Application of fuzzy-rule-based postprocessing to correlation methods in pattern recognition

One of the most important problems in optical pattern recognition by correlation is the appearance of sidelobes in the correlation plane, which causes false alarms. We present a method that eliminate sidelobes of up to a given height if certain conditions are satisfied. The method can be applied to any generalized synthetic discriminant function filter and is capable of rejecting lateral peaks that are even higher than the central correlation. Satisfactory results were obtained in both computer simulations and optical implementation.

Clustering in complex networks. I. General formalism

We develop a full theoretical approach to clustering in complex networks. A key concept is introduced, the edge multiplicity, that measures the number of triangles passing through an edge. This quantity extends the clustering coefficient in that it involves the properties of two¿and not just one¿vertices. The formalism is completed with the definition of a three-vertex correlation function, which is the fundamental quantity describing the properties of clustered networks. The formalism suggests different metrics that are able to thoroughly characterize transitive relations. A rigorous analysis of several real networks, which makes use of this formalism and the metrics, is also provided. It is also found that clustered networks can be classified into two main groups: the weak and the strong transitivity classes. In the first class, edge multiplicity is small, with triangles being disjoint. In the second class, edge multiplicity is high and so triangles share many edges. As we shall see in the following paper, the class a network belongs to has strong implications in its percolation properties.

Clustering in complex networks. II. Percolation properties

The percolation properties of clustered networks are analyzed in detail. In the case of weak clustering, we present an analytical approach that allows us to find the critical threshold and the size of the giant component. Numerical simulations confirm the accuracy of our results. In more general terms, we show that weak clustering hinders the onset of the giant component whereas strong clustering favors its appearance. This is a direct consequence of the differences in the k-core structure of the networks, which are found to be totally different depending on the level of clustering. An empirical analysis of a real social network confirms our predictions.

Tuning clustering in random networks with arbitrary degree distributions

We present a generator of random networks where both the degree-dependent clustering coefficient and the degree distribution are tunable. Following the same philosophy as in the configuration model, the degree distribution and the clustering coefficient for each class of nodes of degree k are fixed ad hoc and a priori. The algorithm generates corresponding topologies by applying first a closure of triangles and second the classical closure of remaining free stubs. The procedure unveils an universal relation among clustering and degree-degree correlations for all networks, where the level of assortativity establishes an upper limit to the level of clustering. Maximum assortativity ensures no restriction on the decay of the clustering coefficient whereas disassortativity sets a stronger constraint on its behavior. Correlation measures in real networks are seen to observe this structural bound.

Conserved chromosomal clustering of genes governed by chromatin regulators in Drosophila

Background: The trithorax group (trxG) and Polycomb group (PcG) proteins are responsible for the maintenance of stable transcriptional patterns of many developmental regulators. They bind to specific regions of DNA and direct the post-translational modifications of histones, playing a role in the dynamics of chromatin structure.Results: We have performed genome-wide expression studies of trx and ash2 mutants in Drosophila melanogaster. Using computational analysis of our microarray data, we have identified 25 clusters of genes potentially regulated by TRX. Most of these clusters consist of genes that encode structural proteins involved in cuticle formation. This organization appears to be a distinctive feature of the regulatory networks of TRX and other chromatin regulators, since we have observed the same arrangement in clusters after experiments performed with ASH2, as well as in experiments performed by others with NURF, dMyc, and ASH1. We have also found many of these clusters to be significantly conserved in D. simulans, D. yakuba, D. pseudoobscura and partially in Anopheles gambiae.Conclusion: The analysis of genes governed by chromatin regulators has led to the identification of clusters of functionally related genes conserved in other insect species, suggesting this chromosomal organization is biologically important. Moreover, our results indicate that TRX and other chromatin regulators may act globally on chromatin domains that contain transcriptionally co-regulated genes.

Dramatic decline of serogrup C meningococcal disease incidence in Catalonia (Spain) 24 months after a mass vaccination programme of children and young people

STUDY OBJECTIVES The objective of this study was to evaluate the effectiveness of a mass vaccination programme carried out in Catalonia (Spain) in the last quarter of 1997 in response to an upsurge of serogroup C meningococcal disease (SCMD). DESIGN Vaccination coverage in the 18 month to 19 years age group was investigated by means of a specific vaccination register. Vaccination effectiveness was calculated using the prospective cohort method. Cases of SCMD were identified on the basis of compulsory reporting and microbiological notification by hospital laboratories. Vaccination histories were investigated in all cases. Unadjusted and age adjusted vaccination effectiveness referred to the time of vaccination and the corresponding 95% confidence intervals (CI) were estimated at 6, 12, 18 and 24 months of follow up. SETTING All population aged 18 months to 19 years of Catalonia. MAIN RESULTS A total of seven cases of SCMD were detected at six months of follow up (one in the vaccinated cohort), 12 cases at 12 months (one in the vaccinated cohort), 19 cases at 18 months (two in the vaccinated cohort) and 24 at 24 months (two in the vaccinated cohort). The age adjusted effectiveness was 84% (95%CI 30, 97) at six months, 92% (95%CI 63, 98) at 12 months, 92% (95% CI 71, 98) at 18 months and 94% (95%CI 78, 98) at 24 months. In the target population, cases have been reduced by more than two thirds (68%) two years after the vaccination programme. In the total population the reduction was 43%. CONCLUSION Vaccination effectiveness has been high in Catalonia, with a dramatic reduction in disease incidence in the vaccinated cohort accompanied by a relevant reduction in the overall population. Given that vaccination coverage was only 54.6%, it may be supposed that this vaccination effectiveness is attributable, in part, to the herd immunity conferred by the vaccine.

