Browsing Mathematical Sciences by Title
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Selenić, Sanja (Beograd , 2014)[more][less]
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Gauss, C. F. (Paris , 1807)[more][less]
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Gauss, C. F. (Gottingen, Leipzig , 1876)[more][less]
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Gauss, C. F. (Gottingen, Leipzig , 1900)[more][less]
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Stanić, Marija (Kragujevac, Srbija , 2007)[more][less]
Abstract: The field of research in this dissertation is consideration of some nonstandard types of orthogonality and their applications to constructions of quadrature rules with maximal degree of exactness, i.e., quadrature rules of Gaussian type. The research in this dissertation is connected with the following subjects: Theory of Orthogonality, Numerical Integration and Approximation Theory. We have tried to produce a balanced work between theoretical results and numerical algorithms. URI: http://hdl.handle.net/123456789/1741 Files in this item: 1
PhD MS.pdf ( 784.9Kb ) -
Jocković, Jelena (Beograd , 2009)[more][less]
URI: http://hdl.handle.net/123456789/2588 Files in this item: 1
magistarskiJelenaJockovic.pdf ( 262.5Kb ) -
Minčić, Svetislav (Novi Sad)[more][less]
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Saltikov, N. (Beograd , 1939)[more][less]
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Stojanović, Boban (Kragujevac, Serbia , 2007)[more][less]
Abstract: Muscles are organs whose primary function is to produce force and motion. There are three types of muscles: skeletal (striated), smooth and hart muscles. Skeletal muscles are attached to bones and can move them voluntarily. There are many daily activities which occur over an extended period of time and during which performances of muscles can be reduced (reduction of maximal force, contraction speed, movement control, etc). Although numerous mathematical models of muscles have been developed, there are only few models which take into account muscle fatigue. Most of the existing muscle fatigue models consider muscle fatigue under specific conditions only. Motivated by the fact that the existing muscle fatigue models are very limited under arbitrary conditions of activation and loading, we here present a new model including muscle fatigue. The proposed model is based on Hill’s phenomenological model consisting of contractile, serial and parallel elastic elements, but now using a fatigue curve under maximal activation and recovery curve as input parameters, in order to predict muscle response under arbitrary loading conditions. Furthermore, an extension of Hill’s model is introduced, in order to take into account different fiber types. Various types of muscle fibers can have very different physiological and mechanical properties, significantly affecting their resistance to fatigue. The developed models are incorporated into the finite element software PAK. The proposed models are verified by comparing the calculated results with experimental measurements and data from literature. By computer modeling of human biceps and triceps muscles, as well as the frog gastrocnemius muscle, it is shown that the models can predict behavior of real muscles with satisfactory precision. Besides application to single muscles, the proposed models can be used for computer simulations of complex musculoskeletal systems. In order to provide efficient modeling of muscles and musculoskeletal systems, a software for automatic muscle generation using medical images has been developed, as well as a module for result post-processing by employing various types of graphs. The proposed models and the developed software can be used as a very powerful tool in designing medical and sport equipment, planning trainings and analyzing exercises. Computer simulations based on the muscle mechanical models can prevent work injuries and significantly reduce costs for individuals and society. URI: http://hdl.handle.net/123456789/1843 Files in this item: 1
Boban Stojanovic - Doktorska disertacija.pdf ( 12.75Mb ) -
Lopandić, Dragomir (Belgrade)[more][less]
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Udovičić, Enes (Belgrade , 1980)[more][less]
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Simovljević, Jovan (None)[more][less]
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Pejić, Dragana (Beograd , 2023)[more][less]
URI: http://hdl.handle.net/123456789/5641 Files in this item: 1
v1_masterDraganaPejic.pdf ( 394.2Kb ) -
Ivanović, Blagoje (Beograd , 2018)[more][less]
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Stanimirović, Zorica (Belgrade , 2007)[more][less]
