Sequence comparisons via algorithmic mutual information.
Milosavljević, A
1994-01-01
One of the main problems in DNA and protein sequence comparisons is to decide whether observed similarity of two sequences should be explained by their relatedness or by mere presence of some shared internal structure, e.g., shared internal tandem repeats. The standard methods that are based on statistics or classical information theory can be used to discover either internal structure or mutual sequence similarity, but cannot take into account both. Consequently, currently used methods for sequence comparison employ "masking" techniques that simply eliminate sequences that exhibit internal repetitive structure prior to sequence comparisons. The "masking" approach precludes discovery of homologous sequences of moderate or low complexity, which abound at both DNA and protein levels. As a solution to this problem, we propose a general method that is based on algorithmic information theory and minimal length encoding. We show that algorithmic mutual information factors out the sequence similarity that is due to shared internal structure and thus enables discovery of truly related sequences. We extend that recently developed algorithmic significance method (Milosavljević & Jurka 1993) to show that significance depends exponentially on algorithmic mutual information.
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.
Mutual Information, Fisher Information, and Efficient Coding.
Wei, Xue-Xin; Stocker, Alan A
2016-02-01
Fisher information is generally believed to represent a lower bound on mutual information (Brunel & Nadal, 1998), a result that is frequently used in the assessment of neural coding efficiency. However, we demonstrate that the relation between these two quantities is more nuanced than previously thought. For example, we find that in the small noise regime, Fisher information actually provides an upper bound on mutual information. Generally our results show that it is more appropriate to consider Fisher information as an approximation rather than a bound on mutual information. We analytically derive the correspondence between the two quantities and the conditions under which the approximation is good. Our results have implications for neural coding theories and the link between neural population coding and psychophysically measurable behavior. Specifically, they allow us to formulate the efficient coding problem of maximizing mutual information between a stimulus variable and the response of a neural population in terms of Fisher information. We derive a signature of efficient coding expressed as the correspondence between the population Fisher information and the distribution of the stimulus variable. The signature is more general than previously proposed solutions that rely on specific assumptions about the neural tuning characteristics. We demonstrate that it can explain measured tuning characteristics of cortical neural populations that do not agree with previous models of efficient coding.
Minimax mutual information approach for independent component analysis.
Erdogmus, Deniz; Hild, Kenneth E; Rao, Yadunandana N; Príncipe, Joséc C
2004-06-01
Minimum output mutual information is regarded as a natural criterion for independent component analysis (ICA) and is used as the performance measure in many ICA algorithms. Two common approaches in information-theoretic ICA algorithms are minimum mutual information and maximum output entropy approaches. In the former approach, we substitute some form of probability density function (pdf) estimate into the mutual information expression, and in the latter we incorporate the source pdf assumption in the algorithm through the use of nonlinearities matched to the corresponding cumulative density functions (cdf). Alternative solutions to ICA use higher-order cumulant-based optimization criteria, which are related to either one of these approaches through truncated series approximations for densities. In this article, we propose a new ICA algorithm motivated by the maximum entropy principle (for estimating signal distributions). The optimality criterion is the minimum output mutual information, where the estimated pdfs are from the exponential family and are approximate solutions to a constrained entropy maximization problem. This approach yields an upper bound for the actual mutual information of the output signals - hence, the name minimax mutual information ICA algorithm. In addition, we demonstrate that for a specific selection of the constraint functions in the maximum entropy density estimation procedure, the algorithm relates strongly to ICA methods using higher-order cumulants. PMID:15130248
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.
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.
Last-passage Monte Carlo algorithm for mutual capacitance.
Hwang, Chi-Ok; Given, James A
2006-08-01
We develop and test the last-passage diffusion algorithm, a charge-based Monte Carlo algorithm, for the mutual capacitance of a system of conductors. The first-passage algorithm is highly efficient because it is charge based and incorporates importance sampling; it averages over the properties of Brownian paths that initiate outside the conductor and terminate on its surface. However, this algorithm does not seem to generalize to mutual capacitance problems. The last-passage algorithm, in a sense, is the time reversal of the first-passage algorithm; it involves averages over particles that initiate on an absorbing surface, leave that surface, and diffuse away to infinity. To validate this algorithm, we calculate the mutual capacitance matrix of the circular-disk parallel-plate capacitor and compare with the known numerical results. Good agreement is obtained.
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
Brain activity: connectivity, sparsity, and mutual information.
Cassidy, Ben; Rae, Caroline; Solo, Victor
2015-04-01
We develop a new approach to functional brain connectivity analysis, which deals with four fundamental aspects of connectivity not previously jointly treated. These are: temporal correlation, spurious spatial correlation, sparsity, and network construction using trajectory (as opposed to marginal) Mutual Information. We call the new method Sparse Conditional Trajectory Mutual Information (SCoTMI). We demonstrate SCoTMI on simulated and real fMRI data, showing that SCoTMI gives more accurate and more repeatable detection of network links than competing network estimation methods.
MISTIC: Mutual information server to infer coevolution.
Simonetti, Franco L; Teppa, Elin; Chernomoretz, Ariel; Nielsen, Morten; Marino Buslje, Cristina
2013-07-01
MISTIC (mutual information server to infer coevolution) is a web server for graphical representation of the information contained within a MSA (multiple sequence alignment) and a complete analysis tool for Mutual Information networks in protein families. The server outputs a graphical visualization of several information-related quantities using a circos representation. This provides an integrated view of the MSA in terms of (i) the mutual information (MI) between residue pairs, (ii) sequence conservation and (iii) the residue cumulative and proximity MI scores. Further, an interactive interface to explore and characterize the MI network is provided. Several tools are offered for selecting subsets of nodes from the network for visualization. Node coloring can be set to match different attributes, such as conservation, cumulative MI, proximity MI and secondary structure. Finally, a zip file containing all results can be downloaded. The server is available at http://mistic.leloir.org.ar. In summary, MISTIC allows for a comprehensive, compact, visually rich view of the information contained within an MSA in a manner unique to any other publicly available web server. In particular, the use of circos representation of MI networks and the visualization of the cumulative MI and proximity MI concepts is novel.
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.
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
Equitability, mutual information, and the maximal information coefficient
Kinney, Justin B.; Atwal, Gurinder S.
2014-01-01
How should one quantify the strength of association between two random variables without bias for relationships of a specific form? Despite its conceptual simplicity, this notion of statistical “equitability” has yet to receive a definitive mathematical formalization. Here we argue that equitability is properly formalized by a self-consistency condition closely related to Data Processing Inequality. Mutual information, a fundamental quantity in information theory, is shown to satisfy this equitability criterion. These findings are at odds with the recent work of Reshef et al. [Reshef DN, et al. (2011) Science 334(6062):1518–1524], which proposed an alternative definition of equitability and introduced a new statistic, the “maximal information coefficient” (MIC), said to satisfy equitability in contradistinction to mutual information. These conclusions, however, were supported only with limited simulation evidence, not with mathematical arguments. Upon revisiting these claims, we prove that the mathematical definition of equitability proposed by Reshef et al. cannot be satisfied by any (nontrivial) dependence measure. We also identify artifacts in the reported simulation evidence. When these artifacts are removed, estimates of mutual information are found to be more equitable than estimates of MIC. Mutual information is also observed to have consistently higher statistical power than MIC. We conclude that estimating mutual information provides a natural (and often practical) way to equitably quantify statistical associations in large datasets. PMID:24550517
Equitability, mutual information, and the maximal information coefficient.
Kinney, Justin B; Atwal, Gurinder S
2014-03-01
How should one quantify the strength of association between two random variables without bias for relationships of a specific form? Despite its conceptual simplicity, this notion of statistical "equitability" has yet to receive a definitive mathematical formalization. Here we argue that equitability is properly formalized by a self-consistency condition closely related to Data Processing Inequality. Mutual information, a fundamental quantity in information theory, is shown to satisfy this equitability criterion. These findings are at odds with the recent work of Reshef et al. [Reshef DN, et al. (2011) Science 334(6062):1518-1524], which proposed an alternative definition of equitability and introduced a new statistic, the "maximal information coefficient" (MIC), said to satisfy equitability in contradistinction to mutual information. These conclusions, however, were supported only with limited simulation evidence, not with mathematical arguments. Upon revisiting these claims, we prove that the mathematical definition of equitability proposed by Reshef et al. cannot be satisfied by any (nontrivial) dependence measure. We also identify artifacts in the reported simulation evidence. When these artifacts are removed, estimates of mutual information are found to be more equitable than estimates of MIC. Mutual information is also observed to have consistently higher statistical power than MIC. We conclude that estimating mutual information provides a natural (and often practical) way to equitably quantify statistical associations in large datasets.
Equitability, mutual information, and the maximal information coefficient.
Kinney, Justin B; Atwal, Gurinder S
2014-03-01
How should one quantify the strength of association between two random variables without bias for relationships of a specific form? Despite its conceptual simplicity, this notion of statistical "equitability" has yet to receive a definitive mathematical formalization. Here we argue that equitability is properly formalized by a self-consistency condition closely related to Data Processing Inequality. Mutual information, a fundamental quantity in information theory, is shown to satisfy this equitability criterion. These findings are at odds with the recent work of Reshef et al. [Reshef DN, et al. (2011) Science 334(6062):1518-1524], which proposed an alternative definition of equitability and introduced a new statistic, the "maximal information coefficient" (MIC), said to satisfy equitability in contradistinction to mutual information. These conclusions, however, were supported only with limited simulation evidence, not with mathematical arguments. Upon revisiting these claims, we prove that the mathematical definition of equitability proposed by Reshef et al. cannot be satisfied by any (nontrivial) dependence measure. We also identify artifacts in the reported simulation evidence. When these artifacts are removed, estimates of mutual information are found to be more equitable than estimates of MIC. Mutual information is also observed to have consistently higher statistical power than MIC. We conclude that estimating mutual information provides a natural (and often practical) way to equitably quantify statistical associations in large datasets. PMID:24550517
Multimodal Data Fusion Based on Mutual Information.
Bramon, Roger; Boada, Imma; Bardera, Anton; Rodríguez, Joaquim; Feixas, Miquel; Puig, Josep; Sbert, Mateu
2012-09-01
Multimodal visualization aims at fusing different data sets so that the resulting combination provides more information and understanding to the user. To achieve this aim, we propose a new information-theoretic approach that automatically selects the most informative voxels from two volume data sets. Our fusion criteria are based on the information channel created between the two input data sets that permit us to quantify the information associated with each intensity value. This specific information is obtained from three different ways of decomposing the mutual information of the channel. In addition, an assessment criterion based on the information content of the fused data set can be used to analyze and modify the initial selection of the voxels by weighting the contribution of each data set to the final result. The proposed approach has been integrated in a general framework that allows for the exploration of volumetric data models and the interactive change of some parameters of the fused data set. The proposed approach has been evaluated on different medical data sets with very promising results.
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
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
Mutual information-based facial expression recognition
NASA Astrophysics Data System (ADS)
Hazar, Mliki; Hammami, Mohamed; Hanêne, Ben-Abdallah
2013-12-01
This paper introduces a novel low-computation discriminative regions representation for expression analysis task. The proposed approach relies on interesting studies in psychology which show that most of the descriptive and responsible regions for facial expression are located around some face parts. The contributions of this work lie in the proposition of new approach which supports automatic facial expression recognition based on automatic regions selection. The regions selection step aims to select the descriptive regions responsible or facial expression and was performed using Mutual Information (MI) technique. For facial feature extraction, we have applied Local Binary Patterns Pattern (LBP) on Gradient image to encode salient micro-patterns of facial expressions. Experimental studies have shown that using discriminative regions provide better results than using the whole face regions whilst reducing features vector dimension.
Quantum corrections to holographic mutual information
NASA Astrophysics Data System (ADS)
Agón, Cesar A.; Faulkner, Thomas
2016-08-01
We compute the leading contribution to the mutual information (MI) of two disjoint spheres in the large distance regime for arbitrary conformal field theories (CFT) in any dimension. This is achieved by refining the operator product expansion method introduced by Cardy [1]. For CFTs with holographic duals the leading contribution to the MI at long distances comes from bulk quantum corrections to the Ryu-Takayanagi area formula. According to the FLM proposal [2] this equals the bulk MI between the two disjoint regions spanned by the boundary spheres and their corresponding minimal area surfaces. We compute this quantum correction and provide in this way a non-trivial check of the FLM proposal.
GENERAL: Mutual Information and Relative Entropy of Sequential Effect Algebras
NASA Astrophysics Data System (ADS)
Wang, Jia-Mei; Wu, Jun-De; Cho, Minhyung
2010-08-01
In this paper, we introduce and investigate the mutual information and relative entropy on the sequential effect algebra, we also give a comparison of these mutual information and relative entropy with the classical ones by the venn diagrams. Finally, a nice example shows that the entropies of sequential effect algebra depend extremely on the order of its sequential product.
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
Information-disturbance theorem for mutually unbiased observables
Miyadera, Takayuki; Imai, Hideki
2006-04-15
We derive a version of information-disturbance theorems for mutually unbiased observables. We show that the information gain by Eve inevitably makes the outcomes by Bob in the conjugate basis not only erroneous but random.
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
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.
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.
Learning biological network using mutual information and conditional independence
2010-01-01
Background Biological networks offer us a new way to investigate the interactions among different components and address the biological system as a whole. In this paper, a reverse-phase protein microarray (RPPM) is used for the quantitative measurement of proteomic responses. Results To discover the signaling pathway responsive to RPPM, a new structure learning algorithm of Bayesian networks is developed based on mutual Information, conditional independence, and graph immorality. Trusted biology networks are thus predicted by the new approach. As an application example, we investigate signaling networks of ataxia telangiectasis mutation (ATM). The study was carried out at different time points under different dosages for cell lines with and without gene transfection. To validate the performance ofthe proposed algorithm, comparison experiments were also implemented using three well-known networks. From the experiment results, our approach produces more reliable networks with a relatively small number of wrong connection especially in mid-size networks. By using the proposed method, we predicted different networks for ATM under different doses of radiation treatment, and those networks were compared with results from eight different protein protein interaction (PPI) databases. Conclusions By using a new protein microarray technology in combination with a new computational framework, we demonstrate an application of the methodology to the study of biological networks of ATM cell lines under low dose ionization radiation. PMID:20438656
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.
Quantum mutual information and the one-time pad
Schumacher, Benjamin; Westmoreland, Michael D.
2006-10-15
Alice and Bob share a correlated composite quantum system AB. If AB is used as the key for a one-time pad cryptographic system, we show that the maximum amount of information that Alice can send securely to Bob is the quantum mutual information of AB.
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-based correlation analysis of herbs against insomnia].
Tian, Jin; Liu, Ren-quan
2015-10-01
This paper aims to analyze Professor Guo Rongjuan's medication experience on insomnia therapy based on the Traditional Chinese Medicine (TCM) Inheritance Support Plat. First, TCM formulae prescribed by Professor Guo for insomnia therapy were collected from the TCM Inheritance Support Plat. Next, unsupervised data mining algorithms, including apriori, modified mutual-information, and entropy clustering of complex system were applied to obtain the frequencies for different herbs and identify the association rules among the herbs. Accordingly, we can gain new insights into Professor Guo's medication experience on insomnia therapy. Based on analysis of 3 084 formulae, we determined the frequencies for herbs in the formulae and identified the association rules among these herbs. At last, 41 core combinations and 7 new formulae were obtained. The identified medication experience conform with Professor Guo's views on the etiology and pathogenesis of insomnia: "pathogenic fire derived from stagnation of liver-QI (Gan Yu Hua Huo)" is the core pathogenesis of insomnia; "liver stagnation and spleen deficiency" and "chronic illness transferred to kidney" are the main features for insomnia. The TCM Inheritance Support Plat is of great practical value for mining clinical experience of famous TCM doctors.
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.
Cross Correlation versus Normalized Mutual Information on Image Registration
NASA Technical Reports Server (NTRS)
Tan, Bin; Tilton, James C.; Lin, Guoqing
2016-01-01
This is the first study to quantitatively assess and compare cross correlation and normalized mutual information methods used to register images in subpixel scale. The study shows that the normalized mutual information method is less sensitive to unaligned edges due to the spectral response differences than is cross correlation. This characteristic makes the normalized image resolution a better candidate for band to band registration. Improved band-to-band registration in the data from satellite-borne instruments will result in improved retrievals of key science measurements such as cloud properties, vegetation, snow and fire.
Species independence of mutual information in coding and noncoding DNA
NASA Astrophysics Data System (ADS)
Grosse, Ivo; Herzel, Hanspeter; Buldyrev, Sergey V.; Stanley, H. Eugene
2000-05-01
We explore if there exist universal statistical patterns that are different in coding and noncoding DNA and can be found in all living organisms, regardless of their phylogenetic origin. We find that (i) the mutual information function I has a significantly different functional form in coding and noncoding DNA. We further find that (ii) the probability distributions of the average mutual information I¯ are significantly different in coding and noncoding DNA, while (iii) they are almost the same for organisms of all taxonomic classes. Surprisingly, we find that I¯ is capable of predicting coding regions as accurately as organism-specific coding measures.
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.
[Method of multi-resolution 3D image registration by mutual information].
Ren, Haiping; Wu, Wenkai; Yang, Hu; Chen, Shengzu
2002-12-01
Maximization of mutual information is a powerful criterion for 3D medical image registration, allowing robust and fully accurate automated rigid registration of multi-modal images in a various applications. In this paper, a method based on normalized mutual information for 3D image registration was presented on the images of CT, MR and PET. Powell's direction set method and Brent's one-dimensional optimization algorithm were used as optimization strategy. A multi-resolution approach is applied to speedup the matching process. For PET images, pre-procession of segmentation was performed to reduce the background artefacts. According to the evaluation by the Vanderbilt University, Sub-voxel accuracy in multi-modality registration had been achieved with this algorithm. PMID:12561358
Feature selection using mutual information based uncertainty measures for tumor classification.
Sun, Lin; Xu, Jiucheng
2014-01-01
Feature selection is a key problem in tumor classification and related tasks. This paper presents a tumor classification approach with neighborhood rough set-based feature selection. First, some uncertainty measures such as neighborhood entropy, conditional neighborhood entropy, neighborhood mutual information and neighborhood conditional mutual information, are introduced to evaluate the relevance between genes and related decision in neighborhood rough set. Then some important properties and propositions of these measures are investigated, and the relationships among these measures are established as well. By using improved minimal-Redundancy-Maximal-Relevancy, combined with sequential forward greedy search strategy, a novel feature selection algorithm with low time complexity is proposed. Finally, several cancer classification tasks are demonstrated using the proposed approach. Experimental results show that the proposed algorithm is efficient and effective.
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.
Extending the mutual information measure to rank inferred literature relationships
Wren, Jonathan D
2004-01-01
Background Within the peer-reviewed literature, associations between two things are not always recognized until commonalities between them become apparent. These commonalities can provide justification for the inference of a new relationship where none was previously known, and are the basis of most observation-based hypothesis formation. It has been shown that the crux of the problem is not finding inferable associations, which are extraordinarily abundant given the scale-free networks that arise from literature-based associations, but determining which ones are informative. The Mutual Information Measure (MIM) is a well-established method to measure how informative an association is, but is limited to direct (i.e. observable) associations. Results Herein, we attempt to extend the calculation of mutual information to indirect (i.e. inferable) associations by using the MIM of shared associations. Objects of general research interest (e.g. genes, diseases, phenotypes, drugs, ontology categories) found within MEDLINE are used to create a network of associations for evaluation. Conclusions Mutual information calculations can be effectively extended into implied relationships and a significance cutoff estimated from analysis of random word networks. Of the models tested, the shared minimum MIM (MMIM) model is found to correlate best with the observed strength and frequency of known associations. Using three test cases, the MMIM method tends to rank more specific relationships higher than counting the number of shared relationships within a network. PMID:15471547
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.
Networks in financial markets based on the mutual information rate.
Fiedor, Paweł
2014-05-01
In the last few years there have been many efforts in econophysics studying how network theory can facilitate understanding of complex financial markets. These efforts consist mainly of the study of correlation-based hierarchical networks. This is somewhat surprising as the underlying assumptions of research looking at financial markets are that they are complex systems and thus behave in a nonlinear manner, which is confirmed by numerous studies, making the use of correlations which are inherently dealing with linear dependencies only baffling. In this paper we introduce a way to incorporate nonlinear dynamics and dependencies into hierarchical networks to study financial markets using mutual information and its dynamical extension: the mutual information rate. We show that this approach leads to different results than the correlation-based approach used in most studies, on the basis of 91 companies listed on the New York Stock Exchange 100 between 2003 and 2013, using minimal spanning trees and planar maximally filtered graphs.
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.
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.
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
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
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
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.
Efficient measurements, purification, and bounds on the mutual information
NASA Astrophysics Data System (ADS)
Jacobs, Kurt
2003-11-01
When a measurement is made on a quantum system in which classical information is encoded, the measurement reduces the observers’ average Shannon entropy for the encoding ensemble. This reduction, being the mutual information, is always non-negative. For efficient measurements the state is also purified; that is, on average, the observers’ von Neumann entropy for the state of the system is also reduced by a non-negative amount. Here we point out that by rewriting a bound derived by Hall [Phys. Rev. A 55, 100 (1997)], which is dual to the Holevo bound, one finds that for efficient measurements, the mutual information is bounded by the reduction in the von Neumann entropy. We also show that this result, which provides a physical interpretation for Hall’s bound, may be derived directly from the Schumacher-Westmoreland-Wootters theorem [Phys. Rev. Lett. 76, 3452 (1996)]. We discuss these bounds, and their relationship to another bound, valid for efficient measurements on pure state ensembles, which involves the subentropy.
MIDER: network inference with mutual information distance and entropy reduction.
Villaverde, Alejandro F; Ross, John; Morán, Federico; Banga, Julio R
2014-01-01
The prediction of links among variables from a given dataset is a task referred to as network inference or reverse engineering. It is an open problem in bioinformatics and systems biology, as well as in other areas of science. Information theory, which uses concepts such as mutual information, provides a rigorous framework for addressing it. While a number of information-theoretic methods are already available, most of them focus on a particular type of problem, introducing assumptions that limit their generality. Furthermore, many of these methods lack a publicly available implementation. Here we present MIDER, a method for inferring network structures with information theoretic concepts. It consists of two steps: first, it provides a representation of the network in which the distance among nodes indicates their statistical closeness. Second, it refines the prediction of the existing links to distinguish between direct and indirect interactions and to assign directionality. The method accepts as input time-series data related to some quantitative features of the network nodes (such as e.g. concentrations, if the nodes are chemical species). It takes into account time delays between variables, and allows choosing among several definitions and normalizations of mutual information. It is general purpose: it may be applied to any type of network, cellular or otherwise. A Matlab implementation including source code and data is freely available (http://www.iim.csic.es/~gingproc/mider.html). The performance of MIDER has been evaluated on seven different benchmark problems that cover the main types of cellular networks, including metabolic, gene regulatory, and signaling. Comparisons with state of the art information-theoretic methods have demonstrated the competitive performance of MIDER, as well as its versatility. Its use does not demand any a priori knowledge from the user; the default settings and the adaptive nature of the method provide good results for a wide
MIDER: network inference with mutual information distance and entropy reduction.
Villaverde, Alejandro F; Ross, John; Morán, Federico; Banga, Julio R
2014-01-01
The prediction of links among variables from a given dataset is a task referred to as network inference or reverse engineering. It is an open problem in bioinformatics and systems biology, as well as in other areas of science. Information theory, which uses concepts such as mutual information, provides a rigorous framework for addressing it. While a number of information-theoretic methods are already available, most of them focus on a particular type of problem, introducing assumptions that limit their generality. Furthermore, many of these methods lack a publicly available implementation. Here we present MIDER, a method for inferring network structures with information theoretic concepts. It consists of two steps: first, it provides a representation of the network in which the distance among nodes indicates their statistical closeness. Second, it refines the prediction of the existing links to distinguish between direct and indirect interactions and to assign directionality. The method accepts as input time-series data related to some quantitative features of the network nodes (such as e.g. concentrations, if the nodes are chemical species). It takes into account time delays between variables, and allows choosing among several definitions and normalizations of mutual information. It is general purpose: it may be applied to any type of network, cellular or otherwise. A Matlab implementation including source code and data is freely available (http://www.iim.csic.es/~gingproc/mider.html). The performance of MIDER has been evaluated on seven different benchmark problems that cover the main types of cellular networks, including metabolic, gene regulatory, and signaling. Comparisons with state of the art information-theoretic methods have demonstrated the competitive performance of MIDER, as well as its versatility. Its use does not demand any a priori knowledge from the user; the default settings and the adaptive nature of the method provide good results for a wide
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.
MIDER: Network Inference with Mutual Information Distance and Entropy Reduction
Villaverde, Alejandro F.; Ross, John; Morán, Federico; Banga, Julio R.
2014-01-01
The prediction of links among variables from a given dataset is a task referred to as network inference or reverse engineering. It is an open problem in bioinformatics and systems biology, as well as in other areas of science. Information theory, which uses concepts such as mutual information, provides a rigorous framework for addressing it. While a number of information-theoretic methods are already available, most of them focus on a particular type of problem, introducing assumptions that limit their generality. Furthermore, many of these methods lack a publicly available implementation. Here we present MIDER, a method for inferring network structures with information theoretic concepts. It consists of two steps: first, it provides a representation of the network in which the distance among nodes indicates their statistical closeness. Second, it refines the prediction of the existing links to distinguish between direct and indirect interactions and to assign directionality. The method accepts as input time-series data related to some quantitative features of the network nodes (such as e.g. concentrations, if the nodes are chemical species). It takes into account time delays between variables, and allows choosing among several definitions and normalizations of mutual information. It is general purpose: it may be applied to any type of network, cellular or otherwise. A Matlab implementation including source code and data is freely available (http://www.iim.csic.es/~gingproc/mider.html). The performance of MIDER has been evaluated on seven different benchmark problems that cover the main types of cellular networks, including metabolic, gene regulatory, and signaling. Comparisons with state of the art information–theoretic methods have demonstrated the competitive performance of MIDER, as well as its versatility. Its use does not demand any a priori knowledge from the user; the default settings and the adaptive nature of the method provide good results for a wide
Compositional genomes: prebiotic information transfer in mutually catalytic noncovalent assemblies.
