to infer the connectivity of complex systems from observed time-series data. We first derive analytically an expression for the Mutual Information Rate (MIR), namely, the amount of information exchanged per unit of time, that can be used to estimate the MIR between two finite-length low-resolution noisy time-series, and then apply it after a proper normalization for the identification of the connectivity structure of small networks of interacting dynamical systems. In particular, we show that our methodology successfully infers the connectivity for heterogeneous networks, different time-series lengths or coupling strengths, and even in the presence of additive noise. Finally, we show that our methodology based on MIR successfully infers the connectivity of networks composed of nodes with different time-scale dynamics, where inference based on Mutual Information fails. PMID:27131481
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.
On conclusive eavesdropping and measures of mutual information in quantum key distribution
NASA Astrophysics Data System (ADS)
Rastegin, Alexey E.
2016-03-01
We address the question of quantifying eavesdropper's information gain in an individual attack on systems of quantum key distribution. It is connected with the concept of conclusive eavesdropping introduced by Brandt. Using the BB84 protocol, we examine the problem of estimating a performance of conclusive entangling probe. The question of interest depends on the choice of a quantitative measure of eavesdropper's information about the error-free sifted bits. The Fuchs-Peres-Brandt probe realizes a very powerful individual attack on the BB84 scheme. In the usual formulation, Eve utilizes the Helstrom scheme in distinguishing between the two output probe states. In conclusive eavesdropping, the unambiguous discrimination is used. Comparing these two versions allows to demonstrate serious distinctions between widely used quantifiers of mutual information. In particular, the so-called Rényi mutual information does not seem to be a completely legitimate measure of an amount of mutual information. It is brightly emphasized with the example of conclusive eavesdropping.
Comparison of co-expression measures: mutual information, correlation, and model based indices
2012-01-01
Background Co-expression measures are often used to define networks among genes. Mutual information (MI) is often used as a generalized correlation measure. It is not clear how much MI adds beyond standard (robust) correlation measures or regression model based association measures. Further, it is important to assess what transformations of these and other co-expression measures lead to biologically meaningful modules (clusters of genes). Results We provide a comprehensive comparison between mutual information and several correlation measures in 8 empirical data sets and in simulations. We also study different approaches for transforming an adjacency matrix, e.g. using the topological overlap measure. Overall, we confirm close relationships between MI and correlation in all data sets which reflects the fact that most gene pairs satisfy linear or monotonic relationships. We discuss rare situations when the two measures disagree. We also compare correlation and MI based approaches when it comes to defining co-expression network modules. We show that a robust measure of correlation (the biweight midcorrelation transformed via the topological overlap transformation) leads to modules that are superior to MI based modules and maximal information coefficient (MIC) based modules in terms of gene ontology enrichment. We present a function that relates correlation to mutual information which can be used to approximate the mutual information from the corresponding correlation coefficient. We propose the use of polynomial or spline regression models as an alternative to MI for capturing non-linear relationships between quantitative variables. Conclusion The biweight midcorrelation outperforms MI in terms of elucidating gene pairwise relationships. Coupled with the topological overlap matrix transformation, it often leads to more significantly enriched co-expression modules. Spline and polynomial networks form attractive alternatives to MI in case of non-linear relationships
Feature selection of fMRI data based on normalized mutual information and fisher discriminant ratio.
Wang, Yanbin; Ji, Junzhong; Liang, Peipeng
2016-03-17
Pattern classification has been increasingly used in functional magnetic resonance imaging (fMRI) data analysis. However, the classification performance is restricted by the high dimensional property and noises of the fMRI data. In this paper, a new feature selection method (named as "NMI-F") was proposed by sequentially combining the normalized mutual information (NMI) and fisher discriminant ratio. In NMI-F, the normalized mutual information was firstly used to evaluate the relationships between features, and fisher discriminant ratio was then applied to calculate the importance of each feature involved. Two fMRI datasets (task-related and resting state) were used to test the proposed method. It was found that classification base on the NMI-F method could differentiate the brain cognitive and disease states effectively, and the proposed NMI-F method was prior to the other related methods. The current results also have implications to the future studies. PMID:27257882
Artifact reduction in mutual-information-based CT-MR image registration
NASA Astrophysics Data System (ADS)
Wei, Mingxiu; Liu, Jundong; Liu, Junhong
2004-05-01
Abstract Mutual information (MI) is currently the most popular match metric in handling the registration problem for multi modality images. However, interpolation artifacts impose deteriorating effects to the accuracy and robustness of MI-based methods. This paper analyzes the generation mechanism of the artifacts inherent in linear partial volume interpolation (PVI) and shows that the mutual information resulted from PVI is a convex function within each voxel grid. We conclude that the generation of the artifacts is due to two facts: 1) linear interpolation causes the histogram bin values to change at a synchronized pace; 2) entropy computation function Σxlgx is convex. As a remedy we propose to use non-uniform interpolation functions as the interpolation kernels in estimating the joint histogram. Cubic B-splin and Gaussian interpolators are compared and we demonstrate the improvements via experiments on misalignments between CT/MR brain scans.
Mutual information and self-control of a fully-connected low-activity neural network
NASA Astrophysics Data System (ADS)
Bollé, D.; Carreta, D. Dominguez
2000-11-01
A self-control mechanism for the dynamics of a three-state fully connected neural network is studied through the introduction of a time-dependent threshold. The self-adapting threshold is a function of both the neural and the pattern activity in the network. The time evolution of the order parameters is obtained on the basis of a recently developed dynamical recursive scheme. In the limit of low activity the mutual information is shown to be the relevant parameter in order to determine the retrieval quality. Due to self-control an improvement of this mutual information content as well as an increase of the storage capacity and an enlargement of the basins of attraction are found. These results are compared with numerical simulations.
Zhang, Xiujun; Zhao, Juan; Hao, Jin-Kao; Zhao, Xing-Ming; Chen, Luonan
2015-03-11
Mutual information (MI), a quantity describing the nonlinear dependence between two random variables, has been widely used to construct gene regulatory networks (GRNs). Despite its good performance, MI cannot separate the direct regulations from indirect ones among genes. Although the conditional mutual information (CMI) is able to identify the direct regulations, it generally underestimates the regulation strength, i.e. it may result in false negatives when inferring gene regulations. In this work, to overcome the problems, we propose a novel concept, namely conditional mutual inclusive information (CMI2), to describe the regulations between genes. Furthermore, with CMI2, we develop a new approach, namely CMI2NI (CMI2-based network inference), for reverse-engineering GRNs. In CMI2NI, CMI2 is used to quantify the mutual information between two genes given a third one through calculating the Kullback-Leibler divergence between the postulated distributions of including and excluding the edge between the two genes. The benchmark results on the GRNs from DREAM challenge as well as the SOS DNA repair network in Escherichia coli demonstrate the superior performance of CMI2NI. Specifically, even for gene expression data with small sample size, CMI2NI can not only infer the correct topology of the regulation networks but also accurately quantify the regulation strength between genes. As a case study, CMI2NI was also used to reconstruct cancer-specific GRNs using gene expression data from The Cancer Genome Atlas (TCGA). CMI2NI is freely accessible at http://www.comp-sysbio.org/cmi2ni. PMID:25539927
Zhang, Xiujun; Zhao, Juan; Hao, Jin-Kao; Zhao, Xing-Ming; Chen, Luonan
2015-01-01
Mutual information (MI), a quantity describing the nonlinear dependence between two random variables, has been widely used to construct gene regulatory networks (GRNs). Despite its good performance, MI cannot separate the direct regulations from indirect ones among genes. Although the conditional mutual information (CMI) is able to identify the direct regulations, it generally underestimates the regulation strength, i.e. it may result in false negatives when inferring gene regulations. In this work, to overcome the problems, we propose a novel concept, namely conditional mutual inclusive information (CMI2), to describe the regulations between genes. Furthermore, with CMI2, we develop a new approach, namely CMI2NI (CMI2-based network inference), for reverse-engineering GRNs. In CMI2NI, CMI2 is used to quantify the mutual information between two genes given a third one through calculating the Kullback–Leibler divergence between the postulated distributions of including and excluding the edge between the two genes. The benchmark results on the GRNs from DREAM challenge as well as the SOS DNA repair network in Escherichia coli demonstrate the superior performance of CMI2NI. Specifically, even for gene expression data with small sample size, CMI2NI can not only infer the correct topology of the regulation networks but also accurately quantify the regulation strength between genes. As a case study, CMI2NI was also used to reconstruct cancer-specific GRNs using gene expression data from The Cancer Genome Atlas (TCGA). CMI2NI is freely accessible at http://www.comp-sysbio.org/cmi2ni. PMID:25539927
Four-state quantum key distribution exploiting maximum mutual information measurement strategy
NASA Astrophysics Data System (ADS)
Chen, Dong-Xu; Zhang, Pei; Li, Hong-Rong; Gao, Hong; Li, Fu-Li
2016-02-01
We propose a four-state quantum key distribution (QKD) scheme using generalized measurement of nonorthogonal states, the maximum mutual information measurement strategy. Then, we analyze the eavesdropping process in intercept-resend and photon number splitting attack scenes. Our analysis shows that in the intercept-resend and photon number splitting attack eavesdropping scenes, our scheme is more secure than BB84 protocol and has higher key generation rate which may be applied to high-density QKD.
NASA Astrophysics Data System (ADS)
Pires, C. L.
2013-12-01
Principal components (PCs) of the low-frequency variability have zero cross correlation by construction but they are not statistically independent. Their degree of dependency is assessed through the Shannon mutual information (MI). PCs were computed here both for: 1) the monthly running means of the stream functions of a one million days run of a T63, 3level, perpetual winter forced, quasi-geostrophic (QG3) model and 2) the annual running means of the SST from GISS 1880-2012 data. One computes both the dyadic MI: I(X,Y) and triadic MI: I(X,Y,Z) among arbitrary PCs X,Y,Z (rotated or not) by using a kernel-based MI estimation method applied to previously Gaussianized marginal variables obtained by Gaussian anamorphosis thus making estimation more resistant to outliers. Non-vanishing MI comes from the non-Gaussianity of the full PDF of the state-vector of retained PCs. Statistically significant non-Gaussian dyadic MI appears between leading PC-pairs, both for the QG3 model run (projecting on planetary-slow scales) and for GISS data where some nonlinear correlations are emphasized between Pacific and Atlantic SST modes. We propose an iterative optimization algorithm looking for uncorrelated variables X, Y, Z, (obtained from orthogonal projections), taken from a multivariate space of N PCs (N≥3), which maximize I(X,Y,Z), i.e. their triadic non-Gaussian interaction. It also maximizes the joint negentropy leading to the presence of relevant non-linear correlations across the three linearly uncorrelated variables. This is solved through an iterative optimization method by maximizing a positive contrast function (e.g. the squared expectation E(XYZ)2 ), vanishing under Gaussian conditions. In order to understand the origin of a statistically significant positive mutual information I(X,Y,Z)>0, one decomposes it into a dyadic term: I2(X,Y,Z)≡I(X,Y)+I(X,Z)+I(Y,Z), vanishing iff X,Y,Z are pair-wised independent and into a triadic term, the so called interactivity term: It(X
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
Using Mutual Information Criterion to Design an Efficient Phoneme Set for Chinese Speech Recognition
NASA Astrophysics Data System (ADS)
Zhang, Jin-Song; Hu, Xin-Hui; Nakamura, Satoshi
Chinese is a representative tonal language, and it has been an attractive topic of how to process tone information in the state-of-the-art large vocabulary speech recognition system. This paper presents a novel way to derive an efficient phoneme set of tone-dependent units to build a recognition system, by iteratively merging a pair of tone-dependent units according to the principle of minimal loss of the Mutual Information (MI). The mutual information is measured between the word tokens and their phoneme transcriptions in a training text corpus, based on the system lexical and language model. The approach has a capability to keep discriminative tonal (and phoneme) contrasts that are most helpful for disambiguating homophone words due to lack of tones, and merge those tonal (and phoneme) contrasts that are not important for word disambiguation for the recognition task. This enables a flexible selection of phoneme set according to a balance between the MI information amount and the number of phonemes. We applied the method to traditional phoneme set of Initial/Finals, and derived several phoneme sets with different number of units. Speech recognition experiments using the derived sets showed its effectiveness.
Query-answering algorithms for information agents
Levy, A.Y.; Rajaraman, A.; Ordille, J.J.
1996-12-31
We describe the architecture and query-answering algorithms used in the Information Manifold, an implemented information gathering system that provides uniform access to structured information sources on the World-Wide Web. Our architecture provides an expressive language for describing information sources, which makes it easy to add new sources and to model the fine-grained distinctions between their contents. The query-answering algorithm guarantees that the descriptions of the sources are exploited to access only sources that are relevant to a given query. Accessing only relevant sources is crucial to scale up such a system to large numbers of sources. In addition, our algorithm can exploit run-time information to further prune information sources and to reduce the cost of query planning.
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. PMID:23248024
2015-01-01
Background The rapid advances in genome sequencing technologies have resulted in an unprecedented number of genome variations being discovered in humans. However, there has been very limited coverage of interpretation of the personal genome sequencing data in terms of diseases. Methods In this paper we present the first computational analysis scheme for interpreting personal genome data by simultaneously considering the functional impact of damaging variants and curated disease-gene association data. This method is based on mutual information as a measure of the relative closeness between the personal genome and diseases. We hypothesize that a higher mutual information score implies that the personal genome is more susceptible to a particular disease than other diseases. Results The method was applied to the sequencing data of 50 acute myeloid leukemia (AML) patients in The Cancer Genome Atlas. The utility of associations between a disease and the personal genome was explored using data of healthy (control) people obtained from the 1000 Genomes Project. The ranks of the disease terms in the AML patient group were compared with those in the healthy control group using "Leukemia, Myeloid, Acute" (C04.557.337.539.550) as the corresponding MeSH disease term. The mutual information rank of the disease term was substantially higher in the AML patient group than in the healthy control group, which demonstrates that the proposed methodology can be successfully applied to infer associations between the personal genome and diseases. Conclusions Overall, the area under the receiver operating characteristics curve was significantly larger for the AML patient data than for the healthy controls. This methodology could contribute to consequential discoveries and explanations for mining personal genome sequencing data in terms of diseases, and have versatility with respect to genomic-based knowledge such as drug-gene and environmental-factor-gene interactions. PMID:26045178
A Method for Evaluating Tuning Functions of Single Neurons based on Mutual Information Maximization
NASA Astrophysics Data System (ADS)
Brostek, Lukas; Eggert, Thomas; Ono, Seiji; Mustari, Michael J.; Büttner, Ulrich; Glasauer, Stefan
2011-03-01
We introduce a novel approach for evaluation of neuronal tuning functions, which can be expressed by the conditional probability of observing a spike given any combination of independent variables. This probability can be estimated out of experimentally available data. By maximizing the mutual information between the probability distribution of the spike occurrence and that of the variables, the dependence of the spike on the input variables is maximized as well. We used this method to analyze the dependence of neuronal activity in cortical area MSTd on signals related to movement of the eye and retinal image movement.
Hybrid Online Mobile Laser Scanner Calibration Through Image Alignment by Mutual Information
NASA Astrophysics Data System (ADS)
Miled, Mourad; Soheilian, Bahman; Habets, Emmanuel; Vallet, Bruno
2016-06-01
This paper proposes an hybrid online calibration method for a laser scanner mounted on a mobile platform also equipped with an imaging system. The method relies on finding the calibration parameters that best align the acquired points cloud to the images. The quality of this intermodal alignment is measured by Mutual information between image luminance and points reflectance. The main advantage and motivation is ensuring pixel accurate alignment of images and point clouds acquired simultaneously, but it is also much more flexible than traditional laser calibration methods.
Weighted mutual information analysis substantially improves domain-based functional network models
Shim, Jung Eun; Lee, Insuk
2016-01-01
Motivation: Functional protein–protein interaction (PPI) networks elucidate molecular pathways underlying complex phenotypes, including those of human diseases. Extrapolation of domain–domain interactions (DDIs) from known PPIs is a major domain-based method for inferring functional PPI networks. However, the protein domain is a functional unit of the protein. Therefore, we should be able to effectively infer functional interactions between proteins based on the co-occurrence of domains. Results: Here, we present a method for inferring accurate functional PPIs based on the similarity of domain composition between proteins by weighted mutual information (MI) that assigned different weights to the domains based on their genome-wide frequencies. Weighted MI outperforms other domain-based network inference methods and is highly predictive for pathways as well as phenotypes. A genome-scale human functional network determined by our method reveals numerous communities that are significantly associated with known pathways and diseases. Domain-based functional networks may, therefore, have potential applications in mapping domain-to-pathway or domain-to-phenotype associations. Availability and Implementation: Source code for calculating weighted mutual information based on the domain profile matrix is available from www.netbiolab.org/w/WMI. Contact: Insuklee@yonsei.ac.kr Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27207946
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]. PMID:21405197
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
Universal behavior of the Shannon and Rényi mutual information of quantum critical chains
NASA Astrophysics Data System (ADS)
Alcaraz, F. C.; Rajabpour, M. A.
2014-08-01
We study the Shannon and Rényi mutual information (MI) in the ground state (GS) of different critical quantum spin chains. Despite the apparent basis dependence of these quantities we show the existence of some particular basis (we will call them conformal basis) whose finite-size scaling function is related to the central charge c of the underlying conformal field theory of the model. In particular, we verified that for large index n, the MI of a subsystem of size ℓ in a periodic chain with L sites behaves as c/4 n/n -1 ln[L/πsin(π/ℓL)], when the ground-state wave function is expressed in these special conformal basis. This is in agreement with recent predictions. For generic local basis, we will show that, although in some cases bnln[L/π sin(π/ℓL)] is a good fit to our numerical data, in general, there is no direct relation between bn and the central charge of the system. We will support our findings with detailed numerical calculations for the transverse field Ising model, Q =3,4 quantum Potts chain, quantum Ashkin-Teller chain, and the XXZ quantum chain. We will also present some additional results of the Shannon mutual information (n =1), for the parafermionic ZQ quantum chains with Q =5,6,7, and 8.
Shannon and Rényi mutual information in quantum critical spin chains
NASA Astrophysics Data System (ADS)
Stéphan, Jean-Marie
2014-07-01
We study the Shannon mutual information in one-dimensional critical spin chains, following a recent conjecture [Alcaraz and Rajabpour, Phys. Rev. Lett. 111, 017201 (2013), 10.1103/PhysRevLett.111.017201], as well as Rényi generalizations of it. We combine conformal field theory (CFT) arguments with numerical computations in lattice discretizations with central charge c =1 and c =1/2. For a periodic system of length L cut into two parts of length ℓ and L -ℓ, all our results agree with the general shape dependence In(ℓ,L)=(bn/4)ln(L/π sin π/ℓL), where bn is a universal coefficient. For the free boson CFT we show from general arguments that bn=c =1. At c =1/2 we conjecture a result for n >1. We perform extensive numerical computations in Ising chains to confirm this, and also find b1≃0.4801629(2), a nontrivial number which we do not understand analytically. Open chains at c =1/2 and n =1 are even more intriguing, with a shape-dependent logarithmic divergence of the Shannon mutual information.
NASA Astrophysics Data System (ADS)
Ikemoto, Shuhei; DallaLibera, Fabio; Hosoda, Koh; Ishiguro, Hiroshi
2014-10-01
Stochastic resonance (SR) is a counterintuitive phenomenon, observed in a wide variety of nonlinear systems, for which the addition of noise of opportune magnitude can improve signal detection. Tuning the noise for maximizing the SR effect is important both for artificial and biological systems. In the case of artificial systems, full exploitation of the SR effect opens the possibility of measuring otherwise unmeasurable signals. In biology, identification of possible SR maximization mechanisms is of great interest for explaining the low-energy high-sensitivity perception capabilities often observed in animals. SR maximization approaches presented in literature use knowledge on the input signal (or stimulus, in the case of living beings), and maximize the mutual information between the input and the output signal. The input signal, however, is unknown in many practical settings. To cope with this problem, this paper introduces an approximation of the input-output mutual information based on the spurious correlation among a set of redundant units. A proof of the approximation, as well as numerical examples of its application are given.
Neural sensitivity to syllable frequency and mutual information in speech perception and production.
Tremblay, Pascale; Deschamps, Isabelle; Baroni, Marco; Hasson, Uri
2016-08-01
Many factors affect our ability to decode the speech signal, including its quality, the complexity of the elements that compose it, as well as their frequency of occurrence and co-occurrence in a language. Syllable frequency effects have been described in the behavioral literature, including facilitatory effects during speech production and inhibitory effects during word recognition, but the neural mechanisms underlying these effects remain largely unknown. The objective of this study was to examine, using functional neuroimaging, the neurobiological correlates of three different distributional statistics in simple 2-syllable nonwords: the frequency of the first and second syllables, and the mutual information between the syllables. We examined these statistics during nonword perception and production using a powerful single-trial analytical approach. We found that repetition accuracy was higher for nonwords in which the frequency of the first syllable was high. In addition, brain responses to distributional statistics were widespread and almost exclusively cortical. Importantly, brain activity was modulated in a distinct manner for each statistic, with the strongest facilitatory effects associated with the frequency of the first syllable and mutual information. These findings show that distributional statistics modulate nonword perception and production. We discuss the common and unique impact of each distributional statistic on brain activity, as well as task differences. PMID:27184201
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.
NASA Astrophysics Data System (ADS)
Sorensen, Julian
2008-12-01
At the heart of many ICA techniques is a nonparametric estimate of an information measure, usually via nonparametric density estimation, for example, kernel density estimation. While not as popular as kernel density estimators, orthogonal functions can be used for nonparametric density estimation (via a truncated series expansion whose coefficients are calculated from the observed data). While such estimators do not necessarily yield a valid density, which kernel density estimators do, they are faster to calculate than kernel density estimators, in particular for a modified version of Renyi's entropy of order 2. In this paper, we compare the performance of ICA using Hermite series based estimates of Shannon's and Renyi's mutual information, to that of Gaussian kernel based estimates. The comparisons also include ICA using the RADICAL estimate of Shannon's entropy and a FastICA estimate of neg-entropy.
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. PMID:25318376
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. PMID:26313855
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
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. PMID:25475346
Entanglement and mutual information in two-dimensional nonrelativistic field theories
NASA Astrophysics Data System (ADS)
Hosseini, Seyed Morteza; Véliz-Osorio, Álvaro
2016-01-01
We carry out a systematic study of entanglement entropy in nonrelativistic conformal field theories via holographic techniques. After a discussion of recent results concerning Galilean conformal field theories, we deduce a novel expression for the entanglement entropy of (1 +1 )-dimensional Lifshitz field theories—this is done both at zero and finite temperature. Based on these results, we pose a conjecture for the anomaly coefficient of a Lifshitz field theory dual to new massive gravity. It is found that the Lifshitz entanglement entropy at finite temperature displays a striking similarity with that corresponding to a flat space cosmology in three dimensions. We claim that this structure is an inherent feature of the entanglement entropy for nonrelativistic conformal field theories. We finish by exploring the behavior of the mutual information for such theories.
Excited-state entanglement and thermal mutual information in random spin chains
NASA Astrophysics Data System (ADS)
Huang, Yichen; Moore, Joel E.
2014-12-01
Entanglement properties of excited eigenstates (or of thermal mixed states) are difficult to study with conventional analytical methods. We approach this problem for random spin chains using a recently developed real-space renormalization group technique for excited states ("RSRG-X"). For the random XX and quantum Ising chains, which have logarithmic divergences in the entanglement entropy of their (infinite-randomness) critical ground states, we show that the entanglement entropy of excited eigenstates retains a logarithmic divergence while the mutual information of thermal mixed states does not. However, in the XX case the coefficient of the logarithmic divergence extends from the universal ground-state value to a universal interval due to the degeneracy of excited eigenstates. These models are noninteracting in the sense of having free-fermion representations, allowing strong numerical checks of our analytical predictions.
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.
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.
