903 resultados para Incidence Matrix


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Random effect models have been widely applied in many fields of research. However, models with uncertain design matrices for random effects have been little investigated before. In some applications with such problems, an expectation method has been used for simplicity. This method does not include the extra information of uncertainty in the design matrix is not included. The closed solution for this problem is generally difficult to attain. We therefore propose an two-step algorithm for estimating the parameters, especially the variance components in the model. The implementation is based on Monte Carlo approximation and a Newton-Raphson-based EM algorithm. As an example, a simulated genetics dataset was analyzed. The results showed that the proportion of the total variance explained by the random effects was accurately estimated, which was highly underestimated by the expectation method. By introducing heuristic search and optimization methods, the algorithm can possibly be developed to infer the 'model-based' best design matrix and the corresponding best estimates.

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Partially supported by the Bulgarian Science Fund contract with TU Varna, No 487.

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One of the tantalising remaining problems in compositional data analysis lies in how to deal with data sets in which there are components which are essential zeros. By anessential zero we mean a component which is truly zero, not something recorded as zero simply because the experimental design or the measuring instrument has not been sufficiently sensitive to detect a trace of the part. Such essential zeros occur inmany compositional situations, such as household budget patterns, time budgets,palaeontological zonation studies, ecological abundance studies. Devices such as nonzero replacement and amalgamation are almost invariably ad hoc and unsuccessful insuch situations. From consideration of such examples it seems sensible to build up amodel in two stages, the first determining where the zeros will occur and the secondhow the unit available is distributed among the non-zero parts. In this paper we suggest two such models, an independent binomial conditional logistic normal model and a hierarchical dependent binomial conditional logistic normal model. The compositional data in such modelling consist of an incidence matrix and a conditional compositional matrix. Interesting statistical problems arise, such as the question of estimability of parameters, the nature of the computational process for the estimation of both the incidence and compositional parameters caused by the complexity of the subcompositional structure, the formation of meaningful hypotheses, and the devising of suitable testing methodology within a lattice of such essential zero-compositional hypotheses. The methodology is illustrated by application to both simulated and real compositional data

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Les systèmes multiprocesseurs sur puce électronique (On-Chip Multiprocessor [OCM]) sont considérés comme les meilleures structures pour occuper l'espace disponible sur les circuits intégrés actuels. Dans nos travaux, nous nous intéressons à un modèle architectural, appelé architecture isométrique de systèmes multiprocesseurs sur puce, qui permet d'évaluer, de prédire et d'optimiser les systèmes OCM en misant sur une organisation efficace des nœuds (processeurs et mémoires), et à des méthodologies qui permettent d'utiliser efficacement ces architectures. Dans la première partie de la thèse, nous nous intéressons à la topologie du modèle et nous proposons une architecture qui permet d'utiliser efficacement et massivement les mémoires sur la puce. Les processeurs et les mémoires sont organisés selon une approche isométrique qui consiste à rapprocher les données des processus plutôt que d'optimiser les transferts entre les processeurs et les mémoires disposés de manière conventionnelle. L'architecture est un modèle maillé en trois dimensions. La disposition des unités sur ce modèle est inspirée de la structure cristalline du chlorure de sodium (NaCl), où chaque processeur peut accéder à six mémoires à la fois et où chaque mémoire peut communiquer avec autant de processeurs à la fois. Dans la deuxième partie de notre travail, nous nous intéressons à une méthodologie de décomposition où le nombre de nœuds du modèle est idéal et peut être déterminé à partir d'une spécification matricielle de l'application qui est traitée par le modèle proposé. Sachant que la performance d'un modèle dépend de la quantité de flot de données échangées entre ses unités, en l'occurrence leur nombre, et notre but étant de garantir une bonne performance de calcul en fonction de l'application traitée, nous proposons de trouver le nombre idéal de processeurs et de mémoires du système à construire. Aussi, considérons-nous la décomposition de la spécification du modèle à construire ou de l'application à traiter en fonction de l'équilibre de charge des unités. Nous proposons ainsi une approche de décomposition sur trois points : la transformation de la spécification ou de l'application en une matrice d'incidence dont les éléments sont les flots de données entre les processus et les données, une nouvelle méthodologie basée sur le problème de la formation des cellules (Cell Formation Problem [CFP]), et un équilibre de charge de processus dans les processeurs et de données dans les mémoires. Dans la troisième partie, toujours dans le souci de concevoir un système efficace et performant, nous nous intéressons à l'affectation des processeurs et des mémoires par une méthodologie en deux étapes. Dans un premier temps, nous affectons des unités aux nœuds du système, considéré ici comme un graphe non orienté, et dans un deuxième temps, nous affectons des valeurs aux arcs de ce graphe. Pour l'affectation, nous proposons une modélisation des applications décomposées en utilisant une approche matricielle et l'utilisation du problème d'affectation quadratique (Quadratic Assignment Problem [QAP]). Pour l'affectation de valeurs aux arcs, nous proposons une approche de perturbation graduelle, afin de chercher la meilleure combinaison du coût de l'affectation, ceci en respectant certains paramètres comme la température, la dissipation de chaleur, la consommation d'énergie et la surface occupée par la puce. Le but ultime de ce travail est de proposer aux architectes de systèmes multiprocesseurs sur puce une méthodologie non traditionnelle et un outil systématique et efficace d'aide à la conception dès la phase de la spécification fonctionnelle du système.