Segré, D; Ben-Eli, D; Lancet, D
2000-04-11
Mutually catalytic sets of simple organic molecules have been suggested to be capable of self-replication and rudimentary chemical evolution. Previous models for the behavior of such sets have analyzed the global properties of short biopolymer ensembles by using graph theory and a mean field approach. In parallel, experimental studies with the autocatalytic formation of amphiphilic assemblies (e.g., lipid vesicles or micelles) demonstrated self-replication properties resembling those of living cells. Combining these approaches, we analyze here the kinetic behavior of small heterogeneous assemblies of spontaneously aggregating molecules, of the type that could form readily under prebiotic conditions. A statistical formalism for mutual rate enhancement is used to numerically simulate the detailed chemical kinetics within such assemblies. We demonstrate that a straightforward set of assumptions about kinetically enhanced recruitment of simple amphiphilic molecules, as well as about the spontaneous growth and splitting of assemblies, results in a complex population behavior. The assemblies manifest a significant degree of homeostasis, resembling the previously predicted quasi-stationary states of biopolymer ensembles (Dyson, F. J. (1982) J. Mol. Evol. 18, 344-350). Such emergent catalysis-driven, compositionally biased entities may be viewed as having rudimentary "compositional genomes." Our analysis addresses the question of how mutually catalytic metabolic networks, devoid of sequence-based biopolymers, could exhibit transfer of chemical information and might undergo selection and evolution. This computed behavior may constitute a demonstration of natural selection in populations of molecules without genetic apparatus, suggesting a pathway from random molecular assemblies to a minimal protocell. PMID:10760281
Compositional genomes: Prebiotic information transfer in mutually catalytic noncovalent assemblies
Segré, Daniel; Ben-Eli, Dafna; Lancet, Doron
2000-01-01
Mutually catalytic sets of simple organic molecules have been suggested to be capable of self-replication and rudimentary chemical evolution. Previous models for the behavior of such sets have analyzed the global properties of short biopolymer ensembles by using graph theory and a mean field approach. In parallel, experimental studies with the autocatalytic formation of amphiphilic assemblies (e.g., lipid vesicles or micelles) demonstrated self-replication properties resembling those of living cells. Combining these approaches, we analyze here the kinetic behavior of small heterogeneous assemblies of spontaneously aggregating molecules, of the type that could form readily under prebiotic conditions. A statistical formalism for mutual rate enhancement is used to numerically simulate the detailed chemical kinetics within such assemblies. We demonstrate that a straightforward set of assumptions about kinetically enhanced recruitment of simple amphiphilic molecules, as well as about the spontaneous growth and splitting of assemblies, results in a complex population behavior. The assemblies manifest a significant degree of homeostasis, resembling the previously predicted quasi-stationary states of biopolymer ensembles (Dyson, F. J. (1982) J. Mol. Evol. 18, 344–350). Such emergent catalysis-driven, compositionally biased entities may be viewed as having rudimentary “compositional genomes.” Our analysis addresses the question of how mutually catalytic metabolic networks, devoid of sequence-based biopolymers, could exhibit transfer of chemical information and might undergo selection and evolution. This computed behavior may constitute a demonstration of natural selection in populations of molecules without genetic apparatus, suggesting a pathway from random molecular assemblies to a minimal protocell. PMID:10760281
Registering multiple medical images using the shared chain mutual information
NASA Astrophysics Data System (ADS)
Jin, Jing; Wang, Qiang; Shen, Yi
2007-07-01
A new approach to the simultaneous registration of multiple medical images is proposed using shared chain mutual information (SCMI) as the matching measure. The presented method applies SCMI to measure the shared information between the multiple images. Registration is achieved by adjusting the relative position of the floating image until the SCMI between all the images is maximized. Using this measure, we registered three and four simulated magnetic resonance imaging (MRI) images using downhill simplex optimization to search for the optimal transformation parameters. Accuracy and validity of the proposed method for multiple-image registration are testified by comparing the results with that of two-image registration. Furthermore, the performance of the proposed method is validated by registering the real ultrasonic image sequence.
Mortazavi, Atiyeh; Moattar, Mohammad Hossein
2016-01-01
High dimensionality of microarray data sets may lead to low efficiency and overfitting. In this paper, a multiphase cooperative game theoretic feature selection approach is proposed for microarray data classification. In the first phase, due to high dimension of microarray data sets, the features are reduced using one of the two filter-based feature selection methods, namely, mutual information and Fisher ratio. In the second phase, Shapley index is used to evaluate the power of each feature. The main innovation of the proposed approach is to employ Qualitative Mutual Information (QMI) for this purpose. The idea of Qualitative Mutual Information causes the selected features to have more stability and this stability helps to deal with the problem of data imbalance and scarcity. In the third phase, a forward selection scheme is applied which uses a scoring function to weight each feature. The performance of the proposed method is compared with other popular feature selection algorithms such as Fisher ratio, minimum redundancy maximum relevance, and previous works on cooperative game based feature selection. The average classification accuracy on eleven microarray data sets shows that the proposed method improves both average accuracy and average stability compared to other approaches. PMID:27127506
Mortazavi, Atiyeh; Moattar, Mohammad Hossein
2016-01-01
High dimensionality of microarray data sets may lead to low efficiency and overfitting. In this paper, a multiphase cooperative game theoretic feature selection approach is proposed for microarray data classification. In the first phase, due to high dimension of microarray data sets, the features are reduced using one of the two filter-based feature selection methods, namely, mutual information and Fisher ratio. In the second phase, Shapley index is used to evaluate the power of each feature. The main innovation of the proposed approach is to employ Qualitative Mutual Information (QMI) for this purpose. The idea of Qualitative Mutual Information causes the selected features to have more stability and this stability helps to deal with the problem of data imbalance and scarcity. In the third phase, a forward selection scheme is applied which uses a scoring function to weight each feature. The performance of the proposed method is compared with other popular feature selection algorithms such as Fisher ratio, minimum redundancy maximum relevance, and previous works on cooperative game based feature selection. The average classification accuracy on eleven microarray data sets shows that the proposed method improves both average accuracy and average stability compared to other approaches.
NASA Astrophysics Data System (ADS)
Diamant, Idit; Shalhon, Moran; Goldberger, Jacob; Greenspan, Hayit
2016-03-01
Classification of clustered breast microcalcifications into benign and malignant categories is an extremely challenging task for computerized algorithms and expert radiologists alike. In this paper we present a novel method for feature selection based on mutual information (MI) criterion for automatic classification of microcalcifications. We explored the MI based feature selection for various texture features. The proposed method was evaluated on a standardized digital database for screening mammography (DDSM). Experimental results demonstrate the effectiveness and the advantage of using the MI-based feature selection to obtain the most relevant features for the task and thus to provide for improved performance as compared to using all features.
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
Gender Classification From Face Images Using Mutual Information and Feature Fusion
NASA Astrophysics Data System (ADS)
Perez, Claudio; Tapia, Juan; Estévez, Pablo; Held, Claudio
2012-01-01
In this article we report a new method for gender classification from frontal face images using feature selection based on mutual information and fusion of features extracted from intensity, shape, texture, and from three different spatial scales. We compare the results of three different mutual information measures: minimum redundancy and maximal relevance (mRMR), normalized mutual information feature selection (NMIFS), and conditional mutual information feature selection (CMIFS). We also show that by fusing features extracted from six different methods we significantly improve the gender classification results relative to those previously published, yielding 99.13% of the gender classification rate on the FERET database.
Contact prediction using mutual information and neural nets.
Shackelford, George; Karplus, Kevin
2007-01-01
Prediction of protein structures continues to be a difficult problem, particularly when there are no solved structures for homologous proteins to use as templates. Local structure prediction (secondary structure and burial) is fairly reliable, but does not provide enough information to produce complete three-dimensional structures. Residue-residue contact prediction, though still not highly reliable, may provide a useful guide for assembling local structure prediction into full tertiary prediction. We develop a neural network which is applied to pairs of residue positions and outputs a probability of contact between the positions. One of the neural net inputs is a novel statistic for detecting correlated mutations: the statistical significance of the mutual information between the corresponding columns of a multiple sequence alignment. This statistic, combined with a second statistic based on the propensity of two amino acid types being in contact, results in a simple neural network that is a good predictor of contacts. Adding more features from amino-acid distributions and local structure predictions, the final neural network predicts contacts better than other submitted contact predictions at CASP7, including contact predictions derived from fragment-based tertiary models on free-modeling domains. It is still not known if contact predictions can improve tertiary models on free-modeling domains. Available at http://www.soe.ucsc.edu/research/compbio/SAM_T06/T06-query.html.
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.
Mutual-information-based registration for ultrasound and CT datasets
NASA Astrophysics Data System (ADS)
Firle, Evelyn A.; Wesarg, Stefan; Dold, Christian
2004-05-01
In many applications for minimal invasive surgery the acquisition of intra-operative medical images is helpful if not absolutely necessary. Especially for Brachytherapy imaging is critically important to the safe delivery of the therapy. Modern computed tomography (CT) and magnetic resonance (MR) scanners allow minimal invasive procedures to be performed under direct imaging guidance. However, conventional scanners do not have real-time imaging capability and are expensive technologies requiring a special facility. Ultrasound (U/S) is a much cheaper and one of the most flexible imaging modalities. It can be moved to the application room as required and the physician sees what is happening as it occurs. Nevertheless it may be easier to interpret these 3D intra-operative U/S images if they are used in combination with less noisier preoperative data such as CT. The purpose of our current investigation is to develop a registration tool for automatically combining pre-operative CT volumes with intra-operatively acquired 3D U/S datasets. The applied alignment procedure is based on the information theoretic approach of maximizing the mutual information of two arbitrary datasets from different modalities. Since the CT datasets include a much bigger field of view we introduced a bounding box to narrow down the region of interest within the CT dataset. We conducted a phantom experiment using a CIRS Model 53 U/S Prostate Training Phantom to evaluate the feasibility and accuracy of the proposed method.
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.
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.
Calculation of mutual information for nonlinear communication channel at large signal-to-noise ratio
NASA Astrophysics Data System (ADS)
Terekhov, I. S.; Reznichenko, A. V.; Turitsyn, S. K.
2016-10-01
Using the path-integral technique we examine the mutual information for the communication channel modeled by the nonlinear Schrödinger equation with additive Gaussian noise. The nonlinear Schrödinger equation is one of the fundamental models in nonlinear physics, and it has a broad range of applications, including fiber optical communications—the backbone of the internet. At large signal-to-noise ratio we present the mutual information through the path-integral, which is convenient for the perturbative expansion in nonlinearity. In the limit of small noise and small nonlinearity we derive analytically the first nonzero nonlinear correction to the mutual information for the channel.
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.
Mutual information and the fidelity of response of gene regulatory models.
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-κB 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.
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.
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
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.
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
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.
Coupled multi-shape model and mutual information for medical image segmentation.
Tsai, A; Wells, W; Tempany, C; Grimson, E; Willsky, A
2003-07-01
This paper presents extensions which improve the performance of the shape-based deformable active contour model presented earlier in [9]. In contrast to that work, the segmentation framework that we present in this paper allows multiple shapes to be segmented simultaneously in a seamless fashion. To achieve this, multiple signed distance functions are employed as the implicit representations of the multiple shape classes within the image. A parametric model for this new representation is derived by applying principal component analysis to the collection of these multiple signed distance functions. By deriving a parametric model in this manner, we obtain a coupling between the multiple shapes within the image and hence effectively capture the co-variations among the different shapes. The parameters of the multi-shape model are then calculated to minimize a single mutual information-based cost functional for image segmentation. The use of a single cost criterion further enhances the coupling between the multiple shapes as the deformation of any given shape depends, at all times, upon every other shape, regardless of their proximity. We demonstrate the utility of this algorithm to the segmentation of the prostate gland, the rectum, and the internal obturator muscles for MR-guided prostate brachytherapy.
Mutual information in coupled multi-shape model for medical image segmentation.
Tsai, A; Wells, W; Tempany, C; Grimson, E; Willsky, A
2004-12-01
This paper presents extensions which improve the performance of the shape-based deformable active contour model presented earlier in [IEEE Conf. Comput. Vision Pattern Recog. 1 (2001) 463] for medical image segmentation. In contrast to that previous work, the segmentation framework that we present in this paper allows multiple shapes to be segmented simultaneously in a seamless fashion. To achieve this, multiple signed distance functions are employed as the implicit representations of the multiple shape classes within the image. A parametric model for this new representation is derived by applying principal component analysis to the collection of these multiple signed distance functions. By deriving a parametric model in this manner, we obtain a coupling between the multiple shapes within the image and hence effectively capture the co-variations among the different shapes. The parameters of the multi-shape model are then calculated to minimize a single mutual information-based cost criterion for image segmentation. The use of a single cost criterion further enhances the coupling between the multiple shapes as the deformation of any given shape depends, at all times, upon every other shape, regardless of their proximity. We found that this resulting algorithm is able to effectively utilize the co-dependencies among the different shapes to aid in the segmentation process. It is able to capture a wide range of shape variability despite being a parametric shape-model. And finally, the algorithm is robust to large amounts of additive noise. We demonstrate the utility of this segmentation framework by applying it to a medical application: the segmentation of the prostate gland, the rectum, and the internal obturator muscles for MR-guided prostate brachytherapy.
A complex network model for seismicity based on mutual information
NASA Astrophysics Data System (ADS)
Jiménez, Abigail
2013-05-01
Seismicity is the product of the interaction between the different parts of the lithosphere. Here, we model each part of the Earth as a cell that is constantly communicating its state to its environment. As a neuron is stimulated and produces an output, the different parts of the lithosphere are constantly stimulated by both other cells and the ductile part of the lithosphere, and produce an output in the form of a stress transfer or an earthquake. This output depends on the properties of each part of the Earth’s crust and the magnitude of the inputs. In this study, we propose an approach to the quantification of this communication, with the aid of the Information Theory, and model seismicity as a Complex Network. We have used data from California, and this new approach gives a better understanding of the processes involved in the formation of seismic patterns in that region.
Model-based image processing using snakes and mutual information
NASA Astrophysics Data System (ADS)
von Klinski, Sebastian; Derz, Claus; Weese, David; Tolxdorff, Thomas
2000-06-01
Any segmentation approach assumes certain knowledge concerning data modalities, relevant organs and their imaging characteristics. These assumptions are necessary for developing criteria by which to separate the organ in question from the surrounding tissue. Typical assumptions are that the organs have homogeneous gray-value characteristics (region growing, region merging, etc.), specific gray-value patterns (classification methods), continuous edges (edge-based approaches), smooth and strong edges (snake approaches), or any combination of these. In most cases, such assumptions are invalid, at least locally. Consequently, these approaches prove to be time consuming either in their parameterization or execution. Further, the low result quality makes post- processing necessary. Our aim was to develop a segmentation approach for large 3D data sets (e.g., CT and MRI) that requires a short interaction time and that can easily be adapted to different organs and data materials. This has been achieved by exploiting available knowledge about data material and organ topology using anatomical models that have been constructed from previously segmented data sets. In the first step, the user manually specifies the general context of the data material and specifies anatomical landmarks. Then this information is used to automatically select a corresponding reference model, which is geometrically adjusted to the current data set. In the third step, a model-based snake approach is applied to determine the correct segmentation of the organ in question. Analogously, this approach can be used for model-based interpolation and registration.
2010-01-01
Background The question of a genetic contribution to the higher prevalence and incidence of end stage kidney disease (ESKD) among African Americans (AA) remained unresolved, until recent findings using admixture mapping pointed to the association of a genomic locus on chromosome 22 with this disease phenotype. In the current study we utilize this example to demonstrate the utility of applying a multi-step admixture mapping approach. Methods A multi-step case only admixture mapping study, consisted of the following steps was designed: 1) Assembly of the sample dataset (ESKD AA); 2) Design of the estimated mutual information ancestry informative markers (n = 2016) screening panel 3); Genotyping the sample set whose size was determined by a power analysis (n = 576) appropriate for the initial screening panel; 4) Inference of local ancestry for each individual and identification of regions with increased AA ancestry using two different ancestry inference statistical approaches; 5) Enrichment of the initial screening panel; 6) Power analysis of the enriched panel 7) Genotyping of additional samples. 8) Re-analysis of the genotyping results to identify a genetic risk locus. Results The initial screening phase yielded a significant peak using the ADMIXMAP ancestry inference program applying case only statistics. Subgroup analysis of 299 ESKD patients with no history of diabetes yielded peaks using both the ANCESTRYMAP and ADMIXMAP ancestry inference programs. The significant peak was found on chromosome 22. Genotyping of additional ancestry informative markers on chromosome 22 that took into account linkage disequilibrium in the ancestral populations, and the addition of samples increased the statistical significance of the finding. Conclusions A multi-step admixture mapping analysis of AA ESKD patients replicated the finding of a candidate risk locus on chromosome 22, contributing to the heightened susceptibility of African Americans to develop non-diabetic ESKD, and
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
NASA Astrophysics Data System (ADS)
Zagrodsky, Vladimir; Shekhar, Raj; Cornhill, J. Fredrick
2001-07-01
Mutual information has been demonstrated to be an accurate and reliable criterion function to perform registration of medical data. Due to speckle noise, ultrasound volumes do not provide a smooth mutual information function. Consequently the optimization technique used must be robust enough to avoid local maxima and converge on the desired global maximum eventually. While the well-known downhill simplex optimization uses a single criterion function, our extension to multi-function optimization uses three criterion functions, namely mutual information computed at three levels of intensity quantization and hence three degrees of noise suppression. Registration was performed with rigid as well as simple non-rigid transformation modes for real-time 3D ultrasound datasets of the left ventricle. Pairs of frames corresponding to the most stationary end- diastolic cardiac phase were chosen, and an initial misalignment was artificially introduced between them. The multi-function simplex optimization reduced the failure rate by a factor of two in comparison to the standard simplex optimization, while the average accuracy for the successful cases was unchanged. A more robust registration resulted form the parallel use of criterion functions. The additional computational cost was negligible, as each of the three implementations of the mutual information used the same joint histogram and required no extra spatial transformation.
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.
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.
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.
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.
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.
Maes, F; Vandermeulen, D; Suetens, P
1999-12-01
Maximization of mutual information of voxel intensities has been demonstrated to be a very powerful criterion for three-dimensional medical image registration, allowing robust and accurate fully automated affine registration of multimodal images in a variety of applications, without the need for segmentation or other preprocessing of the images. In this paper, we investigate the performance of various optimization methods and multiresolution strategies for maximization of mutual information, aiming at increasing registration speed when matching large high-resolution images. We show that mutual information is a continuous function of the affine registration parameters when appropriate interpolation is used and we derive analytic expressions of its derivatives that allow numerically exact evaluation of its gradient. Various multiresolution gradient- and non-gradient-based optimization strategies, such as Powell, simplex, steepest-descent, conjugate-gradient, quasi-Newton and Levenberg-Marquardt methods, are evaluated for registration of computed tomography (CT) and magnetic resonance images of the brain. Speed-ups of a factor of 3 on average compared to Powell's method at full resolution are achieved with similar precision and without a loss of robustness with the simplex, conjugate-gradient and Levenberg-Marquardt method using a two-level multiresolution scheme. Large data sets such as 256(2) x 128 MR and 512(2) x 48 CT images can be registered with subvoxel precision in <5 min CPU time on current workstations. PMID:10709702
A corrected normalized mutual information for performance evaluation of community detection
NASA Astrophysics Data System (ADS)
Lai, Darong; Nardini, Christine
2016-09-01
Normalized mutual information (NMI) is a widely used metric for performance evaluation of community detection methods, recently proven to be affected by finite size effects. To overcome this issue, a metric called relative normalized mutual information (rNMI) has been proposed. However, we show here that rNMI is still a biased metric and may lead, under given circumstances, to erroneous conclusions. The bias is an effect of the so-called reverse finite size effect. We discuss different strategies to address this issue, and then propose a new metric, the corrected normalized mutual information (cNMI), symmetric and well normalized, in the form of empirical calculation and closed-form expression. The experiments show that cNMI not only removes the finite size effect of NMI but also the reverse finite size effect of rNMI, and is hence more suitable for performance evaluation of community detection methods and for other approaches typical of the more general clustering context.
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
Yan, Xiao-Ying; Zhang, Shao-Wu; Zhang, Song-Yao
2016-02-01
The identification of potential drug-target interaction pairs is very important, which is useful not only for providing greater understanding of protein function, but also for enhancing drug research, especially for drug function repositioning. Recently, numerous machine learning-based algorithms (e.g. kernel-based, matrix factorization-based and network-based inference methods) have been developed for predicting drug-target interactions. All these methods implicitly utilize the assumption that similar drugs tend to target similar proteins and yield better results for predicting interactions between drugs and target proteins. To further improve the accuracy of prediction, a new method of network-based label propagation with mutual interaction information derived from heterogeneous networks, namely LPMIHN, is proposed to infer the potential drug-target interactions. LPMIHN separately performs label propagation on drug and target similarity networks, but the initial label information of the target (or drug) network comes from the drug (or target) label network and the known drug-target interaction bipartite network. The independent label propagation on each similarity network explores the cluster structure in its network, and the label information from the other network is used to capture mutual interactions (bicluster structures) between the nodes in each pair of the similarity networks. As compared to other recent state-of-the-art methods on the four popular benchmark datasets of binary drug-target interactions and two quantitative kinase bioactivity datasets, LPMIHN achieves the best results in terms of AUC and AUPR. In addition, many of the promising drug-target pairs predicted from LPMIHN are also confirmed on the latest publicly available drug-target databases such as ChEMBL, KEGG, SuperTarget and Drugbank. These results demonstrate the effectiveness of our LPMIHN method, indicating that LPMIHN has a great potential for predicting drug-target interactions. PMID
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.
Universal behavior of the Shannon mutual information in nonintegrable self-dual quantum chains
NASA Astrophysics Data System (ADS)
Alcaraz, F. C.
2016-09-01
An existing conjecture states that the Shannon mutual information contained in the ground-state wave function of conformally invariant quantum chains, on periodic lattices, has a leading finite-size scaling behavior that, similarly as the von Neumann entanglement entropy, depends on the value of the central charge of the underlying conformal field theory describing the physical properties. This conjecture applies whenever the ground-state wave function is expressed in some special basis (conformal basis). Its formulation comes mainly from numerical evidences on exactly integrable quantum chains. In this paper, the above conjecture was tested for several general nonintegrable quantum chains. We introduce new families of self-dual Z (Q ) symmetric quantum chains (Q =2 ,3 ,... ). These quantum chains contain nearest-neighbor as well next-nearest-neighbor interactions (coupling constant p ). In the cases Q =2 and Q =3 , they are extensions of the standard quantum Ising and three-state Potts chains, respectively. For Q =4 and Q ≥5 , they are extensions of the Ashkin-Teller and Z (Q ) parafermionic quantum chains. Our studies indicate that these models are interesting on their own. They are critical, conformally invariant, and share the same universality class in a continuous critical line. Moreover, our numerical analysis for Q =2 -8 indicate that the Shannon mutual information exhibits the conjectured behavior irrespective if the conformally invariant quantum chain is exactly integrable or not. For completeness we also calculated, for these new families of quantum chains, the two existing generalizations of the Shannon mutual information, which are based on the Rényi entropy and on the Rényi divergence.
Analysis of phylogenetic signal in protostomial intron patterns using Mutual Information.
Hill, Natascha; Leow, Alexander; Bleidorn, Christoph; Groth, Detlef; Tiedemann, Ralph; Selbig, Joachim; Hartmann, Stefanie
2013-06-01
Many deep evolutionary divergences still remain unresolved, such as those among major taxa of the Lophotrochozoa. As alternative phylogenetic markers, the intron-exon structure of eukaryotic genomes and the patterns of absence and presence of spliceosomal introns appear to be promising. However, given the potential homoplasy of intron presence, the phylogenetic analysis of this data using standard evolutionary approaches has remained a challenge. Here, we used Mutual Information (MI) to estimate the phylogeny of Protostomia using gene structure data, and we compared these results with those obtained with Dollo Parsimony. Using full genome sequences from nine Metazoa, we identified 447 groups of orthologous sequences with 21,732 introns in 4,870 unique intron positions. We determined the shared absence and presence of introns in the corresponding sequence alignments and have made this data available in "IntronBase", a web-accessible and downloadable SQLite database. Our results obtained using Dollo Parsimony are obviously misled through systematic errors that arise from multiple intron loss events, but extensive filtering of data improved the quality of the estimated phylogenies. Mutual Information, in contrast, performs better with larger datasets, but at the same time it requires a complete data set, which is difficult to obtain for orthologs from a large number of taxa. Nevertheless, Mutual Information-based distances proved to be useful in analyzing this kind of data, also because the estimation of MI-based distances is independent of evolutionary models and therefore no pre-definitions of ancestral and derived character states are necessary.
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
Min, Byung-Chan; Jin, Seung-Hyun; Kang, In-Hyeng; Lee, Dong Hyung; Kang, Jin Kyu; Lee, Sang Tae; Sakamoto, Kazuyoshi
2003-11-01
To investigate the changes of cortico-cortical connectivity during odor stimulation of subjects classified by occupation, the mutual information content of EEGs was examined for general workers, perfume salespersons and professional perfume researchers. Analysis of the averaged-cross mutual information content (A-CMI) from the EEGs revealed that among the professional perfume researchers changes in the A-CMI values during odor stimulation were more apparent in the frontal region of the brain, while for the general workers and perfume salespersons such changes were more conspicuous in the overall posterior temporal, parietal and frontal regions. These results indicate that the brains of professional perfume researchers respond to odors mainly in the frontal region, reflecting the function of the orbitofrontal cortex (OFC) due to the occupational requirement of these subjects to discriminate or identify odors. During odor stimulation, the perfume salespersons, although relatively more exposed to odors than the general workers, showed similar changes to the general workers. The A-CMI value is in inverse proportion to psychological preferences of the professional perfume researchers and perfume salespersons, though this is not the case with the general workers. This result suggests that functional coupling for people who are occupationally exposed to odors may be related to psychological preference.
Min, Byung-Chan; Jin, Seung-Hyun; Kang, In-Hyeng; Lee, Dong Hyung; Kang, Jin Kyu; Lee, Sang Tae; Sakamoto, Kazuyoshi
2003-11-01
To investigate the changes of cortico-cortical connectivity during odor stimulation of subjects classified by occupation, the mutual information content of EEGs was examined for general workers, perfume salespersons and professional perfume researchers. Analysis of the averaged-cross mutual information content (A-CMI) from the EEGs revealed that among the professional perfume researchers changes in the A-CMI values during odor stimulation were more apparent in the frontal region of the brain, while for the general workers and perfume salespersons such changes were more conspicuous in the overall posterior temporal, parietal and frontal regions. These results indicate that the brains of professional perfume researchers respond to odors mainly in the frontal region, reflecting the function of the orbitofrontal cortex (OFC) due to the occupational requirement of these subjects to discriminate or identify odors. During odor stimulation, the perfume salespersons, although relatively more exposed to odors than the general workers, showed similar changes to the general workers. The A-CMI value is in inverse proportion to psychological preferences of the professional perfume researchers and perfume salespersons, though this is not the case with the general workers. This result suggests that functional coupling for people who are occupationally exposed to odors may be related to psychological preference. PMID:14654441
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.
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.
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.
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
NASA Astrophysics Data System (ADS)
Klein, Stefan; Staring, Marius; Pluim, Josien P. W.
2005-04-01
Nonrigid registration of medical images by maximisation of their mutual information, in combination with a deformation field parameterised by cubic B-splines, has been shown to be robust and accurate in many applications. However, the high computation time is a big disadvantage. This work focusses on the optimisation procedure. Many implementations follow a gradient-descent like approach. The time needed for computing the derivative of the mutual information with respect to the B-spline parameters is the bottleneck in this process. We investigate the influence of several gradient approximation techniques on the number of iterations needed and the computation time per iteration. Three methods are studied: a simple finite difference strategy, the so-called simultaneous perturbation method, and a more analytic computation of the gradient based on a continuous, and differentiable representation of the joint histogram. In addition, the effect of decreasing the number of image samples, used for computing the gradient in each iteration, is investigated. Two types of experiments are performed. Firstly, the registration of an image to itself, after application of a known, randomly generated deformation, is considered. Secondly, experiments are performed with 3D ultrasound brain scans, and 3D CT follow-up scans of the chest. The experiments show that the method using an analytic gradient computation outperforms the other two. Furthermore, the computation time per iteration can be extremely decreased, without affecting the rate of convergence and final accuracy, by using very few samples of the image (randomly chosen every iteration) to compute the derivative. With this approach, large data sets (2563) can be registered within 5 minutes on a moderate PC.
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)
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.