NASA Astrophysics Data System (ADS)
Nielsen, O. F.; Ploug, C.; Mendoza, J. A.; Martínez, K.
2009-05-01
The need for increaseding accuracy and reduced ambiguities in the inversion results has resulted in focus on the development of more advanced inversion methods of geophysical data. Over the past few years more advanced inversion techniques have been developed to improve the results. Real 3D-inversion is time consuming and therefore often not the best solution in a cost-efficient perspective. This has motivated the development of 3D constrained inversions, where 1D-models are constrained in 3D, also known as a Spatial Constrained Inversion (SCI). Moreover, inversion of several different data types in one inversion has been developed, known as Mutually Constrained Inversion (MCI). In this paper a presentation of a Spatial Mutually Constrained Inversion method (SMCI) is given. This method allows 1D-inversion applied to different geophysical datasets and geological information constrained in 3D. Application of two or more types of geophysical methods in the inversion has proved to reduce the equivalence problem and to increase the resolution in the inversion results. The use of geological information from borehole data or digital geological models can be integrated in the inversion. In the SMCI, a 1D inversion code is used to model soundings that are constrained in three dimensions according to their relative position in space. This solution enhances the accuracy of the inversion and produces distinct layers thicknesses and resistivities. It is very efficient in the mapping of a layered geology but still also capable of mapping layer discontinuities that are, in many cases, related to fracturing and faulting or due to valley fills. Geological information may be included in the inversion directly or used only to form a starting model for the individual soundings in the inversion. In order to show the effectiveness of the method, examples are presented from both synthetic data and real data. The examples include DC-soundings as well as land-based and airborne TEM
Automatic registration of optical imagery with 3d lidar data using local combined mutual information
NASA Astrophysics Data System (ADS)
Parmehr, E. G.; Fraser, C. S.; Zhang, C.; Leach, J.
2013-10-01
Automatic registration of multi-sensor data is a basic step in data fusion for photogrammetric and remote sensing applications. The effectiveness of intensity-based methods such as Mutual Information (MI) for automated registration of multi-sensor image has been previously reported for medical and remote sensing applications. In this paper, a new multivariable MI approach that exploits complementary information of inherently registered LiDAR DSM and intensity data to improve the robustness of registering optical imagery and LiDAR point cloud, is presented. LiDAR DSM and intensity information has been utilised in measuring the similarity of LiDAR and optical imagery via the Combined MI. An effective histogramming technique is adopted to facilitate estimation of a 3D probability density function (pdf). In addition, a local similarity measure is introduced to decrease the complexity of optimisation at higher dimensions and computation cost. Therefore, the reliability of registration is improved due to the use of redundant observations of similarity. The performance of the proposed method for registration of satellite and aerial images with LiDAR data in urban and rural areas is experimentally evaluated and the results obtained are discussed.
Omitaomu, Olufemi A; Protopopescu, Vladimir A; Ganguly, Auroop R
2011-01-01
A new approach is developed for denoising signals using the Empirical Mode Decomposition (EMD) technique and the Information-theoretic method. The EMD technique is applied to decompose a noisy sensor signal into the so-called intrinsic mode functions (IMFs). These functions are of the same length and in the same time domain as the original signal. Therefore, the EMD technique preserves varying frequency in time. Assuming the given signal is corrupted by high-frequency Gaussian noise implies that most of the noise should be captured by the first few modes. Therefore, our proposition is to separate the modes into high-frequency and low-frequency groups. We applied an information-theoretic method, namely mutual information, to determine the cut-off for separating the modes. A denoising procedure is applied only to the high-frequency group using a shrinkage approach. Upon denoising, this group is combined with the original low-frequency group to obtain the overall denoised signal. We illustrate our approach with simulated and real-world data sets. The results are compared to two popular denoising techniques in the literature, namely discrete Fourier transform (DFT) and discrete wavelet transform (DWT). We found that our approach performs better than DWT and DFT in most cases, and comparatively to DWT in some cases in terms of: (i) mean square error, (ii) recomputed signal-to-noise ratio, and (iii) visual quality of the denoised signals.
A mutual information-based metric for evaluation of fMRI data-processing approaches.
Afshin-Pour, Babak; Soltanian-Zadeh, Hamid; Hossein-Zadeh, Gholam-Ali; Grady, Cheryl L; Strother, Stephen C
2011-05-01
We propose a novel approach for evaluating the performance of activation detection in real (experimental) datasets using a new mutual information (MI)-based metric and compare its sensitivity to several existing performance metrics in both simulated and real datasets. The proposed approach is based on measuring the approximate MI between the fMRI time-series of a validation dataset and a calculated activation map (thresholded label map or continuous map) from an independent training dataset. The MI metric is used to measure the amount of information preserved during the extraction of an activation map from experimentally related fMRI time-series. The processing method that preserves maximal information between the maps and related time-series is proposed to be superior. The results on simulation datasets for multiple analysis models are consistent with the results of ROC curves, but are shown to have lower information content than for real datasets, limiting their generalizability. In real datasets for group analyses using the general linear model (GLM; FSL4 and SPM5), we show that MI values are (1) larger for groups of 15 versus 10 subjects and (2) more sensitive measures than reproducibility (for continuous maps) or Jaccard overlap metrics (for thresholded maps). We also show that (1) for an increasing fraction of nominally active voxels, both MI and false discovery rate (FDR) increase, and (2) at a fixed FDR, GLM using FSL4 tends to extract more voxels and more information than SPM5 using the default processing techniques in each package. PMID:20533565
Iskarous, Khalil; Mooshammer, Christine; Hoole, Phil; Recasens, Daniel; Shadle, Christine H.; Saltzman, Elliot; Whalen, D. H.
2013-01-01
Coarticulation and invariance are two topics at the center of theorizing about speech production and speech perception. In this paper, a quantitative scale is proposed that places coarticulation and invariance at the two ends of the scale. This scale is based on physical information flow in the articulatory signal, and uses Information Theory, especially the concept of mutual information, to quantify these central concepts of speech research. Mutual Information measures the amount of physical information shared across phonological units. In the proposed quantitative scale, coarticulation corresponds to greater and invariance to lesser information sharing. The measurement scale is tested by data from three languages: German, Catalan, and English. The relation between the proposed scale and several existing theories of coarticulation is discussed, and implications for existing theories of speech production and perception are presented. PMID:23927125
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.
Aguilar, Daniel; Oliva, Baldo; Marino Buslje, Cristina
2012-01-01
Amino acids committed to a particular function correlate tightly along evolution and tend to form clusters in the 3D structure of the protein. Consequently, a protein can be seen as a network of co-evolving clusters of residues. The goal of this work is two-fold: first, we have combined mutual information and structural data to describe the amino acid networks within a protein and their interactions. Second, we have investigated how this information can be used to improve methods of prediction of functional residues by reducing the search space. As a main result, we found that clusters of co-evolving residues related to the catalytic site of an enzyme have distinguishable topological properties in the network. We also observed that these clusters usually evolve independently, which could be related to a fail-safe mechanism. Finally, we discovered a significant enrichment of functional residues (e.g. metal binding, susceptibility to detrimental mutations) in the clusters, which could be the foundation of new prediction tools. PMID:22848494
Aguilar, Daniel; Oliva, Baldo; Marino Buslje, Cristina
2012-01-01
Amino acids committed to a particular function correlate tightly along evolution and tend to form clusters in the 3D structure of the protein. Consequently, a protein can be seen as a network of co-evolving clusters of residues. The goal of this work is two-fold: first, we have combined mutual information and structural data to describe the amino acid networks within a protein and their interactions. Second, we have investigated how this information can be used to improve methods of prediction of functional residues by reducing the search space. As a main result, we found that clusters of co-evolving residues related to the catalytic site of an enzyme have distinguishable topological properties in the network. We also observed that these clusters usually evolve independently, which could be related to a fail-safe mechanism. Finally, we discovered a significant enrichment of functional residues (e.g. metal binding, susceptibility to detrimental mutations) in the clusters, which could be the foundation of new prediction tools. PMID:22848494
2014-01-01
Background Several methods are available for the detection of covarying positions from a multiple sequence alignment (MSA). If the MSA contains a large number of sequences, information about the proximities between residues derived from covariation maps can be sufficient to predict a protein fold. However, in many cases the structure is already known, and information on the covarying positions can be valuable to understand the protein mechanism and dynamic properties. Results In this study we have sought to determine whether a multivariate (multidimensional) extension of traditional mutual information (MI) can be an additional tool to study covariation. The performance of two multidimensional MI (mdMI) methods, designed to remove the effect of ternary/quaternary interdependencies, was tested with a set of 9 MSAs each containing <400 sequences, and was shown to be comparable to that of the newest methods based on maximum entropy/pseudolikelyhood statistical models of protein sequences. However, while all the methods tested detected a similar number of covarying pairs among the residues separated by < 8 Å in the reference X-ray structures, there was on average less than 65% overlap between the top scoring pairs detected by methods that are based on different principles. Conclusions Given the large variety of structure and evolutionary history of different proteins it is possible that a single best method to detect covariation in all proteins does not exist, and that for each protein family the best information can be derived by merging/comparing results obtained with different methods. This approach may be particularly valuable in those cases in which the size of the MSA is small or the quality of the alignment is low, leading to significant differences in the pairs detected by different methods. PMID:24886131
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.
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.
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
NASA Astrophysics Data System (ADS)
Liang, Yongfang; Chen, Hua-mei
2005-04-01
Joint histogram is the only quantity required to calculate the mutual information (MI) between two images. For MI based image registration, joint histograms are often estimated through linear interpolation or partial volume interpolation (PVI). It has been pointed out that both methods may result in a phenomenon known as interpolation induced artifacts. In this paper, we implemented a wide range of interpolation/approximation kernels for joint histogram estimation. Some kernels are nonnegative. In this case, these kernels are applied in two ways as the linear kernel is applied in linear interpolation and PVI. In addition, we implemented two other joint histogram estimation methods devised to overcome the interpolation artifact problem. They are nearest neighbor interpolation with jittered sampling with/without histogram blurring and data resampling. We used the clinical data obtained from Vanderbilt University for all of the experiments. The objective of this study is to perform a comprehensive comparison and evaluation of different joint histogram estimation methods for MI based image registration in terms of artifacts reduction and registration accuracy.
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.
NASA Astrophysics Data System (ADS)
Molina-Vilaplana, Javier; Sodano, Pasquale
2011-10-01
In ( d + 1) dimensional Multiscale Entanglement Renormalization Ansatz (MERA) networks, tensors are connected so as to reproduce the discrete, ( d + 2) holographic geometry of Anti de Sitter space (AdS d+2) with the original system lying at the boundary. We analyze the MERA renormalization flow that arises when computing the quantum correlations between two disjoint blocks of a quantum critical system, to show that the structure of the causal cones characteristic of MERA, requires a transition between two different regimes attainable by changing the ratio between the size and the separation of the two disjoint blocks. We argue that this transition in the MERA causal developments of the blocks may be easily accounted by an AdS d+2 black hole geometry when the mutual information is computed using the Ryu-Takayanagi formula. As an explicit example, we use a BTZ AdS3 black hole to compute the MI and the quantum correlations between two disjoint intervals of a one dimensional boundary critical system. Our results for this low dimensional system not only show the existence of a phase transition emerging when the conformal four point ratio reaches a critical value but also provide an intuitive entropic argument accounting for the source of this instability. We discuss the robustness of this transition when finite temperature and finite size effects are taken into account.
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%.
Zhou, G D
2006-06-01
In this paper, we present a biomedical name recognition system, called PowerBioNE. In order to deal with the special phenomena in the biomedical domain, various evidential features are proposed and integrated through a mutual information independence model (MIIM). In addition, a support vector machine (SVM) plus sigmoid is proposed to resolve the data sparseness problem in the MIIM. In this way, the data sparseness problem in MIIM-based biomedical name recognition can be resolved effectively and a biomedical name recognition system with better performance and better portability can be achieved. Finally, we present two post-processing modules to deal with the nested entity name and abbreviation phenomena in the biomedical domain to further improve the performance. Evaluation shows that our system achieves F-measures of 69.1 and 71.2 on the 23 classes of GENIA V1.1 and V3.0, respectively. In particular, our system achieves an F-measure of 77.8 on the "protein" class of GENIA V3.0. It also shows that our system outperforms the best-reported system on GENIA V1.1 and V3.0. PMID:16112894
Monotonicity of the unified quantum ( r, s)-entropy and ( r, s)-mutual information
NASA Astrophysics Data System (ADS)
Fan, Ya-Jing; Cao, Huai-Xin
2015-12-01
Monotonicity of the unified quantum ( r, s)-entropy Ers(ρ ) and the unified quantum ( r, s)-mutual information Irs(ρ ) is discussed in this paper. Some basic properties of them are explored, and the following conclusions are established. (1) For any 0
Abásolo, D; Escudero, J; Hornero, R; Gómez, C; Espino, P
2008-10-01
We analysed the electroencephalogram (EEG) from Alzheimer's disease (AD) patients with two nonlinear methods: approximate entropy (ApEn) and auto mutual information (AMI). ApEn quantifies regularity in data, while AMI detects linear and nonlinear dependencies in time series. EEGs from 11 AD patients and 11 age-matched controls were analysed. ApEn was significantly lower in AD patients at electrodes O1, O2, P3 and P4 (p < 0.01). The EEG AMI decreased more slowly with time delays in patients than in controls, with significant differences at electrodes T5, T6, O1, O2, P3 and P4 (p < 0.01). The strong correlation between results from both methods shows that the AMI rate of decrease can be used to estimate the regularity in time series. Our work suggests that nonlinear EEG analysis may contribute to increase the insight into brain dysfunction in AD, especially when different time scales are inspected, as is the case with AMI. PMID:18784948
Geometrical mutual information at the tricritical point of the two-dimensional Blume–Capel model
NASA Astrophysics Data System (ADS)
Mandal, Ipsita; Inglis, Stephen; Melko, Roger G.
2016-07-01
The spin-1 classical Blume–Capel model on a square lattice is known to exhibit a finite-temperature phase transition described by the tricritical Ising CFT in 1 + 1 space-time dimensions. This phase transition can be accessed with classical Monte Carlo simulations, which, via a replica-trick calculation, can be used to study the shape-dependence of the classical Rényi entropies for a torus divided into two cylinders. From the second Rényi entropy, we calculate the geometrical mutual information (GMI) introduced by Stéphan et al (2014 Phys. Rev. Lett. 112 127204) and use it to extract a numerical estimate for the value of the central charge near the tricritical point. By comparing to the known CFT result, c = 7/10, we demonstrate how this type of GMI calculation can be used to estimate the position of the tricritical point in the phase diagram.
Holographic mutual information and distinguishability of Wilson loop and defect operators
NASA Astrophysics Data System (ADS)
Hartnoll, Sean A.; Mahajan, Raghu
2015-02-01
The mutual information of disconnected regions in large N gauge theories with holographic gravity duals can undergo phase transitions. These occur when connected and disconnected bulk Ryu-Takayanagi surfaces exchange dominance. That is, the bulk `soap bubble' snaps as the boundary regions are drawn apart. We give a gauge-theoretic characterization of this transition: States with and without a certain defect operator insertion — the defect separates the entangled spatial regions — are shown to be perfectly distinguishable if and only if the Ryu-Takayanagi surface is connected. Meanwhile, states with and without a certain Wilson loop insertion — the Wilson loop nontrivially threads the spatial regions — are perfectly distinguishable if and only if the Ryu-Takayanagi surface is disconnected. The quantum relative entropy of two perfectly distinguishable states is infinite. The results are obtained by relating the soap bubble transition to Hawking-Page (deconfinement) transitions in the Rényi entropies, where defect operators and Wilson loops are known to act as order parameters.
Genomic signatures in viral sequences by in-frame and out-frame mutual information.
Serrano-Solís, Víctor; Cocho, Germinal; José, Marco V
2016-08-21
In order to understand the unique biology of viruses, we use the Mutual Information Function (MIF) to characterize 792 viral sequences comprising 458 viral whole genomes. A 3-base periodicity (3-bp) was observed only in DNA-viruses whereas RNA-viruses showed irregular patterns. The correlation of MIF values at frequencies of 3-bp (in-frame) with frequencies of 4 and 5bps (out-frame), turned out to be useful to distinguish viruses according to their respective taxonomic order, and whether they pertain to any of the three different kingdoms, Eubacteria, Archaea and Eukarya. The clustering of viruses was carried out by the use of a new statistics, namely, the pair of in- and out-frame values of the MIF. The clustering thus obtained turned out to be entirely consistent with the current viral taxonomy. As a result we were able to compare in a single plot both viral and cellular genomes unlike any given phylogenetic reconstruction. PMID:27178876
NASA Astrophysics Data System (ADS)
Hamrouni, Sameh; Rougon, Nicolas; Pr"teux, Françoise
2011-03-01
In perfusion MRI (p-MRI) exams, short-axis (SA) image sequences are captured at multiple slice levels along the long-axis of the heart during the transit of a vascular contrast agent (Gd-DTPA) through the cardiac chambers and muscle. Compensating cardio-thoracic motions is a requirement for enabling computer-aided quantitative assessment of myocardial ischaemia from contrast-enhanced p-MRI sequences. The classical paradigm consists of registering each sequence frame on a reference image using some intensity-based matching criterion. In this paper, we introduce a novel unsupervised method for the spatio-temporal groupwise registration of cardiac p-MRI exams based on normalized mutual information (NMI) between high-dimensional feature distributions. Here, local contrast enhancement curves are used as a dense set of spatio-temporal features, and statistically matched through variational optimization to a target feature distribution derived from a registered reference template. The hard issue of probability density estimation in high-dimensional state spaces is bypassed by using consistent geometric entropy estimators, allowing NMI to be computed directly from feature samples. Specifically, a computationally efficient kth-nearest neighbor (kNN) estimation framework is retained, leading to closed-form expressions for the gradient flow of NMI over finite- and infinite-dimensional motion spaces. This approach is applied to the groupwise alignment of cardiac p-MRI exams using a free-form Deformation (FFD) model for cardio-thoracic motions. Experiments on simulated and natural datasets suggest its accuracy and robustness for registering p-MRI exams comprising more than 30 frames.
Mutual information analysis of sleep EEG in detecting psycho-physiological insomnia.
Aydın, Serap; Tunga, M Alper; Yetkin, Sinan
2015-05-01
The primary goal of this study is to state the clear changes in functional brain connectivity during all night sleep in psycho-physiological insomnia (PPI). The secondary goal is to investigate the usefulness of Mutual Information (MI) analysis in estimating cortical sleep EEG arousals for detection of PPI. For these purposes, healthy controls and patients were compared to each other with respect to both linear (Pearson correlation coefficient and coherence) and nonlinear quantifiers (MI) in addition to phase locking quantification for six sleep stages (stage.1-4, rem, wake) by means of interhemispheric dependency between two central sleep EEG derivations. In test, each connectivity estimation calculated for each couple of epoches (C3-A2 and C4-A1) was identified by the vector norm of estimation. Then, patients and controls were classified by using 10 different types of data mining classifiers for five error criteria such as accuracy, root mean squared error, sensitivity, specificity and precision. High performance in a classification through a measure will validate high contribution of that measure to detecting PPI. The MI was found to be the best method in detecting PPI. In particular, the patients had lower MI, higher PCC for all sleep stages. In other words, the lower sleep EEG synchronization suffering from PPI was observed. These results probably stand for the loss of neurons that then contribute to less complex dynamical processing within the neural networks in sleep disorders an the functional central brain connectivity is nonlinear during night sleep. In conclusion, the level of cortical hemispheric connectivity is strongly associated with sleep disorder. Thus, cortical communication quantified in all existence sleep stages might be a potential marker for sleep disorder induced by PPI. PMID:25732074
Algorithm and program for information processing with the filin apparatus
NASA Technical Reports Server (NTRS)
Gurin, L. S.; Morkrov, V. S.; Moskalenko, Y. I.; Tsoy, K. A.
1979-01-01
The reduction of spectral radiation data from space sources is described. The algorithm and program for identifying segments of information obtained from the Film telescope-spectrometer on the Salyut-4 are presented. The information segments represent suspected X-ray sources. The proposed algorithm is an algorithm of the lowest level. Following evaluation, information free of uninformative segments is subject to further processing with algorithms of a higher level. The language used is FORTRAN 4.
An Innovative Thinking-Based Intelligent Information Fusion Algorithm
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. PMID:23956699
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.
Sun, Leiming; Wang, Chan
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
Exploring a new best information algorithm for Iliad.
Guo, D.; Lincoln, M. J.; Haug, P. J.; Turner, C. W.; Warner, H. R.
1991-01-01
Iliad is a diagnostic expert system for internal medicine. One important feature that Iliad offers is the ability to analyze a particular patient case and to determine the most cost-effective method for pursuing the work-up. Iliad's current "best information" algorithm has not been previously validated and compared to other potential algorithms. Therefore, this paper presents a comparison of four new algorithms to the current algorithm. The basis for this comparison was eighteen "vignette" cases derived from real patient cases from the University of Utah Medical Center. The results indicated that the current algorithm can be significantly improved. More promising algorithms are suggested for future investigation. PMID:1807677
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.
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.
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.
Misra, Sanchit; Pamnany, Kiran; Aluru, Srinivas
2015-01-01
Construction of whole-genome networks from large-scale gene expression data is an important problem in systems biology. While several techniques have been developed, most cannot handle network reconstruction at the whole-genome scale, and the few that can, require large clusters. In this paper, we present a solution on the Intel Xeon Phi coprocessor, taking advantage of its multi-level parallelism including many x86-based cores, multiple threads per core, and vector processing units. We also present a solution on the Intel® Xeon® processor. Our solution is based on TINGe, a fast parallel network reconstruction technique that uses mutual information and permutation testing for assessing statistical significance. We demonstrate the first ever inference of a plant whole genome regulatory network on a single chip by constructing a 15,575 gene network of the plant Arabidopsis thaliana from 3,137 microarray experiments in only 22 minutes. In addition, our optimization for parallelizing mutual information computation on the Intel Xeon Phi coprocessor holds out lessons that are applicable to other domains. PMID:26451815
NASA Astrophysics Data System (ADS)
Zhou, Tianci; Chen, Xiao; Fradkin, Eduardo
We investigate the entanglement entropy(EE) of circular entangling surfaces in the 2+1d quantum Lifshitz model, where the spatially conformal invariant ground state is a Rokhsar-Kivelson state with Gibbs weight of 2d free Boson. We use cut-off independent mutual information regulator to define and calculate the subleading correction in the EE. The subtlety due to the Boson compactification in the replica trick is carefully taken care of. Our results show that for circular entangling surface, the subleading term is a constant on both the sphere of arbitrary radius and infinite plane. For the latter case, it parallels the constancy of disk EE in 2+1d conformal field theory, despite the lack of full space time conformal invariance. In the end, we present the mutual information of two disjoint disks and compare its scaling function in the small parameter regime (radii much smaller than their separation) with Cardy's general CFT results. This work was supported in part by the National Science Foundation Grants NSF-DMR-13-06011(TZ) and DMR-1408713 (XC, EF).
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…
Fast method of homology and purine-pyrimidine mutual relations between DNA sequences search.
Korotkov, E V
1994-01-01
A new algorithm for scanning sequences is described. This algorithm uses the boolean operators AND and OR. The mutual information between the sequences is used as a measure of sequence interrelation. It allows evaluation of the probability of accidental sequence interrelation in a quantitative manner. The proposed algorithm was used for searching for MB1 repeats in human and other mammalian sequences. PMID:7841466
Chen, Chao; Yan, Xuefeng
2015-06-01
In this paper, an optimized multilayer feed-forward network (MLFN) is developed to construct a soft sensor for controlling naphtha dry point. To overcome the two main flaws in the structure and weight of MLFNs, which are trained by a back-propagation learning algorithm, minimal redundancy maximal relevance-partial mutual information clustering (mPMIc) integrated with least square regression (LSR) is proposed to optimize the MLFN. The mPMIc can determine the location of hidden layer nodes using information in the hidden and output layers, as well as remove redundant hidden layer nodes. These selected nodes are highly related to output data, but are minimally correlated with other hidden layer nodes. The weights between the selected hidden layer nodes and output layer are then updated through LSR. When the redundant nodes from the hidden layer are removed, the ideal MLFN structure can be obtained according to the test error results. In actual applications, the naphtha dry point must be controlled accurately because it strongly affects the production yield and the stability of subsequent operational processes. The mPMIc-LSR MLFN with a simple network size performs better than other improved MLFN variants and existing efficient models. PMID:25055386
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.
