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Park, Yongwon Baskiyar Sanjeev. "Dynamic task scheduling onto heterogeneous machines using Support Vector Machine." Auburn, Ala, 2008. http://repo.lib.auburn.edu/EtdRoot/2008/SPRING/Computer_Science_and_Software_Engineering/Thesis/Park_Yong_50.pdf.
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Li, Wei. "Dynamic Reconfigurable Machine Tool Controller." BYU ScholarsArchive, 2005. https://scholarsarchive.byu.edu/etd/235.
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This dissertation presents a dynamic reconfigurable control strategy based on the Direct Machining And Control (DMAC) research at Brigham Young University. A reconfigurable framework is proposed which will allow a machine tool to be controlled by a variety of applications and control laws. This Reconfigurable Mechanism for Application Control (RMAC) paradigm uses a hierarchical architecture to configure a mechanism into a device driver for direct control by an application like CAD/CAM. The RMAC paradigm is one of a mechanism device driver assigned to each mechanism class or model, and uses only the master model to control the mechanism. The traditional M&G code language is no longer necessary since motion entities are passed directly to the mechanism. The design strategy of using dynamic-link libraries (DLL) to form a mechanism device driver permits a mechanism to assume different operating configurations, depending on the number of axes and machine resolution. For example, the machine can perform as a material removal machine in one instant, and then, by loading a new device driver, act as a Coordinate Measuring Machine (CMM). This strategy is possible because RMAC is a software and networked-based control architecture. Both the CAD/CAM planning software and the real-time control software reside on the same PC. The CAM process plan can thus directly control the machine without need for process plan decomposition into the forms supported by the controller. The architectural framework is explained in detail and the methodology for control software reconfiguration into a device driver is presented. For demonstration purposes two device drivers are implemented on a prototype machine to demonstrate feasibility and usefulness.
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Filla, Reno. "Operator and Machine Models for Dynamic Simulation of Construction Machinery." Licentiate thesis, Linköping : Linköpings universitet, 2005. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-4092.
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Bu, Suhol. "Dynamic boundary element analysis of machine foundations." Thesis, University of Glasgow, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.295386.
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Kew, Min Shen Peter. "Dynamic analysis of multi-machine electromechanical systems." Thesis, University of Aberdeen, 1990. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.290341.
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This thesis describes the detailed modelling procedures for d-q axis representation of multi-machine electromechanical systems. It proposes two methods of connecting electrical machine models which have been formulated in various reference frames, to transmission network models. Investigation of these two methods was accomplished, and the effectiveness and merits of each are fully discussed. Conclusions are drawn which form the bases for recommendation of a connection method for developing a generalised multi-machine power system model. In addition two computer programs are written to provide means of simulating both large and limited capacity power systems on personal computers.
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Toulkeridou, Varvara. "Dynamic descriptions : steps towards a design machine." Thesis, Massachusetts Institute of Technology, 2010. http://hdl.handle.net/1721.1/61561.
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Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Architecture, 2010.Cataloged from PDF version of thesis.
Includes bibliographical references (p. 59-61).
This thesis questions which would be a valid approach for building design machine aided by computational intelligence capable of generating surprises for their designers-observers. There have been efforts since the 1960s towards developing frameworks for design machines that were envisioning computational systems as something more than tools for efficient production and representation. Some of them were dealing with design problems as complex systems that needed to be broken down in modular parts, for example Christopher Alexander's "Notes on the Synthesis of Form". However such strategies were associated with explicit languages of descriptions and strong hierarchies, defined in advance by the designer, that were constraining the design space to what these predefined descriptions were anticipating. This thesis draws its motivation from the work of Professor of Design and Computation George Stiny on visual computations operating on non-fixed sets of primitives, as well as from research conducted in the field of Artificial Intelligence on alternative representations. I will propose a framework for a design machine highlighting the importance of it being able to generate its own dynamic descriptions, "entities" that bear content independent of the interpretations of their designers. Inspired by a computational system, developed by Stephen Larson (2003), capable of grounding its own symbols in perception, I will experiment with self-organizing map algorithms suggesting them as a possible way for a design machine to build up and update its language of description from its perceptual information.
by Varvara Toulkeridou.
S.M.
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Höstklint, Niklas, and Jesper Larsson. "Dynamic Test Case Selection using Machine Learning." Thesis, KTH, Hälsoinformatik och logistik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-296634.
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Testing code is a vital part at any software producing company, to ensure no faulty code slips through that could have detrimental consequences. At Ericsson, testing code before publishing is a very costly process which can take several hours. Currently, every single test is run for all submitted code. This report aims to address the issue by building a machine learning model that determines which tests need to be run, so that unnecessary tests are left out, saving time and resources. It is however important to find the failures, as having certain failures pass through into production could have all types of economic, environmental and social consequences. The result shows that there is great potential in several different types of models. A Linear Regression model found 92% of all failures within running 25% of all test categories. The linear model however plateaus before finding the final failures. If finding 100% of failures is essential, a Support Vector Regression model proved the most efficient as it was the only model to find 100% of failures within 90% of test categories being run.Testning av kod är en avgörande del för alla mjukvaruproducerande företag, för att säkerställa att ingen felaktig kod som kan ha skadlig påverkan publiceras. Hos Ericsson är testning av kod innan det ska publiceras en väldigt dyr process som kan ta flera timmar. Vid tiden denna rapport skrivs så körs varenda test för all inlämnad kod. Denna rapport har som mål att lösa/reducera problemet genom att bygga en modell med maskininlärning som avgör vilka tester som ska köras, så onödiga tester lämnas utanför vilket i sin tur sparar tid och resurser. Dock är det viktigt att hitta alla misslyckade tester, eftersom att tillåta dessa passera till produktionen kan innebära alla möjliga olika ekonomiska, miljömässiga och sociala konsekvenser. Resultaten visar att det finns stor potential i flera olika typer av modeller. En linjär regressionsmodell hittade 92% av alla fel inom att 25% av alla test kategorier körts. Den linjära modellen träffar dock en platå innan den hittar de sista felen. Om det är essentiellt att hitta 100% av felen, så visade sig en support vector regressionsmodell vara mest effektiv, då den var den enda modellen som lyckades hitta 100% av alla fel inom att 90% alla test kategorier hade körts.
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Refaat, Tarek. "Virtual Machine Management for Dynamic Vehicular Clouds." Thesis, Université d'Ottawa / University of Ottawa, 2017. http://hdl.handle.net/10393/35864.
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Vehicular clouds involve a dynamic environment where virtual machines are hosted on moving vehicles, leading to frequent changes in the data center network topology. These frequent topological changes require frequent virtual machine migrations in order to meet the service level agreements with cloud users. Such topology changes include fluctuations in connectivity, signal strength and quality. Few studies address vehicles as potential virtual machine hosts, while there is a significant opportunity in capitalizing on underutilized resources. Due to the rapidly changing environment of a vehicular cloud, hosts frequently change or leave coverage. As such, virtual machine management and migration schemes are necessary to ensure cloud subscribers have a satisfactory level of access to the resources. This thesis addresses the need for virtual machine management for the vehicular cloud. First, a mobility model is proposed and utilized to test a set of novel Vehicular Virtual Machine Migration (VVMM) schemes: VVMM-U (Uniform), VVMM-LW (Least Workload), VVMM-MA (Mobility Aware) and MDWLAM (Mobility and Destination Workload Aware Migration). Their performance is evaluated with respect to a set of metrics through simulations with varying levels of vehicular traffic congestion, virtual machine sizes and load restriction levels. The most advanced scheme (MDWLAM) takes into account the workload and mobility of the original host as well as those of the potential destinations. By doing so a valid destination will both have time to receive the workload and migrate the new load when necessary. The behavior of various algorithms is compared and the MDWLAM has been shown to demonstrate the best performance, exhibiting migration drop rates that are negligibly small. Finally, an integer linear program formulation based on a modified single source shortest path problem is presented, tested and successfully shown to be a benchmark that can be used in comparison to the proposed heuristics.