Jin, Seung-Hyun; Lin, Peter; Hallett, Mark
2010-01-01
Objective To propose a model-free method to show linear and nonlinear information flow based on time delayed mutual information (TDMI) by employing uni- and bi-variate surrogate tests and to investigate whether there are contributions of the nonlinear information flow in corticomuscular (CM) interaction. Methods Using simulated data, we tested whether our method would successfully detect the direction of information flow and identify a relationship between two simulated time series. As an experimental data application, we applied this method to investigate CM interaction during a right wrist extension task. Results Results of simulation tests show that we can correctly detect the direction of information flow and the relationship between two time series without a prior knowledge of the dynamics of their generating systems. As experimental results, we found both linear and nonlinear information flow from contralateral sensorimotor cortex to muscle. Conclusions Our method is a viable model-free measure of temporally varying causal interactions that is capable of distinguishing linear and nonlinear information flow. With respect to experimental application, there are both linear and nonlinear information flows in CM interaction from contralateral sensorimotor cortex to muscle, which may reflect the motor command from brain to muscle. Significance This is the first study to show separate linear and nonlinear information flow in CM interaction. PMID:20044309
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.
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.
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.
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.
Abnormal functional connectivity in focal hand dystonia: Mutual information analysis in EEG
Jin, Seung-Hyun; Lin, Peter; Auh, Sungyoung; Hallett, Mark
2011-01-01
The aim of the present study was to investigate functional connectivity (FC) in focal hand dystonia (FHD) patients to understand the pathophysiology underlying their abnormality in movement. We recorded EEG from 58 electrodes in 15 FHD patients and 15 healthy volunteers during rest and a simple finger-tapping task that did not induce any dystonic symptoms. We investigated the mutual information (MI), which provides a quantitative measure of linear and nonlinear coupling, in the alpha, beta and gamma bands. Mean MI of all 58 channels and mean of the channels of interest (COIs) representative of regional FC over sensorimotor areas (C3, CP3, C4, CP4, FCz and Cz) were evaluated. For both groups, we found enhanced MI during the task compared to the rest condition specifically in the beta and gamma bands for mean MI of all channels, and in all bands for mean MI of COIs. Comparing the FHD patients to the healthy volunteers, for both rest and task, there was reduced MI in the beta band for both mean MI of all channels and mean MI of COIs. Regarding the properties of the connectivity in the beta band, we found that the majority of the MI differences were from linear connectivity. The abnormal beta band FC in FHD patients suggests deficient brain connectivity. PMID:21506166
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.
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%.
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.
Fusion of rat brain histology and MRI using weighted multi-image mutual information
NASA Astrophysics Data System (ADS)
Palm, Christoph; Penney, Graeme P.; Crum, William R.; Schnabel, Julia A.; Pietrzyk, Uwe; Hawkes, David J.
2008-03-01
Introduction - Fusion of histology and MRI is frequently demanded in biomedical research to study in vitro tissue properties in an in vivo reference space. Distortions and artifacts caused by cutting and staining of histological slices as well as differences in spatial resolution make even the rigid fusion a difficult task. State-of- the-art methods start with a mono-modal restacking yielding a histological pseudo-3D volume. The 3D information of the MRI reference is considered subsequently. However, consistency of the histology volume and consistency due to the corresponding MRI seem to be diametral goals. Therefore, we propose a novel fusion framework optimizing histology/histology and histology/MRI consistency at the same time finding a balance between both goals. Method - Direct slice-to-slice correspondence even in irregularly-spaced cutting sequences is achieved by registration-based interpolation of the MRI. Introducing a weighted multi-image mutual information metric (WI), adjacent histology and corresponding MRI are taken into account at the same time. Therefore, the reconstruction of the histological volume as well as the fusion with the MRI is done in a single step. Results - Based on two data sets with more than 110 single registrations in all, the results are evaluated quantitatively based on Tanimoto overlap measures and qualitatively showing the fused volumes. In comparison to other multi-image metrics, the reconstruction based on WI is significantly improved. We evaluated different parameter settings with emphasis on the weighting term steering the balance between intra- and inter-modality consistency.
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
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.
Cui, Dong; Pu, Weiting; Liu, Jing; Bian, Zhijie; Li, Qiuli; Wang, Lei; Gu, Guanghua
2016-10-01
Synchronization is an important mechanism for understanding information processing in normal or abnormal brains. In this paper, we propose a new method called normalized weighted-permutation mutual information (NWPMI) for double variable signal synchronization analysis and combine NWPMI with S-estimator measure to generate a new method named S-estimator based normalized weighted-permutation mutual information (SNWPMI) for analyzing multi-channel electroencephalographic (EEG) synchronization strength. The performances including the effects of time delay, embedding dimension, coupling coefficients, signal to noise ratios (SNRs) and data length of the NWPMI are evaluated by using Coupled Henon mapping model. The results show that the NWPMI is superior in describing the synchronization compared with the normalized permutation mutual information (NPMI). Furthermore, the proposed SNWPMI method is applied to analyze scalp EEG data from 26 amnestic mild cognitive impairment (aMCI) subjects and 20 age-matched controls with normal cognitive function, who both suffer from type 2 diabetes mellitus (T2DM). The proposed methods NWPMI and SNWPMI are suggested to be an effective index to estimate the synchronization strength.
NASA Astrophysics Data System (ADS)
Jacobs, Kurt
2006-01-01
The Holevo bound is a bound on the mutual information for a given quantum encoding. In 1996 Schumacher, Westmoreland, and Wootters [Phys. Rev. Lett. 76, 3452 (1996)] derived a bound that reduces to the Holevo bound for complete measurements, but that is tighter for incomplete measurements. The most general quantum operations may be both incomplete and inefficient. Here we show that the bound derived by SWW can be further extended to obtain one that is yet again tighter for inefficient measurements. This allows us, in addition, to obtain a generalization of a bound derived by Hall, and to show that the average reduction in the von Neumann entropy during a quantum operation is concave in the initial state, for all quantum operations. This is a quantum version of the concavity of the mutual information. We also show that both this average entropy reduction and the mutual information for pure state ensembles, are Schur concave for unitarily covariant measurements; that is, for these measurements, information gain increases with initial uncertainty.
Cui, Dong; Pu, Weiting; Liu, Jing; Bian, Zhijie; Li, Qiuli; Wang, Lei; Gu, Guanghua
2016-10-01
Synchronization is an important mechanism for understanding information processing in normal or abnormal brains. In this paper, we propose a new method called normalized weighted-permutation mutual information (NWPMI) for double variable signal synchronization analysis and combine NWPMI with S-estimator measure to generate a new method named S-estimator based normalized weighted-permutation mutual information (SNWPMI) for analyzing multi-channel electroencephalographic (EEG) synchronization strength. The performances including the effects of time delay, embedding dimension, coupling coefficients, signal to noise ratios (SNRs) and data length of the NWPMI are evaluated by using Coupled Henon mapping model. The results show that the NWPMI is superior in describing the synchronization compared with the normalized permutation mutual information (NPMI). Furthermore, the proposed SNWPMI method is applied to analyze scalp EEG data from 26 amnestic mild cognitive impairment (aMCI) subjects and 20 age-matched controls with normal cognitive function, who both suffer from type 2 diabetes mellitus (T2DM). The proposed methods NWPMI and SNWPMI are suggested to be an effective index to estimate the synchronization strength. PMID:27451314
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.
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
Barigye, Stephen J; Marrero-Ponce, Yovani; Santiago, Oscar Martinez; López, Yoan Martinez; Pérez-Giménez, Facundo; Torrens, Francisco
2013-06-01
A new mathematical approach is proposed in the definition of molecular descriptors (MDs) based on the application of information theory concepts. This approach stems from a new matrix representation of a molecular graph (G) which is derived from the generalization of an incidence matrix whose row entries correspond to connected subgraphs of a given G, and the calculation of the Shannon's entropy, the negentropy and the standardized information content, plus for the first time, the mutual, conditional and joint entropy-based MDs associated with G. We also define strategies that generalize the definition of global or local invariants from atomic contributions (local vertex invariants, LOVIs), introducing related metrics (norms), means and statistical invariants. These invariants are applied to a vector whose components express the atomic information content calculated using the Shannon's, mutual, conditional and joint entropybased atomic information indices. The novel information indices (IFIs) are implemented in the program TOMOCOMDCARDD. A principal component analysis reveals that the novel IFIs are capable of capturing structural information not codified by IFIs implemented in the software DRAGON. A comparative study of the different parameters (e.g. subgraph orders and/or types, invariants and class of MDs) used in the definition of these IFIs reveals several interesting results. The mutual entropy-based indices give the best correlation results in modeling of a physicochemical property, namely the partition coefficient of the 34 derivatives of 2-furylethylenes, among the classes of indices investigated in this study. In a comparison with classical MDs it is demonstrated that the new IFIs give good results for various QSPR models.
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.
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).
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.
ERIC Educational Resources Information Center
Wang, Chun
2013-01-01
Cognitive diagnostic computerized adaptive testing (CD-CAT) purports to combine the strengths of both CAT and cognitive diagnosis. Cognitive diagnosis models aim at classifying examinees into the correct mastery profile group so as to pinpoint the strengths and weakness of each examinee whereas CAT algorithms choose items to determine those…
Information filtering via weighted heat conduction algorithm
NASA Astrophysics Data System (ADS)
Liu, Jian-Guo; Guo, Qiang; Zhang, Yi-Cheng
2011-06-01
In this paper, by taking into account effects of the user and object correlations on a heat conduction (HC) algorithm, a weighted heat conduction (WHC) algorithm is presented. We argue that the edge weight of the user-object bipartite network should be embedded into the HC algorithm to measure the object similarity. The numerical results indicate that both the accuracy and diversity could be improved greatly compared with the standard HC algorithm and the optimal values reached simultaneously. On the Movielens and Netflix datasets, the algorithmic accuracy, measured by the average ranking score, can be improved by 39.7% and 56.1% in the optimal case, respectively, and the diversity could reach 0.9587 and 0.9317 when the recommendation list equals to 5. Further statistical analysis indicates that, in the optimal case, the distributions of the edge weight are changed to the Poisson form, which may be the reason why HC algorithm performance could be improved. This work highlights the effect of edge weight on a personalized recommendation study, which maybe an important factor affecting personalized recommendation performance.
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
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.
Cortical Entropy, Mutual Information and Scale-Free Dynamics in Waking Mice.
Fagerholm, Erik D; Scott, Gregory; Shew, Woodrow L; Song, Chenchen; Leech, Robert; Knöpfel, Thomas; Sharp, David J
2016-10-01
Some neural circuits operate with simple dynamics characterized by one or a few well-defined spatiotemporal scales (e.g. central pattern generators). In contrast, cortical neuronal networks often exhibit richer activity patterns in which all spatiotemporal scales are represented. Such "scale-free" cortical dynamics manifest as cascades of activity with cascade sizes that are distributed according to a power-law. Theory and in vitro experiments suggest that information transmission among cortical circuits is optimized by scale-free dynamics. In vivo tests of this hypothesis have been limited by experimental techniques with insufficient spatial coverage and resolution, i.e., restricted access to a wide range of scales. We overcame these limitations by using genetically encoded voltage imaging to track neural activity in layer 2/3 pyramidal cells across the cortex in mice. As mice recovered from anesthesia, we observed three changes: (a) cortical information capacity increased, (b) information transmission among cortical regions increased and (c) neural activity became scale-free. Our results demonstrate that both information capacity and information transmission are maximized in the awake state in cortical regions with scale-free network dynamics.
Cortical Entropy, Mutual Information and Scale-Free Dynamics in Waking Mice
Fagerholm, Erik D.; Scott, Gregory; Shew, Woodrow L.; Song, Chenchen; Leech, Robert; Knöpfel, Thomas; Sharp, David J.
2016-01-01
Some neural circuits operate with simple dynamics characterized by one or a few well-defined spatiotemporal scales (e.g. central pattern generators). In contrast, cortical neuronal networks often exhibit richer activity patterns in which all spatiotemporal scales are represented. Such “scale-free” cortical dynamics manifest as cascades of activity with cascade sizes that are distributed according to a power-law. Theory and in vitro experiments suggest that information transmission among cortical circuits is optimized by scale-free dynamics. In vivo tests of this hypothesis have been limited by experimental techniques with insufficient spatial coverage and resolution, i.e., restricted access to a wide range of scales. We overcame these limitations by using genetically encoded voltage imaging to track neural activity in layer 2/3 pyramidal cells across the cortex in mice. As mice recovered from anesthesia, we observed three changes: (a) cortical information capacity increased, (b) information transmission among cortical regions increased and (c) neural activity became scale-free. Our results demonstrate that both information capacity and information transmission are maximized in the awake state in cortical regions with scale-free network dynamics. PMID:27384059
Cortical Entropy, Mutual Information and Scale-Free Dynamics in Waking Mice.
Fagerholm, Erik D; Scott, Gregory; Shew, Woodrow L; Song, Chenchen; Leech, Robert; Knöpfel, Thomas; Sharp, David J
2016-10-01
Some neural circuits operate with simple dynamics characterized by one or a few well-defined spatiotemporal scales (e.g. central pattern generators). In contrast, cortical neuronal networks often exhibit richer activity patterns in which all spatiotemporal scales are represented. Such "scale-free" cortical dynamics manifest as cascades of activity with cascade sizes that are distributed according to a power-law. Theory and in vitro experiments suggest that information transmission among cortical circuits is optimized by scale-free dynamics. In vivo tests of this hypothesis have been limited by experimental techniques with insufficient spatial coverage and resolution, i.e., restricted access to a wide range of scales. We overcame these limitations by using genetically encoded voltage imaging to track neural activity in layer 2/3 pyramidal cells across the cortex in mice. As mice recovered from anesthesia, we observed three changes: (a) cortical information capacity increased, (b) information transmission among cortical regions increased and (c) neural activity became scale-free. Our results demonstrate that both information capacity and information transmission are maximized in the awake state in cortical regions with scale-free network dynamics. PMID:27384059
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.
Holledge gauge failure testing using concurrent information processing algorithm
Weeks, G.E.; Daniel, W.E.; Edwards, R.E.; Jannarone, R.J.; Joshi, S.N.; Palakodety, S.S.; Qian, D.
1996-04-11
For several decades, computerized information processing systems and human information processing models have developed with a good deal of mutual influence. Any comprehensive psychology text in this decade uses terms that originated in the computer industry, such as ``cache`` and ``memory``, to describe human information processing. Likewise, many engineers today are using ``artificial intelligence``and ``artificial neural network`` computing tools that originated as models of human thought to solve industrial problems. This paper concerns a recently developed human information processing model, called ``concurrent information processing`` (CIP), and a related set of computing tools for solving industrial problems. The problem of focus is adaptive gauge monitoring; the application is pneumatic pressure repeaters (Holledge gauges) used to measure liquid level and density in the Defense Waste Processing Facility and the Integrated DWPF Melter System.
[Collective properties of the mutual-learned neuronal net systems in the information field].
Grosberg, A Iu; Khrustova, N V
1993-01-01
Model of neural networks system, in which networks interact by transmission and associative recognition of signals, is studied by computer simulation and qualitative approach. System behavior depends on the value of learning parameter epsilon, which determines the weight of writing in memory of each network every transmissible signal. Two different regimes are found: regime of auto-governed behavior, which depends only on initial networks characteristics, and regime of collective recognition of initial signal in form of a certain stable signals cycle. Analogy of this model and Aigen's hypercycle, the problem of creation of some new information in this model are discussed, too. PMID:8364077
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.
Integrating a priori information in edge-linking algorithms
NASA Astrophysics Data System (ADS)
Farag, Aly A.; Cao, Yu; Yeap, Yuen-Pin
1992-09-01
This research presents an approach to integrate a priori information to the path metric of the LINK algorithm. The zero-crossing contours of the $DEL2G are taken as a gross estimate of the boundaries in the image. This estimate of the boundaries is used to define the swath of important information, and to provide a distance measure for edge localization. During the linking process, a priori information plays important roles in (1) dramatically reducing the search space because the actual path lies within +/- 2 (sigma) f from the prototype contours ((sigma) f is the standard deviation of the Gaussian kernel used in the edge enhancement step); (2) breaking the ties when the search metrics give uncertain information; and (3) selecting the set of goal nodes for the search algorithm. We show that the integration of a priori information in the LINK algorithms provides faster and more accurate edge linking.
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
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.
Contrasting distributions of pairwise entanglement and mutual information in Heisenberg spin systems
NASA Astrophysics Data System (ADS)
Subrahmanyam, V.
2016-08-01
The correlations between a pair of spins in a many-spin state encoded in the diagonal and off-diagonal spin-spin correlation functions. These spin functions determine the quantum correlation measures, like pair-wise concurrence, quantum discord and other measures of quantum information. We show that for isotropic and translationally invariant states, the quantum correlations depend only on the diagonal spin correlation function. The pair concurrence shows a strict short-ranged behavior. The distribution of concurrence for a random W-like state exhibits a long tail for both time-reversal invariant states and for states that break the time reversal. The quantum discord can be related to the diagonal spin correlation function. As the spin function is long range close to a critical point, analogously the quantum discord exhibits a long range behavior. For the isotropic state, the conditional entropy distribution is a Dirac delta function, whereas it has a twin-peak structure for the anisotropic model.
FPGA implementation of sparse matrix algorithm for information retrieval
NASA Astrophysics Data System (ADS)
Bojanic, Slobodan; Jevtic, Ruzica; Nieto-Taladriz, Octavio
2005-06-01
Information text data retrieval requires a tremendous amount of processing time because of the size of the data and the complexity of information retrieval algorithms. In this paper the solution to this problem is proposed via hardware supported information retrieval algorithms. Reconfigurable computing may adopt frequent hardware modifications through its tailorable hardware and exploits parallelism for a given application through reconfigurable and flexible hardware units. The degree of the parallelism can be tuned for data. In this work we implemented standard BLAS (basic linear algebra subprogram) sparse matrix algorithm named Compressed Sparse Row (CSR) that is showed to be more efficient in terms of storage space requirement and query-processing timing over the other sparse matrix algorithms for information retrieval application. Although inverted index algorithm is treated as the de facto standard for information retrieval for years, an alternative approach to store the index of text collection in a sparse matrix structure gains more attention. This approach performs query processing using sparse matrix-vector multiplication and due to parallelization achieves a substantial efficiency over the sequential inverted index. The parallel implementations of information retrieval kernel are presented in this work targeting the Virtex II Field Programmable Gate Arrays (FPGAs) board from Xilinx. A recent development in scientific applications is the use of FPGA to achieve high performance results. Computational results are compared to implementations on other platforms. The design achieves a high level of parallelism for the overall function while retaining highly optimised hardware within processing unit.
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…
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
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.
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.
NASA Astrophysics Data System (ADS)
Wen, Xueda; Matsuura, Shunji; Ryu, Shinsei
2016-06-01
We develop an approach based on edge theories to calculate the entanglement entropy and related quantities in (2+1)-dimensional topologically ordered phases. Our approach is complementary to, e.g., the existing methods using replica trick and Witten's method of surgery, and applies to a generic spatial manifold of genus g , which can be bipartitioned in an arbitrary way. The effects of fusion and braiding of Wilson lines can be also straightforwardly studied within our framework. By considering a generic superposition of states with different Wilson line configurations, through an interference effect, we can detect, by the entanglement entropy, the topological data of Chern-Simons theories, e.g., the R symbols, monodromy, and topological spins of quasiparticles. Furthermore, by using our method, we calculate other entanglement/correlation measures such as the mutual information and the entanglement negativity. In particular, it is found that the entanglement negativity of two adjacent noncontractible regions on a torus provides a simple way to distinguish Abelian and non-Abelian topological orders.
Amin, Ruhul; Islam, S K Hafizul; Biswas, G P; Khan, Muhammad Khurram; Obaidat, Mohammad S
2015-11-01
In order to access remote medical server, generally the patients utilize smart card to login to the server. It has been observed that most of the user (patient) authentication protocols suffer from smart card stolen attack that means the attacker can mount several common attacks after extracting smart card information. Recently, Lu et al.'s proposes a session key agreement protocol between the patient and remote medical server and claims that the same protocol is secure against relevant security attacks. However, this paper presents several security attacks on Lu et al.'s protocol such as identity trace attack, new smart card issue attack, patient impersonation attack and medical server impersonation attack. In order to fix the mentioned security pitfalls including smart card stolen attack, this paper proposes an efficient remote mutual authentication protocol using smart card. We have then simulated the proposed protocol using widely-accepted AVISPA simulation tool whose results make certain that the same protocol is secure against active and passive attacks including replay and man-in-the-middle attacks. Moreover, the rigorous security analysis proves that the proposed protocol provides strong security protection on the relevant security attacks including smart card stolen attack. We compare the proposed scheme with several related schemes in terms of computation cost and communication cost as well as security functionalities. It has been observed that the proposed scheme is comparatively better than related existing schemes. PMID:26324169
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
Informational properties of neural nets performing algorithmic and logical tasks.
Ritz, B M; Hofacker, G L
1996-06-01
It is argued that the genetic information necessary to encode an algorithmic neural processor tutoring an otherwise randomly connected biological neural net is represented by the entropy of the analogous minimal Turing machine. Such a near-minimal machine is constructed performing the whole range of bivalent propositional logic in n variables. Neural nets computing the same task are presented; their informational entropy can be gauged with reference to the analogous Turing machine. It is also shown that nets with one hidden layer can be trained to perform algorithms solving propositional logic by error back-propagation. PMID:8672562
Informational properties of neural nets performing algorithmic and logical tasks.
Ritz, B M; Hofacker, G L
1996-06-01
It is argued that the genetic information necessary to encode an algorithmic neural processor tutoring an otherwise randomly connected biological neural net is represented by the entropy of the analogous minimal Turing machine. Such a near-minimal machine is constructed performing the whole range of bivalent propositional logic in n variables. Neural nets computing the same task are presented; their informational entropy can be gauged with reference to the analogous Turing machine. It is also shown that nets with one hidden layer can be trained to perform algorithms solving propositional logic by error back-propagation.
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.
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)
C. elegans locomotion analysis using algorithmic information theory.
Skandari, Roghieh; Le Bihan, Nicolas; Manton, Jonathan H
2015-01-01
This article investigates the use of algorithmic information theory to analyse C. elegans datasets. The ability of complexity measures to detect similarity in animals' behaviours is demonstrated and their strengths are compared to methods such as histograms. Introduced quantities are illustrated on a couple of real two-dimensional C. elegans datasets to investigate the thermotaxis and chemotaxis behaviours.
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.…
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.
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
NASA Astrophysics Data System (ADS)
Zhou, Tianci; Chen, Xiao; Faulkner, Thomas; Fradkin, Eduardo
2016-09-01
We investigate the entanglement entropy (EE) of circular entangling cuts in the 2 + 1-dimensional quantum Lifshitz model. The ground state in this model is a spatially conformal invariant state of the Rokhsar–Kivelson type, whose amplitude is the Gibbs weight of 2D Euclidean free boson. We show that the finite subleading corrections of EE to the area-law term, as well as the mutual information, are conformal invariants and calculate them for cylinder, disk-like and spherical manifolds with various spatial cuts. The subtlety due to the boson compactification in the replica trick is carefully addressed. We find that in the geometry of a punctured plane with many small holes, the constant piece of EE is proportional to the number of holes, indicating the ability of entanglement to detect topological information of the configuration. Finally, we compare the mutual information of two small distant disks with Cardy’s relativistic CFT scaling proposal. We find that in the quantum Lifshitz model, the mutual information also scales at long distance with a power determined by the lowest scaling dimension local operator in the theory.
NASA Astrophysics Data System (ADS)
Zhou, Tianci; Chen, Xiao; Faulkner, Thomas; Fradkin, Eduardo
2016-09-01
We investigate the entanglement entropy (EE) of circular entangling cuts in the 2 + 1-dimensional quantum Lifshitz model. The ground state in this model is a spatially conformal invariant state of the Rokhsar-Kivelson type, whose amplitude is the Gibbs weight of 2D Euclidean free boson. We show that the finite subleading corrections of EE to the area-law term, as well as the mutual information, are conformal invariants and calculate them for cylinder, disk-like and spherical manifolds with various spatial cuts. The subtlety due to the boson compactification in the replica trick is carefully addressed. We find that in the geometry of a punctured plane with many small holes, the constant piece of EE is proportional to the number of holes, indicating the ability of entanglement to detect topological information of the configuration. Finally, we compare the mutual information of two small distant disks with Cardy’s relativistic CFT scaling proposal. We find that in the quantum Lifshitz model, the mutual information also scales at long distance with a power determined by the lowest scaling dimension local operator in the theory.
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.
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.
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.
Bramble, J M
1989-02-01
Data compression increases the number of images that can be stored on magnetic disks or tape and reduces the time required for transmission of images between stations. Two algorithms for data compression are compared in application to computed tomographic (CT) images. The first, an information-preserving algorithm combining differential and Huffman encoding, allows reconstruction of the original image. A second algorithm alters the image in a clinically acceptable manner. This second algorithm combines two processes: the suppression of data outside of the head or body and the combination of differential and Huffman encoding. Because the final image is not an exact copy, the second algorithm is information losing. Application of the information-preserving algorithm can double or triple the number of CT images that can be stored on hard disk or magnetic tape. This algorithm may also double or triple the speed with which images may be transmitted. The information-losing algorithm can increase storage or transmission speed by a factor of five. The computation time on this system is excessive, but dedicated hardware is available to allow efficient implementation.
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
Methods of information theory and algorithmic complexity for network biology.
Zenil, Hector; Kiani, Narsis A; Tegnér, Jesper
2016-03-01
We survey and introduce concepts and tools located at the intersection of information theory and network biology. We show that Shannon's information entropy, compressibility and algorithmic complexity quantify different local and global aspects of synthetic and biological data. We show examples such as the emergence of giant components in Erdös-Rényi random graphs, and the recovery of topological properties from numerical kinetic properties simulating gene expression data. We provide exact theoretical calculations, numerical approximations and error estimations of entropy, algorithmic probability and Kolmogorov complexity for different types of graphs, characterizing their variant and invariant properties. We introduce formal definitions of complexity for both labeled and unlabeled graphs and prove that the Kolmogorov complexity of a labeled graph is a good approximation of its unlabeled Kolmogorov complexity and thus a robust definition of graph complexity.
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
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
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
Contrast enhancement algorithm considering surrounding information by illumination image
NASA Astrophysics Data System (ADS)
Song, Ki Sun; Kang, Hee; Kang, Moon Gi
2014-09-01
We propose a contrast enhancement algorithm considering surrounding information by illumination image. Conventional contrast enhancement techniques can be classified as a retinex-based method and a tone mapping function-based method. However, many retinex methods suffer from high-computational costs or halo artifacts. To cope with these problems, efficient edge-preserving smoothing methods have been researched. Tone mapping function-based methods are limited in terms of enhancement since they are applied without considering surrounding information. To solve these problems, we estimate an illumination image with local adaptive smoothness, and then utilize it as surrounding information. The local adaptive smoothness is calculated by using illumination image properties and an edge-adaptive filter based on the just noticeable difference model. Additionally, we employ a resizing method instead of a blur kernel to reduce the computational cost of illumination estimation. The estimated illumination image is incorporated with the tone mapping function to address the limitations of the tone mapping function-based method. With this approach, the amount of local contrast enhancement is increased. Experimental results show that the proposed algorithm enhances both global and local contrasts and produces better performance in objective evaluation metrics while preventing a halo artifact.
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.