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. PMID:25432611
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. PMID:27058285
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.
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…
Use of mutual information to decrease entropy: Implications for the second law of thermodynamics
Lloyd, S.
1989-05-15
Several theorems on the mechanics of gathering information are proved, and the possibility of violating the second law of thermodynamics by obtaining information is discussed in light of these theorems. Maxwell's demon can lower the entropy of his surroundings by an amount equal to the difference between the maximum entropy of his recording device and its initial entropy, without generating a compensating entropy increase. A demon with human-scale recording devices can reduce the entropy of a gas by a negligible amount only, but the proof of the demon's impracticability leaves open the possibility that systems highly correlated with their environment can reduce the environment's entropy by a substantial amount without increasing entropy elsewhere. In the event that a boundary condition for the universe requires it to be in a state of low entropy when small, the correlations induced between different particle modes during the expansion phase allow the modes to behave like Maxwell's demons during the contracting phase, reducing the entropy of the universe to a low value.
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. PMID:26881263
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. PMID:26881263
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
MINT: Mutual Information Based Transductive Feature Selection for Genetic Trait Prediction.
He, Dan; Rish, Irina; Haws, David; Parida, Laxmi
2016-01-01
Whole genome prediction of complex phenotypic traits using high-density genotyping arrays has attracted a lot of attention, as it is relevant to the fields of plant and animal breeding and genetic epidemiology. Since the number of genotypes is generally much bigger than the number of samples, predictive models suffer from the curse of dimensionality. The curse of dimensionality problem not only affects the computational efficiency of a particular genomic selection method, but can also lead to a poor performance, mainly due to possible overfitting, or un-informative features. In this work, we propose a novel transductive feature selection method, called MINT, which is based on the MRMR (Max-Relevance and Min-Redundancy) criterion. We apply MINT on genetic trait prediction problems and show that, in general, MINT is a better feature selection method than the state-of-the-art inductive method MRMR. PMID:27295642
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.
Feng, Yanqiu; Chen, Wufan
2005-01-01
PROPELLER (Periodically Rotated Overlapping ParallEl Lines with Enhanced Reconstruction) MRI, proposed by J. G. Pipe [1], offers a novel and effective means for compensating motion. For the reconstruction of PROPLLER data, algorithms to reliably and accurately extract inter-strip motion from data in central overlapped area are crucial to motion artifacts suppression. When implemented on T1-weighted MR data, the reconstruction algorithm, with motion estimated by registration based on maximizing correlation energy in frequency domain (CF), produces images with low quality due to the inaccurate estimation of motion. In this paper, a new algorithm is proposed for motion estimation based on the registration by maximizing mutual information in spatial domain (MIS). Furthermore, the optimization process is initialized by CF algorithm, so the algorithm is abbreviated as CF-MIS algorithm in this paper. With phantom and in vivo MR imaging, the CF-MIS algorithm was shown to be of higher accuracy in rotation estimation than CF algorithm. Consequently, the head motion in T1-weighted PROPELLER MRI was better corrected. PMID:17282454
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).
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.
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. PMID:26324169
Sosa, Daniela; Miramontes, Pedro; Li, Wentian; Mireles, Víctor; Bobadilla, Juan R.; José, Marco V.
2013-01-01
Recently, Trifonov's group proposed a 10-mer DNA motif YYYYYRRRRR as a solution of the long-standing problem of sequence-based nucleosome positioning. To test whether this generic decamer represents a biological meaningful signal, we compare the distribution of this motif in primates and Archaea, which are known to contain nucleosomes, and in Eubacteria, which do not possess nucleosomes. The distribution of the motif is analyzed by the mutual information function (MIF) with a shifted version of itself (MIF profile). We found common features in the patterns of this generic decamer on MIF profiles among primate species, and interestingly we found conspicuous but dissimilar MIF profiles for each Archaea tested. The overall MIF profiles for each chromosome in each primate species also follow a similar pattern. Trifonov's generic decamer may be a highly conserved motif for the nucleosome positioning, but we argue that this is not the only motif. The distribution of this generic decamer exhibits previously unidentified periodicities, which are associated to highly repetitive sequences in the genome. Alu repetitive elements contribute to the most fundamental structure of nucleosome positioning in higher Eukaryotes. In some regions of primate chromosomes, the distribution of the decamer shows symmetrical patterns including inverted repeats. PMID:23841049
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.
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. PMID:22497153
Improving the trust algorithm of information in semantic web
NASA Astrophysics Data System (ADS)
Wan, Zong-bao; Min, Jiang
2012-01-01
With the rapid development of computer networks, especially with the introduction of the Semantic Web perspective, the problem of trust computation in the network has become an important research part of current computer system theoretical. In this paper, according the information properties of the Semantic Web and interact between nodes, the definition semantic trust as content trust of information and the node trust between the nodes of two parts. By Calculate the content of the trust of information and the trust between nodes, then get the final credibility num of information in semantic web. In this paper , we are improve the computation algorithm of the node trust .Finally, stimulations and analyses show that the improved algorithm can effectively improve the trust of information more accurately.
Improving the trust algorithm of information in semantic web
NASA Astrophysics Data System (ADS)
Wan, Zong-Bao; Min, Jiang
2011-12-01
With the rapid development of computer networks, especially with the introduction of the Semantic Web perspective, the problem of trust computation in the network has become an important research part of current computer system theoretical. In this paper, according the information properties of the Semantic Web and interact between nodes, the definition semantic trust as content trust of information and the node trust between the nodes of two parts. By Calculate the content of the trust of information and the trust between nodes, then get the final credibility num of information in semantic web. In this paper , we are improve the computation algorithm of the node trust .Finally, stimulations and analyses show that the improved algorithm can effectively improve the trust of information more accurately.
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.
Imaging for dismantlement verification: information management and analysis algorithms
Robinson, Sean M.; Jarman, Kenneth D.; Pitts, W. Karl; Seifert, Allen; Misner, Alex C.; Woodring, Mitchell L.; Myjak, Mitchell J.
2012-01-11
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, which must be non-sensitive to be acceptable in an Information Barrier regime. However, this process must be performed with care. Features like the perimeter, area, and intensity of an object, for example, might reveal sensitive information. Any data-reduction technique must provide sufficient information to discriminate a real object from a spoofed or incorrect one, while avoiding disclosure (or storage) of any sensitive object qualities. Ultimately, algorithms are intended to provide only a yes/no response verifying the presence of features in the image. We discuss the utility of imaging for arms control applications and present three image-based verification algorithms in this context. The algorithms reduce full image information to non-sensitive feature information, in a process that is intended to enable verification while eliminating the possibility of image reconstruction. The underlying images can be highly detailed, since they are dynamically generated behind an information barrier. We consider the use of active (conventional) radiography alone and in tandem with passive (auto) radiography. We study these algorithms in terms of technical performance in image analysis and application to an information barrier scheme.
Ossadtchi, Alexei; Pronko, Platon; Baillet, Sylvain; Pflieger, Mark E.; Stroganova, Tatiana
2014-01-01
Spatial component analysis is often used to explore multidimensional time series data whose sources cannot be measured directly. Several methods may be used to decompose the data into a set of spatial components with temporal loadings. Component selection is of crucial importance, and should be supported by objective criteria. In some applications, the use of a well defined component selection criterion may provide for automation of the analysis. In this paper we describe a novel approach for ranking of spatial components calculated from the EEG or MEG data recorded within evoked response paradigm. Our method is called Mutual Information (MI) Spectrum and is based on gauging the amount of MI of spatial component temporal loadings with a synthetically created reference signal. We also describe the appropriate randomization based statistical assessment scheme that can be used for selection of components with statistically significant amount of MI. Using simulated data with realistic trial to trial variations and SNR corresponding to the real recordings we demonstrate the superior performance characteristics of the described MI based measure as compared to a more conventionally used power driven gauge. We also demonstrate the application of the MI Spectrum for the selection of task-related independent components from real MEG data. We show that the MI spectrum allows to identify task-related components reliably in a consistent fashion, yielding stable results even from a small number of trials. We conclude that the proposed method fits naturally the information driven nature of ICA and can be used for routine and automatic ranking of independent components calculated from the functional neuroimaging data collected within event-related paradigms. PMID:24478692
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.…
Improved motion information-based infrared dim target tracking algorithms
NASA Astrophysics Data System (ADS)
Lei, Liu; Zhijian, Huang
2014-11-01
Accurate and fast tracking of infrared (IR) dim target has very important meaning for infrared precise guidance, early warning, video surveillance, etc. However, under complex backgrounds, such as clutter, varying illumination, and occlusion, the traditional tracking method often converges to a local maximum and loses the real infrared target. To cope with these problems, three improved tracking algorithm based on motion information are proposed in this paper, namely improved mean shift algorithm, improved Optical flow method and improved Particle Filter method. The basic principles and the implementing procedure of these modified algorithms for target tracking are described. Using these algorithms, the experiments on some real-life IR and color images are performed. The whole algorithm implementing processes and results are analyzed, and those algorithms for tracking targets are evaluated from the two aspects of subjective and objective. The results prove that the proposed method has satisfying tracking effectiveness and robustness. Meanwhile, it has high tracking efficiency and can be used for real-time tracking.
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
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)
Dey, Siddharth S.; Xue, Yuhua; Joachimiak, Marcin P.; Friedland, Gregory D.; Burnett, John C.; Zhou, Qiang; Arkin, Adam P.; Schaffer, David V.
2012-01-01
Viral genomes are continually subjected to mutations, and functionally deleterious ones can be rescued by reversion or additional mutations that restore fitness. The error prone nature of HIV-1 replication has resulted in highly diverse viral sequences, and it is not clear how viral proteins such as Tat, which plays a critical role in viral gene expression and replication, retain their complex functions. Although several important amino acid positions in Tat are conserved, we hypothesized that it may also harbor functionally important residues that may not be individually conserved yet appear as correlated pairs, whose analysis could yield new mechanistic insights into Tat function and evolution. To identify such sites, we combined mutual information analysis and experimentation to identify coevolving positions and found that residues 35 and 39 are strongly correlated. Mutation of either residue of this pair into amino acids that appear in numerous viral isolates yields a defective virus; however, simultaneous introduction of both mutations into the heterologous Tat sequence restores gene expression close to wild-type Tat. Furthermore, in contrast to most coevolving protein residues that contribute to the same function, structural modeling and biochemical studies showed that these two residues contribute to two mechanistically distinct steps in gene expression: binding P-TEFb and promoting P-TEFb phosphorylation of the C-terminal domain in RNAPII. Moreover, Tat variants that mimic HIV-1 subtypes B or C at sites 35 and 39 have evolved orthogonal strengths of P-TEFb binding versus RNAPII phosphorylation, suggesting that subtypes have evolved alternate transcriptional strategies to achieve similar gene expression levels. PMID:22253435
Decision making algorithm for development strategy of information systems
NASA Astrophysics Data System (ADS)
Derman, Galyna Y.; Nikitenko, Olena D.; Kotyra, Andrzej; Bazarova, Madina; Kassymkhanova, Dana
2015-12-01
The paper presents algorithm of decision making for development strategy of information systems. The process of development is planned taking into account the internal and external factors of the enterprise which affect the prospects of development of both the information system and the whole enterprise. The initial state of the system must be taken into account. The total risk is the criterion for selecting the strategy. The risk is calculated using statistical and fuzzy data of system's parameters. These data are summarized by means of the function of uncertainty. The software for the realization of the algorithm of decision making on choosing the development strategy of information system is developed and created in this paper.
An Iterative Decoding Algorithm for Fusion of Multimodal Information
NASA Astrophysics Data System (ADS)
Shivappa, Shankar T.; Rao, Bhaskar D.; Trivedi, Mohan M.
2007-12-01
Human activity analysis in an intelligent space is typically based on multimodal informational cues. Use of multiple modalities gives us a lot of advantages. But information fusion from different sources is a problem that has to be addressed. In this paper, we propose an iterative algorithm to fuse information from multimodal sources. We draw inspiration from the theory of turbo codes. We draw an analogy between the redundant parity bits of the constituent codes of a turbo code and the information from different sensors in a multimodal system. A hidden Markov model is used to model the sequence of observations of individual modalities. The decoded state likelihoods from one modality are used as additional information in decoding the states of the other modalities. This procedure is repeated until a certain convergence criterion is met. The resulting iterative algorithm is shown to have lower error rates than the individual models alone. The algorithm is then applied to a real-world problem of speech segmentation using audio and visual cues.
Retaining local image information in gamut mapping algorithms.
Zolliker, Peter; Simon, Klaus
2007-03-01
Our topic is the potential of combining global gamut mapping with spatial methods to retain the percepted local image information in gamut mapping algorithms. The main goal is to recover the original local contrast between neighboring pixels in addition to the usual optimization of preserving lightness, saturation, and global contrast. Special emphasis is placed on avoiding artifacts introduced by the gamut mapping algorithm itself. We present an unsharp masking technique based on an edge-preserving smoothing algorithm allowing to avoid halo artifacts. The good performance of the presented approach is verified by a psycho-visual experiment using newspaper printing as a representative of a small destination gamut application. Furthermore, the improved mapping properties are documented with local mapping histograms. PMID:17357727
Bhowmick, Asmit; Sharma, Sudhir C; Honma, Hallie; Head-Gordon, Teresa
2016-07-28
Side chain entropy and mutual entropy information between residue pairs have been calculated for two de novo designed Kemp eliminase enzymes, KE07 and KE70, and for their most improved versions at the end of laboratory directed evolution (LDE). We find that entropy, not just enthalpy, helped to destabilize the preference for the reactant state complex of the designed enzyme as well as favoring stabilization of the transition state complex for the best LDE enzymes. Furthermore, residues with the highest side chain couplings as measured by mutual information, when experimentally mutated, were found to diminish or annihilate catalytic activity, some of which were far from the active site. In summary, our findings demonstrate how side chain fluctuations and their coupling can be an important design feature for de novo enzymes, and furthermore could be utilized in the computational steps in lieu of or in addition to the LDE steps in future enzyme design projects. PMID:27374812
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.
Klus, G T; Song, A; Schick, A; Wahde, M; Szallasi, Z
2001-01-01
Most human tumors are characterized by: (1) an aberrant set of chromosomes, a state termed aneuploidy; (2) an aberrant gene expression pattern; and (3) an aberrant phenotype of uncontrolled growth. One of the goals of cancer research is to establish causative relationships between these three important characteristics. In this paper we were searching for evidence that aneuploidy is a major cause of differential gene expression. We describe how mutual information analysis of cancer-associated gene expression patterns could be exploited to answer this question. In addition to providing general guidelines, we have applied the proposed analysis to a recently published breast cancer-associated gene expression matrix. The results derived from this particular data set provided preliminary evidence that mutual information analysis may become a useful tool to investigate the link between differential gene expression and aneuploidy. PMID:11262960
Yang, Feng; Ding, Mingyue; Zhang, Xuming; Wu, Yi; Hu, Jiani
2013-01-01
Non-rigid multi-modal image registration plays an important role in medical image processing and analysis. Existing image registration methods based on similarity metrics such as mutual information (MI) and sum of squared differences (SSD) cannot achieve either high registration accuracy or high registration efficiency. To address this problem, we propose a novel two phase non-rigid multi-modal image registration method by combining Weber local descriptor (WLD) based similarity metrics with the normalized mutual information (NMI) using the diffeomorphic free-form deformation (FFD) model. The first phase aims at recovering the large deformation component using the WLD based non-local SSD (wldNSSD) or weighted structural similarity (wldWSSIM). Based on the output of the former phase, the second phase is focused on getting accurate transformation parameters related to the small deformation using the NMI. Extensive experiments on T1, T2 and PD weighted MR images demonstrate that the proposed wldNSSD-NMI or wldWSSIM-NMI method outperforms the registration methods based on the NMI, the conditional mutual information (CMI), the SSD on entropy images (ESSD) and the ESSD-NMI in terms of registration accuracy and computation efficiency. PMID:23765270
Artificial Bee Colony Algorithm Based on Information Learning.
Gao, Wei-Feng; Huang, Ling-Ling; Liu, San-Yang; Dai, Cai
2015-12-01
Inspired by the fact that the division of labor and cooperation play extremely important roles in the human history development, this paper develops a novel artificial bee colony algorithm based on information learning (ILABC, for short). In ILABC, at each generation, the whole population is divided into several subpopulations by the clustering partition and the size of subpopulation is dynamically adjusted based on the last search experience, which results in a clear division of labor. Furthermore, the two search mechanisms are designed to facilitate the exchange of information in each subpopulation and between different subpopulations, respectively, which acts as the cooperation. Finally, the comparison results on a number of benchmark functions demonstrate that the proposed method performs competitively and effectively when compared to the selected state-of-the-art algorithms. PMID:25594992
A New Algorithm to Optimize Maximal Information Coefficient.
Chen, Yuan; Zeng, Ying; Luo, Feng; Yuan, Zheming
2016-01-01
The maximal information coefficient (MIC) captures dependences between paired variables, including both functional and non-functional relationships. In this paper, we develop a new method, ChiMIC, to calculate the MIC values. The ChiMIC algorithm uses the chi-square test to terminate grid optimization and then removes the restriction of maximal grid size limitation of original ApproxMaxMI algorithm. Computational experiments show that ChiMIC algorithm can maintain same MIC values for noiseless functional relationships, but gives much smaller MIC values for independent variables. For noise functional relationship, the ChiMIC algorithm can reach the optimal partition much faster. Furthermore, the MCN values based on MIC calculated by ChiMIC can capture the complexity of functional relationships in a better way, and the statistical powers of MIC calculated by ChiMIC are higher than those calculated by ApproxMaxMI. Moreover, the computational costs of ChiMIC are much less than those of ApproxMaxMI. We apply the MIC values tofeature selection and obtain better classification accuracy using features selected by the MIC values from ChiMIC. PMID:27333001
A New Algorithm to Optimize Maximal Information Coefficient
Luo, Feng; Yuan, Zheming
2016-01-01
The maximal information coefficient (MIC) captures dependences between paired variables, including both functional and non-functional relationships. In this paper, we develop a new method, ChiMIC, to calculate the MIC values. The ChiMIC algorithm uses the chi-square test to terminate grid optimization and then removes the restriction of maximal grid size limitation of original ApproxMaxMI algorithm. Computational experiments show that ChiMIC algorithm can maintain same MIC values for noiseless functional relationships, but gives much smaller MIC values for independent variables. For noise functional relationship, the ChiMIC algorithm can reach the optimal partition much faster. Furthermore, the MCN values based on MIC calculated by ChiMIC can capture the complexity of functional relationships in a better way, and the statistical powers of MIC calculated by ChiMIC are higher than those calculated by ApproxMaxMI. Moreover, the computational costs of ChiMIC are much less than those of ApproxMaxMI. We apply the MIC values tofeature selection and obtain better classification accuracy using features selected by the MIC values from ChiMIC. PMID:27333001
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
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.
Information theoretic methods for image processing algorithm optimization
NASA Astrophysics Data System (ADS)
Prokushkin, Sergey F.; Galil, Erez
2015-01-01
Modern image processing pipelines (e.g., those used in digital cameras) are full of advanced, highly adaptive filters that often have a large number of tunable parameters (sometimes > 100). This makes the calibration procedure for these filters very complex, and the optimal results barely achievable in the manual calibration; thus an automated approach is a must. We will discuss an information theory based metric for evaluation of algorithm adaptive characteristics ("adaptivity criterion") using noise reduction algorithms as an example. The method allows finding an "orthogonal decomposition" of the filter parameter space into the "filter adaptivity" and "filter strength" directions. This metric can be used as a cost function in automatic filter optimization. Since it is a measure of a physical "information restoration" rather than perceived image quality, it helps to reduce the set of the filter parameters to a smaller subset that is easier for a human operator to tune and achieve a better subjective image quality. With appropriate adjustments, the criterion can be used for assessment of the whole imaging system (sensor plus post-processing).
An Algorithm Combining for Objective Prediction with Subjective Forecast Information
NASA Astrophysics Data System (ADS)
Choi, JunTae; Kim, SooHyun
2016-04-01
As direct or post-processed output from numerical weather prediction (NWP) models has begun to show acceptable performance compared with the predictions of human forecasters, many national weather centers have become interested in automatic forecasting systems based on NWP products alone, without intervention from human forecasters. The Korea Meteorological Administration (KMA) is now developing an automatic forecasting system for dry variables. The forecasts are automatically generated from NWP predictions using a post processing model (MOS). However, MOS cannot always produce acceptable predictions, and sometimes its predictions are rejected by human forecasters. In such cases, a human forecaster should manually modify the prediction consistently at points surrounding their corrections, using some kind of smart tool to incorporate the forecaster's opinion. This study introduces an algorithm to revise MOS predictions by adding a forecaster's subjective forecast information at neighbouring points. A statistical relation between two forecast points - a neighbouring point and a dependent point - was derived for the difference between a MOS prediction and that of a human forecaster. If the MOS prediction at a neighbouring point is updated by a human forecaster, the value at a dependent point is modified using a statistical relationship based on linear regression, with parameters obtained from a one-year dataset of MOS predictions and official forecast data issued by KMA. The best sets of neighbouring points and dependent point are statistically selected. According to verification, the RMSE of temperature predictions produced by the new algorithm was slightly lower than that of the original MOS predictions, and close to the RMSE of subjective forecasts. For wind speed and relative humidity, the new algorithm outperformed human forecasters.
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.
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.
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
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…
Mutual coupling, channel model, and BER for curvilinear antenna arrays
NASA Astrophysics Data System (ADS)
Huang, Zhiyong
interferers, Doppler spread and convergence are investigated. The tracking mode is introduced to the adaptive array system, and it further improves the BER. The benefit of using faster data rate (wider bandwidth) is discussed. In order to have better performance in a 3D space, the geometries of uniform spherical array (USAs) are presented and different configurations of USAs are discussed. The LMS algorithm based on temporal a priori information is applied to UCAs and USAs to beamform the patterns. Their performances are compared based on simulation results. Based on the analytical and simulation results, it can be concluded that mutual coupling slightly influences the performance of the adaptive array in communication systems. In addition, arrays with curvilinear geometries perform well in AWGN and fading channels.
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.
NASA Astrophysics Data System (ADS)
A. AL-Salhi, Yahya E.; Lu, Songfeng
2016-04-01
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)
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.
Algorithmic complexity of a protein
NASA Astrophysics Data System (ADS)
Dewey, T. Gregory
1996-07-01
The information contained in a protein's amino acid sequence dictates its three-dimensional structure. To quantitate the transfer of information that occurs in the protein folding process, the Kolmogorov information entropy or algorithmic complexity of the protein structure is investigated. The algorithmic complexity of an object provides a means of quantitating its information content. Recent results have indicated that the algorithmic complexity of microstates of certain statistical mechanical systems can be estimated from the thermodynamic entropy. In the present work, it is shown that the algorithmic complexity of a protein is given by its configurational entropy. Using this result, a quantitative estimate of the information content of a protein's structure is made and is compared to the information content of the sequence. Additionally, the mutual information between sequence and structure is determined. It is seen that virtually all the information contained in the protein structure is shared with the sequence.