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Gao, Jian. "Dynamic position sensing for parallel kinematic machine and new generation machine tool." Thesis, University of Nottingham, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.268479.
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Rowe, Michael C. (Michael Charles). "A Machine Learning Method Suitable for Dynamic Domains." Thesis, University of North Texas, 1996. https://digital.library.unt.edu/ark:/67531/metadc278720/.
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The efficacy of a machine learning technique is domain dependent. Some machine learning techniques work very well for certain domains but are ill-suited for other domains. One area that is of real-world concern is the flexibility with which machine learning techniques can adapt to dynamic domains. Currently, there are no known reports of any system that can learn dynamic domains, short of starting over (i.e., re-running the program). Starting over is neither time nor cost efficient for real-world production environments. This dissertation studied a method, referred to as Experience Based Learning (EBL), that attempts to deal with conditions related to learning dynamic domains. EBL is an extension of Instance Based Learning methods. The hypothesis of the study related to this research was that the EBL method would automatically adjust to domain changes and still provide classification accuracy similar to methods that require starting over. To test this hypothesis, twelve widely studied machine learning datasets were used. A dynamic domain was simulated by presenting these datasets in an uninterrupted cycle of train, test, and retrain. The order of the twelve datasets and the order of records within each dataset were randomized to control for order biases in each of ten runs. As a result, these methods provided datasets that represent extreme levels of domain change. Using the above datasets, EBL's mean classification accuracies for each dataset were compared to the published static domain results of other machine learning systems. The results indicated that the EBL's system performance was not statistically different (p>0.30) from the other machine learning methods. These results indicate that the EBL system is able to adjust to an extreme level of domain change and yet produce satisfactory results. This finding supports the use of the EBL method in real-world environments that incur rapid changes to both variables and values.
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Chakraborty, Sanjib. "Dynamic Modeling and Simulation of Digital Displacement Machine." Thesis, Linköpings universitet, Fluida och mekatroniska system, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-85277.
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Improved efficiency, better controllability and low noise are the most demanding features form a displacement machine now-a-days. Most of the conventional displacement machines are basically a reciprocating pumping element controlled by valve plates or with the help of check valve [1]. This kind of hydraulic machines loose efficiency dramatically at partial displacement because all of the pistons remain at high pressure at the cycle time and due to pressure inside the piston leakage and shear losses increases. One approach to improve the efficiency of the displacement machine can be controlling each hydraulic piston by using programmable faster valves called digital valve. As the total displacement will be controlled digitally, the total system is called Digital Displacement Technology. In digital displacement machine it is possible to disconnect some of the pistons from the load and the piston will connect only with the low pressure side, minimizing losses due to leakage and shear. As the valve will control directly with digital controller it will eliminate the necessity of servo-hydraulic control required by conventional systems. Digital valves can open fully and close again with the input signal within one revaluation of the shaft, so it gives better control to the pumping element results reduction in hysteresis and increase the linearity of the pumping element. In Digital Displacement machines by controlling the valves pistons are connected with the machine when pressure is equal, but in the traditional machines piston connection was pre-determined with the shaft angle. By doing the piston control efficiency of the machine will improve and the sound generates for the decompression flow will be reduced [17]. Also energy storage and recovery can be possible by using accumulator.
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Smirnova, Tatiana. "Dynamic Analysis and Modeling of Machine Tool Parts." Licentiate thesis, Karlskrona : Department of Signal Processing, School of Engineering, Blekinge Institute of Technology, 2008. http://www.bth.se/fou/Forskinfo.nsf/allfirst2/8628d01b6722765cc12573e70044bfd2?OpenDocument.
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Narmack, Kirilll. "Dynamic Speed Adaptation for Curves using Machine Learning." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-233545.
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The vehicles of tomorrow will be more sophisticated, intelligent and safe than the vehicles of today. The future is leaning towards fully autonomous vehicles. This degree project provides a data driven solution for a speed adaptation system that can be used to compute a vehicle speed for curves, suitable for the underlying driving style of the driver, road properties and weather conditions. A speed adaptation system for curves aims to compute a vehicle speed suitable for curves that can be used in Advanced Driver Assistance Systems (ADAS) or in Autonomous Driving (AD) applications. This degree project was carried out at Volvo Car Corporation. Literature in the field of speed adaptation systems and factors affecting the vehicle speed in curves was reviewed. Naturalistic driving data was both collected by driving and extracted from Volvo's data base and further processed. A novel speed adaptation system for curves was invented, implemented and evaluated. This speed adaptation system is able to compute a vehicle speed suitable for the underlying driving style of the driver, road properties and weather conditions. Two different artificial neural networks and two mathematical models were used to compute the desired vehicle speed in curves. These methods were compared and evaluated.Morgondagens fordon kommer att vara mer sofistikerade, intelligenta och säkra än dagens fordon. Framtiden lutar mot fullständigt autonoma fordon. Detta examensarbete tillhandahåller en datadriven lösning för ett hastighetsanpassningssystem som kan beräkna ett fordons hastighet i kurvor som är lämpligt för förarens körstil, vägens egenskaper och rådande väder. Ett hastighetsanpassningssystem för kurvor har som mål att beräkna en fordonshastighet för kurvor som kan användas i Advanced Driver Assistance Systems (ADAS) eller Autonomous Driving (AD) applikationer. Detta examensarbete utfördes på Volvo Car Corporation. Litteratur kring hastighetsanpassningssystem samt faktorer som påverkar ett fordons hastighet i kurvor studerades. Naturalistisk bilkörningsdata samlades genom att köra bil samt extraherades från Volvos databas och bearbetades. Ett nytt hastighetsanpassningssystem uppfanns, implementerades samt utvärderades. Hastighetsanpassningssystemet visade sig vara kapabelt till att beräkna en lämplig fordonshastighet för förarens körstil under rådande väderförhållanden och vägens egenskaper. Två olika artificiella neuronnätverk samt två matematiska modeller användes för att beräkna fordonets hastighet. Dessa metoder jämfördes och utvärderades.
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Sîrbu, Adela-Maria. "Dynamic machine learning for supervised and unsupervised classification." Thesis, Rouen, INSA, 2016. http://www.theses.fr/2016ISAM0002/document.
