A modified PNN algorithm with optimal PD modeling using the orthogonal least squares method

In this paper a modified algorithm is suggested for developing polynomial neural network (PNN) models. Optimal partial description (PD) modeling is introduced at each layer of the PNN expansion, a task accomplished using the orthogonal least squares (OLS) method. Based on the initial PD models determined by the polynomial order and the number of PD inputs, OLS selects the most significant regressor terms reducing the output error variance. The method produces PNN models exhibiting a high level of accuracy and superior generalization capabilities. Additionally, parsimonious models are obtained comprising a considerably smaller number of parameters compared to the ones generated by means of the conventional PNN algorithm. Three benchmark examples are elaborated, including modeling of the gas furnace process as well as the iris and wine classification problems. Extensive simulation results and comparison with other methods in the literature, demonstrate the effectiveness of the suggested modeling approach.

Modified Chebyshev algorithm: some applications

Two applications of the modified Chebyshev algorithm are considered. The first application deals with the generation of orthogonal polynomials associated with a weight function having singularities on or near the end points of the interval of orthogonality. The other application involves the generation of real Szego polynomials.

Reconfiguration of distribution systems by a modified genetic algorithm

In this paper a genetic algorithm based reconfiguration method is proposed to minimize the real power losses of distribution systems. The main innovation of this research work is that new types of crossover and mutation operators are proposed, such that the best possible results are obtained, with an acceptable computational effort. The crossover and mutation operators were developed so as to take advantage of the particular characteristics of distribution systems (as the radial topology). Simulation results indicate that the proposed method is very efficient, being able to find excellent configurations, with low computational effort, especially for larger systems. ©2007 IEEE.

Cross-Country Evidence on Output Growth Volatility: Nonstationary Variance and GARCH Models

This paper revisits the issue of conditional volatility in real GDP growth rates for Canada, Japan, the United Kingdom, and the United States. Previous studies find high persistence in the volatility. This paper shows that this finding largely reflects a nonstationary variance. Output growth in the four countries became noticeably less volatile over the past few decades. In this paper, we employ the modified ICSS algorithm to detect structural change in the unconditional variance of output growth. One structural break exists in each of the four countries. We then use generalized autoregressive conditional heteroskedasticity (GARCH) specifications modeling output growth and its volatility with and without the break in volatility. The evidence shows that the time-varying variance falls sharply in Canada, Japan, and the U.K. and disappears in the U.S., excess kurtosis vanishes in Canada, Japan, and the U.S. and drops substantially in the U.K., once we incorporate the break in the variance equation of output for the four countries. That is, the integrated GARCH (IGARCH) effect proves spurious and the GARCH model demonstrates misspecification, if researchers neglect a nonstationary unconditional variance.

Speeding up the EM algorithm for mixture model-based segmentation of magnetic resonance images

Mixture models implemented via the expectation-maximization (EM) algorithm are being increasingly used in a wide range of problems in pattern recognition such as image segmentation. However, the EM algorithm requires considerable computational time in its application to huge data sets such as a three-dimensional magnetic resonance (MR) image of over 10 million voxels. Recently, it was shown that a sparse, incremental version of the EM algorithm could improve its rate of convergence. In this paper, we show how this modified EM algorithm can be speeded up further by adopting a multiresolution kd-tree structure in performing the E-step. The proposed algorithm outperforms some other variants of the EM algorithm for segmenting MR images of the human brain. (C) 2004 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.

Investigating the performance analysis of EASI algorithm and EKENS algorithm in nonlinear model

This paper investigates the performance of EASI algorithm and the proposed EKENS algorithm for linear and nonlinear mixtures. The proposed EKENS algorithm is based on the modified equivariant algorithm and kernel density estimation. Theory and characteristic of both the algorithms are discussed for blind source separation model. The separation structure of nonlinear mixtures is based on a nonlinear stage followed by a linear stage. Simulations with artificial and natural data demonstrate the feasibility and good performance of the proposed EKENS algorithm.

