SCALABLE APPROXIMATION OF KERNEL FUZZY C-MEANS

Virtually every sector of business and industry that uses computing, including financial analysis, search engines, and electronic commerce, incorporate Big Data analysis into their business model. Sophisticated clustering algorithms are popular for deducing the nature of data by assigning labels to unlabeled data. We address two main challenges in Big Data. First, by definition, the volume of Big Data is too large to be loaded into a computer’s memory (this volume changes based on the computer used or available, but there is always a data set that is too large for any computer). Second, in real-time applications, the velocity of new incoming data prevents historical data from being stored and future data from being accessed. Therefore, we propose our Streaming Kernel Fuzzy c-Means (stKFCM) algorithm, which reduces both computational complexity and space complexity significantly. The proposed stKFCM only requires O(n2) memory where n is the (predetermined) size of a data subset (or data chunk) at each time step, which makes this algorithm truly scalable (as n can be chosen based on the available memory). Furthermore, only 2n2 elements of the full N × N (where N >> n) kernel matrix need to be calculated at each time-step, thus reducing both the computation time in producing the kernel elements and also the complexity of the FCM algorithm. Empirical results show that stKFCM, even with relatively very small n, can provide clustering performance as accurately as kernel fuzzy c-means run on the entire data set while achieving a significant speedup.

Gestione automatica di namespace di rete privati in ambienti linux

Sempre più sono i servizi offerti oggigiorno sul cloud. L’isolamento dei vari utenti diviene una componente fondamentale se si vuole proteggere la privacy e la confidenzialità dei dati dei clienti. Mantenere una struttura che offre questo genere di servizi però è estremamente complesso ed oneroso. Si vuole mostrare come sia possibile evitare la creazione di centinaia di migliaia di macchine virtuali, quando potrebbe bastare creare una macchina virtuale per tipo di servizio offerto, e far accedere ogni cliente che necessita di quel servizio semplicemente isolandolo con linux namespace, in maniera automatica.

Heat kernel and worldline path integrals for the Proca theory

In this thesis we study the heat kernel, a useful tool to analyze various properties of different quantum field theories. In particular, we focus on the study of the one-loop effective action and the application of worldline path integrals to derive perturbatively the heat kernel coefficients for the Proca theory of massive vector fields. It turns out that the worldline path integral method encounters some difficulties if the differential operator of the heat kernel is of non-minimal kind. More precisely, a direct recasting of the differential operator in terms of worldline path integrals, produces in the classical action a non-perturbative vertex and the path integral cannot be solved. In this work we wish to find ways to circumvent this issue and to give a suggestion to solve similar problems in other contexts.

Un framework per la gestione di moduli di insider threat detection basati su eBPF

Gli Insider Threat sono una problematica complessa e rappresentano una delle problematiche più costose per le organizzazioni: questi ultimi possono, potenzialmente, realizzare grandi guadagni dalle informazioni sottratte danneggiando i clienti e provocando danni irreparabili all’organizzazione. Screening effettuati prima dell’assunzione e la costruzione di un relazione di fiducia basata sulla collaborazione rimangono fondamentali ma, spesso, non sono sufficienti ed è bene integrare il processo di difesa da insider threat all’interno delle business operation. Date queste precondizioni, l’obiettivo di questa tesi è stato quello di cercare un approccio sistematico per affrontare il problema dell’Insider Threat e di fornire nuovi strumenti per la sua detection altamente specializzati nel campo della cyber-security. Dato il campo applicativo, risulta fondamentale rendere questo processo totalmente trasparente al potenziale insider threat. Le più moderne tecniche di hiding, prese dai moderni malware, sono state implementate utilizzando eBPF rendendo possibile unire una quasi totale invisibilità unita alla stabilità garantita da questa tecnologia.

Caracterização sensorial de amêndoas de castanha-de-caju fritas e salgadas

Shelled, roasted and salted cashew nut kernels were packaged in three different flexible materials (PP/PE= polypropylene / polyethylene; PETmet/PE= metallized polyethylene terephthalate / polyethylene; PET/Al/LDPE= polyethylene terephthalate / aluminum foil / low density polyethylene ), with different barrier properties. Kernels were stored for one year at 30° C and 80% relative humidity. Quantitative descriptive sensory analysis (QDA) were performed at the end of storage time. Descriptive terms obtained for kernels characterization were brown color, color uniformity and rugosity for appearance; toasted kernel, sweet, old and rancidity for odor; toasted kernel, sweet, old rancidity, salt and bitter for taste, crispness for texture. QDA showed that factors responsible for sensory quality decrease, after one year storage, were increase in old aroma and taste, increase in rancidity aroma and taste, decrease in roasted kernel aroma and taste, and decrease of crispness. Sensory quality decrease was higher in kernels packaged in PP/PE.