Leigh, E G
2010-12-01
Like altruism, mutualism, cooperation between species, evolves only by enhancing all participants' inclusive fitness. Mutualism evolves most readily between members of different kingdoms, which pool complementary abilities for mutual benefit: some of these mutualisms represent major evolutionary innovations. Mutualism cannot persist if cheating annihilates its benefits. In long-term mutualisms, symbioses, at least one party associates with the other nearly all its life. Usually, a larger host harbours smaller symbionts. Cheating is restrained by vertical transmission, as in Buchnera; partner fidelity, as among bull-thorn acacias and protective ants; test-based choice of symbionts, as bobtail squid choose bioluminescent bacteria; or sanctioning nonperforming symbionts, as legumes punish nonperforming nitrogen-fixing bacteria. Mutualisms involving brief exchanges, as among plants and seed-dispersers, however, persist despite abundant cheating. Both symbioses and brief-exchange mutualisms have transformed whole ecosystems. These mutualisms may be steps towards ecosystems which, like Adam Smith's ideal economy, serve their members' common good.
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.
The accurate reconstruction of gene regulatory networks from large scale molecular profile datasets represents one of the grand challenges of Systems Biology. The Algorithm for the Reconstruction of Accurate Cellular Networks (ARACNe) represents one of the most effective tools to accomplish this goal. However, the initial Fixed Bandwidth (FB) implementation is both inefficient and unable to deal with sample sets providing largely uneven coverage of the probability density space.
Thermodynamic cost of computation, algorithmic complexity and the information metric
NASA Technical Reports Server (NTRS)
Zurek, W. H.
1989-01-01
Algorithmic complexity is discussed as a computational counterpart to the second law of thermodynamics. It is shown that algorithmic complexity, which is a measure of randomness, sets limits on the thermodynamic cost of computations and casts a new light on the limitations of Maxwell's demon. Algorithmic complexity can also be used to define distance between binary strings.
On Distribution Reduction and Algorithm Implementation in Inconsistent Ordered Information Systems
Zhang, Yanqin
2014-01-01
As one part of our work in ordered information systems, distribution reduction is studied in inconsistent ordered information systems (OISs). Some important properties on distribution reduction are studied and discussed. The dominance matrix is restated for reduction acquisition in dominance relations based information systems. Matrix algorithm for distribution reduction acquisition is stepped. And program is implemented by the algorithm. The approach provides an effective tool for the theoretical research and the applications for ordered information systems in practices. For more detailed and valid illustrations, cases are employed to explain and verify the algorithm and the program which shows the effectiveness of the algorithm in complicated information systems. PMID:25258721
An Introduction to Genetic Algorithms and to Their Use in Information Retrieval.
ERIC Educational Resources Information Center
Jones, Gareth; And Others
1994-01-01
Genetic algorithms, a class of nondeterministic algorithms in which the role of chance makes the precise nature of a solution impossible to guarantee, seem to be well suited to combinatorial-optimization problems in information retrieval. Provides an introduction to techniques and characteristics of genetic algorithms and illustrates their…
NASA Astrophysics Data System (ADS)
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
2016-08-01
Quantum steganography can solve some problems that are considered inefficient in image information concealing. It researches on Quantum image information concealing to have been widely exploited in recent years. Quantum image information concealing can be categorized into quantum image digital blocking, quantum image stereography, anonymity and other branches. Least significant bit (LSB) information concealing plays vital roles in the classical world because many image information concealing algorithms are designed based on it. Firstly, based on the novel enhanced quantum representation (NEQR), image uniform blocks clustering around the concrete the least significant Qu-block (LSQB) information concealing algorithm for quantum image steganography is presented. Secondly, a clustering algorithm is proposed to optimize the concealment of important data. Finally, we used Con-Steg algorithm to conceal the clustered image blocks. Information concealing located on the Fourier domain of an image can achieve the security of image information, thus we further discuss the Fourier domain LSQu-block information concealing algorithm for quantum image based on Quantum Fourier Transforms. In our algorithms, the corresponding unitary Transformations are designed to realize the aim of concealing the secret information to the least significant Qu-block representing color of the quantum cover image. Finally, the procedures of extracting the secret information are illustrated. Quantum image LSQu-block image information concealing algorithm can be applied in many fields according to different needs.
NASA Astrophysics Data System (ADS)
Wang, Guangwei; Araki, Kenji
In this paper, we propose an improved SO-PMI (Semantic Orientation Using Pointwise Mutual Information) algorithm, for use in Japanese Weblog Opinion Mining. SO-PMI is an unsupervised approach proposed by Turney that has been shown to work well for English. When this algorithm was translated into Japanese naively, most phrases, whether positive or negative in meaning, received a negative SO. For dealing with this slanting phenomenon, we propose three improvements: to expand the reference words to sets of words, to introduce a balancing factor and to detect neutral expressions. In our experiments, the proposed improvements obtained a well-balanced result: both positive and negative accuracy exceeded 62%, when evaluated on 1,200 opinion sentences sampled from three different domains (reviews of Electronic Products, Cars and Travels from Kakaku. com). In a comparative experiment on the same corpus, a supervised approach (SA-Demo) achieved a very similar accuracy to our method. This shows that our proposed approach effectively adapted SO-PMI for Japanese, and it also shows the generality of SO-PMI.
A cloud detection algorithm using edge detection and information entropy over urban area
NASA Astrophysics Data System (ADS)
Zheng, Hong; Wen, Tianxiao; Li, Zhen
2013-10-01
Aiming at detecting cloud interference over urban area, an algorithm in this research is proposed to detect urban cloud area combining extracting edge information with information entropy, focusing on distinguishing complex surface features accurately to retain intact surface information. Firstly, image edge sharpening is used. Secondly, Canny edge detector and closing operation are applied to extract and strengthen edge features. Thirdly, information entropy extraction is adopted to ensure cloud positional accuracy. Compared with traditional cloud detection methods, this algorithm protects the integrity of urban surface features efficiently, improving the segmentation accuracy. Test results prove the effectiveness of this algorithm.
NASA Astrophysics Data System (ADS)
Ham, Woonchul; Song, Chulgyu; Lee, Kangsan; Roh, Seungkuk
2016-05-01
In this paper, we propose a new image reconstruction algorithm considering the geometric information of acoustic sources and senor detector and review the two-step reconstruction algorithm which was previously proposed based on the geometrical information of ROI(region of interest) considering the finite size of acoustic sensor element. In a new image reconstruction algorithm, not only mathematical analysis is very simple but also its software implementation is very easy because we don't need to use the FFT. We verify the effectiveness of the proposed reconstruction algorithm by showing the simulation results by using Matlab k-wave toolkit.
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.
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
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.
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.
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.
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.
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)
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…
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…
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
Wang, Jeen-Shing; Lin, Che-Wei; Yang, Ya-Ting C; Ho, Yu-Jen
2012-10-01
This paper presents a walking pattern classification and a walking distance estimation algorithm using gait phase information. A gait phase information retrieval algorithm was developed to analyze the duration of the phases in a gait cycle (i.e., stance, push-off, swing, and heel-strike phases). Based on the gait phase information, a decision tree based on the relations between gait phases was constructed for classifying three different walking patterns (level walking, walking upstairs, and walking downstairs). Gait phase information was also used for developing a walking distance estimation algorithm. The walking distance estimation algorithm consists of the processes of step count and step length estimation. The proposed walking pattern classification and walking distance estimation algorithm have been validated by a series of experiments. The accuracy of the proposed walking pattern classification was 98.87%, 95.45%, and 95.00% for level walking, walking upstairs, and walking downstairs, respectively. The accuracy of the proposed walking distance estimation algorithm was 96.42% over a walking distance.
2013-01-01
Background Influenza A virus (IAV) infection-induced inflammatory regulatory networks (IRNs) are extremely complex and dynamic. Specific biological experiments for investigating the interactions between individual inflammatory factors cannot provide a detailed and insightful multidimensional view of IRNs. Recently, data from high-throughput technologies have permitted system-level analyses. The construction of large and cell-specific IRNs from high-throughput data is essential to understanding the pathogenesis of IAV infection. Results In this study, we proposed a computational method, which combines nonlinear ordinary differential equation (ODE)-based optimization with mutual information, to construct a cell-specific optimized IRN during IAV infection by integrating gene expression data with a prior knowledge of network topology. Moreover, we used the average relative error and sensitivity analysis to evaluate the effectiveness of our proposed approach. Furthermore, from the optimized IRN, we confirmed 45 interactions between proteins in biological experiments and identified 37 new regulatory interactions and 8 false positive interactions, including the following interactions: IL1β regulates TLR3, TLR3 regulates IFN-β and TNF regulates IL6. Most of these regulatory interactions are statistically significant by Z-statistic. The functional annotations of the optimized IRN demonstrated clearly that the defense response, immune response, response to wounding and regulation of cytokine production are the pivotal processes of IAV-induced inflammatory response. The pathway analysis results from the Kyoto Encyclopaedia of Genes and Genomes (KEGG) showed that 8 pathways are enriched significantly. The 5 pathways were validated by experiments, and 3 other pathways, including the intestinal immune network for IgA production, the cytosolic DNA-sensing pathway and the allograft rejection pathway, are the predicted novel pathways involved in the inflammatory response
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.
Representing Uncertain Geographical Information with Algorithmic Map Caricatures
NASA Astrophysics Data System (ADS)
Brunsdon, Chris
2016-04-01
A great deal of geographical information - including the results ion data analysis - is imprecise in some way. For example the the results of geostatistical interpolation should consist not only of point estimates of the value of some quantity at points in space, but also of confidence intervals or standard errors of these estimators. Similarly, mappings of contour lines derived form such interpolations will also be characterised by uncertainty. However, most computerized cartography tools are designed to provide 'crisp' representations of geographical information, such as sharply drawn lines, or clearly delineated areas. In this talk, the use of 'fuzzy' or 'sketchy' cartographic tools will be demonstrated - where maps have a hand-drawn appearance and the degree of 'roughness' and other related characteristics can be used to convey the degree of uncertainty associated with estimated quantities being mapped. The tools used to do this are available as an R package, which will be described in the talk.
Developing Information Power Grid Based Algorithms and Software
NASA Technical Reports Server (NTRS)
Dongarra, Jack
1998-01-01
This was an exploratory study to enhance our understanding of problems involved in developing large scale applications in a heterogeneous distributed environment. It is likely that the large scale applications of the future will be built by coupling specialized computational modules together. For example, efforts now exist to couple ocean and atmospheric prediction codes to simulate a more complete climate system. These two applications differ in many respects. They have different grids, the data is in different unit systems and the algorithms for inte,-rating in time are different. In addition the code for each application is likely to have been developed on different architectures and tend to have poor performance when run on an architecture for which the code was not designed, if it runs at all. Architectural differences may also induce differences in data representation which effect precision and convergence criteria as well as data transfer issues. In order to couple such dissimilar codes some form of translation must be present. This translation should be able to handle interpolation from one grid to another as well as construction of the correct data field in the correct units from available data. Even if a code is to be developed from scratch, a modular approach will likely be followed in that standard scientific packages will be used to do the more mundane tasks such as linear algebra or Fourier transform operations. This approach allows the developers to concentrate on their science rather than becoming experts in linear algebra or signal processing. Problems associated with this development approach include difficulties associated with data extraction and translation from one module to another, module performance on different nodal architectures, and others. In addition to these data and software issues there exists operational issues such as platform stability and resource management.
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…
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.…
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.
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.
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.
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.
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.
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.
A Fuzzy Genetic Algorithm Approach to an Adaptive Information Retrieval Agent.
ERIC Educational Resources Information Center
Martin-Bautista, Maria J.; Vila, Maria-Amparo; Larsen, Henrik Legind
1999-01-01
Presents an approach to a Genetic Information Retrieval Agent Filter (GIRAF) that filters and ranks documents retrieved from the Internet according to users' preferences by using a Genetic Algorithm and fuzzy set theory to handle the imprecision of users' preferences and users' evaluation of the retrieved documents. (Author/LRW)
Technology Transfer Automated Retrieval System (TEKTRAN)
Crop canopy sensors have proven effective at determining site-specific nitrogen (N) needs, but several Midwest states use different algorithms to predict site-specific N need. The objective of this research was to determine if soil information can be used to improve the Missouri canopy sensor algori...
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.
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
NASA Astrophysics Data System (ADS)
Zhang, Chun; Fei, Shu-Min; Zhou, Xing-Peng
2012-12-01
In this paper, we explore the technology of tracking a group of targets with correlated motions in a wireless sensor network. Since a group of targets moves collectively and is restricted within a limited region, it is not worth consuming scarce resources of sensors in computing the trajectory of each single target. Hence, in this paper, the problem is modeled as tracking a geographical continuous region covered by all targets. A tracking algorithm is proposed to estimate the region covered by the target group in each sampling period. Based on the locations of sensors and the azimuthal angle of arrival (AOA) information, the estimated region covering all the group members is obtained. Algorithm analysis provides the fundamental limits to the accuracy of localizing a target group. Simulation results show that the proposed algorithm is superior to the existing hull algorithm due to the reduction in estimation error, which is between 10% and 40% of the hull algorithm, with a similar density of sensors. And when the density of sensors increases, the localization accuracy of the proposed algorithm improves dramatically.
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%.
Cheaters in mutualism networks.
Genini, Julieta; Morellato, L Patrícia C; Guimarães, Paulo R; Olesen, Jens M
2010-08-23
Mutualism-network studies assume that all interacting species are mutualistic partners and consider that all links are of one kind. However, the influence of different types of links, such as cheating links, on network organization remains unexplored. We studied two flower-visitation networks (Malpighiaceae and Bignoniaceae and their flower visitors), and divide the types of link into cheaters (i.e. robbers and thieves of flower rewards) and effective pollinators. We investigated if there were topological differences among networks with and without cheaters, especially with respect to nestedness and modularity. The Malpighiaceae network was nested, but not modular, and it was dominated by pollinators and had much fewer cheater species than Bignoniaceae network (28% versus 75%). The Bignoniaceae network was mainly a plant-cheater network, being modular because of the presence of pollen robbers and showing no nestedness. In the Malpighiaceae network, removal of cheaters had no major consequences for topology. In contrast, removal of cheaters broke down the modularity of the Bignoniaceae network. As cheaters are ubiquitous in all mutualisms, the results presented here show that they have a strong impact upon network topology.
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.
Calculating partial expected value of perfect information via Monte Carlo sampling algorithms.
Brennan, Alan; Kharroubi, Samer; O'hagan, Anthony; Chilcott, Jim
2007-01-01
Partial expected value of perfect information (EVPI) calculations can quantify the value of learning about particular subsets of uncertain parameters in decision models. Published case studies have used different computational approaches. This article examines the computation of partial EVPI estimates via Monte Carlo sampling algorithms. The mathematical definition shows 2 nested expectations, which must be evaluated separately because of the need to compute a maximum between them. A generalized Monte Carlo sampling algorithm uses nested simulation with an outer loop to sample parameters of interest and, conditional upon these, an inner loop to sample remaining uncertain parameters. Alternative computation methods and shortcut algorithms are discussed and mathematical conditions for their use considered. Maxima of Monte Carlo estimates of expectations are biased upward, and the authors show that the use of small samples results in biased EVPI estimates. Three case studies illustrate 1) the bias due to maximization and also the inaccuracy of shortcut algorithms 2) when correlated variables are present and 3) when there is nonlinearity in net benefit functions. If relatively small correlation or nonlinearity is present, then the shortcut algorithm can be substantially inaccurate. Empirical investigation of the numbers of Monte Carlo samples suggests that fewer samples on the outer level and more on the inner level could be efficient and that relatively small numbers of samples can sometimes be used. Several remaining areas for methodological development are set out. A wider application of partial EVPI is recommended both for greater understanding of decision uncertainty and for analyzing research priorities. PMID:17761960
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
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.
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.
Bagos, Pantelis G; Liakopoulos, Theodore D; Hamodrakas, Stavros J
2006-01-01
Background Hidden Markov Models (HMMs) have been extensively used in computational molecular biology, for modelling protein and nucleic acid sequences. In many applications, such as transmembrane protein topology prediction, the incorporation of limited amount of information regarding the topology, arising from biochemical experiments, has been proved a very useful strategy that increased remarkably the performance of even the top-scoring methods. However, no clear and formal explanation of the algorithms that retains the probabilistic interpretation of the models has been presented so far in the literature. Results We present here, a simple method that allows incorporation of prior topological information concerning the sequences at hand, while at the same time the HMMs retain their full probabilistic interpretation in terms of conditional probabilities. We present modifications to the standard Forward and Backward algorithms of HMMs and we also show explicitly, how reliable predictions may arise by these modifications, using all the algorithms currently available for decoding HMMs. A similar procedure may be used in the training procedure, aiming at optimizing the labels of the HMM's classes, especially in cases such as transmembrane proteins where the labels of the membrane-spanning segments are inherently misplaced. We present an application of this approach developing a method to predict the transmembrane regions of alpha-helical membrane proteins, trained on crystallographically solved data. We show that this method compares well against already established algorithms presented in the literature, and it is extremely useful in practical applications. Conclusion The algorithms presented here, are easily implemented in any kind of a Hidden Markov Model, whereas the prediction method (HMM-TM) is freely available for academic users at , offering the most advanced decoding options currently available. PMID:16597327
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.
NASA Astrophysics Data System (ADS)
Jiang, Zhuo; Xie, Chengjun
2013-12-01
This paper improved the algorithm of reversible integer linear transform on finite interval [0,255], which can realize reversible integer linear transform in whole number axis shielding data LSB (least significant bit). Firstly, this method use integer wavelet transformation based on lifting scheme to transform the original image, and select the transformed high frequency areas as information hiding area, meanwhile transform the high frequency coefficients blocks in integer linear way and embed the secret information in LSB of each coefficient, then information hiding by embedding the opposite steps. To extract data bits and recover the host image, a similar reverse procedure can be conducted, and the original host image can be lossless recovered. The simulation experimental results show that this method has good secrecy and concealment, after conducted the CDF (m, n) and DD (m, n) series of wavelet transformed. This method can be applied to information security domain, such as medicine, law and military.
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.
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
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.
Code of Federal Regulations, 2013 CFR
2013-04-01
... Companies § 1.831-3 Tax on insurance companies (other than life or mutual), mutual marine insurance... 26 Internal Revenue 8 2013-04-01 2013-04-01 false Tax on insurance companies (other than life or mutual), mutual marine insurance companies, mutual fire insurance companies issuing perpetual...
Code of Federal Regulations, 2012 CFR
2012-04-01
... Companies § 1.831-3 Tax on insurance companies (other than life or mutual), mutual marine insurance... 26 Internal Revenue 8 2012-04-01 2012-04-01 false Tax on insurance companies (other than life or mutual), mutual marine insurance companies, mutual fire insurance companies issuing perpetual...
Code of Federal Regulations, 2014 CFR
2014-04-01
... Companies § 1.831-3 Tax on insurance companies (other than life or mutual), mutual marine insurance... 26 Internal Revenue 8 2014-04-01 2014-04-01 false Tax on insurance companies (other than life or mutual), mutual marine insurance companies, mutual fire insurance companies issuing perpetual...
Code of Federal Regulations, 2011 CFR
2011-04-01
... Companies § 1.831-3 Tax on insurance companies (other than life or mutual), mutual marine insurance... 26 Internal Revenue 8 2011-04-01 2011-04-01 false Tax on insurance companies (other than life or mutual), mutual marine insurance companies, mutual fire insurance companies issuing perpetual...
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 mutual), mutual marine insurance companies, mutual fire insurance companies issuing perpetual policies...-3 Tax on insurance companies (other than life or mutual), mutual marine insurance companies,...
[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
[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.
NASA Astrophysics Data System (ADS)
Ayazi, S. M.; Mashhorroudi, M. F.; Ghorbani, M.
2014-10-01
Among the main issues in the theory of geometric grids on spatial information systems, is the problem of finding the shortest path routing between two points. In this paper tried to using the graph theory and A* algorithms in transport management, the optimal method to find the shortest path with shortest time condition to be reviewed. In order to construct a graph that consists of a network of pathways and modelling of physical and phasing area, the shortest path routes, elected with the use of the algorithm is modified A*.At of the proposed method node selection Examining angle nodes the desired destination node and the next node is done. The advantage of this method is that due to the elimination of some routes, time of route calculation is reduced.
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
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…
Implant positioning system using mutual inductance.
Zou, You; O'Driscoll, Stephen
2012-01-01
Surgical placement of implantable medical devices (IMDs) has limited precision and post-implantation the device can move over time. Accurate knowledge of the position of IMDs allows better interpretation of data gathered by the devices and may allow wireless power to be focused on the IMD thereby increasing power transfer efficiency. Existing positioning methods require device sizes and/or power consumptions which exceed the limits of in-vivo mm-sized IMDs applications. This paper describes a novel implant positioning system which replaces the external transmitting (TX) coil of a wireless power transfer link by an array of smaller coils, measures the mutual inductance between each coil in the TX array and the implanted receiving (RX) coil, and uses the spatial variation in those mutual inductances to estimate the location of the implanted device. This method does not increase the hardware or power consumption in the IMD. Mathematical analysis and electromagnetic simulations are presented which explain the theory underlying this scheme and show its feasibility. A particle swarm based algorithm is used to estimate the position of the RX coil from the measured mutual inductance values. MATLAB simulations show the positioning estimation accuracy on the order of 1 mm.
An information-bearing seed for nucleating algorithmic self-assembly.
Barish, Robert D; Schulman, Rebecca; Rothemund, Paul W K; Winfree, Erik
2009-04-14
Self-assembly creates natural mineral, chemical, and biological structures of great complexity. Often, the same starting materials have the potential to form an infinite variety of distinct structures; information in a seed molecule can determine which form is grown as well as where and when. These phenomena can be exploited to program the growth of complex supramolecular structures, as demonstrated by the algorithmic self-assembly of DNA tiles. However, the lack of effective seeds has limited the reliability and yield of algorithmic crystals. Here, we present a programmable DNA origami seed that can display up to 32 distinct binding sites and demonstrate the use of seeds to nucleate three types of algorithmic crystals. In the simplest case, the starting materials are a set of tiles that can form crystalline ribbons of any width; the seed directs assembly of a chosen width with >90% yield. Increased structural diversity is obtained by using tiles that copy a binary string from layer to layer; the seed specifies the initial string and triggers growth under near-optimal conditions where the bit copying error rate is <0.2%. Increased structural complexity is achieved by using tiles that generate a binary counting pattern; the seed specifies the initial value for the counter. Self-assembly proceeds in a one-pot annealing reaction involving up to 300 DNA strands containing >17 kb of sequence information. In sum, this work demonstrates how DNA origami seeds enable the easy, high-yield, low-error-rate growth of algorithmic crystals as a route toward programmable bottom-up fabrication.
An algorithmic and information-theoretic approach to multimetric index construction
Schoolmaster, Donald R.; Grace, James B.; Schweiger, E. William; Guntenspergen, Glenn R.; Mitchell, Brian R.; Miller, Kathryn M.; Little, Amanda M.
2013-01-01
The use of multimetric indices (MMIs), such as the widely used index of biological integrity (IBI), to measure, track, summarize and infer the overall impact of human disturbance on biological communities has been steadily growing in recent years. Initially, MMIs were developed for aquatic communities using pre-selected biological metrics as indicators of system integrity. As interest in these bioassessment tools has grown, so have the types of biological systems to which they are applied. For many ecosystem types the appropriate biological metrics to use as measures of biological integrity are not known a priori. As a result, a variety of ad hoc protocols for selecting metrics empirically has developed. However, the assumptions made by proposed protocols have not be explicitly described or justified, causing many investigators to call for a clear, repeatable methodology for developing empirically derived metrics and indices that can be applied to any biological system. An issue of particular importance that has not been sufficiently addressed is the way that individual metrics combine to produce an MMI that is a sensitive composite indicator of human disturbance. In this paper, we present and demonstrate an algorithm for constructing MMIs given a set of candidate metrics and a measure of human disturbance. The algorithm uses each metric to inform a candidate MMI, and then uses information-theoretic principles to select MMIs that capture the information in the multidimensional system response from among possible MMIs. Such an approach can be used to create purely empirical (data-based) MMIs or can, optionally, be influenced by expert opinion or biological theory through the use of a weighting vector to create value-weighted MMIs. We demonstrate the algorithm with simulated data to demonstrate the predictive capacity of the final MMIs and with real data from wetlands from Acadia and Rocky Mountain National Parks. For the Acadia wetland data, the algorithm identified
Scale-free properties of information flux networks in genetic algorithms
NASA Astrophysics Data System (ADS)
Wu, Jieyu; Shao, Xinyu; Li, Jinhang; Huang, Gang
2012-02-01
In this study, we present empirical analysis of statistical properties of mating networks in genetic algorithms (GAs). Under the framework of GAs, we study a class of interaction network model-information flux network (IFN), which describes the information flow among generations during evolution process. The IFNs are found to be scale-free when the selection operator uses a preferential strategy rather than a random. The topology structure of IFN is remarkably affected by operations used in genetic algorithms. The experimental results suggest that the scaling exponent of the power-law degree distribution is shown to decrease when crossover rate increases, but increase when mutation rate increases, and the reason may be that high crossover rate leads to more edges that are shared between nodes and high mutation rate leads to many individuals in a generation possessing low fitness. The magnitude of the out-degree exponent is always more than the in-degree exponent for the systems tested. These results may provide a new viewpoint with which to view GAs and guide the dissemination process of genetic information throughout a population.
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
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.
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.
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.
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
[Research on non-rigid medical image registration algorithm based on SIFT feature extraction].
Wang, Anna; Lu, Dan; Wang, Zhe; Fang, Zhizhen
2010-08-01
In allusion to non-rigid registration of medical images, the paper gives a practical feature points matching algorithm--the image registration algorithm based on the scale-invariant features transform (Scale Invariant Feature Transform, SIFT). The algorithm makes use of the image features of translation, rotation and affine transformation invariance in scale space to extract the image feature points. Bidirectional matching algorithm is chosen to establish the matching relations between the images, so the accuracy of image registrations is improved. On this basis, affine transform is chosen to complement the non-rigid registration, and normalized mutual information measure and PSO optimization algorithm are also chosen to optimize the registration process. The experimental results show that the method can achieve better registration results than the method based on mutual information.
Mutual Mentoring Makes Better Mentors
NASA Astrophysics Data System (ADS)
Blaha, Cindy; Bug, Amy; Cox, Anne; Fritz, Linda; Whitten, Barbara
2011-03-01
In this talk we discuss one of the impacts of an NSF ADVANCE sponsored horizontal, mutual mentoring alliance. Our cohort of five women physicists at liberal arts colleges has found that mutual mentoring has had a profound impact on many aspects of our professional lives. In this talk we will describe how our peer-to-peer mentoring has enabled us to become better mentors for our undergraduate students, for recent graduates beginning their careers and for colleagues at local and neighboring institutions.
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.
Breska, Assaf; Ben-Shakhar, Gershon; Gronau, Nurit
2012-09-01
We examined whether the Concealed Information Test (CIT) may be used when the critical details are unavailable to investigators (the Searching CIT [SCIT]). This use may have important applications in criminal investigations (e.g., finding the location of a murder weapon) and in security-related threats (e.g., detecting individuals and groups suspected in planning a terror attack). Two classes of algorithms designed to detect the critical items and classify individuals in the SCIT were examined. The 1st class was based on averaging responses across subjects to identify critical items and on averaging responses across the identified critical items to identify knowledgeable subjects. The 2nd class used clustering methods based on the correlations between the response profiles of all subject pairs. We applied a principal component analysis to decompose the correlation matrix into its principal components and defined the detection score as the coefficient of each subject on the component that explained the largest portion of the variance. Reanalysis of 3 data sets from previous CIT studies demonstrated that in most cases the efficiency of differentiation between knowledgeable and unknowledgeable subjects in the SCIT (indexed by the area under the receiver operating characteristic curve) approached that of the standard CIT for both algorithms. We also examined the robustness of our results to variations in the number of knowledgeable and unknowledgeable subjects in the sample. This analysis demonstrated that the performance of our algorithms is relatively robust to changes in the number of individuals examined in each group, provided that at least 2 (but desirably 5 or more) knowledgeable examinees are included.