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One of the tantalising remaining problems in compositional data analysis lies in how to deal with data sets in which there are components which are essential zeros. By an essential zero we mean a component which is truly zero, not something recorded as zero simply because the experimental design or the measuring instrument has not been sufficiently sensitive to detect a trace of the part. Such essential zeros occur in many compositional situations, such as household budget patterns, time budgets, palaeontological zonation studies, ecological abundance studies. Devices such as nonzero replacement and amalgamation are almost invariably ad hoc and unsuccessful in such situations. From consideration of such examples it seems sensible to build up a model in two stages, the first determining where the zeros will occur and the second how the unit available is distributed among the non-zero parts. In this paper we suggest two such models, an independent binomial conditional logistic normal model and a hierarchical dependent binomial conditional logistic normal model. The compositional data in such modelling consist of an incidence matrix and a conditional compositional matrix. Interesting statistical problems arise, such as the question of estimability of parameters, the nature of the computational process for the estimation of both the incidence and compositional parameters caused by the complexity of the subcompositional structure, the formation of meaningful hypotheses, and the devising of suitable testing methodology within a lattice of such essential zero-compositional hypotheses. The methodology is illustrated by application to both simulated and real compositional data

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An incidence matrix analysis is used to model a three-dimensional network consisting of resistive and capacitive elements distributed across several interconnected layers. A systematic methodology for deriving a descriptor representation of the network with random allocation of the resistors and capacitors is proposed. Using a transformation of the descriptor representation into standard state-space form, amplitude and phase admittance responses of three-dimensional random RC networks are obtained. Such networks display an emergent behavior with a characteristic Jonscher-like response over a wide range of frequencies. A model approximation study of these networks is performed to infer the admittance response using integral and fractional order models. It was found that a fractional order model with only seven parameters can accurately describe the responses of networks composed of more than 70 nodes and 200 branches with 100 resistors and 100 capacitors. The proposed analysis can be used to model charge migration in amorphous materials, which may be associated to specific macroscopic or microscopic scale fractal geometrical structures in composites displaying a viscoelastic electromechanical response, as well as to model the collective responses of processes governed by random events described using statistical mechanics.

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We discuss the modeling of dielectric responses of electromagnetically excited networks which are composed of a mixture of capacitors and resistors. Such networks can be employed as lumped-parameter circuits to model the response of composite materials containing conductive and insulating grains. The dynamics of the excited network systems are studied using a state space model derived from a randomized incidence matrix. Time and frequency domain responses from synthetic data sets generated from state space models are analyzed for the purpose of estimating the fraction of capacitors in the network. Good results were obtained by using either the time-domain response to a pulse excitation or impedance data at selected frequencies. A chemometric framework based on a Successive Projections Algorithm (SPA) enables the construction of multiple linear regression (MLR) models which can efficiently determine the ratio of conductive to insulating components in composite material samples. The proposed method avoids restrictions commonly associated with Archie’s law, the application of percolation theory or Kohlrausch-Williams-Watts models and is applicable to experimental results generated by either time domain transient spectrometers or continuous-wave instruments. Furthermore, it is quite generic and applicable to tomography, acoustics as well as other spectroscopies such as nuclear magnetic resonance, electron paramagnetic resonance and, therefore, should be of general interest across the dielectrics community.