Modelo de inclusão digital para construção do conhecimento em qualidade de vida e atividade fisica

Universidade Estadual de Campinas. Faculdade de Educação Física

O risco espacial e fatores associados ao edentulismo em idosos em município do Sudeste do Brasil

Objetivou-se identificar fatores associados ao edentulismo e o seu risco espacial em idosos. Foi realizado um estudo transversal em uma amostra de 372 indivíduos de 60 anos e mais, no Município de Botucatu, São Paulo, Brasil, em 2005. Razões de prevalência brutas e ajustadas foram estimadas por meio de regressão de Poisson, com estimativa robusta da variância e procedimentos de modelagem hierárquica. A análise espacial foi realizada por estimativas de densidade de Kernel. A prevalência de edentulismo foi de 63,17%. Os fatores sociodemográficos associados ao edentulismo foram a baixa escolaridade, o aumento do número de pessoas por cômodo, não possuir automóvel e idade mais avançada, presença de comorbidades, ausência de um cirurgião-dentista regular e ter realizado a última consulta há três anos ou mais. A análise espacial mostrou maior risco nas áreas periféricas. Obteve-se uma melhor compreensão da perda dentária entre os idosos, subsidiando o planejamento de ações em saúde coletiva.

Evaluation of corn cultivars harvested at two cutting heights for ensilage

The objective of this study was to evaluate the agronomic characteristics, bromatological-chemical composition and digestibility of 11 corn cultivars (Zea mays) harvested at two cutting heights. Cultivars D 766, D 657, D 1000, P 3021, P 3041, C 805, C 333, AG 5011, FO 01, CO 9621 and BR 205 were evaluated when they were harvested 5 cm above ground (low) and 5 cm below the insertion of the first ear (high). The experiment was designed as random blocks, with three replicates, arranged in an 11 x 2 factorial scheme. Cultivars presented similar productions of forage dry matter and grains. Percentages of stalk, leaf, straw, cob and kernel fractions were different among cultivars, as well as dry matter content of the whole plant at harvest. Considering the whole plant, only the contents of gross energy, nitrogen in neutral detergent fiber, and in vitro neutral and acid detergent fiber digestibility did not differ among cultivars. Increase on the cutting height improved forage quality due to the reduction of stalk and leaf fractions and contents of cell wall constituents.

Stability and ergodicity of piecewise deterministic Markov processes

The main goal of this paper is to establish some equivalence results on stability, recurrence, and ergodicity between a piecewise deterministic Markov process ( PDMP) {X( t)} and an embedded discrete-time Markov chain {Theta(n)} generated by a Markov kernel G that can be explicitly characterized in terms of the three local characteristics of the PDMP, leading to tractable criterion results. First we establish some important results characterizing {Theta(n)} as a sampling of the PDMP {X( t)} and deriving a connection between the probability of the first return time to a set for the discrete-time Markov chains generated by G and the resolvent kernel R of the PDMP. From these results we obtain equivalence results regarding irreducibility, existence of sigma-finite invariant measures, and ( positive) recurrence and ( positive) Harris recurrence between {X( t)} and {Theta(n)}, generalizing the results of [ F. Dufour and O. L. V. Costa, SIAM J. Control Optim., 37 ( 1999), pp. 1483-1502] in several directions. Sufficient conditions in terms of a modified Foster-Lyapunov criterion are also presented to ensure positive Harris recurrence and ergodicity of the PDMP. We illustrate the use of these conditions by showing the ergodicity of a capacity expansion model.