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La direction de recherche que nous abordons dans la thèse est l'application des modèles dynamiques d'apprentissage automatique pour résoudre les problèmes de classification supervisée et non supervisée. Les problèmes particuliers que nous avons décidé d'aborder dans la thèse sont la reconnaissance des piétons (un problème de classification supervisée) et le groupement des données d'expression génétique (un problème de classification non supervisée). Les problèmes abordés sont représentatifs pour les deux principaux types de classification et sont très difficiles, ayant une grande importance dans la vie réelle. La première direction de recherche que nous abordons dans le domaine de la classification non supervisée dynamique est le problème de la classification dynamique des données d'expression génétique. L'expression génétique représente le processus par lequel l'information d'un gène est convertie en produits de gènes fonctionnels : des protéines ou des ARN ayant différents rôles dans la vie d'une cellule. La technologie des micro-réseaux moderne est aujourd'hui utilisée pour détecter expérimentalement les niveaux d'expression de milliers de gènes, dans des conditions différentes et au fil du temps. Une fois que les données d'expression génétique ont été recueillies, l'étape suivante consiste à analyser et à extraire des informations biologiques utiles. L'un des algorithmes les plus populaires traitant de l'analyse des données d'expression génétique est le groupement, qui consiste à diviser un certain ensemble en groupes, où les composants de chaque groupe sont semblables les uns aux autres données. Dans le cas des ensembles de données d'expression génique, chaque gène est représenté par ses valeurs d'expression (caractéristiques), à des points distincts dans le temps, dans les conditions contrôlées. Le processus de regroupement des gènes est à la base des études génomiques qui visent à analyser les fonctions des gènes car il est supposé que les gènes qui sont similaires dans leurs niveaux d'expression sont également relativement similaires en termes de fonction biologique. Le problème que nous abordons dans le sens de la recherche de classification non supervisée dynamique est le regroupement dynamique des données d'expression génique. Dans notre cas, la dynamique à long terme indique que l'ensemble de données ne sont pas statiques, mais elle est sujette à changement. Pourtant, par opposition aux approches progressives de la littérature, où l'ensemble de données est enrichie avec de nouveaux gènes (instances) au cours du processus de regroupement, nos approches abordent les cas lorsque de nouvelles fonctionnalités (niveaux d'expression pour de nouveaux points dans le temps) sont ajoutés à la gènes déjà existants dans l'ensemble de données. À notre connaissance, il n'y a pas d'approches dans la littérature qui traitent le problème de la classification dynamique des données d'expression génétique, définis comme ci-dessus. Dans ce contexte, nous avons introduit trois algorithmes de groupement dynamiques que sont capables de gérer de nouveaux niveaux d'expression génique collectés, en partant d'une partition obtenue précédente, sans la nécessité de ré-exécuter l'algorithme à partir de zéro. L'évaluation expérimentale montre que notre méthode est plus rapide et plus précis que l'application de l'algorithme de classification à partir de zéro sur la fonctionnalité étendue ensemble de donnéesThe research direction we are focusing on in the thesis is applying dynamic machine learning models to salve supervised and unsupervised classification problems. We are living in a dynamic environment, where data is continuously changing and the need to obtain a fast and accurate solution to our problems has become a real necessity. The particular problems that we have decided te approach in the thesis are pedestrian recognition (a supervised classification problem) and clustering of gene expression data (an unsupervised classification. problem). The approached problems are representative for the two main types of classification and are very challenging, having a great importance in real life.The first research direction that we approach in the field of dynamic unsupervised classification is the problem of dynamic clustering of gene expression data. Gene expression represents the process by which the information from a gene is converted into functional gene products: proteins or RNA having different roles in the life of a cell. Modern microarray technology is nowadays used to experimentally detect the levels of expressions of thousand of genes, across different conditions and over time. Once the gene expression data has been gathered, the next step is to analyze it and extract useful biological information. One of the most popular algorithms dealing with the analysis of gene expression data is clustering, which involves partitioning a certain data set in groups, where the components of each group are similar to each other. In the case of gene expression data sets, each gene is represented by its expression values (features), at distinct points in time, under the monitored conditions. The process of gene clustering is at the foundation of genomic studies that aim to analyze the functions of genes because it is assumed that genes that are similar in their expression levels are also relatively similar in terms of biological function.The problem that we address within the dynamic unsupervised classification research direction is the dynamic clustering of gene expression data. In our case, the term dynamic indicates that the data set is not static, but it is subject to change. Still, as opposed to the incremental approaches from the literature, where the data set is enriched with new genes (instances) during the clustering process, our approaches tackle the cases when new features (expression levels for new points in time) are added to the genes already existing in the data set. To our best knowledge, there are no approaches in the literature that deal with the problem of dynamic clustering of gene expression data, defined as above. In this context we introduced three dynamic clustering algorithms which are able to handle new collected gene expression levels, by starting from a previous obtained partition, without the need to re-run the algorithm from scratch. Experimental evaluation shows that our method is faster and more accurate than applying the clustering algorithm from scratch on the feature extended data set
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Yao, Li. "Magnetic field modelling of machine and multiple machine systems using dynamic reluctance mesh modelling." Thesis, University of Nottingham, 2006. http://eprints.nottingham.ac.uk/10224/.
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This thesis concerns the modified and improved, time-stepping, dynamic reluctance mesh (DRM) modelling technique for machines and its application to multiple machine systems with their control algorithms. Improvements are suggested which enable the stable solution of the resulting complex non-linear equations. The concept of finite element (FE) derived, overlap-curves has been introduced to facilitate the evaluation of the air-gap reluctances linking the teeth on the rotor to those on the stator providing good model accuracy and efficient computation. Motivated industrially, the aim of the work is to develop a fast and effective simulation tool principally for evaluating salient pole generator system designs including the generator, exciter and the automatic voltage regulator (AVR). The objective is to provide a modelling system capable of examining the detail of machine operation including saturation of main and leakage flux paths, slotting and space harmonics of the windings. Solutions are obtained in a sufficiently short computational time to facilitate efficient iterative design procedures in an industrial design office. The DRM modelling technique for electrical machines has been shown in this thesis to be a fast and efficient tool for electrical machine simulation. Predicted results for specific machine and system designs have been compared with FE solutions and with experimental results showing, that for engineering purposes, the technique yields excellent accuracy. The DRM method has a great advantage in multiple machine simulations. This is because magnetic field calculations are limited to evaluating only the most important information so saving computation time. A brushless generating system including the excitation system and control scheme has been modelled. Additionally a cascaded, doubly fed induction generator for wind generator applications has also been modelled. These different applications for the dynamic reluctance mesh method have proved that this approach yields an excellent machine and machine-system evaluation and design tool.
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Kulich, Martin. "Dynamic Template Adjustment in Continuous Keystroke Dynamics." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2015. http://www.nusl.cz/ntk/nusl-234927.
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Dynamika úhozů kláves je jednou z behaviorálních biometrických charakteristik, kterou je možné použít pro průběžnou autentizaci uživatelů. Vzhledem k tomu, že styl psaní na klávesnici se v čase mění, je potřeba rovněž upravovat biometrickou šablonu. Tímto problémem se dosud, alespoň pokud je autorovi známo, žádná studie nezabývala. Tato diplomová práce se pokouší tuto mezeru zaplnit. S pomocí dat o časování úhozů od 22 dobrovolníků bylo otestováno několik technik klasifikace, zda je možné je upravit na online klasifikátory, zdokonalující se bez učitele. Výrazné zlepšení v rozpoznání útočníka bylo zaznamenáno u jednotřídového statistického klasifikátoru založeného na normované Euklidovské vzdálenosti, v průměru o 23,7 % proti původní verzi bez adaptace, zlepšení však bylo pozorováno u všech testovacích sad. Změna míry rozpoznání správného uživatele se oproti tomu různila, avšak stále zůstávala na přijatelných hodnotách.
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Filali, Karim. "Multi-dynamic Bayesian networks for machine translation and NLP /." Thesis, Connect to this title online; UW restricted, 2007. http://hdl.handle.net/1773/6857.
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Ebrahimi, S. Morteza K. "Dynamic modelling and simulation of a CNC milling machine." Thesis, Cardiff University, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.287909.