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This paper presents a tool that combines two kinds of Petri Net analyses to set the fastest routes to one vehicle in a bounded area of traffic urban. The first analysis consists of the discovery of possible routes in a state space generated from an IOPT Petri net model given the initial marking as the vehicle position. The second analysis receives the routes found in the first analysis and calculates the state equations at incidence matrix created from the High Level Petri net model to define the fastest route for each vehicle that arrive in the roads. It was considered the exchange of information between vehicle and infrastructure (V2I) to get the position and speed of all vehicles and support the analyses. With the results obtained we conclude that is possible optimizing the urban traffic flow if this tool is applied to all vehicles in a bounded urban traffic. © 2012 IEEE.

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In this paper, a new algebraic-graph method for identification of islanding in power system grids is proposed. The proposed method identifies all the possible cases of islanding, due to the loss of a equipment, by means of a factorization of the bus-branch incidence matrix. The main features of this new method include: (i) simple implementation, (ii) high speed, (iii) real-time adaptability, (iv) identification of all islanding cases and (v) identification of the buses that compose each island in case of island formation. The method was successfully tested on large-scale systems such as the reduced south Brazilian system (45 buses/72 branches) and the south-southeast Brazilian system (810 buses/1340 branches). (C) 2011 Elsevier Ltd. All rights reserved.

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In early generation variety trials, large numbers of new breeders' lines (varieties) may be compared, with each having little seed available. A so-called unreplicated trial has each new variety on just one plot at a site, but includes several replicated control varieties, making up around 10% and 20% of the trial. The aim of the trial is to choose some (usually around one third) good performing new varieties to go on for further testing, rather than precise estimation of their mean yields. Now that spatial analyses of data from field experiments are becoming more common, there is interest in an efficient layout of an experiment given a proposed spatial analysis and an efficiency criterion. Common optimal design criteria values depend on the usual C-matrix, which is very large, and hence it is time consuming to calculate its inverse. Since most varieties are unreplicated, the variety incidence matrix has a simple form, and some matrix manipulations can dramatically reduce the computation needed. However, there are many designs to compare, and numerical optimisation lacks insight into good design features. Some possible design criteria are discussed, and approximations to their values considered. These allow the features of efficient layouts under spatial dependence to be given and compared. (c) 2006 Elsevier Inc. All rights reserved.

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In this study, interactions between potential hierarchical value chains existing in the production structure and industry-wise productivity growths are sought. We applied generalized Chenery-Watanabe heuristics for matrix linearity maximization to triangulate the input-output incidence matrix for both Japan and the Republic of Korea, finding the potential directed flow of values spanning the industrial sectors of the basic (disaggregated) industry classifications for both countries. Sector specific productivity growths were measured by way of the Trönquvist index, using the 2000-2005 linked input-output tables for both Japan and Korea.

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Purpose: Prostate cancer is the most common tumor in males in Brazil. Single nucleotide polymorphisms have been demonstrated to exist in the promoter regions of matrix metalloproteinase genes and they are associated with the development and progression of some cancers. We investigated the correlation between MMP1, 2, 7 and 9 polymorphisms with susceptibility to prostate cancer, and classic prognostic parameters of prostate cancer. Materials and Methods: Genomic DNA was extracted using conventional protocols. The DNA sequence containing the polymorphic site was amplified by realtime polymerase chain reaction using TaqMan (R) fluorescent probes. Results: For the MMP1 gene the polymorphic allele was more common in the control group than in the prostate cancer group (p <0.001). For the MMP9 gene the incidence of the polymorphic homozygote genotype was higher in the prostate cancer group (p <0.001). For higher stage tumors (pT3) a polymorphic allele in the MMP2 gene was more common (p = 0.026). When considering Gleason score, the polymorphic homozygote genotype of MMP9 was more common in Gleason 6 or less tumors (p = 0.003), while a polymorphic allele in the MMP2 gene was more common in Gleason 7 or greater tumors (p = 0.042). Conclusions: MMP1 and MMP2 may protect against prostate cancer development and MMP9 may be related to higher risk. In contrast, MMP9 polymorphism was associated with a lower Gleason score and MMP2 polymorphism was associated with nonorgan confined disease.