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
Information geometric algorithm for estimating switching probabilities in space-varying HMM.
Nascimento, Jacinto C; Barão, Miguel; Marques, Jorge S; Lemos, João M
2014-12-01
This paper proposes an iterative natural gradient algorithm to perform the optimization of switching probabilities in a space-varying hidden Markov model, in the context of human activity recognition in long-range surveillance. The proposed method is a version of the gradient method, developed under an information geometric viewpoint, where the usual Euclidean metric is replaced by a Riemannian metric on the space of transition probabilities. It is shown that the change in metric provides advantages over more traditional approaches, namely: 1) it turns the original constrained optimization into an unconstrained optimization problem; 2) the optimization behaves asymptotically as a Newton method and yields faster convergence than other methods for the same computational complexity; and 3) the natural gradient vector is an actual contravariant vector on the space of probability distributions for which an interpretation as the steepest descent direction is formally correct. Experiments on synthetic and real-world problems, focused on human activity recognition in long-range surveillance settings, show that the proposed methodology compares favorably with the state-of-the-art algorithms developed for the same purpose.
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.
Algorithms for deriving crystallographic space-group information. II: Treatment of special positions
Grosse-Kunstleve, Ralf W.; Adams, Paul D.
2001-10-05
Algorithms for the treatment of special positions in 3-dimensional crystallographic space groups are presented. These include an algorithm for the determination of the site-symmetry group given the coordinates of a point, an algorithm for the determination of the exact location of the nearest special position, an algorithm for the assignment of a Wyckoff letter given the site-symmetry group, and an alternative algorithm for the assignment of a Wyckoff letter given the coordinates of a point directly. All algorithms are implemented in ISO C++ and are integrated into the Computational Crystallography Toolbox. The source code is freely available.
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
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.
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.
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
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…
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.
DRAMMS: deformable registration via attribute matching and mutual-saliency weighting.
Ou, Yangming; Davatzikos, Christos
2009-01-01
A general-purpose deformable registration algorithm referred to as "DRAMMS" is presented in this paper. DRAMMS adds to the literature of registration methods that bridge between the traditional voxel-wise methods and landmark/feature-based methods. In particular, DRAMMS extracts Gabor attributes at each voxel and selects the optimal components, so that they form a highly distinctive morphological signature reflecting the anatomical context around each voxel in a multi-scale and multi-resolution fashion. Compared with intensity or mutual-information based methods, the high-dimensional optimal Gabor attributes render different anatomical regions relatively distinctively identifiable and therefore help establish more accurate and reliable correspondence. Moreover, the optimal Gabor attribute vector is constructed in a way that generalizes well, i.e., it can be applied to different registration tasks, regardless of the image contents under registration. A second characteristic of DRAMMS is that it is based on a cost function that weights different voxel pairs according to a metric referred to as "mutual-saliency", which reflects the uniqueness (reliability) of anatomical correspondences implied by the tentative transformation. As a result, image voxels do not contribute equally to the optimization process, as in most voxel-wise methods, or in a binary selection fashion, as in most landmark/feature-based methods. Instead, they contribute according to a continuously-valued mutual-saliency map, which is dynamically updated during the algorithm's evolution. The general applicability and accuracy of DRAMMS are demonstrated by experiments in simulated images, inter-subject images, single-/multi-modality images, and longitudinal images, from human and mouse brains, breast, heart, and prostate.
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
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
2015-05-05
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.
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
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.
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
Benefit and cost curves for typical pollination mutualisms.
Morris, William F; Vázquez, Diego P; Chacoff, Natacha P
2010-05-01
Mutualisms provide benefits to interacting species, but they also involve costs. If costs come to exceed benefits as population density or the frequency of encounters between species increases, the interaction will no longer be mutualistic. Thus curves that represent benefits and costs as functions of interaction frequency are important tools for predicting when a mutualism will tip over into antagonism. Currently, most of what we know about benefit and cost curves in pollination mutualisms comes from highly specialized pollinating seed-consumer mutualisms, such as the yucca moth-yucca interaction. There, benefits to female reproduction saturate as the number of visits to a flower increases (because the amount of pollen needed to fertilize all the flower's ovules is finite), but costs continue to increase (because pollinator offspring consume developing seeds), leading to a peak in seed production at an intermediate number of visits. But for most plant-pollinator mutualisms, costs to the plant are more subtle than consumption of seeds, and how such costs scale with interaction frequency remains largely unknown. Here, we present reasonable benefit and cost curves that are appropriate for typical pollinator-plant interactions, and we show how they can result in a wide diversity of relationships between net benefit (benefit minus cost) and interaction frequency. We then use maximum-likelihood methods to fit net-benefit curves to measures of female reproductive success for three typical pollination mutualisms from two continents, and for each system we chose the most parsimonious model using information-criterion statistics. We discuss the implications of the shape of the net-benefit curve for the ecology and evolution of plant-pollinator mutualisms, as well as the challenges that lie ahead for disentangling the underlying benefit and cost curves for typical pollination mutualisms.
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…
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.
NASA Astrophysics Data System (ADS)
Bamber, D.; Goodman, I. R.; Torrez, William C.; Nguyen, H. T.
2001-08-01
Conditional probability logics (CPL's), such as Adams', while producing many satisfactory results, do not agree with commonsense reasoning for a number of key entailment schemes, including transitivity and contraposition. Also, CPL's and bayesian techniques, often: (1) use restrictive independence/simplification assumptions; (2) lack a rationale behind choice of prior distribution; (3) require highly complex implementation calculations; (4) introduce ad hoc techniques. To address the above difficulties, a new CPL is being developed: CRANOF - Complexity Reducing Algorithm for Near Optimal Fusion -based upon three factors: (i) second order probability logic (SOPL), i.e., probability of probabilities within a bayesian framework; (ii) justified use of Dirichlet family priors, based on an extension of Lukacs' characterization theorem; and (iii) replacement of the theoretical optimal solution by a near optimal one where the complexity of computations is reduced significantly. A fundamental application of CRANOF to correlation and tracking is provided here through a generic example in a form similar to transitivity: two track histories are to be merged or left alone, based upon observed kinematic and non-kinematic attribute information and conditional probabilities connecting the observed data to the degrees of matching of attributes, as well as relating the matching of prescribed groups of attributes from each track history to the correlation level between the histories.
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
Enhancing a diffusion algorithm for 4D image segmentation using local information
NASA Astrophysics Data System (ADS)
Lösel, Philipp; Heuveline, Vincent
2016-03-01
Inspired by the diffusion of a particle, we present a novel approach for performing a semiautomatic segmentation of tomographic images in 3D, 4D or higher dimensions to meet the requirements of high-throughput measurements in a synchrotron X-ray microtomograph. Given a small number of 2D-slices with at least two manually labeled segments, one can either analytically determine the probability that an intelligently weighted random walk starting at one labeled pixel will be at a certain time at a specific position in the dataset or determine the probability approximately by performing several random walks. While the weights of a random walk take into account local information at the starting point, the random walk itself can be in any dimension. Starting a great number of random walks in each labeled pixel, a voxel in the dataset will be hit by several random walks over time. Hence, the image can be segmented by assigning each voxel to the label where the random walks most likely started from. Due to the high scalability of random walks, this approach is suitable for high throughput measurements. Additionally, we describe an interactively adjusted active contours slice by slice method considering local information, where we start with one manually labeled slice and move forward in any direction. This approach is superior with respect to accuracy towards the diffusion algorithm but inferior in the amount of tedious manual processing steps. The methods were applied on 3D and 4D datasets and evaluated by means of manually labeled images obtained in a realistic scenario with biologists.
Mutuality in the provision of Scottish healthcare.
Howieson, Brian
2015-11-01
The backdrop to this article is provided by the Better Health, Better Care Action Plan (Scottish Government, 2007), Section 1 of which is entitled 'Towards a Mutual NHS'. According to Better Health, Better Care (Scottish Government, 2007: 5): 'Mutual organisations are designed to serve their members. They are designed to gather people around a common sense of purpose. They are designed to bring the organisation together in what people often call "co-production."' The aim of this article is to précis the current knowledge of mutuality in the provision of Scottish healthcare. In detail, it will: introduce the 'mutual' organisation; offer a historical perspective of mutuality; suggest why healthcare mutuality is important; and briefly, detail the differences in mutual health-care policy in England and Scotland. It is hoped that this analysis will help researchers and practitioners alike appreciate further the philosophy of mutuality in the provision of Scottish healthcare.
NASA Technical Reports Server (NTRS)
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.
Mutual coupling between rectangular microstrip patch antennas
NASA Technical Reports Server (NTRS)
Huynh, Tan; Lee, Kai-Fong; Chebolu, Siva R.; Lee, R. Q.
1992-01-01
The paper presents a comprehensive study of the mutual coupling between two rectangular microstrip patch antennas. The cavity model is employed to give numerical results for both mutual impedance and mutual coupling parameters for the E-plane, H-plane, diagonal, and perpendicular orientations. The effects of substrate thickness, substrate permittivity, and feed positions are discussed.
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...
76 FR 36625 - Mutual Holding Company
Federal Register 2010, 2011, 2012, 2013, 2014
2011-06-22
... Office of Thrift Supervision Mutual Holding Company AGENCY: Office of Thrift Supervision (OTS), Treasury... collection. Title of Proposal: Mutual Holding Company. OMB Number: 1550-0072. Form Numbers: MHC-1 (OTS Form... whether the applicant meets the statutory and regulatory criteria to form a mutual holding company...
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/ .
76 FR 20459 - Mutual to Stock Conversion Application
Federal Register 2010, 2011, 2012, 2013, 2014
2011-04-12
... Office of Thrift Supervision Mutual to Stock Conversion Application AGENCY: Office of Thrift Supervision... part of its continuing effort to reduce paperwork and respondent burden, invites the general public and other Federal agencies to comment on proposed and continuing information collections, as required by...
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…
Information-Theoretic Dictionary Learning for Image Classification.
Qiu, Qiang; Patel, Vishal M; Chellappa, Rama
2014-11-01
We present a two-stage approach for learning dictionaries for object classification tasks based on the principle of information maximization. The proposed method seeks a dictionary that is compact, discriminative, and generative. In the first stage, dictionary atoms are selected from an initial dictionary by maximizing the mutual information measure on dictionary compactness, discrimination and reconstruction. In the second stage, the selected dictionary atoms are updated for improved reconstructive and discriminative power using a simple gradient ascent algorithm on mutual information. Experiments using real data sets demonstrate the effectiveness of our approach for image classification tasks.
NASA Astrophysics Data System (ADS)
Gao, Min; Huang, Shutao; Zhong, Xia
2010-11-01
The establishment of multi-source database was designed to promote the informatics process of the geological disposal of High-level Radioactive Waste, the integration of multi-dimensional and multi-source information and its application are related to computer software and hardware. Based on the analysis of data resources in Beishan area, Gansu Province, and combined with GIS technologies and methods. This paper discusses the technical ideas of how to manage, fully share and rapidly retrieval the information resources in this area by using open source code GDAL and Quadtree algorithm, especially in terms of the characteristics of existing data resources, spatial data retrieval algorithm theory, programming design and implementation of the ideas.
NASA Astrophysics Data System (ADS)
Gao, Min; Huang, Shutao; Zhong, Xia
2009-09-01
The establishment of multi-source database was designed to promote the informatics process of the geological disposal of High-level Radioactive Waste, the integration of multi-dimensional and multi-source information and its application are related to computer software and hardware. Based on the analysis of data resources in Beishan area, Gansu Province, and combined with GIS technologies and methods. This paper discusses the technical ideas of how to manage, fully share and rapidly retrieval the information resources in this area by using open source code GDAL and Quadtree algorithm, especially in terms of the characteristics of existing data resources, spatial data retrieval algorithm theory, programming design and implementation of the ideas.
Mutual aid agreements: essential legal tools for public health preparedness and response.
Stier, Daniel D; Goodman, Richard A
2007-04-01
Mutual aid is the sharing of supplies, equipment, personnel, and information across political boundaries. States must have agreements in place to ensure mutual aid to facilitate effective responses to public health emergencies and to detect and control potential infectious disease outbreaks. The 2005 hurricanes triggered activation of the Emergency Management Assistance Compact (EMAC), a mutual aid agreement among the 50 states, the District of Columbia, Puerto Rico, and the US Virgin Islands. Although EMAC facilitated the movement of an unprecedented amount of mutual aid to disaster areas, inadequacies in the response demonstrated a need for improvement. Mutual aid may also be beneficial in circumstances where EMAC is not activated. We discuss the importance of mutual aid, examine obstacles, and identify legal "gaps" that must be filled to strengthen preparedness.
NASA Astrophysics Data System (ADS)
Naser, Mohamed A.; Pekar, Julius; Patterson, Michael S.
2011-02-01
An algorithm to solve the diffuse optical tomography (DOT) problem is described which uses the anatomical information from x-ray CT images. These provide a priori information about the distribution of the optical properties hence reducing the number of variables and permitting a unique solution to the ill-posed problem. The light fluence rate at the boundary is written as a Taylor series expansion around an initial guess corresponding to an optically homogenous object. The second order approximation is considered and the derivatives are calculated by direct methods. These are used in an iterative algorithm to reconstruct the tissue optical properties. The reconstructed optical properties are then used for bioluminescence tomography where a minimization problem is formed based on the L1 norm objective function which uses normalized values for the light fluence rates and the corresponding Green's functions. Then an iterative minimization solution shrinks the permissible regions where the sources are allowed by selecting points with higher probability to contribute to the source distribution. Throughout this process the permissible region shrinks from the entire object to just a few points. The optimum reconstructed bioluminescence distributions are chosen to be the results of the iteration corresponding to the permissible region where the objective function has its global minimum. This provides efficient BLT reconstruction algorithms without the need for a priori information about the bioluminescence sources.
Cross-language opinion lexicon extraction using mutual-reinforcement label propagation.
Lin, Zheng; Tan, Songbo; Liu, Yue; Cheng, Xueqi; Xu, Xueke
2013-01-01
There is a growing interest in automatically building opinion lexicon from sources such as product reviews. Most of these methods depend on abundant external resources such as WordNet, which limits the applicability of these methods. Unsupervised or semi-supervised learning provides an optional solution to multilingual opinion lexicon extraction. However, the datasets are imbalanced in different languages. For some languages, the high-quality corpora are scarce or hard to obtain, which limits the research progress. To solve the above problems, we explore a mutual-reinforcement label propagation framework. First, for each language, a label propagation algorithm is applied to a word relation graph, and then a bilingual dictionary is used as a bridge to transfer information between two languages. A key advantage of this model is its ability to make two languages learn from each other and boost each other. The experimental results show that the proposed approach outperforms baseline significantly.
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.
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
NASA Technical Reports Server (NTRS)
Kummerow, Christian; Giglio, Louis
1994-01-01
This paper describes a multichannel physical approach for retrieving rainfall and vertical structure information from satellite-based passive microwave observations. The algorithm makes use of statistical inversion techniques based upon theoretically calculated relations between rainfall rates and brightness temperatures. Potential errors introduced into the theoretical calculations by the unknown vertical distribution of hydrometeors are overcome by explicity accounting for diverse hydrometeor profiles. This is accomplished by allowing for a number of different vertical distributions in the theoretical brightness temperature calculations and requiring consistency between the observed and calculated brightness temperatures. This paper will focus primarily on the theoretical aspects of the retrieval algorithm, which includes a procedure used to account for inhomogeneities of the rainfall within the satellite field of view as well as a detailed description of the algorithm as it is applied over both ocean and land surfaces. The residual error between observed and calculated brightness temperatures is found to be an important quantity in assessing the uniqueness of the solution. It is further found that the residual error is a meaningful quantity that can be used to derive expected accuracies from this retrieval technique. Examples comparing the retrieved results as well as the detailed analysis of the algorithm performance under various circumstances are the subject of a companion paper.
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…
Code of Federal Regulations, 2012 CFR
2012-04-01
... insurance companies (other than life or mutual), mutual marine insurance companies, and mutual fire... 26 Internal Revenue 8 2012-04-01 2012-04-01 false Tax on insurance companies (other than life or mutual), mutual marine insurance companies, and mutual fire insurance companies issuing...
Code of Federal Regulations, 2013 CFR
2013-04-01
... insurance companies (other than life or mutual), mutual marine insurance companies, and mutual fire... 26 Internal Revenue 8 2013-04-01 2013-04-01 false Tax on insurance companies (other than life or mutual), mutual marine insurance companies, and mutual fire insurance companies issuing...
Code of Federal Regulations, 2011 CFR
2011-04-01
... insurance companies (other than life or mutual), mutual marine insurance companies, and mutual fire... 26 Internal Revenue 8 2011-04-01 2011-04-01 false Tax on insurance companies (other than life or mutual), mutual marine insurance companies, and mutual fire insurance companies issuing...
Construction of bacteria-eukaryote synthetic mutualism.
Kubo, Isao; Hosoda, Kazufumi; Suzuki, Shingo; Yamamoto, Kayo; Kihara, Kumiko; Mori, Kotaro; Yomo, Tetsuya
2013-08-01
Mutualism is ubiquitous in nature but is known to be intrinsically vulnerable with regard to both population dynamics and evolution. Synthetic ecology has indicated that it is feasible for organisms to establish novel mutualism merely through encountering each other by showing that it is feasible to construct synthetic mutualism between organisms. However, bacteria-eukaryote mutualism, which is ecologically important, has not yet been constructed. In this study, we synthetically constructed mutualism between a bacterium and a eukaryote by using two model organisms. We mixed a bacterium, Escherichia coli (a genetically engineered glutamine auxotroph), and an amoeba, Dictyostelium discoideum, in 14 sets of conditions in which each species could not grow in monoculture but potentially could grow in coculture. Under a single condition in which the bacterium and amoeba mutually compensated for the lack of required nutrients (lipoic acid and glutamine, respectively), both species grew continuously through several subcultures, essentially establishing mutualism. Our results shed light on the establishment of bacteria-eukaryote mutualism and indicate that a bacterium and eukaryote pair in nature also has a non-negligible possibility of establishing novel mutualism if the organisms are potentially mutualistic. PMID:23711432
Cloud classification from satellite data using a fuzzy sets algorithm: A polar example
NASA Technical Reports Server (NTRS)
Key, J. R.; Maslanik, J. A.; Barry, R. G.
1988-01-01
Where spatial boundaries between phenomena are diffuse, classification methods which construct mutually exclusive clusters seem inappropriate. The Fuzzy c-means (FCM) algorithm assigns each observation to all clusters, with membership values as a function of distance to the cluster center. The FCM algorithm is applied to AVHRR data for the purpose of classifying polar clouds and surfaces. Careful analysis of the fuzzy sets can provide information on which spectral channels are best suited to the classification of particular features, and can help determine likely areas of misclassification. General agreement in the resulting classes and cloud fraction was found between the FCM algorithm, a manual classification, and an unsupervised maximum likelihood classifier.
Cloud classification from satellite data using a fuzzy sets algorithm - A polar example
NASA Technical Reports Server (NTRS)
Key, J. R.; Maslanik, J. A.; Barry, R. G.
1989-01-01
Where spatial boundaries between phenomena are diffuse, classification methods which construct mutually exclusive clusters seem inappropriate. The Fuzzy c-means (FCM) algorithm assigns each observation to all clusters, with membership values as a function of distance to the cluster center. The FCM algorithm is applied to AVHRR data for the purpose of classifying polar clouds and surfaces. Careful analysis of the fuzzy sets can provide information on which spectral channels are best suited to the classification of particular features, and can help determine like areas of misclassification. General agreement in the resulting classes and cloud fraction was found between the FCM algorithm, a manual classification, and an unsupervised maximum likelihood classifier.
Mutual Event of Transneptunian Binary (79360) Sila-Nunam
NASA Astrophysics Data System (ADS)
Verbiscer, Anne; Grundy, Will; Benecchi, Susan; Rabinowitz, David
2013-02-01
The transneptunian binary (79360) Sila-Nunam (provisionally designated 1997 CS29) is currently undergoing mutual events in which the two nearly-equal brightness components alternate in eclipsing and occulting each other as seen from Earth (Grundy et al. 2012, Verbiscer et al. 2012a). The low eccentricity of the orbit, determined from Hubble Space Telescope observations of the resolved components (Grundy et al. 2012), and the coincidence of the system's photometric lightcurve and orbital period are consistent with a system that is tidally locked and synchronized, like that of Pluto-Charon. Mutual events provide a rich opportunity to learn about size, shape, color, and albedo patterns on the system components. Mutual events of Pluto-Charon observed between 1985-1990 provided the first characterization of their albedo distributions. The duration of the mutual event season depends on the size and separation of the system components. Using sizes determined from thermal observations, the mutual event season for Sila-Nunam should last about a decade; however, the deepest, most central (and thus most informative) events are predicted to be observable in the 2013 apparition, with progressively shallower events observable thereafter for the next 4-5 years. Gemini-North is ideally located to observe a complete mutual event of Sila-Nunam which begins at 5:59 UT on 14 February 2013 and ends at 14:17. Since Sila-Nunam will be near opposition, the target is visible to GMOS for the entire night. This event is a rare opportunity to determine the size, density, and albedo/color patterns on a primitive body which has likely been unaltered since the time of Solar System formation.
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…
Bright Lights and Questions: Using Mutual Interrogation
ERIC Educational Resources Information Center
Adam, Aishikin; Alangui, Willy; Barton, Bill
2010-01-01
Mutual Interrogation is a research methodology for ethnomathematics proposed by Alangui in 2006 in an attempt to avoid the potential inequality set up when a restricted cultural practice is viewed through the lens of the near-universal and highly developed research domain of mathematics. Using three significant examples of mutual interrogation in…
Economic contract theory tests models of mutualism
Weyl, E. Glen; Frederickson, Megan E.; Yu, Douglas W.; Pierce, Naomi E.
2010-01-01
Although mutualisms are common in all ecological communities and have played key roles in the diversification of life, our current understanding of the evolution of cooperation applies mostly to social behavior within a species. A central question is whether mutualisms persist because hosts have evolved costly punishment of cheaters. Here, we use the economic theory of employment contracts to formulate and distinguish between two mechanisms that have been proposed to prevent cheating in host–symbiont mutualisms, partner fidelity feedback (PFF) and host sanctions (HS). Under PFF, positive feedback between host fitness and symbiont fitness is sufficient to prevent cheating; in contrast, HS posits the necessity of costly punishment to maintain mutualism. A coevolutionary model of mutualism finds that HS are unlikely to evolve de novo, and published data on legume–rhizobia and yucca–moth mutualisms are consistent with PFF and not with HS. Thus, in systems considered to be textbook cases of HS, we find poor support for the theory that hosts have evolved to punish cheating symbionts; instead, we show that even horizontally transmitted mutualisms can be stabilized via PFF. PFF theory may place previously underappreciated constraints on the evolution of mutualism and explain why punishment is far from ubiquitous in nature. PMID:20733067
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)
Economic contract theory tests models of mutualism.
Weyl, E Glen; Frederickson, Megan E; Yu, Douglas W; Pierce, Naomi E
2010-09-01
Although mutualisms are common in all ecological communities and have played key roles in the diversification of life, our current understanding of the evolution of cooperation applies mostly to social behavior within a species. A central question is whether mutualisms persist because hosts have evolved costly punishment of cheaters. Here, we use the economic theory of employment contracts to formulate and distinguish between two mechanisms that have been proposed to prevent cheating in host-symbiont mutualisms, partner fidelity feedback (PFF) and host sanctions (HS). Under PFF, positive feedback between host fitness and symbiont fitness is sufficient to prevent cheating; in contrast, HS posits the necessity of costly punishment to maintain mutualism. A coevolutionary model of mutualism finds that HS are unlikely to evolve de novo, and published data on legume-rhizobia and yucca-moth mutualisms are consistent with PFF and not with HS. Thus, in systems considered to be textbook cases of HS, we find poor support for the theory that hosts have evolved to punish cheating symbionts; instead, we show that even horizontally transmitted mutualisms can be stabilized via PFF. PFF theory may place previously underappreciated constraints on the evolution of mutualism and explain why punishment is far from ubiquitous in nature.
[A community model of mutually learning neuronal nets].
Grosberg, A Iu
1990-01-01
A model of a community is suggested whose members are formal neuron nets interacting by signals exchange. As a signal each net can emit an image formed by it when recognising the preceding signal. The emitted signal comes to the inputs of other nets and is used as their initial state for the recognition process. The collective dynamics of such model is discussed for the case of non-learning nets. Possible algorithm of mutual learning of the nets in them course of signals exchange is considered.
Tang, Mengxing; Wang, Wei; Wheeler, James; McCormick, Malcolm; Dong, Xiuzhen
2002-06-01
In electrical impedance tomography, currents are applied to the body through electrodes that are attached to the surface and the corresponding surface voltages are measured. Based on these boundary measurements, the internal admittivity distribution of the body can be reconstructed. In order to improve the image quality it is necessary and useful to apply physiologically meaningful prior information into the image reconstruction. Such prior information usually can be obtained from other sources. For example, information on the object's boundary shape and internal structure can be obtained from computed tomography and magnetic resonance imaging scan. However, this type of prior information may change from time to time and from person to person. As these changes are limited anatomically and physiologically, the prior information including the possible changes can be presented in a number of variational forms. The aim of this paper is to find which form of prior information is more compatible for a specific imaged object at the time of imaging. This paper proposes a new method for selecting the most appropriate form of prior information, through the procedure of iterative image reconstruction by using the information obtained from boundary measurements. The method is based on the principle that incompatible prior information causes errors which are able to affect the image reconstruction's convergence behavior. In this method, according to the various forms of prior information available, several image reconstruction configurations are designed. Then, through monitoring the convergence behavior in an iterative image reconstruction, the configuration with compatible prior information can be found among those different configurations. As an example, the prior information regarding the imaged object's boundary shape and internal structure was studied by computer simulation. Results were shown and discussed.
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.
Local structure information by EXAFS analysis using two algorithms for Fourier transform calculation
NASA Astrophysics Data System (ADS)
Aldea, N.; Pintea, S.; Rednic, V.; Matei, F.; Tiandou, Hu; Yaning, Xie
2009-08-01
The present work is a comparison study between different algorithms of Fourier transform for obtaining very accurate local structure results using Extended X-ray Absorption Fine Structure technique. In this paper we focus on the local structural characteristics of supported nickel catalysts and Fe3O4 core-shell nanocomposites. The radial distribution function could be efficiently calculated by the fast Fourier transform when the coordination shells are well separated while the Filon quadrature gave remarkable results for close-shell coordination.
Mutualisms and Population Regulation: Mechanism Matters
Jha, Shalene; Allen, David; Liere, Heidi; Perfecto, Ivette; Vandermeer, John
2012-01-01
For both applied and theoretical ecological science, the mutualism between ants and their hemipteran partners is iconic. In this well-studied interaction, ants are assumed to provide hemipterans protection from natural enemies in exchange for nutritive honeydew. Despite decades of research and the potential importance in pest control, the precise mechanism producing this mutualism remains contested. By analyzing maximum likelihood parameter estimates of a hemipteran population model, we show that the mechanism of the mutualism is direct, via improved hemipteran growth rates, as opposed to the frequently assumed indirect mechanism, via harassment of the specialist parasites and predators of the hemipterans. Broadly, this study demonstrates that the management of mutualism-based ecosystem services requires a mechanistic understanding of mutualistic interactions. A consequence of this finding is the counter intuitive demonstration that preserving ant participation in the ant-hemipteran mutualism may be the best way of insuring pest control. PMID:22927978
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.