Star pattern recognition algorithm aided by inertial information
NASA Astrophysics Data System (ADS)
Liu, Bao; Wang, Ke-dong; Zhang, Chao
2011-08-01
Star pattern recognition is one of the key problems of the celestial navigation. The traditional star pattern recognition approaches, such as the triangle algorithm and the star angular distance algorithm, are a kind of all-sky matching method whose recognition speed is slow and recognition success rate is not high. Therefore, the real time and reliability of CNS (Celestial Navigation System) is reduced to some extent, especially for the maneuvering spacecraft. However, if the direction of the camera optical axis can be estimated by other navigation systems such as INS (Inertial Navigation System), the star pattern recognition can be fulfilled in the vicinity of the estimated direction of the optical axis. The benefits of the INS-aided star pattern recognition algorithm include at least the improved matching speed and the improved success rate. In this paper, the direction of the camera optical axis, the local matching sky, and the projection of stars on the image plane are estimated by the aiding of INS firstly. Then, the local star catalog for the star pattern recognition is established in real time dynamically. The star images extracted in the camera plane are matched in the local sky. Compared to the traditional all-sky star pattern recognition algorithms, the memory of storing the star catalog is reduced significantly. Finally, the INS-aided star pattern recognition algorithm is validated by simulations. The results of simulations show that the algorithm's computation time is reduced sharply and its matching success rate is improved greatly.
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. PMID:24010024
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.
NASA Astrophysics Data System (ADS)
Adamowski, J. F.; Quilty, J.; Khalil, B.; Rathinasamy, M.
2014-12-01
This paper explores forecasting short-term urban water demand (UWD) (using only historical records) through a variety of machine learning techniques coupled with a novel input variable selection (IVS) procedure. The proposed IVS technique termed, bootstrap rank-ordered conditional mutual information for real-valued signals (brCMIr), is multivariate, nonlinear, nonparametric, and probabilistic. The brCMIr method was tested in a case study using water demand time series for two urban water supply system pressure zones in Ottawa, Canada to select the most important historical records for use with each machine learning technique in order to generate forecasts of average and peak UWD for the respective pressure zones at lead times of 1, 3, and 7 days ahead. All lead time forecasts are computed using Artificial Neural Networks (ANN) as the base model, and are compared with Least Squares Support Vector Regression (LSSVR), as well as a novel machine learning method for UWD forecasting: the Extreme Learning Machine (ELM). Results from one-way analysis of variance (ANOVA) and Tukey Honesty Significance Difference (HSD) tests indicate that the LSSVR and ELM models are the best machine learning techniques to pair with brCMIr. However, ELM has significant computational advantages over LSSVR (and ANN) and provides a new and promising technique to explore in UWD forecasting.
Amanpour, Behzad; Erfanian, Abbas
2013-01-01
An important issue in designing a practical brain-computer interface (BCI) is the selection of mental tasks to be imagined. Different types of mental tasks have been used in BCI including left, right, foot, and tongue motor imageries. However, the mental tasks are different from the actions to be controlled by the BCI. It is desirable to select a mental task to be consistent with the desired action to be performed by BCI. In this paper, we investigated the detecting the imagination of the hand grasping, hand opening, and hand reaching in one hand using electroencephalographic (EEG) signals. The results show that the ERD/ERS patterns, associated with the imagination of hand grasping, opening, and reaching are different. For classification of brain signals associated with these mental tasks and feature extraction, a method based on wavelet packet, regularized common spatial pattern (CSP), and mutual information is proposed. The results of an offline analysis on five subjects show that the two-class mental tasks can be classified with an average accuracy of 77.6% using proposed method. In addition, we examine the proposed method on datasets IVa from BCI Competition III and IIa from BCI Competition IV. PMID:24110165
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.
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…
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.
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.
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…
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)
Behavioral Ecology: Manipulative Mutualism.
Hughes, David P
2015-09-21
A new study reveals that an apparent mutualism between lycaenid caterpillars and their attendant ants may not be all it seems, as the caterpillars produce secretions that modify the brains and behavior of their attendant ants. PMID:26394105
Non-algorithmic access to calendar information in a calendar calculator with autism.
Mottron, L; Lemmens, K; Gagnon, L; Seron, X
2006-02-01
The possible use of a calendar algorithm was assessed in DBC, an autistic "savant" of normal measured intelligence. Testing of all the dates in a year revealed a random distribution of errors. Re-testing DBC on the same dates one year later shows that his errors were not stable across time. Finally, DBC was able to answer "reversed" questions that cannot be solved by a classical algorithm. These findings favor a non-algorithmic retrieval of calendar information. It is proposed that multidirectional, non-hierarchical retrieval of information, and solving problems in a non-algorithmic way, are involved in savant performances. The possible role of a functional rededication of low-level perceptual systems to the processing of symbolic information in savants is discussed. PMID:16453069
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.
A Lip Extraction Algorithm by Using Color Information Considering Obscurity
NASA Astrophysics Data System (ADS)
Shirasawa, Yoichi; Nishida, Makoto
This paper proposes a method for extracting lip shape and its location from sequential facial images by using color information. The proposed method has no need of extra information on a position nor a form in advance. It is also carried out without special conditions such as lipstick or lighting. Psychometric quantities of a metric hue angle, a metric hue difference and a rectangular coordinates, which are defined in CIE 1976 L*a*b* color space, are used for the extraction. The method employs fuzzy reasoning in order to consider obscurity in image data such as shade on the face. The experimental result indicate the effectiveness of the proposed method; 100 percent of facial images data was estimated a lip’s position, and about 94 percent of facial images data was extracted its shape.
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.
A Selective Encryption Algorithm Based on AES for Medical Information
Oh, Ju-Young; Chon, Ki-Hwan
2010-01-01
Objectives The transmission of medical information is currently a daily routine. Medical information needs efficient, robust and secure encryption modes, but cryptography is primarily a computationally intensive process. Towards this direction, we design a selective encryption scheme for critical data transmission. Methods We expand the advandced encrytion stanard (AES)-Rijndael with five criteria: the first is the compression of plain data, the second is the variable size of the block, the third is the selectable round, the fourth is the optimization of software implementation and the fifth is the selective function of the whole routine. We have tested our selective encryption scheme by C++ and it was compiled with Code::Blocks using a MinGW GCC compiler. Results The experimental results showed that our selective encryption scheme achieves a faster execution speed of encryption/decryption. In future work, we intend to use resource optimization to enhance the round operations, such as SubByte/InvSubByte, by exploiting similarities between encryption and decryption. Conclusions As encryption schemes become more widely used, the concept of hardware and software co-design is also a growing new area of interest. PMID:21818420
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.
Algorithmic information theory and the hidden variable question
NASA Astrophysics Data System (ADS)
Fuchs, Christopher
1992-02-01
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.
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.
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…
Robust Blind Learning Algorithm for Nonlinear Equalization Using Input Decision Information.
Xu, Lu; Huang, Defeng David; Guo, Yingjie Jay
2015-12-01
In this paper, we propose a new blind learning algorithm, namely, the Benveniste-Goursat input-output decision (BG-IOD), to enhance the convergence performance of neural network-based equalizers for nonlinear channel equalization. In contrast to conventional blind learning algorithms, where only the output of the equalizer is employed for updating system parameters, the BG-IOD exploits a new type of extra information, the input decision information obtained from the input of the equalizer, to mitigate the influence of the nonlinear equalizer structure on parameters learning, thereby leading to improved convergence performance. We prove that, with the input decision information, a desirable convergence capability that the output symbol error rate (SER) is always less than the input SER if the input SER is below a threshold, can be achieved. Then, the BG soft-switching technique is employed to combine the merits of both input and output decision information, where the former is used to guarantee SER convergence and the latter is to improve SER performance. Simulation results show that the proposed algorithm outperforms conventional blind learning algorithms, such as stochastic quadratic distance and dual mode constant modulus algorithm, in terms of both convergence performance and SER performance, for nonlinear equalization. PMID:25706894
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.
NASA Astrophysics Data System (ADS)
Vijayan, S.; Vani, K.; Sanjeevi, S.
2013-09-01
This study presents the development and implementation of an algorithm for automatic detection, classification and contextual information such as ejecta and the status of degradation of the lunar craters using SELENE panchromatic images. This algorithm works by a three-step process; first, the algorithm detects the simple lunar craters and classifies them into round/flat-floor using the structural profile pattern. Second, it extracts contextual information (ejecta) and notifies their presence if any, and associates it to the corresponding crater using the role of adjacency rule and the Markov random field theory. Finally, the algorithm examines each of the detected craters and assesses its state of degradation using the intensity variation over the crater edge. We applied the algorithm to 16 technically demanding test sites, which were chosen in a manner to represent all possible lunar surface conditions. Crater detection algorithm evaluation was carried out by means of manual analysis for their accuracy in detection, classification, ejecta and degraded-state identification along with a detailed qualitative assessment. The manual analysis depicts that the results are in agreement with the detection, while the overall statistical results reveal the detection performance as: Q ∼ 75% and precision ∼0.83. The results of detection and classification reveal that the simple lunar craters are dominated by the round-floor type rather than flat-floor type. In addition, the results also depicts that the lunar surface is predominant with sub-kilometer craters of lesser depth.
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... of all information furnished in the application in order to determine the safety and soundness of...
NASA Astrophysics Data System (ADS)
Chaturvedi, S.
2002-08-01
After a brief review of the notion of a full set of mutually unbiased bases in an N-dimensional Hilbert space, we summarize the work of Wootters and Fields (W K Wootters and B C Fields, Ann. Phys. 191, 363 (1989)) which gives an explicit construction for such bases for the case N=pr, where p is a prime. Further, we show how, by exploiting certain freedom in the Wootters-Fields construction, the task of explicitly writing down such bases can be simplified for the case when p is an odd prime. In particular, we express the results entirely in terms of the character vectors of the cyclic group G of order p. We also analyse the connection between mutually unbiased bases and the representations of G.
Developments of global greenhouse gas retrieval algorithm using Aerosol information from GOSAT-CAI
NASA Astrophysics Data System (ADS)
Kim, Woogyung; kim, Jhoon; Jung, Yeonjin; lee, Hanlim; Boesch, Hartmut
2014-05-01
Human activities have resulted in increasing atmospheric CO2 concentration since the beginning of Industrial Revolution to reaching CO2 concentration over 400 ppm at Mauna Loa observatory for the first time. (IPCC, 2007). However, our current knowledge of carbon cycle is still insufficient due to lack of observations. Satellite measurement is one of the most effective approaches to improve the accuracy of carbon source and sink estimates by monitoring the global CO2 distributions with high spatio-temporal resolutions (Rayner and O'Brien, 2001; Houweling et al., 2004). Currently, GOSAT has provided valuable information to observe global CO2 trend, enables our extended understanding of CO2 and preparation for future satellite plan. However, due to its physical limitation, GOSAT CO2 retrieval results have low spatial resolution and cannot cover wide area. Another obstruction of GOSAT CO2 retrieval is low data availability mainly due to contamination by clouds and aerosols. Especially, in East Asia, one of the most important aerosol source areas, it is hard to have successful retrieval result due to high aerosol concentration. The main purpose of this study is to improve data availability of GOSAT CO2 retrieval. In this study, current state of CO2 retrieval algorithm development is introduced and preliminary results are shown. This algorithm is based on optimal estimation method and utilized VLIDORT the vector discrete ordinate radiative transfer model. This proto type algorithm, developed from various combinations of state vectors to find accurate CO2 concentration, shows reasonable result. Especially the aerosol retrieval algorithm using GOSAT-CAI measurements, which provide aerosol information for the same area with GOSAT-FTS measurements, are utilized as input data of CO2 retrieval. Other CO2 retrieval algorithms use chemical transport model result or climatologically expected values as aerosol information which is the main reason of low data availability. With
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...
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)
Guo, D.; Lincoln, M. J.; Haug, P. J.; Turner, C. W.; Warner, H. R.
1992-01-01
Iliad is a diagnostic expert system for internal medicine. Iliad's "best information" mode is used to determine the most cost-effective findings to pursue next at any stage of a work-up. The "best information" algorithm combines an information content calculation together with a cost factor. The calculations then provide a rank-ordering of the alternative patient findings according to cost-effectiveness. The authors evaluated five information content models under two different strategies. The first, the single-frame strategy, considers findings only within the context of each individual disease frame. The second, the across-frame strategy, considers the information that a single finding could provide across several diseases. The study found that (1) a version of Shannon's information model performed the best under both strategies---this finding confirms the result of a previous independent study, (2) the across-frame strategy was preferred over the single-frame strategy. PMID:1482918
Combining spatial and spectral information to improve crop/weed discrimination algorithms
NASA Astrophysics Data System (ADS)
Yan, L.; Jones, G.; Villette, S.; Paoli, J. N.; Gée, C.
2012-01-01
Reduction of herbicide spraying is an important key to environmentally and economically improve weed management. To achieve this, remote sensors such as imaging systems are commonly used to detect weed plants. We developed spatial algorithms that detect the crop rows to discriminate crop from weeds. These algorithms have been thoroughly tested and provide robust and accurate results without learning process but their detection is limited to inter-row areas. Crop/Weed discrimination using spectral information is able to detect intra-row weeds but generally needs a prior learning process. We propose a method based on spatial and spectral information to enhance the discrimination and overcome the limitations of both algorithms. The classification from the spatial algorithm is used to build the training set for the spectral discrimination method. With this approach we are able to improve the range of weed detection in the entire field (inter and intra-row). To test the efficiency of these algorithms, a relevant database of virtual images issued from SimAField model has been used and combined to LOPEX93 spectral database. The developed method based is evaluated and compared with the initial method in this paper and shows an important enhancement from 86% of weed detection to more than 95%.
31 CFR 1024.220 - Customer identification programs for mutual funds.
Code of Federal Regulations, 2011 CFR
2011-07-01
... information available, and the mutual fund's customer base. At a minimum, these procedures must contain the... mutual fund must retain the information in paragraph (a)(3)(i)(A) of this section for five years after the date the account is closed. The mutual fund must retain the information in paragraphs...
31 CFR 1024.220 - Customer identification programs for mutual funds.
Code of Federal Regulations, 2013 CFR
2013-07-01
... information available, and the mutual fund's customer base. At a minimum, these procedures must contain the... mutual fund must retain the information in paragraph (a)(3)(i)(A) of this section for five years after the date the account is closed. The mutual fund must retain the information in paragraphs...
31 CFR 1024.220 - Customer identification programs for mutual funds.
Code of Federal Regulations, 2014 CFR
2014-07-01
... information available, and the mutual fund's customer base. At a minimum, these procedures must contain the... mutual fund must retain the information in paragraph (a)(3)(i)(A) of this section for five years after the date the account is closed. The mutual fund must retain the information in paragraphs...
31 CFR 1024.220 - Customer identification programs for mutual funds.
Code of Federal Regulations, 2012 CFR
2012-07-01
... information available, and the mutual fund's customer base. At a minimum, these procedures must contain the... mutual fund must retain the information in paragraph (a)(3)(i)(A) of this section for five years after the date the account is closed. The mutual fund must retain the information in paragraphs...
The impact of reconstruction algorithms and time of flight information on PET/CT image quality
Suljic, Alen; Tomse, Petra; Jensterle, Luka; Skrk, Damijan
2015-01-01
Background The aim of the study was to explore the influence of various time-of-flight (TOF) and non-TOF reconstruction algorithms on positron emission tomography/computer tomography (PET/CT) image quality. Materials and methods. Measurements were performed with a triple line source phantom, consisting of capillaries with internal diameter of ∼ 1 mm and standard Jaszczak phantom. Each of the data sets was reconstructed using analytical filtered back projection (FBP) algorithm, iterative ordered subsets expectation maximization (OSEM) algorithm (4 iterations, 24 subsets) and iterative True-X algorithm incorporating a specific point spread function (PSF) correction (4 iterations, 21 subsets). Baseline OSEM (2 iterations, 8 subsets) was included for comparison. Procedures were undertaken following the National Electrical Manufacturers Association (NEMA) NU-2-2001 protocol. Results Measurement of spatial resolution in full width at half maximum (FWHM) was 5.2 mm, 4.5 mm and 2.9 mm for FBP, OSEM and True-X; and 5.1 mm, 4.5 mm and 2.9 mm for FBP+TOF, OSEM+TOF and True-X+TOF respectively. Assessment of reconstructed Jaszczak images at different concentration ratios showed that incorporation of TOF information improves cold contrast, while hot contrast only slightly, however the most prominent improvement could be seen in background variability - noise reduction. Conclusions On the basis of the results of investigation we concluded, that incorporation of TOF information in reconstruction algorithm mostly affects reduction of the background variability (levels of noise in the image), while the improvement of spatial resolution due to incorporation of TOF information is negligible. Comparison of traditional and modern reconstruction algorithms showed that analytical FBP yields comparable results in some parameter measurements, such as cold contrast and relative count error. Iterative methods show highest levels of hot contrast, when TOF and PSF corrections were applied
Neural network and genetic algorithm technology in data mining of manufacturing quality information
NASA Astrophysics Data System (ADS)
Song, Limei; Qu, Xing-Hua; Ye, Shenghua
2002-03-01
Data Mining of Manufacturing Quality Information (MQI) is the key technology in Quality Lead Control. Of all the data mining methods, Neural Network and Genetic Algorithm is widely used for their strong advantages, such as non-linear, collateral, veracity etc. But if you singly use them, there will be some limitations preventing your research, such as convergence slowly, searching blindness etc. This paper combines their merits and use Genetic BP Algorithm in Data Mining of MQI. It has been successfully used in the key project of Natural Science Foundation of China (NSFC) - Quality Control and Zero-defect Engineering (Project No. 59735120).
Defense mutualisms enhance plant diversification.
Weber, Marjorie G; Agrawal, Anurag A
2014-11-18
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
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
I/O efficient algorithms and applications in geographic information systems
NASA Astrophysics Data System (ADS)
Danner, Andrew
Modern remote sensing methods such a laser altimetry (lidar) and Interferometric Synthetic Aperture Radar (IfSAR) produce georeferenced elevation data at unprecedented rates. Many Geographic Information System (GIS) algorithms designed for terrain modelling applications cannot process these massive data sets. The primary problem is that these data sets are too large to fit in the main internal memory of modern computers and must therefore reside on larger, but considerably slower disks. In these applications, the transfer of data between disk and main memory, or I/O, becomes the primary bottleneck. Working in a theoretical model that more accurately represents this two level memory hierarchy, we can develop algorithms that are I/O-efficient and reduce the amount of disk I/O needed to solve a problem. In this thesis we aim to modernize GIS algorithms and develop a number of I/O-efficient algorithms for processing geographic data derived from massive elevation data sets. For each application, we convert a geographic question to an algorithmic question, develop an I/O-efficient algorithm that is theoretically efficient, implement our approach and verify its performance using real-world data. The applications we consider include constructing a gridded digital elevation model (DEM) from an irregularly spaced point cloud, removing topological noise from a DEM, modeling surface water flow over a terrain, extracting river networks and watershed hierarchies from the terrain, and locating polygons containing query points in a planar subdivision. We initially developed solutions to each of these applications individually. However, we also show how to combine individual solutions to form a scalable geo-processing pipeline that seamlessly solves a sequence of sub-problems with little or no manual intervention. We present experimental results that demonstrate orders of magnitude improvement over previously known algorithms.
FctClus: A Fast Clustering Algorithm for Heterogeneous Information Networks.
Yang, Jing; Chen, Limin; Zhang, Jianpei
2015-01-01
It is important to cluster heterogeneous information networks. A fast clustering algorithm based on an approximate commute time embedding for heterogeneous information networks with a star network schema is proposed in this paper by utilizing the sparsity of heterogeneous information networks. First, a heterogeneous information network is transformed into multiple compatible bipartite graphs from the compatible point of view. Second, the approximate commute time embedding of each bipartite graph is computed using random mapping and a linear time solver. All of the indicator subsets in each embedding simultaneously determine the target dataset. Finally, a general model is formulated by these indicator subsets, and a fast algorithm is derived by simultaneously clustering all of the indicator subsets using the sum of the weighted distances for all indicators for an identical target object. The proposed fast algorithm, FctClus, is shown to be efficient and generalizable and exhibits high clustering accuracy and fast computation speed based on a theoretic analysis and experimental verification. PMID:26090857
NASA Astrophysics Data System (ADS)
Martínez, M. D.; Lana, X.
1991-03-01
The total inversion algorithm and some elements of Mathematical Information Theory are used in the treatment of travel-time data belonging to a seismic refraction experiment from the southern segment (Sardinia Channel) of the European Geotraverse Project. The inversion algorithm allows us to improve a preliminary propagating model obtained by means of usual trial and error procedure and to quantify the resolution degree of parameters defining the crust and upper mantle of such a model. Concepts related to Mathematical Information Theory detect some seismic profiles of the refraction experiment which give the most homogeneous coverage of the model in terms of number of trajectories crossing it. Finally, the efficiency of the inversion procedure is quantified and the uncertainties regarding knowledge of different parts of the model are also evaluated.
Information theoretic bounds of ATR algorithm performance for sidescan sonar target classification
NASA Astrophysics Data System (ADS)
Myers, Vincent L.; Pinto, Marc A.
2005-05-01
With research on autonomous underwater vehicles for minehunting beginning to focus on cooperative and adaptive behaviours, some effort is being spent on developing automatic target recognition (ATR) algorithms that are able to operate with high reliability under a wide range of scenarios, particularly in areas of high clutter density, and without human supervision. Because of the great diversity of pattern recognition methods and continuously improving sensor technology, there is an acute requirement for objective performance measures that are independent of any particular sensor, algorithm or target definitions. This paper approaches the ATR problem from the point of view of information theory in an attempt to place bounds on the performance of target classification algorithms that are based on the acoustic shadow of proud targets. Performance is bounded by analysing the simplest of shape classification tasks, that of differentiating between a circular and square shadow, thus allowing us to isolate system design criteria and assess their effect on the overall probability of classification. The information that can be used for target recognition in sidescan sonar imagery is examined and common information theory relationships are used to derive properties of the ATR problem. Some common bounds with analytical solutions are also derived.
NASA Astrophysics Data System (ADS)
Jang, Kwang Eun; Lee, Jongha; Lee, Kangui; Sung, Younghun; Lee, SeungDeok
2012-03-01
The X-ray tomosynthesis that measures several low dose projections over a limited angular range has been investigated as an alternative method of X-ray mammography for breast cancer screening. An extension of the scan coverage increases the vertical resolution by mitigating the interplane blurring. The implementation of a wide angle tomosynthesis equipment, however, may not be straightforward, mainly due to the image deterioration from the statistical noise in exterior projections. In this paper, we adopt the voltage modulation scheme to enlarge the coverage of the tomosynthesis scan. The higher tube voltages are used for outer angles, which offers the sufficient penetrating power for outlying frames in which the pathway of X-ray photons is elongated. To reconstruct 3D information from voltage modulated projections, we propose a novel algorithm, named information theoretic discrepancy based iterative reconstruction (IDIR) algorithm, which allows to account for the polychromatic acquisition model. The generalized information theoretic discrepancy (GID) is newly employed as the objective function. Using particular features of the GID, the cost function is derived in terms of imaginary variables with energy dependency, which leads to a tractable optimization problem without using the monochromatic approximation. In preliminary experiments using simulated and experimental equipment, the proposed imaging architecture and IDIR algorithm showed superior performances over conventional approaches.
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.
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.