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Chang, David Wei-Yao Spence Allan D. "Dynamic coordinate measuring machine error analysis and improvement strategies." *McMaster only, 2007.
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Dahlberg, Love. "Dynamic algorithm selection for machine learning on time series." Thesis, Karlstads universitet, Institutionen för matematik och datavetenskap (from 2013), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-72576.
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We present a software that can dynamically determine what machine learning algorithm is best to use in a certain situation given predefined traits. The produced software uses ideal conditions to exemplify how such a solution could function. The software is designed to train a selection algorithm that can predict the behavior of the specified testing algorithms to derive which among them is the best. The software is used to summarize and evaluate a collection of selection algorithm predictions to determine which testing algorithm was the best during that entire period. The goal of this project is to provide a prediction evaluation software solution can lead towards a realistic implementation.
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Brun, Yuriy 1981. "Software fault identification via dynamic analysis and machine learning." Thesis, Massachusetts Institute of Technology, 2003. http://hdl.handle.net/1721.1/17939.
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Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2003.Includes bibliographical references (p. 65-67).
I propose a technique that identifies program properties that may indicate errors. The technique generates machine learning models of run-time program properties known to expose faults, and applies these models to program properties of user-written code to classify and rank properties that may lead the user to errors. I evaluate an implementation of the technique, the Fault Invariant Classifier, that demonstrates the efficacy of the error finding technique. The implementation uses dynamic invariant detection to generate program properties. It uses support vector machine and decision tree learning tools to classify those properties. Given a set of properties produced by the program analysis, some of which are indicative of errors, the technique selects a subset of properties that are most likely to reveal an error. The experimental evaluation over 941,000 lines of code, showed that a user must examine only the 2.2 highest-ranked properties for C programs and 1.7 for Java programs to find a fault-revealing property. The technique increases the relevance (the concentration of properties that reveal errors) by a factor of 50 on average for C programs, and 4.8 for Java programs.
by Yuriy Brun.
M.Eng.
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Mbawala, Silipius Joseph. "Behaviour of machine foundations subjected to vertical dynamic loading." Thesis, University of Pretoria, 2015. http://hdl.handle.net/2263/56087.
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The vertical dynamic behaviour of machine foundations subjected to vertical dynamic loading
was investigated for surface and embedded foundations. The responses of these machine
foundations were determined using analytical and numerical solutions ranging from simple to
complex. An accurate prediction of impedance functions for the foundation system is a key step
in the design procedures. The prediction accuracy depends on how close the modelling
procedures are to reality. The subject of soil dynamics is complex. At times, the choice of the
analysis model is based on the experience of the engineer with the model. The chosen model
may or may not result in an optimal, efficient, and accurate design.
The current advancement in manufacturing technology calls for machine foundation systems
with high performance, availability and reliability. The analysis and design of such complex,
large and sensitive machine foundations requires good understanding of their dynamic
behaviour.
The aim of this thesis is to investigate and evaluate the most accurate analytical and numerical
models for determining the dynamic behaviour of surface and embedded machine foundations.
Surface and embedded footings were cast at the experimental station at the University of
Pretoria. The vertical dynamic behaviour of these foundations was determined by vertical
harmonic loading. The measured impedance functions were compared with predicted responses
obtained from analytical solution of the Winkler model, elastic half-space theory, simplified
Lysmer (1965) model, Veletsos and Verbic (1973) models, the Dyna5 program and numerical
solution of finite element method (Abaqus). The dynamic responses of the surface foundation
predicted by the analytical solution proposed by Veletsos and Verbic (1973) soil with mass,
compared reasonably well with the results obtained from field-measured data. The measured impedance functions of the embedded foundation were compared with the
predicted results ascertained using the analytical solution proposed by Novak and Beredugo
(1972), Dyna5 program and numerical solution of the finite element method (Abaqus). It is
shown that embedment increases stiffness, natural frequency, natural frequency ratio, and
damping ratio. The embedment reduces resonant amplitude, resonant amplitude ratio and has an
insignificant effect on resonant frequency and resonant frequency ratio. The measured dynamic
responses compared favourably with the results predicted by the finite element method
(Abaqus).
The conclusion is that the analytical model proposed by Veletsos and Verbic (1973) soil with
mass, and the finite element method (Abaqus) can be used to accurately predict the dynamic
response of surface and embedded machine foundations respectively.Thesis (PhD)--University of Pretoria, 2015.
tm2016
Civil Engineering
PhD
Unrestricted
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Emani, Murali Krishna. "Adaptive parallelism mapping in dynamic environments using machine learning." Thesis, University of Edinburgh, 2015. http://hdl.handle.net/1842/10469.
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Modern day hardware platforms are parallel and diverse, ranging from mobiles to data centers. Mainstream parallel applications execute in the same system competing for resources. This resource contention may lead to a drastic degradation in a program’s performance. In addition, the execution environment composed of workloads and hardware resources, is dynamic and unpredictable. Efficient matching of program parallelism to machine parallelism under uncertainty is hard. The mapping policies that determine the optimal allocation of work to threads should anticipate these variations. This thesis proposes solutions to the mapping of parallel programs in dynamic environments. It employs predictive modelling techniques to determine the best degree of parallelism. Firstly, this thesis proposes a machine learning-based model to determine the optimal thread number for a target program co-executing with varying workloads. For this purpose, this offline trained model uses static code features and dynamic runtime information as input. Next, this thesis proposes a novel solution to monitor the proposed offline model and adjust its decisions in response to the environment changes. It develops a second predictive model for determining how the future environment should be, if the current thread prediction was optimal. Depending on how close this prediction was to the actual environment, the predicted thread numbers are adjusted. Furthermore, considering the multitude of potential execution scenarios where no single policy is best suited in all cases, this work proposes an approach based on the idea of mixture of experts. It considers a number of offline experts or mapping policies, each specialized for a given scenario, and learns online the best expert that is optimal for the current execution. When evaluated on highly dynamic executions, these solutions are proven to surpass default, state-of-art adaptive and analytic approaches.
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Hadraba, Petr. "Kmitání strojů v průmyslové praxi." Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2017. http://www.nusl.cz/ntk/nusl-318140.
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The vibration analysis of a production machine is a key factor of its functionality, service life and occupational safety. This work deals with mathematical dynamic modelling and its contribution to the improvement of a mechanical design and mechanism failure prevention. The whole process is presented on the example of a drum cam rotary indexing table and on the example of actuators of multi spindle automatic lathes. The analysis consisted of complex nonlinear models based on basic linear models. It was computed using Matlab, Simulink and MSC ADAMS. Models of these mechanisms were validated with experimental measurements. The results were used for mechanical design improvement and for speed control optimization.
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Tröger, Jens. "Specification-Driven Dynamic Binary Translation." Queensland University of Technology, 2005. http://eprints.qut.edu.au/16007/.
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Machine emulation allows for the simulation of a real or virtual machine, the source machine, on various host computers. A machine emulator interprets programs that are compiled for the emulated machine, but normally at a much reduced speed. Therefore, in order to increase the executions peed of such interpreted programs, a machine emulator may apply different dynamic optimization techniques.
In our research we focus on emulators for real machines, i.e. existing computer architectures, and in particular on dynamic binary translation as the optimization technique. With dynamic binary translation, the machine instructions of the interpreted source program are translated in to machine instructions for the host machine during the interpretation of the program. Both, the machine emulator and its dynamic binary translator a resource and host machine specific, respectively, and are therefore traditionally hand-written.