2013-01-01
Background Adequate health literacy is important for people to maintain good health and manage diseases and injuries. Educational text, either retrieved from the Internet or provided by a doctor’s office, is a popular method to communicate health-related information. Unfortunately, it is difficult to write text that is easy to understand, and existing approaches, mostly the application of readability formulas, have not convincingly been shown to reduce the difficulty of text. Objective To develop an evidence-based writer support tool to improve perceived and actual text difficulty. To this end, we are developing and testing algorithms that automatically identify difficult sections in text and provide appropriate, easier alternatives; algorithms that effectively reduce text difficulty will be included in the support tool. This work describes the user evaluation with an independent writer of an automated simplification algorithm using term familiarity. Methods Term familiarity indicates how easy words are for readers and is estimated using term frequencies in the Google Web Corpus. Unfamiliar words are algorithmically identified and tagged for potential replacement. Easier alternatives consisting of synonyms, hypernyms, definitions, and semantic types are extracted from WordNet, the Unified Medical Language System (UMLS), and Wiktionary and ranked for a writer to choose from to simplify the text. We conducted a controlled user study with a representative writer who used our simplification algorithm to simplify texts. We tested the impact with representative consumers. The key independent variable of our study is lexical simplification, and we measured its effect on both perceived and actual text difficulty. Participants were recruited from Amazon’s Mechanical Turk website. Perceived difficulty was measured with 1 metric, a 5-point Likert scale. Actual difficulty was measured with 3 metrics: 5 multiple-choice questions alongside each text to measure understanding
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.
Huang, Xiaohui; Ye, Yunming; Zhang, Haijun
2014-08-01
Kmeans-type clustering aims at partitioning a data set into clusters such that the objects in a cluster are compact and the objects in different clusters are well separated. However, most kmeans-type clustering algorithms rely on only intracluster compactness while overlooking intercluster separation. In this paper, a series of new clustering algorithms by extending the existing kmeans-type algorithms is proposed by integrating both intracluster compactness and intercluster separation. First, a set of new objective functions for clustering is developed. Based on these objective functions, the corresponding updating rules for the algorithms are then derived analytically. The properties and performances of these algorithms are investigated on several synthetic and real-life data sets. Experimental studies demonstrate that our proposed algorithms outperform the state-of-the-art kmeans-type clustering algorithms with respect to four metrics: accuracy, RandIndex, Fscore, and normal mutual information.
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
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...
Entropic uncertainty relations and locking: Tight bounds for mutually unbiased bases
Ballester, Manuel A.; Wehner, Stephanie
2007-02-15
We prove tight entropic uncertainty relations for a large number of mutually unbiased measurements. In particular, we show that a bound derived from the result by Maassen and Uffink [Phys. Rev. Lett. 60, 1103 (1988)] for two such measurements can in fact be tight for up to {radical}(d) measurements in mutually unbiased bases. We then show that using more mutually unbiased bases does not always lead to a better locking effect. We prove that the optimal bound for the accessible information using up to {radical}(d) specific mutually unbiased bases is log d/2, which is the same as can be achieved by using only two bases. Our result indicates that merely using mutually unbiased bases is not sufficient to achieve a strong locking effect and we need to look for additional properties.
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.
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.
The evolution of plant-insect mutualisms.
Bronstein, Judith L; Alarcón, Ruben; Geber, Monica
2006-01-01
Mutualisms (cooperative interactions between species) have had a central role in the generation and maintenance of life on earth. Insects and plants are involved in diverse forms of mutualism. Here we review evolutionary features of three prominent insect-plant mutualisms: pollination, protection and seed dispersal. We focus on addressing five central phenomena: evolutionary origins and maintenance of mutualism; the evolution of mutualistic traits; the evolution of specialization and generalization; coevolutionary processes; and the existence of cheating. Several features uniting very diverse insect-plant mutualisms are identified and their evolutionary implications are discussed: the involvement of one mobile and one sedentary partner; natural selection on plant rewards; the existence of a continuum from specialization to generalization; and the ubiquity of cheating, particularly on the part of insects. Plant-insect mutualisms have apparently both arisen and been lost repeatedly. Many adaptive hypotheses have been proposed to explain these transitions, and it is unlikely that any one of them dominates across interactions differing so widely in natural history. Evolutionary theory has a potentially important, but as yet largely unfilled, role to play in explaining the origins, maintenance, breakdown and evolution of insect-plant mutualisms.
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.
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.
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…
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...
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
Economic game theory for mutualism and cooperation.
Archetti, Marco; Scheuring, István; Hoffman, Moshe; Frederickson, Megan E; Pierce, Naomi E; Yu, Douglas W
2011-12-01
We review recent work at the interface of economic game theory and evolutionary biology that provides new insights into the evolution of partner choice, host sanctions, partner fidelity feedback and public goods. (1) The theory of games with asymmetrical information shows that the right incentives allow hosts to screen-out parasites and screen-in mutualists, explaining successful partner choice in the absence of signalling. Applications range from ant-plants to microbiomes. (2) Contract theory distinguishes two longstanding but weakly differentiated explanations of host response to defectors: host sanctions and partner fidelity feedback. Host traits that selectively punish misbehaving symbionts are parsimoniously interpreted as pre-adaptations. Yucca-moth and legume-rhizobia mutualisms are argued to be examples of partner fidelity feedback. (3) The theory of public goods shows that cooperation in multi-player interactions can evolve in the absence of assortment, in one-shot social dilemmas among non-kin. Applications include alarm calls in vertebrates and exoenzymes in microbes.
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…
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 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.
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
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.
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.
Improving Quantum State Estimation with Mutually Unbiased Bases
NASA Astrophysics Data System (ADS)
Adamson, R. B. A.; Steinberg, A. M.
2010-07-01
When used in quantum state estimation, projections onto mutually unbiased bases have the ability to maximize information extraction per measurement and to minimize redundancy. We present the first experimental demonstration of quantum state tomography of two-qubit polarization states to take advantage of mutually unbiased bases. We demonstrate improved state estimation as compared to standard measurement strategies and discuss how this can be understood from the structure of the measurements we use. We experimentally compared our method to the standard state estimation method for three different states and observe that the infidelity was up to 1.84±0.06 times lower by using our technique than it was by using standard state estimation methods.
NASA Astrophysics Data System (ADS)
Horn, Florian; Bayer, Florian; Pelzer, Georg; Rieger, Jens; Ritter, André; Weber, Thomas; Zang, Andrea; Michel, Thilo; Anton, Gisela
2014-03-01
Grating-based X-ray phase-contrast imaging is a promising imaging modality to increase soft tissue contrast in comparison to conventional attenuation-based radiography. Complementary and otherwise inaccessible information is provided by the dark-field image, which shows the sub-pixel size granularity of the measured object. This could especially turn out to be useful in mammography, where tumourous tissue is connected with the presence of supertiny microcalcifications. In addition to the well-established image reconstruction process, an analysis method was introduced by Modregger, 1 which is based on deconvolution of the underlying scattering distribution within a single pixel revealing information about the sample. Subsequently, the different contrast modalities can be calculated with the scattering distribution. The method already proved to deliver additional information in the higher moments of the scattering distribution and possibly reaches better image quality with respect to an increased contrast-to-noise ratio. Several measurements were carried out using melamine foams as phantoms. We analysed the dependency of the deconvolution-based method with respect to the dark-field image on different parameters such as dose, number of iterations of the iterative deconvolution-algorithm and dark-field signal. A disagreement was found in the reconstructed dark-field values between the FFT method and the iterative method. Usage of the resulting characteristics might be helpful in future applications.
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
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.
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
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
An Information Theoretic Algorithm for Finding Periodicities in Stellar Light Curves
NASA Astrophysics Data System (ADS)
Huijse, Pablo; Estevez, Pablo A.; Protopapas, Pavlos; Zegers, Pablo; Principe, José C.
2012-10-01
We propose a new information theoretic metric for finding periodicities in stellar light curves. Light curves are astronomical time series of brightness over time, and are characterized as being noisy and unevenly sampled. The proposed metric combines correntropy (generalized correlation) with a periodic kernel to measure similarity among samples separated by a given period. The new metric provides a periodogram, called Correntropy Kernelized Periodogram (CKP), whose peaks are associated with the fundamental frequencies present in the data. The CKP does not require any resampling, slotting or folding scheme as it is computed directly from the available samples. CKP is the main part of a fully-automated pipeline for periodic light curve discrimination to be used in astronomical survey databases. We show that the CKP method outperformed the slotted correntropy, and conventional methods used in astronomy for periodicity discrimination and period estimation tasks, using a set of light curves drawn from the MACHO survey. The proposed metric achieved 97.2% of true positives with 0% of false positives at the confidence level of 99% for the periodicity discrimination task; and 88% of hits with 11.6% of multiples and 0.4% of misses in the period estimation task.
Bharkhada, Deepak; Yu, Hengyong; Ge, Shuping; Carr, J Jeffrey; Wang, Ge
2009-01-01
High x-ray radiation dose is a major public concern with the increasing use of multidetector computed tomography (CT) for diagnosis of cardiovascular diseases. This issue must be effectively addressed by dose-reduction techniques. Recently, our group proved that an internal region of interest (ROI) can be exactly reconstructed solely from localized projections if a small subregion within the ROI is known. In this article, we propose to use attenuation values of the blood in aorta and vertebral bone to serve as the known information for localized cardiac CT. First, we describe a novel interior tomography approach that backprojects differential fan-beam or parallel-beam projections to obtain the Hilbert transform and then reconstructs the original image in an ROI using the iterative projection onto convex sets algorithm. Then, we develop a numerical phantom based on clinical cardiac CT images for simulations. Our results demonstrate that it is feasible to use practical prior information and exactly reconstruct cardiovascular structures only from projection data along x-ray paths through the ROI.
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...-OPERATIONS Securities and Borrowings § 563.74 Mutual capital certificates. (a) General. No savings association that is in the mutual form shall issue mutual capital certificates pursuant to this section...
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 544.5 - Federal mutual savings association bylaws.
Code of Federal Regulations, 2010 CFR
2010-01-01
... 12 Banks and Banking 5 2010-01-01 2010-01-01 false Federal mutual savings association bylaws. 544... MUTUAL SAVINGS ASSOCIATIONS-CHARTER AND BYLAWS Bylaws § 544.5 Federal mutual savings association bylaws. (a) General. A Federal mutual savings association shall operate under bylaws that contain...
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...
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... MUTUAL SAVINGS ASSOCIATIONS-CHARTER AND BYLAWS Bylaws § 544.5 Federal mutual savings association bylaws. (a) General. A Federal mutual savings association shall operate under bylaws that contain...
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...
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.
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
Mutual Orbits of Transneptunian Multibody Systems
NASA Astrophysics Data System (ADS)
Grundy, William
2014-08-01
We propose to use LGS AO with NIRC2 during stellar appulses to measure relative astrometry of the large sample of transneptunian binaries for which mutual orbits remain unknown. Our long-term goal is to determine as many of their orbits as possible. These orbits provide a crucial constraint on dynamical conditions in outer parts of the protoplanetary nebula, as well as subsequent outer solar system history. They provide system masses and thus bulk densities, as well as enabling constraint of tidal dissipation parameters, scheduling of mutual event seasons, and revealing possible unresolved n>2 systems.
Impact of Mutual Mentoring on Research
NASA Astrophysics Data System (ADS)
Whitten, Barbara; Blaha, Cynthia; Bug, Amy; Cox, Anne; Fritz, Linda
2011-03-01
In this talk we discuss one of the impacts of an NSF ADVANCE sponsored horizontal, mutual mentoring alliance. Our cohort of five women physicists at liberal arts colleges has found that mutual mentoring has had a profound impact on many aspects of our professional lives. In this talk we will give some specific ways that we have supported and helped to expand each other's research. For some new areas of research were opened, for others new focus was brought to existing areas, and still others found acceptance for where they were.
Code of Federal Regulations, 2010 CFR
2010-04-01
... 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 foreign... 26 Internal Revenue 8 2010-04-01 2010-04-01 false Tax on insurance companies (other than life...
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
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
Yang, Liu; Lu, Yinzhi; Zhong, Yuanchang; Wu, Xuegang; Yang, Simon X
2015-12-26
Energy resource limitation is a severe problem in traditional wireless sensor networks (WSNs) because it restricts the lifetime of network. Recently, the emergence of energy harvesting techniques has brought with them the expectation to overcome this problem. In particular, it is possible for a sensor node with energy harvesting abilities to work perpetually in an Energy Neutral state. In this paper, a Multi-hop Energy Neutral Clustering (MENC) algorithm is proposed to construct the optimal multi-hop clustering architecture in energy harvesting WSNs, with the goal of achieving perpetual network operation. All cluster heads (CHs) in the network act as routers to transmit data to base station (BS) cooperatively by a multi-hop communication method. In addition, by analyzing the energy consumption of intra- and inter-cluster data transmission, we give the energy neutrality constraints. Under these constraints, every sensor node can work in an energy neutral state, which in turn provides perpetual network operation. Furthermore, the minimum network data transmission cycle is mathematically derived using convex optimization techniques while the network information gathering is maximal. Simulation results show that our protocol can achieve perpetual network operation, so that the consistent data delivery is guaranteed. In addition, substantial improvements on the performance of network throughput are also achieved as compared to the famous traditional clustering protocol LEACH and recent energy harvesting aware clustering protocols.
NASA 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.
NASA Astrophysics Data System (ADS)
Hou, W.; Wang, J.; Xu, X.; Leitch, J. W.; Delker, T.; Chen, G.
2015-12-01
This paper includes a series of studies that aim to develop a hyperspectral remote sensing technique for retrieving aerosol properties from a newly developed instrument GEO-TASO (Geostationary Trance gas and Aerosol Sensor Optimization) that measures the radiation at 0.4-0.7 wavelengths at spectral resolution of 0.02 nm. GEOS-TASO instrument is a prototype instrument of TEMPO (Tropospheric Emissions: Monitoring of Pollution), which will be launched in 2022 to measure aerosols, O3, and other trace gases from a geostationary orbit over the N-America. The theoretical framework of optimized inversion algorithm and the information content analysis such as degree of freedom for signal (DFS) will be discussed for hyperspectral remote sensing in visible bands, as well as the application to GEO-TASO, which has mounted on the NASA HU-25C aircraft and gathered several days' of airborne hyperspectral data for our studies. Based on the optimization theory and different from the traditional lookup table (LUT) retrieval technique, our inversion method intends to retrieve the aerosol parameters and surface reflectance simultaneously, in which UNL-VRTM (UNified Linearized Radiative Transfer Model) is employed for forward model and Jacobians calculation, meanwhile, principal component analysis (PCA) is used to constrain the hyperspectral surface reflectance.The information content analysis provides the theoretical analysis guidance about what kind of aerosol parameters could be retrieved from GeoTASO hyperspectral remote sensing to the practical inversion study. Besides, the inversion conducted iteratively until the modeled spectral radiance fits with GeoTASO measurements by a Quasi-Newton method called L-BFGS-B (Large scale BFGS Bound constrained). Finally, the retrieval results of aerosol optical depth and other aerosol parameters are compared against those retrieved by AEROENT and/or in situ measurements such as DISCOVER-AQ during the aircraft campaign.
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…
Empowering Public Welfare Workers through Mutual Support.
ERIC Educational Resources Information Center
Sherman, Wendy Ruth; Wenocur, Stanley
1983-01-01
Examines the organizational binds facing social workers concerned with the provision of services to clients in times of fiscal restraint. Suggests a mutual support group as a step toward empowerment. Workers may shift from a support group to a coalition for action as change agents within institutional settings. (JAC)
Mutually unbiased bases and generalized Bell states
Klimov, Andrei B.; Sych, Denis; Sanchez-Soto, Luis L.; Leuchs, Gerd
2009-05-15
We employ a straightforward relation between mutually unbiased and Bell bases to extend the latter in terms of a direct construction for the former. We analyze in detail the properties of these generalized Bell states, showing that they constitute an appropriate tool for testing entanglement in bipartite multiqudit systems.
Do Mutual Children Cement Bonds in Stepfamilies?
ERIC Educational Resources Information Center
Ganong, Lawrence H.; Coleman, Marilyn
1988-01-01
Interviewed 105 midwestern stepfamilies, 39 of whom had reproduced together. Found no significant differences between families with mutual children and those without in terms of marital adjustment, stepparent- and parent-child relationships, and stepfamily affect. It was not possible to predict which families were most likely to reproduce together…
The origin of a mutualism: a morphological trait promoting the evolution of ant-aphid mutualisms.
Shingleton, Alexander W; Stern, David L; Foster, William A
2005-04-01
Mutualisms are mutually beneficial interactions between species and are fundamentally important at all levels of biological organization. It is not clear, however, why one species participates in a particular mutualism whereas another does not. Here we show that pre-existing traits can dispose particular species to evolve a mutualistic interaction. Combining morphological, ecological, and behavioral data in a comparative analysis, we show that resource use in Chaitophorus aphids (Hemiptera: Aphididae) modulates the origin of their mutualism with ants. We demonstrate that aphid species that feed on deeper phloem elements have longer mouthparts, that this inhibits their ability to withdraw their mouthparts and escape predators and that, consequently, this increases their need for protection by mutualist ants.
2011-01-01
Background Envenomation by crotaline snakes (rattlesnake, cottonmouth, copperhead) is a complex, potentially lethal condition affecting thousands of people in the United States each year. Treatment of crotaline envenomation is not standardized, and significant variation in practice exists. Methods A geographically diverse panel of experts was convened for the purpose of deriving an evidence-informed unified treatment algorithm. Research staff analyzed the extant medical literature and performed targeted analyses of existing databases to inform specific clinical decisions. A trained external facilitator used modified Delphi and structured consensus methodology to achieve consensus on the final treatment algorithm. Results A unified treatment algorithm was produced and endorsed by all nine expert panel members. This algorithm provides guidance about clinical and laboratory observations, indications for and dosing of antivenom, adjunctive therapies, post-stabilization care, and management of complications from envenomation and therapy. Conclusions Clinical manifestations and ideal treatment of crotaline snakebite differ greatly, and can result in severe complications. Using a modified Delphi method, we provide evidence-informed treatment guidelines in an attempt to reduce variation in care and possibly improve clinical outcomes. PMID:21291549
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
A mutualism-parasitism system modeling host and parasite with mutualism at low density.
Wang, Yuanshi; Deangelis, Donald L
2012-04-01
A mutualism-parasitism system of two species is considered, where mutualism is the dominant interaction when the predators (parasites) are at low density while parasitism is dominant when the predators are at high density. Our aim is to show that mutualism at low density promotes coexistence of the species and leads to high production of the prey (host). The mutualism-parasitism system presented here is a combination of the Lotka-Volterra cooperative model and Lotka-Volterra predator-prey model. By comparing dynamics of this system with those of the Lotka-Volterra predator-prey model, we present the mechanisms by which the mutualism improves the coexistence of the species and production of the prey. Then the parameter space is divided into six regions, which correspond to the four outcomes of mutualism, commensalism, predation/parasitism and neutralism, respectively. When the parameters are varied continuously among the six regions, it is shown that the interaction outcomes of the system transition smoothly among the four outcomes. By comparing the dynamics of the specific system with those of the Lotka-Volterra cooperative model, we show that the parasitism at high density promotes stability of the system. A novel aspect of this paper is the simplicity of the model, which allows rigorous and thorough analysis and transparency of the results.
Spencer, W.A.; Goode, S.R.
1997-10-01
ICP emission analyses are prone to errors due to changes in power level, nebulization rate, plasma temperature, and sample matrix. As a result, accurate analyses of complex samples often require frequent bracketing with matrix matched standards. Information needed to track and correct the matrix errors is contained in the emission spectrum. But most commercial software packages use only the analyte line emission to determine concentrations. Changes in plasma temperature and the nebulization rate are reflected by changes in the hydrogen line widths, the oxygen emission, and neutral ion line ratios. Argon and off-line emissions provide a measure to correct the power level and the background scattering occurring in the polychromator. The authors` studies indicated that changes in the intensity of the Ar 404.4 nm line readily flag most matrix and plasma condition modifications. Carbon lines can be used to monitor the impact of organics on the analyses and calcium and argon lines can be used to correct for spectral drift and alignment. Spectra of contaminated groundwater and simulated defense waste glasses were obtained using a Thermo Jarrell Ash ICP that has an echelle CID detector system covering the 190-850 nm range. The echelle images were translated to the FITS data format, which astronomers recommend for data storage. Data reduction packages such as those in the ESO-MIDAS/ECHELLE and DAOPHOT programs were tried with limited success. The radial point spread function was evaluated as a possible improved peak intensity measurement instead of the common pixel averaging approach used in the commercial ICP software. Several algorithms were evaluated to align and automatically scale the background and reference spectra. A new data reduction approach that utilizes standard reference images, successive subtractions, and residual analyses has been evaluated to correct for matrix effects.
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.
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.
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.
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.
Trading public goods stabilizes interspecific mutualism.
Archetti, Marco; Scheuring, István
2013-02-01
The existence of cooperation between species raises a fundamental problem for evolutionary theory. Why provide costly services to another species if the feedback of this provision also happens to benefit intra-specific competitors that provide no service? Rewarding cooperators and punishing defectors can help maintain mutualism; this is not possible, however, when one can only respond to the collective action of one's partners, which is likely to be the case in many common symbioses. We show how the theory of public goods can explain the stability of mutualism when discrimination between cooperators and defectors is not possible: if two groups of individuals trade goods that are non-linear, increasing functions of the number of contributions, their mutualistic interaction is maintained by the exchange of these public goods, even when it is not possible to punish defectors, which can persist at relatively high frequencies. This provides a theoretical justification and testable predictions for the evolution of mutualism in the absence of discrimination mechanisms.
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.
Cheating and the evolutionary stability of mutualisms.
Ferriere, Régis; Bronstein, Judith L; Rinaldi, Sergio; Law, Richard; Gauduchon, Mathias
2002-04-22
Interspecific mutualisms have been playing a central role in the functioning of all ecosystems since the early history of life. Yet the theory of coevolution of mutualists is virtually nonexistent, by contrast with well-developed coevolutionary theories of competition, predator-prey and host-parasite interactions. This has prevented resolution of a basic puzzle posed by mutualisms: their persistence in spite of apparent evolutionary instability. The selective advantage of 'cheating', that is, reaping mutualistic benefits while providing fewer commodities to the partner species, is commonly believed to erode a mutualistic interaction, leading to its dissolution or reciprocal extinction. However, recent empirical findings indicate that stable associations of mutualists and cheaters have existed over long evolutionary periods. Here, we show that asymmetrical competition within species for the commodities offered by mutualistic partners provides a simple and testable ecological mechanism that can account for the long-term persistence of mutualisms. Cheating, in effect, establishes a background against which better mutualists can display any competitive superiority. This can lead to the coexistence and divergence of mutualist and cheater phenotypes, as well as to the coexistence of ecologically similar, but unrelated mutualists and cheaters.
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
29 CFR 553.105 - Mutual aid agreements.
Code of Federal Regulations, 2010 CFR
2010-07-01
... 29 Labor 3 2010-07-01 2010-07-01 false Mutual aid agreements. 553.105 Section 553.105 Labor... Mutual aid agreements. An agreement between two or more States, political subdivisions, or interstate governmental agencies for mutual aid does not change the otherwise volunteer character of services performed...
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...
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...
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.
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.
Creating a culture of mutual respect.
Kaplan, Kathryn; Mestel, Pamela; Feldman, David L
2010-04-01
The Joint Commission mandates that hospitals seeking accreditation have a process to define and address disruptive behavior. Leaders at Maimonides Medical Center, Brooklyn, New York, took the initiative to create a code of mutual respect that not only requires respectful behavior, but also encourages sensitivity and awareness to the causes of frustration that often lead to inappropriate behavior. Steps to implementing the code included selecting code advocates, setting up a system for mediating disputes, tracking and addressing operational system issues, providing training for personnel, developing a formal accountability process, and measuring the results. PMID:20362215
12 CFR 12.101 - National bank disclosure of remuneration for mutual fund transactions.
Code of Federal Regulations, 2010 CFR
2010-01-01
... 12 Banks and Banking 1 2010-01-01 2010-01-01 false National bank disclosure of remuneration for... Interpretations § 12.101 National bank disclosure of remuneration for mutual fund transactions. A national bank may fulfill its obligation to disclose information on the source and amount of remuneration,...
78 FR 24445 - Symetra Mutual Funds Trust, et al.; Notice of Application
Federal Register 2010, 2011, 2012, 2013, 2014
2013-04-25
...: Symetra Mutual Funds Trust (the ``Trust'') and Symetra Investment Management, Inc. (the ``Adviser... Investment Management). SUPPLEMENTARY INFORMATION: The following is a summary of the application. The...-end management investment company and currently offers three series which are advised by the...
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.
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.
Herbivores alter the fitness benefits of a plant-rhizobium mutualism
NASA Astrophysics Data System (ADS)
Heath, Katy D.; Lau, Jennifer A.
2011-03-01
Mutualisms are best understood from a community perspective, since third-party species have the potential to shift the costs and benefits in interspecific interactions. We manipulated plant genotypes, the presence of rhizobium mutualists, and the presence of a generalist herbivore and assessed the performance of all players in order to test whether antagonists might alter the fitness benefits of plant-rhizobium mutualism, and vice versa how mutualists might alter the fitness consequences of plant-herbivore antagonism. We found that plants in our experiment formed more associations with rhizobia (root nodules) in the presence of herbivores, thereby increasing the fitness benefits of mutualism for rhizobia. In contrast, the effects of rhizobia on herbivores were weak. Our data support a community-dependent view of these ecological interactions, and suggest that consideration of the aboveground herbivore community can inform ecological and evolutionary studies of legume-rhizobium interactions.
NASA Astrophysics Data System (ADS)
Snyder
1998-04-01
It has been shown by Einstein, Podolsky, and Rosen that in quantum mechanics two different wave functions can simultaneously characterize the same physical existent. This result means that one can make predictions regarding simultaneous, mutually exclusive features of a physical existent. It is important to ask whether people have the capacity to make observations of mutually exclusive phenomena simultaneously? Our everyday experience informs us that a human observer is capable of observing only one set of physical circumstances at a time. Evidence from psychology, though, indicates that people indeed have the capacity to make observations of mutually exclusive phenomena simultaneously, even though this capacity is not generally recognized. Working independently, Sigmund Freud and William James provided some of this evidence. How the nature of the quantum mechanical wave function is associated with the problem posed by Einstein, Podolsky, and Rosen, is addressed at the end of the paper.