An Effective Tri-Clustering Algorithm Combining Expression Data with Gene Regulation Information
Li, Ao; Tuck, David
2009-01-01
Motivation Bi-clustering algorithms aim to identify sets of genes sharing similar expression patterns across a subset of conditions. However direct interpretation or prediction of gene regulatory mechanisms may be difficult as only gene expression data is used. Information about gene regulators may also be available, most commonly about which transcription factors may bind to the promoter region and thus control the expression level of a gene. Thus a method to integrate gene expression and gene regulation information is desirable for clustering and analyzing. Methods By incorporating gene regulatory information with gene expression data, we define regulated expression values (REV) as indicators of how a gene is regulated by a specific factor. Existing bi-clustering methods are extended to a three dimensional data space by developing a heuristic TRI-Clustering algorithm. An additional approach named Automatic Boundary Searching algorithm (ABS) is introduced to automatically determine the boundary threshold. Results Results based on incorporating ChIP-chip data representing transcription factor-gene interactions show that the algorithms are efficient and robust for detecting tri-clusters. Detailed analysis of the tri-cluster extracted from yeast sporulation REV data shows genes in this cluster exhibited significant differences during the middle and late stages. The implicated regulatory network was then reconstructed for further study of defined regulatory mechanisms. Topological and statistical analysis of this network demonstrated evidence of significant changes of TF activities during the different stages of yeast sporulation, and suggests this approach might be a general way to study regulatory networks undergoing transformations. PMID:19838334
Ravari, Alireza Norouzzadeh; Taghirad, Hamid D
2014-10-01
In this paper the problem of loop closing from depth or camera image information in an unknown environment is investigated. A sparse model is constructed from a parametric dictionary for every range or camera image as mobile robot observations. In contrast to high-dimensional feature-based representations, in this model, the dimension of the sensor measurements' representations is reduced. Considering the loop closure detection as a clustering problem in high-dimensional space, little attention has been paid to the curse of dimensionality in the existing state-of-the-art algorithms. In this paper, a representation is developed from a sparse model of images, with a lower dimension than original sensor observations. Exploiting the algorithmic information theory, the representation is developed such that it has the geometrically transformation invariant property in the sense of Kolmogorov complexity. A universal normalized metric is used for comparison of complexity based representations of image models. Finally, a distinctive property of normalized compression distance is exploited for detecting similar places and rejecting incorrect loop closure candidates. Experimental results show efficiency and accuracy of the proposed method in comparison to the state-of-the-art algorithms and some recently proposed methods. PMID:24968363
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.
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
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
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. PMID:27505645
An algorithmic and information-theoretic approach to multimetric index construction
Schoolmaster, Donald R., Jr.; 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…
The Evolution of Interspecific Mutualisms
NASA Astrophysics Data System (ADS)
Doebeli, Michael; Knowlton, Nancy
1998-07-01
Interspecific mutualisms are widespread, but how they evolve is not clear. The Iterated Prisoner's Dilemma is the main theoretical tool to study cooperation, but this model ignores ecological differences between partners and assumes that amounts exchanged cannot themselves evolve. A more realistic model incorporating these features shows that strategies that succeed with fixed exchanges (e.g., Tit-for-Tat) cannot explain mutualism when exchanges vary because the amount exchanged evolves to 0. For mutualism to evolve, increased investments in a partner must yield increased returns, and spatial structure in competitive interactions is required. Under these biologically plausible assumptions, mutualism evolves with surprising ease. This suggests that, contrary to the basic premise of past theoretical analyses, overcoming a potential host's initial defenses may be a bigger obstacle for mutualism than the subsequent recurrence and spread of noncooperative mutants.
[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. PMID:22288336
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. PMID:26723233
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…
ERIC Educational Resources Information Center
Binnington, John P., Ed.
Articles included in this document are: (1) The Backgrounds of the Exchanges, by John P. Binnington, (2) Structure of the Soviet Scientific Information System, by Winifred Sewell, (3) Standards, Patents and Technical Reports, by Frank E. McKenna, (4) The Flow of Information to Users, by William S. Budington, (5) Research in Libraries and…
Fast algorithm for minutiae matching based on multiple-ridge information
NASA Astrophysics Data System (ADS)
Wang, Guoyou; Hu, Jing
2001-09-01
Autonomous real-time fingerprint verification, how to judge whether two fingerprints come from the same finger or not, is an important and difficult problem in AFIS (Automated Fingerprint Identification system). In addition to the nonlinear deformation, two fingerprints from the same finger may also be dissimilar due to translation or rotation, all these factors do make the dissimilarities more great and lead to misjudgment, thus the correct verification rate highly depends on the deformation degree. In this paper, we present a new fast simple algorithm for fingerprint matching, derived from the Chang et al.'s method, to solve the problem of optimal matches between two fingerprints under nonlinear deformation. The proposed algorithm uses not only the feature points of fingerprints but also the multiple information of the ridge to reduce the computational complexity in fingerprint verification. Experiments with a number of fingerprint images have shown that this algorithm has higher efficiency than the existing of methods due to the reduced searching operations.
12 CFR 12.101 - National bank disclosure of remuneration for mutual fund transactions.
Code of Federal Regulations, 2014 CFR
2014-01-01
... by § 12.4, for mutual fund transactions by providing this information to the customer in a current... mutual fund transactions. 12.101 Section 12.101 Banks and Banking COMPTROLLER OF THE CURRENCY, DEPARTMENT... Interpretations § 12.101 National bank disclosure of remuneration for mutual fund transactions. A national...
12 CFR 12.101 - National bank disclosure of remuneration for mutual fund transactions.
Code of Federal Regulations, 2013 CFR
2013-01-01
... by § 12.4, for mutual fund transactions by providing this information to the customer in a current... mutual fund transactions. 12.101 Section 12.101 Banks and Banking COMPTROLLER OF THE CURRENCY, DEPARTMENT... Interpretations § 12.101 National bank disclosure of remuneration for mutual fund transactions. A national...
12 CFR 12.101 - National bank disclosure of remuneration for mutual fund transactions.
Code of Federal Regulations, 2011 CFR
2011-01-01
... by § 12.4, for mutual fund transactions by providing this information to the customer in a current... mutual fund transactions. 12.101 Section 12.101 Banks and Banking COMPTROLLER OF THE CURRENCY, DEPARTMENT... Interpretations § 12.101 National bank disclosure of remuneration for mutual fund transactions. A national...
12 CFR 12.101 - National bank disclosure of remuneration for mutual fund transactions.
Code of Federal Regulations, 2012 CFR
2012-01-01
... by § 12.4, for mutual fund transactions by providing this information to the customer in a current... mutual fund transactions. 12.101 Section 12.101 Banks and Banking COMPTROLLER OF THE CURRENCY, DEPARTMENT... Interpretations § 12.101 National bank disclosure of remuneration for mutual fund transactions. A national...
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). PMID:24369664
Grief and Palliative Care: Mutuality
Moon, Paul J
2013-01-01
Grief and palliative care are interrelated and perhaps mutually inclusive. Conceptually and practically, grief intimately relates to palliative care, as both domains regard the phenomena of loss, suffering, and a desire for abatement of pain burden. Moreover, the notions of palliative care and grief may be construed as being mutually inclusive in terms of one cueing the other. As such, the discussions in this article will center on the conceptualizations of the mutuality between grief and palliative care related to end-of-life circumstances. Specifically, the complementarity of grief and palliative care, as well as a controvertible view thereof, will be considered. PMID:25278758
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.
Lu, Songjian; Lu, Kevin N.; Cheng, Shi-Yuan; Hu, Bo; Ma, Xiaojun; Nystrom, Nicholas; Lu, Xinghua
2015-01-01
An important goal of cancer genomic research is to identify the driving pathways underlying disease mechanisms and the heterogeneity of cancers. It is well known that somatic genome alterations (SGAs) affecting the genes that encode the proteins within a common signaling pathway exhibit mutual exclusivity, in which these SGAs usually do not co-occur in a tumor. With some success, this characteristic has been utilized as an objective function to guide the search for driver mutations within a pathway. However, mutual exclusivity alone is not sufficient to indicate that genes affected by such SGAs are in common pathways. Here, we propose a novel, signal-oriented framework for identifying driver SGAs. First, we identify the perturbed cellular signals by mining the gene expression data. Next, we search for a set of SGA events that carries strong information with respect to such perturbed signals while exhibiting mutual exclusivity. Finally, we design and implement an efficient exact algorithm to solve an NP-hard problem encountered in our approach. We apply this framework to the ovarian and glioblastoma tumor data available at the TCGA database, and perform systematic evaluations. Our results indicate that the signal-oriented approach enhances the ability to find informative sets of driver SGAs that likely constitute signaling pathways. PMID:26317392
Lu, Songjian; Lu, Kevin N; Cheng, Shi-Yuan; Hu, Bo; Ma, Xiaojun; Nystrom, Nicholas; Lu, Xinghua
2015-08-01
An important goal of cancer genomic research is to identify the driving pathways underlying disease mechanisms and the heterogeneity of cancers. It is well known that somatic genome alterations (SGAs) affecting the genes that encode the proteins within a common signaling pathway exhibit mutual exclusivity, in which these SGAs usually do not co-occur in a tumor. With some success, this characteristic has been utilized as an objective function to guide the search for driver mutations within a pathway. However, mutual exclusivity alone is not sufficient to indicate that genes affected by such SGAs are in common pathways. Here, we propose a novel, signal-oriented framework for identifying driver SGAs. First, we identify the perturbed cellular signals by mining the gene expression data. Next, we search for a set of SGA events that carries strong information with respect to such perturbed signals while exhibiting mutual exclusivity. Finally, we design and implement an efficient exact algorithm to solve an NP-hard problem encountered in our approach. We apply this framework to the ovarian and glioblastoma tumor data available at the TCGA database, and perform systematic evaluations. Our results indicate that the signal-oriented approach enhances the ability to find informative sets of driver SGAs that likely constitute signaling pathways. PMID:26317392
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 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.
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
Code of Federal Regulations, 2010 CFR
2010-04-01
... 26 Internal Revenue 8 2010-04-01 2010-04-01 false Tax on insurance companies (other than life or...-3 Tax on insurance companies (other than life or mutual), mutual marine insurance companies, mutual... insurance companies, other than life or mutual or foreign insurance companies not carrying on an...
Lee, S. H.; van der Werf, J. H. J.
2016-01-01
Summary: We have developed an algorithm for genetic analysis of complex traits using genome-wide SNPs in a linear mixed model framework. Compared to current standard REML software based on the mixed model equation, our method is substantially faster. The advantage is largest when there is only a single genetic covariance structure. The method is particularly useful for multivariate analysis, including multi-trait models and random regression models for studying reaction norms. We applied our proposed method to publicly available mice and human data and discuss the advantages and limitations. Availability and implementation: MTG2 is available in https://sites.google.com/site/honglee0707/mtg2. Contact: hong.lee@une.edu.au Supplementary information: Supplementary data are available at Bioinformatics online. PMID:26755623
Algorithms for biomagnetic source imaging with prior anatomical and physiological information
Hughett, P W
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.
A tomographic algorithm to determine tip-tilt information from laser guide stars
NASA Astrophysics Data System (ADS)
Reeves, A. P.; Morris, T. J.; Myers, R. M.; Bharmal, N. A.; Osborn, J.
2016-06-01
Laser Guide Stars (LGS) have greatly increased the sky-coverage of Adaptive Optics (AO) systems. Due to the up-link turbulence experienced by LGSs, a Natural Guide Star (NGS) is still required, preventing full sky-coverage. We present a method of obtaining partial tip-tilt information from LGSs alone in multi-LGS tomographic LGS AO systems. The method of LGS up-link tip-tilt determination is derived using a geometric approach, then an alteration to the Learn and Apply algorithm for tomographic AO is made to accommodate up-link tip-tilt. Simulation results are presented, verifying that the technique shows good performance in correcting high altitude tip-tilt, but not that from low altitudes. We suggest that the method is combined with multiple far off-axis tip-tilt NGSs to provide gains in performance and sky-coverage over current tomographic AO systems.
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.
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. PMID:24922548
Kwarciak, Kamil; Radom, Marcin; Formanowicz, Piotr
2016-04-01
The classical sequencing by hybridization takes into account a binary information about sequence composition. A given element from an oligonucleotide library is or is not a part of the target sequence. However, the DNA chip technology has been developed and it enables to receive a partial information about multiplicity of each oligonucleotide the analyzed sequence consist of. Currently, it is not possible to assess the exact data of such type but even partial information should be very useful. Two realistic multiplicity information models are taken into consideration in this paper. The first one, called "one and many" assumes that it is possible to obtain information if a given oligonucleotide occurs in a reconstructed sequence once or more than once. According to the second model, called "one, two and many", one is able to receive from biochemical experiment information if a given oligonucleotide is present in an analyzed sequence once, twice or at least three times. An ant colony optimization algorithm has been implemented to verify the above models and to compare with existing algorithms for sequencing by hybridization which utilize the additional information. The proposed algorithm solves the problem with any kind of hybridization errors. Computational experiment results confirm that using even the partial information about multiplicity leads to increased quality of reconstructed sequences. Moreover, they also show that the more precise model enables to obtain better solutions and the ant colony optimization algorithm outperforms the existing ones. Test data sets and the proposed ant colony optimization algorithm are available on: http://bioserver.cs.put.poznan.pl/download/ACO4mSBH.zip. PMID:26878124
[Community financing for health care in Africa: mutual health insurance].
Richard, V
2005-01-01
Health care in sub-Saharan Africa is increasingly financed by direct payments from the population. Mutual health insurance plans are developing to ensure better risk sharing. However mutual health insurance cannot fully resolve all equity issues. The low resources available for contribution and the limited availability of care services especially in the public sector cannot guarantee the quality of care necessary for the development of mutual health insurance. National governments must not forget their responsibility especially for defining and ensuring basic services that must be accessible to all. Will mutual health insurance plans be a stepping-stone to universal health care coverage and can these plans be successfully implemented in the context of an informal economy? PMID:15903084
Geometric direct search algorithms for image registration.
Lee, Seok; Choi, Minseok; Kim, Hyungmin; Park, Frank Chongwoo
2007-09-01
A widely used approach to image registration involves finding the general linear transformation that maximizes the mutual information between two images, with the transformation being rigid-body [i.e., belonging to SE(3)] or volume-preserving [i.e., belonging to SL(3)]. In this paper, we present coordinate-invariant, geometric versions of the Nelder-Mead optimization algorithm on the groups SL(3), SE(3), and their various subgroups, that are applicable to a wide class of image registration problems. Because the algorithms respect the geometric structure of the underlying groups, they are numerically more stable, and exhibit better convergence properties than existing local coordinate-based algorithms. Experimental results demonstrate the improved convergence properties of our geometric algorithms. PMID:17784595
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
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
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. PMID:27137240
Mutual Gains Means Everyone Wins.
ERIC Educational Resources Information Center
Flaherty, Bernard L.
1997-01-01
Mutual gains negotiation is an innovative system that emphasizes interests instead of positions and problem solving instead of preconceived solutions. The process can reverse social disintegration, reverse worker alienation, and address a shifting educational environment. It can resolve difficult labor-management problems such as contracting out,…
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…
Assessing the accuracy of prediction algorithms for classification: an overview.
Baldi, P; Brunak, S; Chauvin, Y; Andersen, C A; Nielsen, H
2000-05-01
We provide a unified overview of methods that currently are widely used to assess the accuracy of prediction algorithms, from raw percentages, quadratic error measures and other distances, and correlation coefficients, and to information theoretic measures such as relative entropy and mutual information. We briefly discuss the advantages and disadvantages of each approach. For classification tasks, we derive new learning algorithms for the design of prediction systems by directly optimising the correlation coefficient. We observe and prove several results relating sensitivity and specificity of optimal systems. While the principles are general, we illustrate the applicability on specific problems such as protein secondary structure and signal peptide prediction. PMID:10871264
Che, Yanting; Wang, Qiuying; Gao, Wei; Yu, Fei
2015-01-01
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. PMID:26445048
Che, Yanting; Wang, Qiuying; Gao, Wei; Yu, Fei
2015-01-01
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. PMID:26445048
Zhang, Yan-jun; Liu, Wen-zhe; Fu, Xing-hu; Bi, Wei-hong
2015-07-01
Traditional BOTDR optical fiber sensing system uses single channel sensing fiber to measure the information features. Uncontrolled factors such as cross-sensitivity can lead to a lower scattering spectrum fitting precision and make the information analysis deflection get worse. Therefore, a BOTDR system for detecting the multichannel sensor information at the same time is proposed. Also it provides a scattering spectrum analysis method for multichannel Brillouin optical time-domain reflection (BOT-DR) sensing system in order to extract high precision spectrum feature. This method combines the three times data fusion (TTDF) and the cuckoo Newton search (CNS) algorithm. First, according to the rule of Dixon and Grubbs criteria, the method uses the ability of TTDF algorithm in data fusion to eliminate the influence of abnormal value and reduce the error signal. Second, it uses the Cuckoo Newton search algorithm to improve the spectrum fitting and enhance the accuracy of Brillouin scattering spectrum information analysis. We can obtain the global optimal solution by smart cuckoo search. By using the optimal solution as the initial value of Newton algorithm for local optimization, it can ensure the spectrum fitting precision. The information extraction at different linewidths is analyzed in temperature information scattering spectrum under the condition of linear weight ratio of 1:9. The variances of the multichannel data fusion is about 0.0030, the center frequency of scattering spectrum is 11.213 GHz and the temperature error is less than 0.15 K. Theoretical analysis and simulation results show that the algorithm can be used in multichannel distributed optical fiber sensing system based on Brillouin optical time domain reflection. It can improve the accuracy of multichannel sensing signals and the precision of Brillouin scattering spectrum analysis effectively. PMID:26717729
Chun, Se Young
2016-03-01
PET and SPECT are important tools for providing valuable molecular information about patients to clinicians. Advances in nuclear medicine hardware technologies and statistical image reconstruction algorithms enabled significantly improved image quality. Sequentially or simultaneously acquired anatomical images such as CT and MRI from hybrid scanners are also important ingredients for improving the image quality of PET or SPECT further. High-quality anatomical information has been used and investigated for attenuation and scatter corrections, motion compensation, and noise reduction via post-reconstruction filtering and regularization in inverse problems. In this article, we will review works using anatomical information for molecular image reconstruction algorithms for better image quality by describing mathematical models, discussing sources of anatomical information for different cases, and showing some examples. PMID:26941855
Chen, Yanming; Zhao, Qingjie
2015-01-01
This paper deals with the problem of multi-target tracking in a distributed camera network using the square-root cubature information filter (SCIF). SCIF is an efficient and robust nonlinear filter for multi-sensor data fusion. In camera networks, multiple cameras are arranged in a dispersed manner to cover a large area, and the target may appear in the blind area due to the limited field of view (FOV). Besides, each camera might receive noisy measurements. To overcome these problems, this paper proposes a novel multi-target square-root cubature information weighted consensus filter (MTSCF), which reduces the effect of clutter or spurious measurements using joint probabilistic data association (JPDA) and proper weights on the information matrix and information vector. The simulation results show that the proposed algorithm can efficiently track multiple targets in camera networks and is obviously better in terms of accuracy and stability than conventional multi-target tracking algorithms. PMID:25951338
Chen, Yanming; Zhao, Qingjie
2015-01-01
This paper deals with the problem of multi-target tracking in a distributed camera network using the square-root cubature information filter (SCIF). SCIF is an efficient and robust nonlinear filter for multi-sensor data fusion. In camera networks, multiple cameras are arranged in a dispersed manner to cover a large area, and the target may appear in the blind area due to the limited field of view (FOV). Besides, each camera might receive noisy measurements. To overcome these problems, this paper proposes a novel multi-target square-root cubature information weighted consensus filter (MTSCF), which reduces the effect of clutter or spurious measurements using joint probabilistic data association (JPDA) and proper weights on the information matrix and information vector. The simulation results show that the proposed algorithm can efficiently track multiple targets in camera networks and is obviously better in terms of accuracy and stability than conventional multi-target tracking algorithms. PMID:25951338
Measurement reduction for mutual coupling calibration in DOA estimation
NASA Astrophysics Data System (ADS)
Aksoy, Taylan; Tuncer, T. Engin
2012-01-01
Mutual coupling is an important source of error in antenna arrays that should be compensated for super resolution direction-of-arrival (DOA) algorithms, such as Multiple Signal Classification (MUSIC) algorithm. A crucial step in array calibration is the determination of the mutual coupling coefficients for the antenna array. In this paper, a system theoretic approach is presented for the mutual coupling characterization of antenna arrays. The comprehension and implementation of this approach is simple leading to further advantages in calibration measurement reduction. In this context, a measurement reduction method for antenna arrays with omni-directional and identical elements is proposed which is based on the symmetry planes in the array geometry. The proposed method significantly decreases the number of measurements during the calibration process. This method is evaluated using different array types whose responses and the mutual coupling characteristics are obtained through numerical electromagnetic simulations. It is shown that a single calibration measurement is sufficient for uniform circular arrays. Certain important and interesting characteristics observed during the experiments are outlined.
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
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…
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.
Federal Register 2010, 2011, 2012, 2013, 2014
2013-06-12
..., at 77 FR 39322. FOR FURTHER INFORMATION CONTACT: Surety Bond Branch at (202) 874-6850. SUPPLEMENTARY INFORMATION: The underwriting limitation for the following company has been amended: Liberty Mutual Insurance... Fiscal Service Surety Companies Acceptable on Federal Bonds: Amendment--Liberty Mutual Insurance...
Code of Federal Regulations, 2012 CFR
2012-04-01
... 26 Internal Revenue 8 2012-04-01 2012-04-01 false Tax on insurance companies (other than life or... Companies § 1.831-3 Tax on insurance companies (other than life or mutual), mutual marine insurance...) All insurance companies, other than life or mutual or foreign insurance companies not carrying on...
Code of Federal Regulations, 2011 CFR
2011-04-01
... 26 Internal Revenue 8 2011-04-01 2011-04-01 false Tax on insurance companies (other than life or... Companies § 1.831-3 Tax on insurance companies (other than life or mutual), mutual marine insurance...) All insurance companies, other than life or mutual or foreign insurance companies not carrying on...
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... Companies § 1.831-3 Tax on insurance companies (other than life or mutual), mutual marine insurance...) All insurance companies, other than life or mutual or foreign insurance companies not carrying on...
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... Companies § 1.831-3 Tax on insurance companies (other than life or mutual), mutual marine insurance...) All insurance companies, other than life or mutual or foreign insurance companies not carrying on...
Mutual impedance computation between printed dipoles
NASA Astrophysics Data System (ADS)
Alexopoulos, N. G.; Rana, I. E.
1981-01-01
The mutual impedance between microstrip dipoles printed on a grounded substrate is computed. Results for the microstrip dipoles in broadside, collinear, and echelon arrangements are presented. The significance of surface wave to mutual coupling is discussed.
NASA Astrophysics Data System (ADS)
Tadaki, Kohtaro
2010-12-01
The statistical mechanical interpretation of algorithmic information theory (AIT, for short) was introduced and developed by our former works [K. Tadaki, Local Proceedings of CiE 2008, pp. 425-434, 2008] and [K. Tadaki, Proceedings of LFCS'09, Springer's LNCS, vol. 5407, pp. 422-440, 2009], where we introduced the notion of thermodynamic quantities, such as partition function Z(T), free energy F(T), energy E(T), statistical mechanical entropy S(T), and specific heat C(T), into AIT. We then discovered that, in the interpretation, the temperature T equals to the partial randomness of the values of all these thermodynamic quantities, where the notion of partial randomness is a stronger representation of the compression rate by means of program-size complexity. Furthermore, we showed that this situation holds for the temperature T itself, which is one of the most typical thermodynamic quantities. Namely, we showed that, for each of the thermodynamic quantities Z(T), F(T), E(T), and S(T) above, the computability of its value at temperature T gives a sufficient condition for T (0,1) to satisfy the condition that the partial randomness of T equals to T. In this paper, based on a physical argument on the same level of mathematical strictness as normal statistical mechanics in physics, we develop a total statistical mechanical interpretation of AIT which actualizes a perfect correspondence to normal statistical mechanics. We do this by identifying a microcanonical ensemble in the framework of AIT. As a result, we clarify the statistical mechanical meaning of the thermodynamic quantities of AIT.
Parents Helping Parents: Mutual Parenting Network Handbook.
ERIC Educational Resources Information Center
Simkinson, Charles H.; Redmond, Robert F.
Guidelines for mutual parenting are provided in this handbook. "Mutual parenting" means that everyone in the community shares the responsibility for the safety and well-being of the community's youngsters. Several topics are discussed in the 15 brief chapters of the handbook. Chapters 1 through 3 focus on the formation of a mutual parenting…
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 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).