In this thesis we introduce the Walkabout/Yirr-Ma framework. Walkabout, initially developed by Sun Micro systems, allows among other things for the generation of instrumented machine emulators from a certain type of machine specification files. We extended Walkabout with our generic dynamic optimization framework ‘Yirr-Ma’ which defines an interface for the implementation of various dynamic optimizers: by instrumenting a Walkabout emulator’s instruction interpretation functions, Yirr-Ma observes and intercepts the interpretation of a source machine program, and applies dynamic optimizations to selected traces of interpreted instructions on demand. One instance of Yirr-Ma’s interface for dynamic optimizers implements our specification-driven dynamic binary translator, the major contribution of this thesis.
At first we establish two things: a formal framework that describes the process of machine emulation by abstracting from real machines, and different classes of applicable dynamic optimizations. We define dynamic optimizations by a set of functions over the abstracted machine, and dynamic binary translation as one particular optimization function. Using this formalism, we then derive the upper bound for quality of dynamically translated machine instructions. Yirr-Ma’s dynamic binary translator implements the optimization functions of our formal framework by modules which are either generated from, or parameterized by, machine specification files. They thus allow for the adaptation of the dynamic binary translator to different source and host machines without hand-writing machine dependent code.
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Pape, Tobias, Arian Treffer, Robert Hirschfeld, and Michael Haupt. "Extending a Java Virtual Machine to Dynamic Object-oriented Languages." Universität Potsdam, 2013. http://opus.kobv.de/ubp/volltexte/2013/6743/.
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There are two common approaches to implement a virtual machine (VM) for a dynamic object-oriented language. On the one hand, it can be implemented in a C-like language for best performance and maximum control over the resulting executable. On the other hand, it can be implemented in a language such as Java that allows for higher-level abstractions. These abstractions, such as proper object-oriented modularization, automatic memory management, or interfaces, are missing in C-like languages but they can simplify the implementation of prevalent but complex concepts in VMs, such as garbage collectors (GCs) or just-in-time compilers (JITs). Yet, the implementation of a dynamic object-oriented language in Java eventually results in two VMs on top of each other (double stack), which impedes performance.
For statically typed languages, the Maxine VM solves this problem; it is written in Java but can be executed without a Java virtual machine (JVM). However, it is currently not possible to execute dynamic object-oriented languages in Maxine.
This work presents an approach to bringing object models and execution models of dynamic object-oriented languages to the Maxine VM and the application of this approach to Squeak/Smalltalk. The representation of objects in and the execution of dynamic object-oriented languages pose certain challenges to the Maxine VM that lacks certain variation points necessary to enable an effortless and straightforward implementation of dynamic object-oriented languages' execution models. The implementation of Squeak/Smalltalk in Maxine as a feasibility study is to unveil such missing variation points.Es gibt zwei übliche Wege, um eine virtuelle Maschine (VM) für eine dynamische objektorientierte Programmiersprache zu implementieren. Einerseits kann sie in einer C-ähnlichen Programmiersprache geschrieben werden, um bestmögliche Leistung zu erzielen und größtmöglichen Einfluss auf das sich ergebende ausführbare Programm zu haben. Andererseits kann sie in einer Sprache wie Java geschrieben werden, die weitreichendere Abstraktionen als die C-ähnlichen Sprachen erlaubt. Diese Abstraktionen, beispielsweise echte objektorientierte Modularisierung, automatische Speicherverwaltung oder explizite Schnittstellen, erlauben eine vereinfachtes Implementieren von VM-typischen, aber komplexen Konzepten, wie Speicherbereinigung (garbage collector, GCs) oder just-in-time-Compilern (JITs). Wird eine dynamische objektorientierte Programmiersprache in Java geschrieben, ist jedoch mit Leistungseinbußen zu rechen, da effektiv zwei aufeinander aufbauende virtuelle Maschinen entstehen. Die Maxine VM löst diese Problem für statisch getypte Programmiersprachen; sie ist in Java geschrieben, kann aber ohne jegliche Java VM (JVM) laufen. Es ist jedoch momentan nicht möglich, dynamische objektorientierte Programmiersprachen in Maxine auszuführen. Diese Arbeit stellt einen Ansatz zur Umsetzung von Objekt- und Ausführungsmodellen dynamischer objektorientierter Programmiersprachen innerhalb der Maxine VM vor, sowie dessen Anwendung auf Squeak/Smalltalk. Dabei stellt die Representation von Objekten und die Ausführung dynamischer objektorientierter Programmiersprachen bestimmte Heraus- und Anforderungen an die Maxine VM, die trotz des Fokus auf Modularität und Konfigurierbarkeit einige Variationspunkte vermissen lässt, welche wiederum für eine einfache Implementierung von besagten Ausführungsmodellen jedoch unerlässlich sind. Daher sollen durch eine testweise Implementierung von Squeak/Smalltalk in Maxine eben jene Variationspunkte identifiziert werden.
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Wild, Harald G. "Robust control of high dynamic machine drives employing linear motors." Thesis, University of East London, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.323529.
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Zorello, Ligia Maria Moreira. "Dynamic CPU frequency scaling using machine learning for NFV applications." Universidade de São Paulo, 2018. http://www.teses.usp.br/teses/disponiveis/3/3141/tde-30012019-100044/.
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Growth in the Information and Communication Technology sector is increasing the need to improve the quality of service and energy efficiency, as this industry has already surpassed 12% of global energy consumption in 2017. Data centers correspond to a large part of this consumption, accounting for about 15% of energy expenditure on the Information and Communication Technology domain; moreover, the subsystem that generates the most costs for data center operators is that of servers and storage. Many solutions have been proposed to reduce server consumption, such as the use of dynamic voltage and frequency scaling, a technology that enables the adaptation of energy consumption to the workload by modifying the operating voltage and frequency, although they are not optimized for network traffic. In this thesis, a control method was developed using a prediction engine based on the analysis of the ongoing traffic. Machine learning algorithms based on Neural Networks and Support Vector Machines have been used, and it was verified that it is possible to reduce power consumption by up to 12% on servers with Intel Sandy Bridge processor and up to 21 % in servers with Intel Haswell processor when compared to the maximum frequency, which is currently the most used solution in the industry.O crescimento do setor de Tecnologia da Informação e Comunicação está aumentando a necessidade de melhorar a qualidade de serviço e a eficiência energética, pois o setor já ultrapassou a marca de 12% do consumo energético global em 2017. Data centers correspondem a grande parte desse consumo, representando cerca de 15% dos gastos com energia do setor Tecnologia Informação e Comunicação; além disso, o subsistema que gera mais custos para operadores de data centers é o de servidores e armazenamento. Muitas soluções foram propostas a fim de reduzir o consumo de energia com servidores, como o uso de escalonamento dinâmico de tensão e frequência, uma tecnologia que permite adaptar o consumo de energia à carga de trabalho, embora atualmente não sejam otimizadas para o processamento do tráfego de rede. Nessa dissertação, foi desenvolvido um método de controle usando um mecanismo de previsão baseado na análise do tráfego que chega aos servidores. Os algoritmos de aprendizado de máquina baseados em Redes Neurais e em Máquinas de Vetores de Suporte foram utilizados, e foi verificado que é possível reduzir o consumo de energia em até 12% em servidores com processador Intel Sandy Bridge e em até 21% em servidores com processador Intel Haswell quando comparado com a frequência máxima, que é atualmente a solução mais utilizada na indústria.