A fuzzy-based decision model application on strategic management

In this article, the objective is to demonstrate the effects of different decision styles on strategic decisions and likewise, on an organization. The technique that was presented in the study is based on the transformation of linguistic variables to numerical value intervals. In this model, the study benefits from fuzzy logic methodology and fuzzy numbers. This fuzzy methodology approach allows us to examine the relations between decision making styles and strategic management processes when there is uncertainty. The purpose is to provide results to companies that may help them to exercise the most appropriate decision making style for its different strategic management processes. The study is leaving more research topics for further studies that may be applied to other decision making areas within the strategic management process.

Deciphering the global organization of clustering in real complex networks

We uncover the global organization of clustering in real complex networks. To this end, we ask whether triangles in real networks organize as in maximally random graphs with given degree and clustering distributions, or as in maximally ordered graph models where triangles are forced into modules. The answer comes by way of exploring m-core landscapes, where the m-core is defined, akin to the k-core, as the maximal subgraph with edges participating in at least m triangles. This property defines a set of nested subgraphs that, contrarily to k-cores, is able to distinguish between hierarchical and modular architectures. We find that the clustering organization in real networks is neither completely random nor ordered although, surprisingly, it is more random than modular. This supports the idea that the structure of real networks may in fact be the outcome of self-organized processes based on local optimization rules, in contrast to global optimization principles.

Neural networks complemented with genetic algorithms and fuzzy systems for predicting nitrogenous effluent variables in wastewater treatment plants

This work focuses on the prediction of the two main nitrogenous variables that describe the water quality at the effluent of a Wastewater Treatment Plant. We have developed two kind of Neural Networks architectures based on considering only one output or, in the other hand, the usual five effluent variables that define the water quality: suspended solids, biochemical organic matter, chemical organic matter, total nitrogen and total Kjedhal nitrogen. Two learning techniques based on a classical adaptative gradient and a Kalman filter have been implemented. In order to try to improve generalization and performance we have selected variables by means genetic algorithms and fuzzy systems. The training, testing and validation sets show that the final networks are able to learn enough well the simulated available data specially for the total nitrogen

Amplification and displacement of chaotic attractors by means of unidirectional chaotic driving

Chaotic systems, when used to drive copies of themselves (or parts of themselves) may induce interesting behaviors in the driven system. In case the later exhibits invariance under amplification or translation, they may show amplification (reduction), or displacement of the attractor. It is shown how the behavior to be obtained is implied by the symmetries involved. Two explicit examples are studied to show how these phenomena manifest themselves under perfect and imperfect coupling.

Early diagnosis of osteoporosis by means of orthopantomograms and oral x-rays: a systematic review

Osteoporosis is a systemic bone disease that is characterized by a generalized reduction of the bone mass. It is the main cause of fractures in elderly women. Bone densitometry is used in the lumbar spine and hip in order to detect osteoporosis in its early stages. Different studies have observed a correlation between the bone mineral density of the jaw (BMD) and that of the lumbar spine and/or hip. On the other hand, there are studies that evaluate the findings in the orthopantomograms and perapical X-rays, correlating them with the early diagnosis of osteoporosis and highlighting the role of the dentist in the early diagnosis of this disease. Materials and methods: A search was carried out in the Medline-Pubmed database in order to identify those articles that deal with the association between the X-ray findings observed in the orthopantomograms and the diagnosis of the osteoporosis, as well as those that deal with the bone mineral density of the jaw. Results: There were 406 articles, and with the limits established, this number was reduced to 21. Almost all of the articles indicate that when examining oral X-rays, it is possible to detect signs indicative of osteoporosis. Discussion: The radiomorphometric indices use measurements in orthopantomograms and evaluate possible loss of bone mineral density. They can be analyzed alone or along with the visual indices. In the periapical X-rays, the photodensimetric analyses and the trabecular pattern appear to be the most useful. There are seven studies that analyze the densitometry of the jaw, but only three do so independently of the photodensitometric analysis. Conclusions: The combination of mandibular indices, along with surveys on the risk of fracture, can be useful as indicators of early diagnosis of osteoporosis. Visual and morphometric indices appear to be especially important in the orthopantomograms. Photodensitometry indices and the trabecular pattern are used in periapical X-rays. Studies on mandibular dual-energy X-ray absorptiometry are inconclusive

An expression of mixed animal model equations to account for different means and variances in the base population

This paper presents a general expression to predict breeding values using animal models when the base population is selected, i.e. the means and variances of breeding values in the base generation differ among individuals. Rules for forming the mixed model equations are also presented. A numerical example illustrates the procedure.