The PHEMU97 catalogue of observations of the mutual phenomena of the Galilean satellites of Jupiter
NASA Astrophysics Data System (ADS)
Arlot, J.-E.; Thuillot, W.; Ruatti, C.; Akasawa, H.; Baroni, S.; Beisker, W.; Berthier, J.; Blanco, C.; Boonstra, J.; Bourgeois, J.; Bulder, H.; Casas, R.; Castano, J. G.; Colas, F.; Collins, D.; Cuypers, J.; Czech, W.; D'Ambrosio, V.; Denzau, H.; Descamps, P.; Dimitrescu, A.; Dinakarian, N.; Dourneau, G.; Emelyanov, N.; Enriquez, J. M.; Fernandez, J. M.; Fernandez-Barba, D.; Flatres, T.; Foglia, S.; Goncalves, M.; Guhl, K.; Helmer, G.; Hirose, T.; Irsmambetova, T. R.; Krobusek, B. A.; Lecacheux, J.; Le Campion, J.-F.; Lou, M.; Mallama, A.; Marchis, F.; Navarro, M. A. S.; Nelson, P.; Okura, N.; Park, J.; Pauwels, T.; Pluchino, S.; Priban, V.; Rapaport, M.; Sacré, J.-J.; Salvaggio, F.; Sanchez, M. A.; Sanchez-Bajo, F.; Stefanescu, G.; Tanga, P.; Tejfel, V. G.; Trisan, J. L.; Trunkovsky, E. M.; van Gestel, J.; Vandenbulcke, G.; Vasundhara, R.; Vass, G.; Vingerhoets, P.; Vu, D. T.; Wilds, R. T.
2006-05-01
In 1997 the Sun and the Earth passed through the equatorial plane of Jupiter and therefore through the orbital planes of its main satellites. During this period, mutual eclipses and occultations occurred and were observed. We investigate the precision of the catalogue to produce improved data for the development of dynamical models. Light curves of mutual eclipses and occultations were recorded by the observers of the international campaign PHEMU97 organized by the Institut de Mécanique Céleste, Paris, France. We made 275 observations of 148 mutual events from 42 sites. For each observation, information is given about the telescope, the receiver, the site and the observational conditions. This paper gathers together the data and gives a first estimate of the precision. The catalogue of these rare events represents a collection of improved accurate astrometric data useful for the development of dynamical models.
VizieR Online Data Catalog: Mutual phenomena of Galilean satellites PHEMU03 (Arlot+, 2009)
NASA Astrophysics Data System (ADS)
Arlot, J. E.; Thuillot, W.; Ruatti, C.; Ahmad, A.; Amosse, A.; Anbazhagan, P.; Andreyev, M.; Antov, A.; Appakutty, M.; Asher, D.; Aubry, S.; Baron, N.; Bassiere, N.; Berthe, M.; Bogdanovski, R.; Bosq, F.; Bredner, E.; Buettner, D.; Buromsky, M.; Cammarata, S.; Casas, R.; Chis, G. D.; Christou, A. A.; Coquerel, J.-P.; Corlan, R.; Cremaschini, C.; Crussaire, D.; Cuypers, J.; Dennefeld, M.; Descamps, P.; Devyatkin, A.; Dimitrov, D.; Dorokhova, T. N.; Dorokhov, N. I.; Dourneau, G.; Duenas, M.; Dumitrescu, A.; Emelianov, N.; Ferrara, D.; Fiel, D.; Fienga, A.; Flatres, T.; Foglia, S.; Garlitz, J.; Gerbos, J.; Gilbert, R.; Goncalves, R. M. D.; Gonzales, D. Montagnac S., Moorthy V., Nickel O., Nier J.M., Noel T., Noyelles B., Oksanen A., Parrat D., Pauwels T., Peng Q.Y., Pizzetti G., Priban V., Ramachandran B., Rambaux N., Rapaport M., Rapavy P., Rau G., Sacre J.-J., Sada P.V., Salvaggio F., Sarlin P., Sciuto C., Selvakumar G., Sergeyev A., Sidorov M., Sorescu S., Spampinato S.A., Stellmacher I., Trunkovsky E., Tejfel V., Tudose V., Turcu V., Ugarte I., Vantyghem P., Vasundhara R., Vaubaillon J., Velu C., Venkataramana A.K., Vidal-Sainz J., Vienne A., Vilar J., Vingerhoets P., Vollman W.
2008-11-01
In 2003, the Sun and the Earth passed through both the equatorial plane of Jupiter and therefore the orbital planes of its main satellites. During this period, mutual eclipses and occultations were observed and we present the data collected. Light curves of mutual eclipses and occultations were recorded by the observers of the international campaign PHEMU03 organized by the Institut de Mecanique Celeste, Paris, France We completed 377 observations of 118 mutual events from 42 sites and the corresponding data are presented in this paper. For each observation, information about the telescope, receptor, site, and observational conditions are provided. This paper gathers all data and indicates a first estimate of its precision. This catalogue of these rare events should constitute an improved basis for accurate astrometric data useful in the development of dynamical models. (5 data files).
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.
Protein recognition and selection through conformational and mutually induced fit
Wang, Qian; Zhang, Pengzhi; Hoffman, Laurel; Tripathi, Swarnendu; Homouz, Dirar; Liu, Yin; Waxham, M. Neal; Cheung, Margaret S.
2013-01-01
Protein–protein interactions drive most every biological process, but in many instances the domains mediating recognition are disordered. How specificity in binding is attained in the absence of defined structure contrasts with well-established experimental and theoretical work describing ligand binding to protein. The signaling protein calmodulin presents a unique opportunity to investigate mechanisms for target recognition given that it interacts with several hundred different targets. By advancing coarse-grained computer simulations and experimental techniques, mechanistic insights were gained in defining the pathways leading to recognition and in how target selectivity can be achieved at the molecular level. A model requiring mutually induced conformational changes in both calmodulin and target proteins was necessary and broadly informs how proteins can achieve both high affinity and high specificity. PMID:24297894
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
Relative-Error-Covariance Algorithms
NASA Technical Reports Server (NTRS)
Bierman, Gerald J.; Wolff, Peter J.
1991-01-01
Two algorithms compute error covariance of difference between optimal estimates, based on data acquired during overlapping or disjoint intervals, of state of discrete linear system. Provides quantitative measure of mutual consistency or inconsistency of estimates of states. Relative-error-covariance concept applied, to determine degree of correlation between trajectories calculated from two overlapping sets of measurements and construct real-time test of consistency of state estimates based upon recently acquired data.
Mutual potential between two rigid bodies with arbitrary shapes and mass distributions
NASA Astrophysics Data System (ADS)
Hou, Xiyun; Scheeres, Daniel J.; Xin, Xiaosheng
2016-09-01
Formulae to compute the mutual potential, force, and torque between two rigid bodies are given. These formulae are expressed in Cartesian coordinates using inertia integrals. They are valid for rigid bodies with arbitrary shapes and mass distributions. By using recursive relations, these formulae can be easily implemented on computers. Comparisons with previous studies show their superiority in computation speed. Using the algorithm as a tool, the planar problem of two ellipsoids is studied. Generally, potential truncated at the second order is good enough for a qualitative description of the mutual dynamics. However, for ellipsoids with very large non-spherical terms, higher order terms of the potential should be considered, at the cost of a higher computational cost. Explicit formulae of the potential truncated to the fourth order are given.
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
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.
The macroecology of marine cleaning mutualisms.
Floeter, Sergio R; Vázquez, Diego P; Grutter, Alexandra S
2007-01-01
1. Marine cleaning mutualisms generally involve small fish or shrimps removing ectoparasites and other material from cooperating 'client' fish. We evaluate the role of fish abundance, body size and behaviour as determinants of interactions with cleaning mutualists. 2. Data come from eight reef locations in Brazil, the Caribbean, the Mediterranean and Australia. 3. We conducted a meta-analysis of client-cleaner interactions involving 11 cleaner and 221 client species. 4. There was a strong, positive effect of client abundance on cleaning frequency, but only a weak, negative effect of client body size. These effects were modulated by client trophic group and social behaviour. 5. This study adds to a growing body of evidence suggesting a central role of species abundance in structuring species interactions.
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.
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
A semi-supervised classification algorithm using the TAD-derived background as training data
NASA Astrophysics Data System (ADS)
Fan, Lei; Ambeau, Brittany; Messinger, David W.
2013-05-01
In general, spectral image classification algorithms fall into one of two categories: supervised and unsupervised. In unsupervised approaches, the algorithm automatically identifies clusters in the data without a priori information about those clusters (except perhaps the expected number of them). Supervised approaches require an analyst to identify training data to learn the characteristics of the clusters such that they can then classify all other pixels into one of the pre-defined groups. The classification algorithm presented here is a semi-supervised approach based on the Topological Anomaly Detection (TAD) algorithm. The TAD algorithm defines background components based on a mutual k-Nearest Neighbor graph model of the data, along with a spectral connected components analysis. Here, the largest components produced by TAD are used as regions of interest (ROI's),or training data for a supervised classification scheme. By combining those ROI's with a Gaussian Maximum Likelihood (GML) or a Minimum Distance to the Mean (MDM) algorithm, we are able to achieve a semi supervised classification method. We test this classification algorithm against data collected by the HyMAP sensor over the Cooke City, MT area and University of Pavia scene.
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
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.
7 CFR 550.13 - Mutuality of interest.
Code of Federal Regulations, 2011 CFR
2011-01-01
... 7 Agriculture 6 2011-01-01 2011-01-01 false Mutuality of interest. 550.13 Section 550.13 Agriculture Regulations of the Department of Agriculture (Continued) AGRICULTURAL RESEARCH SERVICE, DEPARTMENT.... Mutual interest exists when both parties benefit in the same qualitative way from the objectives of...
7 CFR 550.13 - Mutuality of interest.
Code of Federal Regulations, 2013 CFR
2013-01-01
... 7 Agriculture 6 2013-01-01 2013-01-01 false Mutuality of interest. 550.13 Section 550.13 Agriculture Regulations of the Department of Agriculture (Continued) AGRICULTURAL RESEARCH SERVICE, DEPARTMENT.... Mutual interest exists when both parties benefit in the same qualitative way from the objectives of...
7 CFR 550.13 - Mutuality of interest.
Code of Federal Regulations, 2012 CFR
2012-01-01
... 7 Agriculture 6 2012-01-01 2012-01-01 false Mutuality of interest. 550.13 Section 550.13 Agriculture Regulations of the Department of Agriculture (Continued) AGRICULTURAL RESEARCH SERVICE, DEPARTMENT OF AGRICULTURE GENERAL ADMINISTRATIVE POLICY FOR NON-ASSISTANCE COOPERATIVE AGREEMENTS Formation of Agreements § 550.13 Mutuality of interest....
7 CFR 550.13 - Mutuality of interest.
Code of Federal Regulations, 2014 CFR
2014-01-01
... 7 Agriculture 6 2014-01-01 2014-01-01 false Mutuality of interest. 550.13 Section 550.13 Agriculture Regulations of the Department of Agriculture (Continued) AGRICULTURAL RESEARCH SERVICE, DEPARTMENT.... Mutual interest exists when both parties benefit in the same qualitative way from the objectives of...
47 CFR 22.131 - Procedures for mutually exclusive applications.
Code of Federal Regulations, 2012 CFR
2012-10-01
... 47 Telecommunication 2 2012-10-01 2012-10-01 false Procedures for mutually exclusive applications...) (according to the filing dates) as acceptable for filing. (4) Window filing group. A window filing group comprises mutually exclusive applications whose filing date is within an announced filing window....
47 CFR 22.131 - Procedures for mutually exclusive applications.
Code of Federal Regulations, 2014 CFR
2014-10-01
... 47 Telecommunication 2 2014-10-01 2014-10-01 false Procedures for mutually exclusive applications...) (according to the filing dates) as acceptable for filing. (4) Window filing group. A window filing group comprises mutually exclusive applications whose filing date is within an announced filing window....
47 CFR 22.131 - Procedures for mutually exclusive applications.
Code of Federal Regulations, 2013 CFR
2013-10-01
... 47 Telecommunication 2 2013-10-01 2013-10-01 false Procedures for mutually exclusive applications...) (according to the filing dates) as acceptable for filing. (4) Window filing group. A window filing group comprises mutually exclusive applications whose filing date is within an announced filing window....
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…
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...
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…
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…
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...
Federal Register 2010, 2011, 2012, 2013, 2014
2012-02-01
..., published July 1, 2011, at 76 FR 38892. FOR FURTHER INFORMATION CONTACT: Surety Bond Branch at (202) 874-6850. SUPPLEMENTARY INFORMATION: Notice is hereby given that American Hardware Mutual Insurance Company... Fiscal Service Surety Companies Acceptable on Federal Bonds--Name Change: American Hardware...
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.
Reducing Deviance Through Youths' Mutual Aid Group Dynamics.
Cheung, Chau-kiu; Ngai, Steven Sek-yum
2016-01-01
The mutual aid group, as supported by the social worker, emerges to play a vital role in helping group members reduce their deviance or behavioral problem. However, how the collaboration of the group and social worker accomplishes the reduction has remained uncharted. Based on social capital theory, mutual aid and cohesion within the group and social workers' specific aid for the group are likely responsible for the reduction. The test of such hypotheses relies on a two-wave panel survey of the members of 60 mutual aid groups who had deviant behavioral problems, located in Hong Kong, China. These groups had 241 youths completing both initial and 1-year follow-up surveys. Results manifested the direct or unconditional contributions of mutual aid, group cohesion, and social workers' specific aid to reducing deviance. Hence, social workers can enhance the effectiveness of the mutual aid group in reducing youths' deviance.
Genetic drift opposes mutualism during spatial population expansion.
Müller, Melanie J I; Neugeboren, Beverly I; Nelson, David R; Murray, Andrew W
2014-01-21
Mutualistic interactions benefit both partners, promoting coexistence and genetic diversity. Spatial structure can promote cooperation, but spatial expansions may also make it hard for mutualistic partners to stay together, because genetic drift at the expansion front creates regions of low genetic and species diversity. To explore the antagonism between mutualism and genetic drift, we grew cross-feeding strains of the budding yeast Saccharomyces cerevisiae on agar surfaces as a model for mutualists undergoing spatial expansions. By supplying varying amounts of the exchanged nutrients, we tuned strength and symmetry of the mutualistic interaction. Strong mutualism suppresses genetic demixing during spatial expansions and thereby maintains diversity, but weak or asymmetric mutualism is overwhelmed by genetic drift even when mutualism is still beneficial, slowing growth and reducing diversity. Theoretical modeling using experimentally measured parameters predicts the size of demixed regions and how strong mutualism must be to survive a spatial expansion.
Mutuality: clinical and metapsychological potentials of a failed experiment.
Castillo Mendoza, Carlos Alberto
2012-03-01
Ferenczi's experiments with mutual analysis are often dismissed, without acknowledging the results obtained from them and his own cautionary remarks about their limits. Though ultimately failed, Ferenczi's experiments with mutual analysis were a source of clinical and metapsychological knowledge, despite the fact that he was unable to elaborate them in his lifetime. In this paper I connect mutuality to the development of the psyche, especially to the constitutive core of the intrapsychic. To understand the latter, it is necessary to take into account, among others, issues such as the common attribute, the mutual flux between the unconsciouses, the dialogue of unconsciouses, the maternal profundity, the primal relationship with the mother, and, above all, the primal unity between mother and child, which are fundamental for the emergence and development of the primary psychic forces. Incidences of rupture, distortion of the core of mutuality in the psychic life, its loss and disadjustment, by means of external traumatizing forces, and some clinical implications are described.
Calcium and ROS: A mutual interplay.
Görlach, Agnes; Bertram, Katharina; Hudecova, Sona; Krizanova, Olga
2015-12-01
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 Ca(2+) 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
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
Calcium and ROS: A mutual interplay.
Görlach, Agnes; Bertram, Katharina; Hudecova, Sona; Krizanova, Olga
2015-12-01
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 Ca(2+) 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.
Laser array having mutually coupled resonators
Sziklas, E.A.; Palma, G.E.
1987-07-21
A laser system is described having at least two independently pumped unstable laser resonators. Each has a feedback region in which optical radiation resonates, an output region. Output radiation exists from the feedback region and an output coupling means for coupling out a main beam from the region in which laser extracted radiation extracted from a first one of at least two unstable laser resonators is coupled unidirectionally into at least one other of the unstable laser resonators. The extracted radiation from the first unstable laser resonator influences at least one other unstable laser resonator. The improvement comprises a system in which each of the resonators is mutually and substantially symmetrically, bidirectionally coupled to at least one other unstable resonator, through extraction means for extracting at least one coupling portion of the output radiation. A coupling radiation power and transporting means transports at least one coupling portion of the output radiation that is mode-matched to an adjoint mode. At least one other unstable laser resonator into at least one corresponding output region of the other one of at least two unstable laser resonators produce a laser system having a scaled-up laser output.
Life on the edge: characterising the edges of mutually non-dominating sets.
Everson, Richard M; Walker, David J; Fieldsend, Jonathan E
2014-01-01
Multi-objective optimisation yields an estimated Pareto front of mutually non- dominating solutions, but with more than three objectives, understanding the relationships between solutions is challenging. Natural solutions to use as landmarks are those lying near to the edges of the mutually non-dominating set. We propose four definitions of edge points for many-objective mutually non-dominating sets and examine the relations between them. The first defines edge points to be those that extend the range of the attainment surface. This is shown to be equivalent to finding points which are not dominated on projection onto subsets of the objectives. If the objectives are to be minimised, a further definition considers points which are not dominated under maximisation when projected onto objective subsets. A final definition looks for edges via alternative projections of the set. We examine the relations between these definitions and their efficacy in many dimensions for synthetic concave- and convex-shaped sets, and on solutions to a prototypical many-objective optimisation problem, showing how they can reveal information about the structure of the estimated Pareto front. We show that the "controlling dominance area of solutions" modification of the dominance relation can be effectively used to locate edges and interior points of high-dimensional mutually non-dominating sets.
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.
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
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)
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
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
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
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
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.
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 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.
Concurrent algorithms for transient FE analysis
NASA Technical Reports Server (NTRS)
Ortiz, M.; Nour-Omid, B.
1989-01-01
Information on concurrent algorithms for transient finite element analysis is given in viewgraph form. Information is given on concurrent dynamic algorithms, interprocessor communication, the performance of the BAR problem on the 32 Processor Hypercube, computational efficiency and accuracy analysis.
47 CFR 27.321 - Mutually exclusive applications.
Code of Federal Regulations, 2011 CFR
2011-10-01
... MISCELLANEOUS WIRELESS COMMUNICATIONS SERVICES Application, Licensing, and Processing Rules for WCS § 27.321... Commission's rules governing the Wireless Communications Services involved. The Commission uses the general procedures in this section for processing mutually exclusive applications in the Wireless...
47 CFR 27.321 - Mutually exclusive applications.
Code of Federal Regulations, 2012 CFR
2012-10-01
... MISCELLANEOUS WIRELESS COMMUNICATIONS SERVICES Application, Licensing, and Processing Rules for WCS § 27.321... Commission's rules governing the Wireless Communications Services involved. The Commission uses the general procedures in this section for processing mutually exclusive applications in the Wireless...
47 CFR 27.321 - Mutually exclusive applications.
Code of Federal Regulations, 2010 CFR
2010-10-01
... MISCELLANEOUS WIRELESS COMMUNICATIONS SERVICES Application, Licensing, and Processing Rules for WCS § 27.321... Commission's rules governing the Wireless Communications Services involved. The Commission uses the general procedures in this section for processing mutually exclusive applications in the Wireless...
47 CFR 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...
47 CFR 101.45 - Mutually exclusive applications.
Code of Federal Regulations, 2014 CFR
2014-10-01
... SERVICES FIXED MICROWAVE SERVICES Applications and Licenses Processing of Applications § 101.45 Mutually... fixed point-to-point microwave applications for authorization under this part will be entitled...
47 CFR 101.45 - Mutually exclusive applications.
Code of Federal Regulations, 2012 CFR
2012-10-01
... SERVICES FIXED MICROWAVE SERVICES Applications and Licenses Processing of Applications § 101.45 Mutually... fixed point-to-point microwave applications for authorization under this part will be entitled...
47 CFR 101.45 - Mutually exclusive applications.
Code of Federal Regulations, 2010 CFR
2010-10-01
... SERVICES FIXED MICROWAVE SERVICES Applications and Licenses Processing of Applications § 101.45 Mutually... fixed point-to-point microwave applications for authorization under this part will be entitled...
47 CFR 101.45 - Mutually exclusive applications.
Code of Federal Regulations, 2013 CFR
2013-10-01
... SERVICES FIXED MICROWAVE SERVICES Applications and Licenses Processing of Applications § 101.45 Mutually... fixed point-to-point microwave applications for authorization under this part will be entitled...
47 CFR 27.321 - Mutually exclusive applications.
Code of Federal Regulations, 2013 CFR
2013-10-01
... MISCELLANEOUS WIRELESS COMMUNICATIONS SERVICES Application, Licensing, and Processing Rules for WCS § 27.321... Commission's rules governing the Wireless Communications Services involved. The Commission uses the general procedures in this section for processing mutually exclusive applications in the Wireless...
47 CFR 27.321 - Mutually exclusive applications.
Code of Federal Regulations, 2014 CFR
2014-10-01
... MISCELLANEOUS WIRELESS COMMUNICATIONS SERVICES Application, Licensing, and Processing Rules for WCS § 27.321... Commission's rules governing the Wireless Communications Services involved. The Commission uses the general procedures in this section for processing mutually exclusive applications in the Wireless...
Parasponia: a novel system for studying mutualism stability.
Behm, Jocelyn E; Geurts, Rene; Kiers, E Toby
2014-12-01
Understanding how mutualistic interactions are stabilized in the presence of cheaters is a major question in evolutionary biology. The legume-rhizobia mutualism has become a model system for studying how plants control cheating partners. However, the generality and evolutionary origins of these control mechanisms are intensely debated. In this Opinion article, we argue that a novel system--the Parasponia-rhizobia mutualism--will significantly advance research in mutualism stability. Parasponia is the only non-legume lineage to have evolved a rhizobial symbiosis, which provides an evolutionary replicate to test how rhizobial exploitation is controlled. Evidence also suggests that this symbiosis is young. This allows studies at an earlier evolutionary stage in mutualisms, so the origin of control mechanisms can be better understood.
Viscosity and mutual diffusion in strongly asymmetric plasma mixtures
Bastea, S
2004-09-07
The authors present molecular dynamics simulation results for the viscosity and mutual diffusion constant of a strongly asymmetric two-component plasma (TCP). They compare the results with available theoretical models previously tested for much smaller asymmetries. for the case of viscosity they propose a new predictive framework based on the linear mixing rule, while for mutual diffusion they point out some consistency problems of widely used Boltzmann equation based models.
Input impedance and mutual coupling of rectangular microstrip antennas
NASA Technical Reports Server (NTRS)
Pozar, D. M.
1982-01-01
A moment method solution to the problem of input impedance and mutual coupling of rectangular microstrip antenna elements is presented. The formulation uses the grounded dielectric slab Green's function to account rigorously for the presence of the substrate and surface waves. Both entire basis (EB) and piecewise sinusoidal (PWS) expansion modes are used, and their relative advantages are noted. Calculations of input impedance and mutual coupling are compared with measured data and other calculations.
A measure for mutual refinements of image segmentations.
Cardoso, Jaime S; Corte-Real, Luís
2006-08-01
In this paper, we recover a graph interpretation of the mutual partition distance, proposed recently by Cardoso and Corte-Real. We deduce some properties of this measure, and establish a correspondence with the partition distance introduced by Almudevar and Field and Gusfield, and independently by Guigues. We also present some different formulations for the computation of the mutual partition distance. Finally, a comparison is made with similar measures. PMID:16900689
Rethinking mutualism stability: cheaters and the evolution of sanctions.
Frederickson, Megan E
2013-12-01
How cooperation originates and persists in diverse species, from bacteria to multicellular organisms to human societies, is a major question in evolutionary biology. A large literature asks: what prevents selection for cheating within cooperative lineages? In mutualisms, or cooperative interactions between species, feedback between partners often aligns their fitness interests, such that cooperative symbionts receive more benefits from their hosts than uncooperative symbionts. But how do these feedbacks evolve? Cheaters might invade symbiont populations and select for hosts that preferentially reward or associate with cooperators (often termed sanctions or partner choice); hosts might adapt to variation in symbiont quality that does not amount to cheating (e.g., environmental variation); or conditional host responses might exist before cheaters do, making mutualisms stable from the outset. I review evidence from yucca-yucca moth, fig-fig wasp, and legume-rhizobium mutualisms, which are commonly cited as mutualisms stabilized by sanctions. Based on the empirical evidence, it is doubtful that cheaters select for host sanctions in these systems; cheaters are too uncommon. Recognizing that sanctions likely evolved for functions other than retaliation against cheaters offers many insights about mutualism coevolution, and about why mutualism evolves in only some lineages of potential hosts.
Adding biotic complexity alters the metabolic benefits of mutualism.
Harcombe, William R; Betts, Alex; Shapiro, Jason W; Marx, Christopher J
2016-08-01
Mutualism is ubiquitous in nature and plays an integral role in most communities. To predict the eco-evolutionary dynamics of mutualism it is critical to extend classic pair-wise analysis to include additional species. We investigated the effect of adding a third species to a pair-wise mutualism in a spatially structured environment. We tested the hypotheses that selection for costly excretions in a focal population (i) decreases when an exploiter is added (ii) increases when a third mutualist is added relative to the pair-wise scenario. We assayed the selection acting on Salmonella enterica when it exchanges methionine for carbon in an obligate mutualism with an auxotrophic Escherichia coli. A third bacterium, Methylobacterium extorquens, was then added and acted either as an exploiter of the carbon or third obligate mutualist depending on the nitrogen source. In the tripartite mutualism M. extorquens provided nitrogen to the other species. Contrary to our expectations, adding an exploiter increased selection for methionine excretion in S. enterica. Conversely, selection for cooperation was lower in the tripartite mutualism relative to the pair-wise system. Genome-scale metabolic models helped identify the mechanisms underlying these changes in selection. Our results highlight the utility of connecting metabolic mechanisms and eco-evolutionary dynamics. PMID:27272242
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.
Pareschi, Fabio; Albertini, Pierluigi; Frattini, Giovanni; Mangia, Mauro; Rovatti, Riccardo; Setti, Gianluca
2016-02-01
We report the design and implementation of an Analog-to-Information Converter (AIC) based on Compressed Sensing (CS). The system is realized in a CMOS 180 nm technology and targets the acquisition of bio-signals with Nyquist frequency up to 100 kHz. To maximize performance and reduce hardware complexity, we co-design hardware together with acquisition and reconstruction algorithms. The resulting AIC outperforms previously proposed solutions mainly thanks to two key features. First, we adopt a novel method to deal with saturations in the computation of CS measurements. This allows no loss in performance even when 60% of measurements saturate. Second, the system is able to adapt itself to the energy distribution of the input by exploiting the so-called rakeness to maximize the amount of information contained in the measurements. With this approach, the 16 measurement channels integrated into a single device are expected to allow the acquisition and the correct reconstruction of most biomedical signals. As a case study, measurements on real electrocardiograms (ECGs) and electromyograms (EMGs) show signals that these can be reconstructed without any noticeable degradation with a compression rate, respectively, of 8 and 10.
Information Filtering on Coupled Social Networks
Nie, Da-Cheng; Zhang, Zi-Ke; Zhou, Jun-Lin; Fu, Yan; Zhang, Kui
2014-01-01
In this paper, based on the coupled social networks (CSN), we propose a hybrid algorithm to nonlinearly integrate both social and behavior information of online users. Filtering algorithm, based on the coupled social networks, considers the effects of both social similarity and personalized preference. Experimental results based on two real datasets, Epinions and Friendfeed, show that the hybrid pattern can not only provide more accurate recommendations, but also enlarge the recommendation coverage while adopting global metric. Further empirical analyses demonstrate that the mutual reinforcement and rich-club phenomenon can also be found in coupled social networks where the identical individuals occupy the core position of the online system. This work may shed some light on the in-depth understanding of the structure and function of coupled social networks. PMID:25003525
12-Step Interventions and Mutual Support Programs for Substance Use Disorders: An Overview
Donovan, Dennis M.; Ingalsbe, Michelle H.; Benbow, James; Daley, Dennis C.