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Marhefka, Duane Winfield. "Fuzzy control and dynamic simulation of a quadruped galloping machine /." The Ohio State University, 2000. http://rave.ohiolink.edu/etdc/view?acc_num=osu1488202171197262.
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Botlani-Esfahani, Mohsen. "Modeling of Dynamic Allostery in Proteins Enabled by Machine Learning." Scholar Commons, 2017. http://scholarcommons.usf.edu/etd/6804.
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Regulation of protein activity is essential for normal cell functionality. Many proteins are regulated allosterically, that is, with spatial gaps between stimulation and active sites. Biological stimuli that regulate proteins allosterically include, for example, ions and small molecules, post-translational modifications, and intensive state-variables like temperature and pH. These effectors can not only switch activities on-and-off, but also fine-tune activities. Understanding the underpinnings of allostery, that is, how signals are propagated between distant sites, and how transmitted signals manifest themselves into regulation of protein activity, has been one of the central foci of biology for over 50 years. Today, the importance of such studies goes beyond basic pedagogical interests as bioengineers seek design features to control protein function for myriad purposes, including design of nano-biosensors, drug delivery vehicles, synthetic cells and organic-synthetic interfaces. The current phenomenological view of allostery is that signaling and activity control occur via effector-induced changes in protein conformational ensembles. If the structures of two states of a protein differ from each other significantly, then thermal fluctuations can be neglected and an atomically detailed model of regulation can be constructed in terms of how their minimum-energy structures differ between states. However, when the minimum-energy structures of states differ from each other only marginally and the difference is comparable to thermal fluctuations, then a mechanistic model cannot be constructed solely on the basis of differences in protein structure. Understanding the mechanism of dynamic allostery requires not only assessment of high-dimensional conformational ensembles of the various individual states, including inactive, transition and active states, but also relationships between them. This challenge faces many diverse protein families, including G-protein coupled receptors, immune cell receptors, heat shock proteins, nuclear transcription factors and viral attachment proteins, whose mechanisms, despite numerous studies, remain poorly understood. This dissertation deals with the development of new methods that significantly boost the applicability of molecular simulation techniques to probe dynamic allostery in these proteins. Specifically, it deals with two different methods, one to obtain quantitative estimates for subtle differences between conformational ensembles, and the other to relate conformational ensemble differences to allosteric signal communication. Both methods are enabled by a new application of the mathematical framework of machine learning. These methods are applied to (a) identify specific effects of employed force fields on conformational ensembles, (b) compare multiple ensembles against each other for determination of common signaling pathways induced by different effectors, (c) identify the effects of point mutations on conformational ensemble shifts in proteins, and (d) understand the mechanism of dynamic allostery in a PDZ domain. These diverse applications essentially demonstrate the generality of the developed approaches, and specifically set the foundation for future studies on PDZ domains and viral attachment proteins.
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Sarkar, Soumen. "Dynamic modeling of an articulated forestry machine for simulation and control." Thesis, McGill University, 1996. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=27255.
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Recently, robotic technology has begun to play an important role in forestry operations. An important class of forestry machines is comprised of systems equipped with a mobile platform fitted with an articulated arm carrying a tree processing head. The dynamics of such systems are needed for simulation and control purposes. In contrast to conventional industrial manipulators, which are mounted on stationary bases, a mobile manipulator is dynamically coupled with its base. Base compliance, non-linearity and coupled dynamics result in positioning inaccuracies which in turn give rise to control problems.The dynamics of the FERIC forwarder forestry machine including its compliant tires were developed and implemented symbolically in compact form with the help of an iterative Newton-Euler dynamic formulation. Various models with increasing complexity were derived. Based on a simplified dynamics model, a valve-sizing methodology was developed and used to size hydraulic proportional valves of the machine's actuators.
System parameters have been obtained by various methods, including use of blueprints, weighing, solid modeling and various experiments. A set-point feedforward controller was designed and the machine's responses for various inputs were obtained to analyze the dynamic behavior of the system. Although initial simulations were done in Matlab and Simulink, C programs were developed for increased speed of execution. In addition, techniques to minimize computation time have been developed and applied to result in almost real time simulation.
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Wu, Hongjin. "Dynamic modelling, simulation, and control of a vertical turret tunnelling machine." Thesis, McGill University, 1992. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=61061.
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Tunnelling machines are utilized for many types of excavations in mining and civil engineering applications. To date, the control of tunnelling machines has not been automated to any significant extent. This thesis investigates the dynamic control of a vertical turret, boom-type tunnelling machine. Models of the actuators, kinematics, rigid body dynamics, and cutter-rock interaction are formulated. These models are validated through computer simulation. Controllers are then designed for the actuators using the pole-placement technique, in both continuous and discrete time. The controllers are tested in a variety of operational modes, using the computer simulation of the machine model. Results show that good tracking and disturbance rejection is achieved.
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Sarkar, Soumen. "Dynamic modeling of an articulated forestry machine for simulation and control." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1997. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp01/MQ29628.pdf.
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Okoro, Ogbonnaya Inya. "Dynamic and thermal modelling of induction machine with non-linear effects." Kassel : Kassel Univ. Press, 2002. http://deposit.d-nb.de/cgi-bin/dokserv?idn=969576749.
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Yang, Donghai, and 杨东海. "Dynamic planning and scheduling in manufacturing systems with machine learning approaches." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2008. http://hub.hku.hk/bib/B41757968.
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Arslan, Oktay. "Machine learning and dynamic programming algorithms for motion planning and control." Diss., Georgia Institute of Technology, 2015. http://hdl.handle.net/1853/54317.
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Robot motion planning is one of the central problems in robotics, and has received considerable amount of attention not only from roboticists but also from the control and artificial intelligence (AI) communities. Despite the different types of applications and physical properties of robotic systems, many high-level tasks of autonomous systems can be decomposed into subtasks which require point-to-point navigation while avoiding infeasible regions due to the obstacles in the workspace. This dissertation aims at developing a new class of sampling-based motion planning algorithms that are fast, efficient and asymptotically optimal by employing ideas from Machine Learning (ML) and Dynamic Programming (DP). First, we interpret the robot motion planning problem as a form of a machine learning problem since the underlying search space is not known a priori, and utilize random geometric graphs to compute consistent discretizations of the underlying continuous search space. Then, we integrate existing DP algorithms and ML algorithms to the framework of sampling-based algorithms for better exploitation and exploration, respectively. We introduce a novel sampling-based algorithm, called RRT#, that improves upon the well-known RRT* algorithm by leveraging value and policy iteration methods as new information is collected. The proposed algorithms yield provable guarantees on correctness, completeness and asymptotic optimality. We also develop an adaptive sampling strategy by considering exploration as a classification (or regression) problem, and use online machine learning algorithms to learn the relevant region of a query, i.e., the region that contains the optimal solution, without significant computational overhead. We then extend the application of sampling-based algorithms to a class of stochastic optimal control problems and problems with differential constraints. Specifically, we introduce the Path Integral - RRT algorithm, for solving optimal control of stochastic systems and the CL-RRT# algorithm that uses closed-loop prediction for trajectory generation for differential systems. One of the key benefits of CL-RRT# is that for many systems, given a low-level tracking controller, it is easier to handle differential constraints, so complex steering procedures are not needed, unlike most existing kinodynamic sampling-based algorithms. Implementation results of sampling-based planners for route planning of a full-scale autonomous helicopter under the Autonomous Aerial Cargo/Utility System Program (AACUS) program are provided.