Xiao, Chuan-Le; Chen, Xiao-Zhou; Du, Yang-Li; Sun, Xuesong; Zhang, Gong; He, Qing-Yu
2013-01-01
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/ . PMID:23163785
Chinese and American Women: Issues of Mutual Concern. Wingspread Brief.
ERIC Educational Resources Information Center
Johnson Foundation, Inc., Racine, WI.
This article briefly describes a conference of Chinese and American women held to discuss womens' issues and promote mutual understanding between the two groups. The cultural exchange of information at the conference focused on discussion of the All China Womens' Federation (ACWF); the roles of women in China and the United States in the areas of…
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
Non-Algorithmic Access to Calendar Information in a Calendar Calculator with Autism
ERIC Educational Resources Information Center
Mottron, L.; Lemmens, K.; Gagnon, L.; Seron, X.
2006-01-01
The possible use of a calendar algorithm was assessed in DBC, an autistic "savant" of normal measured intelligence. Testing of all the dates in a year revealed a random distribution of errors. Re-testing DBC on the same dates one year later shows that his errors were not stable across time. Finally, DBC was able to answer "reversed" questions that…
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.
Mutual Contextualization in Tripartite Graphs of Folksonomies
NASA Astrophysics Data System (ADS)
Yeung, Ching-Man Au; Gibbins, Nicholas; Shadbolt, Nigel
The use of tags to describe Web resources in a collaborative manner has experienced rising popularity among Web users in recent years. The product of such activity is given the name folksonomy, which can be considered as a scheme of organizing information in the users' own way. This research work attempts to analyze tripartite graphs - graphs involving users, tags and resources - of folksonomies and discuss how these elements acquire their semantics through their associations with other elements, a process we call mutual contextualization. By studying such process, we try to identify solutions to problems such as tag disambiguation, retrieving documents of similar topics and discovering communities of users. This paper describes the basis of the research work, mentions work done so far and outlines future plans.
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.
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.
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…
Mutual enhancement of diverse terminologies
Hardiker, Nicholas R.; Casey, Anne; Coenen, Amy; Konicek, Debra
2006-01-01
The purpose of this study was to map the North American Nursing Diagnosis Association (NANDA) nursing diagnoses to the International Classification for Nursing Practice Version 1.0 (ICNP®) and to compare the resulting representations and relationships to those within SNOMED® Clinical Terms (CT). Independent reviewers reached agreement on 25 (i.e. 64%) of the 39 parent-child relationships identified via the mappings between NANDA entities. Other parent-child relationships were more questionable and are in need of further discussion. This work does not seek to promote one terminology over any other. Rather, this collaborative effort has the potential to mutually enhance all three terminologies involved in the study: ICNP®, SNOMED® CT and NANDA. In doing so it provides an example of the type of collaborative effort that is needed to facilitate the development of tools to support interoperability at a global level. PMID:17238355
Entanglement in Mutually Unbiased Bases
NASA Astrophysics Data System (ADS)
Wiesniak, Marcin; Paterek, Tomasz; Zeilinger, Anton
2011-03-01
Higher-dimensional Hilbert spaces are still not fully explored. One issue concerns mutually unbiased bases (MUBs). For primes and their powers (e.g.), full sets of MUBs are known. The question of existence of all MUBs in composite dimensions is still open. We show that for all full sets of MUBs of a given dimension a certain entanglement measure of the bases is constant. This fact could be an argument either for or against the existence of full sets of MUBs in some dimensions and tells us that almost all MUBs are maximally entangled for high-dimensional composite systems, whereas this is not the case for prime dimensions. We present a new construction of MUBs in squared prime dimensions. We use only one entangling operation, which simplifies possible experiments. The construction gives only product states and maximally entangled states. Research supported by ERC Advanced Grant QIT4QAD and FWF SFB-grant F4007 of the Austrian Science Fund.
2012-01-01
Background Nowadays, it is possible to collect expression levels of a set of genes from a set of biological samples during a series of time points. Such data have three dimensions: gene-sample-time (GST). Thus they are called 3D microarray gene expression data. To take advantage of the 3D data collected, and to fully understand the biological knowledge hidden in the GST data, novel subspace clustering algorithms have to be developed to effectively address the biological problem in the corresponding space. Results We developed a subspace clustering algorithm called Order Preserving Triclustering (OPTricluster), for 3D short time-series data mining. OPTricluster is able to identify 3D clusters with coherent evolution from a given 3D dataset using a combinatorial approach on the sample dimension, and the order preserving (OP) concept on the time dimension. The fusion of the two methodologies allows one to study similarities and differences between samples in terms of their temporal expression profile. OPTricluster has been successfully applied to four case studies: immune response in mice infected by malaria (Plasmodium chabaudi), systemic acquired resistance in Arabidopsis thaliana, similarities and differences between inner and outer cotyledon in Brassica napus during seed development, and to Brassica napus whole seed development. These studies showed that OPTricluster is robust to noise and is able to detect the similarities and differences between biological samples. Conclusions Our analysis showed that OPTricluster generally outperforms other well known clustering algorithms such as the TRICLUSTER, gTRICLUSTER and K-means; it is robust to noise and can effectively mine the biological knowledge hidden in the 3D short time-series gene expression data. PMID:22475802
A moments-based algorithm for optimizing the information mined in post-processing spray images
NASA Astrophysics Data System (ADS)
Tan, Z. P.; Zinn, B. T.; Lubarsky, E.; Bibik, O.; Shcherbik, D.; Shen, L.
2016-02-01
The Moments-algorithm was developed to post-process images of sprays with the aim of characterizing the sprays' complex features (e.g., trajectory, dispersions and dynamics) in terms of simple curves, which can be used for developing correlation models and design tools. To achieve this objective, the algorithm calculates the first moments of pixel intensity values in instantaneous images of the spray to determine its center-of-gravity ( CG) trajectory (i.e., the spray density-weighted centerline trajectory). Thereafter, the second moments (i.e., standard-deviations, σ) of intensities are calculated to describe the dispersion of spray materials around the CG. After the instantaneous CG's and σ's for the instantaneous images have been obtained, they are arithmetically averaged to produce the average spray trajectories and dispersions. Additionally, the second moments of instantaneous CG's are used to characterize the spray's fluctuation magnitude. The Moments-algorithm has three main advantages over threshold-based edge-tracking and other conventional post-processing approaches: (1) It simultaneously describes the spray's instantaneous and average trajectories, dispersions and fluctuations, instead of just the outer/inner-edges, (2) the use of moments to define these spray characteristics is more physically meaningful because they reflect the statistical distribution of droplets within the spray plume instead of relying on an artificially interpreted "edge", and (3) the use of moments decreases the uncertainties of the post-processed results because moments are mathematically defined and do not depend upon user-adjustments/interpretations.
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.
A new FOD recognition algorithm based on multi-source information fusion and experiment analysis
NASA Astrophysics Data System (ADS)
Li, Yu; Xiao, Gang
2011-08-01
Foreign Object Debris (FOD) is a kind of substance, debris or article alien to an aircraft or system, which would potentially cause huge damage when it appears on the airport runway. Due to the airport's complex circumstance, quick and precise detection of FOD target on the runway is one of the important protections for airplane's safety. A multi-sensor system including millimeter-wave radar and Infrared image sensors is introduced and a developed new FOD detection and recognition algorithm based on inherent feature of FOD is proposed in this paper. Firstly, the FOD's location and coordinate can be accurately obtained by millimeter-wave radar, and then according to the coordinate IR camera will take target images and background images. Secondly, in IR image the runway's edges which are straight lines can be extracted by using Hough transformation method. The potential target region, that is, runway region, can be segmented from the whole image. Thirdly, background subtraction is utilized to localize the FOD target in runway region. Finally, in the detailed small images of FOD target, a new characteristic is discussed and used in target classification. The experiment results show that this algorithm can effectively reduce the computational complexity, satisfy the real-time requirement and possess of high detection and recognition probability.
The Competitive Strategy of Mutual Learning.
ERIC Educational Resources Information Center
Kelner, Stephen P.; Slavin, Lois
1998-01-01
Defines and discusses mutual learning in organizations. Suggests that the idea of people and companies sharing knowledge is becoming a competitive strategy because mutual learning enables executives and employees to increase their capacity to work together, accelerate organizational learning, and avoid mistakes. (JOW)
Victimization within Mutually Antipathetic Peer Relationships
ERIC Educational Resources Information Center
Card, Noel A.; Hodges, Ernest V. E.
2007-01-01
Children's victimization experiences within relationships characterized by mutual animosity were examined among 210 6th- and 7th-grade boys and girls. Participants reported that a greater proportion of mutual antipathies, relative to other peers, victimized them. Moreover, the receipt of victimization within antipathetic relationships was greater…
Research on the influence of scan path of image on the performance of information hiding algorithm
NASA Astrophysics Data System (ADS)
Yan, Su; Xie, Chengjun; Huang, Ruirui; Xu, Xiaolong
2015-12-01
This paper carried out a study on information hiding performance using technology of histogram shift combining hybrid transform. As the approach of data selection, scan path of images is discussed. Ten paths were designed and tested on international standard testing images. Experiment results indicate that scan path has a great influence on the performance of image lossless information hiding. For selected test image, the peak of optimized path increased up to 9.84% while that of the worst path dropped 24.2%, that is to say, for different test images, scan path greatly impacts information hiding performance by influencing image redundancy and sparse matrix.
[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. PMID:23945438
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. PMID:26381742
Mutual Orbits of Transneptunian Binaries
NASA Astrophysics Data System (ADS)
Grundy, William M.; Noll, K. S.; Roe, H. G.; Porter, S. B.; Trujillo, C. A.; Benecchi, S. D.; Buie, M. W.
2012-10-01
We report the latest results from a program of high spatial resolution imaging to resolve the individual components of binary transneptunian objects. These observations use Hubble Space Telescope and also laser guide star adaptive optics systems on Keck and Gemini telescopes on Mauna Kea. From relative astrometry over multiple epochs, we determine the mutual orbits of the components, and thus the total masses of the systems. Accurate masses anchor subsequent detailed investigations into the physical characteristics of these systems. For instance, dynamical masses enable computation of bulk densities for systems where the component sizes can be estimated from other measurements. Additionally, patterns in the ensemble characteristics of binary orbits offer clues to circumstances in the protoplanetary nebula when these systems formed, as well as carrying imprints of various subsequent dynamical evolution processes. The growing ensemble of known orbits shows intriguing patterns that can shed light on the evolution of this population of distant objects. This work has been supported by an NSF Planetary Astronomy grant and by several Hubble Space Telescope and NASA Keck data analysis grants. The research makes use of data from the Gemini Observatory obtained through NOAO survey program 11A-0017, from a large number of Hubble Space Telescope programs, and from several NASA Keck programs.
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.
Goulermas, John Y; Findlow, Andrew H; Nester, Christopher J; Liatsis, Panos; Zeng, Xiao-Jun; Kenney, Laurence P J; Tresadern, Phil; Thies, Sibylle B; Howard, David
2008-09-01
Wearable human movement measurement systems are increasingly popular as a means of capturing human movement data in real-world situations. Previous work has attempted to estimate segment kinematics during walking from foot acceleration and angular velocity data. In this paper, we propose a novel neural network [GRNN with Auxiliary Similarity Information (GASI)] that estimates joint kinematics by taking account of proximity and gait trajectory slope information through adaptive weighting. Furthermore, multiple kernel bandwidth parameters are used that can adapt to the local data density. To demonstrate the value of the GASI algorithm, hip, knee, and ankle joint motions are estimated from acceleration and angular velocity data for the foot and shank, collected using commercially available wearable sensors. Reference hip, knee, and ankle kinematic data were obtained using externally mounted reflective markers and infrared cameras for subjects while they walked at different speeds. The results provide further evidence that a neural net approach to the estimation of joint kinematics is feasible and shows promise, but other practical issues must be addressed before this approach is mature enough for clinical implementation. Furthermore, they demonstrate the utility of the new GASI algorithm for making estimates from continuous periodic data that include noise and a significant level of variability. PMID:18779089
Zhang, Huanping; Song, Xiaofeng; Wang, Huinan; Zhang, Xiaobai
2009-01-01
Computational analysis of microarray data has provided an effective way to identify disease-related genes. Traditional disease gene selection methods from microarray data such as statistical test always focus on differentially expressed genes in different samples by individual gene prioritization. These traditional methods might miss differentially coexpressed (DCE) gene subsets because they ignore the interaction between genes. In this paper, MIClique algorithm is proposed to identify DEC gene subsets based on mutual information and clique analysis. Mutual information is used to measure the coexpression relationship between each pair of genes in two different kinds of samples. Clique analysis is a commonly used method in biological network, which generally represents biological module of similar function. By applying the MIClique algorithm to real gene expression data, some DEC gene subsets which correlated under one experimental condition but uncorrelated under another condition are detected from the graph of colon dataset and leukemia dataset. PMID:20169000
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…
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...
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…
ERIC Educational Resources Information Center
McNamara, David; Pettitt, Deirdre
1991-01-01
Reviews a body of psychological research which investigated children's errors in subtraction computations to assess whether the literature offers valuable, relevant information for those teaching subtraction and remedying student errors. It concludes that the research offers teachers little, so they must fall back on their knowledge and…
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…
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.
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.
Variation between self- and mutual assessment in animal contests.
Mesterton-Gibbons, Mike; Heap, Stephen M
2014-02-01
Limited resources lead animals into conflicts of interest, which are resolved when an individual withdraws from a direct contest. Current theory suggests that the decision to withdraw can be based on a threshold derived from an individual's own state (self-assessment) or on a comparison between their own state and their opponent's (mutual assessment). The observed variation between these assessment strategies in nature does not conform to theory. Thus, we require theoretical developments that explain the functional significance of different assessment strategies. We consider a hawk-dove game with two discrete classes that differ in fighting ability, in which the players strategically decide on their investment toward mutual assessment. Analysis of the model indicates that there are simultaneous trade-offs relating to assessment strategies. First, weak individuals in a population must decide on whether to acquire information about their opponents at the cost of providing opponents with information about themselves. Secondly, all individuals must decide between investing in mutual assessment and being persistent in contests. Our analysis suggests that the potential for individuals to make errors during contests and differences in the consequences of sharing information within a population may serve as fundamental concepts for explaining variation in assessment strategy. PMID:24464195
Funeriu; Lehn; Fromm; Fenske
2000-06-16
The multisubunit ligand 2 combines two complexation substructures known to undergo, with specific metal ions, distinct self-assembly processes to form a double-helical and a grid-type structure, respectively. The binding information contained in this molecular strand may be expected to generate, in a strictly predetermined and univocal fashion, two different, well-defined output inorganic architectures depending on the set of metal ions, that is, on the coordination algorithm used. Indeed, as predicted, the self-assembly of 2 with eight CuII and four CuI yields the intertwined structure D1. It results from a crossover of the two assembly subprograms and has been fully characterized by crystal structure determination. On the other hand, when the instructions of strand 2 are read out with a set of eight CuI and four MII (M = Fe, Co, Ni, Cu) ions, the architectures C1-C4, resulting from a linear combination of the two subprograms, are obtained, as indicated by the available physico-chemical and spectral data. Redox interconversion of D1 and C4 has been achieved. These results indicate that the same molecular information may yield different output structures depending on how it is processed, that is, depending on the interactional (coordination) algorithm used to read it. They have wide implications for the design and implementation of programmed chemical systems, pointing towards multiprocessing capacity, in a one code/ several outputs scheme, of potential significance for molecular computation processes and possibly even with respect to information processing in biology. PMID:10926214
Novel Algorithms for the Identification of Biologically Informative Chemical Diversity Metrics
Theertham, Bhargav; Wang, Jenna. L.; Fang, Jianwen; Lushington, Gerald H.
2009-01-01
Despite great advances in the efficiency of analytical and synthetic chemistry, time and available starting material still limit the number of unique compounds that can be practically synthesized and evaluated as prospective therapeutics. Chemical diversity analysis (the capacity to identify finite diverse subsets that reliably represent greater manifolds of drug-like chemicals) thus remains an important resource in drug discovery. Despite an unproven track record, chemical diversity has also been used to posit, from preliminary screen hits, new compounds with similar or better activity. Identifying diversity metrics that demonstrably encode bioactivity trends is thus of substantial potential value for intelligent assembly of targeted screens. This paper reports novel algorithms designed to simultaneously reflect chemical similarity or diversity trends and apparent bioactivity in compound collections. An extensive set of descriptors are evaluated within large NCI screening data sets according to bioactivity differentiation capacities, quantified as the ability to co-localize known active species into bioactive-rich K-means clusters. One method tested for descriptor selection orders features according to relative variance across a set of training compounds, and samples increasingly finer subset meshes for descriptors whose exclusion from the model induces drastic drops in relative bioactive colocalization. This yields metrics with reasonable bioactive enrichment (greater than 50% of all bioactive compounds collected into clusters or cells with significantly enriched active/inactive rates) for each of the four data sets examined herein. A second method replaces variance by an active/inactive divergence score, achieving comparable enrichment via a much more efficient search process. Combinations of the above metrics are tested in 2D rectilinear diversity models, achieving similarly successful colocalization statistics, with metrics derived from the active
Estimation of the Mutual Time Delay of Signals with Pseudorandom Frequency Hopping
NASA Astrophysics Data System (ADS)
Ershov, R. A.; Morozov, O. A.; Fidelman, V. R.
2015-07-01
We propose a method for determining the mutual time delay during the propagation of signals with pseudorandom frequency hopping in different channels. A modified algorithm for calculating the uncertainty function, which permits calculation parallelization, is used to compensate for the influence of the Doppler effect during the signal recording. The results of studying the efficiency of the proposed method are presented.
76 FR 71437 - Mutual Savings Association Advisory Committee
Federal Register 2010, 2011, 2012, 2013, 2014
2011-11-17
... Office of the Comptroller of the Currency Mutual Savings Association Advisory Committee AGENCY... Mutual Savings Association Advisory Committee (MSAAC or Committee) formerly administered by the Office of... of and challenges facing mutual savings associations. The OCC is seeking nominations of...
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.
Hsu, Yi-Yu; Chen, Hung-Yu; Kao, Hung-Yu
2013-01-01
Background Determining the semantic relatedness of two biomedical terms is an important task for many text-mining applications in the biomedical field. Previous studies, such as those using ontology-based and corpus-based approaches, measured semantic relatedness by using information from the structure of biomedical literature, but these methods are limited by the small size of training resources. To increase the size of training datasets, the outputs of search engines have been used extensively to analyze the lexical patterns of biomedical terms. Methodology/Principal Findings In this work, we propose the Mutually Reinforcing Lexical Pattern Ranking (ReLPR) algorithm for learning and exploring the lexical patterns of synonym pairs in biomedical text. ReLPR employs lexical patterns and their pattern containers to assess the semantic relatedness of biomedical terms. By combining sentence structures and the linking activities between containers and lexical patterns, our algorithm can explore the correlation between two biomedical terms. Conclusions/Significance The average correlation coefficient of the ReLPR algorithm was 0.82 for various datasets. The results of the ReLPR algorithm were significantly superior to those of previous methods. PMID:24348899
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:
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
Certainty relations, mutual entanglement, and nondisplaceable manifolds
NASA Astrophysics Data System (ADS)
Puchała, Zbigniew; Rudnicki, Łukasz; Chabuda, Krzysztof; Paraniak, Mikołaj; Życzkowski, Karol
2015-09-01
We derive explicit bounds for the average entropy characterizing measurements of a pure quantum state of size N in L orthogonal bases. Lower bounds lead to novel entropic uncertainty relations, while upper bounds allow us to formulate universal certainty relations. For L =2 the maximal average entropy saturates at logN because there exists a mutually coherent state, but certainty relations are shown to be nontrivial for L ≥3 measurements. In the case of a prime power dimension, N =pk , and the number of measurements L =N +1 , the upper bound for the average entropy becomes minimal for a collection of mutually unbiased bases. An analogous approach is used to study entanglement with respect to L different splittings of a composite system linked by bipartite quantum gates. We show that, for any two-qubit unitary gate U ∈U(4 ) there exist states being mutually separable or mutually entangled with respect to both splittings (related by U ) of the composite system. The latter statement follows from the fact that the real projective space R P3⊂C P3 is nondisplaceable by a unitary transformation. For L =3 splittings the maximal sum of L entanglement entropies is conjectured to achieve its minimum for a collection of three mutually entangled bases, formed by two mutually entangling gates.
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. PMID:26335709
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
78 FR 64600 - Mutual Savings Association Advisory Committee
Federal Register 2010, 2011, 2012, 2013, 2014
2013-10-29
... Office of the Comptroller of the Currency Mutual Savings Association Advisory Committee AGENCY... Mutual Savings Association Advisory Committee (MSAAC). DATES: A public meeting of the MSAAC will be held... mutual savings associations and other issues of concern to the existing mutual savings...
75 FR 77048 - Mutual Savings Association Advisory Committee
Federal Register 2010, 2011, 2012, 2013, 2014
2010-12-10
... Office of Thrift Supervision Mutual Savings Association Advisory Committee AGENCY: Department of the... Thrift Supervision has determined that the renewal of the ] Charter of the OTS Mutual Savings Association... facing mutual savings associations. DATES: The Charter of the OTS Mutual Savings Association...
Group Differences in the Mutual Gaze of Chimpanzees (Pan Troglodytes)
ERIC Educational Resources Information Center
Bard, Kim A.; Myowa-Yamakoshi, Masako; Tomonaga, Masaki; Tanaka, Masayuki; Costall, Alan; Matsuzawa, Tetsuro
2005-01-01
A comparative developmental framework was used to determine whether mutual gaze is unique to humans and, if not, whether common mechanisms support the development of mutual gaze in chimpanzees and humans. Mother-infant chimpanzees engaged in approximately 17 instances of mutual gaze per hour. Mutual gaze occurred in positive, nonagonistic…
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 Section 575.3 Banks and Banking OFFICE OF THRIFT SUPERVISION, DEPARTMENT OF THE TREASURY MUTUAL HOLDING COMPANIES § 575.3 Mutual holding company reorganizations. A mutual savings association may reorganize...
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 Section 575.3 Banks and Banking OFFICE OF THRIFT SUPERVISION, DEPARTMENT OF THE TREASURY MUTUAL HOLDING COMPANIES § 575.3 Mutual holding company reorganizations. A mutual savings association may reorganize...
12 CFR 144.1 - Federal mutual charter.
Code of Federal Regulations, 2012 CFR
2012-01-01
... 12 Banks and Banking 1 2012-01-01 2012-01-01 false Federal mutual charter. 144.1 Section 144.1 Banks and Banking COMPTROLLER OF THE CURRENCY, DEPARTMENT OF THE TREASURY FEDERAL MUTUAL SAVINGS ASSOCIATIONS-CHARTER AND BYLAWS Charter § 144.1 Federal mutual charter. A Federal mutual savings association shall have a charter in the following...
12 CFR 544.1 - Federal mutual charter.
Code of Federal Regulations, 2011 CFR
2011-01-01
... 12 Banks and Banking 5 2011-01-01 2011-01-01 false Federal mutual charter. 544.1 Section 544.1 Banks and Banking OFFICE OF THRIFT SUPERVISION, DEPARTMENT OF THE TREASURY FEDERAL MUTUAL SAVINGS ASSOCIATIONS-CHARTER AND BYLAWS Charter § 544.1 Federal mutual charter. A Federal mutual savings association shall have a charter in the following...
12 CFR 144.1 - Federal mutual charter.
Code of Federal Regulations, 2013 CFR
2013-01-01
... 12 Banks and Banking 1 2013-01-01 2013-01-01 false Federal mutual charter. 144.1 Section 144.1 Banks and Banking COMPTROLLER OF THE CURRENCY, DEPARTMENT OF THE TREASURY FEDERAL MUTUAL SAVINGS ASSOCIATIONS-CHARTER AND BYLAWS Charter § 144.1 Federal mutual charter. A Federal mutual savings association shall have a charter in the following...