Optimisation des horaires des agents et du routage des appels dans les centres d’appels

Nous étudions la gestion de centres d'appels multi-compétences, ayant plusieurs types d'appels et groupes d'agents. Un centre d'appels est un système de files d'attente très complexe, où il faut généralement utiliser un simulateur pour évaluer ses performances. Tout d'abord, nous développons un simulateur de centres d'appels basé sur la simulation d'une chaîne de Markov en temps continu (CMTC), qui est plus rapide que la simulation conventionnelle par événements discrets. À l'aide d'une méthode d'uniformisation de la CMTC, le simulateur simule la chaîne de Markov en temps discret imbriquée de la CMTC. Nous proposons des stratégies pour utiliser efficacement ce simulateur dans l'optimisation de l'affectation des agents. En particulier, nous étudions l'utilisation des variables aléatoires communes. Deuxièmement, nous optimisons les horaires des agents sur plusieurs périodes en proposant un algorithme basé sur des coupes de sous-gradients et la simulation. Ce problème est généralement trop grand pour être optimisé par la programmation en nombres entiers. Alors, nous relaxons l'intégralité des variables et nous proposons des méthodes pour arrondir les solutions. Nous présentons une recherche locale pour améliorer la solution finale. Ensuite, nous étudions l'optimisation du routage des appels aux agents. Nous proposons une nouvelle politique de routage basé sur des poids, les temps d'attente des appels, et les temps d'inoccupation des agents ou le nombre d'agents libres. Nous développons un algorithme génétique modifié pour optimiser les paramètres de routage. Au lieu d'effectuer des mutations ou des croisements, cet algorithme optimise les paramètres des lois de probabilité qui génèrent la population de solutions. Par la suite, nous développons un algorithme d'affectation des agents basé sur l'agrégation, la théorie des files d'attente et la probabilité de délai. Cet algorithme heuristique est rapide, car il n'emploie pas la simulation. La contrainte sur le niveau de service est convertie en une contrainte sur la probabilité de délai. Par après, nous proposons une variante d'un modèle de CMTC basé sur le temps d'attente du client à la tête de la file. Et finalement, nous présentons une extension d'un algorithme de coupe pour l'optimisation stochastique avec recours de l'affectation des agents dans un centre d'appels multi-compétences.

“Reconstruction of Gene Regulatory Network from Expression Profile of Plasma RNA Data of Colorectal Cancer Patients using Soft Computing Techniques”

Microarray data analysis is one of data mining tool which is used to extract meaningful information hidden in biological data. One of the major focuses on microarray data analysis is the reconstruction of gene regulatory network that may be used to provide a broader understanding on the functioning of complex cellular systems. Since cancer is a genetic disease arising from the abnormal gene function, the identification of cancerous genes and the regulatory pathways they control will provide a better platform for understanding the tumor formation and development. The major focus of this thesis is to understand the regulation of genes responsible for the development of cancer, particularly colorectal cancer by analyzing the microarray expression data. In this thesis, four computational algorithms namely fuzzy logic algorithm, modified genetic algorithm, dynamic neural fuzzy network and Takagi Sugeno Kang-type recurrent neural fuzzy network are used to extract cancer specific gene regulatory network from plasma RNA dataset of colorectal cancer patients. Plasma RNA is highly attractive for cancer analysis since it requires a collection of small amount of blood and it can be obtained at any time in repetitive fashion allowing the analysis of disease progression and treatment response.

Critérios compostos para delineamentos ótimos robustos

Pós-graduação em Biometria - IBB

Ionenleitfähigkeit in polymeren Matrizes – Synthese, Charakterisierung und Untersuchung dynamischer Prozesse von neuen Lithium- und Protonenleitern