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Yang, Donghai. "Dynamic planning and scheduling in manufacturing systems with machine learning approaches." Click to view the E-thesis via HKUTO, 2008. http://sunzi.lib.hku.hk/hkuto/record/B41757968.
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Chang, Jun-Wei, and 張鈞為. "Dynamic resource allocation in Machine-to-Machine communication." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/eaq6d9.
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碩士國立臺灣大學
電信工程學研究所
105
According to the estimation, Machine-to-Machine(M2M) devices in the Internet of Things(IoT) would be boosted in the near future. LTE system is originally designed for human to human(H2H) communications. The most of radio resource is allocated to data channels but rarely less to control channels. Comparing M2M traffic with H2H traffic, M2M devices only have lightweight uplink packet to report their data. When numerous devices access the network, there are huge amount of the controlling signals would be sent. The overhead of control packets would be too high for the system to maintain the service when massive M2M device access the network. To resolve the problem and improve the performance of LTE system, two scenarios are analyzed. One is a inter-channel dynamic resource allocation scheme designed for massive devices. First, we calculate the resource requirement for each device and estimate the traffic of random access attempts, then allocate data resource and control resource properly in pursuit of high success transmission probability. The other is a game theoretic analysis to a hybrid scenario. We evaluate the performance and find that our proposed scheme in both scenario has better performance in terms of success probability and resource efficiency.
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Tsai, Chien-An, and 蔡建安. "Dynamic characteristics of machine tools." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/57688953798331902023.
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碩士國立中興大學
機械工程學系所
96
High speed and high precision features have become focal points in the development of machine tools in recent years. The appeals in high speed and high precision features have greatly contributed to the demand for high rigidity and stability characters of the machine tool mechanism. The precision and lifetime of machine tools are not only the key but also the core in the in-depth technology. Vibration is the main factor in the determination of precision of machine tools. This study works on the dynamic characters of major five casting objects on machine tools made in Taiwan and Europe respectively. Firstly, we make two integrated processing machines under different structure and bound. The next step is to analyze the natural frequency and modal shapes of the machine tools by the finite element analysis. Measuring the natural frequency by spectrum analyzer based on the analysis modal chart in the third step. Study shows that finite element analysis has high correspondence with experimental results. Accordingly, by the modal test, we can understand dynamic characters of machine tools and experimental way to build up dynamic analysis process of machine tools and related technology. It can help to precisely understand the dynamic character of machine tools mechanism to ensure the feasibility of the design and try another improved schemes to improve precision and lifetime of machine tools.
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Lin, Yan-Ru, and 林彥汝. "Structural Dynamic Analysis of Inkjet Machine." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/z7jsxe.
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碩士國立宜蘭大學
綠色科技學程碩士在職專班
105
The dynamic behaviors of inkjet machine are studied in this research. SolidWorks is used to construct a simplified and full model. After the model is created, ANSYS engineering software is used to perform static analysis, fixed support vibrational analysis, prestress vibration analysis, simple harmonic analysis and spetrum response analysis. The yield strength of structural steel is 250Mpa that is used in the analysis. In the first step the simplified three-axis structure model is analyzed, then the more complete model is used to evaluate its dynamic behaviors. The resonant frequency obtained from spectrm analysis is exactly the same as the frequency obtained by the pre-stress modal analysis, which represents the correctness of the analysis.The maximum stresses for full model after study are all smaller than 250Mpa and maximum deformation is quite smaller, the printing quality is good that match with the working conditions, even if the machine is working at the resonant frequency.
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Weng, Jeng-yi, and 翁正一. "Nonlinear Dynamic Analysis of Turning Machine." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/16367326362573350894.
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碩士義守大學
機械與自動化工程學系碩士班
97
This thesis is to make use of analysis to come to emulation to slice to pare the tool on board knife to has in the process of slicing to pare in, vibrate produce it not the influence and analysis of the line dynamic state system. Also get the system basic dynamic state track by the number emulation of Runge-Kutta method. Again further with Phase Diagram、Power Spectrum、Bifurcation Diagram、Poincarè section four kinds of diagrams are shown to analyze the dynamic state characteristic of the emulation system. End again by maximum Lyapunov exponent. To whether system gets into mentally dense exercise to make nearer substantial evidence of proof. Tool machine while slicing pare, because of work piece quantity lack of impartiality of unbalance power and non- line sexually slice to pare power a bottom a creation to synchronously vibrate, cent the flap, quasi- period vibration and mentally dense exercise etc. the complexity respond to, through the dissimilarity turn soon compare number imitate result after we also find just under the not- line factor function slice to pare to exercise a track to accept irregular now confusion exercise, the dynamic state which slices to pare system responds to in spite of at under the assumption of the day labor piece or the short work piece all the sentence have rather abundant of non- period characteristic. Also at Phase Diagram、Power Spectrum all present equal mess and irregularly the non- period vibrate phenomenon.
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Wen, Peng-Hsiang, and 溫鵬翔. "Development of Digital Dynamic Balancing Machine." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/66812330839121130269.
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碩士國立臺北科技大學
自動化科技研究所
92
The restriction on vibration and noise of rotor became tougher for the better living quality. Rotor unbalance is the major cause of unqualified products. Therefore development of techniques to fix unbalanced rotor is quite important and urgent. Instead of traditional analog way .The aim of this project is use digital method to automate the product procedure for unbalance detection. Vibration measurement techniques and vibration reduction of rotor are also studied in this project. Digital Signal Processing (DSP) involves the digital representation of signals and use of digital processors to analyze, synthesize, or modify such signals. Wavelet is a relatively new signal processing method. it can extract signal features and can keep precise and resolution at same time.
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Regmi, Manish. "Tinyhive dynamic virtual machine for sensor networks /." 2009. http://digital.library.okstate.edu/etd/Regmi_okstate_0664M_10691.pdf.
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Peng, Shin-Yun, and 彭星雲. "Dynamic Analysis of the Centrifugal Crushing Machine." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/66013187166792962028.
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碩士國立交通大學
工學院碩士在職專班精密與自動化工程組
97
Recently, a growing number of the engineering applications require the material of Nano-scale alloy. The main reason is that the physical property would be different when the normal alloy material is mill grinded into Nano-scale powder which is useful for current science. The most important skill is that how to grind the general alloy material into Nano-scale. For the current normal physical grinder the main problem is that grinding generates heat which has negative effect for grinder and powders. Additional methodology and cost are required to reduce or bring out the heat. For this reason, a new grinder with the planetary design is developed. The grinder has a cup with a hammer and the granule could be put in it. When the grinder is working, there is the rotation and revolution motion in the cup. The hammer is rolling in the cup and generating centrifugal force and then crumbling these granules.
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Wei-LongSun and 孫維隆. "Stabilization System Design of Dynamic Machine Vision." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/74evwx.
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Gultekin, San. "Dynamic Machine Learning with Least Square Objectives." Thesis, 2019. https://doi.org/10.7916/d8-nwa1-qk64.
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As of the writing of this thesis, machine learning has become one of the most active research fields. The interest comes from a variety of disciplines which include computer science, statistics, engineering, and medicine. The main idea behind learning from data is that, when an analytical model explaining the observations is hard to find ---often in contrast to the models in physics such as Newton's laws--- a statistical approach can be taken where one or more candidate models are tuned using data.