12 CFR 544.1 - Federal mutual charter.
Code of Federal Regulations, 2013 CFR
2013-01-01
... 12 Banks and Banking 6 2013-01-01 2012-01-01 true Federal mutual charter. 544.1 Section 544.1 Banks and Banking OFFICE OF THRIFT SUPERVISION, DEPARTMENT OF THE TREASURY FEDERAL MUTUAL SAVINGS ASSOCIATIONS-CHARTER AND BYLAWS Charter § 544.1 Federal mutual charter. A Federal mutual savings association shall have a charter in the following...
12 CFR 544.5 - Federal mutual savings association bylaws.
Code of Federal Regulations, 2011 CFR
2011-01-01
... 12 Banks and Banking 5 2011-01-01 2011-01-01 false Federal mutual savings association bylaws. 544.5 Section 544.5 Banks and Banking OFFICE OF THRIFT SUPERVISION, DEPARTMENT OF THE TREASURY FEDERAL MUTUAL SAVINGS ASSOCIATIONS-CHARTER AND BYLAWS Bylaws § 544.5 Federal mutual savings association bylaws. (a) General. A Federal mutual...
Mutualisms in a changing world: an evolutionary perspective.
Toby Kiers, E; Palmer, Todd M; Ives, Anthony R; Bruno, John F; Bronstein, Judith L
2010-12-01
Ecology Letters (2010) 13: 1459-1474 ABSTRACT: There is growing concern that rapid environmental degradation threatens mutualistic interactions. Because mutualisms can bind species to a common fate, mutualism breakdown has the potential to expand and accelerate effects of global change on biodiversity loss and ecosystem disruption. The current focus on the ecological dynamics of mutualism under global change has skirted fundamental evolutionary issues. Here, we develop an evolutionary perspective on mutualism breakdown to complement the ecological perspective, by focusing on three processes: (1) shifts from mutualism to antagonism, (2) switches to novel partners and (3) mutualism abandonment. We then identify the evolutionary factors that may make particular classes of mutualisms especially susceptible or resistant to breakdown and discuss how communities harbouring mutualisms may be affected by these evolutionary responses. We propose a template for evolutionary research on mutualism resilience and identify conservation approaches that may help conserve targeted mutualisms in the face of environmental change. PMID:20955506
Integrating plant carbon dynamics with mutualism ecology.
Pringle, Elizabeth G
2016-04-01
71 I. 71 II. 72 III. 73 IV. 74 V. 74 74 References 74 SUMMARY: 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. PMID:26414800
Mutual inductance between piecewise-linear loops
NASA Astrophysics Data System (ADS)
Cristina Barroso, Ana; Silva, J. P.
2013-11-01
We consider a current-carrying wire loop made out of linear segments of arbitrary sizes and directions in three-dimensional space. We develop expressions to calculate its vector potential and magnetic field at all points in space. We then calculate the mutual inductance between two such (non-intersecting) piecewise-linear loops. As simple applications, we consider in detail the mutual inductance between two square wires of equal length that either lie in the same plane or lie in parallel horizontal planes with their centers on the same vertical axis. Our expressions can also be used to obtain approximations to the mutual inductance between wires of arbitrary three-dimensional shapes.
Code of Federal Regulations, 2011 CFR
2011-04-01
... 26 Internal Revenue 8 2011-04-01 2011-04-01 false Tax on insurance companies (other than life or... insurance companies (other than life or mutual), mutual marine insurance companies, and mutual fire insurance companies issuing perpetual policies. (a) All insurance companies, other than life or mutual...
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... insurance companies (other than life or mutual), mutual marine insurance companies, and mutual fire insurance companies issuing perpetual policies. (a) All insurance companies, other than life or mutual...
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... insurance companies (other than life or mutual), mutual marine insurance companies, and mutual fire insurance companies issuing perpetual policies. (a) All insurance companies, other than life or mutual...
Code of Federal Regulations, 2012 CFR
2012-04-01
... 26 Internal Revenue 8 2012-04-01 2012-04-01 false Tax on insurance companies (other than life or... insurance companies (other than life or mutual), mutual marine insurance companies, and mutual fire insurance companies issuing perpetual policies. (a) All insurance companies, other than life or mutual...
Code of Federal Regulations, 2010 CFR
2010-04-01
... 26 Internal Revenue 8 2010-04-01 2010-04-01 false Tax on insurance companies (other than life or... companies (other than life or mutual), mutual marine insurance companies, and mutual fire insurance companies issuing perpetual policies. (a) All insurance companies, other than life or mutual or...
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. PMID:26792458
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.
2015-01-01
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
Ru, Xiao; Song, Ce; Lin, Zijing
2016-05-15
The genetic algorithm (GA) is an intelligent approach for finding minima in a highly dimensional parametric space. However, the success of GA searches for low energy conformations of biomolecules is rather limited so far. Herein an improved GA scheme is proposed for the conformational search of oligopeptides. A systematic analysis of the backbone dihedral angles of conformations of amino acids (AAs) and dipeptides is performed. The structural information is used to design a new encoding scheme to improve the efficiency of GA search. Local geometry optimizations based on the energy calculations by the density functional theory are employed to safeguard the quality and reliability of the GA structures. The GA scheme is applied to the conformational searches of Lys, Arg, Met-Gly, Lys-Gly, and Phe-Gly-Gly representative of AAs, dipeptides, and tripeptides with complicated side chains. Comparison with the best literature results shows that the new GA method is both highly efficient and reliable by providing the most complete set of the low energy conformations. Moreover, the computational cost of the GA method increases only moderately with the complexity of the molecule. The GA scheme is valuable for the study of the conformations and properties of oligopeptides. © 2016 Wiley Periodicals, Inc. PMID:26833761
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 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
NASA Astrophysics Data System (ADS)
Kozlovskaya, Elena
2000-06-01
This paper presents an inversion algorithm that can be used to solve a wide range of geophysical nonlinear inverse problems. The algorithm in based upon the principle of a direct search for the optimal solution in the parameter space. The main difference of the algorithm from existing techniques such as genetic algorithms and simulated annealing is that the optimum search is performed under control of a priori information formulated as a fuzzy set in the parameter space. In such a formulation the inverse problem becomes a multiobjective optimization problem with two objective functions, one of them is a membership function of the fuzzy set of feasible solutions, the other is the conditional probability density function of the observed data. The solution to such a problem is a set of Pareto optimal solutions that is constructed in the parameter space by a three-stage search procedure. The advantage of the proposed technique is that it provides the possibility of involving a wide range of non-probabilistic a priori information into the inversion procedure and can be applied to the solution of strongly nonlinear problems. It allows one to decrease the number of forward-problem calculations due to selective sampling of trial points from the parameter space. The properties of the algorithm are illustrated with an application to a local earthquake hypocentre location problem with synthetic and real data.
Mutual phenomena of Saturn's satellites in 1979-1980
NASA Technical Reports Server (NTRS)
Aksnes, K.; Franklin, F. A.
1978-01-01
Using two sets of orbital elements and the radii of the Saturnian satellites 1 (Mimas) through 7 (Hyperion), we find that from October 1979 until August 1980 nearly 300 mutual eclipses and occultations involving these bodies will occur. To allow for the expected errors in the satellite ephemerides, we repeat these calculations in order to obtain the additional events that occur when all satellite radii (save Titan's) are increased by 1000 km. A third listing predicts eclipses of satellites by (the shadow of) the ring. Photometric observations of a large number of these events will add much precise information to our knowledge of the Saturnian system at a critical time.
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... Thrift Supervision, 1700 G Street, NW., Washington, DC 20552, by fax to (202) 906-6518, or by e-mail to...'s Office, Office of Thrift Supervision, 1700 G Street, NW., Washington, DC 20552....
Mutual diffusion in a binary isotopic mixture.
Sharma, Raman; Tankeshwar, K
2010-11-17
The mass dependence of the mutual diffusion coefficient, in a binary equimolar mixture of Lennard-Jones fluids, is studied within Mori's memory function formalism. A phenomenological form of the memory function is used to study the time evolution of the self- and relative velocity correlation functions. The diffusion coefficients are calculated from the relevant velocity correlation functions using the Green-Kubo integral formula. Like the self-diffusion coefficient, the mutual diffusion coefficient is also found to be weakly dependent on the mass ratio. The present study shows that the minimum value that the mutual diffusion coefficient in an equimolar mixture of isotopic fluids can have is √(1/2) times the self-diffusion coefficient of any of the species when in isolation. Further, the contribution of the dynamic/distinct cross correlations to the mutual diffusion coefficient is found to be small and positive for the whole range of the mass ratio which is consistent with earlier molecular dynamics results. PMID:21339621
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
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…
NASA Astrophysics Data System (ADS)
Zhou, Xu; Liu, Yanheng; Li, Bin; Sun, Geng
2015-10-01
Identifying community structures in static network misses the opportunity to capture the evolutionary patterns. So community detection in dynamic network has attracted many researchers. In this paper, a multiobjective biogeography based optimization algorithm with decomposition (MBBOD) is proposed to solve community detection problem in dynamic networks. In the proposed algorithm, the decomposition mechanism is adopted to optimize two evaluation objectives named modularity and normalized mutual information simultaneously, which measure the quality of the community partitions and temporal cost respectively. A novel sorting strategy for multiobjective biogeography based optimization is presented for comparing quality of habitats to get species counts. In addition, problem-specific migration and mutation model are introduced to improve the effectiveness of the new algorithm. Experimental results both on synthetic and real networks demonstrate that our algorithm is effective and promising, and it can detect communities more accurately in dynamic networks compared with DYNMOGA and FaceNet.
A Multipopulation Coevolutionary Strategy for Multiobjective Immune Algorithm
Shi, Jiao; Gong, Maoguo; Ma, Wenping; Jiao, Licheng
2014-01-01
How to maintain the population diversity is an important issue in designing a multiobjective evolutionary algorithm. This paper presents an enhanced nondominated neighbor-based immune algorithm in which a multipopulation coevolutionary strategy is introduced for improving the population diversity. In the proposed algorithm, subpopulations evolve independently; thus the unique characteristics of each subpopulation can be effectively maintained, and the diversity of the entire population is effectively increased. Besides, the dynamic information of multiple subpopulations is obtained with the help of the designed cooperation operator which reflects a mutually beneficial relationship among subpopulations. Subpopulations gain the opportunity to exchange information, thereby expanding the search range of the entire population. Subpopulations make use of the reference experience from each other, thereby improving the efficiency of evolutionary search. Compared with several state-of-the-art multiobjective evolutionary algorithms on well-known and frequently used multiobjective and many-objective problems, the proposed algorithm achieves comparable results in terms of convergence, diversity metrics, and running time on most test problems. PMID:24672330
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. PMID:9304668
Zimmerman, K; Levitis, D; Addicott, E; Pringle, A
2016-02-01
We present a novel algorithm for the design of crossing experiments. The algorithm identifies a set of individuals (a 'crossing-set') from a larger pool of potential crossing-sets by maximizing the diversity of traits of interest, for example, maximizing the range of genetic and geographic distances between individuals included in the crossing-set. To calculate diversity, we use the mean nearest neighbor distance of crosses plotted in trait space. We implement our algorithm on a real dataset of Neurospora crassa strains, using the genetic and geographic distances between potential crosses as a two-dimensional trait space. In simulated mating experiments, crossing-sets selected by our algorithm provide better estimates of underlying parameter values than randomly chosen crossing-sets. PMID:26419337
NASA Astrophysics Data System (ADS)
Hashimoto, M.; Nakajima, T.; Morimoto, S.; Takenaka, H.
2014-12-01
We have developed a new satellite remote sensing algorithm to retrieve the aerosol optical characteristics using multi-wavelength and multi-pixel information of satellite imagers (MWP method). In this algorithm, the inversion method is a combination of maximum a posteriori (MAP) method (Rodgers, 2000) and the Phillips-Twomey method (Phillips, 1962; Twomey, 1963) as a smoothing constraint for the state vector. Furthermore, with the progress of computing technique, this method has being combined with the direct radiation transfer calculation numerically solved by each iteration step of the non-linear inverse problem, without using LUT (Look Up Table) with several constraints.Retrieved parameters in our algorithm are aerosol optical properties, such as aerosol optical thickness (AOT) of fine and coarse mode particles, a volume soot fraction in fine mode particles, and ground surface albedo of each observed wavelength. We simultaneously retrieve all the parameters that characterize pixels in each of horizontal sub-domains consisting the target area. Then we successively apply the retrieval method to all the sub-domains in the target area.We conducted numerical tests for the retrieval of aerosol properties and ground surface albedo for GOSAT/CAI imager data to test the algorithm for the land area. The result of the experiment showed that AOTs of fine mode and coarse mode, soot fraction and ground surface albedo are successfully retrieved within expected accuracy. We discuss the accuracy of the algorithm for various land surface types. Then, we applied this algorithm to GOSAT/CAI imager data, and we compared retrieved and surface-observed AOTs at the CAI pixel closest to an AERONET (Aerosol Robotic Network) or SKYNET site in each region. Comparison at several sites in urban area indicated that AOTs retrieved by our method are in agreement with surface-observed AOT within ±0.066.Our future work is to extend the algorithm for analysis of AGEOS-II/GLI and GCOM/C-SGLI data.
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
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. PMID:24815269
Mutual coupling effects and their reduction in wideband direction of arrival estimation
NASA Astrophysics Data System (ADS)
Pasala, K. M.; Friel, E. M.
1994-10-01
The performance of multiple signal classification (MUSIC) algorithm using three different inputs over a wideband of frequencies is considered. These inputs are: (1) ideal voltages; (2) actual voltages which include coupling effects and are obtained with the method of moments; and (3) corrected voltages which are obtained from the actual voltages so that the mutual coupling effects are removed. Linear arrays of dipoles, sleeve dipoles, and spiral antennas are considered over 200 MHz to 400 MHz band.
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.
Automotive radar - investigation of mutual interference mechanisms
NASA Astrophysics Data System (ADS)
Goppelt, M.; Blöcher, H.-L.; Menzel, W.
2010-09-01
In the past mutual interference between automotive radar sensors has not been regarded as a major problem. With an increasing number of such systems, however, this topic is receiving more and more attention. The investigation of mutual interference and countermeasures is therefore one topic of the joint project "Radar on Chip for Cars" (RoCC) funded by the German Federal Ministry of Education and Research (BMBF). RoCC's goal is to pave the way for the development of high-performance, low-cost 79 GHz radar sensors based on Silicon-Germanium (SiGe) Monolithic Microwave Integrated Circuits (MMICs). This paper will present some generic interference scenarios and report on the current status of the analysis of interference mechanisms.
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...
47 CFR 90.165 - Procedures for mutually exclusive applications.
Code of Federal Regulations, 2013 CFR
2013-10-01
... 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...
47 CFR 90.165 - Procedures for mutually exclusive applications.
Code of Federal Regulations, 2012 CFR
2012-10-01
... 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...
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 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...
47 CFR 90.165 - Procedures for mutually exclusive applications.
Code of Federal Regulations, 2014 CFR
2014-10-01
... 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...
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.
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.
Luo, Jiawei; Wu, Juan
2015-01-01
Essential proteins provide valuable information for the development of biology and medical research from the system level. The accuracy of topological centrality only based methods is deeply affected by noise in the network. Therefore, exploring efficient methods for identifying essential proteins would be of great value. Using biological features to identify essential proteins is efficient in reducing the noise in PPI network. In this paper, based on the consideration that essential proteins evolve slowly and play a central role within a network, a new algorithm, named CED, is proposed. CED mainly employs gene expression level, protein complex information and edge clustering coefficient to predict essential proteins. The performance of CED is validated based on the yeast Protein-Protein Interaction (PPI) network obtained from DIP database and BioGRID database. The prediction accuracy of CED outperforms other seven algorithms when applied to the two databases. PMID:26510286
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.
NASA Astrophysics Data System (ADS)
Mafu, Mhlambululi; Dudley, Angela; Goyal, Sandeep; Giovannini, Daniel; McLaren, Melanie; Padgett, Miles J.; Konrad, Thomas; Petruccione, Francesco; Lütkenhaus, Norbert; Forbes, Andrew
2013-09-01
We present an experimental study of higher-dimensional quantum key distribution protocols based on mutually unbiased bases, implemented by means of photons carrying orbital angular momentum. We perform (d+1) mutually unbiased measurements in a classically simulated prepare-and-measure scheme and on a pair of entangled photons for dimensions ranging from d=2 to 5. In our analysis, we pay attention to the detection efficiency and photon pair creation probability. As security measures, we determine from experimental data the average error rate, the mutual information shared between the sender and receiver, and the secret key generation rate per photon. We demonstrate that increasing the dimension leads to an increased information capacity as well as higher key generation rates per photon. However, we find that the benefit of increasing the dimension is limited by practical implementation considerations, which in our case results in deleterious effects observed beyond a dimension of d=4.
78 FR 26424 - Mutual Savings Association Advisory Committee
Federal Register 2010, 2011, 2012, 2013, 2014
2013-05-06
... Office of the Comptroller of the Currency Mutual Savings Association Advisory Committee AGENCY: Office of... Mutual Savings Association Advisory Committee (MSAAC). DATES: A public meeting of the MSAAC will be held... savings associations, and other issues of concern to the existing mutual savings associations. On the...
77 FR 74052 - Mutual Savings Association Advisory Committee Meeting
Federal Register 2010, 2011, 2012, 2013, 2014
2012-12-12
... Office of the Comptroller of the Currency Mutual Savings Association Advisory Committee Meeting AGENCY... Mutual Savings Association Advisory Committee (MSAAC or Committee). DATES: A public meeting of the MSAAC... 8:30 a.m. EST. Agenda items include a discussion of the status of the mutual savings...
26 CFR 1.1502-42 - Mutual savings banks, etc.
Code of Federal Regulations, 2012 CFR
2012-04-01
... 26 Internal Revenue 12 2012-04-01 2012-04-01 false Mutual savings banks, etc. 1.1502-42 Section 1... (CONTINUED) INCOME TAXES (CONTINUED) Special Taxes and Taxpayers § 1.1502-42 Mutual savings banks, etc. (a) In general. This section applies to mutual s avings banks and other institutions described in...
26 CFR 1.1502-42 - Mutual savings banks, etc.
Code of Federal Regulations, 2014 CFR
2014-04-01
... 26 Internal Revenue 12 2014-04-01 2014-04-01 false Mutual savings banks, etc. 1.1502-42 Section 1... (CONTINUED) INCOME TAXES (CONTINUED) Special Taxes and Taxpayers § 1.1502-42 Mutual savings banks, etc. (a) In general. This section applies to mutual s avings banks and other institutions described in...
26 CFR 1.1502-42 - Mutual savings banks, etc.
Code of Federal Regulations, 2013 CFR
2013-04-01
... 26 Internal Revenue 12 2013-04-01 2013-04-01 false Mutual savings banks, etc. 1.1502-42 Section 1... (CONTINUED) INCOME TAXES (CONTINUED) Special Taxes and Taxpayers § 1.1502-42 Mutual savings banks, etc. (a) In general. This section applies to mutual s avings banks and other institutions described in...
26 CFR 1.1502-42 - Mutual savings banks, etc.
Code of Federal Regulations, 2011 CFR
2011-04-01
... 26 Internal Revenue 12 2011-04-01 2011-04-01 false Mutual savings banks, etc. 1.1502-42 Section 1... (CONTINUED) INCOME TAXES (CONTINUED) Special Taxes and Taxpayers § 1.1502-42 Mutual savings banks, etc. (a) In general. This section applies to mutual s avings banks and other institutions described in...
26 CFR 1.1502-42 - Mutual savings banks, etc.
Code of Federal Regulations, 2010 CFR
2010-04-01
... 26 Internal Revenue 12 2010-04-01 2010-04-01 false Mutual savings banks, etc. 1.1502-42 Section 1... (CONTINUED) INCOME TAXES Special Taxes and Taxpayers § 1.1502-42 Mutual savings banks, etc. (a) In general. This section applies to mutual s avings banks and other institutions described in section 593(a)....
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.
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.
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.
Children's Use of Mutual Exclusivity to Learn Labels for Parts of Objects
ERIC Educational Resources Information Center
Hansen, Mikkel B.; Markman, Ellen M.
2009-01-01
When teaching children part terms, adults frequently outline the relevant part rather than simply point. This pragmatic information very likely helps children interpret the label correctly. But the importance of gestures may not negate the need for default lexical biases such as the whole object assumption and mutual exclusivity. On this view,…
Partner selection in the mycorrhizal mutualism.
Werner, Gijsbert D A; Kiers, E Toby
2015-03-01
Partner selection in the mycorrhizal symbiosis is thought to be a key factor stabilising the mutualism. Both plant hosts and mycorrhizal fungi have been shown to preferentially allocate resources to higher quality partners. This can help maintain underground cooperation, although it is likely that different plant species vary in the spatial precision with which they can select partners. Partner selection in the mycorrhizal symbiosis is presumably context-dependent and can be mediated by factors like (relative) resource abundance and resource fluctuations, competition among mycorrhizas, arrival order and cultivation history. Such factors complicate our current understanding of the importance of partner selection and its effectiveness in stimulating mutualistic cooperation. PMID:25421912
Arithmetic, mutually unbiased bases and complementary observables
NASA Astrophysics Data System (ADS)
Sheppeard, M. D.
2010-02-01
Complementary observables in quantum mechanics may be viewed as Frobenius structures in a dagger monoidal category, such as the category of finite dimensional Hilbert spaces over the complex numbers. On the other hand, their properties crucially depend on the discrete Fourier transform and its associated quantum torus, requiring only the finite fields that underlie mutually unbiased bases. In axiomatic topos theory, the complex numbers are difficult to describe and should not be invoked unnecessarily. This paper surveys some fundamentals of quantum arithmetic using finite field complementary observables, with a view considering more general axiom systems.
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.
The architecture of interdependent minds: A Motivation-management theory of mutual responsiveness.
Murray, Sandra L; Holmes, John G
2009-10-01
A model of mutual responsiveness in adult romantic relationships is proposed. Behaving responsively in conflict-of-interest situations requires one partner to resist the temptation to be selfish and the other partner to resist the temptation to protect against exploitation. Managing risk and the attendant temptations of self-interest require the interpersonal mind to function in ways that coordinate trust and commitment across partners. The authors describe a system of procedural or "if... then" rules that foster mutuality in responsiveness by informing and motivating trust and commitment. The authors further argue that tuning rule accessibility and enactment to match the situations encountered in a specific relationship shapes its personality. By imposing a procedural structure on the interdependent mind, the proposed model of mutual responsiveness reframes interdependence theory and generates important research questions for the future. PMID:19839690
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.
There is no generalization of known formulas for mutually unbiased bases
NASA Astrophysics Data System (ADS)
Archer, Claude
2005-02-01
In a quantum system having a finite number N of orthogonal states, two orthonormal bases {ai} and {bj} are called mutually unbiased if all inner products ⟨ai∣bj⟩ have the same modulus 1/√N . This concept appears in several quantum information problems. The number of pairwise mutually unbiased bases is at most N +1 and various constructions of such N +1 bases have been found when N is a power of a prime number. We study families of formulas that generalize these constructions to arbitrary dimensions using finite rings. We then prove that there exists a set of N +1 mutually unbiased bases described by such formulas, if and only if N is a power of a prime number.
Chen, C.T.; Metz, C.E.