2013-01-01
Social workers and other behavioral health professionals are likely to encounter individuals with substance use disorders in a variety of practice settings outside of specialty treatment. 12-Step mutual support programs represent readily available, no cost community-based resources for such individuals; however, practitioners are often unfamiliar with such programs. The present article provides a brief overview of 12-Step programs, the positive substance use and psychosocial outcomes associated with active 12-Step involvement, and approaches ranging from ones that can be utilized by social workers in any practice setting to those developed for specialty treatment programs to facilitate engagement in 12-Step meetings and recovery activities. The goal is to familiarize social workers with 12-Step approaches so that they are better able to make informed referrals that match clients to mutual support groups that best meet the individual’s needs and maximize the likelihood of engagement and positive outcomes. PMID:23731422
The PHESAT95 catalogue of observations of the mutual events of the Saturnian satellites
NASA Astrophysics Data System (ADS)
Thuillot, W.; Arlot, J.-E.; Ruatti, C.; Berthier, J.; Blanco, C.; Colas, F.; Czech, W.; Damani, M.; D'Ambrosio, V.; Descamps, P.; Dourneau, G.; Emelianov, N.; Foglia, S.; Helmer, G.; Irsmambetova, T. R.; James, N.; Laques, P.; Lecacheux, J.; Le Campion, J.-F.; Ledoux, C.; Le Floch, J.-C.; Oprescu, G.; Rapaport, M.; Riccioli, R.; Starosta, B.; Tejfel, V. G.; Trunkovsky, E. M.; Viateau, B.; Veiga, C. H.; Vu, D. T.
2001-05-01
In 1994-1996 the Sun and the Earth passed through the equatorial plane of Saturn and therefore through the orbital planes of its main satellites. During this period, phenomena involving seven of these satellites were observed. Light curves of eclipses by Saturn and of mutual eclipses and occultations were recorded by the observers of the international campaign PHESAT95 organized by the Institut de mécanique céleste, Paris, France. Herein, we report 66 observations of 43 mutual events from 16 sites. For each observation, information is given about the telescope, the receptor, the site and the observational conditions. This paper gathers together all these data and gives a first estimate of the precision providing accurate astrometric data useful for the development of dynamical models.
ERIC Educational Resources Information Center
Denissen, Jaap J. A.; van Aken, Marcel A. G.; Dubas, Judith S.
2009-01-01
According to J. Belsky's (1984) process model of parenting, both adolescents' and parents' personality should exert a significant impact on the quality of their mutual relationship. Using multi-informant, symmetric data on the Big Five personality traits and the relationship quality of mothers, fathers, and two adolescent children, the current…
Ma, Jingjing; Liu, Jie; Ma, Wenping; Gong, Maoguo; Jiao, Licheng
2014-01-01
Community structure is one of the most important properties in social networks. In dynamic networks, there are two conflicting criteria that need to be considered. One is the snapshot quality, which evaluates the quality of the community partitions at the current time step. The other is the temporal cost, which evaluates the difference between communities at different time steps. In this paper, we propose a decomposition-based multiobjective community detection algorithm to simultaneously optimize these two objectives to reveal community structure and its evolution in dynamic networks. It employs the framework of multiobjective evolutionary algorithm based on decomposition to simultaneously optimize the modularity and normalized mutual information, which quantitatively measure the quality of the community partitions and temporal cost, respectively. A local search strategy dealing with the problem-specific knowledge is incorporated to improve the effectiveness of the new algorithm. Experiments on computer-generated and real-world networks demonstrate that the proposed algorithm can not only find community structure and capture community evolution more accurately, but also be steadier than the two compared algorithms.
NASA Astrophysics Data System (ADS)
Li, Weixing; Zhang, Yue; Lin, Jianzhi; Chen, Zengping
2015-10-01
Amplitude-phase errors and mutual coupling errors among multi-channels in digital array radar (DAR) will seriously deteriorate the performance of signal processing such as digital beam-forming (DBF) and high resolution direction finding. In this paper, a combined algorithm for error calibration in DAR has been demonstrated. The algorithm firstly estimates the amplitude-phase errors of each channel using interior calibration sources with the help of the calibration network. Then the signals from far field are received and the amplitude-phase errors are compensated. According to the subspace theories, the relationship between the principle eigenvectors and distorted steering vectors is expressed, and the cost function containing the mutual coupling matrix (MCM) and incident directions is established. Making use of the properties of MCM of uniform linear array, Gauss-Newton method is implied to iteratively compute the MCM and the direction of arrival (DOA). Simulation results have shown the effectiveness and performance of proposed algorithm. Based on an 8-elements DAR test-bed, experiments are carried out in anechoic chamber. The results illustrate that the algorithm is feasible in actual systems.
The "Juggler" algorithm: a hybrid deformable image registration algorithm for adaptive radiotherapy
NASA Astrophysics Data System (ADS)
Xia, Junyi; Chen, Yunmei; Samant, Sanjiv S.
2007-03-01
Fast deformable registration can potentially facilitate the clinical implementation of adaptive radiation therapy (ART), which allows for daily organ deformations not accounted for in radiotherapy treatment planning, which typically utilizes a static organ model, to be incorporated into the fractionated treatment. Existing deformable registration algorithms typically utilize a specific diffusion model, and require a large number of iterations to achieve convergence. This limits the online applications of deformable image registration for clinical radiotherapy, such as daily patient setup variations involving organ deformation, where high registration precision is required. We propose a hybrid algorithm, the "Juggler", based on a multi-diffusion model to achieve fast convergence. The Juggler achieves fast convergence by applying two different diffusion models: i) one being optimized quickly for matching high gradient features, i.e. bony anatomies; and ii) the other being optimized for further matching low gradient features, i.e. soft tissue. The regulation of these 2 competing criteria is achieved using a threshold of a similarity measure, such as cross correlation or mutual information. A multi-resolution scheme was applied for faster convergence involving large deformations. Comparisons of the Juggler algorithm were carried out with demons method, accelerated demons method, and free-form deformable registration using 4D CT lung imaging from 5 patients. Based on comparisons of difference images and similarity measure computations, the Juggler produced a superior registration result. It achieved the desired convergence within 30 iterations, and typically required <90sec to register two 3D image sets of size 256×256×40 using a 3.2 GHz PC. This hybrid registration strategy successfully incorporates the benefits of different diffusion models into a single unified model.
Population dynamics and mutualism: Functional responses of benefits and costs
Holland, J. Nathaniel; DeAngelis, Donald L.; Bronstein, Judith L.
2002-01-01
We develop an approach for studying population dynamics resulting from mutualism by employing functional responses based on density‐dependent benefits and costs. These functional responses express how the population growth rate of a mutualist is modified by the density of its partner. We present several possible dependencies of gross benefits and costs, and hence net effects, to a mutualist as functions of the density of its partner. Net effects to mutualists are likely a monotonically saturating or unimodal function of the density of their partner. We show that fundamental differences in the growth, limitation, and dynamics of a population can occur when net effects to that population change linearly, unimodally, or in a saturating fashion. We use the mutualism between senita cactus and its pollinating seed‐eating moth as an example to show the influence of different benefit and cost functional responses on population dynamics and stability of mutualisms. We investigated two mechanisms that may alter this mutualism's functional responses: distribution of eggs among flowers and fruit abortion. Differences in how benefits and costs vary with density can alter the stability of this mutualism. In particular, fruit abortion may allow for a stable equilibrium where none could otherwise exist.
Mutualism Disruption Threatens Global Plant Biodiversity: A Systematic Review
Aslan, Clare E.; Zavaleta, Erika S.; Tershy, Bernie; Croll, Donald
2013-01-01
Background As global environmental change accelerates, biodiversity losses can disrupt interspecific interactions. Extinctions of mutualist partners can create “widow” species, which may face reduced ecological fitness. Hypothetically, such mutualism disruptions could have cascading effects on biodiversity by causing additional species coextinctions. However, the scope of this problem – the magnitude of biodiversity that may lose mutualist partners and the consequences of these losses – remains unknown. Methodology/Principal Findings We conducted a systematic review and synthesis of data from a broad range of sources to estimate the threat posed by vertebrate extinctions to the global biodiversity of vertebrate-dispersed and -pollinated plants. Though enormous research gaps persist, our analysis identified Africa, Asia, the Caribbean, and global oceanic islands as geographic regions at particular risk of disruption of these mutualisms; within these regions, percentages of plant species likely affected range from 2.1–4.5%. Widowed plants are likely to experience reproductive declines of 40–58%, potentially threatening their persistence in the context of other global change stresses. Conclusions Our systematic approach demonstrates that thousands of species may be impacted by disruption in one class of mutualisms, but extinctions will likely disrupt other mutualisms, as well. Although uncertainty is high, there is evidence that mutualism disruption directly threatens significant biodiversity in some geographic regions. Conservation measures with explicit focus on mutualistic functions could be necessary to bolster populations of widowed species and maintain ecosystem functions. PMID:23840571
Intention-Disguised Algorithmic Trading
NASA Astrophysics Data System (ADS)
Yuen, William; Syverson, Paul; Liu, Zhenming; Thorpe, Christopher
Large market participants (LMPs) must often execute trades while keeping their intentions secret. Sometimes secrecy is required before trades are completed to prevent other traders from anticipating (and exploiting) the price impact of their trades. This is known as "front-running". In other cases, LMPs with proprietary trading strategies wish to keep their positions secret even after trading because their strategies and positions contain valuable information. LMPs include hedge funds, mutual funds, and other specialized market players.
The PHEMU03 catalogue of observations of the mutual phenomena of the Galilean satellites of Jupiter
NASA Astrophysics Data System (ADS)
Arlot, J.-E.; Thuillot, W.; Ruatti, C.; Ahmad, A.; Amossé, A.; Anbazhagan, P.; Andreyev, M.; Antov, A.; Appakutty, M.; Asher, D.; Aubry, S.; Baron, N.; Bassiere, N.; Berthe, M.; Bogdanovski, R.; Bosq, F.; Bredner, E.; Buettner, D.; Buromsky, M.; Cammarata, S.; Casas, R.; Chis, G. D.; Christou, A. A.; Coquerel, J.-P.; Corlan, R.; Cremaschini, C.; Crussaire, D.; Cuypers, J.; Dennefeld, M.; Descamps, P.; Devyatkin, A.; Dimitrov, D.; Dorokhova, T. N.; Dorokhov, N. I.; Dourneau, G.; Dueñas, M.; Dumitrescu, A.; Emelianov, N.; Ferrara, D.; Fiel, D.; Fienga, A.; Flatres, T.; Foglia, S.; Garlitz, J.; Gerbos, J.; Gilbert, R.; Goncalves, R. M. D.; Gonzãles, D.; Gorda, S. Yu.; Gorshanov, D. L.; Hansen, M. W.; Harrington, M.; Irsmambetova, T. R.; Ito, Y.; Ivanova, V.; Izmailov, I. S.; Khovritchev, M. Yu.; Khrutskaya, E. V.; Kieken, J.; Kiseleva, T. P.; Kuppuswamy, K.; Lainey, V.; Lavayssiére, M.; Lazzarotti, P.; Le Campion, J.-F.; Lellouch, E.; Li, Z. L.; Lo Savio, E.; Lou, M.; Magny, E.; Manek, J.; Marinello, W.; Marino, G.; McAuliffe, J. P.; Michelli, M.; Moldovan, D.; Montagnac, S.; Moorthy, V.; Nickel, O.; Nier, J. M.; Noel, T.; Noyelles, B.; Oksanen, A.; Parrat, D.; Pauwels, T.; Peng, Q. Y.; Pizzetti, G.; Priban, V.; Ramachandran, B.; Rambaux, N.; Rapaport, M.; Rapavy, P.; Rau, G.; Sacré, J.-J.; Sada, P. V.; Salvaggio, F.; Sarlin, P.; Sciuto, C.; Selvakumar, G.; Sergeyev, A.; Sidorov, M.; Sorescu, S.; Spampinato, S. A.; Stellmacher, I.; Trunkovsky, E.; Tejfel, V.; Tudose, V.; Turcu, V.; Ugarte, I.; Vantyghem, P.; Vasundhara, R.; Vaubaillon, J.; Velu, C.; Venkataramana, A. K.; Vidal-Sãinz, J.; Vienne, A.; Vilar, J.; Vingerhoets, P.; Vollman, W.
2009-01-01
Context: In 2003, the Sun and the Earth passed through both the equatorial plane of Jupiter and therefore the orbital planes of its main satellites. Aims: During this period, mutual eclipses and occultations were observed and we present the data collected. Methods: Light curves of mutual eclipses and occultations were recorded by the observers of the international campaign PHEMU03 organized by the Institut de mécanique céleste, Paris, France. Results: We completed 377 observations of 118 mutual events from 42 sites and the corresponding data are presented in this paper. For each observation, information about the telescope, receptor, site, and observational conditions are provided. Conclusions: This paper gathers all data and indicates a first estimate of its precision. This catalogue of these rare events should constitute an improved basis for accurate astrometric data useful in the development of dynamical models. Table 4 and lightcurves (in ascii format) are only available in electronic form at the CDS via anonymous ftp to cdsarc.u-strasbg.fr (130.79.128.5) or via http://cdsweb.u-strasbg.fr/cgi-bin/qcat?J/A+A/493/1171
Kumar, Pardeep; Ylianttila, Mika; Gurtov, Andrei; Lee, Sang-Gon; Lee, Hoon-Jae
2014-01-01
Robust security is highly coveted in real wireless sensor network (WSN) applications since wireless sensors' sense critical data from the application environment. This article presents an efficient and adaptive mutual authentication framework that suits real heterogeneous WSN-based applications (such as smart homes, industrial environments, smart grids, and healthcare monitoring). The proposed framework offers: (i) key initialization; (ii) secure network (cluster) formation (i.e., mutual authentication and dynamic key establishment); (iii) key revocation; and (iv) new node addition into the network. The correctness of the proposed scheme is formally verified. An extensive analysis shows the proposed scheme coupled with message confidentiality, mutual authentication and dynamic session key establishment, node privacy, and message freshness. Moreover, the preliminary study also reveals the proposed framework is secure against popular types of attacks, such as impersonation attacks, man-in-the-middle attacks, replay attacks, and information-leakage attacks. As a result, we believe the proposed framework achieves efficiency at reasonable computation and communication costs and it can be a safeguard to real heterogeneous WSN applications. PMID:24521942
Kumar, Pardeep; Ylianttila, Mika; Gurtov, Andrei; Lee, Sang-Gon; Lee, Hoon-Jae
2014-01-01
Robust security is highly coveted in real wireless sensor network (WSN) applications since wireless sensors' sense critical data from the application environment. This article presents an efficient and adaptive mutual authentication framework that suits real heterogeneous WSN-based applications (such as smart homes, industrial environments, smart grids, and healthcare monitoring). The proposed framework offers: (i) key initialization; (ii) secure network (cluster) formation (i.e., mutual authentication and dynamic key establishment); (iii) key revocation; and (iv) new node addition into the network. The correctness of the proposed scheme is formally verified. An extensive analysis shows the proposed scheme coupled with message confidentiality, mutual authentication and dynamic session key establishment, node privacy, and message freshness. Moreover, the preliminary study also reveals the proposed framework is secure against popular types of attacks, such as impersonation attacks, man-in-the-middle attacks, replay attacks, and information-leakage attacks. As a result, we believe the proposed framework achieves efficiency at reasonable computation and communication costs and it can be a safeguard to real heterogeneous WSN applications. PMID:24521942
26 CFR 1.822-5 - Mutual insurance company taxable income.
Code of Federal Regulations, 2010 CFR
2010-04-01
... TAX (CONTINUED) INCOME TAXES Mutual Insurance Companies (other Than Life and Certain Marine Insurance... Premium Deposits) § 1.822-5 Mutual insurance company taxable income. (a) Mutual insurance company taxable... 26 Internal Revenue 8 2010-04-01 2010-04-01 false Mutual insurance company taxable income....
77 FR 73700 - Mutual of America Life Insurance Company, et al;
Federal Register 2010, 2011, 2012, 2013, 2014
2012-12-11
... COMMISSION Mutual of America Life Insurance Company, et al; Notice of Application December 5, 2012. AGENCY... the Act from Section 17(a) of the Act. APPLICANTS: Mutual of America Life Insurance Company (``Mutual... America Life Insurance Company, the ``Insurance Companies''), Mutual of America Separate Account No....
Weber, Thomas; Pelzer, Georg; Bayer, Florian; Horn, Florian; Rieger, Jens; Ritter, André; Zang, Andrea; Durst, Jürgen; Anton, Gisela; Michel, Thilo
2013-07-29
A novel information retrieval algorithm for X-ray grating-based phase-contrast imaging based on the deconvolution of the object and the reference phase stepping curve (PSC) as proposed by Modregger et al. was investigated in this paper. We applied the method for the first time on data obtained with a polychromatic spectrum and compared the results to those, received by applying the commonly used method, based on a Fourier analysis. We confirmed the expectation, that both methods deliver the same results for the absorption and the differential phase image. For the darkfield image, a mean contrast-to-noise ratio (CNR) increase by a factor of 1.17 using the new method was found. Furthermore, the dose saving potential was estimated for the deconvolution method experimentally. It is found, that for the conventional method a dose which is higher by a factor of 1.66 is needed to obtain a similar CNR value compared to the novel method. A further analysis of the data revealed, that the improvement in CNR and dose efficiency is due to the superior background noise properties of the deconvolution method, but at the cost of comparability between measurements at different applied dose values, as the mean value becomes dependent on the photon statistics used.
Weber, Thomas; Pelzer, Georg; Bayer, Florian; Horn, Florian; Rieger, Jens; Ritter, André; Zang, Andrea; Durst, Jürgen; Anton, Gisela; Michel, Thilo
2013-07-29
A novel information retrieval algorithm for X-ray grating-based phase-contrast imaging based on the deconvolution of the object and the reference phase stepping curve (PSC) as proposed by Modregger et al. was investigated in this paper. We applied the method for the first time on data obtained with a polychromatic spectrum and compared the results to those, received by applying the commonly used method, based on a Fourier analysis. We confirmed the expectation, that both methods deliver the same results for the absorption and the differential phase image. For the darkfield image, a mean contrast-to-noise ratio (CNR) increase by a factor of 1.17 using the new method was found. Furthermore, the dose saving potential was estimated for the deconvolution method experimentally. It is found, that for the conventional method a dose which is higher by a factor of 1.66 is needed to obtain a similar CNR value compared to the novel method. A further analysis of the data revealed, that the improvement in CNR and dose efficiency is due to the superior background noise properties of the deconvolution method, but at the cost of comparability between measurements at different applied dose values, as the mean value becomes dependent on the photon statistics used. PMID:23938672
Exploratory study of the impacts of Mutual Health Organizations on social dynamics in Benin.
Ridde, Valery; Haddad, Slim; Yacoubou, Moussa; Yacoubou, Ismaelou
2010-08-01
The primary aim of Mutual Health Organizations (MHOs) is the financial protection of their members. However, given their community-based, participative and voluntary nature, it is conceivable that MHOs, as social organizations, would affect social dynamics. In an exploratory study in Benin, we studied social dynamics related to mutual aid, relationships of trust, and empowerment. Four MHOs, as contrasted cases, were selected from among the 11 in the region. Focus groups (n = 20) and individual interviews (n = 29) were conducted with members, non-members, and elected leaders of the four MHOs, and with professionals from the health facilities concerned. We carried out a qualitative thematic analysis of the content. Mutual aid practices, which pre-date MHOs, can be mobilized to promote MHO membership. Mutual aid practices are based on relationships of trust. The primary reason for joining an MHO is to improve financial accessibility to health services. Non-members see that members have a strong sense of empowerment in this regard, based on a high level of trust in MHOs and their elected leaders, even if their trust in health professionals is not as strong. Non-members share these feelings of confidence in MHOs and their leadership, although they trust health professionals somewhat less than do the members. The MHOs' low penetration rate therefore cannot be explained by lack of trust, as this study shows that, even with some distrust of the professionals, the overall level of trust in MHOs is high and MHOs and their leaders function as intermediaries with health professionals. Other explanatory factors are the lack of information available to villagers and, most especially, the problems they face in being able to pay the MHO premiums.
Lessons learned from two peer-led mutual support groups.
Viverito, Kristen M; Cardin, Scott A; Johnson, Leigh Ann; Owen, Richard R
2013-10-01
This case report and analysis describe the formation of two peer-led mutual support groups conducted within the context of a Veterans Administration Medical Center. Based on our assessment of the success of one of these groups and the failure of the other, we offer several recommendations and suggestions to help promote this modality. More specifically, we hypothesize that such groups are more likely to be successful (1) if participants are transferred en masse from another group, (2) that, at least initially, housing the group in the same context as formal clinician-led groups or overlapping clinician-led and peer-led groups may help smooth the transition from authority-led treatment to a mutual peer support format, and finally, (3) that prior experiences in interpersonal process groups may promote the skills and cohesion to promote successful transition to mutual support. PMID:24004015
Homosexual mutuality: variation on a theme by Erik Erikson.
Sohier, R
The exploratory descriptive study described here was conducted in order to produce the initial empirical evidence to support reformulation of the theoretical construct of heterosexual mutuality (Erikson, 1975). Six persons were interviewed in depth on tape in order to locate them on one of four identity statuses constructed by Marcia (1964, 1966, 1973). The tool was modified and extended to meet the purposes of the study. The questions are directed toward illumination of conflictual moments in the life cycle when the ability to make appropriate decisions engenders character growth, and supports the personality integration of adulthood. An ability to make decisions results in personality integration. The small study provides evidence that there exists a homosexual mutuality (contrary to Erikson's position) which is no less valuable than heterosexual mutuality, and forms an equal basis for adult personality integration.
Empirical study of the tails of mutual fund size
NASA Astrophysics Data System (ADS)
Schwarzkopf, Yonathan; Farmer, J. Doyne
2010-06-01
The mutual fund industry manages about a quarter of the assets in the U.S. stock market and thus plays an important role in the U.S. economy. The question of how much control is concentrated in the hands of the largest players is best quantitatively discussed in terms of the tail behavior of the mutual fund size distribution. We study the distribution empirically and show that the tail is much better described by a log-normal than a power law, indicating less concentration than, for example, personal income. The results are highly statistically significant and are consistent across fifteen years. This contradicts a recent theory concerning the origin of the power law tails of the trading volume distribution. Based on the analysis in a companion paper, the log-normality is to be expected, and indicates that the distribution of mutual funds remains perpetually out of equilibrium.
Occurrence and characteristics of mutual interference between LIDAR scanners
NASA Astrophysics Data System (ADS)
Kim, Gunzung; Eom, Jeongsook; Park, Seonghyeon; Park, Yongwan
2015-05-01
The LIDAR scanner is at the heart of object detection of the self-driving car. Mutual interference between LIDAR scanners has not been regarded as a problem because the percentage of vehicles equipped with LIDAR scanners was very rare. With the growing number of autonomous vehicle equipped with LIDAR scanner operated close to each other at the same time, the LIDAR scanner may receive laser pulses from other LIDAR scanners. In this paper, three types of experiments and their results are shown, according to the arrangement of two LIDAR scanners. We will show the probability that any LIDAR scanner will interfere mutually by considering spatial and temporal overlaps. It will present some typical mutual interference scenario and report an analysis of the interference mechanism.
Long-range RNA pairings contribute to mutually exclusive splicing.
Yue, Yuan; Yang, Yun; Dai, Lanzhi; Cao, Guozheng; Chen, Ran; Hong, Weiling; Liu, Baoping; Shi, Yang; Meng, Yijun; Shi, Feng; Xiao, Mu; Jin, Yongfeng
2016-01-01
Mutually exclusive splicing is an important means of increasing the protein repertoire, by which the Down's syndrome cell adhesion molecule (Dscam) gene potentially generates 38,016 different isoforms in Drosophila melanogaster. However, the regulatory mechanisms remain obscure due to the complexity of the Dscam exon cluster. Here, we reveal a molecular model for the regulation of the mutually exclusive splicing of the serpent pre-mRNA based on competition between upstream and downstream RNA pairings. Such dual RNA pairings confer fine tuning of the inclusion of alternative exons. Moreover, we demonstrate that the splicing outcome of alternative exons is mediated in relative pairing strength-correlated mode. Combined comparative genomics analysis and experimental evidence revealed similar bidirectional structural architectures in exon clusters 4 and 9 of the Dscam gene. Our findings provide a novel mechanistic framework for the regulation of mutually exclusive splicing and may offer potentially applicable insights into long-range RNA-RNA interactions in gene regulatory networks.
Homosexual mutuality: variation on a theme by Erik Erikson.
Sohier, R
The exploratory descriptive study described here was conducted in order to produce the initial empirical evidence to support reformulation of the theoretical construct of heterosexual mutuality (Erikson, 1975). Six persons were interviewed in depth on tape in order to locate them on one of four identity statuses constructed by Marcia (1964, 1966, 1973). The tool was modified and extended to meet the purposes of the study. The questions are directed toward illumination of conflictual moments in the life cycle when the ability to make appropriate decisions engenders character growth, and supports the personality integration of adulthood. An ability to make decisions results in personality integration. The small study provides evidence that there exists a homosexual mutuality (contrary to Erikson's position) which is no less valuable than heterosexual mutuality, and forms an equal basis for adult personality integration. PMID:3835200
Mutual exclusivity in autism spectrum disorders: testing the pragmatic hypothesis.
de Marchena, Ashley; Eigsti, Inge-Marie; Worek, Amanda; Ono, Kim Emiko; Snedeker, Jesse
2011-04-01
While there is ample evidence that children treat words as mutually exclusive, the cognitive basis of this bias is widely debated. We focus on the distinction between pragmatic and lexical constraints accounts. High-functioning children with autism spectrum disorders (ASD) offer a unique perspective on this debate, as they acquire substantial vocabularies despite impoverished social-pragmatic skills. We tested children and adolescents with ASD in a paradigm examining mutual exclusivity for words and facts. Words were interpreted contrastively more often than facts. Word performance was associated with vocabulary size; fact performance was associated with social-communication skills. Thus mutual exclusivity does not appear to be driven by pragmatics, suggesting that it is either a lexical constraint or a reflection of domain-general learning processes.
Wulff, Janie L
2008-05-01
Mutualism can be favored over exploitation of mutualism when interests of potential heterospecific partners are aligned so that individual organisms are beneficial to each others' continued growth, survival, and reproduction, that is, when exploitation of a particular partner individual is costly. A coral reef sponge system is particularly amenable to field experiments probing how costs of exploitation can be influenced by life-history characteristics. Pairwise associations among three of the sponge species are mutually beneficial. A fourth species, Desmapsamma anchorata, exploits these mutualisms. Desmapsamma also differs from the other species by growing faster, fragmenting more readily, and suffering higher mortality rates. Evaluating costs and benefits of association in the context of the complex life histories of these asexually fragmenting sponges shows costs of exploitation to be high for the mutualistic species but very low for this essentially weedy species. Although it benefits from association more than the mutualist species, by relying on their superior tensile strength and extensibility to reduce damage by physical disturbance, exploitation is favored because each individual host is of only ephemeral use. These sponges illustrate how life-history differences can influence the duration of association between individuals and, thus, the role of partner fidelity in promoting mutualism. PMID:18419569