Since the early 2000's this challenge has grown in two ways: (i) The amount of collected data has seen a massive growth due to the proliferation of digital media, and (ii) the data has become more complex. One example for the latter is the high dimensional datasets, which can for example correspond to dyadic interactions between two large groups (such as customer and product information a retailer collects), or to high resolution image/video recordings.
Another important issue is the study of dynamic data, which exhibits dependence on time. Virtually all datasets fall into this category as all data collection is performed over time, however I use the term dynamic to hint at a system with an explicit temporal dependence. A traditional example is target tracking from signal processing literature. Here the position of a target is modeled using Newton's laws of motion, which relates it to time via the target's velocity and acceleration.
Dynamic data, as I defined above, poses two important challenges. Firstly, the learning setup is different from the standard theoretical learning setup, also known as Probably Approximately Correct (PAC) learning. To derive PAC learning bounds one assumes a collection of data points sampled independently and identically from a distribution which generates the data. On the other hand, dynamic systems produce correlated outputs. The learning systems we use should accordingly take this difference into consideration. Secondly, as the system is dynamic, it might be necessary to perform the learning online. In this case the learning has to be done in a single pass. Typical applications include target tracking and electricity usage forecasting.
In this thesis I investigate several important dynamic and online learning problems, where I develop novel tools to address the shortcomings of the previous solutions in the literature. The work is divided into three parts for convenience. The first part is about matrix factorization for time series analysis which is further divided into two chapters. In the first chapter, matrix factorization is used within a Bayesian framework to model time-varying dyadic interactions, with examples in predicting user-movie ratings and stock prices. In the next chapter, a matrix factorization which uses autoregressive models to forecast future values of multivariate time series is proposed, with applications in predicting electricity usage and traffic conditions. Inspired by the machinery we use in the first part, the second part is about nonlinear Kalman filtering, where a hidden state is estimated over time given observations. The nonlinearity of the system generating the observations is the main challenge here, where a divergence minimization approach is used to unify the seemingly unrelated methods in the literature, and propose new ones. This has applications in target tracking and options pricing. The third and last part is about cost sensitive learning, where a novel method for maximizing area under receiver operating characteristics curve is proposed. Our method has theoretical guarantees and favorable sample complexity. The method is tested on a variety of benchmark datasets, and also has applications in online advertising.
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Yu, Chia-Ching, and 余家慶. "Structural Dynamic Simulation of Machine Gun Mount." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/02373658388317045478.
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碩士國立屏東科技大學
車輛工程系所
104
The purpose of this research is to investigate the structure stiffness and strength of machine gun mount under dynamic load by using finite element method. The finite element model (FEM) is established by using commercial code HyperWorks. The material properties of machine gun mount are obtained from tensile test. The weight and center of gravity are measured by expirement to validate FEM. Experimental modal analysis (EMA) is conducted on the body structure to obtain the natural frequencies and mode shapes, which are used to validate the FEM. Good correlation between analysis and test ensures the FEM is equivalent to the actual structure of machine gun mount. Dynamic analysis is performed to simulation the structure dynamic response of machine gun mount under shooting by using commercial code LS-DYNA. Use SigLab and accelerameter to measure acceleration response of machine gun mount, which is obtained from experiment of machine gun shooting test. The correlation between experiment and simulation is relevant. The maximum von Mises stress is located on the position closed to bolt, but the yielding ratio is lower than 20 %. Furthermore, the structure deformations are lower than 0.3 mm. Therefore, we can conclude that the machine gun mount structure is well designed in stiffness and strength.
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li, chiuan-en, and 李銓恩. "Study on Single-machine and Two-machine Problems in the Dynamic Scheduling Environment." Thesis, 2001. http://ndltd.ncl.edu.tw/handle/74914050894309406806.
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碩士中原大學
工業工程研究所
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This paper consider two different dynamic scheduling models. First, minimization of weighted number of tardy jobs on a single machine (1 | | ). Second, minimization of total flow time and makespan on two machine flowshop wherein both no-wait and blocking in process are considered. In the first case, an integer programming model with variables and 9N constraints is formulated. A heuristic is then presented to solve this NP-complete problem. The average solution quality of the heuristic algorithm is about 98%. A 100 job case requires only 0.0165s, on average, to obtain a near or even optimal solution. To the best of our knowledge, this is the first heuristic approach that attempts to solve the 1 | | problem. In the second case, a frozen-event procedure is first proposed to transform a dynamic scheduling problem into a static one. An integer programming model with variables and 9N constrains, is formulated. Since the problem is known to be NP-complete, a heuristic algorithm with the complexity of is provided. A decision index is developed as the basic for the heuristic. Experimental results show that the proposed heuristic algorithm is efficient. The average solution quality of the heuristic algorithm is above 96.74%. A 14-job case requires only 0.000248s, on average, to obtain a near or even optimal solution.
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Lavoie, Erick. "A layered JavaScript virtual machine supporting dynamic instrumentation." Thèse, 2013. http://hdl.handle.net/1866/9995.
Full textAbstract:
L’observation de l’exécution d’applications JavaScript est habituellement réalisée en instrumentant une machine virtuelle (MV) industrielle ou en effectuant une traduction source-à-source ad hoc et complexe. Ce mémoire présente une alternative basée sur la superposition de machines virtuelles. Notre approche consiste à faire une traduction source-à-source d’un programme pendant son exécution pour exposer ses opérations de bas niveau au travers d’un modèle objet flexible. Ces opérations de bas niveau peuvent ensuite être redéfinies pendant l’exécution pour pouvoir en faire l’observation. Pour limiter la pénalité en performance introduite, notre approche exploite les opérations rapides originales de la MV sous-jacente, lorsque cela est possible, et applique les techniques de compilation à-la-volée dans la MV superposée. Notre implémentation, Photon, est en moyenne 19% plus rapide qu’un interprète moderne, et entre 19× et 56× plus lente en moyenne que les compilateurs à-la-volée utilisés dans les navigateurs web populaires. Ce mémoire montre donc que la superposition de machines virtuelles est une technique alternative compétitive à la modification d’un interprète moderne pour JavaScript lorsqu’appliqué à l’observation à l’exécution des opérations sur les objets et des appels de fonction.Run-time monitoring of JavaScript applications is typically achieved by instrumenting a production virtual machine or through ad-hoc, complex source-to-source transformations. This dissertation presents an alternative based on virtual machine layering. Our approach performs a dynamic translation of the client program to expose low-level operations through a flexible object model. These low-level operations can then be redefined at run time to monitor the execution. In order to limit the incurred performance overhead, our approach leverages fast operations from the underlying host VM implementation whenever possible, and applies Just-In-Time compilation (JIT) techniques within the added virtual machine layer. Our implementation, Photon, is on average 19% faster than a state-of-the-art interpreter, and between 19× and 56× slower on average than the commercial JIT compilers found in popular web browsers. This dissertation therefore shows that virtual machine layering is a competitive alternative approach to the modification of a production JavaScript interpreter when applied to run-time monitoring of object operations and function calls.
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Shivers, Olin. "Supporting Dynamic Languages on the Java Virtual Machine." 1996. http://hdl.handle.net/1721.1/6665.
Full textAbstract:
In this note, I propose two extensions to the Java virtual machine (or VM) to allow dynamic languages such as Dylan, Scheme and Smalltalk to be efficiently implemented on the VM. These extensions do not affect the performance of pure Java programs on the machine. The first extension allows for efficient encoding of dynamic data; the second allows for efficient encoding of language-specific computational elements.