1984-01-01
Positron emission tomographic systems capable of time-of-flight measurements open new avenues for image reconstruction. Three algorithms have been proposed previously: the most-likely position method (MLP), the confidence weighting method (CW) and the estimated posterior-density weighting method (EPDW). While MLP suffers from poorer noise properties, both CW and EPDW require substantially more computer processing time. Mathematically, the TOFPET image data at any projection angle represents a 2D image blurred by different TOF and detector spatial resolutions in two perpendicular directions. The integration of TOFPET images over all angles produces a preprocessed 2D image which is the convolution of the true image and a rotationally symmetric point spread function (PSF). Hence the tomographic reconstruction problem for TOFPET can be viewed as nothing more than a 2D image processing task to compensate for a known PSF. A new algorithm based on a generalized iterative deconvolution method and its equivalent filters (''Metz filters'') developed earlier for conventional nuclear medicine image processing is proposed for this purpose. The algorithm can be carried out in a single step by an equivalent filter in the frequency domain; therefore, much of the computation time necessary for CW and EPDW is avoided. Results from computer simulation studies show that this new approach provides excellent resolution enhancement at low frequencies, good noise suppression at high frequencies, a reduction of Gibbs' phenomenon due to sharp filter cutoff, and better quantitative measurements than other methods.
Directions of arrival estimation with planar antenna arrays in the presence of mutual coupling
NASA Astrophysics Data System (ADS)
Akkar, Salem; Harabi, Ferid; Gharsallah, Ali
2013-06-01
Directions of arrival (DoAs) estimation of multiple sources using an antenna array is a challenging topic in wireless communication. The DoAs estimation accuracy depends not only on the selected technique and algorithm, but also on the geometrical configuration of the antenna array used during the estimation. In this article the robustness of common planar antenna arrays against unaccounted mutual coupling is examined and their DoAs estimation capabilities are compared and analysed through computer simulations using the well-known MUltiple SIgnal Classification (MUSIC) algorithm. Our analysis is based on an electromagnetic concept to calculate an approximation of the impedance matrices that define the mutual coupling matrix (MCM). Furthermore, a CRB analysis is presented and used as an asymptotic performance benchmark of the studied antenna arrays. The impact of the studied antenna arrays geometry on the MCM structure is also investigated. Simulation results show that the UCCA has more robustness against unaccounted mutual coupling and performs better results than both UCA and URA geometries. The performed simulations confirm also that, although the UCCA achieves better performance under complicated scenarios, the URA shows better asymptotic (CRB) behaviour which promises more accuracy on DoAs estimation.
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
Galilean satellites - Observations of mutual occultations and eclipses in 1973
NASA Technical Reports Server (NTRS)
Wasserman, L. H.; Elliot, J. L.; Veverka, J.; Liller, W.
1976-01-01
Seven Galilean satellite mutual events, two occultations and two eclipses of Europa and three eclipses of Io, were observed at three wavelengths (0.35, 0.50, 0.91 micrometers) with a time resolution of 0.1 sec. Preliminary model fits to the light curves are presented. Model satellites with different albedo distributions (uniform disk, bright solar caps, bright quadrant) are used in generating model occultation and eclipse curves to demonstrate the sensitivity of observed light curves to the brightness distribution on the surface of the occulted or eclipsed satellite. At the present the observations yield no conclusive information of the limb-darkening of Io. The best data for Europa indicate that the satellite is limb-darkened at both 0.50 and 0.91 micrometers.
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. PMID:23661158
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.
Nutrient loading alters the performance of key nutrient exchange mutualisms.
Shantz, Andrew A; Lemoine, Nathan P; Burkepile, Deron E
2016-01-01
Nutrient exchange mutualisms between phototrophs and heterotrophs, such as plants and mycorrhizal fungi or symbiotic algae and corals, underpin the functioning of many ecosystems. These relationships structure communities, promote biodiversity and help maintain food security. Nutrient loading may destabilise these mutualisms by altering the costs and benefits each partner incurs from interacting. Using meta-analyses, we show a near ubiquitous decoupling in mutualism performance across terrestrial and marine environments in which phototrophs benefit from enrichment at the expense of their heterotrophic partners. Importantly, heterotroph identity, their dependence on phototroph-derived C and the type of nutrient enrichment (e.g. nitrogen vs. phosphorus) mediated the responses of different mutualisms to enrichment. Nutrient-driven changes in mutualism performance may alter community organisation and ecosystem processes and increase costs of food production. Consequently, the decoupling of nutrient exchange mutualisms via alterations of the world's nitrogen and phosphorus cycles may represent an emerging threat of global change. PMID:26549314
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…
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.
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
Mutually unbiased bases and bound entanglement
NASA Astrophysics Data System (ADS)
Hiesmayr, Beatrix C.; Löffler, Wolfgang
2014-04-01
In this contribution we relate two different key concepts: mutually unbiased bases (MUBs) and entanglement. We provide a general toolbox for analyzing and comparing entanglement of quantum states for different dimensions and numbers of particles. In particular we focus on bound entanglement, i.e. highly mixed states which cannot be distilled by local operations and classical communications. For a certain class of states—for which the state-space forms a ‘magic’ simplex—we analyze the set of bound entangled states detected by the MUB criterion for different dimensions d and number of particles n. We find that the geometry is similar for different d and n, consequently the MUB criterion opens possibilities to investigate the typicality of positivity under partial transposition (PPT)-bound and multipartite bound entanglement more deeply and provides a simple experimentally feasible tool to detect bound entanglement.
Detecting Generalized Synchrony Through Mutual Prediction
NASA Astrophysics Data System (ADS)
Schiff, Steven J.; So, Paul
1996-03-01
Detection of synchrony in the nervous system has traditionally relied on linear methods such as cross correlation and coherence. Neurons are floridly nonlinear, however, and neuronal interactions may be inadequately described if it is assumed that ensemble behavior is a linear combination of neuronal activities. We develop an approach to detecting generalized synchrony using mutual nonlinear prediction. Multivariate surrogate data will be employed to establish statistical confidence that synchrony is nonlinear. These results will be applied to an experimental preparation - the motoneuron pool from the spinal cord stretch reflex. The interrelationships between individual neurons, between single neurons and the population of neurons, and between intracellular synaptic currents and single neurons will be examined, and the case for the existence of generalized synchrony made.
Evaluation of mathematical algorithms for automatic patient alignment in radiosurgery.
Williams, Kenneth M; Schulte, Reinhard W; Schubert, Keith E; Wroe, Andrew J
2015-06-01
Image registration techniques based on anatomical features can serve to automate patient alignment for intracranial radiosurgery procedures in an effort to improve the accuracy and efficiency of the alignment process as well as potentially eliminate the need for implanted fiducial markers. To explore this option, four two-dimensional (2D) image registration algorithms were analyzed: the phase correlation technique, mutual information (MI) maximization, enhanced correlation coefficient (ECC) maximization, and the iterative closest point (ICP) algorithm. Digitally reconstructed radiographs from the treatment planning computed tomography scan of a human skull were used as the reference images, while orthogonal digital x-ray images taken in the treatment room were used as the captured images to be aligned. The accuracy of aligning the skull with each algorithm was compared to the alignment of the currently practiced procedure, which is based on a manual process of selecting common landmarks, including implanted fiducials and anatomical skull features. Of the four algorithms, three (phase correlation, MI maximization, and ECC maximization) demonstrated clinically adequate (ie, comparable to the standard alignment technique) translational accuracy and improvements in speed compared to the interactive, user-guided technique; however, the ICP algorithm failed to give clinically acceptable results. The results of this work suggest that a combination of different algorithms may provide the best registration results. This research serves as the initial groundwork for the translation of automated, anatomy-based 2D algorithms into a real-world system for 2D-to-2D image registration and alignment for intracranial radiosurgery. This may obviate the need for invasive implantation of fiducial markers into the skull and may improve treatment room efficiency and accuracy. PMID:25782189
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
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.
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.
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. PMID:25817713
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
Information theoretic approach for accounting classification
NASA Astrophysics Data System (ADS)
Ribeiro, E. M. S.; Prataviera, G. A.
2014-12-01
In this paper we consider an information theoretic approach for the accounting classification process. We propose a matrix formalism and an algorithm for calculations of information theoretic measures associated to accounting classification. The formalism may be useful for further generalizations and computer-based implementation. Information theoretic measures, mutual information and symmetric uncertainty, were evaluated for daily transactions recorded in the chart of accounts of a small company during two years. Variation in the information measures due the aggregation of data in the process of accounting classification is observed. In particular, the symmetric uncertainty seems to be a useful parameter for comparing companies over time or in different sectors or different accounting choices and standards.
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…
77 FR 73115 - Mutual Savings Association Advisory Committee
Federal Register 2010, 2011, 2012, 2013, 2014
2012-12-07
... Office of the Comptroller of the Currency Mutual Savings Association Advisory Committee AGENCY: Office of... has determined that the renewal of the charter of the OCC Mutual Savings Association Advisory... savings associations, the regulatory changes or other steps the OCC may be able to take to ensure...
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...
FAST TRACK COMMUNICATION: Affine constellations without mutually unbiased counterparts
NASA Astrophysics Data System (ADS)
Weigert, Stefan; Durt, Thomas
2010-10-01
It has been conjectured that a complete set of mutually unbiased bases in a space of dimension d exists if and only if there is an affine plane of order d. We introduce affine constellations and compare their existence properties with those of mutually unbiased constellations. The observed discrepancies make a deeper relation between the two existence problems unlikely.
Social Climate Comparison of Mutual Help and Psychotherapy Groups.
ERIC Educational Resources Information Center
Toro, Paul A.; Rappaport, Julian
In recent years, mutual help groups have been formed to address problems in substance abuse, chronic physical illness, mental illness, marital disruption, and child abuse. Despite the proliferation of these groups, little research has been conducted to assess their efficacy or what happens in them. The nature of mutual help groups (N=32) was…
Use of the Mutual Exclusivity Assumption by Young Word Learners
ERIC Educational Resources Information Center
Markman, Ellen M.; Wasow, Judith L.; Hansen, Mikkel B.
2003-01-01
A critical question about early word learning is whether word learning constraints such as mutual exclusivity exist and foster early language acquisition. It is well established that children will map a novel label to a novel rather than a familiar object. Evidence for the role of mutual exclusivity in such indirect word learning has been…
12 CFR 563.74 - Mutual capital certificates.
Code of Federal Regulations, 2010 CFR
2010-01-01
... 12 Banks and Banking 5 2010-01-01 2010-01-01 false Mutual capital certificates. 563.74 Section 563.74 Banks and Banking OFFICE OF THRIFT SUPERVISION, DEPARTMENT OF THE TREASURY SAVINGS ASSOCIATIONS... having a preference or priority over an outstanding class or classes of mutual capital certificates;...
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…
NASA Astrophysics Data System (ADS)
Wang, Chenxi; Platnick, Steven; Zhang, Zhibo; Meyer, Kerry; Yang, Ping
2016-05-01
An optimal estimation (OE) retrieval method is developed to infer three ice cloud properties simultaneously: optical thickness (τ), effective radius (reff), and cloud top height (h). This method is based on a fast radiative transfer (RT) model and infrared (IR) observations from the MODerate resolution Imaging Spectroradiometer (MODIS). This study conducts thorough error and information content analyses to understand the error propagation and performance of retrievals from various MODIS band combinations under different cloud/atmosphere states. Specifically, the algorithm takes into account four error sources: measurement uncertainty, fast RT model uncertainty, uncertainties in ancillary data sets (e.g., atmospheric state), and assumed ice crystal habit uncertainties. It is found that the ancillary and ice crystal habit error sources dominate the MODIS IR retrieval uncertainty and cannot be ignored. The information content analysis shows that for a given ice cloud, the use of four MODIS IR observations is sufficient to retrieve the three cloud properties. However, the selection of MODIS IR bands that provide the most information and their order of importance varies with both the ice cloud properties and the ambient atmospheric and the surface states. As a result, this study suggests the inclusion of all MODIS IR bands in practice since little a priori information is available.
Calcium and ROS: A mutual interplay
Görlach, Agnes; Bertram, Katharina; Hudecova, Sona; Krizanova, Olga
2015-01-01
Calcium is an important second messenger involved in intra- and extracellular signaling cascades and plays an essential role in cell life and death decisions. The Ca2+ signaling network works in many different ways to regulate cellular processes that function over a wide dynamic range due to the action of buffers, pumps and exchangers on the plasma membrane as well as in internal stores. Calcium signaling pathways interact with other cellular signaling systems such as reactive oxygen species (ROS). Although initially considered to be potentially detrimental byproducts of aerobic metabolism, it is now clear that ROS generated in sub-toxic levels by different intracellular systems act as signaling molecules involved in various cellular processes including growth and cell death. Increasing evidence suggests a mutual interplay between calcium and ROS signaling systems which seems to have important implications for fine tuning cellular signaling networks. However, dysfunction in either of the systems might affect the other system thus potentiating harmful effects which might contribute to the pathogenesis of various disorders. PMID:26296072
[Mutual inhibition between positive and negative emotions].
Shimokawa, A
1994-02-01
The purpose of this study is to examine the relationship between positive and negative emotions. In study 1, 62 emotional items were selected in order to measure subjective emotional experiences. In study 2, comics, photos and poems were randomly presented to 1,220 college students to induce emotion. Subjects were asked to rate their momentary emotional intensity on two set of 5-point scales (general emotional intensity scale and 62 specific emotional intensity scale). In analysis 1, positive correlations were suggested between general emotional intensity scale and some of the specific emotional intensity scales which were activated by stimuli. In analysis 2, 10 positive and 10 negative emotional items were extracted from 62 items by factor analysis. In analysis 3, 4 and 5, it became clear that the distribution of frequency of correlations of 10 positive x 10 negative items changed according to the general emotional intensity scale. That is, from low to moderate levels of GEIS, the two kinds of emotion had no or slightly positive correlation, but at high level they became to be negatively correlated. From the facts described above, it is concluded that positive and negative emotions is not always independent, but show mutual inhibition in case of high intensity level of one of each emotions. PMID:8201808
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
Kim, Wangdo; Espanha, Margarida M.; Veloso, António P.; Araújo, Duarte; João, Filipa; Carrão, Luis; Kohles, Sean S.
2013-01-01
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. PMID:24932433
Evaluation of GMI and PMI diffeomorphic-based demons algorithms for aligning PET and CT Images.
Yang, Juan; Wang, Hongjun; Zhang, You; Yin, Yong
2015-01-01
Fusion of anatomic information in computed tomography (CT) and functional information in 18F-FDG positron emission tomography (PET) is crucial for accurate differentiation of tumor from benign masses, designing radiotherapy treatment plan and staging of cancer. Although current PET and CT images can be acquired from combined 18F-FDG PET/CT scanner, the two acquisitions are scanned separately and take a long time, which may induce potential positional errors in global and local caused by respiratory motion or organ peristalsis. So registration (alignment) of whole-body PET and CT images is a prerequisite for their meaningful fusion. The purpose of this study was to assess the performance of two multimodal registration algorithms for aligning PET and CT images. The proposed gradient of mutual information (GMI)-based demons algorithm, which incorporated the GMI between two images as an external force to facilitate the alignment, was compared with the point-wise mutual information (PMI) diffeomorphic-based demons algorithm whose external force was modified by replacing the image intensity difference in diffeomorphic demons algorithm with the PMI to make it appropriate for multimodal image registration. Eight patients with esophageal cancer(s) were enrolled in this IRB-approved study. Whole-body PET and CT images were acquired from a combined 18F-FDG PET/CT scanner for each patient. The modified Hausdorff distance (d(MH)) was used to evaluate the registration accuracy of the two algorithms. Of all patients, the mean values and standard deviations (SDs) of d(MH) were 6.65 (± 1.90) voxels and 6.01 (± 1.90) after the GMI-based demons and the PMI diffeomorphic-based demons registration algorithms respectively. Preliminary results on oncological patients showed that the respiratory motion and organ peristalsis in PET/CT esophageal images could not be neglected, although a combined 18F-FDG PET/CT scanner was used for image acquisition. The PMI diffeomorphic-based demons
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.
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
2014-01-01
Background Alternative splicing is an important process in higher eukaryotes that allows obtaining several transcripts from one gene. A specific case of alternative splicing is mutually exclusive splicing, in which exactly one exon out of a cluster of neighbouring exons is spliced into the mature transcript. Recently, a new algorithm for the prediction of these exons has been developed based on the preconditions that the exons of the cluster have similar lengths, sequence homology, and conserved splice sites, and that they are translated in the same reading frame. Description In this contribution we introduce Kassiopeia, a database and web application for the generation, storage, and presentation of genome-wide analyses of mutually exclusive exomes. Currently, Kassiopeia provides access to the mutually exclusive exomes of twelve Drosophila species, the thale cress Arabidopsis thaliana, the flatworm Caenorhabditis elegans, and human. Mutually exclusive spliced exons (MXEs) were predicted based on gene reconstructions from Scipio. Based on the standard prediction values, with which 83.5% of the annotated MXEs of Drosophila melanogaster were reconstructed, the exomes contain surprisingly more MXEs than previously supposed and identified. The user can search Kassiopeia using BLAST or browse the genes of each species optionally adjusting the parameters used for the prediction to reveal more divergent or only very similar exon candidates. Conclusions We developed a pipeline to predict MXEs in the genomes of several model organisms and a web interface, Kassiopeia, for their visualization. For each gene Kassiopeia provides a comprehensive gene structure scheme, the sequences and predicted secondary structures of the MXEs, and, if available, further evidence for MXE candidates from cDNA/EST data, predictions of MXEs in homologous genes of closely related species, and RNA secondary structure predictions. Kassiopeia can be accessed at http
The origin of the attine ant-fungus mutualism.
Mueller, U G; Schultz, T R; Currie, C R; Adams, R M; Malloch, D
2001-06-01
Cultivation of fungus for food originated about 45-65 million years ago in the ancestor of fungus-growing ants (Formicidae, tribe Attini), representing an evolutionary transition from the life of a hunter-gatherer of arthropod prey, nectar, and other plant juices, to the life of a farmer subsisting on cultivated fungi. Seven hypotheses have been suggested for the origin of attine fungiculture, each differing with respect to the substrate used by the ancestral attine ants for fungal cultivation. Phylogenetic information on the cultivated fungi, in conjunction with information on the nesting biology of extant attine ants and their presumed closest relatives, reveal that the attine ancestors probably did not encounter their cultivars-to-be in seed stores (von Ihering 1894), in rotting wood (Forel 1902), as mycorrhizae (Garling 1979), on arthropod corpses (von Ihering 1894) or ant faeces in nest middens (Wheeler 1907). Rather, the attine ant-fungus mutualism probably arose from adventitious interactions with fungi that grew on walls of nests built in leaf litter (Emery 1899), or from a system of fungal myrmecochory in which specialized fungi relied on ants for dispersal (Bailey 1920) and in which the ants fortuitously vectored these fungi from parent to offspring nests prior to a true fungicultural stage. Reliance on fungi as a dominant food source has evolved only twice in ants: first in the attine ants, and second in some ant species in the solenopsidine genus Megalomyrmex that either coexist as trophic parasites in gardens of attine hosts or aggressively usurp gardens from them. All other known ant-fungus associations are either adventitious or have nonnutritional functions (e.g., strengthening of carton-walls in ant nests). There exist no unambiguous reports of facultative mycophagy in ants, but such trophic ant-fungus interactions would most likely occur underground or in leaf litter and thus escape easy observation. Indirect evidence of fungivory can be deduced
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. PMID:26886201
Controlled mutual quantum entity authentication using entanglement swapping
NASA Astrophysics Data System (ADS)
Min-Sung, Kang; Chang-Ho, Hong; Jino, Heo; Jong-In, Lim; Hyung-Jin, Yang
2015-09-01
In this paper, we suggest a controlled mutual quantum entity authentication protocol by which two users mutually certify each other on a quantum network using a sequence of Greenberger-Horne-Zeilinger (GHZ)-like states. Unlike existing unidirectional quantum entity authentication, our protocol enables mutual quantum entity authentication utilizing entanglement swapping; moreover, it allows the managing trusted center (TC) or trusted third party (TTP) to effectively control the certification of two users using the nature of the GHZ-like state. We will also analyze the security of the protocol and quantum channel. Project supported by the Research Foundation of Korea University.
Mutually connected component of networks of networks with replica nodes
NASA Astrophysics Data System (ADS)
Bianconi, Ginestra; Dorogovtsev, Sergey N.; Mendes, José F. F.
2015-01-01
We describe the emergence of the giant mutually connected component in networks of networks in which each node has a single replica node in any layer and can be interdependent only on its replica nodes in the interdependent layers. We prove that if, in these networks, all the nodes of one network (layer) are interdependent on the nodes of the same other interconnected layer, then, remarkably, the mutually connected component does not depend on the topology of the network of networks. This component coincides with the mutual component of the fully connected network of networks constructed from the same set of layers, i.e., a multiplex network.
NASA Astrophysics Data System (ADS)
Nichols, Jonathan M.; Trickey, Stephen T.; Seaver, Mark
2005-05-01
An information-theoretic approach is described for detecting damage-induced nonlinearities in structures. Both the time-delayed mutual information and time-delayed transfer entropy are presented as methods for computing the amount of information transported between points on a structure. By comparing these measures to "linearized" surrogate data sets, the presence and degree of nonlinearity in a system may be deduced. For a linear, five-degree-of-freedom system both mutual information and transfer entropy are derived. An algorithm is then described for computing both quantities from time-series data and is shown to be in agreement with theory. The approach successfully deduces the amount of damage to the structure even in the presence of simulated temperature fluctuations. We then demonstrate the approach to be effective in detecting varying levels of impact damage in a thick composite plate structure.
Monte Carlo algorithm for least dependent non-negative mixture decomposition.
Astakhov, Sergey A; Stögbauer, Harald; Kraskov, Alexander; Grassberger, Peter
2006-03-01
We propose a simulated annealing algorithm (stochastic non-negative independent component analysis, SNICA) for blind decomposition of linear mixtures of non-negative sources with non-negative coefficients. The demixing is based on a Metropolis-type Monte Carlo search for least dependent components, with the mutual information between recovered components as a cost function and their non-negativity as a hard constraint. Elementary moves are shears in two-dimensional subspaces and rotations in three-dimensional subspaces. The algorithm is geared at decomposing signals whose probability densities peak at zero, the case typical in analytical spectroscopy and multivariate curve resolution. The decomposition performance on large samples of synthetic mixtures and experimental data is much better than that of traditional blind source separation methods based on principal component analysis (MILCA, FastICA, RADICAL) and chemometrics techniques (SIMPLISMA, ALS, BTEM). PMID:16503615
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.
Image scoring and cooperation in a cleaner fish mutualism.
Bshary, Redouan; Grutter, Alexandra S
2006-06-22
Humans are highly social animals and often help unrelated individuals that may never reciprocate the altruist's favour. This apparent evolutionary puzzle may be explained by the altruist's gain in social image: image-scoring bystanders, also known as eavesdroppers, notice the altruistic act and therefore are more likely to help the altruist in the future. Such complex indirect reciprocity based on altruistic acts may evolve only after simple indirect reciprocity has been established, which requires two steps. First, image scoring evolves when bystanders gain personal benefits from information gathered, for example, by finding cooperative partners. Second, altruistic behaviour in the presence of such bystanders may evolve if altruists benefit from access to the bystanders. Here, we provide experimental evidence for both of the requirements in a cleaning mutualism involving the cleaner fish Labroides dimidiatus. These cleaners may cooperate and remove ectoparasites from clients or they may cheat by feeding on client mucus. As mucus may be preferred over typical client ectoparasites, clients must make cleaners feed against their preference to obtain a cooperative service. We found that eavesdropping clients spent more time next to 'cooperative' than 'unknown cooperative level' cleaners, which shows that clients engage in image-scoring behaviour. Furthermore, trained cleaners learned to feed more cooperatively when in an 'image-scoring' than in a 'non-image-scoring' situation. PMID:16791194
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.
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.
29 CFR 553.105 - Mutual aid agreements.
Code of Federal Regulations, 2011 CFR
2011-07-01
... into a mutual aid agreement related to fire protection, a firefighter employed by Town A who also is a volunteer firefighter for Town B will not have his or her hours of volunteer service for Town B counted...
29 CFR 553.105 - Mutual aid agreements.
Code of Federal Regulations, 2010 CFR
2010-07-01
... into a mutual aid agreement related to fire protection, a firefighter employed by Town A who also is a volunteer firefighter for Town B will not have his or her hours of volunteer service for Town B counted...
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...