Automatic differentiation is an effective method for evaluating derivatives of function, which is defined by a formula or a program. Program for evaluating of value of function is by automatic differentiation modified to program, which also evaluates values of derivatives. Computed values are exact up to computer precision and their evaluation is very quick. In this article, we describe a program realization of automatic differentiation. This implementation is prepared in the system UFO, but its principles can be applied in other systems. We describe, how the operations are stored in the first part of the derivative computation and how the obtained records are effectively used in the second part of the computation.
This paper deals with a generalized automatic method used for designing artificial neural network (ANN) structures. One of the most important problems is designing the optimal ANN for many real applications. In this paper, two techniques for automatic finding an optimal ANN structure are proposed. They can be applied in real-time applications as well as in fast nonlinear processes. Both techniques proposed in this paper use the genetic algorithms (GA). The first proposed method deals with designing a structure with one hidden layer. The optimal structure has been verified on a nonlinear model of an isothermal reactor. The second algorithm allows designing ANN with an unlimited number of hidden layers each of which containing one neuron. This structure has been verified on a highly nonlinear model of a polymerization reactor. The obtained results have been compared with the results yielded by a fully connected ANN.
We propose automatic modularization method for artificial neural networks (ANNs). We treat modularization as an optimization task, therefore the optimization criteria are defined and the topology capable of continuous iterative modularization is introduced. The modularization process starts with unstructured plain network topology and iteratively builds up a modular structure. Automatic modularization approach not only learns to map inputs to outputs but it also tries to discover a structure of knowledge represented by training patterns.
Let R be a prime ring of characteristic different from 2, Qr its right Martindale quotient ring and C its extended centroid. Suppose that F, G are generalized skew derivations of R with the same associated automorphism α, and p(x1, ..., xn) is a non-central polynomial over C such that \left[ {F(x),\alpha (y)} \right] = G(\left[ {x,y} \right]). for all x,y\in \left \{ p\left ( r_{1},...,r_{n} \right ):r_{1},...,r_{n}\in R\right \}. The there exist \lambda \in C such that F(x) = G(x) = λα(x) for all X\in R., Vincenzo De Filippis., and Obsahuje seznam literatury
Dysfunkce autonomního nervového systému patří k častým klinickým projevům roztroušené sklerózy (RS). Incidence autonomní dysfunkce (AD) u pacientů s RS se v různých studiích pohybuje mezi 16 a 80 % a jednoznačně se zvyšuje s délkou trvání RS a progredující disabilitou. Může se však projevit v kterékoli fázi demyelinizačního onemocnění a dokonce může být jeho prvním klinickým projevem. AD významně ovlivňuje kvalitu života pacientů s RS a přispívá k celkové disabilitě. Přesto postižení autonomního nervového systému patří mezi stále relativně poddiagnostikované symptomy tohoto onemocnění. Nejčastějším a nejzávažnějším typem AD u pacientů s RS je narušení funkce kardiovaskulárního a/nebo urogenitálního systému. Méně častá je dysfunkce gastrointestinální, sudomotorická či narušení pupilomotoriky. Autonomní (především kardiovaskulární) dysfunkce u pacientů s RS také úzce souvisí s rozvojem únavy. Cílem tohoto sdělení je poskytnout přehled jednotlivých typů AD u pacientů s RS a možností jejich diagnostiky., Autonomic nervous system dysfunction (AD) represents a frequent clinical presentation of multiple sclerosis (MS). According to published studies, the incidence of AD in MS patients ranges between 16 and 80% and gradually increases with the length of the demyelinating disease and with the progression of disability. However, AD can occur in any phase of MS and can even represent its first symptom in some patients. Autonomic dysfunction has a significant negative impact on the quality of life in MS patients and contributes to overall disability. Even so, autonomic nervous system dysfunction is frequently underdiagnosed in patients with multiple sclerosis. Cardiovascular and urogenital dysfunction are the most frequent types of AD in MS patients with the highest impact on their clinical status and the quality of life. Less frequently, gastrointestinal, sudomotor or pupilomotor dysfunction can be found. Autonomic (in particular cardiovascular) dysfunction in multiple sclerosis is closely related to fatigue, another frequent clinical symptom in MS patients. The aim of this paper is to sum up the spectrum of symptoms of autonomic dysfunction in multiple sclerosis and its diagnostic tools. Key words: multiple sclerosis – autonomic nervous system diseases – orthostatic intolerance –urinary incontinence – urinary retention –sexual dysfunction – gastrointestinal dysfunction – sweating The authors declare they have no potential conflicts of interest concerning drugs, products, or services used in the study. The Editorial Board declares that the manuscript met the ICMJE “uniform requirements” for biomedical papers., and I. Šrotová, E. Vlčková, J. Bednařík