Abstract: U ovom radu opisani su različiti genetski algoritmi (GA) za rešavanje četiri NP-teška hab lokacijska problema: problem p-hab medijane neograničenih kapaciteta sa jednostrukim alokacijama (USApHMP), problem p-hab medijane/centra ograničenih kapaciteta sa jednostrukim alokacijama (CSApHMP/CSApHCP) i hab lokacijski problem ograničenih kapaciteta sa jednostrukim alokacijama (CSAHLP). Ovi hab lokacijski problemi nalaze veliku primenu u dizajniranju transportnih i telekomunikacijskih sistema, poštanskih i drugih sistema isporuke, lokalnih i globalnih računarskih mreža, itd. Za problem p-hab medijane neograničenih kapaciteta sa jednostrukim alokacijama (USApHMP), razvijene su GA metode koje koriste dva različita načina kodiranja i adekvatne modifikovane genetske operatore. U cilju poboljšanja efikasnosti predloženih genetskih algoritama, primenjena je hibridizacija oba GA koncepta sa heuristikom lokalnog pretraživanja, pa su tako nastale hibridne HGA1 i HGA2 metode koje su veoma uspešne i pri rešavanju problema velikih dimenzija. Za rešavanje hab lokacijskih problema ograničenih kapaciteta CSApHMP, CSApHCP i CSAHLP takođe su predložene razne verzije genetskih algoritama. Primenjene su dve razičite reprezentacije rešenja i odgovarajući genetski operatori razvijeni u skladu sa prirodom problema. Implementirani genetski operatori čuvaju korektnost jedinki u tokom generacija GA i u smislu očuvanja broja uspostavljenih habova i u smislu ograničenja kapaciteta habova. Sve opisane genetske (evolutivne) metode testirane su na odgovarajućim standardnim ORLIB instancama iz literature. Za sva četiri hab lokacijska problema koja su razmatrana u ovom radu, predloženi (hibridni) genetski algoritmi dostižu sve do sada poznate optimalne vrednosti na datim instancama u zadovoljavajućem vremenu izvršavanja. U radu su data rešenja i za probleme velikih dimenzija (n=100,200 p≤20) za koje optimalna rešenja nisu poznata, a neki od ovih problema do sada nisu rešavani u literaturi. Dobijeni rezultati predloženih GA metoda jasno ukazuju na značaj i potencijal genetskih pristupa rešavanju hab i drugih lokacijskih problema.In this paper some new genetic algorithms (GA) for solving four NP-hard hub location problems are described: Uncapacitated Single Allocation p-hub Center Problem (USApHCP), Capacitated Single Allocation p-hub Median/Center Problem (CSApHMP/CSApHCP) and Capacitated Single Allocation Hub Location Problem (CSAHLP). These hub ploblems have various applications in designing transportation and telecommunications systems, postal and other delivery systems, local and golobal computer area networks, etc. For the Uncapacitated Single Allocation p-hub Center Problem (USApHCP), two hybrid heuristic methods, named HGA1 and HGA2 are proposed. These methods are a combination of a genetic algorithm and a generalization of the well-known fast interchange heuristic (IH). In order to investigate the effect of encoding on GA performance, two different encoding schemes are implemented: binary encoding in HGA1, and integer representation in HGA2. Modified genetic operators that keep the feasibility of individuals are designed and implemented in both HGA1 and HGA2. The performed computational experiments showed the effectiveness of both hybrid methods, even for solving large-scaled problem instances For the capacitated variants of hub location problems CSApHMP, CSApHCP i CSAHLP, new genetic approaches are also described. In proposed genetic algorithms, new encoding schemes are implemented with appropriate objective functions. By using specific representation and modified genetic operators, proposed GA approaches keep the feasibility of individuals, i.e. the fixed number of established hubs and/or satisfying the capacity constraints on hubs. The numerical experiments were carried out on the standard hub data set from the literature. For all four hub problems that were studied, the corresponding GA method proved to be robust and efficient in solving the problem instances with up to 200 nodes and 20 hubs. Computational experiments demonstrate that all proposed GA methods reach all previously known optimal solutions on tested hub instances. The algorithm is also benchmarked on large scale hub instances with n=100,200 nodes and p≤20 hubs that are not solved (to optimality) so far. The presented computational results clearly indicate the usefulness of the proposed GA approaches. URI: http://hdl.handle.net/123456789/298 Files in this item: 1
phdZoricaStanimirovic.pdf ( 666.6Kb ) -
Borak, Biljana (MATEMATIČKI FAKULTET UNIVERZITETA U BEOGRADU , 2009)[more][less]
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Živanović, Nemanja (Beograd , 2023)[more][less]
URI: http://hdl.handle.net/123456789/5652 Files in this item: 1
v1_masterNemanjaZivanovic.pdf ( 700.8Kb ) -
Fijuljanin, Jasmina (MATEMATIČKI FAKULTET UNIVERZITETA U BEOGRADU , 2010)[more][less]
URI: http://hdl.handle.net/123456789/1870 Files in this item: 1
Jasmina Fijuljanin - Master rad.pdf ( 673.7Kb ) -
Ševarlić, Dr B. M.; Brkić, Dr Z. M. (GRAĐEVINSKA KNJIGA , 1963)[more][less]
URI: http://hdl.handle.net/123456789/1550 Files in this item: 1
geodeska astronomija.pdf ( 19.54Mb ) -
Džeparoski, Vojislav (Beograd , 1997)[more][less]