Upravljanje dinamičkim sistemima primenom adaptivnih ortogonalnih neuronskih mreža

The goal of the research in the PhD dissertation is control of dynamical systems by using new types of orthogonal endocrine neural networks, in order to improve their performances. Standard artificial neural networks are described, as well as their historical development and basic types of learning algorithms. Further, possibilities for neural networks applicability within control logic of dynamical systems are presented, as well as the current state of the art of orthogonal and endocrine neural networks. Performance improvement of the laboratory model of a servo system by using a standard neural network with the backpropagation type of learning is analyzed. In addition, a method for selection and optimization of training data, as an efficient way of information preprocessing for the purpose of improving performances of a neural network, is presented. A detailed description of orthogonal functions and implementation methods of endocrine factors inside standard neural networks are provided. By implementation of orthogonal activation functions of neurons, verification of their applicability in control of dynamical systems was performed. The laboratory model of the magnetic levitation system was used to test the designed orthogonal neural network. Furthermore, the endocrine orthogonal neural network based on the biological processes of excitation and inhibition is designed. Network performance checkup is performed by testing its predictive abilities when working with time series data. Final dissertation researches refer to development of hybrid systems. The implemented adaptive endocrine neuro-fuzzy hybrid system is tested through modeling of a laboratory servo system. Other hybrid structure, based on a combination of an orthogonal endocrine neural network and an orthogonal endocrine neuro-fuzzy hybrid system, is designed with the aim to form symbiosis of the positive characteristics of the individual networks. Verification of this structure was performed by using it for PID controller parameters adjustments

Quadrature with multiple nodes, power orthogonality, and moment-preserving spline approximation, part ii

The paper deals with new contributions to the theory of the Gauss quadrature formulas with multiple nodes that are published after 2001, including numerical construction, error analysis and applications. The first part was published in Numerical analysis 2000, Vol. V, Quadrature and orthogonal polynomials (W. Gautschi, F. Marcellan, and L. Reichel, eds.) [J. Comput. Appl. Math. 127 (2001), no. 1-2, 267-286]

Quadrature with multiple nodes, power orthogonality, and moment-preserving spline approximation, part ii

The paper deals with new contributions to the theory of the Gauss quadrature formulas with multiple nodes that are published after 2001, including numerical construction, error analysis and applications. The first part was published in Numerical analysis 2000, Vol. V, Quadrature and orthogonal polynomials (W. Gautschi, F. Marcellan, and L. Reichel, eds.) [J. Comput. Appl. Math. 127 (2001), no. 1-2, 267-286]

Error estimates for Gaussian quadratures of analytic functions

For analytic functions the remainder term of Gaussian quadrature formula and its Kronrod extension can be represented as a contour integral with a complex kernel. We study these kernels on elliptic contours with foci at the points +/-1 and the sum of semi-axes Q > 1 for the Chebyshev weight functions of the first, second and third kind, and derive representation of their difference. Using this representation and following Kronrod's method of obtaining a practical error estimate in numerical integration, we derive new error estimates for Gaussian quadratures

DATA ANALYSIS OF ENVIRONMENTAL CONDITIONS INFLUENCING THE WORK OF LABORATORY EQUIPMENT AND APPLICATION OF MACHINE LEARNING MODELS FOR CLASSIFICATION OF POOR CONDITIONS

Environmental conditions can have a crucial impact on the functioning of laboratory equipment. Electric components are sensitive to the influence of certain environmental factors such as temperature, humidity, vibrations, etc. Environmental factors should, therefore, be monitored to avoid their negative influence on the system and potential faults and failures they could cause. Unlike the traditional approaches which required the presence of special staff to monitor environmental factors and react if they are poor, the rise of the Internet of Things enhanced the application of intelligent solutions where human factor is not necessary. In this paper, research on data analysis, preprocessing and intelligent classification of environmental conditions has been conducted. The data was collected by sensors connected to Raspberry Pi. The applied monitoring system setup enabled long-distance monitoring of laboratory conditions through the internet and full applicability of fundamental IoT concepts. Since data preparation is an important step in the process of designing machine learning models, the collected data was analyzed and preprocessed in Python. Intelligent classification of environmental conditions was performed using machine learning models k-Nearest Neighbors and Random Forest. Grid search was used for model selection, and the performances of k-Nearest Neighbors and Random Forest machine learning models were compared. Experimental results show that these machine learning models can be successfully used for intelligent classification of environmental conditions

Procedure for Creating Personalized Geometrical Models of the Human Mandible and Corresponding Implants