A fuzzy model based on an enhanced supervised fuzzy clustering algorithm is presented in this paper. The supervised fuzzy clustering algorithm [6] allows each rule to represent more than one output with different probabilities for each output. This algorithm implements k-means to initialize the fuzzy model. However, the main drawbacks of this approach are that the number of clusters is unknown and the initial positions of clusters are randomly generated. In this work, the initialization is done by the global k-means algorithm [1], which can autonomously determine the actual number of clusters needed and give a deterministic clustering result. In addition, the fast global k-means algorithm [1] is presented to improve the computation time. The model is tested on medical diagnosis benchmark data and Westland vibration data. The results obtained show that the model that uses the global k-means clustering algorithm [1] has higher accuracy when compared to a model that uses the k-means clustering algorithm. Besides that, the fast global k-means algorithm [1] also improved the computation time without degrading much the model performance.
In recent years the interest of the investors in efficient methods for the forecasting price trend of a share in financial markets has grown steadily. The aim is to accurately forecast the future behavior of the market in order to identificate the so-called "correct timing".
In this paper we analyze three different approaches for forecasting financial data: Autoregression, artificial neural networks and support vector machines and we will determine potentials and limits of these methods. Application to the Italian financial market is also presented.
Genetic characteristics of the first three mutants found in P. apterus L.; white (w/w) 1965, yellow (y/y) 1966 and melanotic (m/m) 1973 have been described in detail. Exact Mendelian proportions of 1 : 1 and 3 : 1 in all standard test crosses and absence of sexual linkage revealed that each of these mutations was inherited as a single autosomal recessive gene. The dihybrid and trihybrid crosses showed that the w gene is epistatic over y. The absence of linkage shows that each of the described mutant genes is situated on a different chromosome. During 30 years of sustained rearings of P. apterus, the white (w/w) and yellow (y/y) mutants never originated de novo, whereas the melanotic (m/m) mutants originated independently from the macropterous strain three times. Triple recessive (w y m) white melanotic strain has been maintained and used for some genetic investigations for over 20 years.
So far, available cytogenetic data on 24 species of Rhopalidae reveal a male diploid chromosome number of 13, with a pair of m chromosomes and an X0/XX (male/female) sex chromosome determining system. As a rule Heteroptera have holokinetic chromosomes and a pre-reductional type of meiosis: the autosomal bivalents and the m pseudobivalent segregate reductionally at first meiotic division, while the X chromosome segregates equationally. In the present study, the meiotic chromosome behaviour was analyzed in males from different Argentinean populations of Jadera haematoloma and J. sanguinolenta. Our results corroborate the diploid chromosome number and general patterns of male meiosis previously reported by other authors in samples from Brazil and Texas (USA). Among bivalents, one is remarkably larger and may present one or two terminal chiasmata. Comparison of mean chiasma frequency between Jadera haematoloma (5.63) and J. sanguinolenta (5.14) revealed that differences are significant. In most individuals of both species the largest pair appears as univalents in a variable number of cells and shows a regular meiotic segregation. Autosomal univalents orientate axially at metaphase I (with their long axis parallel to the spindle axis) and segregate equationally at anaphase I. At metaphase II they associate end-to-end forming a pseudobivalent that segregates reductionally at anaphase II. An hypothesis is suggested to explain the appearance of the largest pair, either as a ring/rod bivalent or as univalents within the same individual, although an asynaptic or desynaptic origin of the univalents cannot be ascertained. The highly regular meiotic behaviour of this autosomal pair could ensure a high fertility of the individuals, and could be considered a selectively neutral condition or, at least, not detrimental.