Die vorliegende Dissertation befasst sich mit der Synthese, physikochemischen und polymerspezifischen Charakterisierung und insbesondere der impedanzspektroskopischen Untersuchung von sowohl neuartigen, solvensfreien lithiumionen- als auch protonenleitfähigen Polymermaterialien für potentielle Anwendungen in sekundären Lithiumionenbatterien bzw. in Hochtemperatur-Protonenaustauschmembran-Brennstoffzellen (engl.: proton exchange membrane fuel cell, auch: polymer electrolyte membrane fuel cell, PEMFC). Beiden Typen von ionenleitfähigen Membranen liegt das gängige Prinzip der chemischen Anbindung einer für den Ionentransport verantwortlichen Seitengruppe an eine geeignete Polymerhauptkette zugrunde („Entkopplung“; auch Immobilisierung), welcher hinsichtlich Glasübergangstemperatur (Tg), elektrochemischer und thermischer Stabilität (Td) eine dynamisch entkoppelte, aber nicht minder bedeutsame Rolle zukommt. Die Transportaktivierung erfolgt in beiden Fällen thermisch. Im Falle der Protonenleiter liegt die zusätzliche Intention darin, eine Alternative aufzuzeigen, in der die Polymerhauptkette gekoppelt direkt am Protonentransportmechanismus beteiligt ist, d.h., dass der translatorisch diffusive Ionentransport entlang der Hauptkette stattfindet und nicht zwischen benachbarten Seitenketten. Ein Hauptaugenmerk der Untersuchungen liegt sowohl bei den lithiumionen- als auch den protonenleitfähigen Polymermembranen auf temperaturabhängigen dynamischen Prozessen der jeweiligen Ionenspezies in der polymeren Matrix, was die Ionenleitfähigkeit selbst, Relaxationsphänomene, die translatorische Ionendiffusion und im Falle der Protonenleiter etwaige mesomere Grenzstrukturübergänge umfasst. Lithiumionenleiter: Poly(meth)acrylate mit (2-Oxo-1,3-dioxolan)resten (Cyclocarbonat-) in der Seitenkette unterschiedlicher Spacerlänge wurden synthetisiert und charakterisiert. Die Leitfähigkeit s(,T) erreicht bei Poly(2-oxo-[1,3]dioxolan-4-yl)methylacrylat (PDOA): Lithium-bis-trifluormethansulfonimid (LiTFSI) (10:3) ca. 10^-3,5 S cm^-1 bei 150 °C. Weichmachen (Dotieren) mit äquimolaren Mengen an Propylencarbonat (PC) bewirkt in allen Fällen einen enormen Anstieg der Leitfähigkeit. Die höchsten Leitfähigkeiten von Mischungen dieser Polymere mit LiTFSI (und LiBOB) werden nicht beim System mit der niedrigsten Tg gefunden. Auch dient Tg nicht als Referenztemperatur (Tref) nach Williams-Landel-Ferry (WLF), so dass eine WLF-Anpassung der Leitfähigkeitsdaten nur über einen modifizierten WLF-Algorithmus gelingt. Die ermittelten Tref liegen deutlich unterhalb von Tg bei Temperaturen, die charakteristisch für die Seitenkettenrelaxation sind („Einfrieren“). Dies legt nahe, dass der Relaxation der Seitenketten eine entscheidende Rolle im Li^+-Leitfähigkeitsmechanismus zukommt. Die Li^+-Überführungszahlen tLi^+ in diesen Systemen schwanken zwischen 0,13 (40 °C) und 0,55 (160 °C). Protonenleiter: Polymere mit Barbitursäure- bzw. Hypoxanthinresten in der Seitenkette und Polyalkylenbiguanide unterschiedlicher Spacerlänge wurden synthetisiert und charakterisiert. Die Leitfähigkeit s(,T) erreicht bei Poly(2,4,6(1H,3H,5H)-trioxopyrimidin-5-yl)methacrylat (PTPMA) maximal ca. 10^-4,4 S cm^-1 bei 140 °C. Höhere Leitfähigkeiten sind nur durch Mischen mit aprotischen Lösungsmitteln erreichbar. Die höchste Leitfähigkeit wird im Falle der Polyalkylenbiguanide bei Polyethylenbiguanid (PEB) erzielt. Sie erreicht 10^-2,4 S cm^-1 bei 190 °C. Die Aktivierungsenergien EA der Polyalkylenbiguanide liegen (jeweils unterhalb von Tg) zwischen ca. 3 – 6 kJ mol^-1. In allen beobachteten Fällen dient Tg als Tref, so dass eine konventionelle WLF-Behandlung möglich ist und davon auszugehen ist, dass die Leitfähigkeit mit dem freien Volumen Vf korreliert.

Multilevel Latent Class Models with Dirichlet Mixing Distribution

Latent class analysis (LCA) and latent class regression (LCR) are widely used for modeling multivariate categorical outcomes in social sciences and biomedical studies. Standard analyses assume data of different respondents to be mutually independent, excluding application of the methods to familial and other designs in which participants are clustered. In this paper, we develop multilevel latent class model, in which subpopulation mixing probabilities are treated as random effects that vary among clusters according to a common Dirichlet distribution. We apply the Expectation-Maximization (EM) algorithm for model fitting by maximum likelihood (ML). This approach works well, but is computationally intensive when either the number of classes or the cluster size is large. We propose a maximum pairwise likelihood (MPL) approach via a modified EM algorithm for this case. We also show that a simple latent class analysis, combined with robust standard errors, provides another consistent, robust, but less efficient inferential procedure. Simulation studies suggest that the three methods work well in finite samples, and that the MPL estimates often enjoy comparable precision as the ML estimates. We apply our methods to the analysis of comorbid symptoms in the Obsessive Compulsive Disorder study. Our models' random effects structure has more straightforward interpretation than those of competing methods, thus should usefully augment tools available for latent class analysis of multilevel data.