The greatest challenge in engineering of human mandible implants lies in its customization for each patient individually, by adapting them to the patient's anatomical, morphological and physiological characteristics. This customization maximizes the efficiency of the patient's health recovery process. The application of anatomically shaped and personalized bone endoprosthesis, fixation plate and scaffold models bring great improvement to the clinical practice in maxillofacial surgery. It ensures that implant meets the biomechanical and dentofacial aesthetic requirements and, ultimately, reduces complications during recovery. In order to create such implants, novel procedure based on personalized models of mandible and its parts, and also plates and scaffold implants is presented in this paper. Design procedures for the creation of the personalized models are based on the application of Method of Anatomical Features, which has been already applied for the creation of geometrical models of human bones. This procedure improves pre-surgical planning, enables better execution of surgical intervention, and as a consequence improves patient recovery processes

The Influence of Wagon Structure Part Shape Optimization on Ultimate Fatigue Strength

This study investigates how shape optimisation affects the ultimate fatigue strength of a mechanical part. The mechanical part chosen for this investigation is an axle guard of running gear elements of the Hccrrs 2x2 axle car-carrying wagon. The static and fatigue strength analysis procedure according to the UIC 517 standard and numerical methods have been applied. Material properties were determined experimentally and the necessary numerical calculations were performed by using the finite element method. The observed axle guard is exposed to low cycle fatigue. ε-N curves and material properties of the S355J2+N steel grade are obtained by combining theoretical formulae and a mathematical function. According to the obtained experimental and numerical results the number of cycles until failure for both shapes of axle guards is obtained

Diferencias de tiempo de reacción simple y electivo en los jóvenes karatecas de ambos sexos de distinto nivel de entrenamiento

Compared to adults, children have longer simple reaction time (SRT) and choice reaction time (CRT) to simple and choice visual stimuli. Based on the available data, it can be concluded that this occurrence could be due to correlation between age and the information processing speed. Other factors may have an impact, too, such as the shorter attention span which children may have. Some studies indicate that karate favors the development of cognitive functions, including the RT. Therefore, the aim of the current study was to determine whether there is a difference in simple and choice reaction time between boys and girls of preadolescent and early adolescent age on the basic and premastery level of karate training. Testing involved 78 participants divided into four subgroups, in accordance with the gender and the level of training, using a custom designed RT measuring software, developed in LabVIEW 2012 software package. A two-way analysis of variance (Two-way ANOVA) confirmed no differences between boys’ and girls’ SRT scores, while the significant differences were found at the mastery criterion subsample level. When it comes to CRT, the differences were found at the boys’ subsample level, as well as between genders on the basic level of training. It cannot be stated with absolute certainty whether the acquired differences are the result of karate training, some other physiological and cognitive phenomena or the maturation process. Consequently, the futher research should involve a broader sample – the population of the physically inactive, as well as the children involved in other sports.U poređenju sa odraslima, deca imaju sporije prosto (PVR) i izborno (IVR) vreme reakcije (VR) na prostu i izbornu vizuelnu draž. Na osnovu podataka iz dostupne literature, može se zaključiti da bi razlog mogla biti povezanost godina starosti sa brzinom obrade informacija, ali i da drugi faktori, poput slabije pažnje, na primer, mogu imati uticaja. Neka istraživanja pokazuju da karate favorizuje razvoj kognitivnih funkcija, uključujući i VR. Stoga je cilj ove studije bio da utvrdi da li između dečaka i devojčica preadolescentskog i ranog adolescentskog uzrasta, na učeničkom i predmajstorskom stepenu obuke u karateu, postoje razlike za prosto i izborno vreme reakcije. Testirano je 78 ispitanika podeljenih u četiri subgrupe, u odnosu na pol i stepen obučenosti, primenom posebno dizajniranog softvera za merenje VR, razvijenog u programskom paketu LabVIEW 2012. Dvofaktorskom analizom varijanse (Two-way ANOVA) utvrđeno je da nema razlika između rezultata dečaka i devojčica ostvarenih za PVR, ali da su one značajne na nivou subuzoraka po kriterijumu majstorstva. Kada je u pitanju IVR, razlike su utvrđene na nivou subuzorka dečaka, kao i između polova na učeničkom nivou obuke. Ne može se sa sigurnošću tvrditi da li su dobijene razlike posledica treninga ili nekih drugih fiziološko-kognitivnih fenomena, odnosno procesa sazrevanja. Stoga bi buduća istraživanja morala da obuhvate širi uzorak - populaciju neaktivne, kao i dece uključene u druge sportove

On the remainder term of Gauss-Radau quadratures for analytic functions

For analytic functions the remainder term of Gauss–Radau quadrature formulae can be represented as a contour integral with a complex kernel. We study the kernel on elliptic contours with foci at the points and a sum of semi-axes for the Chebyshev weight function of the second kind. Starting from explicit expressions of the corresponding kernels the location of their maximum modulus on ellipses is determined. The corresponding Gautschi's conjecture from [On the remainder term for analytic functions of Gauss–Lobatto and Gauss–Radau quadratures, Rocky Mountain J. Math. 21 (1991), 209–226] is proved