Precision of distances and ordering of microsatellite markers in consensus linkage maps of chromosomes 1, 3 and 4 from two reciprocal chicken populations using bootstrap sampling

Some factors complicate comparisons between linkage maps from different studies. This problem can be resolved if measures of precision, such as confidence intervals and frequency distributions, are associated with markers. We examined the precision of distances and ordering of microsatellite markers in the consensus linkage maps of chromosomes 1, 3 and 4 from two F 2 reciprocal Brazilian chicken populations, using bootstrap sampling. Single and consensus maps were constructed. The consensus map was compared with the International Consensus Linkage Map and with the whole genome sequence. Some loci showed segregation distortion and missing data, but this did not affect the analyses negatively. Several inversions and position shifts were detected, based on 95% confidence intervals and frequency distributions of loci. Some discrepancies in distances between loci and in ordering were due to chance, whereas others could be attributed to other effects, including reciprocal crosses, sampling error of the founder animals from the two populations, F(2) population structure, number of and distance between microsatellite markers, number of informative meioses, loci segregation patterns, and sex. In the Brazilian consensus GGA1, locus LEI1038 was in a position closer to the true genome sequence than in the International Consensus Map, whereas for GGA3 and GGA4, no such differences were found. Extending these analyses to the remaining chromosomes should facilitate comparisons and the integration of several available genetic maps, allowing meta-analyses for map construction and quantitative trait loci (QTL) mapping. The precision of the estimates of QTL positions and their effects would be increased with such information.

Nilpotent noncommutativity and renormalization

We analyze renormalizability properties of noncommutative (NC) theories with a bifermionic NC parameter. We introduce a new four-dimensional scalar field model which is renormalizable at all orders of the loop expansion. We show that this model has an infrared stable fixed point (at the one-loop level). We check that the NC QED (which is one-loop renormalizable with a usual NC parameter) remains renormalizable when the NC parameter is bifermionic, at least to the extent of one-loop diagrams with external photon legs. Our general conclusion is that bifermionic noncommutativity improves renormalizability properties of NC theories.

Support vector machines for detecting age-related changes in running kinematics

Age-related changes in running kinematics have been reported in the literature using classical inferential statistics. However, this approach has been hampered by the increased number of biomechanical gait variables reported and subsequently the lack of differences presented in these studies. Data mining techniques have been applied in recent biomedical studies to solve this problem using a more general approach. In the present work, we re-analyzed lower extremity running kinematic data of 17 young and 17 elderly male runners using the Support Vector Machine (SVM) classification approach. In total, 31 kinematic variables were extracted to train the classification algorithm and test the generalized performance. The results revealed different accuracy rates across three different kernel methods adopted in the classifier, with the linear kernel performing the best. A subsequent forward feature selection algorithm demonstrated that with only six features, the linear kernel SVM achieved 100% classification performance rate, showing that these features provided powerful combined information to distinguish age groups. The results of the present work demonstrate potential in applying this approach to improve knowledge about the age-related differences in running gait biomechanics and encourages the use of the SVM in other clinical contexts. (C) 2010 Elsevier Ltd. All rights reserved.

THE VANISHING DISCOUNT APPROACH FOR THE AVERAGE CONTINUOUS CONTROL OF PIECEWISE DETERMINISTIC MARKOV PROCESSES

This work is concerned with the existence of an optimal control strategy for the long-run average continuous control problem of piecewise-deterministic Markov processes (PDMPs). In Costa and Dufour (2008), sufficient conditions were derived to ensure the existence of an optimal control by using the vanishing discount approach. These conditions were mainly expressed in terms of the relative difference of the alpha-discount value functions. The main goal of this paper is to derive tractable conditions directly related to the primitive data of the PDMP to ensure the existence of an optimal control. The present work can be seen as a continuation of the results derived in Costa and Dufour (2008). Our main assumptions are written in terms of some integro-differential inequalities related to the so-called expected growth condition, and geometric convergence of the post-jump location kernel associated to the PDMP. An example based on the capacity expansion problem is presented, illustrating the possible applications of the results developed in the paper.

Generalized Coupled Algebraic Riccati Equations for Discrete-time Markov Jump with Multiplicative Noise Systems

In this paper we consider the existence of the maximal and mean square stabilizing solutions for a set of generalized coupled algebraic Riccati equations (GCARE for short) associated to the infinite-horizon stochastic optimal control problem of discrete-time Markov jump with multiplicative noise linear systems. The weighting matrices of the state and control for the quadratic part are allowed to be indefinite. We present a sufficient condition, based only on some positive semi-definite and kernel restrictions on some matrices, under which there exists the maximal solution and a necessary and sufficient condition under which there exists the mean square stabilizing solution fir the GCARE. We also present a solution for the discounted and long run average cost problems when the performance criterion is assumed be composed by a linear combination of an indefinite quadratic part and a linear part in the state and control variables. The paper is concluded with a numerical example for pension fund with regime switching.