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Objectives: Polychlorinated biphenyls (PCBs) are considered probable human carcinogens by the International Agency for Research on Cancer and one congener, PCB126, has been rated as a known human carcinogen. A period-specific job exposure matrix (JEM) was developed for former PCB-exposed capacitor manufacturing workers (n=12,605) (1938-1977). Methods: A detailed exposure assessment for this plant was based on a number of exposure determinants (proximity, degree of contact with PCBs, temperature, ventilation, process control, job mobility). The intensity and frequency of PCB exposures by job for both inhalation and dermal exposures, and additional chemical exposures were reviewed. The JEM was developed in nine steps: (1) all unique jobs (n=1,684) were assessed using (2) defined PCB exposure determinants; (3) the exposure determinants were used to develop exposure profiles; (4) similar exposure profiles were combined into categories having similar PCB exposures; (5) qualitative intensity (high-medium-low-baseline) and frequency (continuous-intermittent) ratings were developed, and (6) used to qualitatively rate inhalation and dermal exposure separately for each category; (7) quantitative intensity ratings based on available air concentrations were developed for inhalation and dermal exposures based on equal importance of both routes of exposure; (8) adjustments were made for overall exposure, and (9) for each category the product of intensity and frequency was calculated, and exposure in the earlier era was weighted. Results: A period-specific JEM modified for two eras of stable PCB exposure conditions. Conclusions: These exposure estimates, derived from a systematic and rigorous use of the exposure determinant data, lead to cumulative PCB exposure-response relationships in the epidemiological cancer mortality and incidence studies of this cohort. [Authors]

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Reversed phase liquid chromatography (RPLC) coupled to mass spectrometry (MS) is the gold standard technique in bioanalysis. However, hydrophilic interaction chromatography (HILIC) could represent a viable alternative to RPLC for the analysis of polar and/or ionizable compounds, as it often provides higher MS sensitivity and alternative selectivity. Nevertheless, this technique can be also prone to matrix effects (ME). ME are one of the major issues in quantitative LC-MS bioanalysis. To ensure acceptable method performance (i.e., trueness and precision), a careful evaluation and minimization of ME is required. In the present study, the incidence of ME in HILIC-MS/MS and RPLC-MS/MS was compared for plasma and urine samples using two representative sets of 38 pharmaceutical compounds and 40 doping agents, respectively. The optimal generic chromatographic conditions in terms of selectivity with respect to interfering compounds were established in both chromatographic modes by testing three different stationary phases in each mode with different mobile phase pH. A second step involved the assessment of ME in RPLC and HILIC under the best generic conditions, using the post-extraction addition method. Biological samples were prepared using two different sample pre-treatments, i.e., a non-selective sample clean-up procedure (protein precipitation and simple dilution for plasma and urine samples, respectively) and a selective sample preparation, i.e., solid phase extraction for both matrices. The non-selective pretreatments led to significantly less ME in RPLC vs. HILIC conditions regardless of the matrix. On the contrary, HILIC appeared as a valuable alternative to RPLC for plasma and urine samples treated by a selective sample preparation. Indeed, in the case of selective sample preparation, the compounds influenced by ME were different in HILIC and RPLC, and lower and similar ME occurrence was generally observed in RPLC vs. HILIC for urine and plasma samples, respectively. The complementary of both chromatographic modes was also demonstrated, as ME was observed only scarcely for urine and plasma samples when selecting the most appropriate chromatographic mode.

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Salivary gland cancer (SGC) is a rare cancer. The histological classification of SGC is complex and its biological behavior highly variable: it may vary from a low-grade tumor to a high-grade and often fatal malignancy. These circumstances make this cancer a diagnostic and therapeutic challenge. Older age and exposure to ionizing radiation are known risk factors. The mainstay of treatment is surgery combined with adjuvant radiation therapy, when appropriate. In addition to the histological type, the only well known prognostic factor is the TNM classification, which describes the tumor size and the amount of metastases. This study was performed using a full population-based nationwide cohort of SGC patients and tumors diagnosed in Finland in 1991-1996. The annual incidence of SGC in the entire population was, on average, 47.7 per year. By histological re-evaluation of 237 specimens the most frequent histological types were the adenoid cystic carcinoma (n=65; 27%), the mucoepidermoid carcinoma (n=45; 19%) and the acinic cell carcinoma (n=41; 17%). The highest 10-year disease-specific survival rate occurred among patients with acinic cell carcinoma (90%), followed by mucoepidermoid carcinoma (81%) and adenoid cystic carcinoma (60%). A high volume-corrected index (VCI) of Ki-67 correlated with worse survival of patients with SGC. Computer-assisted morphometric analyses of CD34-positive vessels indicated an unfavorable prognosis for patients with mucoepidermoid carcinoma and an association with poor survival among patients with acinic cell carcinoma. A high level of expression of matrix metalloproteinase-9 (MMP-9) showed a trend for a poorer prognosis in salivary duct carcinoma, and a high level of MMP-13 and a low level of MMP-1 had a trend for a poorer prognosis of patients with SGC. A low level of MMP-7 was associated with a poor prognosis of patients with acinic cell and mucoepidermoid carcinoma.