Formalizing argumentative reasoning in a possibilistic logic programming setting with fuzzy unification

Possibilistic Defeasible Logic Programming (P-DeLP) is a logic programming language which combines features from argumentation theory and logic programming, incorporating the treatment of possibilistic uncertainty at the object-language level. In spite of its expressive power, an important limitation in P-DeLP is that imprecise, fuzzy information cannot be expressed in the object language. One interesting alternative for solving this limitation is the use of PGL+, a possibilistic logic over Gödel logic extended with fuzzy constants. Fuzzy constants in PGL+ allow expressing disjunctive information about the unknown value of a variable, in the sense of a magnitude, modelled as a (unary) predicate. The aim of this article is twofold: firstly, we formalize DePGL+, a possibilistic defeasible logic programming language that extends P-DeLP through the use of PGL+ in order to incorporate fuzzy constants and a fuzzy unification mechanism for them. Secondly, we propose a way to handle conflicting arguments in the context of the extended framework.

Diagnosis of Alzheimer’s Disease from EEG by Means of Synchrony Measures in Optimized Frequency Bands

Several clinical studies have reported that EEG synchrony is affected by Alzheimer’s disease (AD). In this paper a frequency band analysis of AD EEG signals is presented, with the aim of improving the diagnosis of AD using EEG signals. In this paper, multiple synchrony measures are assessed through statistical tests (Mann–Whitney U test), including correlation, phase synchrony and Granger causality measures. Moreover, linear discriminant analysis (LDA) is conducted with those synchrony measures as features. For the data set at hand, the frequency range (5-6Hz) yields the best accuracy for diagnosing AD, which lies within the classical theta band (4-8Hz). The corresponding classification error is 4.88% for directed transfer function (DTF) Granger causality measure. Interestingly, results show that EEG of AD patients is more synchronous than in healthy subjects within the optimized range 5-6Hz, which is in sharp contrast with the loss of synchrony in AD EEG reported in many earlier studies. This new finding may provide new insights about the neurophysiology of AD. Additional testing on larger AD datasets is required to verify the effectiveness of the proposed approach.

Study of Johnsons Glacier (Livingston Island, Antarctica) by means of shallow ice cores and their tephra and by analysis of 137Cs content

With the aim of monitoring the dynamics of the Livingston Island ice cap, the Departament de Geodinàmica i Geofísica of the Universitat de Barcelona began ye a r ly surveys in the austral summer of 1994-95 on Johnsons Glacier. During this field campaign 10 shallow ice cores were sampled with a manual ve rtical ice-core drilling machine. The objectives were: i) to detect the tephra layer accumulated on the glacier surface, attributed to the 1970 Deception Island pyroclastic eruption, today interstratified; ii) to verify wheter this layer might serve as a reference level; iii) to measure the 1 3 7Cs radio-isotope concentration accumulated in the 1965 snow stratum; iv) to use the isochrone layer as a mean of verifying the age of the 1970 tephra layer; and, v) to calculate both the equilibrium line of the glacier and average mass balance over the last 28 years (1965-1993). The stratigr a p hy of the cores, their cumulative density curves and the isothermal ice temperatures recorded confi rm that Johnsons Glacier is a temperate glacier. Wi n d, solar radiation heating and liquid water are the main agents controlling the ve rtical and horizontal redistribution of the volcanic and cryoclastic particles that are sedimented and remain interstratified within the g l a c i e r. It is because of this redistribution that the 1970 tephra layer does not always serve as a ve ry good reference level. The position of the equilibrium line altitude (ELA) in 1993, obtained by the 1 3 7Cs spectrometric analysis, varies from about 200 m a.s.l. to 250 m a.s.l. This indicates a rising trend in the equilibrium line altitude from the beginning of the 1970s to the present day. The va rying slope orientation of Johnsons Glacier relative to the prevailing NE wind gives rise to large local differences in snow accumulation, which locally modifies the equilibrium line altitude. In the cores studied, 1 3 7Cs appears to be associated with the 1970 tephra laye r. This indicates an intense ablation episode throughout the sampled area (at least up to 330 m a.s.l), which probably occurred synchronically to the 1970 tephra deposition or later. A rough estimate of the specific mass balance reveals a considerable accumulation gradient related to the increase with altitude.