Pelvic radiography in ATLS algorithms: A diminishing role?

ABSTRACT: BACKGROUND: Pelvic x-ray is a routine part of the primary survey of polytraumatized patients according to Advanced Trauma Life Support (ATLS) guidelines. However, pelvic CT is the gold standard imaging technique in the diagnosis of pelvic fractures. This study was conducted to confirm the safety of a modified ATLS algorithm omitting pelvic x-ray in hemodynamically stable polytraumatized patients with clinically stable pelvis in favour of later pelvic examination by CT scan. METHODS: We conducted a retrospective analysis of all polytraumatized patients in our emergency room between 01.07.2004 and 31.01.2006. Inclusion criteria were blunt abdominal trauma, initial hemodynamic stability and a stable pelvis on clinical examination. We excluded patients requiring immediate intervention because of hemodynamic instability. RESULTS: We reviewed the records of n = 452 polytraumatized patients, of which n = 91 fulfilled inclusion criteria (56% male, mean age = 45 years). The mechanism of trauma included 43% road traffic accidents, 47% falls. In 68/91 (75%) patients, both a pelvic x-ray and a CT examination were performed; the remainder had only pelvic CT. In 6/68 (9%) patients, pelvic fracture was diagnosed by pelvic x-ray. None of these 6 patients was found having a false positive pelvic x-ray, i.e. there was no fracture on pelvic CT scan. In 3/68 (4%) cases a fracture was missed in the pelvic x-ray, but confirmed on CT (false negative on x-ray). None of the diagnosed fractures needed an immediate therapeutic intervention. 5 (56%) were classified type A fractures, and another 4 (44%) B 2.1 in computed tomography (AO classification). One A 2.1 fracture was found in a clinically stable patient who only received CT scan (1/23). CONCLUSION: While pelvic x-ray is an integral part of ATLS assessment, this retrospective study suggests that in hemodynamically stable patients with clinically stable pevis, its sensitivity is only 67% and it may safely be omitted in favor of a pelvic CT examination if such is planned in adjunct assessment and available. The results support the safety and utility of our modified ATLS algorithm. A randomized controlled trial using the algorithm can safely be conducted to confirm the results.

Volatility changes in drachma exchange rates

In January 2001 Greece joined the eurozone. The aim of this article is to examine whether an intention to join the eurozone had any impact on exchange rate volatility. We apply the Iterated Cumulative Sum of Squares (ICSS) algorithm of Inclan and Tiao (1994) to a set of Greek drachma exchange rate changes. We find evidence to suggest that the unconditional volatility of the drachma exchange rate against the dollar, British pound, yen, German mark and ECU/Euro was nonstationary, exhibiting a large number of volatility changes prior to European Monetary Union (EMU) membership. We then use a news archive service to identify the events that might have caused exchange rate volatility to shift. We find that devaluation of the drachma increased exchange rate volatility but ERM membership and a commitment to joining the eurozone led to lower volatility. Our findings therefore suggest that a strong commitment to join the eurozone may be sufficient to reduce some exchange rate volatility which has implications for countries intending to join the eurozone in the future.

The microstructure of the Irish stock market

This is the first paper to examine the microstructure of the Irish Stock Market empirically and is motivated by the adoption, on June 7th of Xetra the modern pan European auction trading system. Prior to this the exchange utilized an antiquated floor based system. This change was an important event for the market as a rich literature exists to suggest that the trading system exerts a strong influence over the behavior of security returns. We apply the ICSS algorithm of Inclan and Tiao (1994) to discover whether the change to the trading system caused a shift in unconditional volatility at the time Xetra was introduced. Because the trading mechanism can influence volatility in a number of ways we also estimate the partial adjustment coefficients of the Amihud and Mendelson (1987) model prior and subsequent to the introduction of Xetra. Although we find no evidence of volatility changes associated with the introduction of Xetra we do find evidence of an increase in the speed of adjustment (JEL: G15).